Journal of Modern Power Systems and Clean Energy最新文献_第4页

A Review of Optimal Scheduling and Distributed Cooperative Control for Smart Grids Integrated with Electric Vehicles 电动汽车集成智能电网最优调度与分布式协同控制研究进展

IF 6.2 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2026-07-01 Epub Date: 2025-09-16 DOI: 10.35833/MPCE.2025.000176

Xue Li;Junlin Yang;Dajun Du;Siqi Bu;Lei Wu;Chi Yung Chung;Kang Li

{"title":"A Review of Optimal Scheduling and Distributed Cooperative Control for Smart Grids Integrated with Electric Vehicles","authors":"Xue Li;Junlin Yang;Dajun Du;Siqi Bu;Lei Wu;Chi Yung Chung;Kang Li","doi":"10.35833/MPCE.2025.000176","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000176","url":null,"abstract":"The technological development of smart grids (SGs) has recently gained increased momentum due to large-scale integration of renewable energy sources (e. g., wind and photovoltaic power) and highly variable loads, including electric vehicles (EVs) along with the deepened decarbonization in power and transport systems as two major greenhouse gas-emitting sectors worldwide. With the development of SGs, fruitful achievements in optimal scheduling and distributed cooperative control have been made. However, a comprehensive survey of these methods covering the low-carbon, economy, and cybersecurity metrics is still missing. This paper bridges the gap with the aim of providing an indepth overview of optimal scheduling and distributed cooperative control from the whole system perspective within the SG framework. First, the fundamental mathematical models of optimal scheduling for low-carbon, economy, and cybersecurity operations are reviewed, the corresponding solution methods are summarized, and the cooperative optimization and scheduling methods for SGs integrated with EVs are specifically analyzed. Second, the performances of centralized and distributed cooperative control methods are compared, and two popular distributed cooperative control frameworks, namely centralized-distributed and autonomous-distribute frameworks, are further discussed comprehensively. Third, typical real-world applications of optimal scheduling and distributed cooperative control are analyzed. Finally, the trends and challenges of optimal scheduling and distributed cooperative control for effectively integrating EVs in SGs are prospected.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1228-1245"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11168117","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148625952","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

Cybersecurity in Virtual Power Plants: A Review of Theoretical Framework, Risk Analysis, and Defense Technologies 虚拟电厂的网络安全：理论框架、风险分析和防御技术综述

IF 6.2 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2026-07-01 Epub Date: 2026-06-19 DOI: 10.35833/MPCE.2026.000042

Jiayu Li;Hongchao Gao;Chongqing Kang;Yiwei Cui;Wenmeng Zhao;Tian Mao

{"title":"Cybersecurity in Virtual Power Plants: A Review of Theoretical Framework, Risk Analysis, and Defense Technologies","authors":"Jiayu Li;Hongchao Gao;Chongqing Kang;Yiwei Cui;Wenmeng Zhao;Tian Mao","doi":"10.35833/MPCE.2026.000042","DOIUrl":"https://doi.org/10.35833/MPCE.2026.000042","url":null,"abstract":"Virtual power plants (VPPs) can participate in electricity market trading by aggregating distributed energy resources, thereby providing flexible regulation services to the power system. However, the interaction between VPPs and the power system involves high-frequency and multi-party data exchange, posing significant cybersecurity risks. To ensure the cybersecurity of VPPs throughout the entire interaction process, this paper first analyzes the intrinsic attributes of VPPs, identifying three key characteristics: aggregation, interaction, and regulation. Based on this, it integrates these attributes with confidentiality, integrity, and availability triad to construct a cyber-security theoretical framework for VPPs. Second, this paper outlines the business processes, data interactions, and communication architecture of VPPs. Then, a risk analysis of potential cyberattacks is performed, detailing their injection points, propagation paths, and potential impacts of typical cyberattacks. Third, the core application mechanisms and use cases of key cybersecurity defense technologies are summarized. These technologies are applicable to interactions between VPP and power systems across different stages, including data anonymization, encryption, privacy-preserving computation, access control, and blockchain. Finally, an analysis of the current status, challenges, and prospects of artificial intelligence (AI)-based cybersecurity technologies is presented, which provides support for constructing a secure and reliable cybersecurity defense system for VPPs.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1151-1171"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11573233","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148626429","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

