Longtian Zhang, Delin Wang, Jun Wang, Muhammad Shahid Mastoi, Zelin He, Mannan Hassan
{"title":"A hybrid optimization approach to evaluating load capacity in distribution networks with new energy and energy storage integration","authors":"Longtian Zhang, Delin Wang, Jun Wang, Muhammad Shahid Mastoi, Zelin He, Mannan Hassan","doi":"10.1049/rpg2.13198","DOIUrl":"https://doi.org/10.1049/rpg2.13198","url":null,"abstract":"<p>New energy can enhance the load capacity of the distribution networks, and the addition of energy storage can suppress the fluctuations caused by the uncertainty of new energy, promoting the stable load absorption of the distribution networks. This paper explored the impact of new energy and energy storage integration into distribution network load-carrying capacity and proposed a method for evaluating the load-carrying capacity of the distribution networks by improving GA-BWO with voltage adaptive control. Under the premise of considering the integration of new energy and energy storage access to the distribution networks, the impact of load increase on the status of the distribution network is derived. Constructing a distribution network load-carrying capacity evaluation indicator system with safety, flexibility, and economy, then calculating indicator weights using the AHP-EWM method and building evaluation function. Building a distribution network load carrying capacity model based on objective function and constraint conditions on this basis, utilizing bus voltage to adaptively control the balance factor and development stage of the Beluga algorithm, and introducing the mutation process of the Genetic algorithm, realize the solution of load carrying capacity. Evaluate the distribution networks with new energy and energy storage, for example, prove the improvement effect of new energy and energy storage output characteristics on the load carrying capacity of the distribution networks and provide a theoretical basis for regional planning and construction.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.13198","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143404720","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}
Alexander Kudzin, Satoshi Takayama, Atsushi Ishigame
{"title":"Energy Management Systems (EMS) for a Decentralized Grid: A Review and Analysis of the Generation and Control Methods Impact on EMS Type and Topology","authors":"Alexander Kudzin, Satoshi Takayama, Atsushi Ishigame","doi":"10.1049/rpg2.70008","DOIUrl":"https://doi.org/10.1049/rpg2.70008","url":null,"abstract":"<p>Grid decarbonization is transitioning the generation method's (GM) topology towards a distributed energy resource (DER)-centric decentralized topology. However, the control method (CM) and energy management system (EMS) are yet to decentralize, resulting in topological mismatch-related issues that pose significant operational challenges. Due to the advantages of topological synergy, CM research is moving towards decentralized topologies. However, the EMS lacks a clear development path and defined target parameters. This study investigates the interdependencies between GM, CM, and EMS topologies, determining their relationship to forecast the future trajectory of EMS research and to determine robust evaluation parameters for EMS proposals. Topological analysis revealed a strong influence of one sector on another, placing significant pressure to decentralize the EMS. Utilizing these findings, a detailed evaluation of the proposed cloud-edge, cluster, and blockchain-based EMS proposals against the established parameters revealed that blockchain-based architectures best aligned with the incoming decentralized GM and CM's limitations, requirements, and advantages, offering superior security, resilience, adaptability, and scalability. Furthermore, blockchain technology has largely overcome the regulatory barriers and technical challenges, such as communication overheads, making blockchain-based EMS the most effective and efficient choice for a next-gen EMS.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143396875","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 Zheng, Jiajie Zheng, Xin Liu, Gengyin Li, Yanhui Xu
