Pub Date : 2024-01-11DOI: 10.35833/MPCE.2023.000386
Wei Dong;Fan Zhang;Meng Li;Xiaolun Fang;Qiang Yang
The intermittency of renewable energy generation, variability of load demand, and stochasticity of market price bring about direct challenges to optimal energy management of microgrids. To cope with these different forms of operation uncertainties, an imitation learning based real-time decision-making solution for microgrid economic dispatch is proposed. In this solution, the optimal dispatch trajectories obtained by solving the optimal problem using historical deterministic operation patterns are demonstrated as the expert samples for imitation learning. To improve the generalization performance of imitation learning and the expressive ability of uncertain variables, a hybrid model combining the unsupervised and supervised learning is utilized. The denoising autoencoder based unsupervised learning model is adopted to enhance the feature extraction of operation patterns. Furthermore, the long short-term memory network based supervised learning model is used to efficiently characterize the mapping between the input space composed of the extracted operation patterns and system state variables and the output space composed of the optimal dispatch trajectories. The numerical simulation results demonstrate that under various operation uncertainties, the operation cost achieved by the proposed solution is close to the minimum theoretical value. Compared with the traditional model predictive control method and basic clone imitation learning method, the operation cost of the proposed solution is reduced by 6.3% and 2.8%, respectively, over a test period of three months.
{"title":"Imitation Learning Based Real-Time Decision-Making of Microgrid Economic Dispatch Under Multiple Uncertainties","authors":"Wei Dong;Fan Zhang;Meng Li;Xiaolun Fang;Qiang Yang","doi":"10.35833/MPCE.2023.000386","DOIUrl":"10.35833/MPCE.2023.000386","url":null,"abstract":"The intermittency of renewable energy generation, variability of load demand, and stochasticity of market price bring about direct challenges to optimal energy management of microgrids. To cope with these different forms of operation uncertainties, an imitation learning based real-time decision-making solution for microgrid economic dispatch is proposed. In this solution, the optimal dispatch trajectories obtained by solving the optimal problem using historical deterministic operation patterns are demonstrated as the expert samples for imitation learning. To improve the generalization performance of imitation learning and the expressive ability of uncertain variables, a hybrid model combining the unsupervised and supervised learning is utilized. The denoising autoencoder based unsupervised learning model is adopted to enhance the feature extraction of operation patterns. Furthermore, the long short-term memory network based supervised learning model is used to efficiently characterize the mapping between the input space composed of the extracted operation patterns and system state variables and the output space composed of the optimal dispatch trajectories. The numerical simulation results demonstrate that under various operation uncertainties, the operation cost achieved by the proposed solution is close to the minimum theoretical value. Compared with the traditional model predictive control method and basic clone imitation learning method, the operation cost of the proposed solution is reduced by 6.3% and 2.8%, respectively, over a test period of three months.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"12 4","pages":"1183-1193"},"PeriodicalIF":5.7,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10396835","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141769489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-11DOI: 10.35833/MPCE.2023.000265
Xinxin Yang;Yusheng Xue;Bin Cai
The nuclear event risk (NER) is an important and disputed factor that should be reasonably considered when planning the pathway of nuclear power development (NPD) to assess the benefits and risks of developing nuclear power more objectively. This paper aims to explore the impact of nuclear events on NPD pathway planning. The influence of nuclear events is quantified as a monetary risk component, and an optimization model that incorporates the NER in the objective function is proposed. To optimize the pathway of NPD in the lowcarbon transition course of power supply structure evolution, a simulation model is built to deduce alternative NPD pathways and corresponding power supply evolution scenarios under the constraint of an exogenously assigned carbon emission pathway (CEP); moreover, a method is proposed to describe the CEP by superimposing the maximum carbon emission space and each carbon emission reduction (CER) component, and various CER components are clustered considering the emission reduction characteristics and resource endowments of different power generation technologies. A case study is conducted to explore the impact of NER and its risk valuation uncertainty on NPD pathway planning. The method presented in this paper allows the impact of nuclear events on NPD pathway planning to be quantified and improves the level of coordinated optimization of benefits and risks.
