International Journal of Electrical Power & Energy Systems最新文献

{"title":"Variable droop gain frequency supporting control with maximum rotor kinetic energy utilization for wind-storage system","authors":"Wenbo Li ,&nbsp;Yujun Li ,&nbsp;Jiapeng Li ,&nbsp;Yang Zhang ,&nbsp;Xiqiang Chang ,&nbsp;Zhongqing Sun","doi":"10.1016/j.ijepes.2024.110289","DOIUrl":"10.1016/j.ijepes.2024.110289","url":null,"abstract":"<div><div>To address the emerging frequency stability issue brought by the large replacement of synchronous generators with renewable generations, wind turbine generators are required to possess frequency-supporting capability. However, existing frequency-supporting control strategies lack the assessment of the frequency support capability of wind turbine generators, leading to degraded control performance under various situations. Aiming to solve this problem, this paper proposes a variable-droop-gain control for wind turbine generators with maximum rotor kinetic energy utilization. Firstly, an analytical relationship was established between droop gain, disturbance scale, and rotor speed. Subsequently, the released energy of the wind turbine generator is evaluated, which equals the difference in the rotor kinetic energy under the initial and the post-disturbance steady-state rotor speed. It was proved that the released kinetic energy cannot exceed a certain proportion of total rotor kinetic energy. Accordingly, a variable initial gain scheme is proposed, which determines the initial droop gain as per the disturbance scale for maximizing the kinetic energy release of wind turbines. Moreover, an additional real-time droop gain adjustment rule is added to prevent the over-deceleration of wind turbines. The simulation results show that the proposed scheme may provide the maximum KE release and effectively improve the system frequency nadir while ensuring the safe operation of wind turbine generators.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"163 ","pages":"Article 110289"},"PeriodicalIF":5.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Size optimization of standalone wind-photovoltaics-diesel-battery systems by Harris hawks optimization (HHO): Case study of a wharf located in Bushehr, Iran","authors":"Kamyar Fakhfour,&nbsp;Fathollah Pourfayaz","doi":"10.1016/j.ijepes.2024.110353","DOIUrl":"10.1016/j.ijepes.2024.110353","url":null,"abstract":"<div><div>The global increase in energy demand has led to a growing focus on renewable energy sources as a potential solution. This study examines the annual total cost of optimized off-grid hybrid multi-resource systems, considering various configurations of Wind Turbines (WT), Photovoltaics (PV), Diesel Generators (DG), and Batteries (Bat). The research focuses on an oil dock in Bushehr, Iran, as a case study. The optimization process employs the Harris Hawk Optimization (HHO) algorithm – which is used for the first time for hybrid configuration and optimal sizing in this paper-, a nature-inspired, population-based optimization technique. This algorithm’s performance is compared to conventional optimization methods to assess its efficiency. The study’s methodology involves: (1) Explaining the economic relationships for each energy source, (2) Formulating a cost function, (3) Using the HHO algorithm to minimize the total cost of the renewable energy-based hybrid systems. The HHO algorithm is inspired by the hunting behavior of Harris hawks, specifically their “wonder attack” strategy. This novel approach to optimization aims to find the most cost-effective configuration of energy sources for the given scenario. Key findings of the study include the HHO algorithm demonstrated superior efficiency compared to Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO) across all configurations tested. The most cost-effective configuration was found to be a combination of photovoltaics, batteries, and diesel generators. This setup had the lowest total annual cost among all configurations examined. The optimal system consisted of 450 photovoltaic units, 9 battery units, and 2 diesel generator units, with a minimum annual cost of approximately $355,525. These results highlight the potential of the HHO algorithm in optimizing renewable energy systems and demonstrate the complex trade-offs between cost and environmental impact in hybrid energy configurations. The study contributes valuable insights to the field of renewable energy system design and optimization, particularly for off-grid applications in industrial settings.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"163 ","pages":"Article 110353"},"PeriodicalIF":5.