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Highlights: [•] Effect of [DBDS], time, air and paper-Cu proximity on Cu x S deposition was studied. [•] XPS and EDX revealed deposition of Cu x S in paper increased with time or [DBDS]. [•] O2 was observed to have a key role in Cu x S displacement from the conductor surface. [•] A bifurcated pathway for Cu x S deposition in oil-immersed equipment is proposed. [Copyright &y& Elsevier]

Abstract: Turkish electricity market law (EML) came into force in 2001 aiming at establishing a financially strong, stable, transparent and competitive electricity market based on bilateral contracts. Also, a balancing and settlement system (BSS) was put into practice in November 2004 to create a market where uncontracted generation can be traded, and actual implementation of the BSS started on August, 1st 2006 following a 21-month virtual implementation period. However, BSS has always been criticized from its beginning as transferring excessive profits to private generation companies. The present paper analyzes the implementation of BSS and argues that current BSS not only undermines the healthy development of the electricity market in Turkey but also prevents power investments due to uncertainties it created. It concludes that since the inconsistency between the objectives of EML and results of BSS in practice is obvious, Turkish policy makers need to modify current electricity market policy in line with suggestions presented in the paper. [Copyright &y& Elsevier]

Switchgear is a vital component of modern power systems, responsible for regulating the flow of electrical power. Contact issues, irregular loads, and other similar problems can cause switchgear to overheat, leading to unexpected disturbances and potential damage to the power equipment. Thermal imaging shows significant potential and is increasingly employed to detect faults in power equipment. However, the unique characteristics of thermal images often pose challenges to accurate fault detection. This research aims to study the effectiveness of transfer learning architectures for switchgear fault detection. This paper applies eleven transfer learning architectures, including SqueezeNet, GoogLeNet, InceptionV3, DenseNet201, ResNet50, Xception, InceptionResNetV2, ShuffleNet, EfficientNetB0, AlexNet, and VGG19. The results of the testing phase demonstrated that the application of transfer learning by fine-tuning pre-trained convolutional neural network architectures was highly effective in the classification of thermal images captured from switchgear units. The models achieved accuracy rates between 83.87% and 98.38%, and values of F 1 -Scores between 83.11% and 98.34% in the pre-trained architectures. [Display omitted] • Transfer learning is applied to address the unique characteristics of thermal images for switchgear fault detection. • A thermal image dataset is setup and augmented to improve the classification performance. • Establish standard comparisons among eleven transfer learning architectures. • Achieve rapid and precise classification with the proposed transfer learning architectures. [ABSTRACT FROM AUTHOR]

Satellites engaged in observation missions often face severe pointing constraints, which can limit the ability of their solar panels optimize the generation of electrical power during payload operations. Some approaches to maximize power generation involve either using orientable solar panels, or performing orbital maneuvers to point fixed or deployable (non-orientable) solar panels towards the Sun, which can compromise the payload's ability to meet its pointing requirements. In this study, an alternative approach that enables high-consuming remote sensing payloads to operate for extended periods without requiring orientable solar panels is presented. The satellite under consideration is equipped with fixed or deployable (non-orientable) solar panels mounted on up to three different perpendicular faces. The on-board payload is required to remain within a fixed angle from a target direction, which can be either nadir or a specific geographical position. To derive an optimal tracking law, the projected solar array area at each instant is maximized, resulting in optimal electrical power generation. This methodology allows the satellite to maintain its pointing constraints and efficiently operate high-consuming payloads for longer periods. The proposed tracking law is validated using an actual mission scenario, comparing the power generation achieved by the proposed method against other techniques. The approach presented in this paper shows improved performance, enabling satellites equipped with non-orientable solar panels to fulfill their observation requirements while optimizing electrical power generation. This work offers significant benefits for satellite operators, reducing the need for costly orientable solar panels and enhancing the overall efficiency of satellite missions. • Guidance law for optimal power generation while complying with payload pointing constraints. • Simple and easy formulation, suitable for real-time systems. • Methodology validated and compared against other attitude strategies. • Integration and simulation of the guidance law into a control scheme. [ABSTRACT FROM AUTHOR]

The electric power industry is a high-risk industry with frequent accidents. To ensure the life safety of employees and reduce the probability of accidents, it is necessary to utilize certain technical means to identify the main causative factors in electric fatal accident reports. This research proposes an accident causation identification method that combines text categorization and catastrophe association analysis. First, an improved text feature extraction method (TF-IDF-GloVe-LDA) is proposed by fusing term frequency-inverse document frequency (TF-IDF), global vectors for word representation (GloVe), and latent dirichlet allocation (LDA) algorithms. Then, an SVM classifier was used to categorize the 473 accident report texts into five categories, ACCIDENT, PROCESS, CAUSE, PROBLEM, and RESPONSE, based on the extracted text feature vectors. Second, for the 461 CAUSEs categorized from the accident report texts, the TF-IDF algorithm is utilized to mine them to obtain 62 accident causative factors. Using the word cloud map and semantic network, a visualization analysis is performed to reveal the intrinsic connection between causative factors. The human factor analysis and classification system (HFACS) is combined to construct a framework and a Boolean dataset for electric power fatal accident causative factors. Finally, the catastrophe progression method is utilized to improve the FP-growth algorithm and propose a catastrophe association analysis method. It is utilized to mine the Boolean dataset to obtain 28 association rules and construct the accident causal network. The main causative factors were ultimately identified by analyzing the critical causal chains within the network and examining the frequency and sensitivity of each node. The findings of this study indicate that a lack of effective management, supervision, and training serves as the fundamental cause of fatal accidents in the electric power industry when compared to equipment and environmental factors. This paper offered a fresh perspective on identifying primary accident causative factors in non-standardized text and exploring their intricate mechanisms of interaction, which holds significant implications for the pre-control management of accidents in the power industry. [ABSTRACT FROM AUTHOR]

The Global Navigation Satellite Systems (GNSS) provide valuable data for computing accurate and reliable Zenith Tropospheric Delay (ZTD) products used in GNSS precise positioning, climate, and meteorological studies. However, inconsistent GNSS data streaming in the East African region, caused by poor internet connectivity, equipment failure, and electrical power outages, results in data gaps that pose an impact on the applications of the ZTD products. To ensure continuous ZTD data availability, alternative approaches are necessary to fill the gaps. This paper evaluates the accuracy and feasibility of computing ZTD over East Africa using the European Centre for Medium-Range Weather Forecasts (ECMWF) 5th Re-Analysis (ERA5) model. The ERA5 ZTD is compared with ZTD data from 13 GNSS stations for the years 2013 to 2020 from the Nevada Geodetic Laboratory (NGL) products. Seven statistical evaluation metrics, including mean bias (MnB), root mean squared error (RMSE), Pearson correlation coefficient (R), coefficient of determination (R2), refined index of agreement (IA), Nash–Sutcliffe coefficient of efficiency (NSE), and Taylor skill score (TSS) were used to determine the agreement between ERA5 and GNSS tropospheric products. The results indicate that ERA5ZTD products match well with GNSS ZTD products, with an average MnB of −0.80 mm, RMSE of 8.94 mm, R of 0.976, R2 of 0.952, IA of 0.986, TSS of 0.975, and NSE of 0.945. The high accuracy and stability of ERA5 data in computing ZTD make it an excellent alternative source of ZTD data to augment GNSS ZTD products for positioning and meteorological applications in the East African region. [ABSTRACT FROM AUTHOR]

Electric power marketing system to electric power group provides the convenience, makes the power organization economic gains and also solve the many problems, but with the deepening of the application system, electric power group met with a lot of network attacks, shows that the system is under a state of risk, if attacked, the key information of power marketing may be leaked, resulting in economic and other losses. Therefore, in order to better protect the electric power marketing system, this paper has carried on the research. This paper introduces the current situation of network security protection of electric power marketing system, and then puts forward the protection technology scheme. The research shows that the technical scheme in this paper has better protection intensity and can protect the safety of electric power marketing system more effectively. [ABSTRACT FROM AUTHOR]

A micro-grid (MG) is regarded as a localized small-scale power supply system designed for providing electrical power for a remote community, which may be connected to the grid. The paper considers six participants' sites in a remote community. The peak energy consumption patterns for these participants must be different to ensure coalition for mutual benefits and this would facilitate efficient utilization of energy resources. This community concerned may include rural communities having participants such as schools, housing estates, industrial sites, etc. The propose approach would ensure that many participants and their needs are captured and optimized profit of the participants would ensure mutual benefits. In islanded MG, most of the cost/profit distributions in energy trading problems are done based on the self-interest of the participants. Some consider a fair (acceptable or reasonable) cost/profit distribution using the cooperative game theory (CGT) based on the Nash bargaining solution (NBS). However, this method leads to a high degree of dissatisfaction. To improve the fairness and mutual benefits for all MG participants, a new flexible approach is developed. Specifically, CGT which uses a generalized NBS (GNBS) has been proposed, which relaxes certain axiom of the NBS to ensure that fairness of game theory is achieved. The approach allows the profit of the MG participants to be shared using a mechanism based on the negotiation power (i.e. weighted fairness) so that the MG would attain an improved economic outcome. Empirical evaluation of the approach indicates that overall profits using CGT is higher when compared with an independent approach. Moreover, different in negotiation power is achieved in which higher profit is allocated to any participant based on participant's mutual agreement in achieving fair profit distribution. A robust optimization algorithm called Teaching-Learning-Based-Optimization (TLBO) is developed to obtain optimal results. The heuristics algorithms are used in testing the effectiveness of TLBO, which confirm that the TLBO is indeed powerful and robust enough to give quality solutions in solving energy-trading problems. [ABSTRACT FROM AUTHOR]

