IET Renewable Power Generation最新文献

{"title":"A cooperative approach for generation and lines expansion planning in microgrid-based active distribution networks","authors":"Bizhan Nemati,&nbsp;Seyed Mohammad Hassan Hosseini,&nbsp;Hassan Siahkali","doi":"10.1049/rpg2.13142","DOIUrl":"https://doi.org/10.1049/rpg2.13142","url":null,"abstract":"<p>With the growth of the load in the electricity networks, sufficient investment in the generation and lines expansion should be made in order to provide the energy needed by consumers with the lowest possible investment and operation costs. This issue is especially important in distribution networks, which are faced with the uncertainties of renewable energy generation and the development of microgrids and related issues.</p><p>In this article, the planning of generation and lines expansion has been modeled with the aim of minimizing the total costs of microgrids, based on the cooperative approach. For this purpose, a bi-level model has been developed; on the upper level, microgrids make investment decisions with a cooperative approach, and a constrained stochastic formulation has been developed with considering operational uncertainties on the lower level. Also, in this article, in order to ensure the supply of critical loads in island conditions, the self-sufficiency index is defined. Three case studies have been considered to ensure the effectiveness of the developed model. In case 1, each microgrid will be able to supply its load only by generating of its units and purchasing from the retail market. In case 2, the possibility of trading with other microgrids in a non-cooperative approach will also be available to the microgrids operators, and in case 3, microgrids can exchange energy with other microgrids in a cooperative manner. The simulation results showed that due to the possibility of using nearby microgrid resources, the cost of microgrid load supply in case 2 was reduced by 4.84% compared to case 1. Also, this cost in case 3 was reduced by 5.23% and 0.38%, respectively, compared to cases 1 and 2, due to the use of a cooperative manner in microgrid load providing.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"18 15","pages":"3355-3377"},"PeriodicalIF":2.6,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.13142","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674082","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":"Models and applications of stochastic programming with decision-dependent uncertainty in power systems: A review","authors":"Wenqian Yin,&nbsp;Yunhe Hou","doi":"10.1049/rpg2.13082","DOIUrl":"https://doi.org/10.1049/rpg2.13082","url":null,"abstract":"<p>Stochastic programming is a competitive tool in power system uncertainty management. Traditionally, stochastic programming assumes uncertainties to be exogenous and independent of decisions. However, there are situations where statistical features of uncertain parameters are not constant but dependent on decisions, classifying such uncertainties as decision-dependent uncertainty (DDU). This is particularly the case with future power systems highly penetrated by multi-source uncertainties, where planning or operation decisions might exert unneglectable impacts on uncertainty features. This paper reviews the stochastic programming with DDU, especially those applied in the field of power systems. Mathematical properties of diversified types of DDU in stochastic programming are introduced, and a comprehensive review on sources and applications of DDU in power systems is presented. Then, focusing on a specific type of DDU, that is, decision-dependent probability distributions, a taxonomy of available modelling techniques and solution approaches for stochastic programming with this type of DDU and different structural features are presented and discussed. Eventually, the outlook of two-stage stochastic programming with DDU for future power system uncertainty management is explored, including both exploring the applications and developing efficient modelling and solution tools.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"18 14","pages":"2819-2834"},"PeriodicalIF":2.6,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.13082","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142541088","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":"Integration and control of grid-scale battery energy storage systems: challenges and opportunities","authors":"Kumars Rouzbehi,&nbsp;Fazel Mohammadi,&nbsp;Juan Manuel Escaño,&nbsp;Vijay K. Sood,&nbsp;Carlos Bordons,&nbsp;Josep M. Guerrero,&nbsp;Mohammad J. Sanjari,&nbsp;Gevork. B. Gharehpetian,&nbsp;Takeshi Hatanaka,&nbsp;Raúl S. Muñoz Aguilar,&nbsp;Jahangir Hossain,&nbsp;José María Maestre","doi":"10.1049/rpg2.13136","DOIUrl":"https://doi.org/10.1049/rpg2.13136","url":null,"abstract":"&lt;p&gt;The current energy storage system technologies are undergoing a historic transformation to become more sustainable and dynamic. Beyond the traditional applications of battery energy storage systems (BESSs), they have also emerged as a promising solution for some major operational and planning challenges of modern power systems and microgrids, for example, enabling the integration of renewable energy sources by reducing their intermittency and improving the voltage, frequency, and reliability profiles of power grids. In other words, energy arbitrage, increased capacity of renewable energy resources, deferred investment in power grid components, reduced congestions, reduced carbon footprint, reduced losses, and stability stress the importance of conducting extensive and ground-breaking research and experimentation in the area of BESSs. This effort will maximize the benefits of using existing and novel BESS technologies in power systems. However, the success in the use of BESSs is driven by many technological developments and cost reductions. The current special issue enables a unique, dedicated opportunity to disseminate state-of-the-art research works in innovative aspects of BESSs from the technology and system points of view.