Journal of Modern Power Systems and Clean Energy最新文献_第3页

Low-Frequency Oscillations and Resonance Analysis of VSG-Controlled PMSG-based Wind Generation Systems

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-10-24 DOI: 10.35833/MPCE.2024.000465

Yizhuo Ma;Jin Xu;Chenxiang Gao;Guojie Li;Keyou Wang

{"title":"Low-Frequency Oscillations and Resonance Analysis of VSG-Controlled PMSG-based Wind Generation Systems","authors":"Yizhuo Ma;Jin Xu;Chenxiang Gao;Guojie Li;Keyou Wang","doi":"10.35833/MPCE.2024.000465","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000465","url":null,"abstract":"With good adaptability to weak power grids, the grid-forming inverter becomes the foundation of future power grids with high-proportion renewable energy. Moreover, the virtual synchronous generator (VSG) control is recognized as the mainstream control strategy for grid-forming inverters. For permanent magnet synchronous generator (PMSG) based wind generation systems connected to power grid via VSG-controlled grid-forming inverters, some novel impacts on the low-frequency oscillations (LFOs) emerge in power grids. The first impact involves the negative/positive damping effect on LFOs. In this paper, the small-signal torque model of VSG-controlled PMSG-based wind generation systems is established based on the damping torque analysis method, revealing the influence mechanism of machine-side dynamics on LFOs and proving the necessity of the double-mass model for accurate stability analysis. The second impact is the resonance effect between torsional oscillation and LFOs. Subsequently, this paper uses the open-loop resonance analysis method to study the resonance mechanism and to predict the root trajectory. Then, a damping enhancement strategy is proposed to weaken and eliminate the negative damping effect of machine-side dynamics on LFOs and the resonance effect between torsional oscillation and LFOs. Finally, the analysis result is validated through a case study involving the connection of the VSG-controlled PMSG-based wind generation system to the IEEE 39-bus AC grid, supporting the industrial application and stable operation of VSG-controlled PMSG-based wind generation systems.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 1","pages":"115-127"},"PeriodicalIF":5.7,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10734987","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143184062","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}

引用次数: 0

Multi-Temporal Optimization of Virtual Power Plant in Energy-Frequency Regulation Market Under Uncertainties

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-10-22 DOI: 10.35833/MPCE.2024.000118

Wenping Qin;Xiaozhou Li;Xing Jing;Zhilong Zhu;Ruipeng Lu;Xiaoqing Han

{"title":"Multi-Temporal Optimization of Virtual Power Plant in Energy-Frequency Regulation Market Under Uncertainties","authors":"Wenping Qin;Xiaozhou Li;Xing Jing;Zhilong Zhu;Ruipeng Lu;Xiaoqing Han","doi":"10.35833/MPCE.2024.000118","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000118","url":null,"abstract":"The virtual power plant (VPP) facilitates the coordinated optimization of diverse forms of electrical energy through the aggregation and control of distributed energy resources (DERs), offering as a potential resource for frequency regulation to enhance the power system flexibility. To fully exploit the flexibility of DER and enhance the revenue of VPP, this paper proposes a multi-temporal optimization strategy of VPP in the energy-frequency regulation (EFR) market under the uncertainties of wind power (WP), photovoltaic (PV), and market price. Firstly, all schedulable electric vehicles (EVs) are aggregated into an electric vehicle cluster (EVC), and the schedulable domain evaluation model of EVC is established. A day-ahead energy bidding model based on Stackelberg game is also established for VPP and EVC. Secondly, on this basis, the multi-temporal optimization model of VPP in the EFR market is proposed. To manage risks stemming from the uncertainties of WP, PV, and market price, the concept of conditional value at risk (CVaR) is integrated into the strategy, effectively balancing the bidding benefits and associated risks. Finally, the results based on operational data from a provincial electricity market demonstrate that the proposed strategy enhances comprehensive revenue by providing frequency regulation services and encouraging EV response scheduling.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"675-687"},"PeriodicalIF":5.7,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10726909","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143698300","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}

