Optimal Operation Method for Virtual Power Plant Based on Joint Sharing of Energy and Reserve of Prosumers

SONG Meng; JING Xinyi; CAI Yunfeng; GAO Ciwei; YAN Xingyu; REN Shuangxue

doi:10.7500/AEPS20231226005

您当前的位置：

首页 >

文章列表页 >

Optimal Operation Method for Virtual Power Plant Based on Joint Sharing of Energy and Reserve of Prosumers

Special Session on Virtual Power Plant with Enormous Flexible Resources | 更新时间：2025-06-16

- Optimal Operation Method for Virtual Power Plant Based on Joint Sharing of Energy and Reserve of Prosumers
- Automation of Electric Power Systems Vol. 48, Issue 18, Pages: 3-13(2024)
- 作者机构：
  
  1.东南大学电气工程学院，江苏省南京市 210096
  2.国网连云港供电公司，江苏省连云港市 222000
  3.国网陕西省电力有限公司经济技术研究院，陕西省西安市 710075
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(52007030);Jiangsu Science and Technology Youth Talent Lifting Project(TJ-2022-042)
- DOI：10.7500/AEPS20231226005
  CLC：
- Received：26 December 2023，
  
  Revised：2024-04-08，
  
  Published Online：13 August 2024，
  
  Published：25 September 2024
- 稿件说明：
移动端阅览
宋梦,经昕怡,蔡昀峰等.基于产消者能量-备用联合共享的虚拟电厂优化运营方法[J].电力系统自动化,2024,48(18):3-13.

SONG Meng,JING Xinyi,CAI Yunfeng,et al.Optimal Operation Method for Virtual Power Plant Based on Joint Sharing of Energy and Reserve of Prosumers[J].Automation of Electric Power Systems,2024,48(18):3-13.
宋梦,经昕怡,蔡昀峰等.基于产消者能量-备用联合共享的虚拟电厂优化运营方法[J].电力系统自动化,2024,48(18):3-13. DOI： 10.7500/AEPS20231226005.

SONG Meng,JING Xinyi,CAI Yunfeng,et al.Optimal Operation Method for Virtual Power Plant Based on Joint Sharing of Energy and Reserve of Prosumers[J].Automation of Electric Power Systems,2024,48(18):3-13. DOI： 10.7500/AEPS20231226005.

摘要

为促进多层级市场环境下多市场主体的协调优化与权责一体，通过虚拟电厂（VPP）将本地点对点（P2P）交易与批发市场衔接起来，提出一种基于产消者能量和备用联合共享的VPP优化运营方法。首先，将备用需求的溯源交易扩展至配电网市场，并通过自适应交替方向乘子法(ADMM)实现本地能量与备用的分布式出清。然后，建立VPP-产消者双层交易模型，上层VPP收集产消者需求并参与批发市场交易，优化购售价格；下层产消者采用通用高斯分布与机会约束理论量化备用需求、决策能量与备用量。最后，基于二分法对模型进行求解。算例结果表明，所提机制在扩大VPP市场收益的同时实现了对产消者备用成本的溯源分摊，而本地市场增大了产消者与VPP的议价空间。

Abstract

To promote the coordination and optimization of multi-market entities and the entities of power and responsibility in a multi-level market environment

this paper combines local peer-to-peer (P2P) transactions with wholesale markets through the virtual power plant (VPP). An optimal operation method for VPP based on the joint sharing of energy and reserve of prosumers is proposed. Firstly

the reserve requirement is extended to the distribution network market and the local energy-reserve market is distributedly cleared by the adaptive alternating direction method of multipliers (ADMM). Secondly

a bi-level trading model of VPP-prosumer is established. The upper-level VPP collects the transaction demands of prosumers and optimizes the purchase and sale prices. The lower-level prosumers quantify reserve demands

decision energy and reserve capacity by using the general Gaussian distribution and opportunity constraint theory. Finally

the model is solved by dichotomy. The results show that the proposed mechanism increases the market income of VPP and realizes the traceability and allocation of reserve cost to prosumers. The local market enlarges the bargaining space of VPP and prosumers.

关键词

Keywords

references

SONG M ， GAO C W . Integration of distributed resources in smart grids for demand response and transactive energy： a case study of TCLs ［M］. Singapore ： Springer Singapore ， 2022 .

SONG M ， GAO C W ， MA S S ， et al . Distributed scheduling of HVACs based on transactive energy and ADMM ［J］. Applied Energy ， 2022 ， 325 ： 119831 .

