IET Renewable Power Generation最新文献

{"title":"Optimising Wind Energy Site Selection in Northern Afghanistan: An Integrated Analysis of Analytical Hierarchy Process and Genetic Algorithms","authors":"Abdul Baser Qasimi,&nbsp;Areej Al Bahir,&nbsp;Ara Toomanian,&nbsp;Vahid issazade,&nbsp;Najmeh Neysani Samany","doi":"10.1049/rpg2.70032","DOIUrl":"https://doi.org/10.1049/rpg2.70032","url":null,"abstract":"<p>The present work evaluates wind energy capabilities in different provinces in Afghanistan using analytical hierarchy process (AHP) and genetic algorithms (GA) techniques. AHP analysis used Expert Choice software to achieve the best criterion weights according to life cycle assessment results involving major criteria such as wind speed, slope, elevation, climate zone, air pressure and vicinity to infrastructure. The study further shows that the northwestern provinces, namely Kunduz, Balkh, Jawzjan, and Faryab, have the greatest potential in large wind power plants because of cost influences and wind speed. Altogether, these provinces would be expected to produce roughly 26.3 GWh of renewable energy per year, strongly supporting Afghanistan's renewable energy goals. On the low side, provinces like Badakhshan and Takhar have small sizing capacity with maximum suitability for localised and off-grid applications; Badakhshan has an area of 432 km² within a total of 2292 km²; Takhar has 217.7 km² and has limited potential for utility-scale connected wind farms. However, the GA method, which is known for its accuracy, supports the AHP result for Badakhshan but depicts lower suitability for Takhar. The GA unequivocally points out Kunduz medium-suitable areas and sporadic potentiality levels in Samangan and Baghlan Province. A total of 918 km² of the Kunduz area is potential, while 854 km² are moderately potential for wind energy. The province of Sar-e-Pul has identified the Southern region as a potential wind energy source-524 km². In total, 1816 km² provinces of Balkh and Jawzjan together have the largest wind energy potential of about 14.3 GWh per annum. Combined with the estimate, the total harvestable wind energy in the study area is 46.6 GWh. The results of this paper are important for policymakers and stakeholders to select appropriate sites for wind farm development, promote the sustainable energy agenda, and meet the increasing energy demands in Afghanistan.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70032","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143741524","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":"Comparative Study of Optimisation Algorithms for Cloud Electric Vehicle-to-Grid Battery Operations in Microgrids With High Penetration of Solar Photovoltaics","authors":"Thanh Tung To,&nbsp;Solmaz Kahourzade,&nbsp;Amin Mahmoudi","doi":"10.1049/rpg2.70017","DOIUrl":"https://doi.org/10.1049/rpg2.70017","url":null,"abstract":"<p>This paper proposes optimisation techniques for the operations of cloud electric vehicle-to-grid battery (CEVB) in microgrids with high penetration of solar photovoltaics (PVs). It thoroughly scrutinises popular methods such as gradient descent (GD), as well as three heuristic methods, including pattern search (PS), particle swarm optimisation, and genetic algorithms. Addressing the limitations of these methods, such as local optimality and constraint violations, is achieved through intensive experimentation, utilising stochastic initialisation and a hybrid heuristic-GD multiple-run strategy. These experiments also investigate the effects of heuristic algorithm parameter settings on the optimisation results, identify optimal parameters for each heuristic-GD method, and assess their effectiveness in handling uncertainties in CEVB operational model inputs (solar irradiance, electricity price, and electric vehicle [EV] power demand). Evaluations conducted using actual operational data from an EV charging station in South Australia demonstrate that all proposed methods can achieve global optimal results in fewer than 100 runs with appropriate parameter settings. Scalability tests were conducted to validate the method's feasibility for larger systems, offering valuable insights into computation times as the number of CEVBs grows. The proposed methods demonstrate robustness in addressing uncertainties in electricity prices and EV power demand, ensuring reliable and adaptable performance across various scenarios.