考虑负荷虚拟储能特性的商业区储能优化配置

doi:10.11930/j.issn.1004-9649.201809067

中国电力 ›› 2020, Vol. 53 ›› Issue (4): 96-104.DOI: 10.11930/j.issn.1004-9649.201809067

考虑负荷虚拟储能特性的商业区储能优化配置

高文浩¹, 赵海兵¹, 殷爽睿², 崔德民¹, 田怀源¹, 葛杨¹, 李晓博¹, 孙海涛¹

1. 国网山东省电力公司德州供电公司，山东德州 253000;
2. 上海交通大学电子信息与电气工程学院，上海 200240

收稿日期:2018-09-19 修回日期:2019-02-02 发布日期:2020-04-05
作者简介:高文浩(1986-),男,本科,工程师,从事配电网规划、配电网前期、电源接入管理研究,E-mail:dzfzchb@163.com;殷爽睿(1995-),女,通信作者,博士研究生,从事能源互联网及虚拟电厂优化运行研究,E-mail:yinsr28@sjtu.edu.cn
基金资助:
国网山东省电力公司科技项目（2017A-90）

Optimal Configuration of BESS in Commercial Area Considering Virtual Energy Storage Characteristics of Load

GAO Wenhao¹, ZHAO Haibing¹, YIN Shuangrui², CUI Demin¹, TIAN Huaiyuan¹, GE Yang¹, LI Xiaobo¹, SUN Haitao¹

1. Dezhou Power Supply Company, State Grid Shandong Electric Power Company, Dezhou 253000, China;
2. School of Electronic Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai 200240, China

Received:2018-09-19 Revised:2019-02-02 Published:2020-04-05
Supported by:
This work is supported by Science and Technology Project of State Grid Shandong Electric Power Corporation (No.2017A-90)

摘要/Abstract

摘要： 储能技术的快速发展使得电力系统的经济性与灵活性逐渐提高，而基于需求侧管理的负荷虚拟储能则作为广义储能其中的一种获得了广泛关注。以商业区产消者为研究对象，基于人体舒适度范围建立具有时间解耦特性的空调负荷虚拟储能模型。在此基础上考虑负荷与光伏发电的季节性及气候性差异，计及全寿命周期成本建立考虑负荷虚拟储能特性的蓄电池储能双层优化配置模型，并采用Gurobi求解器与改进的差分进化算法配合求解。最后通过具体算例，证明了负荷虚拟储能的引入可有效提高商业区蓄电池储能配置的经济性，并分析储能系统对光伏消纳的影响。

关键词: 虚拟储能, 空调负荷, 蓄电池储能, 优化配置, 差分进化算法

Abstract: The rapid development of energy storage technology has gradually increased the economic efficiency and flexibility of power systems, while the virtual energy storage of load(VES) based on demand side management has received extensive attention as a kind of generalized energy storage. We take the commercial area prosumers as the research objects and establish the VES model of air conditioning load with time decoupling characteristics based on human comfort range. On this basis, considering the seasonal and climatic differences between load and photovoltaic (PV) power generation and the life cycle cost, a bi-level optimal configuration model for battery energy storage system (BESS) considering the VES characteristics is established, and the Gurobi solver combined with the modified differential evolution (MDE) is adopted. Finally, the specific example shows that the participation of VES can effectively improve the economic efficiency of BESS configuration in commercial area, and the impact of energy storage system on PV consumption is analyzed.

Key words: virtual energy storage, air conditioning load, battery energy storage, optimal configuration, differential evolution algorithm

高文浩, 赵海兵, 殷爽睿, 崔德民, 田怀源, 葛杨, 李晓博, 孙海涛. 考虑负荷虚拟储能特性的商业区储能优化配置[J]. 中国电力, 2020, 53(4): 96-104.

GAO Wenhao, ZHAO Haibing, YIN Shuangrui, CUI Demin, TIAN Huaiyuan, GE Yang, LI Xiaobo, SUN Haitao. Optimal Configuration of BESS in Commercial Area Considering Virtual Energy Storage Characteristics of Load[J]. Electric Power, 2020, 53(4): 96-104.

