Search

Assessing the performance of active balancing methods poses a significant challenge due to the time required to replicate the equalization of various balancing techniques under identical initial cell conditions. Conventional circuit simulation methods, designed for high-frequency switching behavior, impose a considerable computational burden when applied to the long-term equalization of battery cells. To address this challenge, this paper presents an efficient performance evaluation method employing an average equivalent model of the equalizers. By representing the charge transfer mechanism inherent to the equalization process, the proposed approach is compatible with the most widely used switched-energy-tank equalizers. The validity of this method is confirmed through simulation and experimental results. In the case of four series-connected battery cells, our proposed approach can assess the performance of a three-hour equalization process in just one minute of execution time. The use cases in the paper highlight the practical feasibility of the AM in facilitating performance comparisons of SET-Es under various initial conditions. [ABSTRACT FROM AUTHOR]

The transformer is a fundamental piece of equipment for power grids. The analysis and optimization of their life-cycle costs are of great importance to reinforce the economic efficiency of electrical networks. This paper constructs a comprehensive transformer life-cycle cost (LCC) model by fusing life-cycle cost theory with relevant transformer expenditure. It proceeds to examine the life-cycle cost aspects of the transformer, delving into its cost dynamics under various influencing factors, establishing interconnections between these factors and analyzing the cost relationship. By employing MATLAB software (Matlab 2021a) along with the whale optimization algorithm (WOA) this paper optimizes the objective function. Through this, it establishes the LCC model for 20 power transformers, obtaining the optimal objective function curve and the maximum value for LCC optimization of the transformer. Unlike previous research, this study adds a detailed analysis of several factors that influence LCC. At the same time, it develops a more complete, scientific and rational LCC optimization model. An illustrative example validates the model and the superiority of the whale optimization algorithm. The algorithm not only shows its scientific basis and superiority, but also serves as a guiding mechanism for LCC management in transformer engineering practices. Ultimately, it emerges as a fundamental tool to improve the efficiency of power grid asset management. [ABSTRACT FROM AUTHOR]

This paper presents a simulation model for a system equipped with thermoelectric elements, considering the impact of independent thermal contact resistances on each side of the module. An analytical model was constructed, taking into account the asymmetry of thermal resistances between the generator/cooler and the respective heat source/heat sink. A comparative analysis of thermoelectric device operating indicators such as conducted heat, efficiency, and the electricity/cooling power produced was performed. The selection of electrical current in the circuit was analysed based on the maximization of power or efficiency. This paper discusses deviations from ideal conditions, specifically the absence of thermal resistance between the heat source/sink and the thermoelectric junction. The model accurately simulates the operating conditions of the thermoelectric system with a low computational cost. The results indicate that the total thermal resistance, rather than its location, predominantly affects the operation of the thermoelectric generator. However, in cooling operations, the influence of thermal resistance significantly depends on the cooling power demand and temperature. [ABSTRACT FROM AUTHOR]

A Hybrid Photovoltaic Thermal (PVT) system is one of the most emerging and energy-efficient technologies in the area of solar energy engineering. This review paper provides a comprehensive review of hybrid PVT systems in the context of the history of PVT, general classification, and parameter analysis. Several cell technologies with spectrum analysis are discussed to understand the application's ability and energy efficiency. Hybrid PVT concept, characteristics, and structure analysis is also discussed in this study. An extensive analysis on the classifications of hybrid PVT systems from the recent literature is also presented here. These literatures are identified based on several criteria. In order to provide a complete and energy-efficient technology, an innovative classification of the hybrid PVT system is proposed in this paper. This proposed classification is a combination and upgrade of various existing classifications mentioned in recent research studies. Parameters have a significant and unavoidable impact on the performance and efficiency of the hybrid PVT system. A brief analysis of different parameters and the optimization of the system is conducted after reviewing recent research articles. This analysis provides insights into the impact of parameter variations on the system. A novel parameter model comprising parametric and optimistic analyses is also presented in this paper. It provides a detailed parametric description that significantly affects the performance and efficiency of the hybrid PVT system. Finally, the assessment focuses on a critical analysis of the main challenges in adopting PVT technology and suggests ways to overcome these barriers. [ABSTRACT FROM AUTHOR]

The sustainable implementation of resources and the transition to low-carbon construction is on the world's daily agenda. This paper describes the development of criteria for the efficient management of material resources in low-carbon construction. Net income, gross profit, balance sheets, and equity are proposed as indicators that serve as criteria for assessing the efficient use of resources. Nonlinear regression models were the methodological basis for the establishment of cause-and-effect relationships of the volume of construction of transport structures. It was established that since construction companies do not purchase materials for storage, the cost of materials for use in low-carbon technological construction work is directly proportional to the cost of construction. The volume of production in the construction industry is determined by construction costs. More efficient use of low-carbon materials reduces cost and construction waste. In this paper, we have established the relationship between the indicator of efficiency for the functioning of the construction enterprises in Ukraine and the use of low-carbon materials for the construction of transport structures. The practical value of the obtained results for low-carbon construction management lies in proving the relationship between the performance indicators of the construction enterprise (net profit, gross profit, output volume, balance sheets, and equity capital) and the use of low-carbon material resources. Our results form the basis for future research into the use of a cost-based model for low-carbon economy transition in municipalities and regions. [ABSTRACT FROM AUTHOR]

The essential role of Information and Communication Technologies (ICT) in modern electricity grids makes it necessary to consider them when evaluating the scalability and replicability capabilities of smart grid systems. This paper proposes a novel step-by-step methodology to quantitatively perform an ICT scalability and replicability analysis (SRA) in a smart grid context. The methodology is validated and exemplified by applying it to two real case studies that are demonstrated in the EU-funded RESPONSE project and comprise solutions relying on different communication technologies. The results of the proposed methodology are summarised through ICT scalability and replicability maps, which are introduced in this paper as a quick way of obtaining an overview of the scalability and replicability capabilities of an ICT system and as an efficient way of estimating the feasibility of scenarios not covered in the SRA. [ABSTRACT FROM AUTHOR]

ANNs have become a cornerstone in efficiently managing building energy management systems (BEMSs) as they offer advanced capabilities for prediction, control, and optimization. This paper offers a detailed review of recent, significant research in this domain, highlighting the use of ANNs in optimizing key energy systems, such as HVAC systems, domestic water heating (DHW) systems, lighting systems (LSs), and renewable energy sources (RESs), which have been integrated into the building environment. After illustrating the conceptual background of the most common ANN architectures for controlling BEMSs, the current work dives deep into relative research applications, thereby exhibiting their methodology and outcomes. By summarizing the numerous impactful applications during 2015–2023, this paper categorizes the predominant ANN-based techniques according to their methodological approach, specific energy equipment, and experimental setups. Grounded in the different perspectives that the integrated studies illustrate, the primary focus of this paper is to evaluate the overall status of ANN-driven control in building energy management, as well as to offer a deep understanding of the prevailing trends at the building level. Leveraging detailed graphical depictions and comparisons between different concepts, future directions, and fruitful conclusions are drawn, and the upcoming innovations of ANN-based control frameworks in BEMSs are highlighted. [ABSTRACT FROM AUTHOR]