引用次数: 0

Reinforcement Learning- and Option-Jointed Modeling for Cross-Market and Cross-Time Trading of Generators in Electricity and Carbon Markets

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-10-22 DOI: 10.35833/MPCE.2024.000013

Kai Jiang;Kunyu Wang;Lin Yang;Nian Liu

{"title":"Reinforcement Learning- and Option-Jointed Modeling for Cross-Market and Cross-Time Trading of Generators in Electricity and Carbon Markets","authors":"Kai Jiang;Kunyu Wang;Lin Yang;Nian Liu","doi":"10.35833/MPCE.2024.000013","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000013","url":null,"abstract":"With the development of the carbon markets (CMs) and electricity markets (EMs), discrepancies in prices between the two markets and between two time periods offer profit opportunities for generation companies (GenCos). Motivated by the carbon option and Black-Scholes (B-S) model, GenCos are given the right but not the obligation to trade carbon emission allowances (CEAs) and use instruments to hedge against price risks. To model the strategic behaviors of GenCos that capitalize on these cross-market and cross-time opportunities, a multi-market trading strategy that incorporates option-jointed daily trading and reinforcement learning-jointed weekly continuous trading are modeled. The daily trading is built with a bi-level structure, where a profit-oriented bidding model that jointly considers both the optimal CEA holding shares and the best bidding curves is developed at the upper level. At the lower level, in addition to market clearing models of the day-ahead EM and auction-based CM, a B-S model that considers carbon trading asynchronism and option pricing is constructed. Then, by expanding the daily trading, the weekly continuous trading is modeled and solved using reinforcement learning. Binary expansion and strike-to-spot price ratio are utilized to address the nonlinearity. Finally, case studies on an IEEE 30-bus system are conducted to validate the effectiveness of the proposed trading strategy. Results show that the proposed trading strategy can increase GenCo profits by influencing market prices and leveraging carbon options.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"637-649"},"PeriodicalIF":5.7,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10726915","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716549","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}

引用次数: 0

Dynamic Modelling, Control, and Stability Analysis of DC Modular Multilevel Converter Connected to HVDC Cables 与高压直流电缆相连的直流模块化多电平转换器的动态建模、控制和稳定性分析

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-10-15 DOI: 10.35833/MPCE.2023.001004

Salman Badkubi;Aliakbar Jamshidi Far;Sumeet S. Aphale

{"title":"Dynamic Modelling, Control, and Stability Analysis of DC Modular Multilevel Converter Connected to HVDC Cables","authors":"Salman Badkubi;Aliakbar Jamshidi Far;Sumeet S. Aphale","doi":"10.35833/MPCE.2023.001004","DOIUrl":"https://doi.org/10.35833/MPCE.2023.001004","url":null,"abstract":"Innovative dynamic models for the DC modular multilevel converter (DC-MMC) in rotating <tex>${dq}$</tex> frame are presented in this paper, which are specifically designed to enhance converter design and stability analysis. Open-loop and closed-loop models are developed using three <tex>${dq}$</tex> frames, providing a detailed examination of the impact of 2ndand 3rd harmonic components on the model accuracy. A novel contribution of this paper is the integration of a 2ndharmonic current suppression controller (SHCSC) within the closed-loop model, offering new insights into its effects on system stability. The DC-MMC model is further extended by coupling it with high-voltage direct current (HVDC) cables on each side, forming an interconnected system model that accurately represents a more authentic scenario for future DC grids. The proposed model is rigorously validated against PSCAD benchmark model, confirming their precision and reliability. The interconnected system model is then utilized to analyze the influence of cable length on system stability, demonstrating practical applications. The closed-loop model is subsequently employed for stability assessment of the inter-connected system, showcasing its applicability in real-world scenarios. Additionally, a damping controller is designed using participation factor and residue approaches, offering a refined approach to oscillation damping and stability optimization. The effectiveness of the controller is evaluated through eigenvalue analysis, supported by simulation results, underscoring its potential for enhancing system stability.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"710-719"},"PeriodicalIF":5.7,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10719598","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143698262","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}