高赐威 . 虚拟电厂的概念思辨［J］. 供用电， 2023 ， 40 （ 12 ）： 2 - 6 .

GAO Ciwei . Conceptual reflection on virtual power plants ［J］. Distribution & Utilization ， 2023 ， 40 （ 12 ）： 2 - 6 .

袁桂丽，钟飞，张睿，等 . 考虑碳捕集及需求响应的虚拟电厂热电联合优化调度［J］. 电网技术， 2023 ， 47 （ 11 ）： 4458 - 4467 .

YUAN Guili ， ZHONG Fei ， ZHANG Rui ， et al . Combined heat and power scheduling optimization for virtual power plants considering carbon capture and demand response ［J］. Power System Technology ， 2023 ， 47 （ 11 ）： 4458 - 4467 .

王晛，张华君，张少华 . 风电和电动汽车组成虚拟电厂参与电力市场的博弈模型［J］. 电力系统自动化， 2019 ， 43 （ 3 ）： 155 - 162 .

WANG Xian ， ZHANG Huajun ， ZHANG Shaohua . Game model of electricity market involving virtual power plant composed of wind power and electric vehicles ［J］. Automation of Electric Power Systems ， 2019 ， 43 （ 3 ）： 155 - 162 .

李嘉媚，艾芊，殷爽睿 . 虚拟电厂参与调峰调频服务的市场机制与国外经验借鉴［J］. 中国电机工程学报， 2022 ， 42 （ 1 ）： 37 - 56 .

LI Jiamei ， AI Qian ， YIN Shuangrui . Market mechanism and foreign experience of virtual power plant participating in peak-regulation and frequency-regulation ［J］. Proceedings of the CSEE ， 2022 ， 42 （ 1 ）： 37 - 56 .

孙国强，周亦洲，卫志农，等 . 能量和旋转备用市场下虚拟电厂热电联合调度鲁棒优化模型［J］. 中国电机工程学报， 2017 ， 37 （ 11 ）： 3118 - 3128 .

SUN Guoqiang ， ZHOU Yizhou ， WEI Zhinong ， et al . Thermal and electrical scheduling of a virtual power plant for participating in energy and spinning reserve markets based on robust optimization ［J］. Proceedings of the CSEE ， 2017 ， 37 （ 11 ）： 3118 - 3128 .

SONG Meng ， XU Xiaoyuan ， GAO Ciwei ， et al . Two-stage stochastic scheduling of virtual power plant based on transactive control ［J/OL］. CSEE Journal of Power and Energy Systems ［ 2023-06-27 ］. https：//ieeexplore.ieee.org/document/10165671 https://ieeexplore.ieee.org/document/10165671 .

SONG M ， SUN W ， WANG Y F ， et al . Hierarchical scheduling of aggregated TCL flexibility for transactive energy in power systems ［J］. IEEE Transactions on Smart Grid ， 2020 ， 11 （ 3 ）： 2452 - 2463 .

HU J ， HARMSEN R ， CRIJNS-GRAUS W ， et al . Identifying barriers to large-scale integration of variable renewable electricity into the electricity market： a literature review of market design ［J］. Renewable and Sustainable Energy Reviews ， 2018 ， 81 ： 2181 - 2195 .

SONG M ， CAI Y F ， GAO C W ， et al . Transactive energy in power distribution systems： paving the path towards cyber-physical-social system ［J］. International Journal of Electrical Power and Energy Systems ， 2022 ， 142 ： 108289 .

ZHANG Z ， LI R ， LI F R . A novel peer-to-peer local electricity market for joint trading of energy and uncertainty ［J］. IEEE Transactions on Smart Grid ， 2020 ， 11 （ 2 ）： 1205 - 1215 .

KHORASANY M ， MISHRA Y ， LEDWICH G . A decentralized bilateral energy trading system for peer-to-peer electricity markets ［J］. IEEE Transactions on Industrial Electronics ， 2020 ， 67 （ 6 ）： 4646 - 4657 .

蔡昀峰，宋梦，高赐威，等 . 考虑碳积分与电能溯源的绿色社区能量共享策略［J］. 中国电机工程学报， 2024 ， 44 （ 6 ）： 2157 - 2171 .

CAI Yunfeng ， SONG Meng ， GAO Ciwei ， et al . Energy sharing strategy in green communities considering carbon credit and power traceability ［J］. Proceedings of the CSEE ， 2024 ， 44 （ 6 ）： 2157 - 2171 .