&lt;/p&gt;&lt;p&gt;In this special issue, twenty-two articles have been received, all of which underwent peer review. Of the twenty-two originally submitted articles, seven have been accepted and the rest have been “rejected,” that is, they did not meet the IET Renewable Power Generation journal criteria for publication. Thus, the overall submissions were of high quality, which marks the success of this special issue. A brief presentation of each of the articles in this special issue follows:&lt;/p&gt;&lt;p&gt;In [&lt;span&gt;1&lt;/span&gt;], the use of a multi-port DC/DC power converter-based BESS as a multi-functional device in improving the transient stability and enhancing the power transmission capacity of high voltage direct current (HVDC) grids is analyzed. The presented control structure is an effective control framework that deals with multi-port DC/DC power converters to achieve DC voltage control and eliminate voltage and power oscillations. Also, the control scheme of the DC/DC converter can control the power flow in the intended transmission line. Analysis and time-domain simulations of the system demonstrate that the presented method gives the system an appropriate and acceptable damping improvement. The presented method simultaneously improves the transient stability of DC voltage and controls power oscillation damping within HVDC grids using BESS.&lt;/p&gt;&lt;p&gt;In [&lt;span&gt;2&lt;/span&gt;], a construction method of lithium-ion batteries' thermoelectric coupling model based on digital twin for the problems of long simulation time and low accuracy in existing models is presented. In this regard, the digital twin structure system of lithium-ion batteries is analyzed, and then the thermoelectric coupling model of the batteries is constructed on the digital twin ","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"18 15","pages":"2835-2837"},"PeriodicalIF":2.6,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.13136","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674355","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 enhanced sensitivity-based combined control method of battery energy storage systems for voltage regulation in PV-rich residential distribution networks","authors":"Farzaneh Rezaei,&nbsp;Saeid Esmaeili","doi":"10.1049/rpg2.13109","DOIUrl":"https://doi.org/10.1049/rpg2.13109","url":null,"abstract":"<p>Commercial off-the-shelf (OTS) photovoltaic systems coupled with battery energy storage units (PV-BES) are typically designed to increase household self-consumption, neglecting their potential for voltage regulation in low voltage distribution networks (LVDNs). This work proposes an enhanced sensitivity-based combined (ESC) control method for voltage regulation, using BES control as level 1 and reactive power compensation as level 2. A centralized controller manages charging/discharging intervals, while local inverters handle real-time power rates and reactive power, ensuring effective LVDN voltage regulation. The BES set points are obtained concerning the measured local bus voltage and according to enhanced sensitivity coefficients. The enhancement algorithm ensures that the full capacity of BES is utilized and that there is adequate capacity during charging and discharging time intervals. The proposed method, tested on 8-bus and 116-bus LV test feeders, outperforms OTS and an adaptive decentralized (AD) control method by completely preventing overvoltage issues, minimizing various changes in the direction of BES power, and reducing voltage deviation without significantly affecting consumers' grid dependency.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"18 14","pages":"2641-2657"},"PeriodicalIF":2.6,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.13109","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540843","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":"Imputation based wind speed forecasting technique during abrupt changes in short term scenario","authors":"Karan Sareen,&nbsp;Bijaya Ketan Panigrahi,&nbsp;Tushar Shikhola,&nbsp;Ravi Nath Tripathi,&nbsp;Ashok Kumar Rajput","doi":"10.1049/rpg2.13124","DOIUrl":"https://doi.org/10.1049/rpg2.13124","url":null,"abstract":"<p>It is tough and complex to forecast wind speed due to its intermittent and stochastic nature as well as sudden and abrupt variations in the wind speed. Further, it is required to handle the variety of scenarios e.g. cyber-attacks, unexpected power device malfunction, communication/sensor outages etc. that can cause the missing data.This paper proposes and employs a de-noising autoencoder algorithm for wind speed forecasting to ensure the handling of missing data information. At the next step, the data is processed via variational mode decomposition technique to mitigate the noise and improves the model's prediction accuracy. Furthermore, the bi-directional long-short term memory deep learning approach is tied with convolution neural network to increase prediction accuracy and anticipating the sudden/abrupt changes in wind speed accurately. Finally, actual wind speed related data is examined to scrutinize meticulousness of projected forecast methodology particularly during sudden/abrupt changes in the wind speed. The parameter indicators of the wind speed forecasting technique exhibit the capability of improved predictions under the diversified conditions.