Despite their key role in integrated waste management, direct (incineration) and indirect (gasification/pyrolysis) waste combustion processes are still opposed by some of the general public due to the past emission levels of air pollutants. In fact, although the release of air pollutants (especially dioxin) to the atmosphere from waste combustion processes has gradually decreased over the years, thanks to the introduction of stricter regulations and more advanced removal technologies, there is still an unsolved problem regarding the public acceptance of waste-to-energy facilities. The aim of this paper is to provide an overview of the state-of-the-art air pollution control (APC) technologies used in waste combustion facilities. Air pollution control technologies are designed to reduce or eliminate the emissions of harmful pollutants into the atmosphere. These technologies are important for safeguarding public health, protecting ecosystems, complying with regulations, and promoting a more sustainable and resilient future for both local and global communities. This paper will highlight the complexity behind emission control and the efforts made by this sector over the years. This paper will also propose suggested configurations based on the interactions/complementarity between different APC technologies and recent findings to improve their performance. [ABSTRACT FROM AUTHOR]

Economic Dispatch Problems (EDP) refer to the process of determining the power output of generation units such that the electricity demand of the system is satisfied at a minimum cost while technical and operational constraints of the system are satisfied. This procedure is vital in the efficient energy management of electricity networks since it can ensure the reliable and efficient operation of power systems. As power systems transition from conventional to modern ones, new components and constraints are introduced to power systems, making the EDP increasingly complex. This highlights the importance of developing advanced optimization techniques that can efficiently handle these new complexities to ensure optimal operation and cost-effectiveness of power systems. This review paper provides a comprehensive exploration of the EDP, encompassing its mathematical formulation and the examination of commonly used problem formulation techniques, including single and multi-objective optimization methods. It also explores the progression of paradigms in economic dispatch, tracing the journey from traditional methods to contemporary strategies in power system management. The paper categorizes the commonly utilized techniques for solving EDP into four groups: conventional mathematical approaches, uncertainty modelling methods, artificial intelligence-driven techniques, and hybrid algorithms. It identifies critical research gaps, a predominant focus on single-case studies that limit the generalizability of findings, and the challenge of comparing research due to arbitrary system choices and formulation variations. The present paper calls for the implementation of standardized evaluation criteria and the inclusion of a diverse range of case studies to enhance the practicality of optimization techniques in the field. [ABSTRACT FROM AUTHOR]

The paper presents a proposed system that supplies a 400 Hz single-phase onboard grid from the DC onboard bus. This system enables independent compensation of reactive power in the AC grid. Independent control of active and reactive power flow requires the decomposition of current in the grid into active and reactive components. Independent control of active and reactive power requires the use of synchronizers that operate in the dq frame system. If synchronization is performed with a single-phase grid, the transformation of dq requires the virtual quadrature signals. Standard quadrature signal generation systems use a second-order generalized integrator. To improve the dynamics of the system, the paper proposes a new quadrature generator that operates on the basis of trigonometric calculations instead of a second-order integration system. The developed system was implemented in a proportional-resonant current control system. Tests carried out in steady state and in dynamic states related to typical grid disturbances proved significantly better dynamic properties than those of a standard integrator-based system. [ABSTRACT FROM AUTHOR]

The transportation sector remains a major contributor to greenhouse gas emissions. The understanding of energy-efficient driving behaviors and utilization of energy-efficient driving strategies are essential to reduce vehicles' fuel consumption. However, there is no comprehensive investigation into energy-efficient driving behaviors and strategies. Furthermore, many state-of-the-art AI models have been applied for the analysis of eco-friendly driving styles, but no overview is available. To fill the gap, this paper conducts a thorough literature review on ecological driving behaviors and styles, and analyzes the driving factors influencing energy consumption and state-of-the-art methodologies. With a thorough scoping review process, thirty-seven articles with full text were assessed, and the methodological and related data are compared. The results show that the factors that impact driving behaviors can be summarized into eleven features including speed, acceleration, deceleration, pedal, steering, gear, engine, distance, weather, traffic signal, and road parameters. This paper finds that supervised/unsupervised learning algorithms and reinforcement learning frameworks have been popularly used to model the vehicle's energy consumption with multi-dimensional data. Furthermore, the literature shows that the driving data are collected from either simulators or real-world experiments, and the real-world data are mainly stored and transmitted by meters, controller area networks, onboard data services, smartphones, and additional sensors installed in the vehicle. Based on driving behavior factors, driver characteristics, and safety rules, this paper recommends nine energy-efficient driving styles including four guidelines for the drivers' selection and adjustment of the vehicle parameters, three recommendations for the energy-efficient driving styles in different driving scenarios, and two subjective suggestions for different types of drivers and employers. [ABSTRACT FROM AUTHOR]

The electrification of road transport is developing dynamically around the world. Many automotive companies are introducing electric vehicles to the market, and their popularity is constantly growing. The increasing popularity of electric vehicles is caused by individual countries' governments encouraging people to switch to electric vehicles and their lower operating costs. In 2022, the number of electric vehicles in China will exceed 10 million. Europe and the USA rank second and third in global electric car stock, respectively. The number of available electric vehicle models is constantly growing, remaining approximately 2.5 times smaller than the case of vehicles with an internal combustion engine. Among others, a significant limitation to the popularity of electric cars is users' fear of range and the density of the charging infrastructure network. This paper presents the objectives regarding public areas and charging stations around the European Union's comprehensive and core transport network. It is worth noting that the vehicle and charging point's charging connectors vary depending on the geographical region. Therefore, the currently used charging connectors for different regions are presented. Charging time depends significantly on the charging current, the power of the charging point, and the devices installed in the vehicle. The paper analyzes the limitations of charging power resulting from the onboard charger's power and the charging point's power. It presents the charging time of selected electric vehicles. The second aspect that is also the subject of user concerns and discussed in this article is issues related to the safety of electric vehicles. General safety indicators of such vehicles based on Euro-NCAP tests are characterized. Attention was also paid to more detailed problems related to active and passive safety and functional safety analyses. The issue of the fire hazard of electric vehicles was discussed together with modern experiences regarding post-accident procedures in the event of fires. [ABSTRACT FROM AUTHOR]

Internal arc testing is still a controversial topic in the instrument transformer world. The main reason for that is the fact that even a fully successful test guarantees only a certain degree of transformer safety. Furthermore, the test does not cover a plethora of operational fault scenarios and has requirements which are not defined clearly enough. In addition, there are very few data available in the literature on the internal arc performance of alternative, biodegradable dielectric liquids. Some liquids (such as natural and synthetic esters) do inherently come with higher flash and fire points compared to conventional mineral oil, but there is insufficient test experience to corroborate the influence this high fire point has on the actual operation. Specifically, to the authors' knowledge, internal arc tests on instrument transformers were never performed with biodegradable dielectric liquids, making the contributions of this paper a true world premiere. In short, this paper is intended to augment the existing standards, thus providing additional insight into how to test internal arc performance, what to look out for and what level of performance to expect, which is of broad interest to researchers, utility engineers and public alike. [ABSTRACT FROM AUTHOR]