Value-Based Data Governance and Security Protection for Virtual Power Plants Aggregated by Demand-Side Flexible Loads 需求侧灵活负荷聚合的虚拟电厂基于价值的数据治理与安全防护

IF 6.2 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2026-07-01 Epub Date: 2025-12-09 DOI: 10.35833/MPCE.2025.000787

Jiabao Li;Hongxun Hui;Yonghua Song;Ye Chen;Tao Chen;Pierluigi Siano

{"title":"Value-Based Data Governance and Security Protection for Virtual Power Plants Aggregated by Demand-Side Flexible Loads","authors":"Jiabao Li;Hongxun Hui;Yonghua Song;Ye Chen;Tao Chen;Pierluigi Siano","doi":"10.35833/MPCE.2025.000787","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000787","url":null,"abstract":"Virtual power plants (VPPs) aggregated by demand-side flexible loads have become a key mechanism for balancing supply and demand in power systems. However, compared with conventional power plants, VPPs generate vast and heterogeneous datasets that are challenging to manage and protect effectively. Existing solutions often fail to unlock the full value of these data while imposing excessive security costs. This paper proposes a value-based data governance and security protection framework tailored for VPPs aggregated by demand-side flexible loads. Within this framework, a real-time data value assessment model is developed to dynamically assess the value of demand-side flexible load data. Furthermore, a fine-grained data management and protection strategy is introduced to enable differentiated governance and security measures. These measures are applied across different stages of the data life cycle according to the assessed data value levels. Numerical results demonstrate that the proposed framework <sup>en</sup>hances both data protection and operational performance while reducing security costs. Moreover, it promotes data circulation and value creation, and supports the sustainable and intelligent transformation of modern power systems.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1172-1184"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11293064","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148626648","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

Day-Ahead Pricing Strategy for Virtual Power Plants Considering Privacy Protection of User Data 考虑用户数据隐私保护的虚拟电厂日前电价策略

IF 6.2 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2026-07-01 Epub Date: 2026-06-19 DOI: 10.35833/MPCE.2025.000971

Xiangyu Kong;Bohan Yang;Peirong Zhang;Wenqi Lu;Gaohua Liu

{"title":"Day-Ahead Pricing Strategy for Virtual Power Plants Considering Privacy Protection of User Data","authors":"Xiangyu Kong;Bohan Yang;Peirong Zhang;Wenqi Lu;Gaohua Liu","doi":"10.35833/MPCE.2025.000971","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000971","url":null,"abstract":"As an advanced aggregation and control technology for multi-type source-load resources, virtual power plant (VPP) enables intelligent interconnection and coordinated optimization of distributed load resources. This paper proposes a day-ahead pricing strategy for VPPs considering privacy protection of user data. First, a day-ahead pricing model for VPP is constructed, which considers historical demand response (DR) contributions of users to enhance fairness in the pricing process. The asynchronous advantage actor-critic (A3C) algorithm is adopted to solve this model and optimize pricing decisions. Furthermore, an encrypted horizontal federated learning (HFL) method is proposed for model training, which is based on improved weighted federated averaging algorithm and aims to mitigate data silos and protect privacy of user data across different regions. Instead of directly transmitting user data during training, partially homomorphic encryption (PHE) scheme is applied to encrypt exchanged model parameters, thereby reducing the risk of privacy leakage. Case studies validate that the proposed pricing strategy can enhance the fairness of multi-user regulation decisions and improve the performance of VPPs in day-ahead DR while ensuring the security of user data.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1198-1209"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11573228","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148628308","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