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Robust contingency-constrained load restoration method for transmission systems considering modified SOCP formulation of power flow","authors":"Lei Sun ,&nbsp;Weikang Fang ,&nbsp;Youwang Wei ,&nbsp;Zhenzhi Lin ,&nbsp;Xudong Jin","doi":"10.1016/j.ijepes.2024.110345","DOIUrl":"10.1016/j.ijepes.2024.110345","url":null,"abstract":"<div><div>A proper load restoration method can speed up the load restoration phase and reduce the outage losses of power systems after natural disasters. Existing research assumes that transmission lines would not trip again in the load restoration phase, which is not always acceptable, especially in the outage scenario due to natural disasters. Besides, the feasibility of the load restoration scheme relies on an exact mathematical model of the load restoration problem, while the existing second-order cone programming (SOCP) based model is not suitable for transmission power systems due to the lack of voltage angle related arctangent constraints. To address these two main drawbacks in existing research on load restoration, a robust contingency-constrained load restoration model (CCLRM) for transmission systems considering the modified SOCP formulation of power flow is proposed with the objective of reducing the outage losses taking the worst contingency into account. To identify the worst contingency for the CCLRM, a bi-level worst contingency identification model (WOCIM) is proposed and reformulated into a single-level model by employing the duality theory to make the WOCIM solvable. The non-linear voltage angle related arctangent constraints in the modified SOCP based power flow expression in both models are studied and reformulated into the convex ones based on the convex envelope theory, thereby enhancing the accuracy of the presented models. Case studies on the IEEE 30-bus power system and IEEE 118-bus power system are conducted to illustrate the effectiveness of the proposed method.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"163 ","pages":"Article 110345"},"PeriodicalIF":5.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Feasible region identification approach for the regional integrated energy system considering flexible ramping constraints based on polyhedral projection algorithm","authors":"Zhan Xiong ,&nbsp;Chunyan Zhang ,&nbsp;Dawei Qiu ,&nbsp;Lingling Wang ,&nbsp;Chuanwen Jiang ,&nbsp;Shichao Zhou","doi":"10.1016/j.ijepes.2024.110347","DOIUrl":"10.1016/j.ijepes.2024.110347","url":null,"abstract":"<div><div>The low-carbon agenda promotes the increasing penetration of renewable energy, this however also results in a rapid decrease in the flexibility of power systems with less controllable generation. There is an urgent requirement to explore user-side resources to provide flexibility for the power system. The regional integrated energy system (RIES) contains a large number of multi-energy coupling devices with abundant flexibility. However, considering the multi-energy complementary characteristics and complex multi-energy networks, as well as the uncertainty of the renewable energy, it is difficult to quantify the energy purchasing demand and flexibility support ability of RIES in the market, making it challenging to identify the RIES feasible region. This paper proposes a novel approach to tackle this challenge by introducing a projection method based on second-order cone programming. The approach aims to describe the energy purchasing and flexible reserve feasible regions of an RIES. Specifically, a max–min RIES operating model is constructed with the goal of minimizing the distance from the boundary of the feasible region in the worst case. Subsequently, the strong duality principle and Karush-Kuhn-Tucker (KKT) optimality conditions are leveraged to reformulate the max–min optimization problem into a solvable second-order cone programming problem. Additionally, the chance constraint is introduced to address and express the risk associated the uncertainty of the renewable energy output in RIES. Moreover, for the convenience of subsequent solving, the deterministic equivalent method is used to convert it into a deterministic constraint. Case studies conducted on an RIES incorporating a 33-bus distribution network and a 7-node natural gas network demonstrate the effectiveness and efficiency of the proposed approach in projecting the feasible region in terms of both operating costs and computational time.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"163 ","pages":"Article 110347"},"PeriodicalIF":5.0,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 voltage stability of grid forming power converters based on model predictive controller","authors":"Qudrat Ullah ,&nbsp;Enio Costa Resende ,&nbsp;Luiz Carlos Gomes Freitas ,&nbsp;Hannu Laaksonen ,&nbsp;Marcelo Godoy Simões","doi":"10.1016/j.ijepes.2024.110317","DOIUrl":"10.1016/j.ijepes.2024.110317","url":null,"abstract":"<div><div>This research article proposes an advanced control strategy based on a finite control set model predictive controller (FCS-MPC) for parallel-connected voltage source inverters (VSIs) for standalone operation of AC microgrids (MGs). The AC MGs may be consisted of two or more parallel connected VSIs connected and have ability to regulate the output line to line voltages at the point of common coupling (PCC) sustaining the local power demand. It is possible to attain these functionalities using traditional and linear control approaches, but there exist several challenges like sensitivity problems associated to parametric and non-parametric variations and they are unable to handle with existing constraints in system and resulting in slow dynamic response. An imperative feature of this research study is that proportional integral (PI) as well as proportional resonant (PR) controller based VSI was designed, studied and its performance was compared with FCS-MPC based VSI. The proposed FCS-MPC-based scheme handles several challenges effectually by confirming a stable and robust operation for Gridforming (GFM) inverters of AC MGs. In this scheme, the voltage reference over the predictive horizon is tracked by formulating a cost function (CF) and droop control is used to attain power sharing among distributed generations (DGs). The operation of standalone AC MG is authenticated by extensive simulations in MATLAB/Simulink environment, demonstrating that the FCS-MPC strategy shows quick dynamic response, improved power quality as well as enhanced voltage stability. The simulation results also reveal that total harmonic distortion (THD) of output line to line voltages is 0.86% for linear loads and 0.98 % for nonlinear loads, verifying that the THD level is primarily in the acceptable range defined by the IEC as well as IEEE standards, highlighting the AC MG system’s compliance with international standards.