Metallic electrodes are widely used in many applications, the analysis of their frequency-domain behavior is an important subject, particularly in applications related to earthing/grounding systems, from dc up into the MHz range. In this paper, a numerical evaluation of the frequency-dependent complex impedance of the hemispherical ground electrode is implemented. A closed-form solution for non-zero frequencies is still a difficult task to achieve as evidenced in a previous paper dedicated to the subject and, therefore, numerical approaches should be an alternative option. The aim of this article is to present a solution based on a numerical method using finite element analysis. In typical commercial FE tools, electric currents exhibit azimuthal orientation and, as such, the magnetic field has a null azimuthal component but non-null axial and radial components. On the contrary, a dual problem is considered in this work, with a purely azimuthal magnetic field. To overcome the difficulty of directly using a commercial FE tool, a novel formulation is developed. An innovative 2D formulation, the ι-form, is developed as a modification of the H-formulation applied to axisymmetric magnetic field problems. The results are validated using a classical 3D H-formulation; comparisons showed very good agreement. The electrode complex impedance is analyzed considering two different cases. Firstly, the grounding system is constituted by a hemispherical electrode surrounded by a remote concentric electrode; in the second case, the grounding system is constituted by two identical thin hemispherical electrodes. Computed results are presented and discussed, showing how the grounding impedance depends on the frequency and, also, on the radius of the remote concentric electrode (first case) or on the distance between the two hemispherical electrodes (second case). [ABSTRACT FROM AUTHOR]

This paper investigates the deterioration of, and the abnormal temperature rise in, the GFRP core rod material of compact V-string composite insulators subjected to prolonged alternating flexural loading under wind-induced stresses. The axial stress on the GFRP (Glass Fiber Reinforced Plastic) core rod, resulting from transverse wind loads, is a focal point of examination. By establishing a stress model and damage model, the paper simulates and computes the evolution of damage in the outer arc material of composite insulator core rods subjected to alternating flexural loads. Additionally, a multi-factor coupled aging platform is set up, integrating humidity, heat, and mechanical stress, to simulate the crazing deterioration process of composite insulators under alternating flexural loads. Experimental results reveal that during 400,000 alternating load cycles, the core rod underwent stages of surface damage, damage increasing, fatigue embrittlement, matrix hydrolysis, and fiber fracture. Simultaneously, the silicone rubber sheath on the outer side of the composite insulator's bending arc develops cracks over aging time, creating pathways for moisture ingress into the interface and core rod. The dielectric constant and dielectric loss factor of the aging region of the core rod increase to varying degrees compared to the non-aging part. Moreover, the degree of abnormal heating of the samples intensifies with the duration of aging experiments. These findings underscore the significance of understanding the aging and decay-like fracture process of compact line V-string composite insulators. They provide crucial insights for future research aimed at enhancing the material properties of composite insulator core rods. [ABSTRACT FROM AUTHOR]

In recent years, several research works have addressed and developed the phase-locked loop (PLL) in single-phase grid-connected converters with different structures and properties. Each has merits and demerits, such as a complex structure, high computational burden, and slow transient response. This paper aims to comprehensively review advanced single-phase PLLs based on transport delay operators to realize signal orthogonality. A deep insight into the PLLs' small-signal modeling, main characteristics, stability analysis, and loop filter design are provided in this paper. The main advantages and drawbacks are explained for each type of PLL in terms of different performance indexes, such as settling time, estimation error, and ripples in the estimated grid information. This paper also aims to provide optimal tuning and design of the loop filter gains from the large-signal model point of view, including all the nonlinearities, adopting the stochastic optimization method. All simulations are implemented using the MATLAB/Simulink 2018b environment to validate all theoretical analyses of this paper. The sampling and nominal frequencies are set to be 100 kHz and 50 Hz throughout all the simulation studies. [ABSTRACT FROM AUTHOR]

This paper proposes a simple design scheme for a modular NPC inverter using thermal RC network analysis. The proposed design process is an efficient and straightforward approach to designing the heatsink for a 300 kW modular neutral-point-clamped inverter. The heatsink design plays a crucial role in achieving high power density of a power converter because the weight and size of the heatsink are primarily influenced by its type. The structure and dimensions of the heatsink are mainly determined based on the generated heat by losses of the power semiconductor switches. In this paper, a thermal RC network model was established using parameters from the power switch module and was applied to the simulation of the power converter. The thermal losses of the power semiconductor switches were calculated via this process, and the heatsink was designed according to the calculated thermal losses. The proposed design scheme was analyzed and compared with the thermal fluid dynamic model. To validate the feasibility of the proposed design process, The simulation results were compared with experimental results. [ABSTRACT FROM AUTHOR]

The reduction in GHG emissions has become one of the most important objectives in Europe. One of these clean technologies in the quest for large-scale decarbonisation is the blending of hydrogen and natural gas (H2NG). The significance of this article lies in conducting a technical–economic analysis that relies on simulating annual consumption patterns. This study focuses on the utilization of H2NG at different proportions within a distribution network in Bucharest, Romania's largest city. The paper is a fallow up of another paper and presents a case study for the injection through all four entry points in the city of different percentages of hydrogen and the dynamic of the mix through the gas distribution network. The study found that the variation in H2 in the network is high and depends on the entry point levels and consumption. An economic analysis was conducted on seasonal real consumption, which confirmed the investment's profitability. [ABSTRACT FROM AUTHOR]

The AC battery utilizing second-life time batteries has gained great interest currently with the advantages of both power solutions and economic benefits. In this system, the power converters play a crucial role in the stable and effective operation of the system. This paper focused on the AC/DC stage with the chosen topology being the interleaved full bridge (IFB) converter due to its flexibility and the ability to increase the power rate of the system. For the sake of high-performance operation, various pulse width modulation (PWM) methods for this converter are analyzed. First, based on the theory of the traditional PWM methods for a full bridge inverter in combination with the interleaved technique, this paper proposed three interleaved PWM methods for the IFB converter. Secondly, the proposed methods are theoretically compared in terms of the output current, common-mode voltage, and power losses. Finally, the evaluation is carried out by both the simulation and the experimental prototype, in which the results are in good agreement with the theoretical analysis. [ABSTRACT FROM AUTHOR]

The interaction of water waves with floating bodies can be modeled with linear potential flow theory and numerically solved with the boundary element method (BEM). This method requires the construction of dense matrices and the resolution of the corresponding linear systems. The cost of this method in terms of time and memory grows at least quadratically with the size of the mesh, and the resolution of large problems (such as large farms of wave energy converters) can, thus, be very costly. Approximating some blocks of the matrix with data-sparse matrices can limit this cost. While matrix compression with low-rank blocks has become a standard tool in the larger BEM community, the present paper provides its first application (to our knowledge) to linear potential flows. In this paper, we assess how efficiently low-rank blocks can approximate interaction matrices between distant meshes when using the Green function of linear potential flow. Due to the complexity of this Green function, a theoretical study is difficult, and numerical experiments are used to test the approximation method. Typical results on large arrays of floating bodies show that 99% of the accuracy can be reached with 10% of the coefficients of the matrix. [ABSTRACT FROM AUTHOR]

To better address and improve the issues related to DC power quality, this paper proposes an identification method tailored for DC power quality disturbances. First, it explores the underlying mechanisms and waveform characteristics of common DC power disturbances. By integrating the results of time–frequency analysis obtained through the S-transform, five distinct features are designed and extracted to serve as classification indicators. The SABO algorithm is subsequently employed to optimize the BP neural network, assisting in determining the optimal input weights and hidden layer thresholds. This optimization technique helps prevent the network from becoming stuck in local minima, thereby enhancing its robustness and generalization capabilities. This paper presents a simulation system for AC/DC power systems to conduct experimental verification. The system simulates various DC power quality issues and monitors abnormal waveforms. According to the designated classification index, the features of simulated disturbance signals are extracted. The SABO-BP classification prediction model is then used to automatically classify and identify the samples. The experimental results demonstrate high accuracy in classification and identification using the proposed method. In comparison to the BP neural network method, the SABO-BP method demonstrates an 8.207% improvement in accurately identifying disturbance signals. It is capable of accurately identifying direct current power quality signals, thereby assisting in the evaluation and control of power quality issues. [ABSTRACT FROM AUTHOR]

This paper's research question is to evaluate the potential impact of large numbers of battery electric vehicles (BEVs) on the future electric grid, and whether the flexibility of BEV charging can induce enough system benefits to remunerate BEV users for the change in their recharging pattern. The considered scenario refers to the Italian situation and what might occur through the year 2040, where a share of BEV stock of 40% can be foreseen, as well as significant increases in PV and wind generation. Although this study is focused on Italy, its results are applicable, with minor differences, to several EU countries. This paper first shows that the future impact of increasing penetration of BEVs appears to be compatible with the expected growth of generation from renewable energy sources (RES) and the corresponding reduction in fossil fuel-based generation. It also gives an estimate of the CO2 emission reduction resulting from these changes, considering an unmanaged BEV charge profile and two different managed profiles that shift the car's charging period to hours of the day when they have no negative impact on the grid and maximize the utilization of RES. Finally, it shows an evaluation of the economic benefits of displacing private car charging ranging from 4 to 10 cEUR/kWh, which could be used as tariff incentives to stimulate this displacing in recharging time. [ABSTRACT FROM AUTHOR]

To enhance the accuracy of theft detection for electricity consumers, this paper introduces a novel strategy based on the fusion of the dual-time feature and deep learning methods. Initially, considering electricity-consumption features at dual temporal scales, the paper employs temporal convolutional networks (TCN) with a long short-term memory (LSTM) multi-level feature extraction module (LSTM-TCN) and deep convolutional neural network (DCNN) to parallelly extract features at these scales. Subsequently, the extracted features are coupled and input into a fully connected (FC) layer for classification, enabling the precise detection of theft users. To validate the method's effectiveness, real electricity-consumption data from the State Grid Corporation of China (SGCC) is used for testing. The experimental results demonstrate that the proposed method achieves a remarkable detection accuracy of up to 94.7% during testing, showcasing excellent performance across various evaluation metrics. Specifically, it attained values of 0.932, 0.964, 0.948, and 0.986 for precision, recall, F1 score, and AUC, respectively. Additionally, the paper conducts a comparative analysis with mainstream theft identification approaches. In the comparison of training processes, the proposed method exhibits significant advantages in terms of identification accuracy and fitting degree. Moreover, with adjustments to the training set proportions, the proposed method shows minimal impact, indicating robustness. [ABSTRACT FROM AUTHOR]

With the continuous development of large-scale wind and photovoltaic power worldwide, the net load fluctuation of systems is increasing, thereby imposing higher demands for power supply assurance and new energy consumption capacity within emerging power systems. It is imperative to establish a quantifiable and efficient model for planning new power systems, to propose an analytical approach for determining optimal evolutionary paths, and to advance research on flexible resource planning across wide areas. In this paper, based on the simplified operating characteristics of multi-type flexible resources, a source-grid-load-storage collaborative planning and evolution analysis framework is established. Secondly, the lowest total cost of the whole life cycle of the system is taken as the optimization goal, the multiple flexible resource investment decisions and production operation constraints of various flexible resources on all sides of the system are considered, and the source-grid-load-storage planning model is established. Then, through the investment decision-making strategy setting of the system in different planning level years, the evolutionary path analysis method of the whole life cycle economy and weighted environmental protection benefit of the system is given. Finally, by taking the sending-end power grid in Gansu Province as an example, a case study is carried out. Calculations of new energy, key channels within the province, energy storage capacity, and load-side response capacity requirements for 2025, 2030, and 2060 are optimized. Based on the above analysis, the optimal evolution path of the power grid is proposed. When considering the weighted benefits of economy and environmental protection, the greater the weight of environmental protection benefits, the greater the possibility of choosing a radical scheme. The model and method proposed in this paper can provide technical reference for the future development planning and evolution analysis of new power systems. [ABSTRACT FROM AUTHOR]

The objective of this study is to analyze the economic viability of municipal household solid waste (organic matter + paper) for the production of gas, coke and biofuel through the pyrolysis and distillation process. The waste was collected in the city of Belém do Pará-Brazil and pretreated at the Federal University of Pará. The analyzed fraction (organic matter + paper) was subjected to the pretreatment of drying, crushing, and sieving and was subsequently subjected to proximate characterization and, finally, pyrolysis of the organic fraction (organic matter + paper) in a fixed bed reactor. Initially, it was necessary to review the literature, and with the yields obtained by pyrolysis of the fraction, economic feasibility analyses were carried out. The economic indicators for evaluating the most viable pyrolysis process were basic payback, discounted payback, net present value, internal rate of return, and profitability index, which are all financial metrics commonly used in investment analysis and decision making. These metrics provide valuable insights into the financial viability and attractiveness of investment projects. They are essential tools for assessing the feasibility and profitability of various ventures, helping decision-makers make informed choices in allocating resources. The analysis of the indicators showed the economic viability considering an analysis horizon of 10 years of materials based on organic material and paper. The breakeven point obtained was USD 0.96/dm3 and the minimum biofuel sales price found in this project was USD 1.30/dm3. The sensitivity research found that material costs (organic matter + paper), bio-oil yield, total project investment and electricity, respectively, are the variables that most affect the minimum biofuel sales price. [ABSTRACT FROM AUTHOR]

The modern world is moving towards a zero-emission economy; therefore, various actions are being taken to reduce the share of fossil fuels in energy production. The article examines the potential for the continued expansion of photovoltaic farms, with a special emphasis on farms utilising east–west panel orientation. The east–west orientation is an innovative solution with many advantages over the traditional north–south arrangement. The paper also makes a detailed assessment of the photovoltaic farm environment by applying two analyses based on the following factors: Political, Economic, Social, and Technological (PEST) and Demographic, Economic, Environmental, Political, Legal, Informational, Social, and Technological (DEEPLIST) factors. This is followed by an insightful, comprehensive review of the most important factors that contribute to the efficiency of photovoltaic installations, namely site conditions, existing infrastructure, and ability to connect to the electricity grid. The paper also devotes space to an analysis of daily energy price changes that affect the economic efficiency of the installation and discusses the potential for energy storage in the context of photovoltaic farms. The development of photovoltaics also requires investing in energy storage. All discussed issues fall within the scope of photovoltaic farm development and optimal use of energy resources. [ABSTRACT FROM AUTHOR]

