基于源-荷匹配的区域电网风/光/储容量配比优化方法

doi:10.11930/j.issn.1004-9649.202012091

中国电力 ›› 2022, Vol. 55 ›› Issue (1): 46-54.DOI: 10.11930/j.issn.1004-9649.202012091

• 含大规模储能的高比例新能源电力系统协调规划与优化调度技术专栏 • 上一篇下一篇

基于源-荷匹配的区域电网风/光/储容量配比优化方法

李湃¹, 方保民², 祁太元², 黄越辉¹, 史昭娣¹, 王莲芳²

1. 新能源与储能运行控制国家重点实验室(中国电力科学研究院有限公司), 北京 100192;
2. 国网青海省电力公司, 青海西宁 810008

收稿日期:2020-12-21 修回日期:2021-09-22 出版日期:2022-01-28 发布日期:2022-01-20
作者简介:李湃(1988-),男,博士,高级工程师,从事新能源发电并网及调度运行技术研究,E-mail:lipai@epri.sgcc.com.cn;方保民(1973-),男,高级工程师,从事新能源发电并网及调度运行管理工作,E-mail:fangbaomin@163.com;祁太元(1965-),男,高级工程师,从事能源与电力运营、电力系统运行管理工作
基金资助:
国家电网有限公司科技项目(5419-202034054A-0-0-00)

Capacity Proportion Optimization of Wind, Solar Power and Battery Energy Storage System for Regional Power Grid Based on Source-Load Matching

LI Pai¹, FANG Baomin², QI Taiyuan², HUANG Yuehui¹, SHI Zhaodi¹, WANG Lianfang²

1. State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems (China Electric Power Research Institute), Beijing 100192, China;
2. State Grid Qinghai Electric Power Company, Xining 810008, China

Received:2020-12-21 Revised:2021-09-22 Online:2022-01-28 Published:2022-01-20
Supported by:
This work is supported by the Science and Technology Project of SGCC (No.5419-202034054A-0-0-00)

摘要/Abstract

摘要： 合理优化风/光/储容量配比是实现大规模区域电网新能源高效利用的基础。提出一种基于源-荷匹配的区域电网风/光/储容量配比优化方法。首先，考虑了新能源与储能的运行特性、装机容量、新能源弃电率、新能源发电量占比等约束条件，建立以全网新能源发电量最大为目标的多区域风/光装机容量优化模型，并通过引入系统负荷匹配偏差约束来保证系统发电功率与用电负荷变化特性相一致。然后，以风/光全年出力时间序列为输入，通过时序生产模拟计算，确定满足源-荷最优匹配后的风/光/储最优接入容量配比。最后，以中国“三北”地区某区域电网为对象进行算例验证，验证了所提模型和方法的有效性和实用性。

关键词: 新能源, 化学储能, 容量配比优化, 源-荷匹配, 时序生产模拟

Abstract: Capacity proportion optimization of the wind, solar power, and battery energy storage system is the basis for efficient utilization of renewable energy in a large-scale regional power grid. In this regard, an optimization method based on source-load matching was proposed to allocate the capacity proportion of the wind, solar, and battery energy storage system in a regional power grid. An optimization model was built to maximize wind and solar power generation. The optimization model considered the operational characteristics of wind and solar power and energy storage, constraints of installed capacity, annual curtailment rates, and proportions of wind and solar power generation. Moreover, the constraint of system-load matching deviation was placed to maintain the match between system power outputs and load demand. Then, with the annual output time-series of wind and solar as the input, the optimal capacity proportion of the wind, solar power, and battery energy storage system, which met the optimal source-load matching, was obtained by solving the proposed model. Finally, the effectiveness and practicability of the proposed model and method were verified by testing on an actual regional power grid in the north of China.

Key words: renewable energy, battery energy storage, capacity proportion optimization, source-load matching, time sequence simulation

李湃, 方保民, 祁太元, 黄越辉, 史昭娣, 王莲芳. 基于源-荷匹配的区域电网风/光/储容量配比优化方法[J]. 中国电力, 2022, 55(1): 46-54.