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143726781","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":"The Importance of the Steel Price in Offshore Wind","authors":"Laura Castro-Santos,&nbsp;Isabel Lamas-Galdo,&nbsp;David Cordal Iglesias,&nbsp;L. Piegari,&nbsp;P. Tricoli,&nbsp;Almudena Filgueira-Vizoso","doi":"10.1049/rpg2.70029","DOIUrl":"https://doi.org/10.1049/rpg2.70029","url":null,"abstract":"<p>The price of some raw materials has been increased during the last 2 years. Firstly, the COVID pandemic and, secondly, the Ukraine-Russia war, have bringing a lot of economic consequences for the majority of the world's economies. The main purpose of the present paper is to analyse the importance of steel price in offshore wind. In this context, several economic indicators usually considered in energy industry, such as LCOE (levelized cost of energy) will be calculated. The method was carried out for a floating offshore wind farm composed by semisubmersible substructures and located in the main Atlantic Islands of Spain: the Canary Islands. Moreover, several cases of study with different prices of steel have been calculated in order to know the influence of this parameter in the economics of an offshore wind farm. Results of the three cases of study considered the highest economic variations are related to the internal rate of return and LCOE, with values of −7.6% and 5.4% respectively. Therefore, variations on the price of steel during last 3 years has repercussion on decisions about renewable energy, particularly floating offshore wind, where different types of materials for offshore platforms are being tested (steel or concrete, for instance).</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70029","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143689558","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":"Accurate Impedance Measurement Technology for Power Line Communication Considering Noise Interference","authors":"Yu Zhou,&nbsp;Fan Gao,&nbsp;Yue Li,&nbsp;Zhen Zhang,&nbsp;Chao Zhou","doi":"10.1049/rpg2.70028","DOIUrl":"https://doi.org/10.1049/rpg2.70028","url":null,"abstract":"<p>The impedance of power line channels is related to various factors such as frequency, time, connection location, load type, and power grid structure. The impedance mismatch will reduce the coupling efficiency and transmission efficiency of signals, and seriously affect the quality of power line communication. Therefore, accurate measurement of power line channel impedance and analysis of impedance characteristics are of great significance for improving the reliability of power line communication. In this paper, an improved ratio method considering the noise interference is proposed. In the method, the original generation method of sweep frequency signals is changed to one-time multi frequency and variable amplitude injection signals. Based on real-time signal processing technology, the voltage information at all tested frequency points is measured at once, including amplitude and phase. Through digital signal processing technology, the influence of noise is weakened, and the impedance amplitude and phase of all tested frequency points are accurately calculated. By the method, the requirements of the measurement circuit are simplified and the frequency range of impedance measurement is expanded to 100 kHz to 12 MHz. Finally, the impedance characteristics on the concentrator side and the user meter side are measured, laying the foundation for impedance matching design and improving power line communication quality.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70028","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143689557","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 Distributionally Robust Post-Disaster Recovery Method for Distribution Networks Considering Line Repair and Spatiotemporal Dynamic Scheduling of Mobile Energy Storage","authors":"Mengqi Huang,&nbsp;Yonghui Li,&nbsp;Jun Yang,&nbsp;Mengke Wang,&nbsp;Wangang He,&nbsp;Issarachai Ngamroo","doi":"10.1049/rpg2.70027","DOIUrl":"https://doi.org/10.1049/rpg2.70027","url":null,"abstract":"<p>Extreme disasters often cause large-scale power outages in distribution networks due to damaged lines, significantly impacting system reliability. Current research faces several challenges: traditional methods fail to fully consider the uncertainty of line repair time, existing robust optimization methods encounter difficulties in solving problems involving mobile energy storage (ME), and simple symmetric intervals cannot accurately describe the uncertainty of repair time. To address these challenges, this paper proposes a two-stage distributionally robust post-disaster recovery model that optimizes the connection location of ME in the first stage and adjusts the output of resources such as ME in the second stage to minimize load loss. A Weibull distribution is introduced to fit the repair time of damaged lines, while confidence intervals replace simple symmetric fluctuation intervals to handle the uncertainty of line repair time, improving prediction credibility. The column and constraint generation algorithm is applied to decompose and solve the model. Case studies demonstrate the proposed method's efficacy in maintaining power supply during recovery by simultaneously addressing repair time uncertainty and PV generation variability. At least 26% of the load can be in service even under worst-case scenarios.