Pub Date : 2024-03-05DOI: 10.35833/MPCE.2023.000741
Jie Li;Xiaoming Liu;Zixuan Zheng;Xianyong Xiao;Shu Zhang;Hongzhi Gao;Yongjun Zhou
The optimal planning and operation of multi-type flexible resources (FRs) are critical prerequisites for maintaining power and energy balance in regional power grids with a high proportion of clean energy. However, insufficient consideration of the multi-dimensional and heterogeneous features of FRs, such as the regulation characteristics of diversified battery energy storage systems (BESSs), poses a challenge in economically relieving imbalance power and adequately sharing feature information between power supply and demand. In view of this disadvantage, an optimal planning and operation method based on differentiated feature matching through response capability characterization and difference quantification of FRs is proposed in this paper. In the planning stage, a model for the optimal planning of diversified energy storages (ESs) including Lithium-ion battery (Li-B), supercapacitor energy storage (SC-ES), compressed air energy storage (CAES), and pumped hydroelectric storage (PHS) is established. Subsequently, in the operating stage, the potential, direction, and cost of FR response behaviors are refined to match with the power and energy balance demand (PEBD) of power grid operation. An optimal operating algorithm is then employed to quantify the feature differences and output response sequences of multi-type FRs. The performance and effectiveness of the proposed method are demonstrated through comparative studies conducted on an actual regional power grid in northwest China. Analysis and simulation results illustrate that the proposed method can effectively highlight the advantages of BESSs compared with other ESs, and economically reduce imbalance power of the regional power grid under practical operating conditions.
{"title":"Optimal Planning and Operation of Multi-Type Flexible Resources Based on Differentiated Feature Matching in Regional Power Grid with High Proportion of Clean Energy","authors":"Jie Li;Xiaoming Liu;Zixuan Zheng;Xianyong Xiao;Shu Zhang;Hongzhi Gao;Yongjun Zhou","doi":"10.35833/MPCE.2023.000741","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000741","url":null,"abstract":"The optimal planning and operation of multi-type flexible resources (FRs) are critical prerequisites for maintaining power and energy balance in regional power grids with a high proportion of clean energy. However, insufficient consideration of the multi-dimensional and heterogeneous features of FRs, such as the regulation characteristics of diversified battery energy storage systems (BESSs), poses a challenge in economically relieving imbalance power and adequately sharing feature information between power supply and demand. In view of this disadvantage, an optimal planning and operation method based on differentiated feature matching through response capability characterization and difference quantification of FRs is proposed in this paper. In the planning stage, a model for the optimal planning of diversified energy storages (ESs) including Lithium-ion battery (Li-B), supercapacitor energy storage (SC-ES), compressed air energy storage (CAES), and pumped hydroelectric storage (PHS) is established. Subsequently, in the operating stage, the potential, direction, and cost of FR response behaviors are refined to match with the power and energy balance demand (PEBD) of power grid operation. An optimal operating algorithm is then employed to quantify the feature differences and output response sequences of multi-type FRs. The performance and effectiveness of the proposed method are demonstrated through comparative studies conducted on an actual regional power grid in northwest China. Analysis and simulation results illustrate that the proposed method can effectively highlight the advantages of BESSs compared with other ESs, and economically reduce imbalance power of the regional power grid under practical operating conditions.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"12 6","pages":"1724-1736"},"PeriodicalIF":5.7,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10460467","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142841992","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 : 2024-03-03DOI: 10.35833/MPCE.2023.001028
Jie Liu;Shunjiang Lin;Weikun Liang;Yanghua Liu;Mingbo Liu
As transmission power among interconnected regional grids is increasing rapidly, formulating the power distribution and maintenance schedules of multiple paralleled transmission channels are critical to ensure the secure and economic operation in an AC/DC power system. A coordinated optimization for power distribution and maintenance schedules (COPD-MS) of multiple paralleled transmission channels is proposed, and the active power losses of the resistances of earth line in the high-voltage direct current (HVDC) transmission lines are taken into account when one pole is under maintenance while the other pole is operating under monopolar ground circuit. To solve the proposed COPD-MS model efficiently, the generalized Benders decomposition (GBD) algorithm is used to decompose the proposed COPD-MS model into master problem of maintenance scheduling and sub-problems of power distribution scheduling, and the optimal solution of the original model is obtained by the alternative iteration between them. Moreover, a recursive acceleration (RA) algorithm is proposed to solve the master problem, which can directly obtain its solution in the new iteration by using the solution in the last iteration and the newly added Benders cut. Convex relaxation techniques are applied to the nonlinear constraints in the sub-problem to ensure the reliable convergence. Additionally, since there is no coupling among the power distributions during each time interval in the sub-problem, parallel computing technology is used to improve the computational efficiency. Finally, case studies on the modified IEEE 39-bus system and an actual 1524-bus large-scale AC/DC hybrid power system demonstrate the effectiveness of the proposed COPD-MS model.