LI Pai, FANG Baomin, QI Taiyuan, HUANG Yuehui, SHI Zhaodi, WANG Lianfang. Capacity Proportion Optimization of Wind, Solar Power and Battery Energy Storage System for Regional Power Grid Based on Source-Load Matching[J]. Electric Power, 2022, 55(1): 46-54.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202012091

https://www.electricpower.com.cn/CN/Y2022/V55/I1/46

参考文献

[1] 陈国平, 董昱, 梁志峰. 能源转型中的中国特色新能源高质量发展分析与思考[J]. 中国电机工程学报, 2020, 40(17): 5493–5506
CHEN Guoping, DONG Yu, LIANG Zhifeng. Analysis and reflection on high-quality development of new energy with Chinese characteristics in energy transition[J]. Proceedings of the CSEE, 2020, 40(17): 5493–5506
[2] 习近平. 继往开来, 开启全球应对气候变化新征程[R]. 气候雄心峰会, 2020.
Xi Jinping. Start a new journey of global response to climate change [R]. Climate Ambition Summit, 2020.
[3] 赵健, 王奕凡, 谢桦, 等. 高渗透率可再生能源接入系统中储能应用综述[J]. 中国电力, 2019, 52(4): 167–177
ZHAO Jian, WANG Yifan, XIE Hua, et al. An overview of energy storage applications in power systems with high penetration renewable energy resources[J]. Electric Power, 2019, 52(4): 167–177
[4] 胡亚伟, 李江, 胡立强, 等. 基于风电出力预测误差补偿度与经济效益的最佳储能容量配置[J]. 中国电力, 2016, 49(5): 141–148
HU Yawei, LI Jiang, HU Liqiang, et al. Optimized energy storage capacity allocation based on prediction error compensation degree and economic benefits of wind power[J]. Electric Power, 2016, 49(5): 141–148
[5] 方保民, 李红志, 孔祥鹏, 等. 含高比例光伏出力的长期分布式储能配置研究[J]. 电力系统保护与控制, 2021, 49(2): 121–129
FANG Baomin, LI Hongzhi, KONG Xiangpeng, et al. Research on long-term distributed energy storage configuration with a high proportion of photovoltaic output[J]. Power System Protection and Control, 2021, 49(2): 121–129
[6] 李晖, 高涵宇, 张艳, 等. 考虑相关性的大规模风光互补电网扩展规划[J]. 电网技术, 2018, 42(7): 2120–2127
LI Hui, GAO Hanyu, ZHANG Yan, et al. Expansion planning of large scale hybrid wind-photovoltaic transmission network considering correlation[J]. Power System Technology, 2018, 42(7): 2120–2127
[7] 胡迪, 丁明, 毕锐, 等. 光伏和风电互补性对高渗透率可再生能源集群接入规划影响分析[J]. 中国电机工程学报, 2020, 40(3): 821–836
HU Di, DING Ming, BI Rui, et al. Impact analysis of PV and WT complementarity on access planning of high penetrated renewable energy cluster[J]. Proceedings of the CSEE, 2020, 40(3): 821–836
[8] 万家豪, 苏浩, 冯冬涵, 等. 计及源荷匹配的风光互补特性分析与评价[J]. 电网技术, 2020, 44(9): 3219–3226
WAN Jiahao, SU Hao, FENG Donghan, et al. Analysis and evaluation of the complementarity characteristics of wind and photovoltaic considering source-load matching[J]. Power System Technology, 2020, 44(9): 3219–3226
[9] 刘永前, 梁超, 阎洁, 等. 风-光电站中储能系统混合最优配置及其经济性研究[J]. 中国电力, 2020, 53(12): 143–150
LIU Yongqian, LIANG Chao, YAN Jie, et al. Optimal configuration and economics of hybrid energy storage system in wind and solar power plant[J]. Electric Power, 2020, 53(12): 143–150
[10] 陈景文, 肖妍, 莫瑞瑞, 等. 考虑光伏校正的微电网储能容量优化配置[J]. 电力系统保护与控制, 2021, 49(10): 59–66
CHEN Jingwen, XIAO Yan, MO Ruirui, et al. Optimized allocation of microgrid energy storage capacity considering photovoltaic correction[J]. Power System Protection and Control, 2021, 49(10): 59–66
[11] 徐国栋, 程浩忠, 方斯顿, 等. 用于提高风电场运行效益的电池储能配置优化模型[J]. 电力系统自动化, 2016, 40(5): 62–70
XU Guodong, CHENG Haozhong, FANG Sidun, et al. An optimization model of battery energy storage system configuration to improve benefits of wind farms[J]. Automation of Electric Power Systems, 2016, 40(5): 62–70
[12] 张熙, 张峰, 巩乃奇, 等. 基于荷电状态动态调整的储能电站容量规划[J]. 电力自动化设备, 2015, 35(11): 20–25
ZHANG Xi, ZHANG Feng, GONG Naiqi, et al. BESS capacity planning based on dynamic SOC adjustment[J]. Electric Power Automation Equipment, 2015, 35(11): 20–25