Hierarchical Coordination Optimization Method of Isolated Electricity-Hydrogen Microgrids with High Penetration of Renewable Energy Sources 高可再生能源渗透率电氢隔离微电网层次协调优化方法

IF 6.2 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2026-07-01 Epub Date: 2025-11-12 DOI: 10.35833/MPCE.2025.000303

Jizhong Zhu;Taiheng Guo;Shenglin Li;Hanjiang Dong;Alberto Borghetti;Xuemeng Lan

{"title":"Hierarchical Coordination Optimization Method of Isolated Electricity-Hydrogen Microgrids with High Penetration of Renewable Energy Sources","authors":"Jizhong Zhu;Taiheng Guo;Shenglin Li;Hanjiang Dong;Alberto Borghetti;Xuemeng Lan","doi":"10.35833/MPCE.2025.000303","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000303","url":null,"abstract":"Renewable energy sources (RESs), particularly solar and wind energy, present a viable pathway for decarbonizing isolated microgrids (MGs). However, as the penetration of RESs increases, ensuring the optimal utilization of RESs while maintaining the system reliability poses significant challenges for isolated MGs. Therefore, a hierarchical coordination optimization method of the isolated electricity-hydrogen MG with high penetration of RESs is proposed to achieve low-carbon dispatching. The developed isolated electricity-hydrogen MG is an integrated system featuring hybrid battery-hydrogen energy storage, which encompasses three interconnected subsystems: an AC subsystem, a DC subsystem, and a hydrogen subsystem. The proposed method can be divided into two dispatch horizons: an annual horizon and a daily horizon. The annual horizon focuses on the inter-day energy dispatch, addressing hydrogen storage boundary conditions to solve seasonal energy mismatches. The daily horizon focuses on the day-ahead power dispatch to ensure the daily power balance of MG, taking into account the errors in annual estimated data. The effectiveness of the proposed method is validated through a series of case studies for an isolated electricity-hydrogen MG under varying penetrations of RESs and energy storage configurations. Simulation results show the promising potential of the proposed method in facilitating sustainable isolated electricity-hydrogen MGs.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1451-1464"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11244253","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148627278","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

A Data-Driven and Deep Learning-Based Method for Power System Operating Mode Identification 基于数据驱动和深度学习的电力系统运行模式识别方法

IF 6.2 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2026-07-01 Epub Date: 2026-04-02 DOI: 10.35833/MPCE.2025.000634

Chuan He;Honghao Zhang;Nan Lu;Jiawei Hu;Tianqi Liu;Biao Wang;Jian Gao;Xi Ye

{"title":"A Data-Driven and Deep Learning-Based Method for Power System Operating Mode Identification","authors":"Chuan He;Honghao Zhang;Nan Lu;Jiawei Hu;Tianqi Liu;Biao Wang;Jian Gao;Xi Ye","doi":"10.35833/MPCE.2025.000634","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000634","url":null,"abstract":"Efficient and accurate analysis for power system operating mode identification is crucial for handling the operation, planning, and stability analysis of future power systems. This paper proposes a data-driven and deep learning-based method for power system operating mode identification, while also addressing the needs for identifying future operating modes. Firstly, an operating mode analysis method is developed based on adaptive threshold affinity propagation (AP) clustering with dynamic time warping (DTW), which incorporates historical load sequences and employs a modified distance function and adaptive thresholds for clustering. Secondly, a parallel temporal fusion network (PTFN) model with temporal feature proj ection is proposed to address load uncertainty. Finally, based on the results of historical operating mode analysis and future load forecasting, a Shapley additive explanation with parallel temporal convolution network and the squeeze-excitation mechanism (SHAP-PTCN-SE) is proposed for identifying future operating modes. Numerical examples demonstrate the efficiency and accuracy of the proposed data-driven and deep learning-based method in identifying future operating modes, providing guidance for system monitoring and protection.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1284-1296"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11473942","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148628152","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-Agent Bi-Level Game Model for Park-Level Integrated Energy System Based on Electricity-Carbon Market Collaborative Decision-Making Mechanism 基于电力-碳市场协同决策机制的园区级综合能源系统多智能体双层博弈模型

