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The stable operation of transformers is an important guarantee of power system security. The temperature distribution of main insulation is different in long‐term operation. The temperature difference between the local hottest spot temperature and the average oil temperature in the transformer exceeds 30 K. Therefore, the oil‐paper insulation inside the transformer will exhibit non‐uniform ageing after long‐term operation. At present, frequency domain dielectric response (FDS) technology is widely used in transformer ageing assessment. However, the existing assessment methods are only used for overall insulation ageing assessment. The average moisture content and polymerization degree of the overall insulation between each phase winding are obtained. But it still cannot be used to assess the non‐uniform ageing of the transformer's main insulation. The radial, axial, and two directions non‐uniform ageing models have been made in the laboratory in this study. The FDS and physicochemical properties of non‐uniform ageing models were tested. The variation law of FDS for non‐uniform ageing models was analysed. Meanwhile, the dielectric relaxation model of non‐uniform ageing for main insulation was established. The method of frequency division iterative calculation was proposed. Combined with the Fessler moisture balance formula of ageing oil‐paper insulation, the quantitative assessment method for ageing parameters of the non‐uniform ageing model can be realized. Compared the calculated results with the chemical analysis results, the relative error of the polymerization degree calculation is less than 4%, and the error of the moisture content calculation is less than 0.3%. The calculation results can meet the needs of the engineering apply. Therefore, this method can realize the quantitative assessment of transformer main insulation ageing, which is of great significance to assess the transformer insulation state. [ABSTRACT FROM AUTHOR]

This document is a guest editorial from the journal IET Generation, Transmission & Distribution. It emphasizes the need to improve the reliability and resilience of modern power systems in the face of various threats. The editorial highlights the importance of modeling, assessing, and enhancing the reliability and resilience of power grids that are increasingly incorporating grid-edge resources. The document also provides a summary of the papers included in a special issue of the journal, which cover topics such as planning reliable energy systems, analyzing power grid operations, and enhancing service restoration and grid-support load response. Additionally, the text discusses the issue of equity in power distribution system restoration processes and proposes a model called the equity-aware power distribution system restoration model. The model aims to balance equity and resilience in restoring power after outages by focusing on fair distribution of energy resources while maintaining operational efficiency. The text also includes brief biographies of several authors who have contributed to the field of power electronics and power system reliability. [Extracted from the article]

Municipal water supply system (WSS) consist of different pumping stages viz. intake, water treatment plant (WTP) and intermediate pumping station (IPS). Usually, the power supply for WSS is obtained through public power tapping sources. However, this often leads to load shedding and disruption of the water supply. This paper focuses on the concept, considering WSS as a multi-source multi-area microgrid scheme, this includes renewable energy sources (RES) such as solar, wind, etc. Moreover, the study incorporates a Battery Energy Storage System (BESS) and a Diesel Engine Generator (DEG) to provide power supply during peak demand at each pumping station. Frequency control is essential for optimizing system performance. This paper proposes Enhanced Harris Hawks Optimization Algorithm (EHHO) based PID controller for regulating the frequency in the multi-microgrid-based water supply system. The proposed controller is implemented in MATLAB simulation software, and its response is compared with other optimization methods such as Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO). Moreover, implementation and comparison of higher degree order controller such as 3DOF-FOPIDN controller and 3DOF-TIDN controllers are tested under PSO method to observe the performance as well as robustness of the controller. The results indicate that the proposed controller provides better performance in controlling the load frequency deviation, thus improving the efficiency and reliability of the multi-microgrid system for consideration of municipal water supply. [ABSTRACT FROM AUTHOR]

Power system operation and control are based on power flow calculations. In order to solve the uncertainty of the increasing penetration of renewable energy, the voltage fluctuation at the load point increases in the distribution network, and the inaccuracy of the power flow calculation due to the insufficient power flow data collection capability of the traditional power system. In this paper, a data‐driven power flow analysis model is proposed, a back propagation neural network combined with genetic algorithm (GA) and adaptive moment estimation (ADAM) optimization algorithm model is constructed to analyze the power flow calculation method of distribution networks under stochasticity. Firstly, the power flow initial value information, topology characteristics, and power factor index are introduced to construct a training set, and the mapping relationship between bus voltage and power is fully explored by training the regression model. Second, the GA‐ADAM algorithm is used to optimize the initial values and weight parameters of the model. Finally, it is verified based on IEEE‐33 bus distribution model, and the model is used for power flow calculation, and compared with other methods through each relevant error evaluation indicators. The results show that the model constructed in this paper has small error indicators and high accuracy, which improves the efficiency and accuracy of power flow calculation. [ABSTRACT FROM AUTHOR]

With the continuous breakthrough of natural language processing, the application of intelligent question-answering technology in electric power systems has attracted wide attention. However, at present, the traditional question-answering system has poor performance and is difficult to apply in engineering practice. This paper proposes an improved BERTserini algorithm for the intelligent answering of electric power regulations based on a BERT model. The proposed algorithm is implemented in two stages. The first stage is the text-segmentation stage, where a multi-document long text preprocessing technique is utilized that accommodates the rules and regulations text, and then Anserini is used to extract paragraphs with high relevance to the given question. The second stage is the answer-generation and source-retrieval stage, where a two-step fine-tuning based on the Chinese BERT model is applied to generate precise answers based on given questions, while the information regarding documents, chapters, and page numbers of these answers are also output simultaneously. The algorithm proposed in this paper eliminates the necessity for the manual organization of professional question–answer pairs, thereby effectively reducing the manual labor cost compared to traditional question-answering systems. Additionally, this algorithm exhibits a higher degree of exact match rate and a faster response time for providing answers. [ABSTRACT FROM AUTHOR]

Inter-turn short circuit fault (ISCF) is the main fault type of dry-type air-core reactors (DARs), and the reactor burnout event caused by winding ISCF seriously threatens the safe and stable operation of the electric power system. In order to effectively curb the further worsening of ISCF in DARs, a fault detection method based on frequency response analysis was proposed. First, the effect of ISCF on the frequency response curve of the windings was investigated based on the distributed parameter model of DARs. Then, four sets of eigenvalues were proposed for ISCF diagnosis based on the influence law and curve data analysis theory. Finally, based on the eigenvalues, the support vector machine model optimized by the sparrow search algorithm was used to effectively classify the degree of ISCF of the reactor, and the accuracy reached 96%. Furthermore, a test platform was built based on the theoretical analysis for experimental verification, and the test results are consistent with the simulation results. Hence, the method proposed in this paper could effectively classify the ISCF and its severity in DARs. The research in this paper could provide effective guidance for the diagnosis of ISCF in DARs. [ABSTRACT FROM AUTHOR]

