Charging and Discharging Strategies of Independent Energy Storage for Distribution Grid Side Considering Distributed PV Carrying Capacity

doi:10.11930/j.issn.1004-9649.202305016

Abstract

Abstract:

In the context of carbon peaking and carbon neutrality goals and new power system construction, China’s distributed photovoltaic (PV) development accelerates. Areas with a high proportion of distributed PV access are prone to grid voltage rise over the limit, reverse tide equipment overload, and other problems, affecting the distribution grid carrying capacity with the distributed PV access. This paper fully considers the regulating role of independent energy storage on the distribution grid side and proposes an optimal configuration of independent energy storage and charging/discharging strategy for improving the carrying capacity of the grid with distributed PV access. Specifically, the comprehensive cost effectiveness of the independent energy storage application of the distribution grid side based on the time-series tide and two-step iteration is considered, and the independent energy storage configuration capacity and charging/discharging control strategy are scientifically and reasonably determined based on the principle of the minimum system cost. The low-voltage distribution grid of a village is selected as a case study, and the effectiveness of the independent energy storage charging and discharging control strategy proposed in this paper is simulated and analyzed by the Distribution System Analysis and Optimization Platform (DSAP).

Key words: distributed photovoltaic carrying capacity, independent energy storage of distribution grid side, charging and discharging strategy, comprehensive cost effectiveness

Yu ZHANG, Xinchi WEI, Kaihui FENG, Shanshan SHI, Zihan MENG, Yuan LIANG. Charging and Discharging Strategies of Independent Energy Storage for Distribution Grid Side Considering Distributed PV Carrying Capacity[J]. Electric Power, 2024, 57(4): 111-117.