[13] 席星璇, 熊敏鹏, 袁家海. 风电场发电侧配置储能系统的经济性研究[J]. 智慧电力, 2020, 48(11): 16–21,47
XI Xingxuan, XIONG Minpeng, YUAN Jiahai. Economic analysis of energy storage system in wind farm generation side[J]. Smart Power, 2020, 48(11): 16–21,47
[14] 李湃, 黄越辉, 王跃峰, 等. 含抽蓄电站的多端柔性直流电网风光接入容量配比优化方法[J]. 中国电力, 2019, 52(4): 32–40
LI Pai, HUANG Yuehui, WANG Yuefeng, et al. Optimization of wind and solar power capacity proportion integrated in multi-terminal VSC-HVDC system with a pumped storage power station[J]. Electric Power, 2019, 52(4): 32–40
[15] 董存, 李明节, 范高锋, 等. 基于时序生产模拟的新能源年度消纳能力计算方法及其应用[J]. 中国电力, 2015, 48(12): 166–172
DONG Cun, LI Mingjie, FAN Gaofeng, et al. Research and application of renewable energy accommodation capability evaluation based on time series production simulation[J]. Electric Power, 2015, 48(12): 166–172
[16] 史昭娣, 王伟胜, 黄越辉, 等. 多能互补发电系统储电和储热容量分层优化规划方法[J]. 电网技术, 2020, 44(9): 3263–3271
SHI Zhaodi, WANG Weisheng, HUANG Yuehui, et al. Hierarchical optimization method for electrical energy storage and heat storage capacity planning in multi-energy complementary generation system[J]. Power System Technology, 2020, 44(9): 3263–3271
[17] 曹阳, 黄越辉, 袁越, 等. 基于时序仿真的风光容量配比分层优化算法[J]. 中国电机工程学报, 2015, 35(5): 1072–1078
CAO Yang, HUANG Yuehui, YUAN Yue, et al. Stratified optimization algorithm for optimal proportion of wind and solar capacity based on time sequence simulation[J]. Proceedings of the CSEE, 2015, 35(5): 1072–1078
[18] 任大伟, 金晨, 侯金鸣, 等. 基于时序运行模拟的新能源配置储能替代火电规划模型[J]. 中国电力, 2021, 54(7): 18–26
REN Dawei, JIN Chen, HOU Jinming, et al. Planning model for renewable energy with energy storage replacing thermal power based on time series operation simulation[J]. Electric Power, 2021, 54(7): 18–26
[19] 任大伟, 金晨, 肖晋宇, 等. 计及灵活性基于时序的“十四五”储能需求分析[J]. 中国电力, 2021, 54(8): 190–198
REN Dawei, JIN Chen, XIAO Jinyu, et al. Demand analysis of energy storage for the 14th five-year plan period based on time series considering power system flexibility[J]. Electric Power, 2021, 54(8): 190–198
[20] 叶林, 屈晓旭, 么艳香, 等. 风光水多能互补发电系统日内时间尺度运行特性分析[J]. 电力系统自动化, 2018, 42(4): 158–164
YE Lin, QU Xiaoxu, YAO Yanxiang, et al. Analysis on intraday operation characteristics of hybrid wind-solar-hydro power generation system[J]. Automation of Electric Power Systems, 2018, 42(4): 158–164
[21] 刘永前, 王函, 韩爽, 等. 考虑风光出力波动性的实时互补性评价方法[J]. 电网技术, 2020, 44(9): 3211–3220
LIU Yongqian, WANG Han, HAN Shuang, et al. Real-time complementarity evaluation method for real-time complementarity of wind and solar power considering their volatility[J]. Power System Technology, 2020, 44(9): 3211–3220
[22] 李驰, 刘纯, 黄越辉, 等. 基于波动特性的风电出力时间序列建模方法研究[J]. 电网技术, 2015, 39(1): 208–214
LI Chi, LIU Chun, HUANG Yuehui, et al. Study on the modeling method of wind power time series based on fluctuation characteristics[J]. Power System Technology, 2015, 39(1): 208–214
[23] LI C, ZHANG J T, HUANG Y H, et al. Research on analysis method for photovoltaic power considering weather type[C]//International Conference on Renewable Power Generation (RPG 2015). Beijing, China. The Institution of Engineering and Technology, 2015: 5–10.
[24] 曲凯, 李湃, 黄越辉, 等. 面向新能源消纳能力评估的年负荷序列建模及场景生成方法[J]. 电力系统自动化, 2021, 45(1): 123–131
QU Kai, LI Pai, HUANG Yuehui, et al. Modeling and scenario generation method of annual load series for evaluation of new energy accommodation capacity[J]. Automation of Electric Power System, 2021, 45(1): 123–131
[25] RICHARD E R. GAMS-A user’s guide [DB/OL]. Washington DC: GAMS Development Corporation2014, 2014. https://www.gams.com/help/topic/gams.doc/userguides/GAMSUsersGuide.pdf.

