Search

A safe and stable operation power system is very important for the maintenance of national industrial security and social economy. However, with the increasing complexity of the power grid topology and its operation, new challenges in estimating and evaluating the grid structure performance have received significant attention. Complex network theory transfers the power grid to a network with nodes and links, which helps evaluate the system conveniently with a global view. In this paper, we employ the complex network method to address the cascade failure process and grid structure performance assessment simultaneously. Firstly, a grid cascade failure model based on network topology and power system characteristics is constructed. Then, a set of performance evaluation indicators, including invulnerability, reliability, and vulnerability, is proposed based on the actual functional properties of the grid by renewing the power-weighted degree, medium, and clustering coefficients according to the network cascade failure. Finally, a comprehensive network performance evaluation index, which combines the invulnerability, reliability, and vulnerability indicators with an entropy-based objective weighting method, is put forward in this study. In order to confirm the approach's efficacy, an IEEE-30 bus system is employed for a case study. Numerical results show that the weighted integrated index with a functional network could better evaluate the power grid performance than the unweighted index with a topology network, which demonstrates and validates the effectiveness of the method proposed in this paper. [ABSTRACT FROM AUTHOR]

The quality of electricity is one of the most discussed issues in the regulatory context, structured by guidelines that allow the assessment of efficiency in electricity supply. Regarding electricity distribution systems, it is essential to highlight the aspects associated with the definition of continuity indicators to measure the service provided by the utilities. The parameters used to calculate the indicators are set by specific agencies in each country based on studies and their characteristics. With the growth in demand for electricity, debates associated with reducing greenhouse gas emissions in the atmosphere, and the increase in Distributed Energy Resources (DERs) connected to the grid, a new trend related to the energy supply is verified. Given these new scenarios, this paper presents a literature review in the regulatory field of existing distribution systems in South American countries. The research proposes to analyze, compare, and expose the current models to evaluate their methods and indicators, including a complete case study in Brazil. This paper seeks to illustrate and point out perspectives, challenges, and future perspectives through the collected and analyzed data. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to address an urgent operational issue referring to optimal power flow (OPF), which is associated with a number of technical and financial aspects relating to issues of environmental concern. In the last few decades, OPF has become one of the most significant issues in nonlinear optimization research. OPF generally improves the performance of electric power distribution, transmission, and production within the constraints of the control system. It is the purpose of an OPF to determine the most optimal way to run a power system. For the power system, OPFs can be created with a variety of financial and technical objectives. Based on these findings, this paper proposes the peafowl optimization algorithm (POA). A powerful meta-heuristic optimization algorithm inspired by collective foraging activities among peafowl swarms. By balancing local exploitation with worldwide exploration, the OPF is able to strike a balance between exploration and exploitation. In order to solve optimization problems involving OPF, using the standard IEEE 14-bus and 57-bus electrical network, a POA has been employed to find the optimal values of the control variables. Further, there are five study cases, namely, reducing fuel costs, real energy losses, voltage skew, fuel cost as well as reducing energy loss and voltage skew, and reducing fuel costs as well as reducing energy loss and voltage deviation, as well as reducing emissions costs. The use of these cases facilitates a fair and comprehensive evaluation of the superiority and effectiveness of POA in comparison with the coot optimization algorithm (COOT), golden jackal optimization algorithm (GJO), heap-based optimizer (HPO), leader slime mold algorithm (LSMA), reptile search algorithm (RSA), sand cat optimization algorithm (SCSO), and the skills optimization algorithm (SOA). Based on simulations, POA has been demonstrated to outperform its rivals, including COOT, GJO, HPO, LSMA, RSA, SCSO, and SOA. In addition, the results indicate that POA is capable of identifying the most appropriate worldwide solutions. It is also successfully investigating preferred search locations, ensuring a fast convergence speed and enhancing the search engine's capabilities. [ABSTRACT FROM AUTHOR]

The electrification of the transportation sector contributes to a cleaner environment in non-interconnected island (NII) systems or standalone islands. Moreover, e-mobility can significantly contribute to achieving very high renewable energy source (RES) penetration levels in islands, allowing a reduction both in the emissions due to the conventional generation and the system's cost. Ιncreased RES penetration, however, can pose technical challenges for an island's system. In order to overcome these challenges, new technologies like grid-forming converters are important. Moreover, the provision of new ancillary services in relation to battery storage systems might be considered, while novel control and protection schemes are needed to ensure secure operation. E-mobility can also contribute to solving technical problems that arise from very high RES penetration by providing frequency containment reserves or reactive power compensation. Since EV charging demand introduces modifications in the system's load curve, e-mobility may affect the power grid for long-term planning and short-term operation, i.e., line loading and voltages. The application of specifically developed smart charging methodologies can mitigate the relevant grid impact, while effective exploitation of EV–RES synergies can achieve higher RES penetration levels. This paper examines how e-mobility can contribute to increasing RES penetration in islands while considering the technical issues caused. In particular, this paper takes into account the distinct characteristics of NIIs towards the identification of solutions that will achieve very high RES penetration while also addressing the relevant technical challenges (voltage control, frequency control, short circuit protection, etc.). The effect of e-mobility in the power grid of NII systems is evaluated, while smart charging methodologies to mitigate the relevant impact and further increase RES penetration are identified. [ABSTRACT FROM AUTHOR]

The timescale of the energy-release process of an energy storage system has put forward higher requirements with the increasing proportion of new energy power generation in the power grid. In this paper, a new type of compressed-air energy storage system with an ejector and combustor is proposed in order to realize short-timescale and long-timescale energy-release processes under the non-supplementary combustion condition and ejector supplementary combustion condition, respectively. A simulation model of the new system is established in APROS software. The results of this study show that the new system can realize continuous power output when energy storage and energy release operate simultaneously, and especially when the ejector coefficient is 0.8 and burner thermal power is 10 MW, the power-generation time is 12.45 h and the total generated power is 140,052 kW∙h, which are 15.6 and 17.5 times greater those of the short-timescale condition, respectively. In summary, the compressed-air energy storage system with an ejector and combustor that is proposed in this paper can flexibly meet the demands of multiple timescales' power generation. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive overview of the microgrid (MG) concept, including its definitions, challenges, advantages, components, structures, communication systems, and control methods, focusing on low-bandwidth (LB), wireless (WL), and wired control approaches. Generally, an MG is a small-scale power grid comprising local/common loads, energy storage devices, and distributed energy resources (DERs), operating in both islanded and grid-tied modes. MGs are instrumental to current and future electricity network development, such as a smart grid, as they can offer numerous benefits, such as enhanced network stability and reliability, increased efficiency, an increased integration of clean and renewable energies into the system, enhanced power quality, and so forth, to the increasingly growing and complicated power systems. By considering several objectives in both islanded and grid-tied modes, the development of efficient control systems for different kinds of MGs has been investigated in recent years. Among these control methods, LB communication (LBcom)-based control methods have attracted much attention due to their low expenses, recent developments, and high stability. This paper aims to shed some light on different aspects, a literature review, and research gaps of MGs, especially in the field of their control layers, concentrating on LBcom-based control methods. [ABSTRACT FROM AUTHOR]