In recent times, various research studies have proven that the marine currents turbine (MCT) resource has enormous potential for electric power. For the proper exploitation of this resource, it is necessary to understand the hydrodynamics of the marine current turbine. In this paper a modeling was done in order to design a horizontal axis MCT, in an optimal way. In the first step, we evaluated the energy potential of the northern region of Morocco Ksar Srir. In the second step, we described the different building blocks of the conversion chain of a marine current turbine system. Finally, we present the simulation results obtained on Matlab/Simulink. The multi-physical and the hydrodynamic modeling were tested on the P66 marine current turbine of Guinard energy of 3,5 kW. [ABSTRACT FROM AUTHOR]

One of the major concerns of electric power utilities in recent years is mitigating wildfire risks. While different mitigations have been proposed and some are implemented, customer experience is less focused in some methods, and not even considered in some extreme methods. This paper focuses on minimizing such tradeoff: reliability vs. wildfire risk reduction. This paper first proposes a methodology to quantify the wildfire risk raised by electric distribution systems, utilizing the vegetation factor at proper locations as well as the probability of fault. An optimization framework is then developed in this work that considers system reliability improvement in decision-making while reducing the risk of wildfires. The means to achieve such optimization are reclosers and fuses: optimally locate them to minimize the wildfire risk while the negative impact on reliability is minimized. Both fuse-blowing and saving schemes are investigated in this work. Moreover, the temporary and permanent types of faults are taken into account by formulating their impact on the operation of reclosers and fuses in both fuse-blowing and saving schemes. The optimization framework utilizes the exchange market algorithm (EMA) to find optimal results. The effectiveness of the proposed approach is verified by utilizing a modified IEEE 123 node system. • A proposed index models the wildfire risk associated with conductors and fuses. • A novel optimization framework is presented for recloser and fuse siting. • This model minimizes the wildfire risk and its impact on the system's reliability. • The optimization approach considers the recloser-fuse coordination practices. • This method provides different formulas for the fuse-saving and blowing schemes. [ABSTRACT FROM AUTHOR]

The use of power converters to regulate voltage and power in electrical power systems has been attracting attention due to the increasing number of research and applications on renewable energy. The integration of these switched devices may cause instability and undesired oscillations depending on the operation conditions, such as when they feed constant power loads (CPLs). Therefore, this paper proposes an analysis of the effect of the power regulation in a multi-stage converter system made by buck-buck cascaded converters, in which the first converter operates as a voltage regulator and the second operates as a power regulator. To support that analysis, the region of attraction (ROA) is estimated based on convex optimization with linear matrix inequalities (LMIs) constraints considering the effect of the power variation and the voltage regulator dynamics. These regions are validated through tests in a simulated environment, showing that the trajectories initiated within those regions remain confined in those despite the CPL power variation disturbance. Finally, a case study for the experimental environment is presented. The power variation test is carried out and shows the efficacy of the stability analysis approach ratifying the simulation results. • In this paper, an LMI-based stability analysis for the microgrid operation point is presented considering the CPL effects. • The region of attraction (ROA) of a microgrid with CPL is estimated to ensure the operational stability conditions. • Analysis of the impact of the voltage regulation speed on the stability of the microgrid with a CPL whose dynamics are previously known. [ABSTRACT FROM AUTHOR]

The paper discusses issues involved in mission control of the International Space Station (ISS), in particular, specific aspects of monitoring and evaluating the status of Power Supply Systems (PSS) and solar arrays (SA) as their components. Power budget simulations use as their initial computational parameter the current SA performance, which is determined on the basis of a special performance evaluation mode. The obtained data make it possible to take into account the spaceflight factors resulting in performance degradation. Besides that, when using the SA performance evaluation mode as a method for periodically checking the SA status, the more accurate determination of the actual SA performance involves taking into account the shadowing of the photovoltaic cells, the effect of the light reflected off the Earth surface, and current generation resulting from illumination of both the front and the back surfaces of the SA. The paper presents the results of space experiment Albedo carried out onboard the Russian Segment (RS) of the ISS, which included development of techniques for taking into account the above factors when simulating the PSS power budget for the Service Module (SM) Zvezda. Developed as a result of carrying out the space experiment was a procedure for determining SA performance and simulating the power input from the ISS RS SM SA taking into account the Earth albedo; recommendations were made for the orbital spacecraft PSS control modes taking into account the possibility of power generation from the Earth outgoing light flux. Based on the results of testing the developed computational schemes for evaluating the SA performance and simulations of incoming power that take into account the Earth albedo, substantiated values were obtained for the proposed reference parameter for evaluating the ISS RS SM SA. The developed procedure provides the most accurate performance evaluation for both front and back surfaces of the SA. Computational schemes for predicting incoming power proposed within the framework of the procedure make it possible to give highly accurate predictions of incoming power using precise simulations of light flux coming from Earth, as well as to determine the contribution of variable components into the SA performance determined during a periodic SA performance estimate. • Solar arrays current as the sum of the front and back solar arrays sides components. • Solar arrays current as the sum of Sun and emissions coming from Earth components. • Prediction models of incoming electric power characterized by Earth albedo accounting features. • Current generation coefficients are found by function minimizing by Newton-Gauss method. [ABSTRACT FROM AUTHOR]

District heating networks offer promising solutions for remote communities, providing centralized heat supply, improved efficiency, and diverse energy sources, especially with existing diesel generation. Hence, this paper bridges gaps in the existing literature by developing comprehensive dynamic models of combined district heating networks within existing electric power networks in remote communities, which allows identifying challenges and benefits of district heating networks for these communities. It is shown that district heating networks allow utilizing waste energy to enable energy exchanges between the electricity and heating systems, enabling the provision of necessary ancillary services for remote microgrids with renewable energy sources. The presented dynamic district heating network model incorporates particular considerations in remote, northern communities such as soil limitations, extreme cold conditions, and piping insulation to minimize heat loss. It also addresses accurate sizing of heat pumps based on realistic thermal load requirements, weather conditions, and consumer profiles, proposing demand management controls to enhance frequency regulation for the integration of variable renewable energy sources. The main contributions of the paper include detailed dynamic modeling for district heating network operation, heat pump demand response control system design, and a comparative analysis between centralized district heating networks and decentralized electric thermal storage units that have been deployed for thermal supply in remote areas. The presented dynamic models are applied, tested, and validated in an existing electric microgrid at Kasabonika Lake First Nation in Northern Ontario, showcasing the role of a potential district heating network in facilitating renewable energy sources integration in isolated microgrids. • Use diesel generation exhaust for district heating in remote communities. • Use heat pump demand response for frequency control in remote microgrids. • Facilitate renewable energy integration using district heating networks in isolated microgrids. • Compare district heating networks with electric thermal storage units for thermal supply and frequency control in remote microgrids. [ABSTRACT FROM AUTHOR]

The paper investigates the application of machine learning (ML) for voltage sag source localization (VSSL) in electrical power systems. To overcome feature-selection challenges for traditional ML methods and provide more meaningful sequential features for deep learning methods, the paper proposes three time-sample-based feature forms, and evaluates an existing feature form. The effectiveness of these feature forms is assessed using k-means clustering with k = 2 referred to as downstream and upstream classes, according to the direction of voltage sag origins. Through extensive voltage sag simulations, including noises in a regional electrical power network, k-means identifies a sequence involving the multiplication of positive-sequence current magnitude with the sine of its angle as the most prominent feature form. The study develops further traditional ML methods such as decision trees (DT), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), an ensemble learning (EL), and a designed one-dimensional convolutional neural network (1D-CNN). The results found that the combination of 1D-CNN or SVM with the most prominent feature achieved the highest accuracies of 99.37% and 99.13%, respectively, with acceptable/fast prediction times, enhancing VSSL. The exceptional performance of the CNN was also approved by field measurements in a real power network. However, selecting the best ML methods for deployment requires a trade-off between accuracy and real-time implementation requirements. The research findings benefit network operators, large factory owners, and renewable energy park producers. They enable preventive maintenance, reduce equipment downtime/damage in industry and electrical power systems, mitigate financial losses, and facilitate the assignment of power-quality penalties to responsible parties. • Comprehensive study on enhanced voltage sag source localization assisted by ML. • Proposing three new time sample-based feature forms, effective for ML methods. • Identifying the most influential feature form (form 4) utilizing k-means clustering. • Developing diverse supervised models, including a designed one-dimensional CNN. • CNN-Feature form 4 achieved 99.37% accuracy with an acceptable prediction speed. [ABSTRACT FROM AUTHOR]

This paper focuses on the estimation of electrical power output (P e) in a combined cycle power plant (CCPP) using ambient temperature (AT), vacuum in the condenser (V), ambient pressure (AP), and relative humidity (RH). The study stresses accurate estimation for better CCPP performance and energy efficiency through responsive control to changing conditions. The novelty lies in applying genetic programming (GP) on a publicly available dataset to generate Symbolic Expressions (SEs) for high-accuracy P e. To address the challenge of numerous GP hyperparameters, a random hyperparameter values search method (RHVS) is introduced to find optimal combinations, resulting in SEs with higher accuracy. SEs are created with varying input variables, and their performance is evaluated using multiple metrics (coefficient of determination (R 2), mean absolute error (M A E), mean square error (M S E), root mean square error (R M S E), mean absolute percentage error (M A P E), Kling–Gupta Efficiency (K G E), and Bland–Altman (B-A) analysis). A key innovation involves combining the best SEs through an Averaging ensemble (AE), leading to a robust estimation accuracy. Notably, the AE Y V E − 2 achieves the highest (P e) accuracy, including R 2 = 0. 9368 , M A E = 3. 3378 , M S E = 18. 4800 , R M S E = 4. 2985 , M A P E = 0. 7354 % , and K G E = 0. 9479. The investigation highlights AT as the most influential variable, underscoring the importance of choosing inputs aligned with physical processes. This paper's outlined procedure, combining GP, hyperparameter optimization, and ensemble techniques, offers an efficient method for estimating P e in CCPP. It promises simplicity and effectiveness in real-world applications. B-A analysis proves valuable for SE selection, enhancing the proposed methodology. • GP symbolic expressions can estimate electrical power output of CCPP. • Symbolic expressions with AT-V, AT-AP, AT-RH, AT-V-AP, AT-V-RH, AT-AP-RH, AT-V-AP-RH as input variables are most accurate. • B-A analysis, R2, MAE, MSE, RMSE, MAPE, and KGE metrics used as filter of large number of expressions. • Lower estimation errors are achieved with averaging ensemble. [ABSTRACT FROM AUTHOR]

• Challenges that mass amounts of electric vehicles (EVs) impose to power system operations. • Opportunities of intelligently managing the flexibility of smart charging of EVs are discussed. • Hybrid DERMS concept is proposed as a key tool for safe integration and proper management of emerging distribution grids with high amounts of EVs. • A real-life case study of integrating two large-scale EV charging stations into an existing feeder is presented. Global initiatives are actively progressing to integrate large numbers of electric vehicles (EVs) as part of efforts to electrify and decarbonize the transportation sector. This approach plays a crucial role in addressing global greenhouse emissions and pollution problems. However, mass integration of EVs imposes unprecedented challenges to electrical power systems, especially to their distribution grids. These challenges range from planning issues, where the traditional panning procedures are not adequate for integration of EVs and their charging stations, to operational challenges, where a huge number of dispersed EVs can cause peak load increase, voltage violations, congestions, feeder overloads, etc. Hence, despite the significant importance of maximizing the deployment of EVs, their stochastic integration can give rise to critical challenges in electric power systems, thereby impeding their subsequent expansion. Therefore, in order to properly integrate mass amounts of EVs, without causing technical violations in the electrical power system, intelligent software tools are required, to aid distribution system operators and engineers in the transition to a new era of electrified transportation. In this paper, we argue that novel software solutions called Distributed Energy Resource Management Systems (DERMSs) are a key solution for enabling a safe integration of mass amounts of EVs into emerging distribution grids. Specifically, we introduce a novel Hybrid DERMS framework, as an integration of multiple hierarchical levels of DER management solutions, and propose this solution as a suitable instrument for distribution system operators and grid engineers to safely integrate and manage high volumes of EVs within the grid infrastructure. The hypothesis is validated through a real-life use case for integration and management of high amounts of EVs into an existing distribution grid, using an industrial DERMS solution. Specifically, an in-depth analysis of adding two large charging stations, boasting capacities of 5 MW each, has been performed through all stages of integration, from the planning stage, up to using their flexible output to manage technical constraint violations in real time. The influence of these EV charging stations on both the feeder where they are planned to be integrated, as well as on the entire supply substation, have been analyzed in detail. The resultant findings, especially on successfully managing overloads, peak load increases, as well as voltage violations through intelligent use of aggregated EVs through DERMS, have proven to be notably encouraging, further substantiating the paper's hypothesis. [ABSTRACT FROM AUTHOR]

The vast majority of Earth-orbiting satellites carry an electrical power subsystem (EPS) which main components are solar panels and secondary batteries. During eclipse periods, satellites are powered only by rechargeable batteries which have a large energy density but a limited power density. This fact limits the power capabilities of small satellites during eclipse periods. Due to the large power density of Supercapacitors (SCs), ground and on-orbit tests have been conducted to verify their applicability on satellite EPSs. At the moment, no studies are underway on the issue of sizing SCs for eclipse operations. Hybrid configuration could reduce the mass and volume of EPS or maintain those reference values but increasing peak power capabilities. This paper deals with this issue. On the one hand, novel analytical expressions of a variable capacitance SCs are derived, including time–voltage dependence in constant power applications. Also an equivalent formulation for a SCs bank (SCsB) is derived. On the other hand, a SCsB sizing procedure is presented, considering the energy and power requirements of a particular space mission as an input. Finally, a simple mission is analysed, the results showing an improvement on the hybrid EPS design with respect to the traditional, being the mass reduction of 36%. • Implementation of a simple but accurate supercapacitor (SC) model for spacecraft applications. • Innovative analytical expressions of the performance of a SC in constant power applications. • Novel determination of the electrical parameters of a SCs bank, treated as an equivalent SC model. • Estimation of key variables in the operation of hybrid storage systems for space applications. • Preliminary design of a SCs bank devoted to supply high power during eclipse times. [ABSTRACT FROM AUTHOR]

Nowadays, there is extensive penetration of renewable energy sources (RESs) in microgrids such as solar power stations (SPS) and wind power stations (WPS). The RESs are power electronic converter-dominated systems that have zero inertia making the microgrid to have very low inertia. Low inertia microgrid has a high rate of change of frequency (RoCoF), and the frequency response is highly volatile. To cope with this issue virtual inertia and damping are emulated into the microgrid. Virtual inertia and damping, i.e., converter with short-term energy storage device (ESD), which delivers and absorbs electrical power depending on the frequency response of microgrid and minimizes the power variation between power generation and power consumption. In this paper virtual inertia and damping are emulated based on a novel two-degree of freedom PID (2DOFPID) controller optimized with African vultures optimization algorithm (AVOA) technique. The meta-heuristic technique, AVOA, tunes the gains of the 2DOFPID controller and also the inertia and damping gain of the virtual inertia and damping control (VIADC) loop. AVOA comes out to be superior to other optimization techniques when compared in terms of convergence rate and quality. The performance of the proposed controller is compared to other conventional control methodology that has demonstrated its better performance. The dynamic response of such a proposed methodology in a microgrid model is verified in an OPAL-RT real-time environmental simulator, i.e., OP4510. • The Renewable energy sources are mostly converter-based sources which cause the microgrid to have low Inertia. • Low inertia microgrid experiences a high rate of change of frequency. • Enhance the microgrid inertia to emulate virtual inertia and damping in the microgrid. • Estimate the inertia and damping gain of the virtual synchronous generator and tune by the two degrees of freedom order controller using different metaheuristic optimization. [ABSTRACT FROM AUTHOR]

The carbon dioxide (CO 2) emissions have reached their highest levels since measurements began in recent years. This is widely regarded as one of the primary factors contributing to the increasing frequency of extreme climate events. Consequently, accurate and reliable CO 2 emission data becomes the benchmark in shaping policies and setting targets aimed at reducing emissions, which are essential for carbon emission-related research. Among all industries, the electric power sector takes the highest proportion of CO 2 emissions, making the carbon emission accounting for this sector a crucial component of overall carbon emissions accounting. Therefore, the objective of this paper is to provide a comprehensive review of the applied technologies and research progress in electricity carbon emissions accounting. The paper begins by introducing the fundamental concept of electricity carbon emission accounting. Electricity carbon emissions are categorized into two types: direct carbon emissions from electricity production and indirect carbon emissions from electricity consumption. Then, the current applied approaches for accounting for these two types of emissions are reviewed separately. After analyzing the shortages of existing applied carbon emission accounting approaches, the paper proceeds to review the research on the improved approaches of direct and indirect carbon emission accounting. Finally, the paper outlines the future development prospects of carbon emission accounting technology. • Application status of carbon emission accounting approaches in the electric power industry is analyzed. • Direct carbon emission accounting approaches based on big data technologies are introduced. • Research exploration in electricity indirect carbon emission accounting is reviewed and compared. [ABSTRACT FROM AUTHOR]

A mixed-signal four-channel biphasic current-mode functional electrical stimulator chip with a novel charge compensation circuit is presented in this paper. This chip can induce programmable biphasic current ranging from 10 μ A to 2.56 mA for each channel. However, a significant problem with functional electrical stimulation is charge balancing (CB) due to anodic and cathodic current mismatch for process variation. Therefore, a novel compensation module including both passive and active charge compensation schemes are adopted in this chip. The charge compensation module autonomously adjusts the supply and compensation current to achieve fast compensation and low-power consumption simultaneously. The proposed biphasic stimulator is designed and fabricated in a 0.18 μ m CMOS process with a die area of 2.27 mm × 1.99 mm. The measurement results from a test bench demonstrate the proposed circuit functionalities, and the standby power consumption of this chip is 193.7 μ W. Besides, animal experiments on mice for seizure suppression with deep brain stimulation were performed to verify the efficacy and safety of the developed stimulation chip. • A biphasic current-mode electrical stimulator with charge compensation is presented. • A novel module including both passive and active charge compensation schemes is adopted in this chip. • The proposed biphasic stimulator is designed and fabricated in a 0.18 μ m CMOS process. • Fast residual charge compensation and low power consumption module implemented. • Animal experiments were performed to verify the efficacy and safety of the developed stimulator. [ABSTRACT FROM AUTHOR]

The electric power industry is related to the national livelihood, and regional economic development is closely related to the pillar industry. At present, China's economy continues to develop steadily, and the promotion of domestic industrialization has also increased the demand for electricity. In recent years, the state power industry has made great progress, in order to further adapt to the needs of domestic and foreign market competition, the State Grid has also carried out a systematic reform of its own management system. In the reform process, strengthening the construction of performance appraisal system is a very important change. According to statistics, as of June 2020, the number of employees of State Grid has reached more than 900,000. As the most basic business unit of the state grid, the team is the cell of the state grid. It is the basis for the completion of various production management work and plays an important role in the safe production and stable output of electric power enterprises. Based on the relevant indicators of the work of the team, this paper analyzes the performance of the team through the production cost performance model, and provides suggestions for the optimization of the team for power grid enterprises [ABSTRACT FROM AUTHOR]

CubeSats have become in the last decade ideal platforms to demonstrate new technology or to facilitate access to space due to the reduction in development time and costs. However, one of the main problems is the short lifetime of their missions. In many cases, it is due to the lack of correct thermal design and thermal analysis or even no thermal analysis at all. Specifically, the solar panel thermal design affects the global satellite behavior as the electric power supplied by the solar cells depends on their temperature. Typically, the solar panel thermal design is reduced to use its backside as a radiator (if they are deployable). This paper presents a new thermal solar panel assembly using an intermediate layer of PGS (Pyrolitic Graphite Sheet), which at room temperature has a thermal conductivity 3.8 times greater than pure copper, between the solar cells and the solar panel support, in order to homogenize the solar cells temperature. The new design is compared to the standard design developing the GMM (Geometrical Mathematical Model) and TMM (Thermal Mathematical Model) of a CubeSat 6U located in LEO using ESATAN-TMS. The proposed design gets a reduction of up to 5 °C in the temperature variation of the solar cells. [ABSTRACT FROM AUTHOR]

Due to air quality concerns and stricter carbon targets, surface transport electrification is quickly spreading, posing questions on the impact it will have on national and local electrical networks. This paper proposes an agent-based model to assess the per-minute weekday and weekend impact of the uptake of Electric Vehicles (EVs) over the next decade on local electrical and charging infrastructures, aimed at local decision-makers and stakeholders for transport electrification forecasting purposes. This study compares two scenarios, the first assessing the case where no restrictions are imposed on the daily charging events, and the second scenario where the peak electrical demand period between 5pm and 8.30pm is constrained for charging. Swindon Borough is selected as case study since it has one of UK's highest EV adoption rates and has ambitious aims for decarbonisation. The results show that, over time, scenario two consistently lessened the constraints imposed on the grid by lowering the weekday and weekend peak loads up to 7% and 20%, respectively, and through lowering the usage rate of the charging infrastructure by around 12%. This scenario postponed the 5pm to 8.30pm EV charging demand to later hours, resulting in delayed load waves in residential areas that, over time, took values of higher proportion of the daily peak, forecasted to match it by 2036. However, controlling the EV demand through this strategy became less effective over time, and so, constraining charging between 7am and 2.30pm is suggested for further control. To conclude, this scenario can be portrayed in reality by adding flexibility to the grid, through the use of time-of-use tariffs (TOUTs), hence, if well implemented, postponing the upgrade of the grid and the charging infrastructure, presenting savings to the network operator, charging network stakeholders and EV users. The paper thus highlights the advantages of using a model of a heterogeneous population with fine spatial and temporal detail to provide decision-support to key stakeholders in planning energy transitions. [ABSTRACT FROM AUTHOR]

The growth of demand, the need for economic efficiency and optimal utilisation of electric power networks and the high cost of construction of new power networks result in inevitable challenges, such as overloading and excessive power transfer along transmission lines, high losses, voltage instability, low power quality, reliability problems and voltage profile problems. To manage the power transmission system, the recently developed Flexible AC Transmission System (FACTS) can be used for electric transmission networks since it plays an important role in enhancing the static and dynamic performance of power systems. However, location, type and capacity of FACTS devices should be optimised to maximise the resulting benefits. In this paper, different types of FACTS devices are discussed along with their modelling and functions. In addition, the proposed and the compared techniques and approaches in the existing research works, such as analytic approaches, arithmetic programming methods, meta-heuristic optimisation techniques and hybrid methods, are discussed. Analytic approaches have insufficient computation accuracy in determining optimal allocation of FACTS devices and arithmetic programming approaches are often inefficient in managing constrained optimisation problems. However, meta-heuristic approaches are stochastic, population-based optimisation algorithms that are highly efficient in dealing with a multimodal, highly constrained, multi-objective and discrete system. Meta-heuristic techniques are the most commonly used methodologies to determine the optimal allocation of FACTS devices. Furthermore, the utilisation of analytic methods or classical optimisation approaches with meta-heuristic optimisation techniques plays an important role in reducing the search space of the proposed meta-heuristic optimisation technique. In the present paper, an overall review of 50 recent research work studies, including proposed and compared approaches and techniques, objective functions, approaches, the utilised FACTS devices, constraints, contingency conditions and all the analysed and simulated parameters, is provided and discussed in details. In addition, a more weighted discussion of the proposed methods based on meta-heuristic optimisation techniques is provided. [ABSTRACT FROM AUTHOR]

Using high power space transportation systems equipped with electric propulsion requires development and qualification of electric thrusters with power equal to tens of kW. The optimal specific impulse of such systems designed for deep space missions should be very high (6000 ... 8000 s). Elements for electric propulsion systems are developing at Keldysh Research Center (KeRC). This paper presents qualification status of IT-500 35-kW ion thruster and FCU-500 flow control unit. 2000-hours lifetime test of the IT-500 and FCU-500 was performed as a part of qualification. The ion thruster accomplished 2018 h of operation for the most part at input power of 17,8 kW, utilized 40 kg of xenon. Magnetic field and ion optics improvement and graphite grids development status are also described in this paper. • Ion thruster with power 35 kW passed qualification test. • 2000-h lifetime test was performed as a part of qualification. • Ion optics and magnetic field design modifications increase the thruster parameters. • New carbon-carbon grid design with improved mechanical strength of ion optics grids. [ABSTRACT FROM AUTHOR]

The exponential growth in the semiconductor industry and hence the increase in chip complexity, has led to more power usage and power density in modern processors. On the other hand, most of today's embedded systems are battery-powered, so the power consumption is one of the most critical criteria in these systems. Dynamic Voltage and Frequency Scaling (DVFS) is known as one of the most effective energy-saving methods. In this paper, we propose the optimal DVFS profile to minimize the energy consumption of a battery-based system with uncertain task execution time under deadline constraints using the Calculus of Variations (CoV). The contribution of this work is to analytically calculate the lower bound of expected battery charge consumption for a given task with uncertain execution time. Most of the research in dynamic voltage and frequency scaling tends to discretize time and value factors. This is presumably because of the context of embedded systems which is mainly based on digital design and algorithms. However, important factors in power and energy, such as supply voltage, supply current, and operational frequency, are continuous functions of time. The CoV is a branch of mathematics, where system parameters are considered as continuous functions of time. So, for dealing with this kind of problems, which system parameters are continuous functions of time, we can use the CoV as a powerful way to solve continuous optimization problems. In this paper, we obtain the exact analytical solution for maximizing battery lifetime, which is applicable to any convex power model. • The optimal battery charge usage is obtained and, on the other hand, the analytical upper bound on the possible battery lifetime is provided. • Both battery nonlinear behavior and uncertain task execution time are considered together in one problem. • The battery optimization problem is formulated as a functional and the CoV is used to solve the problem. • The optimal speed profile of a task from the battery charge point of view is calculated in closed form. [ABSTRACT FROM AUTHOR]

Drones and UAVs are gaining worldwide popularity and are now considered a popular choice for both military and commercial applications. Icing poses tremendous safety and performance concerns for the operation of all types of drones. This paper is part of a project that studies icing effects on the hovering 0.66 m diameter Bell APT70 drone rotor and the development of potential ice protection systems. The objective of this paper is to investigate the use of electrothermal heaters with severe icing conditions and to characterize the energy efficiency of anti-icing or de-icing regimes. Rotor speeds of 3880, 4440 and 4950 RPM were used while two air temperatures, −5 and −12 °C, were also tested. The heat transfer profile on the blade was studied using dry run tests where the rotor operated with heating but without water spray. Anti-icing tests with variable heating power were tested to determine the location of the initial ice accumulation as well as the minimum heating power requirement to protect the leading edge. Moreover, anti-icing tests with constant heating rates were done and compared to previous tests of unprotected blades, under similar condition. On the other hand, de-icing tests with various heating cycles were also carried out. Results indicate that although de-icing requires significantly less heating energy compared to anti-icing, there is clear trade-off on rotor stable aerodynamic output, electrical power consumption and vibration levels, depending on the adopted de-icing mode. Future work is about investigating the rise of secondary effects, such as shed ice impact due to de-icing. Work is also planned for a hybrid ice protection system that combines electro-thermal heaters with icophobic or superhydrophobic coatings. [ABSTRACT FROM AUTHOR]

Electrical power distribution systems are experiencing a deep penetration of renewable energy integration, which is reversing the power flow during some periods and modifying their conventional operation. In this context, the curtailment of renewable distributed generation is needed to consider the electrical limitations of transformers and lines, mainly voltage deviations and power overloads. Multiport converters with energy storage stand as a potential solution for enhancing power flow operation in the distribution system and minimising renewable generation curtailments. This paper presents an optimisation-based methodology to size multiport power converters and a techno-economic comparison to other conventional approaches. The optimisation includes energy storage components and AC power flow constraints. Moreover, specific days are considered to reduce computational requirements. This methodology is evaluated in a case study based on a medium voltage benchmark network from CIGRE to identify the best scenarios where multiport converters can be considered as a potential solution. Results conclude that the multiport converter provides clear advantages and is economically viable specially in scenarios with unbalanced distributed generation in the feeders, where their rated power is around 25 MVA, or if batteries are initially installed in the feeders. [Display omitted] • Optimisation-based methodology to size a multiport converter. • Multiport converter comparison with other solutions to reduce renewable curtailment. • Multiport converter can reduce curtailment the same or more than battery solutions. • High renewable penetration scenarios are feasible to install a multiport converter. [ABSTRACT FROM AUTHOR]

• The study investigates shipboard power systems and distortion evaluation in "EXPERT 3." • The study analyzes distortions in converter-based propulsion systems with variable-frequency drives. • The study confirms MATLAB model accuracy at ship synchronous generators. • The paper introduces a resonance-based compensating device, validated experimentally. • The research investigates methods for managing high-frequency disturbances. This research addresses electromagnetic compatibility and power quality (EMC and PQ) challenges in shipboard electric power systems (SEPS) with dynamic positioning (DP) capabilities, focusing on the self-propelled floating crane (SPFC) "EXPERT 3." Our goal is to enhance methodologies for evaluating power quality indicators (PQI) related to voltage and current waveform distortions, specifically in converter-based propulsion complexes (CBPCs) featuring variable-frequency regulated asynchronous drives (VFDs). We investigate harmonic current and voltage distortions, reactive power generation, and power factor (PF) in SEPS "EXPERT 3″ during the operation of VFDs with conventional semiconductor power converters (SPCs). A refined MATLAB model considers equipment and cable network parameters, validating distortion indicators at ship synchronous generators (SGs). PQI compliance with international maritime standards is verified at the point of common coupling (PCC) for various VFD configurations with pulse width modulated (PWM) SPCs and filter-compensating devices (FCDs). We propose an improved controlled FCD (CFCD) incorporating a resonance filter (RF) and a controllable reactor compensator (CRC). CFCD efficiency in various VFD configurations is experimentally validated. We analyze harmonic distortions of voltage and current, including high-frequency (HF) commutations in VFDs with input thyristor-based rectifiers (TBRs), considering parasitic "phase-hull" capacitances of cable line segments (CLS). Our study examines harmonics in CBPC-based SEPS in two sub-frequency ranges: low-frequency (LF) − 0 to 2 kHz and high-frequency (HF) − 2 kHz to 500 kHz.© 2017 Elsevier Inc. All rights reserved. [ABSTRACT FROM AUTHOR]

The three-phase power delivery systems are reliable and efficient means of delivering electric power to customer node points. However, the unequal distribution of loads over the three phases leads to unbalance voltage between phases, resulting in increased power losses in distribution transformers and lines. It is highly challenging to install photovoltaic (PV) generators in unbalanced power distribution networks (PDNs) to restore power supply efficiency. This paper proposes dynamic reconfiguration (DR) in unbalanced PDNs to foster efficient integration of PV generators and improve system performance. Since the demand for electricity at residential node points and the PV-generated power varies with the season, this study proposes a seasonal DR of the PDNs. A framework with multiple objectives has been proposed for the DR-coupled PV deployment problem. A novel value-adaptive weight-aggregated (VAWA) grey-wolf optimizer (GWO) has been synthesized to contribute to system performance enhancement. The proposed strategy was validated and established through comparative investigations on an Indian 19-bus and modified IEEE 123-bus unbalanced radial distribution systems (URDSs). [ABSTRACT FROM AUTHOR]

By integrating the original service resources, modern power supply enterprises have optimized and upgraded the traditional business services and system functions of the existing business halls and used advanced management methods and service concepts to strengthen the intelligent and interactive construction of power business halls, which can reduce the operation and management costs of the business hall can also improve the work efficiency of the business hall staff, provide customers with high-quality and efficient services, and improve the overall image of the power supply enterprise. The intelligent interactive business hall includes physical business halls, interactive terminal business halls, mobile phone business halls, online business halls, etc. It is based on the business hall interactive management system and two-way interactive service system and establishes a collection of customer service, corporate publicity, and product marketing. A multi-functional intelligent and interactive service platform, such as new business and new product display, transforms the traditional "business-centric" power marketing service model to a "customer-centric" intelligent service direction, improving service Quality and service level and enhancing the market competitiveness of power supply enterprises. The interactive construction of business halls is an essential means to realize a new power supply and consumption relationship between power customers and power supply companies with a two-way interaction of power flow, information flow, and business flow. It is a critical way to effectively improve the level of power supply services and establish the brand value of power supply companies. The interactive construction of business halls must be based on effective interactive supporting technologies. This paper conducts research and analysis from three aspects: related technology, hardware equipment, and management software, and develops a set of comprehensive application systems suitable for the interactive construction of business halls, high-quality customer service, and unified operation management. It has good fitting parameter results and is reliable. [ABSTRACT FROM AUTHOR]

Electrical power conversions are common in a large variety of engineering applications. With reference to AC/DC and DC/AC power conversions, a strong research interest resides in multilevel converters, thanks to the many advantages they provide over standard two-level converters. In this paper, a power-oriented model of single-phase Modular Multilevel Converters (MMCs) is first provided, followed by a detailed harmonic analysis. The model is given in the form of a Power Oriented Graphs block scheme that can be directly implemented in the Matlab/Simulink environment. The performed harmonic analysis gives a deep and exact understanding of the different terms affecting the evolution of the voltage trajectories in the upper and lower arms of the converter. Next, a new model-based cascade control architecture for MMCs is proposed. Combined with the real-time calculation of the ideal average capacitor voltages reference, the proposed control architecture allows to properly track the desired load current while minimizing the tracking error and the harmonic content in the generated load current itself. [Display omitted] • Power-Oriented Modeling of Modular Multilevel Converters. • Full Harmonic Analysis of Modular Multilevel Converters. • Calculation of the Ideal Voltage Tracking Reference for the Capacitors Voltages. • Model-Based Cascade Control of Modular Multilevel Converters. • Load Current Tracking Error and Harmonic Content Reduction. [ABSTRACT FROM AUTHOR]

Solar photovoltaic generation has become the dominant global method of producing renewable electricity around the globe. However, solar PV farms require a considerable amount of land. Agrivoltaics has been a promising field of interest recently as this system maximizes the land's utilization by producing crops beneath the photovoltaics panels. This paper proposes a new agrivoltaics system that simultaneously produces crops and electrical power by installing PV panels on agricultural land in such a way that the production of regular crops does not get curtailed and can still grow around and beneath the panels, avoiding any reduction in crop yield. The architectural design of the proposed mounting structure and the installation method are discussed, ensuring full utilization of the land area under the panel with no crop limitations. Bangladesh is considered a case study location as its economy is mostly dependent on agriculture. The country started allocating enormous amounts of farmland for solar photovoltaic farms to mitigate the energy crisis. After a preliminary survey, an agrivoltaics system was designed, developed and installed in the Chuadanga District of Bangladesh. Then a detailed techno-economic analysis was performed to evaluate the feasibility and economic viability of the implemented agrivoltaics project. A comparative analysis of seven different scenarios is demonstrated in terms of equity payback, internal rate of return, modified internal rate of return, net present value, annual life cycle savings, and benefit-cost ratio to determine the optimum agrivoltaics approach as well as to showcase the superiority of the proposed system. The results demonstrate that the proposed agrivoltaics system achieves full land utilization, by producing crops along with electricity generation with the lowest payback period, highest profit margin, and highest benefit-cost ratio over the project lifetime. • An innovative Agrivoltaic (AV) approach for simultaneous food and energy production on the same land. • A technique to minimise the shading effect on the crop yield ensures full farmland utilization. • A quantitative techno-economic analysis for evaluating profit margin and energy balance. • Reduced payback period (3 years) compared to typical PV system (5–6 Years). [ABSTRACT FROM AUTHOR]

Sustainability has become key for many industries, including the energy sector, which often has negative environmental impacts and overall low sustainability levels. Literature exploring environmental, social and governance (ESG) scores in the energy sector is limited, despite the critical effect of the energy production on sustainability. In light of institutional theory, we select four factors (i.e., energy source used by a firm, firm position in the supply chain (SC), firm geographic location, and firm size) that may influence the strategies and operations of firms in electric power SCs impacting their ESG scores. Five hypotheses on the influence of the four factors on firms' ESG scores are developed and tested by means of multiple linear regressions on secondary data from the Refinitiv Eikon database. The Nomenclature of Economic Activities classification was applied to determine 416 relevant firms along electric power SCs (i.e., from mining to electricity transmission and distribution firms, with electricity production firms as focal firms) for which data was extracted for the fiscal years 2020 and 2021. Our findings reveal that geographic location and firm size significantly influence ESG scores, while the mix of energy sources influences the environmental performance only and the influence of firm position in the SC remains insignificant. These results are explained within institutional theory perspective. This paper contributes to the literature by highlighting variables that may correlate with the sustainability scores of firms along electric power SCs. Moreover, it assists managers and policymakers in identifying, understanding, and influencing sustainability differences in these SCs. • The first holistic study on ESG scores determinants in the electric power SC. • Specifying a set of correlations between the determinants and ESG scores. • Analyzing ESG scores of 416 energy firms using multiple linear regression. • Determining the highest impacts on ESG scores: geographic location and size. [ABSTRACT FROM AUTHOR]

• In the context of the Deep Convolutional Neural Networks (CNNs), there are developed and evaluated six novel CNN models for short-term prediction of multi-energy vectors of a novel integrated energy system consisting of three different electric, heat and gas networks and a total of 39 interconnected buildings. • The novel prediction CNN models can be classified function of the type and the number of input and output variables, and type of learning (centralized or distributed). • High correlations between the next and the previous 24 hours building power consumptions are envisaged, and higher correlations than the ones calculated with regard to the weather temperature data (°C) or the solar radiance. • The numerical results obtained for the testing datasets and evaluated in terms of Signal-to-Noise Ratio (SNR) and Normalized Root Mean Square Error (NRMSE), show that the single input variable/single output variable CNN models (CNN_1 and CNN_3), which input/output variables are corresponding to each building and each type of energy consumption, predict the best in comparison to the other models. • For the novel integrated energy system comprising the three distinct networks (electric, heat and gas), it is shown that as the input data is more non-linear and scarce, then it becomes more difficult to predict, and this is to be expected also for any other single or integrated energy system. Forecasting power consumptions of integrated electrical, heat and gas network systems is essential in order to operate more efficiently the multi-energy network system. Multi-energy systems are increasingly seen as a key component of future energy systems, and a valuable source of flexibility, which can significantly contribute to a cleaner and more sustainable integrated energy system. Therefore, there is a stringent need for developing novel and performant models for forecasting multi-energy demands of integrated energy systems, which to account for the different types of interacting energy vectors and of the coupling between them. Previous efforts in demand forecasting focused only on electrical power consumptions or, more recently, on the single heat or gas power consumptions. Therefore, in order to address the multi-energy demand forecasting problem, in this paper six novel prediction models based on Convolutional Neural Networks (CNNs) are developed, for either individual or joint prediction of multi-energy power consumptions: the single input/single output variable CNN model with determining the optimum number of epochs (CNN_1), the multiple input/single output variable CNN model (CNN_2), the single input/single output CNN model with training/validation/testing datasets (CNN_3), the joint prediction CNN model (CNN_4), the multiple-building input/output CNN model (CNN_5) and the federated learning CNN model (CNN_6). All six models are applied in a comprehensive manner on a novel integrated electrical, heat and gas network system, which only recently has started to be used for forecasting. The forecast horizon is short-term (i.e. next half an hour) and all the prediction results are evaluated in terms of the Signal to Noise Ratio (SNR) and the Normalized Root Mean Square Error (NRMSE), while the Mean Absolute Percentage Error (MAPE) is used for comparison purposes with other existent results from literature. The numerical results show that the single input/single output variable CNN model with training/validation/testing datasets (CNN_3) is able to equal the performances of the single input/single output variable CNN model with determining the optimum number of epochs (CNN_1), and to outperform the other four prediction models. The prediction accuracy of the multi-energy networks loads is shown to significantly depend on the level of non-linearity and scarcity existent in the input training dataset(s). Furthermore, this extensive multi-model study reveals that the characteristics (i.e. connections between the different networks, correlations between the different energy vectors) of the considered integrated energy system need to be explored when designing the CNNs prediction models. [ABSTRACT FROM AUTHOR]

The recent international agreements signed by the majority of developed countries, such as those reached at the Climate Change Conferences in Paris'15 and Dubai'23, propose an increasingly rapid transition toward an energy ecosystem with a clear predominance of renewable energy in electrical power systems. The development of such ambitious energy programs should deal with the inherited stochasticity that renewable energy systems entail, which, when coupled with uncertainty about the capacity of the grid to maintain a power supply owing to increasing demands, decarbonization processes and the widespread closure of nuclear power plants, pose a serious threat to the normal functioning of energy systems. When combined with the escalation of armed conflicts that imply the loss of supply as a result of attacks or cyberattacks on power plants and distribution networks, it becomes clear that the current energy paradigm in which there is a centralized grid supplying numerous consumers, many of whom do not have their own generation capacity, must shift toward increasing the deployment of renewable-energy-based self-consumption facilities. The continuous advances toward a decentralized energy system of this nature will also lead to more cooperation, increasing the presence of energy communities with a great need to strengthen internal resilience as a sustaining factor. Considering the challenging framework of smart grids and energy transition, Microgrids would appear to be the key technology for the aggregation of generation, load and energy storage systems, and a cornerstone with which to provide the resilience and flexibility required for this new renewable-energy-based scenario. In addition to the complexity of the microgrid control problem, the issue of resilience energy management also has to be considered, which refers to the ability to adapt and supply loads during a specified period after a disruptive event with a loss of grid supply. This paper introduces an innovative method based on Model Predictive Control (MPC) techniques with the aim of enhancing resilience in microgrids by maximizing the energy surplus and reducing the aforementioned critical instants at which the capacity to feed loads is minimum in the case of power grid outages. The results obtained show that the proposed algorithm enhances the energy resilience in microgrids while the overall operational cost is optimized. A method with which to enhance the resilience of interconnected microgrids through cooperative optimization methods is also developed and validated. [Display omitted] • New techniques for resilience enhancement in microgrids/ networks of microgrids. • Optimizing energy management by enhancing surplus during critical resilience points. • Cooperative resilience management in networked microgrids with cost efficiency. [ABSTRACT FROM AUTHOR]

A number of 17 high current thyristor converters with an installed pulsed power of about 600 MVA feed the complex system of copper magnet coils, which induce the plasma current and provide positioning, shaping and ohmic heating of the plasma. At the moment currents of up to ±45 kA and voltage levels of up to ±3 kV are possible for max. 10 s. But no currently available converter can reach all these parameters at the same time. To achieve this goal a new thyristor converter group, called "Group 7", to work in conjunction with the actual "Group 6", is planned. This paper describes the design of the converter. Since the design of the power section will be in most parts a copy of the already existing converter "Group 6", the focus in this paper will be on the control system. A completely new design using a fully digital control system will be implemented. This paper also introduces the new FAST communication protocol and its aimed features and performance used for the control system. [ABSTRACT FROM AUTHOR]

• 2018 CFETR design point recreated in PROCESS from the view of high-level objectives (different plasma scenario). • Given uncertainties on a number of key input parameters a number of output design points were created. • PROCESS found 124 feasible design points in the operational space near the CFETR design point. • Paper mentions that of particular is the magnet build to give the large fields required for the CFETR plasma scenario and the vary large Psep/R values. The Chinese Fusion Engineering Test Reactor (CFETR) bridges the gap between ITER and a fusion power plant (FPP). The primary objectives of CFETR are: ∼2 GW of fusion power, producing ∼700 MW of net electric power, demonstrate tritium self-sufficiency, operate in steady-state and have a duty cycle of 30–50%. CFETR is in the pre-conceptual design phase and is currently envisaged to be a four-phase machine (from phase I P fus ∼200 MW to phase IV P fus ∼2 GW). In 2016 the EU and China began a collaboration on topics relating to nuclear fusion research and one topic of the work is on CFETR and DEMO. This contribution documents the progress on the collaboration on systems codes studies of CFETR. Systems codes attempt to model all aspects of a fusion power plant using simplified models (0-D, 1-D) and capture the interactions between plant systems. This allows the user to explore many reactor designs at a high level and optimise for different figures-of-merit (e.g. minimise major radius, R 0 , or maximise fusion gain, Q). The EU systems code used for this work is PROCESS, which is the systems code used to create the EU-DEMO baseline designs. This paper details the work on analysing a 2018 CFETR design point in EU systems code PROCESS and the feasibility of the design with regards to meeting the performance objectives and operation of the machine. The work comments on the four-phased nature of the device and the systems code output focuses on phase IV. In combination with the systems code, an uncertainty quantification tool is used to investigate the sensitivity of a CFETR design point to changes in the input assumptions in the systems code. This paper details sensitivities of the CFETR design and shows that given the specified inputs and the uncertainties there are a reasonable number of feasible design points around the CFETR phase IV design point that still fulfil the high-level objectives of the machine. [ABSTRACT FROM AUTHOR]

• We describe the design of the MB and PF joints in ITER. • The joints preparation for hydraulic characterization is detailed. • The hydraulic test sequence is explained. • The main results are highlighted. • The consequences on the cryoplant operation are raised. The ITER magnet system will be the largest superconducting magnet system ever built. The system, all inside a cryostat, is mainly composed of a Central Solenoid (CS) split in 6 modules, a set of 18 Toroidal Field (TF) d -shaped coils and 6 Poloidal Field (PF) coils. Each of these coils uses variable type of cable-in-conduit-conductors (CICC) actively cooled by a forced supercritical helium flow. Their electrical supply from the current feedthrough of the cryostat is done with Main Busbars (MB) using similar CICC. The electrical MB to coils as well as internal PF and TF coils connections rely on the twin box concept developed by CEA in the early R&D phase. After electrical validation of joint prototypes for the PF and the MB conductors on full size samples, specific hydraulic characterization tasks were done through the Magnet Infrastructure Facilities for ITER (MIFI) contract between ITER Organization (IO) and CEA devoted to develop, improve and qualify manufactured components and assembly processes. These tasks were done on the samples using the CEA OTHELLO dedicated facility able to operate with gaseous N 2 in a large Reynolds range at room temperature. The paper explains the way followed to get a full hydraulic characterization of the MB and PF5 joints for the two flow directions. The study of the flow distribution between parallel cooling channels inside the PF5 joint revealed a bypass of the active joint region. The paper reports on this hydraulic behaviour in the relevant magnets operating conditions and outlines the design changes in the joints provoked by the results of this study. [ABSTRACT FROM AUTHOR]

• Developing the simulation tool of superconducting magnet power supply system to analyze the KSTAR power system. • Analyzing the electrical operation data of KSTAR fusion experiment and issues. • A study on the impact of plasma control system on the faults of KSTAR pulsed electric power network. • Solutions for the issues and future upgrade of KSTAR power system. To achieve 2 MA plasma current with 300 s pulse length in the Korea Superconducting Tokamak Advanced Research (KSTAR), its pulsed electric power network (PEPN) was designed. The PEPN system, which was installed in 2012, consists of an exciter, a synchronous machine (SM), and a large power variable voltage and variable frequency (VVVF) inverter. Several commissioning activities were performed on the mechanical parts of SM, and the PEPN has been used to supply AC power to the KSTAR superconducting magnet power supplies (MPSs) since entering into service in 2015. However, due to electrical faults in the VVVF inverter during certain types of plasma operations, the operation window of KSTAR has decreased, especially during high plasma current and long-pulse operations. The operation results of the KSTAR PEPN are reviewed in this paper. In addition, a comprehensive study of faults in the VVVF inverter system is performed from the viewpoint of active power variation using real plasma operational scenario results and model-based simulations. This paper also describes the design upgrade of the PEPN system for extended KSTAR operations in the future. [ABSTRACT FROM AUTHOR]

Highlights • We compare mobility cost of three different e-fuels, diesel, methanol, and LOHC. • The energy market design has a major influence on the production costs of e-fuels. • Dynamic and price-sensitive production of e-fuels can make them competitive in 2035. • LOHC is the most cost-effective option compared to synthetic diesel or methanol. • The optimal setup of e-fuel production is decisively affected by the market design. Abstract Electric fuels (e-fuels) enable CO 2 -neutral mobility and are therefore an alternative to battery-powered electric vehicles. This paper compares the cost-effectiveness of Fischer-Tropsch diesel, methanol and Liquid Organic Hydrogen Carriers. The production costs of those fuels are to a large part driven by the energy-intensive electrolytic hydrogen production. In this paper, we apply a multi-level electricity market model to calculate future hourly electricity prices for various electricity market designs in Germany for the year 2035. We then assess the economic efficiency of the different fuels under various future market conditions. In particular, we use the electricity price vectors derived from an electricity market model calibrated for 2035 as an input for a mathematical model of the entire process chain from hydrogen production and chemical bonding to the energetic utilization of the fuels in a vehicle. Within this model, we perform a sensitivity analysis, which quantifies the impact of various parameters on the fuel production cost. Most importantly, we consider prices resulting from own model calculations for different energy market designs, the investment cost for the electrolysis systems and the carbon dioxide purchase price. The results suggest that the use of hydrogen, which is temporarily bound to Liquid Organic Hydrogen Carriers, is a favorable alternative to the more widely discussed synthetic diesel and methanol. [ABSTRACT FROM AUTHOR]

Highlights • It describes the motivation of a cluster approach and defines its associated boundary dimensions. • A set of influencing factors on urban energy systems at cluster level are identified. • Three main categories of RES envelope solutions are summarized. • Modelling techniques for energy systems at cluster level are reviewed. Abstract The emergence of renewable-energy-source (RES) envelope solutions, building retrofit requirements and advanced energy technologies brought about challenges to the existing paradigm of urban energy systems. It is envisioned that the building cluster approach—that can maximize the synergies of RES harvesting, building performance, and distributed energy management—will deliver the breakthrough to these challenges. Thus, this paper aims to critically review urban energy systems at the cluster level that incorporate building integrated RES solutions. We begin with defining cluster approach and the associated boundaries. Several factors influencing energy planning at cluster scale are identified, while the most important ones are discussed in detail. The closely reviewed factors include RES envelope solutions, solar energy potential, density of buildings, energy demand, integrated cluster-scale energy systems and energy hub. The examined categories of RES envelope solutions are (i) the solar power, (ii) the solar thermal and (iii) the energy-efficient ones, out of which solar energy is the most prevalent RES. As a result, methods assessing the solar energy potentials of building envelopes are reviewed in detail. Building density and the associated energy use are also identified as key factors since they affect the type and the energy harvesting potentials of RES envelopes. Modelling techniques for building energy demand at cluster level and their coupling with complex integrated energy systems or an energy hub are reviewed in a comprehensive way. In addition, the paper discusses control and operational methods as well as related optimization algorithms for the energy hub concept. Based on the findings of the review, we put forward a matrix of recommendations for cluster-level energy system simulations aiming to maximize the direct and indirect benefits of RES envelope solutions. By reviewing key factors and modelling approaches for characterizing RES-envelope-solutions-based urban energy systems at cluster level, this paper hopes to foster the transition towards more sustainable urban energy systems. [ABSTRACT FROM AUTHOR]

Highlights • Innovative multiple tuned mass damper (MTMD) for potential transformers for seismic mitigation. • Characterizing effectiveness of large number of MTMD mass units and large mass ratio. • Analytical solution of controlled potential transformer (PT) under harmonic excitations. • FE modeling and analysis of MTMD controlled and non-controlled PTs under earthquake loading. • Quantifying the limitations of MTMD for PTs. Abstract Porcelain electrical equipment, such as potential transformers (PT), are important components of power supply system that have experienced damage during past earthquakes. The goal of this paper is to propose and investigate the effectiveness of an innovative multiple tuned mass damper (MTMD) mitigation strategy for PTs using analytical and computational finite element methods. The paper discusses the reference seismic performance of two non-controlled typical 110-kV and 220-kV PTs through shake table tests. A novel MTMD damping device is proposed for the 220-kV PT and the effect of different parameters such as the number of mass units and mass ratio is investigated first using analytical solutions for harmonic excitations. Next, a finite element model for the PT is developed and validated using the shake table tests. The model is used to investigate the MTMD damping effectiveness and robustness using linear and nonlinear time history analysis under seven different earthquake records. Large mass ratios, up to 30% of the PT weight, and different number of mass units, up to 9 units, are considered in optimizing the MTMD design parameters and studying its limitations with focus on detuning effect and geometric nonlinearity. A nonlinear time history analysis is also conducted for controlled and non-controlled to determine the effectiveness of the proposed MTMD in withstanding larger earthquakes. The analysis is extended to interconnected equipment and systems to study the conductors' influence on the MTMD effectiveness. The study concludes that PT controlled using MTMD demonstrate a superior seismic performance and can withstand earthquakes with about 30% larger intensity when compared to non-controlled cases. The proposed MTMD is practical and can have a great potential in mitigating substations seismic damage if extended to other electrical equipment. [ABSTRACT FROM AUTHOR]

Graphical abstract In exploring China's optimal power generation mix, we employ scenario analysis to investigate the influence of cost, risk factors, technological development restrictions and different policy targets. Under the technological realizable case, the risk minimization portfolio remains unchanged while the cost and risk of cost minimization portfolio increase when the policy target package improves. Highlights • China's optimal power generation mix of 2030 is explored using portfolio approach. • Grid availability is used to reflect the risk for non-fossil generation technologies. • Fossil fuel forms have no priorities when considering technological restrictions. • Positive effects exist for a non-fossil generation goal or a policy target package. Abstract This paper employs portfolio theory to explore China's optimal power generation mix in 2030, which considers the possibilities of technological developments, and the government's non-fossil generation and non-hydro renewable generation policy targets. The aim of this paper is to investigate China's efficient generation portfolios by comparing the portfolio costs, risks, efficient frontiers, and diversification levels under different cases and scenarios. The results show that fossil fuel generation technologies have no advantages when considering the technological restrictions. In addition, various preferences for non-fossil generation technologies are influenced greatly by the goals of pursuing cost or risk minimization and different policy targets. Positive effects exist for a non-fossil generation goal or a policy target package from the perspectives of minimizing cost and risk, as well as for improving the diversification level. [ABSTRACT FROM AUTHOR]

• Compared with the traditional flexible interconnection method, the EDC-DN power supply architecture proposed in this paper does not simply use MTDC to achieve feeder interconnection but first optimizes and adds dynamic reactive power compensation devices based on voltage source converters in the context of a high percentage of DG access to the grid, and then the dynamic reactive power compensation equipment between different feeders is interconnected on the DC side by adding additional lines, thus weakening the voltage fluctuation of the grid when DG is connected while achieving closed-loop flexible interconnection between multiple feeders. This can achieve closed-loop flexible interconnection between multiple feeders while weakening the voltage fluctuation of the grid when DG is connected, provide a flexible active power adjustment path for high proportional DG access to DN, and realize power mutual aid between different feeders and network-level bearing of DG. • For the issue of power supply recovery after EDC-DN fault, a comprehensive analysis was conducted on the impact of different fault locations on the power supply recovery process. The collaborative plan between EDC and DAS was first proposed, clarifying the information interaction content between the distribution network automation central station, feeder sub-station, and EDC sub-station during the power supply recovery process. An EDC-DN two-stage power supply restoration architecture considering EDC continuous regulation, combinatorial optimization of interconnection switch and sectionalizing switch is proposed and designed, which fills the technical gap in the integration of EDC and DAS systems. • This paper demonstrates the real-time dynamics of EDC in the EDC-DN power supply restoration process through simulation. The restoration process includes a fast restoration phase based on EDC continuous regulation of power supply, a non-fault section transfer process based on mechanical switch action, and an economically optimal operation phase using an optimal combination of switches to reconfigure the distribution network topology. The current power supply restoration strategy of SOP focuses on the final restoration state of EDC continuous regulation and switch combination rather than on the whole process of power supply restoration. This paper considers the real-time dynamics of the entire EDC-DN power supply restoration process. It fills the technical gap in the current SOP power supply restoration without considering the intermediate process. The flexible interconnection device (FID) enables multiple distribution feeders in closed-loop mode to support a higher proportion of distributed generation (DG) and large-scale new loads connected to the distribution network (DN). Moreover, the closed-loop operation mode based on FIDs provides an effective technology roadmap for high-quality and highly reliable power users, especially the quick restoration of power supply after the failure of DN. This paper proposes a new supply shape in which the multi-terminal DC links are flexibly embedded in the AC DN (EDC-DN) to realize closed-loop operation, achieving lower investment costs than the existing mode that replaces tie switches with soft open points (SOPs). Meanwhile, a two-stage power supply quick recovery control technology is proposed for the EDC-DN, including the fast power supply recovery stage based on EDC and the optimizing restoration stage based on network reconfiguration. Firstly, the role of EDC in the process of power supply restoration of three different faults on AC feeder is analyzed. Secondly, a detailed power supply recovery process is proposed, which is based on a distribution automation system (DAS) and the real-time control capability of EDC. Thirdly, the power supply restoration second stage is implemented, which is based on network reconfiguration with switch combination and EDC continuous variable optimization. Finally, a 58-node DN with an EDC system was constructed using PSCAD/MTDC simulation software to verify the effectiveness of the two-stage strategy for EDC-DN power restoration. © 2017 Elsevier Inc. All rights reserved. [ABSTRACT FROM AUTHOR]

• The optimization problem of EPS and flexibility-enhanced DHSis formulated. • The DHS is retrofitted with BCT and uses a variable mass flow operation strategy. • A conditional-DRO is employed to hedge against the uncertainty of renewable energy. • Propose adouble-layer distributed algorithm to achieve the distributed solution. In an integrated electricity and heating system (IEHS), building flexibility-enhanced district heating systems (DHSs) that use advanced flexibility-enhanced technologies are effective for promoting renewable energy accommodation. However, it is challenging to comprehensively utilize these flexibility-enhanced technologies in IEHS dispatch. This paper proposes a distributed conditional-distributionally robust coordination method for an electrical power and flexibility-enhanced DHS. The DHS is retrofitted with bypass compensation technology and uses a variable mass flow operation strategy to enhance its flexibility and promote renewable energy accommodation. Moreover, conditional-distributionally robust optimization is used to consider the inherent dependency between the forecasting error of a wind farm and the forecast output information, which goes beyond the state-of-the-art models. Additionally, a novel reformulation method is adopted to transform the problem with random variables and bilinear constraints into a more tractable programming problem, yielding a conservative approximative model of the original model that guarantees feasibility. Finally, to protect the privacy of electrical power system and DHS operators, this paper proposes a double-layer distributed algorithm to solve the problem in a distributed fashion while guaranteeing feasibility. Case studies demonstrate that the proposed model with flexibility-enhanced DHSs significantly promotes renewable energy accommodation and reduces dispatch costs, and the proposed double-layer distributed algorithm effectively solves the dispatch problem in a distributed fashion and guarantees the feasibility of dispatch results. [ABSTRACT FROM AUTHOR]

The low inertia of electrical power networks as renewable energy penetration levels increase is regarded as a significant issue confronting worldwide ambitions for the anticipated renewable energy transition. Load frequency control (LFC) is an efficient way of improving the frequency stability and dependability of renewable energy-based power networks. Therefore, this paper introduces a novel three-degree-of-freedom (3 DoF) load frequency control method for two-area-linked power systems. To implement the suggested LFC approach, the proposed control employs an enhanced hybrid fractional order control method (namely FOTPID), and the tilt integrator differentiator with filter (TIDF) is employed in the frequency deviation and tie-line power loop feedforward compensation. As a consequence, this study proposes a novel 3DoF cascaded FOTPID-TIDF controller. Furthermore, this work proposes a modified method of the recently developed Manta-Ray Foraging Optimizer (MRFO) to optimize the parameters of the new suggested 3DoF cascaded FOTPID-TIDF controller. The paper includes extensive performance comparisons and discussions to validate the superior performance metrics of the new proposed control and optimization methods. The results reveal that by taking into account the characteristics and uncertainties of renewable sources, interconnected loads, and grid inertia, the results perfectly mitigate various existing deviations in frequency and tie-line power compared to existing contemporary LFC approaches. [ABSTRACT FROM AUTHOR]

The multi-objective optimization algorithms (MOO) are used to obtain the best compromising solutions when two or more objective functions need to be optimized simultaneously. The convergence and diversity are critical factors to consider while solving the MOO problems because they determine the possibility of obtaining an evenly distributed Pareto front. This paper proposes a hybrid optimization algorithm to solve a multi-objective economic emission dispatch (MOEED) problem of electrical power systems. The electrical power generated by consuming fossil fuels is very costly and also burning of these fuels contributes to global warming. Hence, electrical power is generated at the least cost and emission. The MOEED problems have been solved in the past by using swarm intelligence and evolutionary algorithms. However, the solutions reported in the literature, are either inferior or the constraints are violated. The algorithm proposed in this paper is an integration of an Artificial Bee Colony optimization algorithm and a Non-Dominated Sorting Genetic Algorithm-II. The effectiveness of the proposed algorithm is evaluated by applying it to three test systems having 6, 10, and 40 coal-based generators. Additionally, various multi-criteria decision-making algorithms are used to identify the best non-dominated solutions obtained by the proposed algorithm and compared with previously reported results. The best fuel costs obtained by the proposed approach, for a 6-unit test system with and without transmission losses are found to be 605.9983 and 600.11140 $/h respectively. While the best emission values, for this test system, with and without transmission losses are found to be 0.1941 and 0.1942 tons/h. Moreover, the best fuel costs obtained by the proposed approach, for 10 and 40-unit test systems are found to be 111181.9871 and 121369.0838 $/h respectively. Furthermore, the best emission values for these test systems are found to be 3932.24322 and 176682.264 tons/h respectively. All these results are obtained without constraint violations and within 10–600 iterations. • Combined economic emission dispatch problem is solved by ABC-NSGA-II Algorithm. • Best compromising solution, best fuel cost, and best emission values are compared. • Results of combined economic emission dispatch problem in old articles are analyzed. • Multi-criteria decision-making methods are used to find trade-off solution. • Statistical analysis using hypervolume indicator is presented. [ABSTRACT FROM AUTHOR]

This paper proposes a design for a modified distribution static compensator (DSTATCOM) with a proposed current controller for microgrid (MG) applications. The modified DSTATCOM is incorporated in a three-phase four-wire network system to deal accurately at grid connected mode with balanced, unbalanced and excursion load for both nonlinear and inductive loads. Moreover, it handles the stability issues of the MG at fault caused islanding incidents. The design criteria of the modified DSTATCOM parameters is presented and discussed. The hysteresis current controller is introduced to drive the voltage source converter (VSC) and its reference voltage signal is generated based on the instantaneous symmetrical components theory (ISCT). Matlab/Simulink software is used to verify the performance of the modified DSTATCOM with the proposed controller under different load types and loading conditions for grid connected mode and islanded mode of MG operation. Based on the simulation results, the power factor is improved and the non-linear harmonics currents are compensated therefore the harmonic distortion of the supply currents and voltage are reduced, moreover the stability operation at fault cause islanding is maintained. The results show the superiority of the proposed modification of DSTATCOM in dealing with unbalanced, distorted and bad power factor system in comparing with conventional DSTATCOM. [ABSTRACT FROM AUTHOR]

The information system of low-voltage distribution network correctly records the topological structure of distribution network, which is the premise of fine management and safe operation of electric power grid. In the topology, the most important element is the household change relationship [1]. At present, the low-voltage distribution network topology data in the information system is manually entered, so the correctness of the information can not be guaranteed. With the continuous expansion of the scale of power grid, the structure of low-voltage distribution network is complex, the amount of data of marketing measurement [2] , GIS and other information systems is increasing rapidly, each information system operates independently, and the data circulation is poor, which makes it difficult to identify the topology data, so it is urgent to carry out topology verification. The method proposed in this paper effectively solves the problem of electric data verification, and carries out corresponding experiments and demonstrations on the results, with high accuracy. [ABSTRACT FROM AUTHOR]