{"title":"Pathway Planning of Nuclear Power Development Incorporating Assessment of Nuclear Event Risk","authors":"Xinxin Yang;Yusheng Xue;Bin Cai","doi":"10.35833/MPCE.2023.000265","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000265","url":null,"abstract":"The nuclear event risk (NER) is an important and disputed factor that should be reasonably considered when planning the pathway of nuclear power development (NPD) to assess the benefits and risks of developing nuclear power more objectively. This paper aims to explore the impact of nuclear events on NPD pathway planning. The influence of nuclear events is quantified as a monetary risk component, and an optimization model that incorporates the NER in the objective function is proposed. To optimize the pathway of NPD in the lowcarbon transition course of power supply structure evolution, a simulation model is built to deduce alternative NPD pathways and corresponding power supply evolution scenarios under the constraint of an exogenously assigned carbon emission pathway (CEP); moreover, a method is proposed to describe the CEP by superimposing the maximum carbon emission space and each carbon emission reduction (CER) component, and various CER components are clustered considering the emission reduction characteristics and resource endowments of different power generation technologies. A case study is conducted to explore the impact of NER and its risk valuation uncertainty on NPD pathway planning. The method presented in this paper allows the impact of nuclear events on NPD pathway planning to be quantified and improves the level of coordinated optimization of benefits and risks.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"12 2","pages":"500-513"},"PeriodicalIF":6.3,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10396833","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140291141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-11DOI: 10.35833/MPCE.2023.000379
Charalampos G. Arsoniadis;Vassilis C. Nikolaidis
This paper proposes a novel fault location method for overhead feeders, which is based on the direct load flow approach. The method is developed in the phase domain to effectively deal with unbalanced network conditions, while it can also handle distributed generation (DG) units of any type without requiring equivalent models. By utilizing the line series parameters and synchronized or unsynchronized voltage and current phasor measurements taken from the sources, the method reliably identifies the most probable faulty sections. With the aid of an index, the exact faulty section among the multiple candidates is determined. Extensive simulation studies for the IEEE 123-bus test feeder demonstrate that the proposed method accurately estimates the fault position under numerous short-circuit conditions with varying pre-fault system loading conditions, fault resistances, and measurement errors. The proposed method is promising for practical applications due to the limited number of required measurement devices as well as the short computation time.
{"title":"Fault Location Method for Overhead Feeders with Distributed Generation Units Based on Direct Load Flow Approach","authors":"Charalampos G. Arsoniadis;Vassilis C. Nikolaidis","doi":"10.35833/MPCE.2023.000379","DOIUrl":"10.35833/MPCE.2023.000379","url":null,"abstract":"This paper proposes a novel fault location method for overhead feeders, which is based on the direct load flow approach. The method is developed in the phase domain to effectively deal with unbalanced network conditions, while it can also handle distributed generation (DG) units of any type without requiring equivalent models. By utilizing the line series parameters and synchronized or unsynchronized voltage and current phasor measurements taken from the sources, the method reliably identifies the most probable faulty sections. With the aid of an index, the exact faulty section among the multiple candidates is determined. Extensive simulation studies for the IEEE 123-bus test feeder demonstrate that the proposed method accurately estimates the fault position under numerous short-circuit conditions with varying pre-fault system loading conditions, fault resistances, and measurement errors. The proposed method is promising for practical applications due to the limited number of required measurement devices as well as the short computation time.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"12 4","pages":"1135-1146"},"PeriodicalIF":5.7,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10396834","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141769440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-02DOI: 10.35833/MPCE.2023.000394
Junkai Huang;Yan Xu
Droop-based fast frequency response (FFR) control of wind turbines can improve the frequency performance of power systems with high penetration of wind power. Explicitly formulating the feasible region of the droop-based FFR controller parameters can allow system operators to conveniently assess the feasibility of FFR controller parameter settings to comply with system frequency security, and efficiently tune and optimize FFR controller parameters to meet frequency security requirements. However, the feasible region of FFR controller parameters is inherently nonlinear and implicit because the power point tracking controllers of wind turbine would counteract the effect of FFR controllers. To address this issue, this letter proposes a linear feasible region formulation method, where frequency regulation characteristics of wind turbines, the dead band, and reserve limits of generators are all considered. The effectiveness of the proposed method and its application is demonstrated on a 10-machine power system.
{"title":"On Feasible Region of Droop-Based Fast Frequency Response Controller Parameters of Wind Turbines","authors":"Junkai Huang;Yan Xu","doi":"10.35833/MPCE.2023.000394","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000394","url":null,"abstract":"Droop-based fast frequency response (FFR) control of wind turbines can improve the frequency performance of power systems with high penetration of wind power. Explicitly formulating the feasible region of the droop-based FFR controller parameters can allow system operators to conveniently assess the feasibility of FFR controller parameter settings to comply with system frequency security, and efficiently tune and optimize FFR controller parameters to meet frequency security requirements. However, the feasible region of FFR controller parameters is inherently nonlinear and implicit because the power point tracking controllers of wind turbine would counteract the effect of FFR controllers. To address this issue, this letter proposes a linear feasible region formulation method, where frequency regulation characteristics of wind turbines, the dead band, and reserve limits of generators are all considered. The effectiveness of the proposed method and its application is demonstrated on a 10-machine power system.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"12 5","pages":"1690-1695"},"PeriodicalIF":5.7,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10379574","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142328375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-02DOI: 10.35833/MPCE.2023.000546
Wenlong Liao;Dechang Yang;Qi Liu;Yixiong Jia;Chenxi Wang;Zhe Yang
Reactive power optimization of distribution networks is traditionally addressed by physical model based methods, which often lead to locally optimal solutions and require heavy online inference time consumption. To improve the quality of the solution and reduce the inference time burden, this paper proposes a new graph attention networks based method to directly map the complex nonlinear relationship between graphs (topology and power loads) and reactive power scheduling schemes of distribution networks, from a data-driven perspective. The graph attention network is tailored specifically to this problem and incorporates several innovative features such as a self-loop in the adjacency matrix, a customized loss function, and the use of max-pooling layers. Additionally, a rule-based strategy is proposed to adjust infeasible solutions that violate constraints. Simulation results on multiple distribution networks demonstrate that the proposed method outperforms other machine learning based methods in terms of the solution quality and robustness to varying load conditions. Moreover, its online inference time is significantly faster than traditional physical model based methods, particularly for large-scale distribution networks.