The disordered access of massively distributed energy resources (DERs) brings great challenges to the operation stability of the power grid. This paper puts forward the concept of a cluster, which gathers DERs in large quantities, small capacities, dispersion and disorder to form a large, centralized and orderly whole, namely cluster, with certain incentive measures. In this paper, a multi-timescale optimization method of day-ahead planning and intra-day rolling optimization is proposed according to the characteristics of aggregated clusters and the requirements of China's power grid architecture. Specifically, the day ahead model is proposed in two steps: the first step is to establish an optimization model with the goal of optimal fitting the target load curve and maximizing the utilization of DERs; The second step is to establish a potential game model considering the reasonable distribution of cluster benefits. Taking the minimum percentage of output correction of each cluster as the objective, considering the deviation of load forecasting and the deviation of day ahead instruction execution, an intra-day rolling optimization model is established. Finally, the application scenario of cluster participation in power grid auxiliary peak shaving is simulated and verified. The simulation results show that the cluster collaborative optimization method proposed in this paper can effectively reduce the load peak valley difference and maximize the use of cluster resources. The optimization tasks can be reasonably allocated while ensuring the stable and reliable operation of the power grid. [ABSTRACT FROM AUTHOR]

Power transformers are still equipment of primary importance within power grids. The recent paradigm changes registered in the field of energy require the interconnection of electrical grids of much larger areas, even up to the level of an entire continent. In this context, knowing the state of the electrical equipment and that of the power transformers is an essential aspect to ensure safe operation conditions. The present work is related to the vulnerability of the oil–paper insulation systems of power transformers to different aging factors and their quick degradation under certain conditions. In this regard, the study proposed in this paper considers the measurement of DC resistivity on mineral oil samples contaminated with small amounts of accelerated aging oil under the action of high-strength electric field and partial discharges. In the absence of standardized procedures for accelerated electrical aging of mineral oil, an original method presented and discussed in previous articles is used. The obtained results clearly indicate that under the action of electrical stress, the mineral oil resistivity decreases significantly, showing that the oil's electric properties worsen. [ABSTRACT FROM AUTHOR]

Extreme weather events are one of the main causes of large-scale power outages in distribution systems. The changing climate has led to an increase in the frequency and severity of these events, which, if not mitigated, are expected to lead to more instances of widespread outages and the severe societal and economic damages that ensue. Protecting the power grid against such events, which are high impact yet low frequency, requires a paradigm shift in grid design practices. In recent years, many researchers have focused on the resilience of the power grid against extreme weather events by proposing various grid hardening and/or redundancy solutions. The goal of this paper is to provide a survey of the literature related to the infrastructural resilience of the power grid against extreme events. Currently, no standard definitions or metrics exist for power grid resilience, and researchers adopt various models for quantifying and assessing it. Hence, a review of the most commonly used definitions and metrics for resilience is provided first, with a discussion of their advantages and disadvantages. Next, the paper presents an extensive and critical review of the solution methodologies proposed in the literature for improving the infrastructural resilience of the power grid. The shortcomings of the current solution methods and gaps in research are identified, followed by a discussion of the future directions in research. [ABSTRACT FROM AUTHOR]

Studying a renewable energy integrated power system's features is essential, especially for deregulated systems. The unpredictability of renewable sources is the main barrier to integrating renewable energy-producing units with the current electrical grid. Due to its unpredictable nature, integrating wind power into an existing power system requires significant consideration. In a deregulated electricity market, this paper examines the implications of wind farm (WF) integration with CAES on electric losses, voltage profile, generation costs, and system economics. Comparative research was done to determine the impact of wind farm integration on regulated and deregulated environments. Four randomly chosen locations in India were chosen for this investigation, together with real-time information on each location's real wind speed (RWS) and predicted wind speed (PWS). Surplus charge rates and deficit charge rates were created to assess the imbalance cost arising from the discrepancy between predicted and real wind speeds to calculate the system economics. When the effect of imbalance cost is considered, the daily system profit shows a variation of about 1.9% for the locations under study. Customers are always seeking electricity that is dependable, affordable, and efficient due to the reorganization of the power system. As a result, the system security limit could be exceeded or the system might function dangerously. The final section of this paper presents an economic risk analysis using heuristic algorithms such as sequential quadratic programming (SQP), artificial bee colony algorithms (ABC), and moth flame optimization algorithms (MFO). It also discusses how the CAES is used to correct the deviation of WF integration in the real-time electricity market. Economic risk analysis tools include value-at-risk (VaR) and conditional value-at-risk (CVaR). The entire piece of work was validated using a modified IEEE 30-bus test system. This works shows that with a three-fold increase in wind generation, the risk coefficient values improves by 1%. [ABSTRACT FROM AUTHOR]

As the world is transitioning to electric vehicles (EVs), the existing power grids are facing several challenges. In particular, the additional charging power demand may repeatedly overload the traditionally-sized distribution transformers and adversely impact their operational life. To address this challenge, this paper proposes an EV-based reactive power compensation strategy for transformer overloading mitigation. Specifically, a low-bandwidth centralized recursive controller is proposed to determine a set point for the EV's onboard charger's reactive power. Importantly, the proposed strategy is practically implementable in existing distribution grids as it does not rely on smart grid infrastructure and is stable under potential communication delays and partial failures. This paper discusses the controller's structure, design, and stability in detail. The proposed solution is tested with a realistic secondary distribution system considering four different EV charging scenarios with both Level 1 and Level 2 residential EV charging. Specifically, IEEE Standard C57.91-2011 is used to quantify the impact of EV charging on the transformer's life. It is shown that with the proposed method, transformer overloading is significantly reduced, and the transformer's life improves by an average of 47% over a year in all four scenarios. [ABSTRACT FROM AUTHOR]

The convergence of Information Technologies and Operational Technology systems in industrial networks presents many challenges related to availability, integrity, and confidentiality. In this paper, we evaluate the various cybersecurity risks in industrial control systems and how they may affect these areas of concern, with a particular focus on energy-sector Operational Technology systems. There are multiple threats and countermeasures that Operational Technology and Information Technology systems share. Since Information Technology cybersecurity is a relatively mature field, this paper emphasizes on threats with particular applicability to Operational Technology and their respective countermeasures. We identify regulations, standards, frameworks and typical system architectures associated with this domain. We review relevant challenges, threats, and countermeasures, as well as critical differences in priorities between Information and Operational Technology cybersecurity efforts and implications. These results are then examined against the recommended National Institute of Standards and Technology framework for gap analysis to provide a complete approach to energy sector cybersecurity. We provide analysis of countermeasure implementation to align with the continuous functions recommended for a sound cybersecurity framework. [ABSTRACT FROM AUTHOR]

The integration of large-scale wind and photovoltaic power into modern power grids leads to an imbalance between the supply and demand for resources of the system, where this threatens the safety and stable operation of the grid. The traditional mode of grid dispatch and the capability of regulation of conventional thermal power units cannot satisfy the demands of grid connection for large-scale renewable energy, where the system requires the compensation and coordinated dispatch of flexible power sources. In light of this problem, this paper establishes a model to quantify the uncertainty in the forecasted outputs of wind and photovoltaic power. This is used to develop forecasts of the output of wind and photovoltaic power for several groups of scenarios, and predictions with the best complementarity are selected as a typical set of scenarios by means of their generation, reduction, and combination. By taking full advantage of the complementarity in the rates of regulation of conventional thermal power and concentrating solar power (CSP), a coordinated model of dispatch for wind power, photovoltaic power, CSP, and thermal power is established for a number of typical combinations of scenarios. The influence of uncertainty in the outputs of wind and photovoltaic power on the dispatch of the power grid is examined, and different modes of dispatch are formulated through simulations to analyze the superiority of the dispatch strategy proposed in this paper in terms of abandoned wind quantity, abandoned solar quantity, and the cost of dispatch. [ABSTRACT FROM AUTHOR]

The terminal equipment interconnection and the network communication environment are complex in power cyber–physical systems (CPS), and the frequent interaction between the information and energy flows aggravates the risk of false data injection attacks (FDIAs) in the power grid. This paper proposes an active defense framework against FDIAs of power CPS based on data-driven algorithms in order to ensure that FDIAs can be efficiently detected and processed in real-time during power grid operation. First, the data transmission scenario and false data injection forms of power CPS were analyzed, and the FDIA mathematical model was expounded. Then, from a data-driven perspective, the algorithm improvement and process design were carried out for the three key links of data enhancement, attack detection, and data reconstruction. Finally, an active defense framework against FDIAs was proposed. The example analysis verified that the method proposed in this paper could effectively detect FDIAs and perform data reconstruction, providing a new idea for the active defense against FDIAs of power CPS. [ABSTRACT FROM AUTHOR]

The transmission and distribution systems are essential in facilitating power flow from the source multiple loads over large distances with high magnitudes of voltages and currents. Hence, the monitoring and control of various components of these structures are crucial. Traditionally, this was implemented by sensing only the grid current and grid voltage parameters through coils, clamps, or instrument transformers. However, these have bulky structures that restrict them to the substation and have installation and maintenance issues due to their direct contact with high voltage conductors. Currently, the power grid is undergoing various developments e.g., penetration of renewable energy sources, remote control, and automation, bidirectional power flow, etc. These developments call for compact and energy-efficient sensors to sense multiple grid parameters such as the magnetic field data, temperature, humidity, acoustics, etc., to enable real time, wide area monitoring and the predictive maintenance of the power grid. The goal of this paper is to summarize the advancements in sensing technologies on transmission and distribution systems over a decade and to explain their role in the forthcoming expansion of the power grids. This paper aims to outline the current state-of-affairs of sensor technology as well as to fill research gaps by exploring their limitations. [ABSTRACT FROM AUTHOR]

Microgrids (MGs) and networked (interconnected) microgrids (NMGs) are emerging as an efficient way for integrating distributed energy resources (DERs) into power distribution systems. MGs and NMGs can disconnect from the main grid and operate autonomously, strengthen grid resilience, and help mitigate grid disturbances and maintain power quality. In addition, when supported by sophisticated and efficient management strategies, MGs and NMGs have the ability to enhance power supply reliability. However, their deployment comes with many challenges, in particular regarding the efficient management of DERs. That is why a survey of recent advances in the smart management—the term refers to a variety of planning and control tasks—of MGs and NMGs is presented in this paper. It aims at establishing a picture of strategies and identifying trends in methods. The reader is provided with an in-depth analysis of a variety of papers recently published in peer-reviewed journals: the way the methods are used and the common issues addressed by the scientific community are discussed. Following this analysis, one can especially observe that (1) model-based predictive control (MPC) is emerging as a competitive alternative to conventional methods, in particular in voltage and frequency regulation and DER management (2) due to their ability to handle complex tasks, data-driven strategies are getting more and more attention from the scientific community (3) game theory (GT) is a very good candidate for efficient management of complex systems as NMGs (4) MPC and artificial intelligence are increasingly being used for proper MG islanded operation or to manage electric vehicles (EVs) efficiently. [ABSTRACT FROM AUTHOR]

The high-voltage (HV) assets in the existing power transmission network will experience increased electrical, thermal, environmental and mechanical stresses and, therefore, robust condition monitoring is critical for power system reliability planning. Fibre Bragg grating (FBG) sensors offer a promising technology in HV applications due to their immunity to electromagnetic interference and multiplexing capability. This paper reviews the current technology readiness levels of FBG sensors for condition monitoring of transformers, transmission lines, towers, overhead insulators and power cables, with the aim of stimulating further development and deployment of fibre-based HV asset management systems. Currently, there are several reported cases of FBG sensors used for condition monitoring of HV assets in the field, proving their feasibility for long-term use in the power grid. The review shows that FBG technology is versatile and can facilitate multi-parameter measurements, which will standardise the demodulation equipment and reduce challenges with integrating different sensing technologies. [ABSTRACT FROM AUTHOR]

Prior to switching operations, the dispatch automation system is required to be able to search for closed-loop paths quickly in real time. In order to improve the efficiency of closed-loop path search, this paper proposes a multi-stage real-time fast search method for closed-loop paths based on the characteristics of power grid hierarchical partitioning. First, we divide the closed-loop judgement process into three phases: initialization, acceptance of the closed-loop judgement command, and post-operation. Then, we define three types of nodes, including root nodes, same-layer contact nodes, and common nodes, and construct path data models for each type of node in accordance with the node liaison relationship in grid hierarchical zoning. In the initialization phase, we design a method for the automatic generation of real-time nodal path data models and study a hierarchical partitioned closed-loop path search method based on a nodal path data model for the phase of accepting closed-loop judgement commands. Next, we design a fast local correction method for nodal path models after the switch closure and disconnection operations in the post-operation idle phase are performed. Finally, a real power grid model is used as an example to test the above closed-loop path search method, which improves the search efficiency by eight times compared with the conventional breadth-first search method. The method is applicable to real large and complex power grids. [ABSTRACT FROM AUTHOR]

Renewable penetration, particularly the increasing deployment of PV by residential customers, organizations, and utilities, is leading to the rapid evolution of the power grid. However, the power system's architectural changes affect the quality of supply and give rise to power quality issues such as harmonics, fluctuations, disturbances, etc., at the point of common coupling (PCC). Therefore, in this work, a power network was modeled to study the impact of PV systems on PCC. At first, a detailed review is presented for on-grid PV systems with different inverter topologies, control techniques, sources of harmonic generation, and their mitigation strategies. After that, several use cases considering various sources of harmonics in a network with on-grid PV are modeled and simulated using MATLAB/Simulink. In-depth research was performed in this work to examine the many variables that affect harmonics, such as solar radiation levels, controller tuning, and load changes. Results with a real-time simulation platform (OPAL-RT) are presented in this paper for several use cases. Lastly, comprehensive discussions are presented from the acquired offline and real-time simulation results. [ABSTRACT FROM AUTHOR]

China has a vast scale of hydropower, and the small hydropower stations account for a large proportion. In flood season, the excessive inflow keeps these stations at a high reservoir level, leading to a worse condition of hindered power output and a great error in the calculation of power generation. Therefore, this paper proposes a mid-term optimal scheduling model for low-head cascaded hydropower stations considering inflow unevenness, in which the power output is controlled by the expected power output curve and daily inflow–maximum power output curve. A case study of nine hydropower stations on the Guangxi power grid shows that, regardless of considering the fitted curve or not, there are different degrees of error between the planned and actual situations. However, the error and power generation are decreased when considering the fitted curve, which reflects the impact of hindered power output. Meanwhile, according to the comparison, the weekly plan is more in line with the real condition when using this model to solve the problem. The results indicate that this model improves the accuracy of power output calculation for low-head hydropower stations with uneven inflow, playing a key role in the process of scheduling. [ABSTRACT FROM AUTHOR]

The electricity market has increasingly played a significant role in ensuring the smooth operation of the power grid. The latest incarnation of the electricity market follows a bottom-up paradigm, rather than a top-down one, and aims to provide flexibility services to the power grid. The blockchain-based local energy market (LEM) is one such bottom-up market paradigm. It essentially enables consumers and prosumers (those who can generate power locally) within a defined power network topology to trade renewable energy amongst each other in a peer-to-peer (P2P) fashion using blockchain technology. This paper presents the development of such a P2P trading-facilitated LEM and the analysis of the proposed blockchain-based LEM by means of a case study using actual German residential customer data. The performance of the proposed LEM is also compared with that of BAU, in which power is traded via time-of-use (ToU) and feed-in-tariff (FiT) rates. The comparative results demonstrate: (1) the participants' bill savings; (2) mitigation of the power grid's export and import; (3) no/minimal variations in the margins of energy suppliers and system operators; and (4) cost comparison of Ethereum versus Polygon blockchain, thus emphasising the domineering performance of the developed P2P trading-based LEM mechanism. [ABSTRACT FROM AUTHOR]

The future power system will be characterized by many small decentralized power plants—so-called distributed energy resources (DERs). The integration of these DERs is vital from an economic and grid operation point of view. One approach to this is the aggregation of such DERs. The formation of coalitions as an aggregation method has already been examined in the literature and applied in virtual power plants, active distribution networks, and microgrids. The spread of DERs also increases the need for flexibility and dynamics in the power grid. One approach to address this can be overlapping coalitions. Therefore, in this paper, we first performed an analysis of related work and, in this context, found no work on overlapping coalitions for energy use cases in the literature. We then described a method for dynamic coalition formation, called dynamic coalition in electricity markets (DYCE), and analyzed how DYCE would need to be extended to include overlapping coalition formation. The extension includes the phases of product portfolio optimization and the actual coalition formation. Our analysis of DYCE shows that the methods used for the optimization of the DYCE sub-tasks are not suitable for overlapping coalitions and would have to be replaced by other methods in order to be able to form overlapping coalitions. [ABSTRACT FROM AUTHOR]

Agricultural biogas plant operations are energy sources that fit well with rural land use. The continuous increase in cattle and pigs creates the need to manage animal waste, especially slurry. Using it for energy production in biogas plants offers the possibility of obtaining electricity, heat, and highly efficient manure. The thermal energy generated in an agricultural biogas plant is used to heat the substrate in the fermentation process and can also be used to heat buildings, dry fodder, or wood. Electricity can be used to cover the farm's needs and sold to an energy company. However, the energy generated in the biogas plant must be of the right quality. One of the main factors describing the quality of electricity is the voltage distortion from the sinusoidal waveform. This paper presents the results of a study of the impact of biogas plant operation on the course of voltage and current in the grid. The theoretical analysis of the voltage distortion mechanism at the point of connection of an agricultural biogas plant was based on a simplified power system model consisting of a voltage source and the equivalent impedance of the power system. According to the theoretical analyses, agricultural biogas plant operation should reduce the voltage distortion factor. In order to confirm this statement, field tests were carried out at three agricultural biogas plants, based on which an analysis was made of the impact of the power generated in the biogas plants on the value of voltage distortion occurring at the point of their connection. However, the field tests did not confirm the conclusion of the theoretical analysis. Only in one case (where the biogas plant was connected near a substation and there was the highest short-circuit power) could it be seen that an increase in generation affected the voltage distortion factor. In the other two cases, generation did not significantly affect the shape of the voltage waveform. However, in each of the biogas plants studied, as the generation power increased, the current distortion factor decreased, suggesting that agricultural biogas plants should operate as close to the rated power as possible. [ABSTRACT FROM AUTHOR]

With the continuous development of the global economic level, global energy consumption is also on the rise, and the global power industry is faced with a number of formidable challenges including load growth, low energy efficiency, high power quality, and environmental protection. Despite the fact that distributed energy cannot be directly connected to the power grid, the concept of the microgrid (MG) is proposed to make better use of distributed energy and reduce its effect on the power grid. The low cost and high controllability of DC MGs have piqued the interest of academicians both at home and abroad. If DC MGs are to be implemented in real-world engineering, a stability control strategy is required; therefore, research on voltage stability and coordinated control of DC MGs is extremely important and promising. This paper summarizes the current research on the voltage control strategy of the DC MG from the perspective of the voltage control strategy of the DC MG. Lastly, it is proposed that the future development of DC MGs will be more focused on intelligence and control precision and that the consistency algorithm combined with the benefits of centralized control and distributed control can effectively aid the future development of DC MGs, taking into account the grid's dependability and control precision. [ABSTRACT FROM AUTHOR]

Load forecasting is an important component of power system and resource planning for electrical grids. The adoption of electric vehicles (EVs), behind-the-meter (BTM) solar, and heat pumps will significantly change the amount and variability of loads. Electrification adoption and load forecasting in arctic regions and Alaska is limited. This paper provides the first load and electrification adoption forecast for the Alaska Railbelt transmission system, including yearly adoption rates of EVs, BTM solar, and heat pumps and hourly load data for the forecasted year of 2050. The adoption rates were based on the available historical data and compared to other regional and national trends. Two forecasts were created: (1) a moderate adoption forecast based on projections from current adoption rates and comparisons to other regional and national projections and (2) an aggressive forecast, which provides an illustrative comparison of a high adoption rate of 90% for all technologies. The results of these forecasts demonstrate a significant increase in both energy, 80% and 116%, and peak load demand, 113% and 219%, for the moderate and aggressive electrification adoption scenarios, respectively. These findings highlight a need for resource planning and demand management in this region due to the adoption of EVs, BTM solar, and heat pumps. [ABSTRACT FROM AUTHOR]

Clustering-based reactive voltage partitioning is successful in reducing grid cascading faults, by using clustering methods to categorize different power-consuming entities in the power grid into distinct regions. In reality, each power-consuming entity has different electrical characteristics. Additionally, due to the irregular and uneven distribution of the population, the distribution of electricity consumption is also irregular and uneven. However, the existing method neglects the electrical difference among each entity and the irregular and uneven density distribution of electricity consumption, resulting in poor accuracy and adaptability of these methods. To address these problems, an enhanced density peak model-based power grid reactive voltage partitioning method is proposed in this paper, called EDPVP. First, the power grid is modeled as a weighted reactive network to consider entity electrical differences. Second, the novel local density and density following distance are designed to enhance the density peak model to address the problem that the traditional density peak model cannot adapt to weighted networks. Finally, the enhanced density peak model is further equipped with an optimized cluster centers selection strategy and an updated remaining node assignment strategy, to better identify irregular and uneven density distribution of electricity consumption, and to achieve fast and accurate reactive voltage partition. Experiments on two real power grids demonstrate the effectiveness of the EDPVP. [ABSTRACT FROM AUTHOR]

Renewables are the greener substitute for the conventional polluting sources of generating energy. For their successful integration into the power grid, accurate forecasts are required. In this paper, we report the lessons acquired from our previous works on generating time-series ARIMA-based forecasting models for renewables. To this end, we considered a consistent dataset spanning the last four years. Assuming four different performance metrics for each of the best ARIMA-based models of our previous works, we derived a new optimal model for each month of the year, as well as for the two different methodologies suggested in those works. We then evaluated the performance of those models, by comparing the two methodologies: in doing so, we proposed a hybrid methodology that took the best models out of those two methodologies. We show that our proposed hybrid methodology has improved yearly accuracy of about 89.5% averaged over 12 months of the year. Also, we illustrate in detail for the four years under study and each month of the year the observed percentage of renewables and its corresponding accuracy compared to the generated forecasts. Finally, we give the implementation details of our open-source REN4KAST software platform, which provides several services related to renewables in Germany. [ABSTRACT FROM AUTHOR]

Constructing a renewable energy-based power system has become an important development path for the power industry's low-carbon transformation. However, as the proportion of renewable energy generation (REG) increases, the power grid gradually changes to uncertainty. Technologies to address this issue have been introduced. However, the majority of existing reviews focus on specific uncertainty modeling approaches and applications, lacking the consideration of temporal and spatial interdependence. Therefore, this paper provides a comprehensive review of the uncertainty modeling of temporal and spatial interdependence. It includes the discrete and continuous stochastic process-based methods to address temporal interdependence, the correlation coefficient and copula functions in modeling spatial interdependence, and the Itô process and random fields theory to describe temporal and spatial interdependence. Finally, their applications in power system stability, control, and economic scheduling are summarized. [ABSTRACT FROM AUTHOR]

Power-converter-based energy-harvesting and storage systems are becoming more prevalent in the electrical grid, replacing conventional synchronous generators. Consequently, grid inertia is diminishing, and to address this, inverter-based energy conversion systems are required by grid codes to provide frequency control support to the main grid. This is undertaken to increase the equivalent inertia of the system and reduce frequency variations. This type of control is necessary and designed for handling large system transients. However, it also impacts the small-signal stability of the grid-connected converters. To investigate this issue, this paper addresses the influence of synthetic inertia control on the output admittance of a grid-following inverter and its interaction with the grid equivalent impedance. A synchronous reference frame dynamic model of the grid-following inverter closed-loop system is obtained and linearized at an operating point to analyze the small-signal stability of the low-switching frequency inverter. The models are validated through numerical simulations. The analysis verifies the interactions of the internal control loops, such as the AC current control with voltage feedforward, DC-link voltage control with power-feedforward, phase-locked loop, and AC voltage control with inertial control. Additionally, the interactions between the output admittance of the inverter and the grid impedance are verified using the generalized Nyquist criterion. The stability regions are validated through simulations, and the results show that the system gain margin is reduced for increasing values of synthetic inertia gain and lower grid short-circuit ratios. Furthermore, there is a limit in the voltage and power-feedforward bandwidth to avoid degrading the system stability when utilizing the synthetic inertia control. [ABSTRACT FROM AUTHOR]

With the increasing proportion of distributed photovoltaic (DPV) installations in county-level power grids, to improve the centralized operation and maintenance of the stations and to meet the needs of power grid dispatching, the output of the county-level regional DPV stations group needs to be predicted. In this paper, the weather prediction information is used to predict the output based on the model input average strategy. To eliminate the effect of the selected non-optimal training sample collection period on the prediction accuracy, an ensemble prediction method based on the minimum redundancy maximum relevance criterion and TabNet model is carried out. To reduce the influence of weather prediction errors on the power output prediction, a modified model based on error prediction is proposed. The ensemble prediction model is used to predict the day-ahead output, and a combination prediction model based on the proposed ensemble prediction model and the proposed modified model is established to predict the hour-ahead output. The experimental results verify the effectiveness of the proposed models. Compared with the corresponding reference models, the proposed ensemble prediction method reduces the normalized mean absolute errors (nMAEs) and the normalized root mean square errors (nRMSEs) of the day-ahead output prediction results by 2.86% and 5.51%, respectively. The combination prediction model reduces the nMAE and nRMSE of the hour-ahead output prediction results by 3.05% and 3.05%, respectively. Therefore, the prediction accuracy can be improved by the proposed models. [ABSTRACT FROM AUTHOR]

Large-scale development of small-scale generation, and facilities based on this, with their integration into existing distribution networks, qualitatively change the modes and tasks of network management and transform previously passive electric networks into active ones. Features of parameters and modes of small-scale generation, insufficient observability and manageability in centralized management determine the need to use a decentralized multi-agent control of the modes of such networks. First of all, this applies to emergency management, which includes automatic restoration of the integrity and normal operation of the network. This paper presents a set of specialized methods for emergency management of active power grid modes and the results of a study of their effectiveness on mathematical and physical models that confirm the feasibility of using decentralized emergency management and network recovery management. In particular, this includes: a method of emergency proactively balanced separation of grid energy districts along one of the a priori fixed network cross-sections in the event of disturbances with the transition to island mode, and a method for two-stage restoration of the integrity and normal network mode with decentralized synchronization of active parts on remote network switches. In the case of the decentralized remote synchronization of active parts, it is proposed to use special control of the excitation and speed of generators to create conditions for the successful operation of automatic reclosing devices with synchronization detection. It is essential for emergency management in active networks with small generation to reject the concept of ensuring the reliability of power supply through maintaining the integrity of the network in favor of the concept of an emergency-balanced breakdown of the network into balanced areas with the subsequent automatic restoration of integrity. To conduct research on the physical model, a prototype of distributed system emergency automation has been developed that does not use data transmission tools, which ensures its high cybersecurity and the feasibility of decentralized management. [ABSTRACT FROM AUTHOR]

Virtual power plants (VPPs) are a critical technology for distribution systems that can integrate various renewable energy resourcescontrollable loads and energy storage systems into one specific power plant through a distributed energy management system. This paper proposes a coordinated dispatch optimization model between the main grid and VPPs aiming to minimize both the power generation cost and total system active loss. When the time of the equivalent dispatching model is not divisible due to the existence of a time coupling constraint inside the VPPs, this model can obtain the global optimal solution through iteration between the main grid and the VPPs. By employing multi-parametric quadratic programming to obtain accurate critical domains and optimal cost functions, the convergence speed and stability are significantly improved. Additionally, a reactive power and voltage optimization technique leveraging the generalized Benders decomposition is presented for the coordination of the main grid and the VPPs. Moreover, the impact of distributed energy resource (DER) clusters on the main grid was studied, from which we proved that the proposed approach can expeditiously abate energy production expenditure and system active dissipation whilst enhancing the system equilibrium. [ABSTRACT FROM AUTHOR]

In modern power systems, interharmonics have emerged as noninteger frequency components that appear in current or voltage signals. Double-stage AC-DC-AC converters have been identified as a primary source of interharmonics. Previous studies have highlighted modulation techniques, filters, passive components, unbalanced conditions and DC link effects as relevant factors. However, the interaction between these factors and the inertial properties of induction motors has not been explored. This study assesses various types of AC drives, including variable frequency drives (VFDs) and soft starters (AC choppers), to investigate their interaction with machine inertial properties in interharmonic generation. The employed technique for time-frequency spectral analysis is the wavelet synchrosqueezed transform combined with a clustering method. This paper demonstrates that the interaction of the inertial properties of low-power induction motors with the variations of the switching frequencies of the VFDs, the filters used in the DC link and a soft start indirectly contribute to harmonic generation and potentially to interharmonics in the electrical grid and the outputs of the inverter. [ABSTRACT FROM AUTHOR]

Drones are becoming a greater threat to modern electrical grids with the capability to cause expensive and time-consuming damage repairs to substations and transmission lines. Consumer drones have the potential to cause harm at a low cost, and finding methods to counter these threats is becoming more crucial to keep grids secure. In 2021, there was an attempted attack on a substation with a consumer drone which highlighted the need for research in this area. Previously, there has been a large focus on counter drones around places such as airports; however, more focus is warranted to analyze drone impact on the grid infrastructure. Methods to counter drones' harmful impacts vary from physical methods to using electromagnetic waves. This article looks to identify and propose potential applications for existing technologies, as well as developing anti-drone technologies. These methods have not been adopted yet; thus, there is a great opportunity to utilize these existing technologies to defend the grid. The methods investigated were surveillance cameras, patrolling drones, nets, signal jammers, and energy weapons. The existing technology is currently lacking in the area of drone defense and can be improved with existing studies. However, there is a need to identify those methods and find ways to apply them to the power grid. Different defending technologies vary concerning their potential implementation. This paper also identifies and categorizes different results these methods produce to counter drones and their associated costs. [ABSTRACT FROM AUTHOR]

A distribution grid is the dispatching part of the power grid where electricity is finally utilized by the end users. In the electricity industry, automation habitually means the smart grid. The SG is a broad topic with different elements working towards grid optimization. One best way of optimizing a power grid is to balance the electricity supply and usage. This paper proposes an automated approach and presents a coordinative concept to develop a real-time interfacing network for demand-side management mitigations. The SDNS network concept uses a master–slave metering hierarchy to coordinate the devices between the utility and the end users by regulating the electrons' movement from the utility to the consumer's side. This concept was tested on MATLAB and a prototype. The results proved the efficiency of this design in demand-side management. The SDNS is an innovative tech, and it also plays a vital role in making consumers role players in easing the grid. The results proved that load management could replace load shedding by correctly implementing the SDNS concept. [ABSTRACT FROM AUTHOR]

With the large-scale access of renewable energy, the randomness, fluctuation and intermittency of renewable energy have great influence on the stable operation of a power system. Energy storage is considered to be an important flexible resource to enhance the flexibility of the power grid, absorb a high proportion of new energy and satisfy the dynamic balance between the supply and demand of a system. At present, the cost of energy storage is still high, and how to achieve the optimal energy storage configuration is the primary problem to be solved. Therefore, the current research progress in energy storage application scenarios, modeling method and optimal configuration strategies on the power generation side, grid side and user side are summarized in this paper. On this basis, the shortcomings that still exist of energy storage configuration research are summarized, and the future research direction for energy storage configuration is prospected. This review can provide reference for the latest development and future research and innovation direction for energy storage configuration. [ABSTRACT FROM AUTHOR]

Electric vehicles have become a crucial component of modern power systems, possessing substantial energy reserves that can be important power supplies in blackouts where the power grid has weak reserves or limited connections to other grids. In order to clarify the technical conditions and control methods of the centralized electric vehicle charging station as the black-start power source of the power grid, assuming that the centralized electric vehicle charging station can be considered a single, large-scale energy storage system, this paper proposes a three-stage coordinated recovery strategy based on the centralized electric vehicle charging station. The strategy involves three distinct stages, beginning with the establishment of AC frequency and voltage by the electric vehicle charging station to initiate the auxiliary load of the power plant. In the middle stage, considering the traditional generator has been connected, the charging station's control mode is set to provide constant active and reactive power output, providing extra voltage and frequency support to the grid-connected generating units and crucial loads. Finally, in the later stage, control strategies are tailored to the charging power stations' capacities, with one group of additional oscillation damping controllers, while the other group adopts additional frequency control to decrease power disturbances, ensuring a smooth recovery of the power grid. A PSCAD/EMTDC-based model was constructed to verify the proposed coordinated grid recovery strategies. The results demonstrated that the centralized station successfully established the voltage and frequency of the AC system, and the designed additional controller also made the recovery process much more stable. [ABSTRACT FROM AUTHOR]

The forthcoming surge in electric vehicle (EV) adoption demands the comprehensive advancement of associated charging infrastructure. In this study, an exploration of EV charging's impact on the power distribution system is conducted via the simulation of a parking lot equipped with six distinct types of EVs, each showcasing unique charging curves, charging power, and battery capacities. A charging profile is synthesized and compared with laboratory-obtained data to ascertain the implications on the grid. To further understand the effects of smart parking on the power distribution system, a mathematical algorithm was created and applied to a segment of an urban electrical grid that includes 70 private residences. Basic electrical parameters were computed using the node voltage method. Four scenarios were simulated: (1) the existing distribution system, (2) the current system plus smart parking, (3) the current system plus 50% of houses equipped with 3.5 kW photovoltaic installations, and (4) the current system plus photovoltaics and smart parking. This paper examines the core distribution system parameters, namely voltage and current, across these four scenarios, and the simulation results are extensively detailed herein. [ABSTRACT FROM AUTHOR]

The paper conducts a literature review of applications of autoregressive methods to short-term forecasting of power demand. This need is dictated by the advancement of modern forecasting methods and their achievement in good forecasting efficiency in particular. The annual effectiveness of forecasting power demand for the Polish National Power Grid for the next day is approx. 1%; therefore, the main objective of the review is to verify whether it is possible to improve efficiency while maintaining the minimum financial outlays and time-consuming efforts. The methods that fulfil these conditions are autoregressive methods; therefore, the paper focuses on autoregressive methods, which are less time-consuming and, as a result, cheaper in development and applications. The prepared review ranks the forecasting models in terms of the forecasting effectiveness achieved in the literature on the subject, which enables the selection of models that may improve the currently achieved effectiveness of the transmission system operator. Due to the applied approach, a transparent set of forecasting methods and models was obtained, in addition to knowledge about their potential in the context of the needs for short-term forecasting of electricity demand in the national power system. The articles in which the MAPE error was used to assess the quality of short-term forecasts were analyzed. The investigation included 47 articles, several dozen forecasting methods, and 264 forecasting models. The articles date from 1997 and, apart from the autoregressive methods, also include the methods and models that use explanatory variables (non-autoregressive ones). The input data used come from the period 1998–2014. The analysis included 25 power systems located on four continents (Asia, Europe, North America, and Australia) that were published by 44 different research teams. The results of the review show that in the autoregressive methods applied to forecasting short-term power demand, there is a potential to improve forecasting effectiveness in power systems. The most promising prognostic models using the autoregressive approach, based on the review, include Fuzzy Logic, Artificial Neural Networks, Wavelet Artificial Neural Networks, Adaptive Neurofuse Inference Systems, Genetic Algorithms, Fuzzy Regression, and Data Envelope Analysis. These methods make it possible to achieve the efficiency of short-term forecasting of electricity demand with hourly resolution at the level below 1%, which confirms the assumption made by the authors about the potential of autoregressive methods. Other forecasting models, the effectiveness of which is high, may also prove useful in forecasting by electricity system operators. The paper also discusses the classical methods of Artificial Intelligence, Data Mining, Big Data, and the state of research in short-term power demand forecasting in power systems using autoregressive and non-autoregressive methods and models. [ABSTRACT FROM AUTHOR]

Power systems are experiencing some profound changes, which are posing new challenges in many different ways. One of the most significant of such challenges is the increasing presence of inverter-based resources (ibrs), both as loads and generators. This calls for new approaches and a wide reconsideration of the most commonly established practices in almost all the levels of power systems' analysis, operation, and planning. This paper focuses specifically on the impacts on stability analyses of the numerical models of power system passive components (e.g., lines, transformers, along with their on-load tap changers). Traditionally, loads have been modelled as constant power loads, being this both a conservative option for what concerns stability results and a computationally convenient simplification. However, compared to their counterparts above, in some operating conditions ibrs can effectively be considered real constant power loads, whose behaviour is much more complex in terms of the equivalent impedance seen by the network. This has an impact on the way passive network components should be modelled to attain results and conclusions consistent with the real power system behaviour. In this paper, we investigate these issues on the ieee14 bus test network. To begin with, we assess the effects of constant-power and constant-impedance load models. Then, we replace a transmission line with a dc line connected to the network through two modular multilevel converters (mmcs), which account for the presence of ibrs in modern grids. Lastly, we analyse how and to which extent inaccurate modelling of mmcs and other passive components can lead to wrong stability analyses and transient simulations. [ABSTRACT FROM AUTHOR]

CO2 net neutralization by 2050 is a global target. Renewable energy and nuclear power generation are emerging as major power sources for CO2 net neutralization. Therefore, this paper comprehensively reviews the load-following operation method of nuclear power plants as a method to compensate for intermittency, which is the biggest weakness of renewable energy. First, this paper looks at the types of SMRs and elaborates the concept and necessity of load following. The comprehensive requirements for the load-following operation of an SMR, i.e., planned operation, automatic generation control, governor-free operation, cooperative control of the reactor and turbine generator, unit control of a multiple-module SMR, cogeneration, etc., are studied. Finally, the interaction between an SMR and the power grid during load-following operation and other technical issues are also reviewed. This paper can be used as a guide for load-following operations or as a guide for requirement analysis when developing a comprehensive control system of load following in SMR fleets. [ABSTRACT FROM AUTHOR]

The application of on-load tap-charger (OLTC) transformer technology has become the most direct and effective way to solve the voltage fluctuation of power grid. With the development of active distribution technology, the research focus of on-load voltage regulation technology has gradually turned to the development direction of arc free, fast and intelligent. This paper presents a flexible on-load voltage regulation topology based on power electronic technology. The flexible on-load voltage regulation (flexible OLVR) transformer is a combination of power electronic technology and traditional on-load tap-charger transformer, which can realize fast arcless switching, voltage step-less regulation, power regulation and other functions. In this paper, a new type of flexible on-load voltage regulation transformer is proposed. The OLTC switches of the device adopts the power electronic switch of anti-parallel thyristors, which can realize step, fast and arcless voltage regulation; the power electronic converter (PEC) module is connected to the primary side of the main transformer. At the same time, it proposed a new reactive power compensation control strategy, which could realize the functions of step-less voltage regulation and reactive power compensation. In the end, the rationality and validity of the proposed topology is tested and verified by simulations and experimental tests. [ABSTRACT FROM AUTHOR]

In the 21st century, the worldwide concern about global warming has forced energy to transform in the direction of low-carbon and non-carbon. The utilization of renewable energy is developing rapidly, which makes the non-synchronous generator sources become the main part of the newly added power sources. Based on the fundamentals of AC power grid operation, this paper describes three technical challenges faced by the power system in transition: the inadequacy of the classic synchronization stability concept in representing the new synchronization connotation of AC power systems with large proportion of non-synchronous generator sources; the inapplicability of the electromechanical transient analysis method in analyzing the generalized synchronization stability; and the wideband resonance instability caused by negative resistance of power electronic equipment. The decisive factors for maintaining the generalized synchronization stability, the countermeasure to solve the inapplicability of the electromechanical transient analysis method and a systematic approach to tackle the broadband resonance instability are proposed in the paper. [ABSTRACT FROM AUTHOR]