Short-term wind power forecasting has difficult problems due to the very large variety of speeds of the wind, which is a key factor in producing energy. From the point of view of the whole country, an important problem is predicting the total impact of wind power's contribution to the country's energy demands for succeeding days. Accordingly, efficient planning of classical power sources may be made for the next day. This paper will investigate this direction of research. Based on historical data, a few neural network predictors will be combined into an ensemble that is responsible for the next day's wind power generation. The problem is difficult since wind farms are distributed in large regions of the country, where different wind conditions exist. Moreover, the information on wind speed is not available. This paper proposes and compares different structures of an ensemble combined from three neural networks. The best accuracy has been obtained with the application of an MLP combiner. The results of numerical experiments have shown a significant reduction in prediction errors compared to the naïve approach. The improvement in results with this naïve solution is close to two in the one-day-ahead prediction task. [ABSTRACT FROM AUTHOR]

This paper reports on the linear colorimetric and electrochromic (EC) characteristics of electrodeposited polyaniline (PANI) films. This paper also investigates the infrared EC properties of acid-doped PANI films. The electrochemical polymerization method was employed to create a porous and thin PANI film layer onto PET-ITO substrates. This layer was capped with WO3 film to create a gel electrolyte sandwich structure that demonstrates the compatibility of PANI films with cathodic WO3 films in full devices. The electrodeposition of the film was fabricated by applying different voltages and time, with the optimal film quality achieved with the 1.7 V voltage and a 20 min deposition period. The surface morphology, optical performance, electrochemical behavior, and molecular structure evolution are comprehensively studied in this work. The linear colorimetric behaviors and the corresponding significant changes in the structure in Raman spectra build direct strong quantitative relations in EC polymers. The well-defined oxidation and reduction peaks observed in the cyclic voltammetry indicate the ion-diffusion dominant process in the electrochromism of PANI. Significant transitions between the benzene and quinone phases in the Raman spectra are found in the bleached and colored states of polymers. This study enhances the understanding of PANI film structure and electrochemical and associated optical properties, providing more insights into the dual-function EC charge storage polymers and other energy-related functional materials. [ABSTRACT FROM AUTHOR]

It is a critical issue to allocate redundancy to critical smart grid infrastructure for disaster recovery planning. In this study, a framework to combine statistical prediction methods and optimization models for the optimal redundancy allocation problem is presented. First, statistical simulation methods to identify critical nodes of very large-scale smart grid infrastructure based on the topological features of embedding networks are developed, and then a linear integer programming model based on generalized assignment problem (GAP) for the redundancy allocation of critical nodes in smart grid infrastructure is presented. This paper aims to contribute to the field by employing a general redundancy allocation problem (GRAP) model from high-order nonlinear to linear model transformation. The model is specifically implemented in the context of smart grid infrastructure. The innovative linear integer programming model proposed in this paper capitalizes on the logarithmic multiplication property to reframe the inherently nonlinear resource allocation problem (RAP) into a linearly separable function. This reformulation markedly streamlines the problem, enhancing its suitability for efficient and effective solutions. The findings demonstrate that the combined approach of statistical simulation and optimization effectively addresses the size limitations inherent in a sole optimization approach. Notably, the optimal solutions for redundancy allocation in large grid systems highlight that the cost of redundancy is only a fraction of the economic losses incurred due to weather-related outages. [ABSTRACT FROM AUTHOR]

Drying processes are among the most energy-intensive industrial processes. There is a need for development of the efficient methods needed for estimating, measuring, and reducing energy use. Different machine learning algorithms might provide some of the answers to these issues in a faster and less costly way, without the need for time-consuming and expensive experiments done at different scales of the dryers. The aim of this paper was to provide a comprehensive overview of machine learning applications for addressing energy-related challenges by exploration of different energy types and energy reduction opportunities. Also, the analysis of the applied algorithms, their specific applications and a critical evaluation of the obtained results are provided. The paper is based on the necessity of the improvements in energy use needed for drying related on the existing data. The overview of the ways for such achievements, and a general classification of machine learning algorithm are the background of the paper. The methods used are the machine learning techniques employed in different energy-related issues for drying processes. The paper focuses on the applications of artificial neural networks and other machine learning algorithms and models for different energy-related issues, including different energy types applications, challenges associated with energy consumption, and opportunities for energy reduction. Not only the applied algorithms, but also their specific applications, and the statistical analysis of the obtained results are also overviewed. Finally, a critical evaluation of the findings highlighting the potentials of machine learning algorithms in addressing energy-related challenges (such as estimation of energy consumption, opportunities for energy reduction, and use of different energy sources) is provided. The presented analysis underscored the effectiveness of machine learning applications for these purposes. [ABSTRACT FROM AUTHOR]

This paper deals with an electrothermal model of a thermoelectric converter dedicated to performing simulations of coupled thermal and electrical phenomena taking place in harvesting processes. The proposed model is used to estimate the electrical energy gain from waste heat that would be sufficient to supply electronic circuits, in particular autonomous battery-less nodes of wireless sensor networks (WSN) and Internet of Things (IoT) devices. The developed model is not limited to low-power electronic solutions such as WSN or IoT; it can also be scaled up and applied to simulations of considerably higher thermal power conversion. In this paper, a few practical case studies are presented that show the feasibility and suitability of the proposed model for complex simultaneous simulation processes in both the electrical and thermal domains. The first example deals with a combined simulation of the electrothermal model of a thermoelectric generator (TEG) and an electronic harvester circuit based on Analog Devices' power management integrated circuit LTC3108. The second example relates to the thermalization effect in heat sink-less harvesting applications that could be mitigated by a pulse mode operation. The unique contribution and advancement of the model is the hierarchical structure for scaling up and down, incorporating the complexity of the Seebeck effect, the Joule effect, heat conduction, as well as the temperature dependence of the used materials and the thermoelectric pellet geometries. The simulations can be performed in steady as well as transient states under changing electrical loads and temperatures. [ABSTRACT FROM AUTHOR]

With the continuous promotion of digital transformation in the field of power transformation, the diversification of application scenarios, and the scale of pilot construction, the real-time, concurrency, and security requirements for data fusion and application support of the power monitoring system, management information system, and other business platforms are getting higher and higher, and this paper puts forward a high concurrency and availability "cloud-side-end collaboration" based on edge computing. This paper proposes a high concurrency and availability "cloud, edge and end collaboration" architecture based on edge computing for substation operation support systems. First, this paper summarizes the development status of domestic substation operation support systems and analyzes the advantages and disadvantages of various technical architectures. Then, a "cloud-side-end cooperative" substation operation support system architecture with "high real-time, high concurrency, high security and high stability" is proposed, which focuses on remote inspection, remote operation, and remote safety control of substation businesses from the perspective of engineering applications. It realizes transparent monitoring of equipment operation, unified management of operation data, and integration of production command and decision-making; solves the problems of dispersed coexistence of multiple systems for dispatching, monitoring, analysis, management, and other businesses, switching between multiple systems, and insufficient real-time and stability of the system; and controls the risks of the grid, reduces the potential safety hazards, and solves the contradiction between the continuous growth of the grid equipment and the shortage of production personnel. The results of engineering application examples show that the proposed architecture compared with the existing system architecture has greater advantages and can meet the requirements of large-scale access to the substation, with feasible popularization and application. [ABSTRACT FROM AUTHOR]

Increasing energy security is a crucial component of achieving the Sustainable Development Goals (SDGs). Three main factors influence energy security: (1) the efficiency of resource use in energy production, (2) the extent of energy losses, and (3) the use of new energy sources. Novel food products can impact these factors, and this paper explores whether they are being studied in the context of reducing energy consumption. Specifically, we investigate the role of technical progress and know-how in the creation and development of novel food products and whether novel methods of food production using artificial intelligence aim to reduce energy expenditures while improving product quality, variety, and the use of new energy sources. This paper seeks to examine the impact determinants of novel foods on energy security, considering economic, technological, social, and environmental aspects of knowledge about new food. To implement the study, the relevant international literature published in the past ten years have been reviewed and methods of modeling, visualization, and descriptive statistics applied. The review is structured into three sections: the first section presents ways to save energy and other resources in the food production chain through the intensive use of artificial intelligence tools; the second section presents the development of novel food products; and the last section presents marketing challenges for novel foods. The findings show that the topic addressed by this paper is currently critical, with many authorities, research centers, food producers, and energy producers interested. However, the research problem remains open, as a systematic review of secondary sources revealed little knowledge of the topic under study, and each author's study presents a new solution. The conclusion is that utilizing new foods and innovative production techniques that require less energy not only enhances production diversity but also improves its quality. [ABSTRACT FROM AUTHOR]

In the case of new investment in RES technology, there are two issues related to efficiency assessment. The first one is how to join technical, financial and economic efficiency assessments in one. An investment feasibility study is usually conducted through a financial analysis to obtain the internal rate of return and the net present value. However, a new RES investment is typically financially unprofitable unless the environmental and social aspects are included. The second one is a lack of required financial data. The new RES investment is often innovative and neither the owner nor other entities have financial data on the operating costs and expenditure for the last periods. Therefore, in this paper, we proposed two methods of efficiency assessment. The first one is based on the avoided costs theory. Furthermore, the second one belongs to heuristic methods and is based on the experts' assessment of different kinds of parameters. The purpose of this study is to assess the efficiency of the pilot project of VPPs using two recommended methods. This paper emphasizes the advantages and disadvantages of each method. The actual technical and financial data for the period of six months from the pilot study were calculated. [ABSTRACT FROM AUTHOR]

Increased effectiveness of methane drainage from sealed post-mining goaves in hard coal mines contributes to reduced methane emission from goaves into the mine ventilation system. This paper focuses on issues concerning the assessment of the additional amount of methane released from the goaf into mine workings during periods of atmospheric pressure drops, which can be captured with a methane drainage system. Thanks to the solutions presented in the paper, it is possible to control the efficiency of the goaf drainage system, which in turn leads to the reduction of methane emission from the mine ventilation air into Earth's atmosphere. These solutions are of great added value for both the environment and coal mines as they reduce the costs arising from greenhouse gas emissions that are incurred by mining companies, increasing the efficiency of methane capture and its use in gas engines or district heating systems. The paper uses relationships relating to the influence of atmospheric pressure changes on the process of gas release from the goaf according to the hysteresis loop of methane release during atmospheric pressure changes, which was developed based on conducted research. The analysis and conclusions presented in this paper may facilitate the development of strategies aimed at reducing methane emissions from a mine's ventilated air into Earth's atmosphere. [ABSTRACT FROM AUTHOR]

Electrical drive systems are commonly applied for the mechanisms of precise movement, where having a high-quality position and high-quality speed control is especially valuable. Very often, the mechanical part of these systems reveals resonant properties that are related to the limited stiffness of the interconnection between subsequent parts of the mechanism. In most cases, this sort of system may be described as a model of several linked masses. If only the structure of the mechanical part is known and the corresponding parameters are constant and identified, the demanded control quality may be obtained using a properly tuned ADRC or PID controller equipped with appropriate anti-resonance filtration. However, if the parameters of the mechanical part are variant, adaptive control may be considered as a solution. In this paper, artificial neural network (ANN) is considered to be a speed controller and its training method assures adaptation to the unknown mechanical parameters. The paper is particularly focused on a three-mass system, which possesses, due to its structure, two resonant frequencies. The unique property of the analyzed system is the application of drive units at both ends of the system, so that the controller has the ability to influence the resonant system from both sides. The coordination of the drive unit is performed by the aforementioned ANN, from which two outputs affect the drive units independently. The derivation of the mathematical model is followed by its implementation in a computer simulation and finally the evaluation in a dedicated laboratory setup, the construction of which is also presented in the paper. [ABSTRACT FROM AUTHOR]

As the main source of energy supply and carbon emissions, the oil and gas industry has entered the comprehensive low-carbon transition stage driven by various factors. Since different oil companies possess distinct understandings of transition paths, the effect of low carbon transition varies greatly. Obviously, it is necessary to evaluate the performance of low-carbon transitions within the oil and gas industry. Therefore, in this paper, 10 major international oil companies are taken as examples, and a super-efficiency slack-based measurement (super-SBM) model is applied in the present study to analyze the efficiency of low-carbon transitions. Furthermore, the logarithmic mean Divisia index (LMDI) is used to decompose the driving factors of carbon emissions and analyze their impact on the low-carbon transition of international oil companies. The obtained results reveal that although major oil companies have taken different measures in low-carbon transition and achieved a year-on-year reduction in carbon emissions, from the perspective of the efficiency of the entire production and operation process, these oil companies are inefficient in carbon emissions and need to adopt more effective low-carbon transition strategies; Moreover, after the further decomposition of the carbon emission driving factors of the 10 companies, it is found that improving the energy consumption intensity and development level of oil companies can effectively improve the effect of low-carbon transition of international oil companies. Drawing on the above findings, this paper puts forward suggestions for the low-carbon transition of energy companies, thus providing theoretical support and guidance for energy companies in different countries to implement low-carbon transition and green development strategies. [ABSTRACT FROM AUTHOR]

