双重需求响应的虚拟电厂建模与调度研究

doi:10.16182/j.issn1004731x.joss.21-1234

系统仿真学报 ›› 2023, Vol. 35 ›› Issue (4): 822-832.doi: 10.16182/j.issn1004731x.joss.21-1234

• 论文 • 上一篇

双重需求响应的虚拟电厂建模与调度研究

陈强¹(), 王意²^,³(), 李康顺⁴

^1.东莞城市学院计算机与信息学院, 广东东莞 523109
^2.华南农业大学人工智能学院, 广东广州 510642
^3.广东科技学院计算机学院, 广东东莞 523083
^4.华南农业大学数学与信息学院, 广东广州 510642

收稿日期:2021-12-02 修回日期:2022-01-22 出版日期:2023-04-29 发布日期:2023-04-12
通讯作者: 王意 E-mail:48044244@qq.com;gust312@163.com
作者简介:陈强(1976-)，男，副教授，博士生，研究方向为智能计算。E-mail：48044244@qq.com
基金资助:
广东省自然科学基金(2020A1515010784);广东省青年特色创新项目(2021KQNCX120)

Research on Modeling and Scheduling of Virtual Power Plant with Dual Demand Response

Qiang Chen¹(), Yi Wang²^,³(), Kangshun Li⁴

^1.School of Computer and Information, Dongguan City College, Dongguan 523109, China
^2.College of Artificial Intelligence, South China Agricultural University, Guangzhou 510642, China
^3.School of Computer Science, Guangdong University of Science and Technology, DongGuan 523083, China
^4.College of Mathematics and Information, South China Agricultural University, Guangzhou 510642, China

Received:2021-12-02 Revised:2022-01-22 Online:2023-04-29 Published:2023-04-12
Contact: Yi Wang E-mail:48044244@qq.com;gust312@163.com

摘要/Abstract

摘要：

虚拟电厂技术为聚合分布式能源和用户侧资源参与电力调度提供了有效手段。现有研究大部分聚焦在分布式能源的调度优化，而对用户侧需求响应的研究较少。将用户侧资源分为签约的可靠响应负荷和非签约的随机响应负荷，并通过价格调整机制调控负荷响应以适应分布式能源发力变化。为此构建一种双重需求响应的虚拟电厂优化调度模型，并以电网整体收益最大化为优化目标，使用带约束惩罚的改进差分进化算法进行优化。仿真实验表明所提出模型较无需求响应模型可提升10%的收益，具有较大的应用潜力。

关键词: 虚拟电厂, 双重需求响应, 差分进化算法, 约束, 调度

Abstract:

Virtual power plant technology provides an effective means to aggregate distributed power and user side resources to participate in power scheduling. Most of the existing research focus on the scheduling optimization of distributed energy instead of the demand response of user side. The user side resources are divided into contracted reliable response load and non-contracted random response load, and the load response is regulated through price adjustment mechanism to adapt to the change of distributed. A virtual power plant optimal scheduling model with dual demands response is constructed, in which the maximizing overall profit of the power grid is set to be the optimization objective, and an improved differential evolution algorithm with constraint penalty is used to optimize the model. Simulation results shows that, compared with the scheduling model without demand response, the proposed model can increase the revenue by 10%.

Key words: virtual power plant, dual demands response, differential evolution algorithm, constraints, scheduling

中图分类号:

TP391.9

陈强, 王意, 李康顺. 双重需求响应的虚拟电厂建模与调度研究[J]. 系统仿真学报, 2023, 35(4): 822-832.

Qiang Chen, Yi Wang, Kangshun Li. Research on Modeling and Scheduling of Virtual Power Plant with Dual Demand Response[J]. Journal of System Simulation, 2023, 35(4): 822-832.

图/表 9

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CEC2010 10维	GA mean ± std	PSO mean ± std	DE mean ± std	DE-PE mean ± std
F1	-7.10e-1 ± 3.86e-2	-3.34e-1 ± 8.09e-2	-3.89e-1 ± 5.25e-2	-7.24e-1 ± 2.69e-2
F2	3.51e+0 ± 1.12e+0	3.15e+0 ± 1.09e-1	1.84e+0 ± 0.00e+0	1.80e+0 ± 0.00e+0
F3	1.15e+13 ± 2.72e+13	1.11e+13 ± 2.93e+13	2.55e+12 ± 1.01e+12	6.80e+11 ± 8.16e+10
F4	5.02e+0 ± 5.63e+0	6.32e+0 ± 9.94e-1	4.95e+0 ± 1.00e+0	4.76e+0 ± 5.92e+0
F5	5.24e+2 ± 0.00e+0	4.86e+2 ± 1.08e+2	2.28e+2 ± 3.82e+2	1.50e+2 ± 9.17e+1
F6	3.65e+2 ± 9.62e+1	4.37e+2 ± 1.39e+2	4.38e+2 ± 8.50e+1	3.08e+2 ± 4.09e+2
F7	7.12e+2 ± 2.32e+3	6.46e+5 ± 1.48e+6	1.82e+9 ± 1.25e+9	1.36e+8 ± 2.22e+8
F8	5.38e+9 ± 0.00e+0	2.12e+10 ± 5.47e+9	2.69e+9 ± 3.82e+8	1.85e+9 ± 1.22e+8
F9	3.51e+13 ± 3.03e+13	7.32e+12 ± 4.81e+12	5.61e+12 ± 1.20e+12	5.56e+12 ± 1.88e+12
F10	1.16e+13 ± 7.21e+12	6.38e+12 ± 5.01e+12	1.82e+12 ± 2.59e+12	1.54e+12 ± 5.26e+11
F11	4.56e-2 ± 9.04e-3	9.44e-2 ± 8.37e-2	-1.08e+0 ± 1.12e+0	-1.72e+0 ± 2.72 e-1
F12	3.84e+1 ± 2.15e+0	2.05e+1 ± 1.64e+0	2.87e+1 ± 2.38e+0	2.22e+1 ± 1.27e+0
F13	-6.50e+1 ± 2.80e+0	-5.42e+1 ± 3.76e+0	-4.19e+1 ± 2.91e+0	-7.16e+1 ± 8.75e+0
F14	8.00e+13 ± 9.81e+12	8.18e+13 ± 7.00e+13	1.43e+12 ± 3.71e+11	9.84e+10 ± 4.55e+10
F15	4.75e+13 ± 7.90e+12	1.00e+14 ± 9.70e+13	2.17e+13 ± 2.36e+12	1.13e+12 ± 1.39e+11
F16	1.48e+0 ± 4.92e-2	1.05e+0 ± 3.63e-2	9.81e-2 ± 9.11e-2	2.63e-2 ± 3.71e-2
F17	5.37e+2 ± 2.03e+2	5.02e+2 ± 4.32e+2	1.50e+3 ± 3.39e+1	1.14e+3 ± 6.65e+0
F18	1.36e+4 ± 6.57e+3	2.10e+4 ± 1.13e+4	9.17e+3 ± 0.00e+0	6.24e+3 ± 1.62e+3

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双重需求响应的虚拟电厂建模与调度研究

Research on Modeling and Scheduling of Virtual Power Plant with Dual Demand Response

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需求响应模型	收益
无需求响应	21 000
仅可靠需求响应	19 400
双重需求响应	23 100