{"title":"Energy Management of V2G-Containing Multiource Microgrid Cluster Based on Two-Layer Hybrid Game","authors":"Mei Li, Zhengde Yu","doi":"10.1155/etep/6795794","DOIUrl":"https://doi.org/10.1155/etep/6795794","url":null,"abstract":"<div>\u0000 <p>With the large-scale entry of electric vehicles into the grid, the impact on the new power system with new energy as the main status is gradually expanding. Utilizing V2G technology to make vehicle–network interaction, a two-layer hybrid game energy management transaction method for multisource microgrid clusters is proposed. The upper layer constructs a microgrid group transaction model containing an energy management system based on a cooperative game; the lower layer constructs a master–slave game model with each microgrid as the leader and its interest as the objective function, and the follower EV aggregator adjusts the charging and discharging time according to the net power to strive for its maximum interest. The model is optimally solved by the CPLEX solver through simulation cases, and the results verify the effectiveness and superiority of the proposed two-layer hybrid game model.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/6795794","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143741322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Akanksha Shukla, Mohammed Imran, Kusum Verma, Hitesh R. Jariwala
{"title":"Hybrid Control DC Microgrid Embedded With BESS and Multimode Adaptive Standalone PV","authors":"Akanksha Shukla, Mohammed Imran, Kusum Verma, Hitesh R. Jariwala","doi":"10.1155/etep/3773958","DOIUrl":"https://doi.org/10.1155/etep/3773958","url":null,"abstract":"<div>\u0000 <p>The advantages of DC distribution over AC distribution, combined with greater penetration of photovoltaic (PV) systems, have enhanced the popularity of DC microgrids. With the intermittency of a PV system, power management in a DC microgrid is an issue, but it can be addressed by using a battery energy storage system (BESS) as a backup. The goal is to maintain a constant DC-link voltage while balancing demand and supply. The study establishes a hybrid control approach for a DC microgrid involving PV, BESS, and DC loads, utilizing both the PV system and the BESS. PV will operate as a primary voltage regulator, making BESS a secondary control, resulting in decreased battery consumption and extended battery life. To achieve this objective, a flexible power point tracking (FPPT) algorithm is suggested, which requires the PV to track the load profile by adaptively modifying its PV power output. The effectiveness of the devised control method is tested by running time domain simulations on several case studies. To assess the adapted system’s tolerance to seasonal changes, k-means clustering is utilized to generate a cluster of irradiance profiles. These clustering solar irradiance and load profiles were simulated for 24 h to illustrate the resilience of the devised control method.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/3773958","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143707499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimizing Power Flow in Photovoltaic-Hybrid Energy Storage Systems: A PSO and DPSO Approach for PI Controller Tuning","authors":"Samira Heroual, Belkacem Belabbas, Yasser Diab, Mohamed Metwally Mahmoud, Tayeb Allaoui, Naima Benabdallah","doi":"10.1155/etep/9958218","DOIUrl":"https://doi.org/10.1155/etep/9958218","url":null,"abstract":"<div>\u0000 <p>This paper focuses on developing power management strategies for hybrid energy storage systems (HESSs) combining batteries and supercapacitors (SCs) with photovoltaic (PV) systems. The proposed control scheme is based on proportional-integral (PI) controllers optimized with particle swarm optimization (PSO) and duplicate particle swarm optimization (DPSO) algorithms. The aim is to reduce peak current and the energy management system’s response time while enhancing the system’s stability during the charging and discharging of the HSS under various operating conditions. A comparative study with other tuning methods is presented to demonstrate the effectiveness of the proposed DPSO algorithm in particle duplication, population diversity, and the convergence speed toward the global optimum, enhancing the overall system’s performance. The results demonstrate the feasibility and robustness of the PI − DPSO in providing quick and accurate responses even under variable load, variable solar irradiations, and variable temperature, thus enhancing the dynamic response of the SC and reducing battery stress, resulting in a longer lifespan for the HESS.