A Coordinated Planning Model for Wind-Solar Capacity Ratio Considering both Accommodation and Supply Preservation

doi:10.16628/j.cnki.2095-8188.2025.12.004

Abstract

Abstract:

With the in-depth advancement of the construction of new power systems, ensureing the accomodation of wind and solar energy while maintaining the stable power supply of the power system has become a key challenge in the coordinated planning of wind-solar capacity ratios. First, a systematic analysis framework covering data processing, model input, modeling solution, and result output is built. Secondly, taking into account constraints such as the volatility of new energy output and equipment operation, a planning model with the goal of economic optimization is constructed, and the power abandonment rate and power shortage rate are proposed as evaluation indicators. Finally, the effects of different wind-solar ratios on the new energy absorption level and system power supply capacity are analyzed through examples. The results show that a reasonable wind-solar ratio can effectively improve the resource absorption capacity and optimize the economy while ensuring power supply.

Key words: capacity configuration, wind-solar complementarity, power abandonment rate, power shortage rate, NSGA-Ⅱ algorithm

CLC Number:

TM73

TIAN Xiaoyu, ZHAI Wenhui, KANG Pengpeng, YANG Guixing, SUN Yiqian, GUAN Qi. A Coordinated Planning Model for Wind-Solar Capacity Ratio Considering both Accommodation and Supply Preservation[J]. LOW VOLTAGE APPARATUS, 2025, 0(12): 25-33.

Figures/Tables 10

References 22

[1]	李增辉, 顾雪平, 姚伟锋, 等. 新型电力系统电力平衡风险防控研究[J]. 新型电力系统, 2025, 3(1):74-87.
[2]	郭强, 顾永强. 可再生能源弃电原因分析及应对措施[J]. 节能与环保, 2024(12):39-45.
[3]	蒋金荷, 袁全红. “双碳”目标下我国三北地区能源外送新途径研究[J]. 价格理论与实践, 2023(7):30-34.
[4]	LIU Y, XU X, LIU Y, et al. Grid abandonment potential of photovoltaic and storage-based system in China[J]. International Journal of Electrical Power & Energy Systems, 2024,155:109414.
[5]	YANG X, ZHOU Y, YU Z, et al. Research on Gansu power transmission capacity under multi-energy complementary[C]// 2024 6th International Conference on Energy, Power and Grid(ICEPG).Guangzhou,China, 2024:177-182.
[6]	张程, 江炜龙, 罗玉锦, 等. 考虑风光不确定性的多数据中心微网与共享储能协同优化运行[J]. 电力系统保护与控制, 2025, 53(4):72-84.
[7]	白忠彬. 多尺度灵活性资源博弈下风电场储能容量优化[J]. 电器与能效管理技术, 2023(5):79-88.
[8]	刘颖明, 陈亮, 王晓东, 等. 混合储能参与风电集群一次调频的容量配置优化[J]. 电器与能效管理技术, 2020(10):55-63.
[9]	杨颖, 刘友波, 黄媛, 等. 电能替代下考虑需求响应的综合园区风光储配置方法[J]. 电力建设, 2021, 42(10):9-18.. doi: 10.12204/j.issn.1000-7229.2021.10.002
[10]	DING H J, PINSON P, HU Z C, et al. Optimal offering and operating strategy for a large wind-storage system as a price maker[J]. IEEE Transactions on Power Systems, 2017, 32(6):4904-4913. doi: 10.1109/TPWRS.2017.2681720
[11]	DIRIN S, RAHIMIYAN M, BARINGO L. Optimal offering strategy for wind-storage systems under correlated wind production[J]. Applied Energy, 2023,333:120552.
[12]	刘金朋, 胡国松, 彭锦淳, 等. 多能互补的虚拟电厂低碳-经济-鲁棒优化调度[J]. 中国电机工程学报, 2024, 44(24):9718-9731.
[13]	梁远升, 徐真理, 李海锋, 等. 基于随机响应面法的配电网故障恢复全时段不确定性优化方法[J]. 中国电机工程学报, 2024, 44(23):9200-9213.
[14]	伍峻杭, 刘继春, 吴沂洋. 偏远地区能源自洽系统源储容量协同配置方法[J]. 电网技术, 2024, 48(5):2031-2042.
[15]	商立群, 张建涛. 计及储能电池寿命衰减的居民小区光储优化配置[J]. 电气技术, 2024, 25(2):1-11.
[16]	WANG J, SUN Y, DU X, et al. Optimal configuration and pricing strategies for electric-heat cloud energy storage:A stackelberg game approach[J]. Sustainable Energy Technologies and Assessments, 2022,53 (Oct.Pt.B):1-12.
[17]	张普育. 双碳背景下风光储一体化可再生能源绿色标准化发展及实践[J]. 中国标准化, 2024(S2):72-76.
[18]	何婷, 乔俊强, 吴国栋. 基于GRU算法的弃电量预测及电-氢混合储能系统的运行优化[J]. 储能科学与技术, 2024, 13(5):1731-1740. doi: 10.19799/j.cnki.2095-4239.2023.0828
[19]	杜维柱, 白恺, 李海波, 等. 兼顾保供电/消纳的源荷储灵活性资源优化规划[J]. 电力建设, 2023, 44(9):13-23. doi: 10.12204/j.issn.1000-7229.2023.09.002
[20]	许涛, 王国春, 董昱, 等. 新型电力系统平衡机理及演进过程研究[J]. 中国电机工程学报, 2025, 45(1):1-14.
[21]	孙亚璐, 丁坤, 杨昌海, 等. “双碳”背景下统筹保供与转型的新型电力系统建设研究[J]. 电子元器件与信息技术, 2023, 7(3):125-128.
[22]	高红均, 郭明浩, 刘俊勇, 等. 从四川高温干旱限电事件看新型电力系统保供挑战与应对展望[J]. 中国电机工程学报, 2023, 43(12):4517-4538.