To achieve a more ecologically friendly energy transition by the year 2050 under the European "green" accord, hydrogen has recently gained significant scientific interest due to its efficiency as an energy carrier. This paper focuses on large-scale hydrogen production systems based on marine renewable-energy-based wind turbines and tidal turbines. The paper reviews the different technologies of hydrogen production using water electrolyzers, energy storage unit base hydrogen vectors, and fuel cells (FC). The focus is on large-scale hydrogen production systems using marine renewable energies. This study compares electrolyzers, energy storage units, and FC technologies, with the main factors considered being cost, sustainability, and efficiency. Furthermore, a review of aging models of electrolyzers and FCs based on electrical circuit models is drawn from the literature and presented, including characterization methods of the model components and the parameters extraction methods, using a dynamic current profile. In addition, industrial projects for producing hydrogen from renewable energies that have already been completed or are now in progress are examined. The paper is concluded through a summary of recent hydrogen production and energy storage advances, as well as some applications. Perspectives on enhancing the sustainability and efficiency of hydrogen production systems are also proposed and discussed. This paper provides a review of behavioral aging models of electrolyzers and FCs when integrated into hydrogen production systems, as this is crucial for their successful deployment in an ever-changing energy context. We also review the EU's potential for renewable energy analysis. In summary, this study provides valuable information for research and industry stakeholders aiming to promote a sustainable and environmentally friendly energy transition. [ABSTRACT FROM AUTHOR]

The government has set an ambitious target of renewable energy development in Malaysia. As a promising renewable energy source, wind energy plays an important role in the Malaysia renewable energy roadmap. Compared to onshore wind energy, offshore wind resources with better quality can be provided in the areas away from the coast, which has greater potential to contribute to electricity generation. Wind and bathymetry conditions are two important factors that determine the feasibility and economics of offshore wind turbines. In this paper, an investigation is conducted on wind and bathymetry conditions around Malaysia. The data source mainly originates from the Global Wind Atlas. The conditions of the coastal areas in different states and federal territories of both Peninsular Malaysia and East Malaysia are analysed, with a specific focus on wind speed, wind energy density, and bathymetry conditions in high-wind-speed regions. The data and survey are verified and compared with the past published literature. This paper aims to investigate the wind and bathymetry conditions around Malaysia, assess the potential of offshore wind energy, discuss the feasibility of offshore wind turbines, and provide references for offshore wind development in Malaysia. [ABSTRACT FROM AUTHOR]

The world is warming, and the demand for cooling is increasing. Developing a future green hydrogen economy will also increase the demand for cooling for hydrogen liquefaction. This increase in cooling demand will happen mainly in tropical and developing countries due to their increase in population, improvements in quality of life, and the export of their renewable potential with liquid hydrogen. To solve this increase in demand for cooling, this paper proposes the use of ammonia airship cooling (AAC). AAC extracts cold from the tropopause (−80 °C) with airships and ammonia refrigeration cycles. The liquid ammonia is then transported back to the surface to provide low temperature cooling services (−33 °C). This cooling service is particularly interesting for lowering the electricity consumption in hydrogen liquefaction plants. If all the technological challenges mentioned in the paper are addressed, it is estimated that the cost of cooling with the technology is 8.25 USD/MWht and that AAC could reduce the electricity demand for hydrogen liquefaction by 30%. AAC is an innovative renewable cooling technology that has the potential to complement other renewable energy sources in a sustainable future. [ABSTRACT FROM AUTHOR]

Solar forecasting is becoming increasingly important due to the exponential growth in total global solar capacity each year. More photovoltaic (PV) penetration in the grid poses problems for grid stability due to the inherent intermittent and variable nature of PV power production. Therefore, forecasting of solar quantities becomes increasingly important to grid operators and market participants. This review presents the most recent relevant studies focusing on short-term forecasting of solar irradiance and PV power production. Recent research has increasingly turned to machine learning to address this challenge. The paper provides a discussion about building a solar forecasting model, including evaluation measures and machine learning method selection through analysed literature. Given that machine learning is data-driven, the focus of this review has been placed on data sources referenced in the literature. Open-access data sources have been compiled and explored. The main contribution of this paper is the establishment of a benchmark for assessing the performance of solar forecasting models. This benchmark utilizes the mentioned open-source datasets, offering a standardized platform for future research. It serves the crucial purpose of streamlining investigations and facilitating direct comparisons among different forecasting methodologies in the field of solar forecasting. [ABSTRACT FROM AUTHOR]

This paper presents a case study in which the influence of the 6-pulse thyristor-bridge input reactor size on the shunt active power filter (SAPF)'s work performance is investigated. The purpose of using an SAPF in the power system is in most cases for fundamental harmonic reactive power compensation, harmonics and asymmetry mitigation. The work efficiency of such a filter depends not only on the designed control system, interface filter and dc-link capacitor parameters, but also on the parameters of the electrical system in which it is connected. Therefore, it is necessary to study and know the power system (supplier and consumer sides) before its installation. For instance, in the electrical system with diode or thyristor-bridge as loads, the SAPF performance efficiency may not be satisfied due to the high rate of current change (di/dt) at the points of commutation notches. In this paper, the performed simulation and laboratory experiments show that for a better operating efficiency of the SAPF, the input reactor parameters should be selected based not only on the effective reduction in the inverter switching ripple or the control system demand, but also on the parameters of the load, such as the parameters of the diode or thyristor-bridge input reactor. Apart from the experimental demonstrations on how the input reactor size influences the SAPF work efficiency, the novelties in this paper are: the formulated recommendations on how to choose the SAPF input reactor parameters (the SAPF is more efficient in terms of harmonics, asymmetry and reactive power mitigation when the inductance of its input reactor (L-filter) is smaller than the one of the diode or thyristor-bridge input reactor); the proposed SAPF control system; the proposed expressions to compute the SAPF input reactor inductance, DC voltage and capacitor. [ABSTRACT FROM AUTHOR]

This paper describes a new underwater pumped storage hydropower concept (U.PSH) that can store electric energy by using the high water pressure on the seabed or in deep lakes to accomplish the energy transition from fossil to renewable sources. Conventional PSH basically consists of two storage reservoirs (upper and lower lake) at different topographical heights. It needs special topographic conditions, which are only limitedly available in mountain regions. Furthermore, due to the lack of acceptance and the environmental impact, new conventional PSH projects are very unlikely to be built in larger numbers in Europe in the near future. The presented solution solves these issues by placing the storage system on the seabed, thus having other geographical requirements. It operates as follows: in contrast to well-known conventional PSH plants, which use two separated water reservoirs of different heights, the U.PSH concept uses the static pressure of the water column in deep waters by installing a hollow concrete sphere in deep water. Storage of electricity is achieved by using a reversible pump in the hollow sphere. Upon opening a valve, water flows into the sphere, driving a turbine/generator, thereby discharging the storage device. In order to re-charge, the water is pumped out of the sphere against the pressure of the surrounding water. The power and energy, respectively, are proportional to the surrounding water pressure at the seabed. The amount of energy stored depends on the water depth and the volume of the spheres. The spheres need a cable connection to the shore or to a close-by floating transformer station (e.g., an offshore wind plant). No other connections such as pipes are needed. The functional principle of this energy storage technology, its state of the art, its storage capacity and the shape and size of the required spheres are discussed in this paper. [ABSTRACT FROM AUTHOR]