Pumped storage units improve the stability of the power grid, and the key component is the pump–turbine. A pump–turbine usually needs to start and shutdown frequently, and the operating head varies greatly due to changes in the water level of the reservoir, which makes the dynamic behavior of a pump–turbine runner extremely complex. This paper investigates the effects of operating head on the dynamic response characteristics of a pump–turbine runner in turbine mode. The flow characteristics of the pump–turbine at maximum head, rated head and minimum head are analyzed, and the dynamic response characteristic of the pump–turbine runner are numerically studied. The results show that operating head can affect the pressure pulsation and dynamic stress characteristics of the pump–turbine runner, but it has little effect on the frequency spectra. The conclusions of this paper intend to improve understanding of the effects of the operating head on the dynamic behavior of the pump–turbine runner, therefore providing a theoretical reference for safe and stable operation of the pump–turbine unit. [ABSTRACT FROM AUTHOR]

One of the crucial steps for a successful integration of electric bus fleets into the existing electric power systems is the active and intelligent usage of their flexibility. This is important not only for reducing the eventual negative effects on the power grid but also for reducing energy and infrastructure costs. The first step in the optimal usage of flexibility is its quantification, which allows the maximum provision of flexibility without any negative effects for the fleet operation. This paper explores the available flexibility of large-scale electric bus fleets with a concept of centralized and unidirectional depot charging. An assessment of available positive and negative flexibility was conducted based on the data from two real bus depots in the city of Hamburg, Germany. The analysis shows the biggest flexibility potential was in the period from 16:00 h to 24:00 h, and the smallest one was in the periods from 08:00 h to 16:00 h, as well as from 02:00 h to 08:00 h. The paper also gives an overview of the possible markets for flexibility commercialization in Germany, which can provide an additional economic benefit for the fleet operators. A further analysis of the impact of parameters such as the timeline (working day or weekend), charging concept, ambient temperature, and electrical preconditioning provides an additional understanding of available flexibility. [ABSTRACT FROM AUTHOR]

Through the transformation that the electrical sector has been passing by, improvements in asset management and the guarantee of sustainable and quality services have become essential aspects for power companies. Thus, the digitalization of energy utilities presents itself as an important and crucial process. A concept that involves a variety of innovative trends is the digital twin. It consists of a 3D virtual replica of existing physical objects and real-time monitoring of certain measures. By developing a digital twin in the electrical power grid, a virtual replica of the network is obtained providing network virtual maps, 3D asset models, dynamic and real-time data of grid assets, and IoT sensing. All these data can feed a platform where AI-based models and advanced field operation technologies and solutions will be applied. With a Network Digital Twin©development, applications involving on-field activities can be improved through augmented reality (AR) and virtual reality (VR) to enhance workforce operations. This paper discusses the best practices for the development of a digital twin for the electrical power sector. These practices were found during the development of a project carried out by Enel Distribuição São Paulo, applying a living lab concept in the densest region of Brazil. The results of this paper present 3D images captured with specialized tools, and how they influence the workforce activities of human interface operation. Furthermore, financial and operational returns are presented through a cost–benefit analysis for each relevant aspect. [ABSTRACT FROM AUTHOR]

With the increase in capacitor voltage transformer (CVT) operation life, CVT impedance changes, and the short-time switching of overhead lines, it is very easy to cause a transient oscillation accident in which a CVT participates, reduce the insulation level of a CVT, and even induce regional power grid oscillation and easily cause capacitor breakdown, after long-term operation with defects. In this paper, the whole power network, including the generator, power grid, and consumer, is modeled, and the theoretical model of the CVT ferro-resonance connected grid is built. The frequency spectrum analysis, and the measurements of resonance bus voltage and line voltage, were carried out to find the design method of a fast saturation damper (FSD) and its voltage–current characteristics that affect the vibration, based on theory and practice; this paper puts forward effective measures to reduce the resonance effect of a CVT in operation, and avoid the oscillation of the line and even the regional power grid system. [ABSTRACT FROM AUTHOR]

The aim of this paper is to analyze the heat distribution in the high-current electrical contact under the action of an assumed current of 3000 A using mathematical modeling and simulation. Electrical contacts that carry high currents are an essential component of many electric devices. In transmission and distribution systems, the electrical contacts are of particular importance because they must withstand adverse weather conditions that decrease their effectiveness. Therefore, it is essential to detect any rise in temperature of the electrical contact to ensure efficient and reliable energy transmission. For this paper, simulations of the temperature field in direct electrical contact were carried out in ANSYS and discussed. During the simulation, a high-current electric contact was exposed to 3000 A current and the change of the adverse effects of contaminated contact layers affected temperature field. According to the results, electric contact in good condition (represented by impurity layer of lower resistivity) had a temperature of 80 °C lower than an electric contact that was worn out (represented by impurity layer of higher resistivity). The investigation of the resistivity of contaminated contact layers has led to the determination of permissible values for the power grid operators to maintain these types of devices when temperatures rise. [ABSTRACT FROM AUTHOR]

Identifying statistical trends for a wide range of practical power system applications, including sustainable energy forecasting, demand response, energy decomposition, and state estimation, is regarded as a significant task given the rapid expansion of power system measurements in terms of scale and complexity. In the last decade, deep learning has arisen as a new kind of artificial intelligence technique that expresses power grid datasets via an extensive hypothesis space, resulting in an outstanding performance in comparison with the majority of recent algorithms. This paper investigates the theoretical benefits of deep data representation in the study of power networks. We examine deep learning techniques described and deployed in a variety of supervised, unsupervised, and reinforcement learning scenarios. We explore different scenarios in which discriminative deep frameworks, such as Stacked Autoencoder networks and Convolution Networks, and generative deep architectures, including Deep Belief Networks and Variational Autoencoders, solve problems. This study's empirical and theoretical evaluation of deep learning encourages long-term studies on improving this modern category of methods to accomplish substantial advancements in the future of electrical systems. [ABSTRACT FROM AUTHOR]

The frequency stability of interconnected power systems becomes quite challenging when incorporating renewable energy sources (mostly wind power). Distributed model predictive control (DMPC) is an effective method to maintain stable grid frequency and realize power system load frequency control (LFC). This paper proposes a two-layer robust DMPC for the LFC of an interconnected power system. In the scheme, the wind power penetrating the power grid is largely affected by the environment condition, and it is taken as an uncertain disturbance to the power system. The two-layer robust DMPC consists of a nominal DMPC controller and an ancillary DMPC controller. The nominal DMPCs coordinate with each other in achieving the systemwide LFC objective, where the systemwide objective is a strict convex combination of the local LFC objectives. The nominal optimization problems are solved supposing the wind power fluctuation is zero. The ancillary DMPC generates the actual control signal for each generation unit based on signals which are transmitted from the nominal DMPC controller. The simulation on a four-area interconnected power system demonstrates the effectiveness of the proposed algorithm in alleviating the frequency deviation caused by varying the load and uncertain wind power fluctuation. [ABSTRACT FROM AUTHOR]