引用次数: 0

Dynamic Nonlinear Droop-Based Fast Frequency Regulation for Power Systems with Flexible Resources Using Meta-Reinforcement Learning Approach

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-10-07 DOI: 10.35833/MPCE.2024.000062

Yuxin Ma;Zechun Hu;Yonghua Song

{"title":"Dynamic Nonlinear Droop-Based Fast Frequency Regulation for Power Systems with Flexible Resources Using Meta-Reinforcement Learning Approach","authors":"Yuxin Ma;Zechun Hu;Yonghua Song","doi":"10.35833/MPCE.2024.000062","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000062","url":null,"abstract":"The increasing penetration of renewable energy resources and reduced system inertia pose risks to frequency security of power systems, necessitating the development of fast frequency regulation (FFR) methods using flexible resources. However, developing effective FFR policies is challenging because different power system operating conditions require distinct regulation logics. Traditional fixed-coefficient linear droop-based control methods are suboptimal for managing the diverse conditions encountered. This paper proposes a dynamic nonlinear <tex>${P}-{f}$</tex> droop-based FFR method using a newly established meta-reinforcement learning (meta-RL) approach to enhance control adaptability while ensuring grid stability. First, we model the optimal FFR problem under various operating conditions as a set of Markov decision processes and accordingly formulate the frequency stability-constrained meta-RL problem. To address this, we then construct a novel hierarchical neural network (HNN) structure that incorporates a theoretical frequency stability guarantee, thereby converting the constrained meta-RL problem into a more tractable form. Finally, we propose a two-stage algorithm that leverages the inherent characteristics of the problem, achieving enhanced optimality in solving the HNN-based meta-RL problem. Simulations validate that the proposed FFR method shows superior adaptability across different operating conditions, and achieves better trade-offs between regulation performance and cost than benchmarks.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"379-390"},"PeriodicalIF":5.7,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10707106","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716390","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}

引用次数: 0

Graph Attention Network Based Deep Reinforcement Learning for Voltage/var Control of Topologically Variable Power System

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-10-04 DOI: 10.35833/MPCE.2023.000712

Xiaofei Liu;Pei Zhang;Hua Xie;Xuegang Lu;Xiangyu Wu;Zhao Liu

{"title":"Graph Attention Network Based Deep Reinforcement Learning for Voltage/var Control of Topologically Variable Power System","authors":"Xiaofei Liu;Pei Zhang;Hua Xie;Xuegang Lu;Xiangyu Wu;Zhao Liu","doi":"10.35833/MPCE.2023.000712","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000712","url":null,"abstract":"The high proportion of renewable energy integration and the dynamic changes in grid topology necessitate the enhancement of voltage/var control (VVC) to manage voltage fluctuations more rapidly. Traditional model-based control algorithms are becoming increasingly incompetent for VVC due to their high model dependence and slow online computation speed. To alleviate these issues, this paper introduces a graph attention network (GAT) based deep reinforcement learning for VVC of topologically variable power system. Firstly, combining the physical information of the actual power grid, a physics-informed GAT is proposed and embedded into the proximal policy optimization (PPO) algorithm. The GAT-PPO algorithm can capture topological and spatial correlations among the node features to tackle topology changes. To address the slow training, the ReliefF -S algorithm identifies critical state variables, significantly reducing the dimensionality of state space. Then, the training samples retained in the experience buffer are designed to mitigate the sparse reward issue. Finally, the validation on the modified IEEE 39-bus system and an actual power grid demonstrates superior performance of the proposed algorithm compared with state-of-the-art algorithms, including PPO algorithm and twin delayed deep deterministic policy gradient (TD3) algorithm. The proposed algorithm exhibits enhanced convergence during training, faster solution speed, and improved VVC performance, even in scenarios involving grid topology changes and increased renewable energy integration. Meanwhile, in the adopted cases, the network loss is reduced by 6.9%, 10.80%, and 7.70%, respectively, demonstrating favorable economic outcomes.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 1","pages":"215-227"},"PeriodicalIF":5.7,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10705987","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143183933","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}