IF 6.2 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2026-07-01 Epub Date: 2025-12-30 DOI: 10.35833/MPCE.2025.000463

Yumin Zhang;Jingrui Li;Xingquan Ji;Zhaoyang Dong;Li Yu

{"title":"Multi-Agent Bi-Level Game Model for Park-Level Integrated Energy System Based on Electricity-Carbon Market Collaborative Decision-Making Mechanism","authors":"Yumin Zhang;Jingrui Li;Xingquan Ji;Zhaoyang Dong;Li Yu","doi":"10.35833/MPCE.2025.000463","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000463","url":null,"abstract":"Effective coordination between electricity and carbon markets is critical for enabling energy-efficient decarbonization in integrated energy system. However, the inherent differences in trading products and timescales between two markets render independent electricity - carbon market mechanism invalid and target mismatch, particularly within multi-agent market environments. Hence, a multi-agent bi-level game model for park-level integrated energy system (PIES) is proposed in this paper, incorporating a novel electricity-carbon market collaborative decision-making mechanism. An equal-interval time discretization method is developed to reconcile the heterogeneity of discrete electricity market and continuous carbon market, enabling consistent timescale coordination. An improved alternating direction method of multipliers (ADMM) algorithm based on Peaceman-Rachford is adopted to achieve benefit allocation and rapid privacy-solving. Simulation results demonstrate the effectiveness of proposed multi-agent bi-level game model in balancing carbon reduction and economic efficiency, and enhancing the operation efficiency of multi-agent collaboration.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1479-1490"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11319373","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148628296","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

Corrective $N-k$ Security-constrained Unit Commitment Using Lossy Shift Factors and Fictitious Injections 利用有损移位因子和虚拟注入校正$N-k$安全约束单元承诺

IF 6.2 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2026-07-01 Epub Date: 2026-01-16 DOI: 10.35833/MPCE.2025.000430

Sergio Ramírez-López;Guillermo Gutiérrez-Alcaraz;José M. Arroyo;Víctor H. Hinojosa

{"title":"Corrective $N-k$ Security-constrained Unit Commitment Using Lossy Shift Factors and Fictitious Injections","authors":"Sergio Ramírez-López;Guillermo Gutiérrez-Alcaraz;José M. Arroyo;Víctor H. Hinojosa","doi":"10.35833/MPCE.2025.000430","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000430","url":null,"abstract":"Power systems worldwide are increasingly experiencing the simultaneous failure of multiple components due to severe weather conditions, which are becoming more frequent and intense. This consequently triggers growing interest in more stringent security standards. Indeed, electricity markets are moving toward explicitly including generator outages within auction models seeking the most economical and reliable generation scheduling and dispatch. Within this context, a corrective <tex>$N-k$</tex> security-constrained unit commitment model is proposed to address the need for tighter security standards. As a major distinctive feature, the proposed model jointly considers multiple out-of-service generators and lines, corrective actions, and transmission line losses. Moreover, unlike previous studies, lossy shift factors are used to represent the effect of the lossy transmission network while accurately characterizing transmission line losses by a binary-variable-based piecewise linear approximation. Additionally, line outages are incorporated by modeling fictitious injections of active power. The proposed model using lossy shift factors and fictitious injections is cast as an instance of mixed-integer linear programming. The solution of the resulting mathematical problem allows co-optimizing energy and reserves to accommodate the power fluctuations due to the component outages under consideration. Numerical experience is reported using three standard benchmarks comprising 14, 118, and 500 buses.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1272-1283"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11357499","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148625954","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

Tractable Modeling of Decision-Dependent Customer Interruption Cost and Cold Load Pickup for Optimizing Power Distribution System Restoration 基于决策依赖的客户中断成本建模及冷负荷提取优化配电系统恢复

IF 6.2 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2026-07-01 Epub Date: 2026-01-19 DOI: 10.35833/MPCE.2025.000213