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"163 ","pages":"Article 110317"},"PeriodicalIF":5.0,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Bidding strategy for the virtual power plant based on cooperative game participating in the Electricity-Carbon joint market","authors":"Ronghui Liu ,&nbsp;Keyu Chen ,&nbsp;Gaiping Sun ,&nbsp;Shunfu Lin ,&nbsp;Chuanwen Jiang","doi":"10.1016/j.ijepes.2024.110325","DOIUrl":"10.1016/j.ijepes.2024.110325","url":null,"abstract":"<div><div>With the proposal of “Dual-carbon” target, the electricity market and carbon market has been gradually improved. Establishing a deep coupling of electricity-carbon market to promote the in-depth development of two markets has become a new research focus. Based on the cooperative game theory, a bidding strategy for the virtual power plant (VPP) which considers Chinese certified emission reduction mechanism and demand response is proposed. Firstly, the framework of VPP participating in the electricity-carbon joint market is constructed. Secondly, an upper and lower iterative bidding strategy model is established. The upper model uses the whale optimization algorithm to obtain the optimal bidding strategy, and the lower model is optimized to obtain the optimal power consumption. Thirdly, the elastic influence weight is introduced into the price-based demand response, and then an improved Shapley value method about profit distribution considering prediction accuracy and environmental benefits is proposed. Finally, the examples and simulation results verify that the proposed model can increase the total profit, reduce the carbon emission and the peak-valley difference rate of load. Meanwhile, it’s demonstrated that the profit distribution method improves the enthusiasm of the cooperative operation of the internal units in VPP.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"163 ","pages":"Article 110325"},"PeriodicalIF":5.0,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Twin delayed deep deterministic policy gradient based stochastic optimal dispatch of hydro and wind power considering the uncertainty of wind power in power-time dimensions","authors":"Yuhong Wang,&nbsp;Xu Zhou,&nbsp;Yunxiang Shi,&nbsp;Chenyu Zhou,&nbsp;Qiliang Jiang,&nbsp;Zongsheng Zheng","doi":"10.1016/j.ijepes.2024.110326","DOIUrl":"10.1016/j.ijepes.2024.110326","url":null,"abstract":"<div><div>The randomness, fluctuation and uncertainty of wind power brings great challenges to the dispatch and control of the power system. In order to raise the economy of hydro and wind power optimal dispatch, a stochastic optimal dispatching model considering the uncertainty of wind power in both time and power dimensions is proposed. The versatile distribution is used to describe the uncertainty of wind power in different power-time intervals, providing foundation for positive and negative reserves of hydro power. Moreover, to solve the multi-objective stochastic optimal dispatching model, the twin delayed deep deterministic policy gradient (TD3) algorithm is utilized, which can avoid falling into local optimum and has stronger search ability when dealing with high-dimensional multi-objective optimization problem. Simulations in a wind farm and hydro power station of western China show that the proposed model can accurately describe the uncertainty of wind power, and TD3 algorithm can find the global optimal solution more effectively than the traditional intelligent algorithms and other deep reinforcement learning algorithms.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"163 ","pages":"Article 110326"},"PeriodicalIF":5.0,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Peak interval-focused wind power forecast with dynamic ramp considerations","authors":"Nanyang Zhu ,&nbsp;Ying Wang ,&nbsp;Kun Yuan ,&nbsp;Jianhu Lv ,&nbsp;Bo Su ,&nbsp;Kaifeng Zhang","doi":"10.1016/j.ijepes.2024.110340","DOIUrl":"10.1016/j.ijepes.2024.110340","url":null,"abstract":"<div><div>Wind power forecast (WPF) plays a crucial role in the reliable and safe operation of power systems. Existing wind power prediction methods mainly focus on the overall trend information, often neglecting the performance of some typical intervals that can significantly impact the reserve requirements of power system, <strong><em>e.g.