装机情况	最大负荷/MW	火电/MW	水电/MW	储能/MW	抽水蓄能/MW	新能源/MW	生物质/MW
1	38 690	26 300	10 000	10 000	7 800	80 000	1 000
2	38 690	26 300	10 000	11 000	7 800	80 000	1 000
3	38 690	26 300	10 000	12 000	7 800	80 000	1 000
4	38 690	26 300	10 000	10 000	7 800	90 000	1 000
5	38 690	26 300	10 000	11 000	7 800	90 000	1 000
6	38 690	26 300	10 000	12 000	7 800	90 000	1 000
7	38 690	26 300	10 000	10 000	7 800	100 000	1 000
8	38 690	26 300	10 000	11 000	7 800	100 000	1 000
9	38 690	26 300	10 000	12 000	7 800	100 000	1 000

装机情况	风电/MW	光伏/MW	风光比	缺电情况/%	新能源弃电率/%	储能等效利用小时数/h	抽蓄等效利用小时数/h
1	3 873	4 127	0.938 3	2	16.02	1 414	2 138
2	3 735	4 265	0.875 8	2	15.86	1 426	2 141
3	3 597	4 403	0.817 1	2	15.72	1 421	2 154
4	3 822	5 178	0.738 2	2	23.20	1 405	2 137
5	3 685	5 315	0.693 2	2	23.10	1 434	2 152
6	3 547	5 453	0.650 4	2	23.03	1 422	2 155
7	3 800	6 200	0.612 9	2	29.30	1 407	2 150
8	3 800	6 200	0.612 9	2	29.05	1 412	2 139
9	3 800	6 200	0.612 9	2	28.81	1 417	2 144

装机情况	风电等效利用小时数/h	光伏等效利用小时数/h	火电等效利用小时数/h	最大缺口/ 万kW	风电利用率/%	光伏利用率/%
1	2 241	1 374	3 082	77.38	86.19	80.80
2	2 221	1 402	3 107	77.38	85.40	82.45
3	2 131	1 482	3 000	77.38	81.95	87.19
4	1 921	1 362	3 067	77.38	73.87	80.12
5	1 848	1 412	3 093	77.38	71.08	83.07
6	1 908	1 369	3 120	77.38	73.37	80.54
7	1 797	1 228	3 052	77.38	69.10	72.20
8	1 813	1 225	3 035	77.38	69.74	72.08
9	1 814	1 233	3 019	77.38	69.76	72.53

风光比例	风电装机/MW	光伏装机/MW	缺电率/%	弃电率/%	短时储能等效利用小时数/h	长时储能等效利用小时数/h
1.139	42 599	37 401	1.85	17.00	1 095	1 825
1.100	41 905	38 095	1.85	16.77	1 095	1 825
1.050	40 976	39 024	1.85	16.53	1 095	1 825
1.000	40 000	40 000	1.84	16.48	1 095	1 825
0.955	39 079	40 921	1.84	16.34	1 095	1 825
0.900	37 895	42 105	1.83	16.28	1 095	1 825
0.817	35 974	44 026	1.82	16.25	1 095	1 825
0.800	不满足边界条件