叶宇剑，袁泉，刘文雯，等 . 基于参数共享机制多智能体深度强化学习的社区能量管理协同优化［J］. 中国电机工程学报， 2022 ， 42 （ 21 ）： 7682 - 7695 .

YE Yujian ， YUAN Quan ， LIU Wenwen ， et al . Parameter sharing empowered multi-agent deep reinforcement learning for coordinated management of energy communities ［J］. Proceedings of the CSEE ， 2022 ， 42 （ 21 ）： 7682 - 7695 .

GUO Z W ， PINSON P ， CHEN S B ， et al . Chance-constrained peer-to-peer joint energy and reserve market considering renewable generation uncertainty ［J］. IEEE Transactions on Smart Grid ， 2021 ， 12 （ 1 ）： 798 - 809 .

YAN X Y ， GAO C W ， SONG M ， et al . An IGDT-based day-ahead co-optimization of energy and reserve in a VPP considering multiple uncertainties ［J］. IEEE Transactions on Industry Applications ， 2022 ， 58 （ 3 ）： 4037 - 4049 .

JIANG T ， WU C H ， ZHANG R F ， et al . Risk-averse TSO-DSOs coordinated distributed dispatching considering renewable energy and demand response uncertainties ［J］. Applied Energy ， 2022 ， 327 ： 120024 .

YAN X Y ， SONG M ， CAO J C ， et al . Peer-to-Peer transactive energy trading of multiple microgrids considering renewable energy uncertainty ［J］. International Journal of Electrical Power & Energy Systems ， 2023 ， 152 ： 109235 .

CUI S C ， WANG Y W ， SHI Y ， et al . A new and fair peer-to-peer energy sharing framework for energy buildings ［J］. IEEE Transactions on Smart Grid ， 2020 ， 11 （ 5 ）： 3817 - 3826 .

李鹏，吴迪凡，李雨薇，等 . 基于综合需求响应和主从博弈的多微网综合能源系统优化调度策略［J］. 中国电机工程学报， 2021 ， 41 （ 4 ）： 1307 - 1321 .

LI Peng ， WU Difan ， LI Yuwei ， et al . Optimal dispatch of multi-microgrids integrated energy system based on integrated demand response and Stackelberg game ［J］. Proceedings of the CSEE ， 2021 ， 41 （ 4 ）： 1307 - 1321 .

MORSTYN T ， MCCULLOCH M D . Multiclass energy management for peer-to-peer energy trading driven by prosumer preferences ［J］. IEEE Transactions on Power Systems ， 2019 ， 34 （ 5 ）： 4005 - 4014 .

SINHA A ， MALO P ， DEB K . A review on bilevel optimization： from classical to evolutionary approaches and applications ［J］. IEEE Transactions on Evolutionary Computation ， 2018 ， 22 （ 2 ）： 276 - 295 .

COLSON B ， MARCOTTE P ， SAVARD G . An overview of bilevel optimization ［J］. Annals of Operations Research ， 2007 ， 153 （ 1 ）： 235 - 256 .

CHENG Y H ， ZHANG N ， ZHANG B S ， et al . Low-carbon operation of multiple energy systems based on energy-carbon integrated prices ［J］. IEEE Transactions on Smart Grid ， 2020 ， 11 （ 2 ）： 1307 - 1318 .

陈乐飞，朱自伟，王凯，等 . 基于混合博弈的配电网与多综合能源微网优化运行［J］. 电网技术， 2023 ， 47 （ 6 ）： 2229 - 2243 .

CHEN Lefei ， ZHU Ziwei ， WANG Kai ， et al . Optimal operation of distribution networks and multiple integrated energy microgrids based on mixed game theory ［J］. Power System Technology ， 2023 ， 47 （ 6 ）： 2229 - 2243 .

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Market Mechanisms and Profit Modes of Virtual Power Plants and Analysis of Their Operation Cases in Europe

Bidding Mechanism Design for Building Virtual Power Plant to Participate in Demand Response Markets

Two-stage Robust Trading Strategy for Virtual Power Plant in Multi-level Electricity-Carbon Coupling Market

风电和电动汽车组成虚拟电厂参与电力市场的博弈模型

Related Author

WANG Di

AI Qian

YU Tao

ZUO Juan

LU Yi

LI Jiamei

HUANG Yuxiang

HUANG Weiliang

Related Institution

Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education (Shanghai Jiao Tong University)

State Grid Shanghai Municipal Electric Power Company

State Grid Shanghai Energy Interconnection Research Institute Co., Ltd.

School of Electric Power Engineering, South China University of Technology

Guangdong Power Grid Co., Ltd.

⁰