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143689309","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":"Adaptive Dual Droop for Active Power-Frequency Control in Power System With Photovoltaic System","authors":"Arash Rostami,&nbsp;Amir Khorsandi","doi":"10.1049/rpg2.70026","DOIUrl":"https://doi.org/10.1049/rpg2.70026","url":null,"abstract":"<p>As the penetration of photovoltaic systems (PVs) increases, the ability to control network frequency becomes limited. Traditional PV control typically relies on maximum power point tracking (MPPT); however, in MPPT mode, PVs cannot contribute to frequency control. By implementing droop control on PVs, it becomes feasible for them to participate in frequency regulation. This research introduces a dual droop control approach that focuses on both slow and fast frequency responses to ensure frequency stability and provide a fast response to frequency deviations. Additionally, an adaptive droop coefficient (ADC) is introduced via a fuzzy logic controller, which is incorporated into the dual droop control system to enhance its effectiveness. The ADC provides more flexibility for PVs by providing an appropriate coefficient based on frequency conditions during both fast and slow frequency responses. Additionally, the power from the PV systems is divided into two components: the usable maximum power point and the stored power. Suitable algorithms are presented to facilitate the participation of these two active power components in achieving power balance. This approach enables the control system to maintain active power balance in response to sudden changes for effective frequency control. The proposed control system is simulated in MATLAB/Simulink.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143638652","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":"Benders Decomposition-Based Power Network Expansion Planning According to Eco-Sizing of High-Voltage Direct-Current System, Power Transmission Cables and Renewable/Non-Renewable Generation Units","authors":"Kazem Emdadi,&nbsp;Sasan Pirouzi","doi":"10.1049/rpg2.70025","DOIUrl":"https://doi.org/10.1049/rpg2.70025","url":null,"abstract":"<p>High-voltage DC (HVDC) systems are taken into consideration while simultaneous generation and transmission expansion planning in this paper. It is based on the placement and sizing of generating units, AC transmission cables, and HVDC systems. Within HVDC system, reactive power of transmission network may be managed by AC and DC substations equipped with AC/DC and DC/AC power electronic converters, respectively. Plan takes the form of a bi-stage optimization, where the upper level aims to minimize yearly cost of constructing the items stated, while taking into account constraints related to size and investment budget. Minimization of yearly planning costs of generating units and the cost of energy losses are taken into consideration in the lower-level problem. Linearized AC power flow model and the operating parameters of both non-renewable and renewable generating units bind the goal function. To simulate the uncertainty of demand and renewable electricity, stochastic optimization is used. Utilizing the Benders decomposition approach, problem is solved and the best solution is extracted. Numerical outcomes derived from several cases demonstrate plan's potential to enhance transmission network's technical and economic features. In comparison to network power flow studies, the economic (operating) status of the network is improved by around 10% (10–40%).</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143632793","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":"Fuzzy-Based Multi-Objective Optimal Allocation of Capacitors and DSTATCOMs to Minimize Installation Cost and Power Loss and Improve Voltage Profile by Optimal Control of Fuzzy Parameters","authors":"Ali Solati,&nbsp;Ali Asghar Shojaei,&nbsp;Sepehr Soltani,&nbsp;Seyed Ali Hosseini","doi":"10.1049/rpg2.70018","DOIUrl":"https://doi.org/10.1049/rpg2.70018","url":null,"abstract":"<p>Reducing power losses and improving voltage profile are among the most important concerns of the distribution network operators. Since the cause of the mentioned challenges is the lack of reactive power, these problems can be solved by installing reactive power compensators such as capacitors and DSTATCOMs. On the other hand, considering that the installation of reactive power resources based on just a few peak hours causes overdesigned and uneconomical project, a solution should be provided for the optimal allocation of these resources based on all hours of the study period. In this paper, a method based on fuzzy logic is developed to optimally allocate the reactive power compensators by considering the amount of network load in all hours of the study period. Another unique feature of the developed method is that the simulation time is very short due to the lack of need to run multiple load flows to calculate network variables. Therefore, as the first innovative contribution, the optimal allocation of capacitors and DSTATCOMs is done using a developed method based on standard fuzzy logic. Then, as the second contribution, fuzzy membership function parameters have been optimized and the developed method has been improved. The results showed the efficiency of the developed method to optimally allocate capacitors and DSTATCOMs in distribution network. Optimizing the fuzzy membership functions parameters reduced the total costs (improved the voltage profile) by 2.4%, 4.4% and 6% (by 1.3%, 3% and 3.7%), respectively, by installing one, two and three capacitors and DSTATCOMs.