Add to citation manager EndNote|Ris|BibTeX

URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202305016

https://www.electricpower.com.cn/EN/Y2024/V57/I4/111

Figures/Tables 9

References 21

1	张珍珍, 吕清泉, 张健美. “双碳” 目标下分布式光伏发电技术的研究进展及展望[J]. 太阳能, 2023, (1): 17- 21.
	ZHANG Zhenzhen, LYU Qingquan, ZHANG Jianmei. Research progress and prospect of distributed PV power generation technology under the goal of emission peak and carbon neutrality[J]. Solar Energy, 2023, (1): 17- 21.
2	丁明, 王伟胜, 王秀丽, 等. 大规模光伏发电对电力系统影响综述[J]. 中国电机工程学报, 2014, 34 (1): 1- 14.
	DING Ming, WANG Weisheng, WANG Xiuli, et al. A review on the effect of large-scale PV generation on power systems[J]. Proceedings of the CSEE, 2014, 34 (1): 1- 14.
3	国家发展和改革委员会, 国家能源局, 等. “十四五”可再生能源发展规划(发改能源〔2021〕1445号)[Z].
4	黄碧斌, 洪博文, 胡静, 等. 分布式光伏发电技术特性及对电力系统的影响[J]. 大众科技, 2016, 18 (1): 41- 43. DOI
	HUANG Bibin, HONG Bowen, HU Jing, et al. Technical characteristics of distributed photovoltaic power generation and its effects on power system[J]. Popular Science & Technology, 2016, 18 (1): 41- 43. DOI
5	赵波, 肖传亮, 徐琛, 等. 基于渗透率的区域配电网分布式光伏并网消纳能力分析[J]. 电力系统自动化, 2017, 41 (21): 105- 111. DOI
	ZHAO Bo, XIAO Chuanliang, XU Chen, et al. Penetration based accommodation capacity analysis on distributed photovoltaic connection in regional distribution network[J]. Automation of Electric Power Systems, 2017, 41 (21): 105- 111. DOI
6	黄碧斌, 李琼慧, 高菲, 等. 高渗透率分布式光伏发电接入农村电网的成本分析[J]. 电力系统及其自动化学报, 2017, 29 (6): 102- 106.
	HUANG Bibin, LI Qionghui, GAO Fei, et al. Cost analysis of distributed photovoltaic integration with high penetration rate in rural network[J]. Proceedings of the CSU-EPSA, 2017, 29 (6): 102- 106.
7	丁琦欣, 覃洪培, 万灿, 等. 基于机会约束规划的配电网分布式光伏承载能力评估[J]. 东北电力大学学报, 2022, 42 (6): 28- 38.
	DING Qixin, QIN Hongpei, WAN Can, et al. Chance-constrained optimization-based distributed photovoltaic hosting capacity assessment of distribution networks[J]. Journal of Northeast Electric Power University, 2022, 42 (6): 28- 38.
8	丁浩然, 张博, 唐巍, 等. 考虑源-网-荷-储协同的配电台区分布式光伏消纳能力评估[J]. 供用电, 2023, 40 (3): 2- 8, 31.
	DING Haoran, ZHANG Bo, TANG Wei, et al. Evaluation of distributed photovoltaic consumption capacity of distribution station area considering source-network-load-storage collaboration[J]. Distribution & Utilization, 2023, 40 (3): 2- 8, 31.
9	李世辉, 王琪, 贾晓卜, 等. 考虑热泵负荷和分布式光伏的配微网协调调度[J]. 中国电力, 2022, 55 (9): 29- 37.
	LI Shihui, WANG Qi, JIA Xiaobo, et al. Coordinated scheduling of distribution networks and microgrids considering heat pump load and distributed photovoltaic[J]. Electric Power, 2022, 55 (9): 29- 37.
10	李振坤, 鲍新雨, 邵宇鹰, 等. 考虑多种调压措施的分布式光伏消纳能力研究[J]. 电力系统保护与控制, 2018, 46 (8): 10- 16.
	LI Zhenkun, BAO Xinyu, SHAO Yuying, et al. Studying accommodation ability of distributed photovoltaic considering various voltage regulation measures[J]. Power System Protection and Control, 2018, 46 (8): 10- 16.
11	张光儒, 任浩栋, 马振祺, 等. 提升配电网承载力和调节能力的整县分布式光伏储能配置方法[J]. 电气技术, 2022, 23 (11): 49- 55, 61.
	ZHANG Guangru, REN Haodong, MA Zhenqi, et al. County-wide distributed photovoltaic energy storage configuration method to improve the carrying capacity and regulation capacity of distribution network[J]. Electrical Engineering, 2022, 23 (11): 49- 55, 61.
12	国务院办公厅. 关于转发国家发展改革委国家能源局关于促进新时代新能源高质量发展实施方案的通知(国办函〔2022〕39号)[Z].
13	孙充勃, 李敬如, 罗凤章, 等. 考虑分布式电源接入的配电系统典型算例设计[J]. 电力建设, 2020, 41 (10): 47- 62. DOI
	SUN Chongbo, LI Jingru, LUO Fengzhang, et al. Typical case design of distribution system considering DG integration[J]. Electric Power Construction, 2020, 41 (10): 47- 62. DOI
14	陈璨, 白明辉, 张婉明, 等. 分布式光伏边界渗透率快速定位及消纳方案择优[J]. 中国电力, 2022, 55 (8): 40- 50.
	CHEN Can, BAI Minghui, ZHANG Wanming, et al. Fast positioning of marginal hosting capacity and optimal selection of accommodation scheme for distributed PVs[J]. Electric Power, 2022, 55 (8): 40- 50.
15	蒋向兵, 汤波, 余光正, 等. 面向新能源就地消纳的园区储能与电价协调优化方法[J]. 电力系统自动化, 2022, 46 (5): 51- 64.
	JIANG Xiangbing, TANG Bo, YU Guangzheng, et al. Coordination and optimization method of park-level energy storage and electricity price for local accommodation of renewable energy[J]. Automation of Electric Power Systems, 2022, 46 (5): 51- 64.
16	李翠萍, 东哲民, 李军徽, 等. 提升配电网新能源消纳能力的分布式储能集群优化控制策略[J]. 电力系统自动化, 2021, 45 (23): 76- 83.
	LI Cuiping, DONG Zhemin, LI Junhui, et al. Optimal control strategy of distributed energy storage cluster for prompting renewable energy accomodation in distribution network[J]. Automation of Electric Power Systems, 2021, 45 (23): 76- 83.
17	饶萍, 向月, 姚昊天, 等. 市场环境下配电网分布式光储协同规划[J]. 中国电力, 2022, 55 (1): 178- 188.
	RAO Ping, XIANG Yue, YAO Haotian, et al. Collaborative planning for distribution network and PV-ESS in the marketization environment[J]. Electric Power, 2022, 55 (1): 178- 188.
18	黄碧斌, 李琼慧, 高菲. 计及电网改造的高渗透率分布式光伏优化规划[J]. 电力建设, 2015, 36 (10): 82- 87.
	HUANG Bibin, LI Qionghui, GAO Fei. Distributed photovoltaic optimal planning with high permeability considering grid reinforcement[J]. Electric Power Construction, 2015, 36 (10): 82- 87.
19	梁志峰, 夏俊荣, 孙檬檬, 等. 数据驱动的配电网分布式光伏承载力评估技术研究[J]. 电网技术, 2020, 44 (7): 2430- 2439.
	LIANG Zhifeng, XIA Junrong, SUN Mengmeng, et al. Data driven assessment of distributed photovoltaic hosting capacity in distribution network[J]. Power System Technology, 2020, 44 (7): 2430- 2439.
20	国家能源局. 分布式电源接入电网承载力评估导则: DL/T 2041—2019[S]. 北京: 中国电力出版社.
21	黄碧斌, 李琼慧. 储能支撑大规模分布式光伏接入的价值评估[J]. 电力自动化设备, 2016, 36 (6): 88- 93.
	HUANG Bibin, LI Qionghui. Value assessment for energy storage in supporting large-scale integration of distributed PVs[J]. Electric Power Automation Equipment, 2016, 36 (6): 88- 93.