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https://www.electricpower.com.cn/CN/Y2020/V53/I4/96

参考文献

[1] 王仕俊, 平常, 薛国斌. 考虑共享储能的社区综合能源系统协同优化研究[J]. 中国电力, 2018, 51(8): 77–84
WANG Shijun, PING Chang, XUE Guobin. Synergic optimization of community energy internet considering the shared energy storage[J]. Electric Power, 2018, 51(8): 77–84
[2] 洪博文, 胡静, 王建国, 等. 面向能源互联网的用户侧分布式储能价值评估[J]. 中国电力, 2018, 51(3): 113–120, 130
HONG Bowen, HU Jing, WANG Jianguo, et al. Energy internet oriented evaluation of distributed energy storage utility in user-side[J]. Electric Power, 2018, 51(3): 113–120, 130
[3] 凌开元, 赵乐冰, 张新松, 等. 基于双储能系统的主动配电网储能配置[J]. 电力自动化设备, 2018, 38(5): 171–176
LING Kaiyuan, ZHAO Lebing, ZHANG Xinsong, et al. Storage allocation of active distribution network based on double-storage system[J]. Electric Power Automation Equipment, 2018, 38(5): 171–176
[4] 贾龙, 胡泽春, 宋永华, 等. 储能和电动汽车充电站与配电网的联合规划研究[J]. 中国电机工程学报, 2017, 37(1): 73–84
JIA Long, HU Zechun, SONG Yonghua, et al. Joint planning of distribution networks with distributed energy storage systems and electric vehicle charging stations[J]. Proceedings of the CSEE, 2017, 37(1): 73–84
[5] 李刚, 李峰, 孔亮, 等. 不同电价下含储能系统的微电网经济调度[J]. 中国电力, 2018, 51(2): 125–132
LI Gang, LI Feng, KONG Liang, et al. Economic dispatch of microgrid with energy storage under different price policies[J]. Electric Power, 2018, 51(2): 125–132
[6] 韩笑, 周明, 李庚银. 计及储能和空调负荷的主动配电网多目标优化调度[J]. 电力系统保护与控制, 2018, 46(7): 14–23
HAN Xiao, ZHOU Ming, LI Gengyin. Multi-objective optimal dispatching of active distribution networks considering energy storage systems and air-conditioning loads[J]. Power System Protection and Control, 2018, 46(7): 14–23
[7] 李辉, 郭忠涵, 李肇汉, 等. 基于几何加权移动平均滤波算法的改进储能平滑控制策略[J]. 中国电力, 2018, 51(3): 105–112
LI Hui, GUO Zhonghan, LI Zhaohan, et al. Improved energy storage smoothing control strategy based on geometric weighted moving average filter algorithm[J]. Electric Power, 2018, 51(3): 105–112
[8] 向育鹏, 卫志农, 孙国强, 等. 基于全寿命周期成本的配电网蓄电池储能系统的优化配置[J]. 电网技术, 2015, 39(1): 264–270
XIANG Yupeng, WEI Zhinong, SUN Guoqiang, et al. Life cycle cost based optimal configuration of battery energy storage system in distribution network[J]. Power System Technology, 2015, 39(1): 264–270
[9] 李逐云, 雷霞, 邱少引, 等. 考虑“源-网-荷”三方利益的主动配电网协调规划[J]. 电网技术, 2017, 41(2): 378–387
LI Zhuyun, LEI Xia, QIU Shaoyin, et al. Coordinated planning of active distribution network considering “Source-Grid-Load” benefits[J]. Power System Technology, 2017, 41(2): 378–387
[10] 张建华, 于雷, 刘念, 等. 含风/光/柴/蓄及海水淡化负荷的微电网容量优化配置[J]. 电工技术学报, 2014, 29(2): 102–112
ZHANG Jianhua, YU Lei, LIU Nian, et al. Capacity configuration optimization for island microgrid with wind/photovoltaic/diesel/storage and seawater desalination load[J]. Transactions of China Electrotechnical Society, 2014, 29(2): 102–112
[11] 王树东, 杜巍, 林莉, 等. 基于合作博弈的需求侧响应下光储微电网优化配置[J]. 电力系统保护与控制, 2018, 46(1): 129–137