This research paper presents a comprehensive review of the literature on microgrid development in the UAE, focusing on the socio-economic costs and benefits, policy frameworks, market dynamics, and environmental implications. The analysis encompasses publications from 2011 to 2021, with a particular emphasis on the United Arab Emirates (UAE) and the Gulf Cooperation Council (GCC) countries. A total of 33 papers were identified and classified, revealing gaps in comprehensive valuation models, consideration of environmental and social governance factors, and research informing policy and investment decisions. The findings highlight the significance of microgrid technology in the UAE, its limited adoption and commercialization, and its predominant usage in remote areas and academic testbeds. The paper underscores the UAE's vision for net-zero emissions by 2050 and the potential of microgrids in supporting its realization. Recommendations include the development of a comprehensive valuation framework to drive effective investments in microgrid technology, aligning with the UAE's sustainable energy goals. The study contributes to the understanding of microgrid development in the UAE, offering insights into its socio-economic, policy, market, and environmental dimensions. [ABSTRACT FROM AUTHOR]

This paper presents a hydrodynamic investigation carried out on the "Wave Attenuator" device, which is a new type of floating breakwater anchored with piles and equipped with a linear Power Take Off (PTO) mechanism, which is typical for wave energy converters. The device is tested in the wave flume, under regular waves, in slightly non-linear conditions. The PTO mechanism, that restrains one of the two degrees of freedom, is simulated through an actuator and a programmable logic controller with preassigned strategy. The paper presents the system identification procedure followed in the laboratory, supported by a numerical investigation essential to set up a credible control strategy aiming at maximizing the wave energy harvesting. The maximum power conversion efficiency under the optimal PTO control strategy is found: it is of order 50–70% when the incident wave frequency is lower than the resonance one, and only of order 20% for higher frequencies. This type of experimental investigation is essential to evaluate the actual efficiency limitations imposed by device geometry. [ABSTRACT FROM AUTHOR]

Outphasing power amplifiers (OPAs) can be used in wireless information and power transfer systems due to their excellent conversion efficiency. With the rapid advancement of technology, there is a strong demand for OPAs to achieve wideband and multi-band operations to enhance frequency coverage. This paper provides a comprehensive review of the research progress on the development of broadband and multi-band board-level OPAs. Firstly, the paper introduces the fundamental components of an OPA. Then, the paper delves into a detailed analysis of the load modulation of OPAs. Subsequently, previous works on the circuit topology and design methods for broadband and multi-band OPAs are discussed and compared. The paper highlights various design strategies and their respective advantages and disadvantages. Finally, the paper explores some potential design methods for broadband and multi-band OPAs, discussing emerging technologies and highlighting potential research directions. [ABSTRACT FROM AUTHOR]

Due to their high specific heat capacity and constant thermal regeneration through flow, rivers are a promising renewable environmental heat source. The suitability of a river for hydrothermal use depends on river section-specific and site-specific factors. This paper presents a methodological proposal for a river section-specific potential analysis and site-specific feasibility study. The presentation of measured values in the form of hydrographs and duration curves as well as the use of suitable mean values and confidence intervals are central steps in the evaluation. The application of the potential analysis showed that the discharge in particular influences the size of the heat potential, while the water temperature determines whether and how the hydrothermal use is possible. The focus of this work was on the analysis of water temperature. Its significance for hydro-thermal use is multi-layered, and an assessment should be carried out at different levels. Using two specific sites on the Lahn river as a case study, the feasibility study method is demonstrated in this paper. [ABSTRACT FROM AUTHOR]

In response to the volatility of photovoltaic power generation, this paper proposes a short-term photovoltaic power generation prediction model (HWOA-MVMD-TPA-TCN) based on a Hybrid Whale Optimization Algorithm (HWOA), multivariate variational mode decomposition (MVMD), temporal pattern attention mechanism (TPA), and temporal convolutional network (TCN). In order to improve the accuracy of photovoltaic power generation forecasting, HWOA-MVMD is used for data decomposition, the Minimum Mode Overlap Component (MMOC) is used as the objective function, the photovoltaic power generation sequence is decomposed into finite Intrinsic Mode Functions (IMFs) according to the optimal solution, and the training set is formed with key meteorological variable data such as total radiation (unit: W/m2), ambient temperature, and humidity. Then, the TPA-TCN model is used to train the sub-sequences, the final predicted values are obtained after superimposing the reconstruction of the prediction results, and finally the prediction error of the photovoltaic power generation data is studied. The proposed method is applied to real photovoltaic power generation data from a commercial center in Tianjin and is compared with HWOA-MVMD-BiLSTM, GWO-MVMD-TPA-TCN, and TPA-TCN prediction models. The simulation results demonstrate that the MAE value of the forecast method proposed in this paper is 1.95 MW and the RMSE value is 2.55 MW, which can be reduced by up to 33.74% and 38.85%, respectively. The HWOA-MVMD-TPA-TCN-based short-term photovoltaic power generation prediction model presented in this paper achieves higher prediction accuracy and superior performance, serving as a valuable reference for related research. [ABSTRACT FROM AUTHOR]

The efficient utilization of low-cost carbon feedstocks, such as municipal solid waste (MSW), in biorefineries has become increasingly important for reducing GHG emissions and meeting the growing demand for renewable energy sources. However, MSW as a feedstock presents several challenges, including high moisture content, compositional variability, particle size and shape, density, and ash content. To address these challenges, the potential of mechanical dewatering and high-moisture pelleting processes for densifying MSW fractions, such as paper, cardboard, thin plastic, and thick plastic, into low-cost carbon feedstocks with improved handling and conversion properties were investigated. The effect of these preprocessing technologies on the critical quality attributes (CQAs) of the resulting pellets, including bulk density, durability, and size uniformity, were evaluated. The results showed that with these preprocessing technologies, the paper and cardboard fractions could be pelleted at moisture contents over 40% (w.b.) while achieving >99% durability and >300 kg/m3, while the high moisture plastic fractions were not suitable for pelleting. The thick plastic fraction processed in a screw press was shown to remove up to 30% of the moisture content in a single pass. These findings suggest that these mechanical preprocessing technologies can improve the physical properties of low-cost municipal solid waste fractions for biofuels production. [ABSTRACT FROM AUTHOR]

Concentrating solar power plants use sensible thermal energy storage, a mature technology based on molten salts, due to the high storage efficiency (up to 99%). Both parabolic trough collectors and the central receiver system for concentrating solar power technologies use molten salts tanks, either in direct storage systems or in indirect ones. But even though this is a mature technology, it still shows challenges in its implementation and operation. This paper underscores the critical importance of stringent design criteria for molten salt tanks in thermal storage technology. Focusing on the potential ramifications of design failures, the study explores various dimensions where an inadequate design can lead to severe consequences, even jeopardizing the viability of the entire technology. Key areas discussed include structural integrity, corrosion, thermal shock, thermal expansions, and others. By elucidating the multifaceted risks associated with design shortcomings, this paper aims to emphasize the necessity of thorough reviews and adherence to robust design principles for ensuring the success, safety, and sustainability of thermal storage technology. [ABSTRACT FROM AUTHOR]