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"18 14","pages":"2751-2772"},"PeriodicalIF":2.6,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.13124","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540844","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 temperature rise calculation model of wind turbine gearbox gear considering crack fault and tooth number difference","authors":"Shiyu Lin,&nbsp;Hongshan Zhao,&nbsp;Weixin Yang,&nbsp;Xibei Li,&nbsp;Chengyan Sun","doi":"10.1049/rpg2.13145","DOIUrl":"https://doi.org/10.1049/rpg2.13145","url":null,"abstract":"<p>The crack fault of gear is usually accompanied by temperature rise. Therefore, to master the temperature characteristics of the cracked gear of the wind turbine gearbox, a temperature rise calculation model of wind turbine gearbox gear considering crack fault and tooth number difference is proposed. Firstly, the time-varying meshing stiffness model of the cracked gear considering the tooth number difference is established based on the potential energy method. Secondly, the calculation method of the meshing surface normal load of the cracked gear is deduced. Thirdly, the temperature rise calculation model of the meshing surface of the cracked gear is constructed based on Blok flash temperature theory. Finally, the data of the high-speed gear of a wind turbine gearbox in northern China is selected for simulation verification. By comparing with the finite element method, the effectiveness of the proposed method is verified. The simulation results reveal the gear temperature characteristics of the wind turbine gearbox with different crack ratios. The research can provide some theoretical support for the accurate fault diagnosis and maintenance of wind turbine gearbox, and can also be applied to the fault diagnosis of gear cracks in other mechanical structures with a large transmission ratio.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"18 15","pages":"3416-3428"},"PeriodicalIF":2.6,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.13145","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674354","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":"Improving maximum power point tracking efficiency in solar photovoltaic systems using super-twisting algorithm and grey wolf optimizer","authors":"Nassir Deghfel,&nbsp;Abd Essalam Badoud,&nbsp;Ahmad Aziz Al-Ahmadi,&nbsp;Mohit Bajaj,&nbsp;Ievgen Zaitsev,&nbsp;Sherif S. M. Ghoneim","doi":"10.1049/rpg2.13138","DOIUrl":"https://doi.org/10.1049/rpg2.13138","url":null,"abstract":"<p>This study presents a new Maximum Power Point Tracking (MPPT) approach for solar photovoltaic (PV) systems, combining the Super-Twisting Algorithm (STA) and Grey Wolf Optimizer (GWO). The STA-GWO-MPPT method improves efficiency in dynamic conditions by using STA for control and GWO for parameter optimization, enhancing stability and robustness. Performance evaluation is conducted through MATLAB/Simulink simulations and experimental validation on a small-scale test bench. Various quantitative metrics, including rise time, settling time, power production, efficiency, root mean square error (RMSE), and standard deviation (STD), are employed for assessment. Results indicate significantly faster convergence speeds for the proposed method compared to conventional MPPT techniques. Specifically, the rise time for the proposed method is 0.0129 seconds, outperforming Fuzzy Logic Control (FLC) (0.2638 seconds) and Grey Wolf Optimizer with Sliding Mode Control (GWO-SMC) (0.0181 seconds). Additionally, the proposed method exhibits superior tracking efficiency, with an average efficiency of 99.33%, surpassing FLC (96.93%) and GWO-SMC (99.19%). Moreover, it reduces power fluctuations, with an RMSE of 7.819% and STD of 6.547%, compared to FLC (RMSE: 13.471%, STD: 4.519%) and GWO-SMC (RMSE: 8.507%, STD: 6.108%). Overall, this study contributes valuable insights into enhancing MPPT efficiency in solar PV systems, with implications for both research and practical applications.