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629853","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":"RETRACTION: Probability Modelling of Storage Based-Smart Energy Hub Considering Electric Vehicles Charging Stations Performance and Demand Side Management","authors":"","doi":"10.1049/rpg2.70024","DOIUrl":"https://doi.org/10.1049/rpg2.70024","url":null,"abstract":"<p><b>RETRACTION</b>: S. S. M. Javid, G. Derakhshan, S. M. Hakimi: Probability modelling of storage based-smart energy hub considering electric vehicles charging stations performance and demand side management. <i>IET Renewable Power Generation</i> 17, 3221–3239 (2023). https://doi.org/10.1049/rpg2.12839</p><p>The above article, published online on 29^th August 2023 in Wiley Online Library (wileyonlinelibrary.com) has been retracted by agreement between the journal's Editor-in-Chief; David Infield; the Institution of Engineering and Technology; John Wiley &amp; Sons Ltd.; and the authors.</p><p>Since publication, the authors have alerted the journal about substantial text overlap between the article and an unpublished source of a different research group. Following an investigation, the IET and the journal have verified a substantial text overlap. Accordingly, the article is retracted. The authors apologise for the oversight.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70024","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594874","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 Cyber Insurance and Defense for Multi-Energy Systems Under False Data Injections","authors":"Alexis Pengfei Zhao,&nbsp;Chenghong Gu,&nbsp;Zhaoyao Bao,&nbsp;Xi Cheng,&nbsp;Mohannad Alhazmi","doi":"10.1049/rpg2.70011","DOIUrl":"https://doi.org/10.1049/rpg2.70011","url":null,"abstract":"<p>This article introduces a novel cyber insurance planning model specifically designed to enhance the resilience of information and communication technology (ICT)-integrated multi-energy systems (MES) against cyber threats, particularly false data injection (FDI) attacks. The proposed hierarchical cyber insurance planning model (HCIPM) offers an integrated approach to managing the dual challenges of financial risk and operational disruptions caused by sophisticated cyber-attacks. The model is built upon a two-stage hierarchical optimization framework: the first stage determines the optimal allocation of cyber insurance to minimize costs while ensuring adequate risk coverage, and the second stage focuses on real-time operational defense strategies, such as load shedding and resource management, to mitigate the impact of cyber incidents. A key innovation of the HCIPM is its incorporation of a distributionally robust optimization (DRO) methodology, combined with Conditional Value at Risk (CVaR), to effectively handle the uncertainties inherent in FDI attack scenarios. By representing extreme events and their probabilities, this framework ensures robust decision-making under high uncertainty. Extensive simulations conducted on a 33-20 node distribution system demonstrate the efficacy of the proposed model. Results indicate that the HCIPM achieves a 35% reduction in load shedding costs and a 28% improvement in resilience metrics, such as system recovery time and operational continuity, compared to traditional approaches. Additionally, the model demonstrates a significant decrease in financial losses attributable to cyber-attacks, with a 40% reduction in economic damages across high-risk scenarios. The findings underline the model's capability to not only reduce operational costs but also enhance system stability and resilience under diverse attack scenarios. By integrating financial mechanisms such as cyber insurance with technical defenses, the HCIPM represents a comprehensive solution for managing cyber risks in critical infrastructure. This research bridges the gap between operational resilience and financial protection, offering a pioneering framework for future applications of cyber insurance in power systems and other critical infrastructures. The proposed model provides a scalable and adaptable strategy, making it an invaluable tool for utilities and policymakers in their efforts to safeguard modern energy systems against evolving cyber threats.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"19 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.70011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143535995","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}