配置储能比例/ %	储能策略	储能投资成本 (年化)/元	储能运维成本/ 元	限电损失/ 元	损耗损失/ 元	综合成本/ 元	增量度电成本/ (元·(kW·h)^–1)
0	无	0	0	4465	6491	10956	基准
5	固定策略	1399	108	3797	5162	10466	–0.005
5	智能策略	1399	108	3217	5153.6	9877	–0.011
10	固定策略	2797	216	3300	5148.4	11462	0.005
10	智能策略	2797	216	2423	5131.6	10568	–0.004
15	固定策略	4196	324	2933	5152.4	12605	0.017
15	智能策略	4196	324	1819	5116	11455	0.005
20	固定策略	5595	432	2704	5174.4	13905	0.030
20	智能策略	5595	432	1662	5108.4	12797	0.019
30	固定策略	8392	648	2604	5277.2	16921	0.060
30	智能策略	8392	648	1384	5101.2	15525	0.046

配置储能比例/ %	储能策略	储能投资成本 (年化)/元	储能运维成本/ 元	限电损失/ 元	损耗损失/ 元	综合成本/ 元	增量度电成本/ (元·(kW·h)^–1)
0	无	0	0	4465	6491	10956	基准
5	固定策略	1399	108	3797	5162	10466	–0.005
5	智能策略	1399	108	3217	5153.6	9877	–0.011
10	固定策略	2797	216	3300	5148.4	11462	0.005
10	智能策略	2797	216	2423	5131.6	10568	–0.004
15	固定策略	4196	324	2933	5152.4	12605	0.017
15	智能策略	4196	324	1819	5116	11455	0.005
20	固定策略	5595	432	2704	5174.4	13905	0.030
20	智能策略	5595	432	1662	5108.4	12797	0.019
30	固定策略	8392	648	2604	5277.2	16921	0.060
30	智能策略	8392	648	1384	5101.2	15525	0.046