基于源-荷匹配的区域电网风/光/储容量配比优化方法

Capacity Proportion Optimization of Wind, Solar Power and Battery Energy Storage System for Regional Power Grid Based on Source-Load Matching

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	张磊, 马晓伟, 王满亮, 陈力, 高丙团. 互联新能源电力系统区内AGC机组分布式协同控制策略[J]. 中国电力, 2025, 58(3): 8-19.
[2]	汪林光, 李旭涛, 任勇, 谢小荣. 基于元启发式算法的新能源电力系统振荡稳定性最差工况搜索方法[J]. 中国电力, 2025, 58(3): 65-72.
[3]	邹小燕, 张瑞宏. 考虑政府干预的可再生能源与储能企业合作模式演化博弈研究[J]. 中国电力, 2025, 58(1): 153-163.
[4]	王雨晴, 张敏, 王嘉兴, 李泊皓, 杨天阳, 曾鸣. 基于超模博弈的共享储能容量租赁价格决策[J]. 中国电力, 2025, 58(1): 164-173.
[5]	孙东磊, 王宪, 孙毅, 孟祥飞, 张涌琛, 张玉敏. 基于多面体不确定集合的电力系统灵活性量化评估方法[J]. 中国电力, 2024, 57(9): 146-155.
[6]	孙东磊, 孙毅, 刘蕊, 孙鹏凯, 张玉敏. 计及多层级配电网的分布式新能源最大消纳空间分解测算[J]. 中国电力, 2024, 57(8): 108-116.
[7]	李鲁阳, 陈龙翔, 陈磊, 孙大卫, 吴林林, 闵勇. 用于新能源一次调频的储能经济配置研究[J]. 中国电力, 2024, 57(7): 54-65.
[8]	邵冲, 胡荣义, 余姣, 王明典. 考虑荷电与储氢状态的风光氢储系统动态控制仿真模型[J]. 中国电力, 2024, 57(7): 109-124.
[9]	王硕, 霍慧娟, 徐丹, 郄鑫, 辛诚, 李薇薇, 段婧. 计及特高压交流工程建设的区域碳减排测算及分摊[J]. 中国电力, 2024, 57(7): 163-172.
[10]	李佳蔚, 张冠宇. 大规模分布式新能源接入对省级电网稳定性影响[J]. 中国电力, 2024, 57(6): 174-180.
[11]	高政南, 姜楠, 陈启鑫, 徐江, 王海利, 辛力, 徐青贵. 德国电力市场能源转型建设及启示[J]. 中国电力, 2024, 57(6): 204-214.
[12]	李咸善, 丁胜彪, 李飞, 李欣. 考虑水电调节费用补偿的风光水联盟优化调度策略[J]. 中国电力, 2024, 57(5): 26-38.
[13]	朱子民, 张锦芳, 常清, 周专, 张晓林. 大规模新能源接入弱同步支撑柔直系统的送端自适应VSG控制策略[J]. 中国电力, 2024, 57(5): 211-221.
[14]	王帅, 黄越辉, 聂元弘, 刘思扬. 基于生产模拟的受端电网新能源发展场景研究[J]. 中国电力, 2024, 57(5): 240-250.
[15]	李虎军, 张栋, 吕梦璇, 邓方钊, 杨萌, 元博. 考虑碳排放约束的新能源与调峰资源优化配置方法[J]. 中国电力, 2024, 57(4): 42-51.

模态框（Modal）标题

基于源-荷匹配的区域电网风/光/储容量配比优化方法

Capacity Proportion Optimization of Wind, Solar Power and Battery Energy Storage System for Regional Power Grid Based on Source-Load Matching

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics