参与气电市场的虚拟电厂内部优化随机模型

doi:10.11930/j.issn.1004-9649.201902182

中国电力 ›› 2020, Vol. 53 ›› Issue (9): 181-188.DOI: 10.11930/j.issn.1004-9649.201902182

• 基于虚拟电厂的调度运行优化专栏 • 上一篇下一篇

参与气电市场的虚拟电厂内部优化随机模型

彭院院¹, 周任军¹, 曾子琪², 冯剑³, 程远林³, 方绍凤³

1. 湖南省清洁能源与智能电网协同创新中心（长沙理工大学），湖南长沙 410004;
2. 国网湖南省电力有限公司娄底供电分公司，湖南娄底 417000;
3. 中国能源建设集团湖南省电力设计院有限公司，湖南长沙 410007

收稿日期:2019-02-28 修回日期:2019-08-09 发布日期:2020-09-09
作者简介:彭院院(1994—)，男，硕士研究生，从事电力系统运行与控制、电力需求侧响应研究，E-mail: 915277388@qq.com;周任军(1964—)，女，教授，从事电网规划、新能源接入系统、风险分析、分布式电源规划等研究，E-mail：zrj0731@163.com
基金资助:
国家自然科学基金资助项目(多源数据融合与人机混合实验驱动的两级电力市场全景式建模与决策理论研究，91746118)；湖南省自然科学基金资助项目(源荷特性指标与新能源消纳建模及数据驱动随机优化方法研究，2019JJ40302)

Internal Optimization Stochastic Model of Virtual Power Plant Participating in Gas and Electricity Market

PENG Yuanyuan¹, ZHOU Renjun¹, ZENG Ziqi², FENG Jian³, CHENG Yuanlin³, FANG Shaofeng³

1. Hunan Province Collaborative Innovation Center of Clean Energy and Smart Grid(Changsha University of Science and Technology), Changsha 410004, China;
2. Loudi Power Supply Branch, Hunan Province Electric Power Co.Ltd., Loudi 417000, China;
3. China Energy Engineering Group Hunan Electric Power Design Institute Co., Ltd., Changsha 410007, China

Received:2019-02-28 Revised:2019-08-09 Published:2020-09-09
Supported by:
This work is supported by National Natural Science Foundation of China (Multiple Data Fusion and Experimental Economics Driven Modeling and Decision Making Theory of Two Stage Power Market, No.91746118) and Natural Science Foundation of Hunan Province (Research on Characteristic Indexes and New Energy Consumption Modeling and Data-Driven Stochastic Optimization Methods, No.2019JJ40302).

摘要/Abstract

摘要： 虚拟电厂总体降低了不确定因素的影响，但若不考虑其内部的随机性，则会使虚拟电厂在参与电力、天然气市场过程中，因其调度方案的保守性，难以获得最高的经济效益。为了充分挖掘虚拟电厂的经济效益，提出了一种气电市场下计及电价和风光不确定性的电-热-气虚拟电厂随机优化调度模型。模型目标函数为虚拟电厂总效益，即售电售热售气收益与电转气成本、碳捕集成本、碳排放权成本和燃料成本之差。引入超分位数方法将含多随机变量的虚拟电厂总效益最优模型转化为其超分位数随机优化模型，为了便于计算进而处理为其离散化计算模型，并利用空间粒子群算法进行求解。算例分析表明：虚拟电厂通过优化售电和售气方案来获得最优效益，在参与气电市场过程中考虑多种随机变量，使得虚拟电厂规避风险后有更多的机会获得更高的经济效益。

关键词: 气电市场, 电-热-气虚拟电厂, 不确定性, 内部优化, 超分位数方法, 空间粒子群算法

Abstract: The virtual power plant (VPP) generally reduces the impact of uncertainties, but due to the conservative nature of its scheduling schemes, it is difficult for a VPP to obtain the highest economic benefits without considering the internal randomness in the process of participating in the electricity and gas market. In order to fully exploit the economic benefits of VPPs, a stochastic optimization scheduling model is proposed for electric-thermal-gas VPPs with consideration of the uncertainty of electricity price and wind-photovoltaic under gas and electricity market. The objective function of the model is the total benefit of VPPs, which is the difference between the sales of electricity, heat and gas and the cost for electricity to gas conversion, carbon capture, carbon emission and fuel. The superquantile method is introduced to convert the total benefit optimal model of VPPs with multiple random variables into a super-quantile random optimization model. For the convenience of calculation, the model is further processed into a discretization calculation model, and is solved with the spatial particle swarm optimization algorithm. The simulation results show that the VPP obtains the optimal benefits through optimizing the sale schemes of electricity and gas, and with consideration of various random variables in the process of participating in gas and electricity market, the VPP has more opportunities to obtain higher economic benefits after avoiding risks.

Key words: gas and electricity market, electric-thermal-gas virtual power plant, uncertainty, internal optimization, superquantile method, spatial particle swarm optimization algorithm

彭院院, 周任军, 曾子琪, 冯剑, 程远林, 方绍凤. 参与气电市场的虚拟电厂内部优化随机模型[J]. 中国电力, 2020, 53(9): 181-188.

PENG Yuanyuan, ZHOU Renjun, ZENG Ziqi, FENG Jian, CHENG Yuanlin, FANG Shaofeng. Internal Optimization Stochastic Model of Virtual Power Plant Participating in Gas and Electricity Market[J]. Electric Power, 2020, 53(9): 181-188.

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https://www.electricpower.com.cn/CN/Y2020/V53/I9/181

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参与气电市场的虚拟电厂内部优化随机模型

Internal Optimization Stochastic Model of Virtual Power Plant Participating in Gas and Electricity Market

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参与气电市场的虚拟电厂内部优化随机模型

Internal Optimization Stochastic Model of Virtual Power Plant Participating in Gas and Electricity Market

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