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/9958218","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143689238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimizing Virtual Power Plant Operations in Energy and Frequency Regulation Reserve Markets: A Risk-Averse Two-Stage Scenario-Oriented Stochastic Approach","authors":"Asad Mujeeb, Zechun Hu, Jianxiao Wang, Rui Diao, Likai Liu, Zhiyuan Bao","doi":"10.1155/etep/6640754","DOIUrl":"https://doi.org/10.1155/etep/6640754","url":null,"abstract":"<div>\u0000 <p>The intermittent nature of distributed energy resources (DERs) has introduced significant challenges in power system operations, particularly in terms of flexibility, efficiency, and market participation. Aggregating DERs into a virtual power plant (VPP) offers a promising solution to these challenges, but it requires effective strategies to manage the inherent uncertainties and optimize operations across multiple energy markets. This paper develops an optimal bidding strategy for an aggregated multienergy virtual power plant (MEVPP) participating in both the day-ahead (DA) energy market and the frequency regulation reserve market (FRRM). To effectively address these uncertainties, we propose a two-stage scenario-oriented stochastic optimization model that aims to maximize revenue and minimize operational costs by incorporating risk management strategies. Then, a novel fast forward selection and simultaneous reduction (FFS&SR) algorithm is proposed, which efficiently generates and refines scenarios, ensuring computational feasibility without compromising accuracy. The proposed VPP’s decision-making problem considers the VPP’s risk-averse nature, employing the conditional value at risk (CVaR) metric as a risk-aversion parameter. Simulation results conducted over a 24-h planning horizon validate the model’s performance, exhibiting superior performance in the bidding market scenarios. Furthermore, the numerical findings compare the risk-neutral VPP framework with the proposed risk-sensitive VPP strategy, revealing a trade-off between expected profit and CvaR, indicating that as the risk aversion parameter escalates, expected profits decline while CVaR value rises, underscoring the importance of risk management in VPP optimization.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/6640754","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143689022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Le Chi Kien, Truong Van Hien, Hoang Do Ngoc Tram, Thai Dinh Pham
{"title":"Optimal Integration of Renewable Energy–Based Distributed Generation Units in Radial Distribution System","authors":"Le Chi Kien, Truong Van Hien, Hoang Do Ngoc Tram, Thai Dinh Pham","doi":"10.1155/etep/8694811","DOIUrl":"https://doi.org/10.1155/etep/8694811","url":null,"abstract":"<div>\u0000 <p>Determining the optimal integration of renewable energy–based distributed generation units (DGUs) in electric distribution systems brings many positive technical and economic impacts and contributes significantly for improving the performance of the distribution system. The suitable installation of DGUs is always a challenging problem because the output behaviors of DGUs, specifically photovoltaic units (PVUs) and wind turbine units (WTUs) are strongly affected by stochastic natural conditions. In this study, the main purpose is to address optimal nonlinear constrained problems with three targets in the multiobjective function (MOF) for minimizing (1) total power loss, (2) voltage deviation, and (3) the cost of purchasing energy from the main grid considering the uncertainties of solar irradiance and wind speed in the actual region in Binh Thuan Province, Vietnam. This paper solves three problems related to optimal connection of DGUs in the distribution system considering constant power generation and consumption with unity power factor (PF) (Problem 1), constant power generation and consumption with optimal PF (Problem 2), and time-varying power generation and consumption with optimal PF (Problem 3). Besides, this research also proposes a novel meta-heuristic optimization algorithm called revised coyote optimization algorithm (RCOA) for addressing the optimization problems of the simultaneous integration of DGUs in IEEE 69-bus radial distribution system. The obtained results in above three problems are compared with the original and published methods to demonstrate the superior economic and technical benefits of the proposed method.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/8694811","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143632789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Waseem Akram, Saneea Zahra, Safdar Raza, Sumayya Bibi, Mohammad R. Altimania, Hafiz Mudassir Munir, Ievgen Zaitsev