</em></strong>, unexpected ramp-up and ramp-down, local peak interval (LPI), and so on. Therefore, the primary focus of this paper is to explore techniques for enhancing the accuracy of wind power during the LPI. Considering that the points during the LPI are influenced by dynamic ramp characteristics, with the steepness and magnitude of ramps influencing the range of LPI, this paper proposes a novel focused-LPI model by incorporating dynamic ramp considerations. Specifically, beyond the tradition forecasting model, the proposed model encodes the information of ramp occurrence in wind power data based on a positional encoder; subsequently, the proposed model not only outputs standard predictions within a prediction range but also identifies the presence of ramps within these predictions. In addition, this paper employs a dynamically weighted loss function to optimize the proposed multi-task model. The proposed model is applied for various network architectures, and the results confirm that the proposed model is widely suitable for various basis network architectures. Specifically, the R-squared (R2) of the proposed model for the overall trend can exist a little error compared to the initial basic network architectures; the Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Relative Error (MRE) of the proposed model for predicting the LPI points can outperform the initial basis network architecture by average enhancements of 7.10%, 2.66%, and 3.46%, respectively. In addition, compared to existing state-of-the-art (SoTA) models in the LPI points, the proposed model obtains improved performance with 14.43% for MAE and 11.19% for RMSE, respectively, presenting its substantial performance enhancement.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"163 ","pages":"Article 110340"},"PeriodicalIF":5.0,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 reliability-constrained planning model for antarctic electricity and heat integrated energy system","authors":"Ziru Xie ,&nbsp;Jia Su ,&nbsp;Yixun Xue ,&nbsp;Xinyue Chang ,&nbsp;Yixuan Li ,&nbsp;Zening Li ,&nbsp;Hongbin Sun","doi":"10.1016/j.ijepes.2024.110346","DOIUrl":"10.1016/j.ijepes.2024.110346","url":null,"abstract":"<div><div>In order to maintain the supply adequacy of energy for the Antarctic integrated energy system, which in turn supports normal scientific research activities and the life safety of researchers, it is imperative that the reliability criterion be applied in planning issues. In this paper, a reliability-constrained planning model for the Antarctic electricity-heat integrated energy system is proposed, thus the optimal allocation of the wind turbines, photovoltaic, diesel engine, battery storage system, and Hydrogen storage system are obtained. Firstly, the reliability-oriented planning model applicable to the Antarctic integrated energy system is constructed. In particular, the improved Gaussian mixture model is introduced to accurately describe the probabilistic characteristics of renewable energy in Antarctica considering its unique geographical location and operating environment. Then, a rolling horizon based Sequential Monte Carlo method is developed to address the problem of intractable reliability constraints in the planning formulation. More specifically, the explicit reliability function is exacted by approximation function, which can be easily added to the planning model. Finally, the online-offline numerical approach is proposed to speed up the online computation. The validity and feasibility of the proposed method is verified on the actual Antarctic energy system. The results indicate that the optimal allocation results calculated by proposed method can guarantee the reliable supply of the Antarctic energy system.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"162 ","pages":"Article 110346"},"PeriodicalIF":5.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142573320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Mode identification-based model-free adaptive predictive damping control method for power system with wind farm considering communication delays","authors":"Fang Liu ,&nbsp;Yuheng Peng ,&nbsp;Qianyi Liu ,&nbsp;Haotian Li ,&nbsp;Kangzhi Liu ,&nbsp;Yanjian Peng","doi":"10.1016/j.ijepes.2024.110303","DOIUrl":"10.1016/j.ijepes.2024.110303","url":null,"abstract":"<div><div>With the widespread utilization of large-scale power electronics and the integration of wind power into power grid, the problem of low-frequency oscillations in new power systems become increasingly critical. In this paper, a mode identification-based model-free adaptive predictive control (MI-MFAPC) method with full-form dynamic linearization (FFDL) is proposed to design wide-area damping controller (WADC) to suppress multi-modal oscillations. Modal identification method is adopted in MFAPC-WADC to screen the controller input signals with high observability and low coupling, and the controller parameters are set separately for different oscillation modes. The improved control and adaptive law are proposed to rigorously guarantees the asymptotic convergence of the control error to zero under steady-state conditions. The proposed method integrates with the rolling optimization and introduces the future time input and output data, so it has strong robustness for the time-delay system. Simulation results show that MI-MFAPC-WADC greatly improves the dynamic quality and system stability, and the multiple oscillation modes are suppressed efficiently. Considering communication delays, the proposed method without the adaptive delay compensator even obtains better damping performance than the existed method with the adaptive delay compensator.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"162 ","pages":"Article 110303"},"PeriodicalIF":5.0,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}