Wei Wang;Minwu Chen;Hongbin Wang;Gaoqiang Peng;Hongzhou Chen

{"title":"Tractable Modeling of Decision-Dependent Customer Interruption Cost and Cold Load Pickup for Optimizing Power Distribution System Restoration","authors":"Wei Wang;Minwu Chen;Hongbin Wang;Gaoqiang Peng;Hongzhou Chen","doi":"10.35833/MPCE.2025.000213","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000213","url":null,"abstract":"Developing optimized restoration strategies for power distribution systems (PDSs) is critical to enhancing resilience. Prior knowledge of customer interruption cost (CIC) and load restoration behaviors, particularly cold load pickup (CLPU), is essential for effective decision-making. However, both CIC and CLPU are reciprocally influenced by the realized customer interruption duration (CID), making them decision-dependent and challenging to model, especially with limited understanding of underlying physical mechanisms. This study proposes a tractable modeling approach of decision-dependent CIC and CLPU for optimizing power distribution system restoration to capture the varying patterns of both CIC and CLPU with CID, i.e., patterns derived from data that reflect observable surface-level correlations rather than underlying mechanisms, thereby enabling practical surrogate modeling of decision-dependent factors. Specifically, quadratic functions are employed to model the increasing rate of CIC with respect to CID according to data fitting results. For CLPU, several defining characteristics are extracted and modeled in a piecewise linear form relative to CID, from which the actual restored load accounting for CLPU is subsequently reconstructed. Building on these models, a PDS restoration framework is developed, incorporating mobile energy storage systems (MESSs) and network reconfiguration strategies. Case studies validate the effectiveness of the proposed approach and highlight the unique potential of MESS in accelerating CLPU-related restoration.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1374-1386"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11358962","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148626685","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 Urban Multi-Network Coordination Considering Hybrid Pricing Strategy for Electricity and Hydrogen Trading 考虑电氢混合定价策略的城市多网最优协调

IF 6.2 1区工程技术

Journal of Modern Power Systems and Clean Energy Pub Date : 2026-07-01 Epub Date: 2025-09-05 DOI: 10.35833/MPCE.2025.000147

Cun Zhang;Yifei Wang;Yujian Ye;Qingshan Xu;Pei Zhang

{"title":"Optimal Urban Multi-Network Coordination Considering Hybrid Pricing Strategy for Electricity and Hydrogen Trading","authors":"Cun Zhang;Yifei Wang;Yujian Ye;Qingshan Xu;Pei Zhang","doi":"10.35833/MPCE.2025.000147","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000147","url":null,"abstract":"The growing demand for optimal urban multi-network coordination has intensified the interdependencies among urban transportation, energy systems, and carbon emissions, with integrated charging stations (ICSs) playing a pivotal role in this interconnected ecosystem. However, optimal coordination across these networks and hybrid pricing strategy for electricity and hydrogen trading remain significant challenges. This paper presents an optimal urban multi-network coordination framework, integrating the urban traffic network (UTN), power distribution network (PDN), urban hydrogen network (UHN), hydrogen supply chain (HSC), ICS, and carbon emission evaluation. The proposed framework aims to maximize regional social welfare, support low-carbon objectives, and optimize multi-network coordination through a two-layer iterative optimization process. Next, a hybrid pricing strategy for electricity and hydrogen trading is introduced, focusing on addressing urban safety constraints. This strategy employs peer-to-peer (P2P) trading for transactions between logistics operators and ICSs. Finally, simulation results on a IEEE 20-node UTN and IEEE 33-node PDN validate the efficiency and accuracy of the proposed framework, demonstrating improvements in multi-network coordination, reductions in traffic congestion and hydrogen transport risks, lower carbon emissions, and enhanced economic performance of both ICSs and central hydrogen production facility (CHPF).","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 4","pages":"1491-1502"},"PeriodicalIF":6.2,"publicationDate":"2026-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11152643","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148626833","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