{"title":"Optimization for Power Distribution and Maintenance Schedules of Paralleled Transmission Channels in AC/DC Power System","authors":"Jie Liu;Shunjiang Lin;Weikun Liang;Yanghua Liu;Mingbo Liu","doi":"10.35833/MPCE.2023.001028","DOIUrl":"https://doi.org/10.35833/MPCE.2023.001028","url":null,"abstract":"As transmission power among interconnected regional grids is increasing rapidly, formulating the power distribution and maintenance schedules of multiple paralleled transmission channels are critical to ensure the secure and economic operation in an AC/DC power system. A coordinated optimization for power distribution and maintenance schedules (COPD-MS) of multiple paralleled transmission channels is proposed, and the active power losses of the resistances of earth line in the high-voltage direct current (HVDC) transmission lines are taken into account when one pole is under maintenance while the other pole is operating under monopolar ground circuit. To solve the proposed COPD-MS model efficiently, the generalized Benders decomposition (GBD) algorithm is used to decompose the proposed COPD-MS model into master problem of maintenance scheduling and sub-problems of power distribution scheduling, and the optimal solution of the original model is obtained by the alternative iteration between them. Moreover, a recursive acceleration (RA) algorithm is proposed to solve the master problem, which can directly obtain its solution in the new iteration by using the solution in the last iteration and the newly added Benders cut. Convex relaxation techniques are applied to the nonlinear constraints in the sub-problem to ensure the reliable convergence. Additionally, since there is no coupling among the power distributions during each time interval in the sub-problem, parallel computing technology is used to improve the computational efficiency. Finally, case studies on the modified IEEE 39-bus system and an actual 1524-bus large-scale AC/DC hybrid power system demonstrate the effectiveness of the proposed COPD-MS model.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"12 6","pages":"2030-2044"},"PeriodicalIF":5.7,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10520023","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142844230","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 : 2024-03-03DOI: 10.35833/MPCE.2023.000718
Ye Tang;Qiaozhu Zhai;Yuzhou Zhou
Energy storage (ES), as a fast response technology, creates an opportunity for microgrid (MG) to participate in the reserve market such that MG with ES can act as an independent reserve provider. However, the potential value of MG with ES in the reserve market has not been well realized. From the viewpoint of reserve provider, a novel day-ahead model is proposed comprehensively considering the effect of the real-time scheduling process, which differs from the model that MG with ES acts as a reserve consumer in most existing studies. Based on the proposed model, MG with ES can schedule its internal resources to give reserve service to other external systems as well as to realize optimal self-scheduling. Considering that the proposed model is just in concept and cannot be directly solved, a multi-stage robust optimization reserve provision method is proposed, which leverages the structure of model constraints. Next, the original model can be converted into a mixed-integer linear programming problem and the model is tractable with guaranteed solution feasibility. Numerical tests in a real-world context are provided to demonstrate efficient operation and economic performance.
储能（ES）作为一种快速响应技术，为微电网（MG）参与储备市场创造了机会，使带有 ES 的微电网可以充当独立的储备供应商。然而，带 ES 的微电网在储备市场中的潜在价值尚未得到很好的体现。本文从储备提供者的角度出发，提出了一种综合考虑了实时调度过程影响的新型日前模型，该模型有别于现有大多数研究中将带 ES 的 MG 视为储备消费者的模型。基于提出的模型，带 ES 的 MG 可调度其内部资源为其他外部系统提供储备服务，并实现最优的自我调度。考虑到所提出的模型只是概念，无法直接求解，因此提出了一种多阶段鲁棒优化储备供应方法，该方法利用了模型约束的结构。接下来，原始模型可转换为混合整数线性规划问题，模型具有可操作性，并保证了求解的可行性。在现实世界中进行的数值测试证明了该方法的高效运行和经济效益。
{"title":"From Viewpoint of Reserve Provider: A Day-Ahead Multi-Stage Robust Optimization Reserve Provision Method for Microgrid with Energy Storage","authors":"Ye Tang;Qiaozhu Zhai;Yuzhou Zhou","doi":"10.35833/MPCE.2023.000718","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000718","url":null,"abstract":"Energy storage (ES), as a fast response technology, creates an opportunity for microgrid (MG) to participate in the reserve market such that MG with ES can act as an independent reserve provider. However, the potential value of MG with ES in the reserve market has not been well realized. From the viewpoint of reserve provider, a novel day-ahead model is proposed comprehensively considering the effect of the real-time scheduling process, which differs from the model that MG with ES acts as a reserve consumer in most existing studies. Based on the proposed model, MG with ES can schedule its internal resources to give reserve service to other external systems as well as to realize optimal self-scheduling. Considering that the proposed model is just in concept and cannot be directly solved, a multi-stage robust optimization reserve provision method is proposed, which leverages the structure of model constraints. Next, the original model can be converted into a mixed-integer linear programming problem and the model is tractable with guaranteed solution feasibility. Numerical tests in a real-world context are provided to demonstrate efficient operation and economic performance.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"12 5","pages":"1535-1547"},"PeriodicalIF":5.7,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10520021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142324271","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}
Decarbonization in the power sector is one of the critical factors in achieving carbon neutrality, and the top-level design needs to be carried out from the perspective of power planning. A multi-stage provincial power expansion planning (PPEP) model is proposed to simulate the power expansion planning at different stages of the power systems rich in renewable energy generation. This model covers 16 types of power supply, considering macro-policy demands and micro-operation constraints. The stand-alone capacity aggregation model for coal-based units within the PPEP model allows for accurate construction and retirement with different stand-alone capacities. Moreover, the soft dynamic time warping (soft-DTW) based $K-text{medoids}$ technique is adopted to generate typical scenarios for balancing the model accuracy and solution efficiency. Additionally, a multi-market trading equilibrium (MMTE) mechanism is proposed to address the differences in the levelized cost of energy between the coal-based and renewable-based units by participating in energy and ancillary service markets. Since the coal-based units take on the task of providing ancillary services from renewable-based units in the ancillary service market, the MMTE mechanism can effectively equalize the profits of both by having renewable-based units purchase ancillary services from coal-based units and pay for them, thus improving the motivation of coal-based units. A case study in Xinjiang province, China, verifies the effectiveness of the planning results of the PPEP model and the profit equilibrium realization of the MMTE mechanism.
{"title":"Multi-Stage Provincial Power Expansion Planning and Multi-Market Trading Equilibrium","authors":"Guangsheng Pan;Zhongfan Gu;Yuanyuan Sun;Kaiqi Sun;Wei Gu","doi":"10.35833/MPCE.2024.000171","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000171","url":null,"abstract":"Decarbonization in the power sector is one of the critical factors in achieving carbon neutrality, and the top-level design needs to be carried out from the perspective of power planning. A multi-stage provincial power expansion planning (PPEP) model is proposed to simulate the power expansion planning at different stages of the power systems rich in renewable energy generation. This model covers 16 types of power supply, considering macro-policy demands and micro-operation constraints. The stand-alone capacity aggregation model for coal-based units within the PPEP model allows for accurate construction and retirement with different stand-alone capacities. Moreover, the soft dynamic time warping (soft-DTW) based \u0000<tex>$K-text{medoids}$</tex>\u0000 technique is adopted to generate typical scenarios for balancing the model accuracy and solution efficiency. Additionally, a multi-market trading equilibrium (MMTE) mechanism is proposed to address the differences in the levelized cost of energy between the coal-based and renewable-based units by participating in energy and ancillary service markets. Since the coal-based units take on the task of providing ancillary services from renewable-based units in the ancillary service market, the MMTE mechanism can effectively equalize the profits of both by having renewable-based units purchase ancillary services from coal-based units and pay for them, thus improving the motivation of coal-based units. A case study in Xinjiang province, China, verifies the effectiveness of the planning results of the PPEP model and the profit equilibrium realization of the MMTE mechanism.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"12 5","pages":"1652-1665"},"PeriodicalIF":5.7,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10520020","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142328378","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}
During the power modulation process of line commutated converter-based high-voltage direct current (LCC-HVDC), the transient power mismatch between the fast-change converter station and the slow-response reactive power compensators (RPCs) can cause transient voltage disturbances at the weak sending end of the AC grid. To mitigate such voltage disturbances, this paper proposes a coordinated feedback power control method for the hybrid multi-infeed HVDC (HMI-HVDC) system comprising an LCC-HVDC and voltage source converter-based HVDC (VSC-HVDC) systems. The mechanism of the disturbance caused by transient power mismatch is quantitatively analyzed, and the numerical relationship between the instantaneous unbalanced power and the AC voltage is derived. Based on the numerical relationship and considering the time-varying relationship of reactive power between converter stations, the unbalanced power is set as the feedback and coordinately distributed among the inverter stations of VSC-HVDC, and the rectifier and the inverter stations of LCC-HVDC. Simulation results verify that the proposed method can effectively suppress voltage disturbance without relying on remote communication, thus enhancing the operation performance of the HMI-HVDC system.
{"title":"Coordinated Feedback Power Control Method for Hybrid Multi-Infeed HVDC System","authors":"Jiachen Zhang;Qi Xie;Zixuan Zheng;Chunyi Guo;Yi Zou;Jie Ren","doi":"10.35833/MPCE.2023.000586","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000586","url":null,"abstract":"During the power modulation process of line commutated converter-based high-voltage direct current (LCC-HVDC), the transient power mismatch between the fast-change converter station and the slow-response reactive power compensators (RPCs) can cause transient voltage disturbances at the weak sending end of the AC grid. To mitigate such voltage disturbances, this paper proposes a coordinated feedback power control method for the hybrid multi-infeed HVDC (HMI-HVDC) system comprising an LCC-HVDC and voltage source converter-based HVDC (VSC-HVDC) systems. The mechanism of the disturbance caused by transient power mismatch is quantitatively analyzed, and the numerical relationship between the instantaneous unbalanced power and the AC voltage is derived. Based on the numerical relationship and considering the time-varying relationship of reactive power between converter stations, the unbalanced power is set as the feedback and coordinately distributed among the inverter stations of VSC-HVDC, and the rectifier and the inverter stations of LCC-HVDC. Simulation results verify that the proposed method can effectively suppress voltage disturbance without relying on remote communication, thus enhancing the operation performance of the HMI-HVDC system.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"12 6","pages":"2045-2057"},"PeriodicalIF":5.7,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10520022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142844446","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 : 2024-02-28DOI: 10.35833/MPCE.2023.000742
Xiao Xu;Ziwen Qiu;Teng Zhang;Hui Gao
The vehicle-to-grid (V2G) technology enables the bidirectional power flow between electric vehicle (EV) batteries and the power grid, making EV-based mobile energy storage an appealing supplement to stationary energy storage systems. However, the stochastic and volatile charging behaviors pose a challenge for EV fleets to engage directly in multi-agent cooperation. To unlock the scheduling potential of EVs, this paper proposes a source-load-storage cooperative low-carbon scheduling strategy considering V2G aggregators. The uncertainty of EV charging patterns is managed through a rolling-horizon control framework, where the scheduling and control horizons are adaptively adjusted according to the availability periods of EVs. Moreover, a Minkowski-sum based aggregation method is employed to evaluate the scheduling potential of aggregated EV fleets within a given scheduling horizon. This method effectively reduces the variable dimension while preserving the charging and discharging constraints of individual EVs. Subsequently, a Nash bargaining based cooperative scheduling model involving a distribution system operator (DSO), an EV aggregator (EVA), and a load aggregator (LA) is established to maximize the social welfare and improve the low-carbon performance of the system. This model is solved by the alternating direction method of multipliers (ADMM) algorithm in a distributed manner, with privacy of participants fully preserved. The proposed strategy is proven to achieve the objective of low-carbon economic operation.
{"title":"Distributed Source-Load-Storage Cooperative Low-Carbon Scheduling Strategy Considering Vehicle-to-Grid Aggregators","authors":"Xiao Xu;Ziwen Qiu;Teng Zhang;Hui Gao","doi":"10.35833/MPCE.2023.000742","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000742","url":null,"abstract":"The vehicle-to-grid (V2G) technology enables the bidirectional power flow between electric vehicle (EV) batteries and the power grid, making EV-based mobile energy storage an appealing supplement to stationary energy storage systems. However, the stochastic and volatile charging behaviors pose a challenge for EV fleets to engage directly in multi-agent cooperation. To unlock the scheduling potential of EVs, this paper proposes a source-load-storage cooperative low-carbon scheduling strategy considering V2G aggregators. The uncertainty of EV charging patterns is managed through a rolling-horizon control framework, where the scheduling and control horizons are adaptively adjusted according to the availability periods of EVs. Moreover, a Minkowski-sum based aggregation method is employed to evaluate the scheduling potential of aggregated EV fleets within a given scheduling horizon. This method effectively reduces the variable dimension while preserving the charging and discharging constraints of individual EVs. Subsequently, a Nash bargaining based cooperative scheduling model involving a distribution system operator (DSO), an EV aggregator (EVA), and a load aggregator (LA) is established to maximize the social welfare and improve the low-carbon performance of the system. This model is solved by the alternating direction method of multipliers (ADMM) algorithm in a distributed manner, with privacy of participants fully preserved. The proposed strategy is proven to achieve the objective of low-carbon economic operation.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"12 2","pages":"440-453"},"PeriodicalIF":6.3,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10453376","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140291201","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 : 2024-02-28DOI: 10.35833/MPCE.2023.000746
Carmen Bas Domenech;Antonella Maria De Corato;Pierluigi Mancarella
Community batteries (CBs) are emerging to support and even enable energy communities and generally help consumers, especially space-constrained ones, to access potential techno-economic benefits from storage and support local grid decarbonization. However, the economic viability of CB projects is often uncertain. In this regard, typical feasibility studies assess CB value for behind-the-meter (BTM) operation or whole-sale market participation, i.e., front-of-meter (FOM). This work proposes a novel techno-economic operational framework that allows systematic assessment of the different options and introduces a two-meter architecture that co-optimizes both BTM and FOM benefits. A real CB project application in Australia is used to demonstrate the significant two-meter co-optimization opportunities that could enhance the business case of CB and energy communities by multi-service provision and value stacking.
{"title":"Co-Optimization of Behind-the-Meter and Front-of-Meter Value Streams in Community Batteries","authors":"Carmen Bas Domenech;Antonella Maria De Corato;Pierluigi Mancarella","doi":"10.35833/MPCE.2023.000746","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000746","url":null,"abstract":"Community batteries (CBs) are emerging to support and even enable energy communities and generally help consumers, especially space-constrained ones, to access potential techno-economic benefits from storage and support local grid decarbonization. However, the economic viability of CB projects is often uncertain. In this regard, typical feasibility studies assess CB value for behind-the-meter (BTM) operation or whole-sale market participation, i.e., front-of-meter (FOM). This work proposes a novel techno-economic operational framework that allows systematic assessment of the different options and introduces a two-meter architecture that co-optimizes both BTM and FOM benefits. A real CB project application in Australia is used to demonstrate the significant two-meter co-optimization opportunities that could enhance the business case of CB and energy communities by multi-service provision and value stacking.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"12 2","pages":"334-345"},"PeriodicalIF":6.3,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10453377","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140291166","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 : 2024-02-26DOI: 10.35833/MPCE.2023.000512
Hongtao Ren;Chung-Li Tseng;Fushuan Wen;Chongyu Wang;Guoyan Chen;Xiao Li
Joint operation optimization for electric vehicles (EVs) and on-site or adjacent photovoltaic generation (PVG) are pivotal to maintaining the security and economics of the operation of the power system concerned. Conventional offline optimization algorithms lack real-time applicability due to uncertainties involved in the charging service of an EV charging station (EVCS). Firstly, an optimization model for real-time EV charging strategy is proposed to address these challenges, which accounts for environmental uncertainties of an EVCS, encompassing EV arrivals, charging demands, PVG outputs, and the electricity price. Then, a scenario-based two-stage optimization approach is formulated. The scenarios of the underlying uncertain environmental factors are generated by the Bayesian long short-term memory (B-LSTM) network. Finally, numerical results substantiate the efficacy of the proposed optimization approach, and demonstrate superior profitability compared with prevalent approaches.
{"title":"Scenario-Based Optimal Real-Time Charging Strategy of Electric Vehicles with Bayesian Long Short-Term Memory Networks","authors":"Hongtao Ren;Chung-Li Tseng;Fushuan Wen;Chongyu Wang;Guoyan Chen;Xiao Li","doi":"10.35833/MPCE.2023.000512","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000512","url":null,"abstract":"Joint operation optimization for electric vehicles (EVs) and on-site or adjacent photovoltaic generation (PVG) are pivotal to maintaining the security and economics of the operation of the power system concerned. Conventional offline optimization algorithms lack real-time applicability due to uncertainties involved in the charging service of an EV charging station (EVCS). Firstly, an optimization model for real-time EV charging strategy is proposed to address these challenges, which accounts for environmental uncertainties of an EVCS, encompassing EV arrivals, charging demands, PVG outputs, and the electricity price. Then, a scenario-based two-stage optimization approach is formulated. The scenarios of the underlying uncertain environmental factors are generated by the Bayesian long short-term memory (B-LSTM) network. Finally, numerical results substantiate the efficacy of the proposed optimization approach, and demonstrate superior profitability compared with prevalent approaches.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"12 5","pages":"1572-1583"},"PeriodicalIF":5.7,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10445407","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142324365","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 : 2024-02-26DOI: 10.35833/MPCE.2023.000633
Shida Zhang;Shaoyun Ge;Hong Liu;Guocheng Hou;Chengshan Wang
To provide guidance for photovoltaic (PV) system integration in net-zero distribution systems (DSs), this paper proposes an analytical method for delineating the feasible region for PV integration capacities (PVICs), where the impact of battery energy storage system (BESS) flexibility is considered. First, we introduce distributionally robust chance constraints on network security and energy/carbon net-zero requirements, which form the upper and lower bounds of the feasible region. Then, the formulation and solution of the feasible region is proposed. The resulting analytical expression is a set of linear inequalities, illustrating that the feasible region is a polyhedron in a high-dimensional space. A procedure is designed to verify and adjust the feasible region, ensuring that it satisfies network loss constraints under alternating current (AC) power flow. Case studies on the 4-bus system, the IEEE 33-bus system, and the IEEE 123-bus system verify the effectiveness of the proposed method. It is demonstrated that the proposed method fully captures the spatio-temporal coupling relationship among PVs, loads, and BESSs, while also quantifying the impact of this relationship on the boundaries of the feasible region.
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Pub Date : 2024-02-12DOI: 10.35833/MPCE.2023.000909
Leijiao Ge;Tianshuo Du;Zhengyang Xu;Luyang Hou;Jun Yan;Yuanliang Li
The accurate identification of smart meter (SM) fault types is crucial for enhancing the efficiency of operation and maintenance (O&M) and the reliability of power collection systems. However, the intelligent classification of SM fault types faces significant challenges owing to the complexity of features and the imbalance between fault categories. To address these issues, this study presents a fault diagnosis method for SM incorporating three distinct modules. The first module employs a combination of standardization, data imputation, and feature extraction to enhance the data quality, thereby facilitating improved training and learning by the classifiers. To enhance the classification performance, the data imputation method considers feature correlation measurement and sequential imputation, and the feature extractor utilizes the discriminative enhanced sparse autoencoder. To tackle the interclass imbalance of data with discrete and continuous features, the second module introduces an assisted classifier generative adversarial network, which includes a discrete feature generation module. Finally, a novel Stacking ensemble classifier for SM fault diagnosis is developed. In contrast to previous studies, we construct a two-layer heuristic optimization framework to address the synchronous dynamic optimization problem of the combinations and hyper-parameters of the Stacking ensemble classifier, enabling better handling of complex classification tasks using SM data. The proposed fault diagnosis method for SM via two-layer stacking ensemble optimization and data augmentation is trained and validated using SM fault data collected from 2010 to 2018 in Zhejiang Province, China. Experimental results demonstrate the effectiveness of the proposed method in improving the accuracy of SM fault diagnosis, particularly for minority classes.
准确识别智能电表（SM）故障类型对于提高运行和维护（O&M）效率以及电力采集系统的可靠性至关重要。然而，由于特征的复杂性和故障类别之间的不平衡性，智能电表故障类型的智能分类面临着巨大挑战。为解决这些问题，本研究提出了一种包含三个不同模块的 SM 故障诊断方法。第一个模块采用标准化、数据估算和特征提取相结合的方法来提高数据质量，从而促进分类器的训练和学习。为了提高分类性能，数据估算方法考虑了特征相关性测量和顺序估算，而特征提取器则利用了判别增强型稀疏自动编码器。为了解决具有离散和连续特征的数据类间不平衡问题，第二个模块引入了辅助分类器生成对抗网络，其中包括离散特征生成模块。最后，我们开发了一种用于 SM 故障诊断的新型 Stacking 集合分类器。与以往研究不同的是，我们构建了一个双层启发式优化框架，以解决 Stacking 集合分类器的组合和超参数的同步动态优化问题，从而更好地处理使用 SM 数据的复杂分类任务。通过两层堆叠集合优化和数据增强提出的 SM 故障诊断方法，利用 2010 年至 2018 年在中国浙江省收集的 SM 故障数据进行了训练和验证。实验结果表明，所提出的方法能有效提高 SM 故障诊断的准确性，尤其是对少数类别的故障诊断。
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