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"18 15","pages":"3329-3354"},"PeriodicalIF":2.6,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.13138","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674356","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":"Optimal planning of SOP in distribution network considering 5G BS collaboration","authors":"Zihao Hou,&nbsp;Chao Long,&nbsp;Qi Qi,&nbsp;Xiangjun Liu,&nbsp;Kejia Wang","doi":"10.1049/rpg2.13131","DOIUrl":"https://doi.org/10.1049/rpg2.13131","url":null,"abstract":"<p>The flexibility of soft open point (SOP) in spatial power regulation enhances the distribution network's (DN) integration of large-scale renewable energy sources. However, the high cost of SOP and its limited capability for temporal power regulation impede its widespread adoption. Given the rapid expansion of 5G base stations (BSs), utilizing their energy storage to participate in DN planning and operation optimization provides a promising solution. Therefore, this paper proposes an optimal planning method of SOP in DN, considering collaborations with 5G BSs. The objective is to enhance DN’s power regulation in both temporal and spatial dimensions, while minimizing the investment cost of SOP and fully utilizing the unused capacity in base station energy storage (BSES). Firstly, the flexible regulation models of SOP and 5G BS are established, with the real-time dispatchability of BSES formulated. Then, a bi-level optimization model is proposed, where the planning layer aims to minimize the total cost, while the operational layer aims to decrease the average voltage deviation. Additionally, an improved Shapley value method based on interactive power is developed for benefit allocation, which enhances the engagement of 5G BSs to participate in DN regulation. The effectiveness of proposed method is validated by simulation results.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"18 15","pages":"3040-3052"},"PeriodicalIF":2.6,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.13131","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674053","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":"Power quality improvement of grid-connected solar power plant systems using a novel fractional order proportional integral derivative controller technique","authors":"Hariprabhu Manoharan,&nbsp;Sundararaju Karuppannan,&nbsp;Kumar Chandrasekaran,&nbsp;Sourav Barua","doi":"10.1049/rpg2.13128","DOIUrl":"https://doi.org/10.1049/rpg2.13128","url":null,"abstract":"<p>Recently, there has been a push to integrate renewable energy system (RES) into grid-connected load system in enhancing reliability and reducing losses. However, integrating these systems introduces power quality (PQ) issues, especially with non-linear, critical, and imbalanced loads. Addressing this, a hybrid mantis search-reptile search algorithm (HMS-RSA) combined with a unified power quality conditioner (UPQC) to mitigate PQ problems related to current and voltages in RES systems. In other words, the UPQC, enhanced by fractional order proportional integral derivative controller parameters tuned using the proposed HMS-RSA assists in enhancing the power quality. The approach has been validated by connecting a non-linear load to the system, which typically creates PQ issues. The proposed method is implemented in MATLAB/Simulink and their performance is analysed in three scenarios, such as sag, swell, and disturbance, and the total harmonic distortion is evaluated to quantify improvements in PQ. Finally, the proposed method is compared with existing approaches, such as ant colony optimization (ACO), artificial bee colony optimization (ABC), and bacterial foraging optimization (BFO). The method also outperforms ACO, ABC, and BFO in terms of convergence speed and effectiveness in mitigating PQ issues.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"18 15","pages":"3268-3284"},"PeriodicalIF":2.6,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.13128","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674201","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":"Fast stability enhancement of inverter-based microgrids using NGO-LSTM algorithm","authors":"Kai Pang,&nbsp;Zhiyuan Tang","doi":"10.1049/rpg2.13137","DOIUrl":"https://doi.org/10.1049/rpg2.13137","url":null,"abstract":"<p>To improve the stability of the inverter-based microgrid (MG), this paper employs a novel data-driven based method to coordinately adjust control parameters of inverters in a fast local manner. During the design process, an offline eigenvalue based optimization problem that is used to calculate the optimal control parameters under various operating conditions is first constructed. In order to reduce reliance on full system information, a feature selection algorithm is utilized to extract the most relevant local measurements that influence the adjustment of each control parameter. Then, regarding local measurements as input variables and optimal control parameters as output variables, based on northern goshawk optimization (NGO) and long short-term memory (LSTM) network, a novel deep learning algorithm is proposed to train the local parameter adjustment model (LPAM) by learning the mapping relationship between them. During the application, to guarantee the stability of MG all the time, a security region based shielding mechanism is developed, where the improper control parameter adjustment will be replaced by a safe one. The case study indicates that the proposed algorithm has better mapping accuracy than traditional LSTM neural networks and also faster calculation speed than the traditional offline optimization-based method. The effectiveness and advantages of the proposed method are demonstrated in a modified 9-bus MG.</p>","PeriodicalId":55000,"journal":{"name":"IET Renewable Power Generation","volume":"18 15","pages":"3317-3328"},"PeriodicalIF":2.6,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rpg2.13137","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674052","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}