{"title":"Data-Driven Reactive Power Optimization of Distribution Networks via Graph Attention Networks","authors":"Wenlong Liao;Dechang Yang;Qi Liu;Yixiong Jia;Chenxi Wang;Zhe Yang","doi":"10.35833/MPCE.2023.000546","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000546","url":null,"abstract":"Reactive power optimization of distribution networks is traditionally addressed by physical model based methods, which often lead to locally optimal solutions and require heavy online inference time consumption. To improve the quality of the solution and reduce the inference time burden, this paper proposes a new graph attention networks based method to directly map the complex nonlinear relationship between graphs (topology and power loads) and reactive power scheduling schemes of distribution networks, from a data-driven perspective. The graph attention network is tailored specifically to this problem and incorporates several innovative features such as a self-loop in the adjacency matrix, a customized loss function, and the use of max-pooling layers. Additionally, a rule-based strategy is proposed to adjust infeasible solutions that violate constraints. Simulation results on multiple distribution networks demonstrate that the proposed method outperforms other machine learning based methods in terms of the solution quality and robustness to varying load conditions. Moreover, its online inference time is significantly faster than traditional physical model based methods, particularly for large-scale distribution networks.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"12 3","pages":"874-885"},"PeriodicalIF":6.3,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10379575","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141091167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-02DOI: 10.35833/MPCE.2023.000357
Qiangqiang Wang;Liangzhong Yao;Jian Xu;Yuping Zheng;Wei Li;Wei Wang
Due to the fact that a high share of renewable energy sources (RESs) are connected to high-voltage direct current (HVDC) sending-end AC power systems, the voltage and frequency regulation capabilities of HVDC sending-end AC power systems have diminished. This has resulted in potential system operating problems such as overvoltage and overfrequency, which occur simultaneously when block faults exist in the HVDC link. In this study, a steady-state voltage security-constrained optimal frequency control method for weak HVDC sending-end AC power systems is proposed. The integrated virtual inertia control of RESs is employed for system frequency regulation. Additional dynamic reactive power compensation devices are utilized to control the voltage of all nodes meet voltage security constraints. Then, an optimization model that simultaneously considers the frequency and steady-state voltage security constraints for weak HVDC sending-end AC power systems is established. The optimal control scheme with the minimum total cost of generation tripping and additional dynamic reactive power compensation required is obtained through the optimization solution. Simulations are conducted on a modified IEEE 9-bus test system and practical Qing-Yu line commutated converter based HVDC (LCC-HVDC) sending-end AC power system to verify the effectiveness of the proposed method.
{"title":"Steady-state Voltage Security-constrained Optimal Frequency Control for Weak HVDC Sending-end AC Power Systems","authors":"Qiangqiang Wang;Liangzhong Yao;Jian Xu;Yuping Zheng;Wei Li;Wei Wang","doi":"10.35833/MPCE.2023.000357","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000357","url":null,"abstract":"Due to the fact that a high share of renewable energy sources (RESs) are connected to high-voltage direct current (HVDC) sending-end AC power systems, the voltage and frequency regulation capabilities of HVDC sending-end AC power systems have diminished. This has resulted in potential system operating problems such as overvoltage and overfrequency, which occur simultaneously when block faults exist in the HVDC link. In this study, a steady-state voltage security-constrained optimal frequency control method for weak HVDC sending-end AC power systems is proposed. The integrated virtual inertia control of RESs is employed for system frequency regulation. Additional dynamic reactive power compensation devices are utilized to control the voltage of all nodes meet voltage security constraints. Then, an optimization model that simultaneously considers the frequency and steady-state voltage security constraints for weak HVDC sending-end AC power systems is established. The optimal control scheme with the minimum total cost of generation tripping and additional dynamic reactive power compensation required is obtained through the optimization solution. Simulations are conducted on a modified IEEE 9-bus test system and practical Qing-Yu line commutated converter based HVDC (LCC-HVDC) sending-end AC power system to verify the effectiveness of the proposed method.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"12 2","pages":"658-669"},"PeriodicalIF":6.3,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10379571","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140291145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-02DOI: 10.35833/MPCE.2023.000119
Jipeng Gu;Xiaodong Yang;Youbing Zhang;Luyao Xie;Licheng Wang;Wenwei Zhou;Xiaohui Ge
The unbalanced state of charge (SOC) of distributed energy storage systems (DESSs) in autonomous DC microgrid causes energy storage units (ESUs) to terminate operation due to overcharge or overdischarge, which severely affects the power quality. In this paper, a fuzzy droop control for SOC balance and stability analysis of DC microgrid with DESSs is proposed to achieve SOC balance in ESUs while maintaining a stable DC bus voltage. First, the charge and discharge modes of ESUs are determined based on the power supply requirements of the DC microgrid. One-dimensional fuzzy logic is then applied to establish the relationship between SOC and the droop coefficient $R_{d}$