{"title":"Small-Signal Synchronization Stability Enhancement of GFL-Based Renewable Energy Generation Using the Koopman Operator","authors":"Le Zheng, Jiajie Zheng, Xin Liu, Gengyin Li, Yanhui Xu","doi":"10.1049/rpg2.70014","DOIUrl":"https://doi.org/10.1049/rpg2.70014","url":null,"abstract":"<p>Recent reports have highlighted small-signal synchronous instability issues in grid-following converter-based renewable energy generation systems connected to weak power grids. This study introduces a Koopman operator-based approach for system state prediction and small-signal synchronization stability enhancement through a data-driven strategy. Initially, system dynamics are identified and forecasted using measured data via delay embedding and the Koopman operator, effectively transforming the original nonlinear system dynamics into a more manageable linear framework in a higher-dimensional space. Subsequently, a supplementary control loop is implemented, and control variables are calculated employing model predictive control within the elevated Koopman space. This proposed technique is independent of the ‘white box’ model structure and parameters, thereby offering adaptability to changes in operational conditions. The effectiveness of this method has been confirmed through case studies conducted on a modified IEEE 39-bus system, demonstrating its viability.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143389267","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":"An equivalent thermal model for dynamic analysis of integrated electricity and heat systems for renewable energy accommodation","authors":"Qihan Sun, Rui Wang","doi":"10.1049/rpg2.70007","DOIUrl":"https://doi.org/10.1049/rpg2.70007","url":null,"abstract":"<p>The rapid development of electric heating and combined heat and power generation for improving the level of renewable energy accommodation has necessitated integrated analysis of the electric power system and district heating networks. However, the thermal dynamic model is governed by partial differential equations related to time and space variables. Its complicated features make it hard to perform an efficient integrated analysis with renewable fluctuation. To address this issue, this paper propose an equivalent model for an accurate and concise integrated dynamic analysis. First, an analytical formulation is derived based on Laplace transform to explicitly describe the relation between the port temperature. The transform avoids the discretization in time domain, which accurately captures the thermal dynamics. On this basis, a space discretization strategy is introduced to further keep track of the dynamics. Meanwhile, the multiple cascaded space pipeline segments are aggregated to form an equivalent model for a concise analysis. Furthermore, to reduce the model complexity and computational burden of the high-order Laplacian “s” in the equivalent process, a reduction strategy is developed by preserving the low-frequency thermal dynamic feature. Then, the analytical expression of state fluctuation can be conveniently derived to analyse the embedded impact and interaction between EPS and DHN. Finally, case studies are conducted to prove the effectiveness of proposed model.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143380371","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}
Haiya Qian, Shupei Chen, Qingshan Xu, Haixiang Zang, Feng Li
{"title":"Improved Gaussian based rapid quantification of scheduling uncertainty considering source-load extreme scenario enhancement","authors":"Haiya Qian, Shupei Chen, Qingshan Xu, Haixiang Zang, Feng Li","doi":"10.1049/rpg2.70001","DOIUrl":"https://doi.org/10.1049/rpg2.70001","url":null,"abstract":"<p>Extreme events are typically low-probability occurrences with limited historical data and a high degree of unpredictability. The inherent conflict between the dispatch rationality in extreme and conventional scenarios, makes it hard for traditional methods to consider both performances. This article introduces a rapid quantification method for evaluating dispatch uncertainty in extreme scenarios within integrated energy systems. The method enhances the speed and precision of energy dispatch predictions by establishing a direct correlation between meteorological data and energy dispatch. The process begins with the collection of extreme scenarios sets. The Maximal Information Coefficient (MIC) is then employed to identify distinctive meteorological characteristics across different sets of extreme scenarios. To compensate for the lack of historical data in these scenarios, the Synthetic Minority Over-Sampling Technique (SMOTE) is utilized to augment the scenario dataset. Subsequently, the outcomes of the integrated energy system (IES) are calculated as output. Finally, Gaussian Process Quantile Regression (GPR-Q) is applied to predict dispatch uncertainty in these extreme scenarios. After comparing with existing approaches, this method can innovatively avoid the prediction error of new energy to a certain extent and quickly provide the interval probability distribution of scheduling predictions with richer information. Such results better align with the needs of real dispatch scenarios.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143380086","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":"Distributionally robust optimization of voltage fluctuations and imbalance in islanded bipolar DC microgrids","authors":"Zahra Majd, Mohsen Kalantar, Jamshid Aghaei","doi":"10.1049/rpg2.70003","DOIUrl":"https://doi.org/10.1049/rpg2.70003","url":null,"abstract":"<p>DC microgrids (DCMGs) are gaining popularity due to the rise of DC devices, increased use of solar power, and the absence of frequency and reactive power concerns. Key challenges in DCMGs include voltage fluctuations due to unpredictable changes in renewable energy resources (RERs), power flow management, and power distribution among distributed generations (DGs). To ensure the stability and reliability of DCMGs, it is crucial to maintain proper DC bus voltage levels and effectively manage power flow between different components. This paper presents a new scheduling framework for bipolar DCMGs (BPDCMGs) that simultaneously considers voltage variations and imbalances. A novel objective function focused on voltage variations is developed based on advanced load flow equations for BPDCMGs. Also, distributionally robust optimization (DRO) is utilized for RERs and load consumption uncertainties based on the Kullback–Leibler divergence metric. Following the reformulation of the multiobjective DRO problem, an optimal compromise solution is found using min–max fuzzy criteria. The proposed model has been tested on the IEEE 33 bus system, simulating an islanded BPDCMG. Detailed analysis demonstrates the model's effectiveness in managing voltage fluctuations and imbalances, with numerical results indicating over a 90% reduction in voltage fluctuations and over 40% decrease in unbalancing.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248703","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}
Mohammad Waqas Chandio, Shafiq Ur Rehman Qureshi, Laveet Kumar, Abdul Ghafoor Memon
{"title":"Energy, exergy and exergoenvironmental assessments of waste heat operated basic and modified cogeneration systems for freshwater and hydrogen production","authors":"Mohammad Waqas Chandio, Shafiq Ur Rehman Qureshi, Laveet Kumar, Abdul Ghafoor Memon","doi":"10.1049/rpg2.13180","DOIUrl":"https://doi.org/10.1049/rpg2.13180","url":null,"abstract":"<p>In this study, thermodynamic and environmental assessments of waste heat driven cogeneration systems are carried out. The cogeneration systems include basic and modified configurations of Organic Rankine cycle (ORC), Reverse osmosis (RO) unit and Proton exchange membrane (PEM) electrolyser. The ORCs are aimed at transforming waste heat into power for the operation of a reverse osmosis (RO) unit and a proton exchange membrane (PEM) electrolyser, for generation of fresh water and hydrogen, respectively. The systems were simulated in engineering equation solver (EES). Among the studied configurations and working fluids, the findings demonstrate that the ORC configuration that combines both an internal heat exchanger and a mixing chamber (HMORC) and employing Isopentane as working fluid showed optimal performance, and showcasing energy and exergy efficiencies, and sustainability index values of 19.31%, 24.63%, and 2.033, respectively. Furthermore, this setup achieves maximum flow rates of 5.211 m<sup>3</sup>/h for fresh water and 2.737 kg/h for hydrogen. Moreover, The parametric study indicates that performance of the cogeneration systems improves with rise in evaporator pressure and drop in condenser pressure. The results highlight the promise of optimised system configuration for effective waste heat recovery and sustainable resource use.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.13180","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248508","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}
Ashish Gulagi, Ayobami Solomon Oyewo, Dmitrii Bogdanov, Pamela Simamora, Agus Tampubolon, Mentari Pujantoro, Philip Godron, Fabby Tumiwa, Christian Breyer
{"title":"Accelerating the transition from coal to renewables in Indonesia to achieve a net-zero energy system","authors":"Ashish Gulagi, Ayobami Solomon Oyewo, Dmitrii Bogdanov, Pamela Simamora, Agus Tampubolon, Mentari Pujantoro, Philip Godron, Fabby Tumiwa, Christian Breyer","doi":"10.1049/rpg2.13188","DOIUrl":"https://doi.org/10.1049/rpg2.13188","url":null,"abstract":"<p>Historically heavily reliant on coal, Indonesia is at a crucial juncture to accelerate its transition to renewable energy in order to meet its net-zero goals. However, most transition pathways generally do not focus on the fast transition from fossil fuels to achieve carbon neutrality. This study compares the techno-economic feasibility of three distinctive energy transition pathways. The net-zero pathway, with an accelerated transition from