引用次数: 0

Communication-Aware Restoration of Smart Distribution Grids Based on Optimal Allocation of Resilience Resources

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-10-04 DOI: 10.35833/MPCE.2024.000015

Youba Nait-Belaid;Yiping Fang;Zhiguo Zeng;Patrick Coudray;Anne Barros

{"title":"Communication-Aware Restoration of Smart Distribution Grids Based on Optimal Allocation of Resilience Resources","authors":"Youba Nait-Belaid;Yiping Fang;Zhiguo Zeng;Patrick Coudray;Anne Barros","doi":"10.35833/MPCE.2024.000015","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000015","url":null,"abstract":"Although power grids have become safer with increased situational awareness, major extreme events still pose reliability and resilience challenges, primarily at the distribution level, due to increased vulnerabilities and limited recovery resources. Information and communication technologies (ICIs) have introduced new vulnerabilities that have been widely investigated in previous studies. These vulnerabilities include remote device failures, communication channel disturbances, and cyber-attacks. However, only few studies have explored the opportunity offered by communications to improve the resilience of pow-er grids and eliminate the notion that power-telecom interdepen-dencies always pose a threat. This paper proposes a communication-aware restoration approach of smart distribution grids, which leverages power-telecom interdependencies to determine the optimal restoration strategies. The states of grid-energized telecom points are tracked to provide the best restoration actions, which are enabled through the resilience resources of re-pair, manual switching, remote reconfiguration, and distributed generators. As the telecom network coordinates the allocation of these resilience resources based on their coupling tendencies, different telecom architectures have been introduced to investigate the contribution of private and public ICTs to grid management and restoration operations. System restoration uses the configuration that follows a remote fast response as the input to formulate the problem as mixed-integer linear programming. Results from numerical simulations reveal an enhanced restoration process derived from telecom-aware recovery and the co-optimization of resilience resources. The existing disparity between overhead and underground power line configurations is also quantified.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"527-539"},"PeriodicalIF":5.7,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10705979","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716516","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}

引用次数: 0

Subsequent Commutation Failure Suppression Considering Negative-Sequence Voltage Caused by Symmetrical Fault at AC Side of Inverter 考虑到逆变器交流侧对称故障引起的负序电压，抑制后续换向故障

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-10-04 DOI: 10.35833/MPCE.2024.000352

Shenghu Li;Yikai Li

{"title":"Subsequent Commutation Failure Suppression Considering Negative-Sequence Voltage Caused by Symmetrical Fault at AC Side of Inverter","authors":"Shenghu Li;Yikai Li","doi":"10.35833/MPCE.2024.000352","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000352","url":null,"abstract":"The negative-sequence voltage is often caused by the asymmetrical fault in the AC system, as well as the harmonics after the symmetrical fault at the AC side of inverter in line commutated converter based high-voltage DC (LCC-HVDC). The negative-sequence voltage affects the phase-locked loop (PLL) and the inverter control, thus the inverter is vulnerable to the subsequent commutation failure (SCF). In this paper, the analytical expression of the negative-sequence voltage resulting from the symmetrical fault with the commutation voltage is derived using the switching function and Fourier decomposition. The analytical expressions of the outputs of the PLL and inverter control with respect to time are derived to quantify the contribution of the negative-sequence voltage to the SCF. To deal with the AC component of the input signals in the PLL and the inverter control due to the negative-sequence voltage, the existing proportional-integral controls of the PLL, constant current control, and constant extinction angle control are replaced by the linear active disturbance rejection control against the SCF. Simulation results verify the contributing factors to the SCF. The proposed control reduces the risk of SCF and improves the recovery speed of the system under different fault conditions.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"720-731"},"PeriodicalIF":5.7,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10705982","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143698356","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}