The methods of artificial intelligence (AI) have been used in the planning and operation of electric power systems for more than 40 years. In recent years, due to the development of microprocessor and data storage technologies, the effectiveness of this use has greatly increased. This paper provides a systematic overview of the application of AI, including the use of machine learning (ML) in the electric power system. The potential application areas are divided into four blocks and the classification matrix has been used for clustering the AI application tasks. Furthermore, the data acquisition methods for setting the parameters of AI and ML algorithms are presented and discussed in a systematic way, considering the supervised and unsupervised learning methods. Based on this, three complex application examples, being wind power generation forecasting, smart grid security assessment (using two methods), and automatic system fault detection are presented and discussed in detail. A summary and outlook conclude the paper. [ABSTRACT FROM AUTHOR]

Integration of renewable energy sources (RES) to the grid in today's electrical system is being encouraged to meet the increase in demand of electrical power and also overcome the environmental related problems by reducing the usage of fossil fuels. Power Quality (PQ) is a critical problem that could have an effect on utilities and consumers. PQ issues in the modern electric power system were turned on by a linkage of RES, smart grid technologies and widespread usage of power electronics equipment. Unified Power Quality Conditioner (UPQC) is widely employed for solving issues with the distribution grid caused by anomalous voltage, current, or frequency. To enhance UPQC performance, Fractional Order Proportional Integral Derivative (FOPID) is developed; nevertheless, a number of tuning parameters restricts its performance. The best solution for the FOPID controller problem is found by using a Coati Optimization Algorithm (COA) and Osprey Optimization Algorithm (OOA) are combined to make a hybrid optimization CO-OA algorithm approach to mitigate these problems. This paper proposes an improved FOPID controller to reduce PQ problems while taking load power into account. In the suggested model, a RES is connected to the grid system to supply the necessary load demand during the PQ problems period. Through the use of an enhanced FOPID controller, both current and voltage PQ concerns are separately modified. The pulse signal of UPQC was done using the optimal controller, which analyzes the error value of reference value and actual value to generate pulses. The integrated design mitigates PQ issues in a system at non-linear load and linear load conditions. The proposed model provides THD of 12.15% and 0.82% at the sag period, 10.18% and 0.48% at the swell period, and 10.07% and 1.01% at the interruption period of non-linear load condition. A comparison between the FOPID controller and the traditional PI controller was additionally taken. The results showed that the recommended improved FOPID controller for UPQC has been successful in reducing the PQ challenges in the grid-connected RESs system. [ABSTRACT FROM AUTHOR]

Introduction: In order to dispatch frequency regulation resources in regional power grids efficiently and promote the development of spot markets, China Southern Power Grid (CSG) established the unified frequency regulation control area. However, the existing regional control performance standards (CPS) for evaluating the performance of frequency control in bulk power systems is no longer suitable for the unified frequency control mode. Method: This paper proposed an innovative frequency control performance standard, named tertiary control performance standards (TCPS) and used Gaussian mixture model (GMM) and folded normal distribution (FND) to describe the distributions of frequency deviations and power deviations of tie line. Result and Discussion: Based on these probability models, the parameters of the proposed TCPS can be determined optimized. Finally, case studies were carried out with the practical data from CSG and indicated that the parameters of proposed TCPS index could be calculated and improved the control performance for the real time power balance of the regional power grid with spot markets. [ABSTRACT FROM AUTHOR]

Traditionally, electric power systems are subject to uncertainties related to equipment availability, topological changes, faults, disturbances, behaviour of load, etc. In particular, the dissemination of distributed generation (DG), especially those based on renewable sources, has introduced new challenges to power systems, adding further randomness to the management of this segment. In this context, stochastic analysis could support planners and operators in a more appropriate manner than traditional deterministic analysis, since the former is able to properly model the power system uncertainties. The objective of this work is to present recent achievements of one of the most important techniques for stochastic analysis, the Monte Carlo Method (MCM), to study the technical and operational aspects of electric networks with DG. Besides covering the DG topic itself, this paper also addresses emerging themes related to smart grids and new technologies, such as electric vehicles, storage, demand response, and electrothermal hybrid systems. This review encompasses more than 90 recent articles, arranged according to the MCM application and the type of analysis of power systems. The majority of the papers reviewed apply the MCM within stochastic optimization, indicating a possible trend. [ABSTRACT FROM AUTHOR]

Multi‐terminal high‐voltage direct current technology based on voltage‐source converter stations (VSC‐MTDC) is expected to be one of the most important contributors to the future of electric power systems. In fact, among other features, it has already been shown how this technology can contribute to improve transient stability in power systems by the use of supplementary controllers. Along this line, this paper will investigate in detail how these supplementary controllers affect electromechanical oscillations, by means of small‐signal stability analysis. The paper analyses two control strategies based on the modulation of active‐power injections (P‐WAF) and reactive‐power injections (Q‐WAF) in the VSC stations which were presented in previous work. Both control strategies use global signals of the frequencies of the VSC‐MTDC system and they presented significant improvements on transient stability. The paper will provide guidelines for the design of these type of controllers to improve both large‐ and small‐disturbance angle stability. Small‐signal stability analysis (in Matlab) has been compared with non‐linear time domain simulation (in PSS/E) to confirm the results using CIGRE Nordic32A benchmark test system with a VSC‐MTDC system. The paper analyses the impact of the controller gains and communication latency on electromechanical‐oscillation damping. The main conclusion of the paper is that transient‐stability‐tailored supplementary controllers in VSC‐MTDC systems can be tuned to damp inter‐area oscillations too, maintaining their effectiveness. [ABSTRACT FROM AUTHOR]

Pre-disaster protection strategies are essential for enhancing the resilience of electric power systems against natural disasters. Considering the budgets for protection strategies, the dependency of other infrastructure systems on electricity, and the uncertainty of disaster scenarios, this paper develops risk-neutral and risk management models of strategies for pre-disaster protection. The risk-neutral model is a stochastic model designed to maximize the expected value of resilience (EVR) of the integrated system. The risk management model is a multi-objective model prioritizing the minimization of risk metrics as a secondary goal alongside maximizing the EVR. A case study conducted on the energy infrastructure systems in the Greater Toronto Area (GTA) validates the effectiveness of the models. The findings reveal the following: (i) increasing the budget enhances the EVR of the integrated system; however, beyond a certain budget threshold, the incremental benefits to the EVR significantly diminish; (ii) reducing the value of the downside risk often results in an increase in the EVR, with the variation in Pareto-optimal solutions between the two objectives being non-linear; and (iii) whether for the risk-neutral or risk management protection strategies, there are reasonable budgets when considering disaster intensity and the cost of protection measures. The models can help decision-makers to select effective protection measures for natural disasters. [ABSTRACT FROM AUTHOR]

In this paper, we demonstrated a distributed feedback fiber-laser- (DFB-FL) based ultrasound detection system with a high signal-to-noise ratio (SNR), high sensitivity and wide frequency response range. The DFB-FL was fabricated by UV-inscribing a π phase-shifted grating in the Erbium–Ytterbium co-doped fiber using the phase mask method. The theory of DFB-FL and the sensing principle has been discussed and analyzed. The sensing signal was demodulated via an unbalanced Mach–Zehnder interferometer (MZI) system. The experimental results showed that the sensitivity of the sensor reached 75.18 mV/kPa and the flat frequency response range covered over 30 MHz, which covered the ultrasonic detection frequency range of abnormal discharge in the electric power system. The SNR of this DFB-FL was 42.9 dB, and the corresponding noise-equivalent pressure was calculated as 0.12 kPa. [ABSTRACT FROM AUTHOR]

Power system stability characteristics are typically evaluated in terms of small‐ and large‐signal (transient) stability. Access to the time‐varying A‐matrix of a state‐space‐based power systems model during transient conditions can be utilized to apply linear time‐varying system concepts for large‐signal stability analysis. In linear time‐varying system analysis, the differential Riccati equation (DRE) plays a vital role when the power system is subjected to a severe disturbance. The Möbius transformation is proposed in this paper to solve the DRE with singularity issues. It is shown that the solution of the DREs follows a specific mathematical pattern when the power system is stable but does not follow this pattern when the system progresses toward instability. The proposed method can be used in large‐signal stability analysis to predict instability and make the stability analysis more efficient. Additionally, the vector‐DRE is proposed to generalize the index in a large‐scale power system. Results show that analyzing the corresponding Riccati equation's behaviour can help researchers predict a power system's performance and improve the control and management of the system. [ABSTRACT FROM AUTHOR]

This paper was conceived to investigate some central issues related to the upheaval of current energy scenarios in Sicily. New power connection lines that are about to be built in the Mediterranean area, planned with a view to a constantly increasing renewable generation, encourage the carrying out of analyses on how the Sicilian electric power system will be able to make itself ready to support large power injections, especially due to new renewables plants that will be established in the region soon. This study, carried out in close collaboration with the Italian TSO Terna S.p.A and the University of Palermo, defines what the impacts of new renewable power plants will be on the Sicilian power transmission grid under intact and non-intact grid conditions. This study consists of steady-state simulations carried out using WinCreso® software version 7.62.1-3 in two energy scenarios estimated for the years 2024 and 2027, based on real connection requests by producers to Terna, and allows one to go beyond the studies conducted so far on a 2030 basis through the precise identification of network nodes or lines in difficulty. Finally, as well as presenting an interesting case study due to Sicily's strategic position in the Mediterranean Sea, this article proposes a methodological approach that can easily be adopted in other contexts and by other TSOs to analyze similar situations. [ABSTRACT FROM AUTHOR]

In the past few years, technical progress has determined traditional electric power system conversion to Smart Grids, and consequently empowered a worldwide renaissance in the forgotten PQ field. Since the installation of PQ monitors is currently associated with high investments and operational costs, it is inappropriate to install a monitor on each grid busbar. Hence, grid operators must establish the best cost–benefit scenario for monitors installation and achieve maximal observability with a limited number of analyzers. Firstly, this paper presents a review of the state-of-the-art of displacement strategies, and discusses them regarding the tendencies of node selection criteria, the test schemes used, and the grid size. Secondly, the relevant fundamental issues which must be solved in the future in order to eliminate restrictions in PQ monitors' allocation planning are presented and discussed. These issues concern the treatment, interpretation, and assessment of PQ events, measurement chain technical features, PQ's role in the grid planning stage, communication technologies, and other remote monitoring aspects, and integration with other Smart Grid applications. The provided insights are based on experience which has been obtained during the PQ measurement campaign in the Lithuanian DSO grid. Finally, a PQ system development strategy—both short-term and long-term perspectives—in the Lithuanian distribution grid is presented, including monitors allocation criteria. [ABSTRACT FROM AUTHOR]

By increasing load demands and extending power networks to respond to customers' needs, the complexity and integration of power systems have been boosted, increasing the system's short circuit current level, which may threaten the network's reliability. Over the years, some approaches have been proposed to deal with this issue. Proper examples are reconfiguring networks, increasing circuit breakers (CBs) capacity, and implementing fault current limiters (FCLs). Reconfiguration and increasing CB rating have applied exorbitant costs to the system, and in some cases, it may be infeasible. Hence, FCLs can play a pivotal role in the mitigation of the fault current level, but the effectiveness of FCLs depends on the numbers and impedance of FCLs. In this paper, a novel and multi-objective approach is presented to optimize three objective functions simultaneously: decreasing the short circuit level, increasing the systems reliability level, and minimizing the costs of FCL installation. The adaptive penalty factor and Pareto-based multi-objective evolutionary algorithm based on decomposition are used to optimize the objectives mentioned above. Numerical and graphical results of optimization studies in MATLAB software on the IEEE RTS 24-Bus system confirm the proposed method's competence. [ABSTRACT FROM AUTHOR]

Renewable energy sources have a multifaceted impact on power grids, ranging from the reliability and quality of electricity to the selective impact on equipment. While renewables used to be distributed in distribution networks, now their capacity is commensurate with thermal power plants and their impact on the grid should not be underestimated. According to the statistics on the interruption of the bulk electric networks, one of the main reasons for emergency shutdowns of extra high-voltage power lines are single-phase short circuits. The problem of mathematical modeling of the limit modes in terms of static stability is very relevant to the design and operation of electric power systems (EPS). Calculations of limit modes have both an independent value and a component of other electrical engineering tasks related to ensuring the required level of reliability and cost-effectiveness of the operation of the united PS. Despite the great degree of development of issues of planning and control of electric modes, system accidents associated with unacceptable loads of network elements occur in the Ukrainian energy industry. Non-phase modes regularly occur in electric power systems, which can lead to an unacceptable load of intersystem network elements, which imposes significant restrictions on their throughput. Single-phase short circuits are more than 95% of other damage that occurs in the line. The use of single-phase auto reclose on the transmission lines allows disconnecting only the damaged phase for a short period of time and not the entire transmission line. This action preserves the transit of electricity along the line and prevents the violation of the stability of parallel operation. To achieve this, the current-free pause of the single-phase auto reclose should last as short as possible. On the other hand, an important task to be solved when using single-phase auto reclose is to choose the minimum duration of the current-free pause necessary for its success. The problem studied in this paper deals with the safety and correct operation of transmission lines (TS) of the Ukrainian bulk power system in special conditions (not predictable, changing due to frequent attacks). For a quickly changing configuration, the power grid uses switches, and in the case of ultra-high voltage, the TS needs to solve the problem of secondary arc currents and recovering stresses in the place of arc burning after its extinction. One of the methods of reducing secondary arc currents and recovering stresses in the place of arc burning after its extinction is the implementation of single-phase automatic reclosing (SPAR). The main theoretical result of the paper is a proposed mathematical model of a compensated power transmission line based on the use of matrix n-poles, which makes it possible to model in detail stationary power transmission modes, including the SPAR mode. The proposed mathematical model of three-phase power transmission has been created using phase coordinates and can be used for the analysis of complex asymmetric modes. The main practical result of the paper is physically interpreted simplified models of three-phase TS, which can be used for the study of resonant overvoltages and currents of the feeding arc in non-full-phase circuit SPAR. The conclusion that can be drawn from the obtained results points out which line lengths must take into account the influence of longitudinal asymmetry when choosing the inductive resistance, i.e., take into account the dependence of the mode parameters on the location of the damaged phase. The observed results show that the largest values of the multiplicity of overvoltages will take place in phase B. The novelty of the work is the developed technique that makes it possible to determine in advance, depending on the disconnected phase of the line, the values of the primary conductivities of the STC (static thyristor compensators) and the corresponding angles of control of the thyristor switches, which satisfy almost complete compensation of the secondary arc at any point of the line in the specific condition (hard) of the bulk power system operation. [ABSTRACT FROM AUTHOR]

Topics of interest for publication included, but were not limited to, advanced simulation and modeling methods for complex energy problems, soft computing and artificial intelligence in energy systems, machine learning, multi-energy systems, co-simulation, distributed energy resources, and energy demand prediction. The second paper, "A statistical assessment of blending hydrogen into gas networks" [[6]], provides a tool for the statistical assessment of deploying hydrogen in existing gas networks. The need for a "smarter" energy grid infrastructure, with the large-scale integration of renewables and a better demand-response mechanism, is leading to an ever-increasing complexity of next-generation energy networks [[1]]. [Extracted from the article]

For wide-body all-electric aircraft (AEA), a high-power-delivery, low-system-mass electric power system (EPS) necessitates advanced cable technologies. Increasing voltage levels enhances power density yet poses challenges in aircraft cable design, including managing arc-related risks, partial discharges (PDs), and thermal management. Developing multilayer multifunctional electrical insulation (MMEI) systems for aircraft applications is a feasible option to tackle these challenges and reduce the size and mass of cable systems. This approach involves selecting layers of different materials to address specific challenges. Our prior research concentrated on the modeling and simulation-based design of MMEI systems for MVDC power cables. Experimental tests are essential for determining the behavior of PDs under varying pressure conditions. Also, the dielectric strength and time to failure of the designs need to be assessed. In this work, the fabrication process of a down-selected MMEI flat configuration is discussed and analyzed. This paper analyzes the fabrication process of power cables employing MMEI configurations and evaluates the PD characteristics of down-selected ARC-SC-T-MMEI cable samples. This study presents a detailed analysis of the characteristics of PD under atmospheric and low-pressure conditions, which will provide essential insights into the design of MVDC cables for future AEA applications. [ABSTRACT FROM AUTHOR]

Air-source heat pumps (ASHPs), functioning as thermally controlled loads, possess significant adjustable capabilities and controllability when aggregated, establishing them as premium resources for demand-response engagement. This paper proposes a control strategy for the aggregation of ASHP loads to participate in demand response across multiple scenarios, framed within a three-tier architecture: electric power system, Load Aggregator (LA), and thermal load. Load Aggregators, considering the user-comfort temperature ranges and the thermal storage characteristics of buildings, aim to minimize heating costs through time-of-use electricity pricing, while assessing the adjustability of the load. Upon receiving control directives from the power system's dispatch department, the strategy allocates load adjustments by considering user comfort and system regulatory needs, thereby addressing issues like aggregated power oscillations and significant rebound loads. The effectiveness of the proposed strategy is corroborated through simulation, demonstrating its potential to enhance demand-response participation and ameliorate associated power stability challenges. [ABSTRACT FROM AUTHOR]

The renewable-dominant hybrid generation systems (HGSs) are increasingly important to the electric power system worldwide. However, influenced by uncertain meteorological factors, the operational robustness of HGSs must be evaluated to inform the associated decision-making. Additionally, the main factors affecting the HGS's robustness should be urgently identified under deep uncertainties, as this provides valuable guidance for HGS capacity configuration. In this paper, a multivariate stochastic simulation method is developed and used to generate uncertain resource scenarios of runoff, photovoltaic power, and wind power. Subsequently, a long-term stochastic optimization model of the HGS is employed to derive the optimal operating rules. Finally, these operating rules are used to simulate the long-term operation of an HGS, and the results are used to evaluate the HGS's robustness and identify its main sensitivities. A clean energy base located in the Upper Yellow River Basin, China, is selected as a case study. The results show that the HGS achieves greater operational robustness than an individual hydropower system, and the robustness becomes weaker as the total capacity of photovoltaic and wind power increases. Additionally, the operational robustness of the HGS is found to be more sensitive to the total capacity than to the capacity ratio between photovoltaic and wind power. [ABSTRACT FROM AUTHOR]

With the development of EVs (Electric Vehicles) and the rapidly developing policies on low carbon and environmental protection, electric power systems and natural gas systems become increasingly larger. Under these circumstances, the V2G (Vehicle-to-grid) and the coordinated operation of an integrated electricity–gas distribution system (IEGDS), considering CO2 emissions, can play a part together in the process of energy conservation. Firstly, the V2G model is discussed; this paper presents the cost differences between out-of-order and order for the car. Secondly, the IEGDS model presents coupling constraints of gas turbines and power-to-gas. Lastly, carbon emission is considered in this paper; a carbon capture plant (CCP) captures the CO2 burning by fossil fuel in the power generation process and stores it in a carbon storage tank. This paper also considers trading with the carbon market via a carbon storage warehouse. With the cooperation of various components, a comprehensive model considers the use of V2G to store power in the IEGDS system, with consideration of the carbon trade. Numerical experiments validate the effectiveness of the combination between V2G and IEGDS, considering carbon emissions and carbon trading. [ABSTRACT FROM AUTHOR]

A Reward and Penalty Scheme (RPS) is generally used for setting up service quality and it will bring about financial benefits for distribution companies due to customer reliability and the resulting demand. In this paper, an algorithm was presented for the optimal switch number and placement in distribution networks in the presence of RPS. The main objective of this paper is to improve the reliability and minimize the costs of Sectionalizing Switches (SS) and Tie Switches (TS) for a given regulatory period considering the acceptable financial risk. In this algorithm, uncertainty in the reliability appears as a financial risk. A genetic algorithm was adopted to solve the optimization problem. The numbers and locations of SS and TS were determined by considering the financial incentives of RPS, capital investment and annual operation, and maintenance costs. The performance of the proposed approach was assessed and illustrated within a real distribution network. The results showed the efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In an electricity and heat integrated energy system, the transmission of thermal energy encounters significant delays, and the delays are often not integer multiples of the dispatch interval. This mismatch poses challenges for achieving coordinated dispatch with the electric power system. To address this problem, the fictitious node method is proposed in this paper, offering a novel approach to calculating the quasi-dynamic characteristics of the heating network. Furthermore, to enhance the local consumption capacity of wind power, the heat storage capacity of the heat supply network was taken into consideration in this study, and a combined energy supply model equipped with electric boilers, incorporating combined heat and power (CHP) units and gas turbine units, was developed. This model effectively expands the operational range of CHP units and enables the decoupling of electricity and heat operations in gas turbine units. The analysis conducted demonstrated the effectiveness of the proposed method and model in achieving the coordinated dispatch of electricity and heat. Moreover, it highlighted the positive impact on the overall economy of system operation and the promotion of wind power consumption. The optimal configuration presented in this paper resulted in an 8.2% improvement in system operating economics and a 38.3% enhancement in wind power integration. [ABSTRACT FROM AUTHOR]

Multi-area economic distribution of load (MAED) is a generalization of the basic problems of economic distribution of load (ED), which evaluate the optimal power distribution of multiple areas in terms of operating costs. In the following parts of this paper, the concept of MAED is extended to multi-regional economic/environmental distribution (MAEED) by considering environmental issues. The purpose of MAEED is to distribute power among different areas by minimizing operating costs and emissions at the same time. In this paper, first the MAEED problem was expressed as a formula; then, a multi-objective and advanced particle optimization (MOPSO) algorithm was expressed to deduce its Pareto optimal solutions, during the optimization process. The transmission limits of communication lines were expressed as a set of constraints to ensure the security of the system. In addition, the rotating storage area was to increase the reliability of the system. A reserve sharing pattern was applied to ensure each region's capability to meet reserve demand. The simulation was based on the four-zone experimental power system, and it showed the effect of the proposed optimization process and the effects caused by different issues. [ABSTRACT FROM AUTHOR]

Energy harvesting systems are key elements for the widespread deployment of wireless sensor nodes. Although many energy harvesting systems exist, electric field energy harvesting is a promising choice because it can provide uninterrupted power regardless of external conditions and depends only on the presence of AC voltage in the grid, regardless of the magnitude of the line current, even under no-load conditions. However, it also has some disadvantages, such as low power availability, the need for storage, or reliance on capacitive coupling, which is a complex phenomenon that depends on parasitic capacitances. This paper aims to provide useful and practical information on the possibilities of electric field energy harvesting for both high- and low-voltage applications. Since the objective of this paper is to quantify the physical limit of the harvested energy, it considers only the physical harvester itself and not the electronic circuitry required to transfer the harvested energy to the load. Theoretical, simulation, and experimental results show the feasibility of this energy source for low-power applications such as wireless sensor nodes. [ABSTRACT FROM AUTHOR]

The identification and analysis of harmonics, frequency, and transient events are essential today. It is necessary to have available data relating to harmonics, frequency, and transient events to understand power systems and their proper control and analysis. Power quality monitoring is the first step in identifying power quality disturbances and reducing them and, as a result, improving the performance of the power system. In this paper, while presenting different methods for measuring these quantities, we have made some corrections to them. These reforms have been obtained through the analysis of power network signals. Finally, we introduce a new monitoring system capable of measuring harmonics, frequency, and transient events in the network. In addition, these values are provided for online and offline calculations of harmonics, frequency, and transient events. In this paper, two new and practical methods of the "algebraic method" are used to calculate network harmonics and wavelet transform to calculate transient modes in the network. Furthermore, the proposed monitoring system is able to reduce the amount of data-storage memory. The results of the simulations performed in this article show the superiority of using the new method presented for online and offline monitoring of power quality in electric power systems. [ABSTRACT FROM AUTHOR]

The electrical energy supply relies on the satisfactory operation of insulators. The ultrasound recorded from insulators in different conditions has a time series output, which can be used to classify faulty insulators. The random convolutional kernel transform (Rocket) algorithms use convolutional filters to extract various features from the time series data. This paper proposes a combination of Rocket algorithms, machine learning classifiers, and empirical mode decomposition (EMD) methods, such as complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), empirical wavelet transform (EWT), and variational mode decomposition (VMD). The results show that the EMD methods, combined with MiniRocket, significantly improve the accuracy of logistic regression in insulator fault diagnosis. The proposed strategy achieves an accuracy of 0.992 using CEEMDAN, 0.995 with EWT, and 0.980 with VMD. These results highlight the potential of incorporating EMD methods in insulator failure detection models to enhance the safety and dependability of power systems. [ABSTRACT FROM AUTHOR]

Addressing the issue of reduced system inertia and significantly increased risk of system frequency deviation due to high penetration of renewable energy sources, this paper proposes a power system disturbance frequency trajectory prediction method based on light gradient boosting machine (LightGBM) Spearman to provide data support for advanced system stability judgment and the initiation of stability control measures. Firstly, the optimal cluster is determined by combining the K-means clustering algorithm with the elbow method to eliminate redundant electrical quantities. Subsequently, the Spearman coefficient is used to analyze feature correlation and filter out electrical quantities that are strongly correlated with frequency stability. Finally, a frequency trajectory prediction model is built based on LightGBM to achieve accurate prediction of disturbed frequency trajectories. The method is validated using a case study on the New England 10-machine 39-bus system constructed on the CloudPSS 4.0 full electromagnetic cloud simulation platform, and the results show that the proposed method has high accuracy in frequency trajectory prediction. [ABSTRACT FROM AUTHOR]

Optimal power flow (OPF) is a challenging optimization problem with a large number of variables and constraints. To overcome the OPF issue, high-performance optimization algorithms are needed. In this direction, this paper has been centered on the optimization of the OPF with the circulatory system-based optimization (CSBO) algorithm. The performance of the algorithm was evaluated on the IEEE 57- and 118-bus power networks for the optimization of non-convex OPF objectives, i.e., fuel cost, power loss, voltage deviation, and enhancement of voltage stability. The solution quality of CSBO is compared with state-of-theart metaheuristic algorithms such as Artificial Rabbits Optimization (ARO), African Vultures Optimization Algorithm (AVOA), and Chaos Game Optimization (CGO). Based on the OPF results, it is seen that the best fuel cost and voltage deviation results are calculated to be 41666.2344 $/h and 0.5871 p.u with the CSBO algorithm for the IEEE 57-bus power system. The CSBO algorithm obtained the best objective function results for the IEEE 118-bus power network with a fuel cost of 134934.3140 $/h and a power loss of 16.4688 MW. In conclusion, the present paper reports that the CSBO is a powerful and efficient metaheuristic algorithm to solve the OPF problem. [ABSTRACT FROM AUTHOR]

The optimal operation of power systems is one of the most critical issues for operators. Optimizing the operation of power systems while accommodating the increasing penetration of RES, owing to the intermittent and variable nature of these resources, stands as one of the most critical challenges for power systems. Numerous primary challenges, including fluctuations in load and nonlinear constraints, further complicate the issue, given its substantial dimensions. Therefore, this paper introduces an approach for improving the management of optimal generation and the associated carbon emissions costs of traditional power plants, which is achieved through integrating wind farms and incorporating battery energy storage. This enhancement is achieved by integrating wind farms and utilizing battery storage systems while considering the costs associated with traditional units using fossil fuels and the expenses related to carbon emissions. The simulation incorporates seven load customer types and five traditional generation sources integrated with wind farms and battery storage devices. The simulation results demonstrate that the new problem formulation has significantly improved the ability and performance of optimizing the scheduling of power plant generations. [ABSTRACT FROM AUTHOR]

The electric power system is rapidly transforming to address the urgent need for decarbonization and combat climate change. Integration of renewable energy sources into the power grid is accelerating, creating new challenges such as intermittency and uncertainty. To address these challenges, this paper proposes a new design of automatic generation control (AGC) ancillary service cost allocation based on the causer-pays rule. The proposed design treats reserves as inventory and aims to minimize them by allocating costs among consumers based on the causative factors for AGC operation. Two cost-allocation methods based on the causer-pays principle are introduced. The first method distributes costs according to the changes in loads causing ancillary service operation, while the second method considers opportunity costs. The case study on the IEEE 39 Bus System demonstrates that the proposed methods incentivize consumers to minimize volatility, resulting in reduced reserve requirements for system operation. In particular, the opportunity cost-based approach encourages loads and variable renewable energy (VRE) to actively reduce volatility, resulting in more efficient power system operation. In conclusion, the novel AGC ancillary service cost allocation methods offer a promising strategy for minimizing spinning reserves, increasing the power system's efficiency, and incentivizing consumers to actively participate in frequency regulation for a more sustainable and reliable electricity market. [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]

Carbon peaking and carbon neutrality goals have proposed by many countries, including China. Meanwhile, China has also proposed the construction of a new-type electric power system with new energy as the main body, which will have great impacts on coal-fired power generation enterprises. The transformation of coal-fired power enterprises is imperative, and the evaluation of the organizational performance of coal-fired power enterprises is urgent, which can accurately determine the development status and even can find issues related to the transformation of coal-fired power enterprises. In this paper, a hybrid evaluation model is proposed based on the Variational Auto-Encoder algorithm and fuzzy comprehensive evaluation method improved by a vague set to comprehensively evaluate the organizational performance of coal-fired power enterprises. Eight coal-fired power enterprises in North China are selected for empirical analysis. The results show that the YC coal-fired power enterprise has the best organizational performance, while the NK coal-fired power enterprise has the worst organizational performance. Moreover, sensitivity and comparative analyses are carried out to verify the robustness of the evaluation result using the proposed hybrid method in this paper. This paper focuses on the organizational performance evaluation of coal-fired power enterprises, which can provide a reference for the smooth transformation and sustainable development of coal-fired power enterprises in the context of "Dual-Carbon" goals. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the instability of the electricity generation of renewable energy sources (RESs), specifically Digital Twins of RESs. The first part deals with the analysis of RES electricity generation around the world and Ukraine. The following chapter describes features of functioning power grids in modern conditions in Ukraine and ways to ensure the balance reliability in the power system for conditions of high-grade RES integration. The rapid increase in electricity generation RESs causes control problems of distributed power supply in the power grid. A mathematical model of the parameter controls in normal mode electric power systems for conditions with high integration of RESs is proposed in the second part. The study investigates components of the optimality criterion at the control of normal mode parameters of the electric power system with RESs. In general, digital transformation helps decarbonize the energy supply, decrease dependency on fossil fuels, and integrate renewables into power systems. A model Digital Twin (DT) of a photovoltaic system, or an exact 3D visualization, analyzing the accumulator system depending on load and generation, are presented. The problems of Digital Twin are very widely discussed, but many papers and studies are general without any practical implementations. The main part of this paper focuses on research and deals with daily electricity generation from different kinds of RESs, namely mini-hydropower stations, photovoltaic power stations, and wind power stations. Measured data of electricity generation from photovoltaic power plants, wind power plants, and mini-hydropower plants and obtained meteorological factors were used for the calculation of Spearman's, Kendall's, and Pearson's correlation rank coefficients. The main contribution of this research is to determine the main metrological factors for each kind of studied RES. In the future, it will help to decide the task of forecasting power generation more presciently. Additionally, the presented model of DT RESs allows the installation and operation of grids with higher efficiency, because it can help to predict all influences, from shading up to the optimization of the battery storage system. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) represent a promising green technology for mitigating environmental impacts. However, their widespread adoption has significant implications for management, monitoring, and control of power systems. The integration of renewable energy sources (RESs), commonly referred to as green energy sources or alternative energy sources, into the network infrastructure is a sustainable and effective approach to addressing these matters. This paper provides a comprehensive review of the integration of RESs and EVs into power systems. The bibliographic analysis revealed that IEEE Access had the highest impact among journals. In order to enhance the classification of the reviewed literature, we have provided an analytical summary of the contributions made by each paper. The categorization facilitated the recognition of the primary objectives explored in the reviewed works, including the classification of EVs and RESs, the incorporation of RESs and EVs into power systems with an emphasis on emissions, the establishment of EV charging stations and parking facilities, EV batteries and battery energy storage systems, strategies for managing the integration of RESs with EVs, EV aggregators, and the financial implications. In order to provide researchers with a valuable synopsis of the implementation particulars, the papers were bifurcated into two primary classifications, namely mathematical algorithms and heuristic algorithms. The mixed integer linear programming algorithm and particle swarm optimization algorithm were commonly utilized formulations in optimization. MATLAB/Simulink was the primary platform used for executing a considerable portion of these algorithms, with CPLEX being the dominant optimization tool. Finally, this study offers avenues for further discourse and investigation regarding areas of research that remain unexplored. [ABSTRACT FROM AUTHOR]

An electric power system is an important factor in national economic development. However, as an electric power system requires more electric equipment in its operation process, it is prone to short circuits, faults and other problems, which can lead to fires. To help prevent fires in such power systems, the hydraulic performance of the existing firefighting monitor should be optimized. A rectifier is an important structure which affects the performance of the firefighting monitor. In this paper, numerical simulations based on CFD (computational fluid dynamics) are carried out to analyze the fluid flow inside firefighting monitors with five different rectifier structures. In addition, the effects of rectifier structure on both the turbulent kinetic energy and axial velocity of the fluid inside the firefighting monitor are analyzed. The results show that rectifier installation can reduce the turbulent energy of the inlet and outlet of the firefighting monitor and improve the axial velocity distribution inside the firefighting monitor. Specifically, a forked row rectifier arrangement can significantly improve the effect of flow stabilization. However, there are limits to improving rectifier stabilization performance by changing the number of blades, as too many blades can cause reverse direction flow and large pressure losses. [ABSTRACT FROM AUTHOR]

Penetration of wind power plants (WPPs) in the electric power system will complicate the system load flow analysis. Consequently, the traditional load flow algorithm can no longer be used to find the solution to the load flow problem of such a system. This paper proposes a doubly fed induction generator (DFIG)-based WPP model for a load flow analysis of the electric power system. The proposed model is derived based on the power formulations of the WPP—namely, DFIG power, DFIG power loss, and WPP power output formulas. The model can be applied to various DFIG power factor operating modes. In the present paper, applications of the proposed methods in two representative electric power systems (i.e., IEEE 14-bus and 30-bus systems) have been investigated. The investigation results verify the proposed method's capability to solve the load flow problem of the system embedded with DFIG-based variable-speed WPPs. [ABSTRACT FROM AUTHOR]

The detection of defects on small cotter pins that are installed in electric power fittings is an essential part of the inspection task of overhead lines using Unmanned Aerial Vehicles (UAV). It is challenging to detect small defects from a large number of UAV images. In this paper, an efficient and high-performance defect detection model called DDNet is proposed to recognize defects from images of unmanned aerial vehicles. The attention mechanism was adopted in the improved detection model in order to enhance the representation learning of the image. Inspired by the human visual system, the RFB module is added to the FPN module, increasing the receptive field of the entire detection network, which is conducive to the detection of small objects. Then a dataset of cotter pins for model training and testing was introduced. The study demonstrates that the proposed DDNet increases the average precision from 82.0 to 90.1% and reduces the miss rate of defect detection from 14.5 to 7.4% in our dataset compared to the baseline RetinaNet model. We also compared existing frameworks for object detection and discussed other common ways to improve precision. The results showed that our optimized model in this paper improved detection performance, which subsequently proved the practicability and effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

Background and Objectives: Due to the increased sensitive loads, improving power quality in distribution grids by custom power tools is one of the important fields of electrical engineering. This paper proposes a new kind of three-phase three-wire dynamic voltage restorer (without including storage sources or DC link) and also its control method. Methods: The proposed structure includes an AC/AC converter, low-pass filters at the input and output sides, and three-phase injection transformers. The control system is based on the combination of feedback and feedforward control that its advantages are high speed, good response quality, and very simple implementation. To overcome the harmonics raised from AC/AC converter switching on the main line, a SOGI-PLL has been used. Also, SOGI-PLL operates independently on each phase so that the asymmetric voltage variations can be identified. Results: The proposed control method is capable to compensate the power quality problems such as voltage sag, swell, and harmonics in balanced and unbalanced conditions. The detailed modelling and design of the proposed controller are verified through computer simulations and experimental results under different operating conditions. Simulation and experimental results show that the proposed control strategy can compensate the power quality events as close as possible to the desired values under different operation modes. Conclusion: In this paper, a three-phase three-wire dynamic voltage restorer (DVR) was assessed using direct AC/AC converters without a supply source and DC link. A control system based on combined feedback and feedforward control (CFBFFC) and SOGI-PLL has been proposed for the DVR. The simulation results on a three-phase 20kV system as well as the experimental results obtained from a single-phase 220V system verified the performance of the DVR and the control system. It was shown that this structure can compensate for 0.5pu voltage sag, above 1pu voltage swell, and all kinds of harmonic faults. [ABSTRACT FROM AUTHOR]

The wind power interval prediction of offshore wind farms and power plan arrangement of conventional thermal power units are of vital importance in the consumption of offshore wind power, the reduction of greenhouse gas impact on the environment, and the electric power system safe and economic operating. With the purpose of selecting the appropriate Copula function on the basis of the results of wind speed and wind power normal test, establish the mathematical model of wind-fire joint optimal scheduling, and optimize coal-fired power units power generation after comparing the convergence performance of particle swarm optimization method and crow search algorithm. Results indicate that the selected Copula function meets the expected criteria, and the optimized thermal unit climbs more smoothly and through the optimization of CSA the complete economic consumption of running is lessened. An idea is presented by this paper, which considers the uncertainties of offshore wind power generation, and the basis for the operational performance of CSA over PSO, and which provides a joint wind-thermal economic optimal dispatch strategy. [ABSTRACT FROM AUTHOR]

This paper contains the design of active optical lenses used for the detection of arc flashing emissions. The phenomenon of an arc flashing emission and its characteristics were contemplated. Methods of preventing these emissions in electric power systems were discussed as well. The article also includes a comparison of commercially available detectors. An analysis of the material properties of fluorescent optical fiber UV-VIS-detecting sensors constitutes a major part of the paper. The main purpose of the work was to make an active lens using photoluminescent materials, which can convert ultraviolet radiation into visible light. As part of the work, active lenses with materials such as Poly(methyl 2-methylpropenoate) (PMMA) and phosphate glass doped with lanthanides, such as terbium (Tb3+) and europium (Eu3+) ions, were analyzed. These lenses were used to make optical sensors, which were supported by commercially available sensors in their construction. [ABSTRACT FROM AUTHOR]

As the most promising alternative to internal combustion engines (ICEs), electric vehicles (EVs) have an excellent development outlook. The charging route scheduling of EVs can simultaneously affect traffic congestion in the transportation network (TN) and power flow distribution in the power distribution network (PDN). The research on TN and PDN coupling networks based on the static traffic flow model is relatively mature; however, it ignores that the traffic flow will spread across periods in a short scheduling period. In this paper, a semi‐dynamic traffic flow model is proposed to represent the dynamic propagation characteristics of EVs and ICEs flow. Furthermore, the cost of carbon emission and system operation are combined as the overall goal of system optimisation. Since the model has become a more complex non‐linear model, this paper proposes to combine the heuristic sequential boundary tightening and binary expansion method to linearise the model. The study compared four cases and found that a 20% penetration rate of EVs can reduce carbon emissions by 4.2% while reducing the system's total cost by 10%. Moreover, the impact of network congestion on the spatiotemporal distribution of traffic flow and power flow in the coupled network is alleviated. [ABSTRACT FROM AUTHOR]

When the T-connected transmission line fails, there is a certain relationship between the phases of the three-terminal power frequency fault current, which can be applied to protect the current differential of the T-connected line. In this paper, using the MATLAB/Simulink electric power system simulation software, when the T-connected transmission line is faulty, the power frequency fault current variation law monitored at the installation point is deeply studied, and the judgment method of the T-connected transmission line fault branch based on the power frequency current is proposed. [ABSTRACT FROM AUTHOR]

Electric power information has garnered particular interest in conventional electrical power systems because it plays a crucial role in the electric power industry. Additionally, electric power communication networks ensure the overall power system's reliability and safety. The concepts and techniques used in digital twin (DT)‐based online tools for electric power communication networks are introduced in this paper. Moreover, online DT tools are proposed as daily learning and training resources for both new staff and communication commissioners, which can be used for the internet and the company intranets. Users can control DT and physical equipment simultaneously, and device status can be seen in real time. The design, modelling, control principles, data collection, and visual display of the DT tools are all covered in this study. To validate the applicability of the proposed framework, a case study for optical fibre damage and the recovery process in a typical communication interruption malfunction is investigated. The research presented in this paper has the potential to provide useful tools and new paradigms for designing online DT training and education systems. [ABSTRACT FROM AUTHOR]

For each photovoltaic power plant, it is extremely important to perform an analysis of its efficiency, as well as an analysis of all parameters that may affect efficiency. The electric energy of the photovoltaic system, which is delivered to the electric power system on a daily basis, is determined through the average daily insolation, the surface of the panel and the average efficiency value. One of the parameters that affect the conversion efficiency of a photovoltaic power plant is a decrease in the conversion efficiency due to an increase in panel temperature. In this paper an example is a real photovoltaic power plant with a nominal power of 50 kW, which is installed on the rooftop of the building of the Institute "Mihajlo Pupin", located in Zvezdara forest, Belgrade, Serbia. The correlation analysis of the estimated temperature of the photovoltaic panel was performed using two models and the measured temperature of the photovoltaic panel. The temperature of the photovoltaic panel was estimated using models, one of which does not take into account, and the other takes into account the influence of wind speed on the temperature of the panel. [ABSTRACT FROM AUTHOR]

Optimal power flow (OPF) is one of the fundamental mathematical tools currently used to operate power systems within the technical limits of the transmission power system. To determine OPF, a highly non-linear complex problem, it is essential to research power system planning and control. This study presents a practical and trustworthy optimization approach for the OPF problem in electrical transmission power systems. Many intelligence optimization algorithms and methods have recently been developed to solve OPF, particularly the non-linear complex optimization problems. In this paper, a novel meta-heuristic algorithm called the mountain gazelle optimizer (MGO) is suggested for solving the OPF problem. The suggested algorithm applies the improved three single objective functions to the MGO algorithm for the best OPF issue control variable settings. Three objective functions that reflect the minimization of generating fuel cost, the minimizing of active power loss, and the minimizing of voltage deviations have been used to investigate and test the proposed algorithm on the standard IEEE 30-bus test system. The simulation results demonstrate the efficiency of the proposed MGO algorithm; the fuel costs are reduced by 11.407%, power losses are considerably decreased by 51.016%, and the voltage profile is significantly reduced by 91.501%. Furthermore, the outcomes produced by the proposed algorithm have also been contrasted with outcomes produced by applying other comparable optimization algorithms published in recent years. The optimal results are encouraging and demonstrate the resilience and efficacy of the suggested strategy. [ABSTRACT FROM AUTHOR]

Fishbone drilling (FbD) involves drilling multiple micro-holes branching out in various directions from the primary vertical or deviated wellbore. FbD is similar to multilateral micro-hole drilling and can be employed to boost hydrocarbon production in naturally fractured formations or during refracturing operations by connecting existing natural fractures. Key design elements in fishbones include determining the number, length, and spacing between the branches, and the angle at which the branches deviate from the main borehole. Fishbone wells have emerged as a promising technology for improving well performance and reducing environmental impact. In this paper, we present a comprehensive review of the different applications of fishbone wells in conventional and renewable energy systems. We discuss the potential of fishbone wells for enhanced oil and gas recovery, as well as their application in unconventional resources such as coal bed methane. Moreover, we examine the feasibility of fishbone wells in renewable energy systems, such as geothermal energy and carbon capture, utilization, and storage (CCUS). We highlight the various benefits of fishbone wells, including reduced carbon footprint, enhanced efficiency, and increased sustainability. Finally, we discuss the challenges and limitations associated with fishbone wells in different energy systems. This review provides a comprehensive overview of the potential and challenges of fishbone wells in reducing carbon footprint and improving well performance in a wide range of energy systems. [ABSTRACT FROM AUTHOR]

When optimizing electric power system operational decisions, it is of great importance to prevent potential failures in both the system operation and the optimization algorithm. In "An Alternating Direction Method of Multipliers-Based Distributed Optimization Method for Solving Security-Constrained Alternating Current Optimal Power Flow," Gholami, Sun, Zhang, and Sun propose a novel two-level algorithm that (1) effectively prevents power system operational failures through consideration of impactful contingencies and (2) guarantees convergence when parallelized on a computing cluster with multiple nodes. Extensive numerical experiments suggest that the proposed algorithm is able to provide high-quality feasible solutions under the time limit of 10–45 minutes for various synthetic and industrial networks with up to 30,000 buses and 22,000 contingencies, comparable with the size of the U.S. power grid. In this paper, we study efficient and robust computational methods for solving the security-constrained alternating current optimal power flow (SC-ACOPF) problem, a two-stage nonlinear optimization problem with disjunctive constraints, that is central to the operation of electric power grids. The first-stage problem in SC-ACOPF determines the operation of the power grid in normal condition, whereas the second-stage problem responds to various contingencies of losing generators, transmission lines, and transformers. The two stages are coupled through disjunctive constraints, which model generators' active and reactive power output changes responding to system-wide active power imbalance and voltage deviations after contingencies. Real-world SC-ACOPF problems may involve power grids with more than 30,000 buses and 22,000 contingencies and need to be solved within 10–45 minutes to get a base case solution with high feasibility and reasonably good generation cost. We develop a comprehensive algorithmic framework to solve SC-ACOPF that meets the challenge of speed, solution quality, and computation robustness. In particular, we develop a smoothing technique to approximate disjunctive constraints by a smooth structure that can be handled by interior-point solvers; we design a distributed optimization algorithm to efficiently generate first-stage solutions; we propose a screening procedure to prioritize contingencies; and finally, we develop a reliable and parallel computation architecture that integrates all algorithmic components. Extensive tests on industry-scale systems demonstrate the superior performance of the proposed algorithms. History: This paper has been accepted for the Operations Research Special Issue on Computational Advances in Short-Term Power System Operations. Funding: The authors acknowledge the continued support of ARPA-E [Grant DE-AR0001089] and the National Science Foundation [Grant 1751747]. Supplemental Material: The e-companion is available at https://doi.org/10.1287/opre.2023.2486. [ABSTRACT FROM AUTHOR]