coal to renewable energy, leads to a 42% reduction in annualised energy system cost and achieves carbon neutrality by 2050, compared to a pathway dependent on continued coal investments. This is enabled by the cost competitiveness of solar photovoltaics-based electrification of the energy system, supported by batteries, transmission grid expansion across the main islands, and various power-to-X routes for flexibility. Furthermore, Indonesia should carefully consider the environmental impact of large-scale palm oil cultivation and biofuel expansion. We find that the land efficiency of solar photovoltaics-based e-fuel production is much higher than cultivating oil palm for biofuel synthesis. Thus, a fast transition towards a net-zero energy system will bring various direct and indirect benefits to Indonesia.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.13188","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143111248","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":"Enhancing wind power forecasting and ramp detection using long short-term memory networks and the swinging door algorithm","authors":"Ravi Pandit, Shikun Mu, Davide Astolfi","doi":"10.1049/rpg2.70002","DOIUrl":"https://doi.org/10.1049/rpg2.70002","url":null,"abstract":"<p>Accurate prediction of short-term wind power ramps is essential for effective smart grid management. This study introduces the swinging door algorithm for ramp detection, which outperforms traditional methods by precisely identifying ramp events. Additionally, a long short-term memory (LSTM) network is evaluated against established models such as support vector machines, artificial neural networks, convex multi-task feature learning, and random forest for wind power ramp forecasting. The LSTM model demonstrates superior performance, achieving the lowest weighted mean absolute percentage error of 8.36% and normalized root mean squared error of 0.60, alongside the highest <i>R</i>-squared (<i>R</i><sup>2</sup>) value of 0.73, indicating strong predictive accuracy and correlation with observed data. Furthermore, the combined swinging door algorithm-LSTM framework improved ramp event detection by 15% compared to traditional methods, showcasing its robustness in capturing both mild and extreme ramp events. This research underlines LSTM's effectiveness in wind power forecasting, marking a notable advancement in prediction methodologies. By illustrating the strengths of LSTM and swinging door algorithm, the study contributes to the refinement of prediction models for smart grid applications, highlighting their potential to transform wind power ramp prediction and detection.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143120023","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}
Md Adil Azad, Adil Sarwar, Mohd Tariq, Farhad Ilahi Bakhsh, Shafiq Ahmad, Adamali Shah Noor Mohamed, Md Rasidul Islam
{"title":"Global maximum power point tracking for photovoltaic systems under partial and complex shading conditions using a PID based search algorithm (PSA)","authors":"Md Adil Azad, Adil Sarwar, Mohd Tariq, Farhad Ilahi Bakhsh, Shafiq Ahmad, Adamali Shah Noor Mohamed, Md Rasidul Islam","doi":"10.1049/rpg2.70005","DOIUrl":"https://doi.org/10.1049/rpg2.70005","url":null,"abstract":"<p>In scenarios of partial shading, the effectiveness of power transmission within a photovoltaic system experiences a notable decline, potentially leading to hotspots within the photovoltaic array. While incorporating bypass diodes can mitigate this challenge, it may lead to numerous power peaks along the power–voltage (<i>P</i>–<i>V</i>) characteristics, thus complicating the task of maximum power tracking. Addressing this issue, using metaheuristic algorithms for maximum power point tracking (MPPT) offers promising outcomes by circumventing convergence towards local power peaks and easing the computational strain on the microcontroller. This study presents a fresh approach to MPPT technique utilizing the proportional–integral–derivative-based search algorithm to effectively identify the MPP under varying partial shading conditions. Compared to existing methods, the proposed algorithm demonstrates superior performance in power tracking efficiency, tracking time, stability with fewer fluctuations, and achieving higher maximum power output. Evaluation against state-of-the-art algorithms like particle swarm optimization and JAYA confirms the effectiveness of the proposed MPPT technique. MATLAB/Simulink software-based analysis and its validation using real-time analysis from the typhoon based hardware-in-the-loop (HIL-402) emulator support its efficacy.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143120022","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}