{"title":"A Battery-Based Energy Management Approach for Weak Microgrid System","authors":"Waseem Akram, Saneea Zahra, Safdar Raza, Sumayya Bibi, Mohammad R. Altimania, Hafiz Mudassir Munir, Ievgen Zaitsev","doi":"10.1155/etep/9951673","DOIUrl":"https://doi.org/10.1155/etep/9951673","url":null,"abstract":"<div>\u0000 <p>The conversion loss is the significant challenge due to the usage of multiple converters at different stages of a power distribution system. These stages include distribution of energy, energy storage, grid integration, and energy demand management. The conversion losses at each stage adversely impacts the performance of the power system, especially toward energy conservation if efforts are made toward it. To address this, a novel microgrid (MG) energy management scheme is introduced to mitigate conversion losses in distribution systems specifically under weak MG environment. This scheme employs a sophisticated control algorithm that assesses the potency of power available on the DC side before initiation of the conversion process. Conversion is executed only when available power meets the specific level. Otherwise, it is diverted and stored in a battery bank to prevent high losses. In this scenario, the AC loads are supplied by the utility grid while solar and battery bank catered the DC loads. The conversion process is selectively activated, prioritizing its use during indispensable circumstances. By optimizing conversion losses, this work reduces the energy prices by 1.95%. The proposed scheme guarantees economical deployment and affordability because of its effectiveness in a weak MG environment, thus promoting sustainable energy resources.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/9951673","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143622575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Study on a Trans-Inverse High Gain SEPIC-Based DC-DC Converter With ZCS Characteristics for Photovoltaic Applications","authors":"Mahdi Elmi, Mohamad Reza Banaei, Hadi Afsharirad","doi":"10.1155/etep/3760078","DOIUrl":"https://doi.org/10.1155/etep/3760078","url":null,"abstract":"<div>\u0000 <p>This paper aims to propose, study, and implement a non-isolated trans-inverse high step-up SEPIC-based DC-DC converter for photovoltaic applications. To increase the output voltage level, the presented configuration utilizes a three-winding coupled inductor and an improved voltage multiplier cell. However, unlike other coupled inductor-based DC-DC structures, the voltage gain could be enhanced by raising and lowering the secondary and tertiary winding turns ratio, respectively. Furthermore, a passive voltage clamp is employed to reduce the voltage stress on the switch and recover the energy stored in the leakage inductance of the coupled inductor. Hence, a switch with low RDS-ON could be used. Thanks to the soft switching performance of all diodes, their reverse recovery problem is eliminated. The outstanding merits of the converter such as continuous input current and high efficiency make the presented structure a promising solution for photovoltaic applications. In the end, the proposed converter is compared to different types of DC-DC converters to prove its advantages over the converters designed before. To confirm the converter’s performance and theoretical analysis, a 200 W laboratory prototype is implemented that steps up an input voltage of 25 V to an output voltage of 400 V at the switching frequency of 50 kHz. Experimental results are illustrated. At the end, the experimental results are presented to validate the analyses conducted.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/3760078","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143622576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Advanced Solar Irradiance Forecasting Using Hybrid Ensemble Deep Learning and Multisite Data Analytics for Optimal Solar-Hydro Hybrid Power Plants","authors":"Sudharshan Konduru, Naveen C., Jagabar Sathik M.","doi":"10.1155/etep/6694504","DOIUrl":"https://doi.org/10.1155/etep/6694504","url":null,"abstract":"<div>\u0000 <p>Solar energy with hydropower power plants marks a significant leap forward in renewable energy innovation. The combination ensures a consistent power supply by merging the fluctuations of solar energy with the predictable storage provided by hydropower. This research aims to predict high solar irradiance