引用次数: 0

Operational Coordination Optimization of Electricity and Natural Gas Networks Based on Sequential Symmetrical Second-Order Cone Programming

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-10-04 DOI: 10.35833/MPCE.2023.000750

Liang Min;Chengwei Lou;Jin Yang;James Yu;Zhibin Yu

{"title":"Operational Coordination Optimization of Electricity and Natural Gas Networks Based on Sequential Symmetrical Second-Order Cone Programming","authors":"Liang Min;Chengwei Lou;Jin Yang;James Yu;Zhibin Yu","doi":"10.35833/MPCE.2023.000750","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000750","url":null,"abstract":"The variable and unpredictable nature of renewable energy generation (REG) presents challenges to its large-scale integration and the efficient and economic operation of the electricity network, particularly at the distribution level. In this paper, an operational coordination optimization method is proposed for the electricity and natural gas networks, aiming to overcome the identified negative impacts. The method involves the implementation of bi-directional energy flows through power-to-gas units and gas-fired power plants. A detailed model of the three-phase power distribution system up to each phase is employed to improve the representation of multi-energy systems to consider real-world end-user consumption. This method allows for the full consideration of unbalanced operational scenarios. Meanwhile, the natural gas network is modelled and analyzed with steady-state gas flows and the dynamics of the line pack in pipelines. The sequential symmetrical second-order cone programming (SS-SOCP) method is employed to facilitate the simultaneous analysis of three-phase imbalance and line pack while accelerating the solution process. The efficacy of the operational coordination optimization method is demonstrated in case studies comprising a modified IEEE 123-node power distribution system with a 20-node natural gas network. The studies show that the operational coordination optimization method can simultaneously minimize the total operational cost, the curtailment of installed REG, the voltage imbalance of three-phase power system, and the overall carbon emissions.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"488-499"},"PeriodicalIF":5.7,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10705989","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716446","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}

引用次数: 0

Optimal Power Dispatch of Active Distribution Network and P2P Energy Trading Based on Soft Actor-Critic Algorithm Incorporating Distributed Trading Control

IF 5.7 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2024-09-19 DOI: 10.35833/MPCE.2024.000471

Yongjun Zhang;Jun Zhang;Guangbin Wu;Jiehui Zheng;Dongming Liu;Yuzheng An

{"title":"Optimal Power Dispatch of Active Distribution Network and P2P Energy Trading Based on Soft Actor-Critic Algorithm Incorporating Distributed Trading Control","authors":"Yongjun Zhang;Jun Zhang;Guangbin Wu;Jiehui Zheng;Dongming Liu;Yuzheng An","doi":"10.35833/MPCE.2024.000471","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000471","url":null,"abstract":"Peer-to-peer (P2P) energy trading in active distribution networks (ADNs) plays a pivotal role in promoting the efficient consumption of renewable energy sources. However, it is challenging to effectively coordinate the power dispatch of ADNs and P2P energy trading while preserving the privacy of different physical interests. Hence, this paper proposes a soft actor-critic algorithm incorporating distributed trading control (SAC-DTC) to tackle the optimal power dispatch of ADNs and the P2P energy trading considering privacy preservation among prosumers. First, the soft actor-critic (SAC) algorithm is used to optimize the control strategy of device in ADNs to minimize the operation cost, and the primary environmental information of the ADN at this point is published to prosumers. Then, a distributed generalized fast dual ascent method is used to iterate the trading process of prosumers and maximize their revenues. Subsequently, the results of trading are encrypted based on the differential privacy technique and returned to the ADN. Finally, the social welfare value consisting of ADN operation cost and P2P market revenue is utilized as a reward value to update network parameters and control strategies of the deep reinforcement learning. Simulation results show that the proposed SAC-DTC algorithm reduces the ADN operation cost, boosts the P2P market revenue, maximizes the social welfare, and exhibits high computational accuracy, demonstrating its practical application to the operation of power systems and power markets.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"540-551"},"PeriodicalIF":5.7,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10684500","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716402","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}

引用次数: 0