WANG Shudong, DU Wei, LIN Li, et al. Optimal allocation of photovoltaic energy storage microgrid under the demand side response based on cooperative game[J]. Power System Protection and Control, 2018, 46(1): 129–137
[12] 杨锡运, 张璜, 修晓青, 等. 基于商业园区源/储/荷协同运行的储能系统多目标优化配置[J]. 电网技术, 2017, 41(12): 3996–4003
YANG Xiyun, ZHANG Huang, XIU Xiaoqing, et al. Multi-objective optimal configuration of energy storage systems based on coordinated operation of source/storage/load in commercial park[J]. Power System Technology, 2017, 41(12): 3996–4003
[13] 高赐威, 李倩玉, 李扬. 基于DLC的空调负荷双层优化调度和控制策略[J]. 中国电机工程学报, 2014, 34(10): 1546–1555
GAO Ciwei, LI Qianyu, LI Yang. Bi-level optimal dispatch and control strategy for air-conditioning load based on direct load control[J]. Proceedings of the CSEE, 2014, 34(10): 1546–1555
[14] 艾欣, 赵阅群, 周树鹏. 空调负荷直接负荷控制虚拟储能特性研究[J]. 中国电机工程学报, 2016, 36(6): 1596–1603
AI Xin, ZHAO Yuequn, ZHOU Shupeng. Study on virtual energy storage features of air conditioner direct load control[J]. Proceedings of the CSEE, 2016, 36(6): 1596–1603
[15] 王怡岚, 童亦斌, 黄梅, 等. 基于需求侧响应的空调负荷虚拟储能模型研究[J]. 电网技术, 2017, 41(2): 394–401
WANG Yilan, TONG Yibin, HUANG Mei, et al. Research on virtual energy storage model of air conditioning loads based on demand response[J]. Power System Technology, 2017, 41(2): 394–401
[16] 靳小龙, 穆云飞, 贾宏杰, 等. 融合需求侧虚拟储能系统的冷热电联供楼宇微网优化调度方法[J]. 中国电机工程学报, 2017, 37(2): 581–591
JIN Xiaolong, MU Yunfei, JIA Hongjie, et al. Optimal scheduling method for a combined cooling, heating and power building microgrid considering virtual storage system at demand side[J]. Proceedings of the CSEE, 2017, 37(2): 581–591
[17] 陈健, 张维桐, 张逸成, 等. 考虑不同空调负荷特性的微网双层优化调度[J]. 电网技术, 2018, 42(5): 1424–1431
CHEN Jian, ZHANG Weitong, ZHANG Yicheng, et al. Bi-level optimal dispatch of microgrid considering different air-conditioning load characteristics[J]. Power System Technology, 2018, 42(5): 1424–1431
[18] 宋梦, 高赐威, 苏卫华. 面向需求响应应用的空调负荷建模及控制[J]. 电力系统自动化, 2016, 40(14): 158–167
SONG Meng, GAO Ciwei, SU Weihua. Modeling and controlling of air-conditioning load for demand response applications[J]. Automation of Electric Power Systems, 2016, 40(14): 158–167
[19] 颜学峰, 余娟, 钱峰, 等. 基于改进差分进化算法的超临界水氧化动力学参数估计[J]. 华东理工大学学报: 自然科学版, 2006, 32(1): 94–97, 24
YAN Xuefeng, YU Juan, QIAN Feng, et al. Kinetic parameter estimation of oxidation in supercritical water based on modified differential evolution[J]. Journal of East China University of Science and Technology(Natural Science Edition), 2006, 32(1): 94–97, 24
[20] Gurobi优化器的特点和优势[EB/OL]. [2019-02-01]. http://www.gurobi.com/products/features-benefits.

考虑负荷虚拟储能特性的商业区储能优化配置

Optimal Configuration of BESS in Commercial Area Considering Virtual Energy Storage Characteristics of Load

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考虑负荷虚拟储能特性的商业区储能优化配置

Optimal Configuration of BESS in Commercial Area Considering Virtual Energy Storage Characteristics of Load

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