on hydropower plants to maximize active power generation. A novel hybrid decomposed residual ensembling model for deep learning (SBL<sub>TSR</sub>A<sub>R</sub>W) using models such as autoregressive integrated moving average (ARIMA) and seasonal-trend decomposition using loess (STL) along with prediction and optimization models such as Bidirectional LSTM (Bi-LSTM), and Whale Optimization Algorithm (WOA) methods are used to predict the irradiances. Various forecasting methods, including STL-Bi-LSTM, SBL<sub>TS</sub>A<sub>R</sub>, SBL<sub>T</sub>A<sub>RS</sub>, and SBL<sub>TSR</sub>A<sub>R</sub> models, are assessed to determine their effectiveness in predicting solar radiation. The results show the accuracy of the proposed model, with RMSE and MAE values of 1.85 W/m<sup>2</sup> and 1.31 W/m<sup>2</sup>, respectively. The proposed SBL<sub>TSR</sub>A<sub>R</sub>W model results are more accurate than the Bi-LSTM, STL-Bi-LSTM, SBL<sub>TS</sub>A<sub>R</sub>, SBL<sub>T</sub>A<sub>RS</sub>, and SBL<sub>TSR</sub>A<sub>R</sub> models, with RMSE value reductions of 517%, 217%, 151%, 98%, and 1%, respectively.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/6694504","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Resilient Deep Learning Approach for State Estimation in Distribution Grids With Distributed Generation","authors":"Ronald Kfouri, Harag Margossian","doi":"10.1155/etep/2734170","DOIUrl":"https://doi.org/10.1155/etep/2734170","url":null,"abstract":"<div>\u0000 <p>State estimation is a challenging problem, particularly in distribution grids that have unique characteristics compared with transmission grids. Conventional methods that solve the state estimation problem at the transmission level require the grid to be observable, which does not apply to distribution grids. To make the distribution grid observable, researchers resort to pseudomeasurements, which are inaccurate. Also, the high integration of renewable energy introduces uncertainty, making the Distribution System State Estimation (DSSE) problem even more complex. This work proposes a deep neural network approach that solves the DSSE problem in unobservable distribution grids without employing erroneous pseudomeasurements. We create a dataset that emulates real-life scenarios of diverse operating conditions with distributed generation. We then subject the neural network to multiple test scenarios featuring noisier measurements and bad data to evaluate the robustness of our algorithm. We test our approach on three networks. Results demonstrate that our method efficiently solves the DSSE problem—which cannot be solved using conventional methods—and detects and mitigates bad data, further enhancing the reliability of the state estimation results.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/2734170","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143530159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Danyal Ghasemi, Jafar Siahbalaee, Mohammad Divandari
{"title":"Optimal Control Strategy of Five-Phase PMSMs in a Wide Speed Range Using Third Harmonics","authors":"Danyal Ghasemi, Jafar Siahbalaee, Mohammad Divandari","doi":"10.1155/etep/4373929","DOIUrl":"https://doi.org/10.1155/etep/4373929","url":null,"abstract":"<div>\u0000 <p>The utilization of the third current harmonic in five-phase motors offers the potential to enhance their performance. This paper presents a comprehensive theory for optimally controlling five-phase permanent magnet synchronous motors (PMSMs) across all speeds, considering both motor and inverter limitations. A three-region speed profile is defined based on motor and inverter constraints, with precise relationships derived for determining region boundaries. Distinct control strategies are proposed for each region: maximum torque per ampere (MTPA) for copper loss minimization and maximum voltage–maximum current (Max V–Max I) and maximum power per voltage (MPPV) for core loss minimization. Optimal components of the first and third current harmonics are calculated for each strategy, serving as reference values for control methods such as FOC, DTC, or MPC in motor drives. Analysis results indicate that the proposed strategies significantly increase electromagnetic torque and output power and decrease power loss of five-phase PMSM motors.</p>\u0000 </div>","PeriodicalId":51293,"journal":{"name":"International Transactions on Electrical Energy Systems","volume":"2025 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/etep/4373929","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143535801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}