Research on Development Scenario of Renewable Energy in Receiving-End Power Grid Based on Production Simulation

doi:10.11930/j.issn.1004-9649.202307086

Abstract

Abstract:

Driven by the goals of "carbon peaking and carbon neutrality", the large-scale integration of renewable energy into the receiving-end power grid, coupled with the increasing proportion of external electricity, has made it more difficult to balance electricity and achieve clean substitution in the receiving-end power grid. Based on actual operating data, the low output characteristics of renewable energy and its matching characteristics with load were analyzed, and the key issues faced by high-proportion renewable energy power systems were summarized. On this basis, a time series production simulation model for the power system was established, and the scenario for the 2060 case was designed based on the standardization of the 2030 forecast data. Quantitative analysis was conducted on the allocation of renewable energy, coal-fired power, and flexible resources in typical provincial receiving-end power grids, as well as the implementation of clean substitution solutions in different renewable energy development scenarios, and relevant measures and suggestions were proposed.

Key words: renewable energy, time series production simulation, standardization, flexible resources, carbon neutrality

Shuai WANG, Yuehui HUANG, Yuanhong NIE, Siyang LIU. Research on Development Scenario of Renewable Energy in Receiving-End Power Grid Based on Production Simulation[J]. Electric Power, 2024, 57(5): 240-250.

Add to citation manager EndNote|Ris|BibTeX

URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202307086

https://www.electricpower.com.cn/EN/Y2024/V57/I5/240

Figures/Tables 11

References 29

1	国务院. 2030年前碳达峰行动方案[R]. 北京: 国务院, 2022.
2	国家能源局. 新型电力系统发展蓝皮书(征求意见稿)[R]. 北京: 国家能源局, 2023.
3	石文辉, 白宏, 屈姬贤, 等. 我国风电高效利用技术趋势及发展建议[J]. 中国工程科学, 2018, 20 (3): 51- 57. DOI
	SHI Wenhui, BAI Hong, QU Jixian, et al. Technology trend and development suggestions for wind power efficient utilization in China[J]. Strategic Study of CAE, 2018, 20 (3): 51- 57. DOI
4	文云峰, 杨伟峰, 汪荣华, 等. 构建100%可再生能源电力系统述评与展望[J]. 中国电机工程学报, 2020, 40 (6): 1843- 1856.
	WEN Yunfeng, YANG Weifeng, WANG Ronghua, et al. Review and prospect of toward 100% renewable energy power systems[J]. Proceedings of the CSEE, 2020, 40 (6): 1843- 1856.
5	国家能源局. 2020年全国电力工业统计数据[R]. 北京: 国家能源局, 2021.
6	财政部, 国家发展改革委, 国家能源局. 关于促进非水可再生能源发电健康发展的若干意见(财建〔2020〕4号)[R]. 北京: 财政部, 国家发展改革委, 国家能源局, 2020.
7	周原冰, 杨方, 余潇潇, 等. 中国能源电力碳中和实现路径及实施关键问题[J]. 中国电力, 2022, 55 (5): 1- 11.
	ZHOU Yuanbing, YANG Fang, YU Xiaoxiao, et al. Realization pathways and key problems of carbon neutrality in China's energy and power system[J]. Electric Power, 2022, 55 (5): 1- 11.
8	单葆国, 冀星沛, 许传龙, 等. 近期全球能源供需形势分析及中国能源电力保供策略[J]. 中国电力, 2022, 55 (10): 1- 13.
	SHAN Baoguo, JI Xingpei, XU Chuanlong, et al. Recent situation of global energy supply-demand and guarantee strategy of China's energy and power supply[J]. Electric Power, 2022, 55 (10): 1- 13.
9	陈国平, 梁志峰, 董昱. 基于能源转型的中国特色电力市场建设的分析与思考[J]. 中国电机工程学报, 2020, 40 (2): 369- 379.
	CHEN Guoping, LIANG Zhifeng, DONG Yu. Analysis and reflection on the marketization construction of electric power with Chinese characteristics based on energy transformation[J]. Proceedings of the CSEE, 2020, 40 (2): 369- 379.
10	彭迎港. 考虑源荷时序相关性的新能源跨区域消纳研究[D]. 北京: 北京交通大学, 2021.
	PENG Yinggang. Research on cross-regional consumption of renewable energy with consideration of time series correlation between renewable energy and load[D]. Beijing: Beijing Jiaotong University, 2021.
11	张兴友, 韩德顺, 马杰, 等. 受端电网新能源消纳影响因素分析及应对策略[J]. 济南大学学报(自然科学版), 2019, 33 (1): 68- 72.
	ZHANG Xingyou, HAN Deshun, MA Jie, et al. Analysis of influence factors and countermeasures for renewable energy usage in terminal power grid[J]. Journal of University of Jinan (Science and Technology), 2019, 33 (1): 68- 72.
12	杨昆, 孙磊, 房超运, 等. 促进新能源消纳的混合发电系统[J]. 中国电力, 2022, 55 (2): 145- 151.
	YANG Kun, SUN Lei, FANG Chaoyun, et al. Hybrid power generation system to promote new energy consumption[J]. Electric Power, 2022, 55 (2): 145- 151.
13	崔杨, 程广岩, 仲悟之, 等. 计及受端电网调峰趋势的风-光-火特高压直流外送调度方法[J]. 太阳能学报, 2021, 42 (8): 32- 40.
	CUI Yang, CHENG Guangyan, ZHONG Wuzhi, et al. Wind-photovoltaic-fire UHVDC external dispatching method considering peaking trend of power grid[J]. Acta Energiae Solaris Sinica, 2021, 42 (8): 32- 40.
14	王利利, 王皓, 任洲洋, 等. 计及灵活资源调节潜力的高压配电网新能源接纳能力评估[J]. 中国电力, 2022, 55 (10): 124- 131.
	WANG Lili, WANG Hao, REN Zhouyang, et al. Evaluation of renewable energy accommodation capacity of high voltage distribution networks considering regulation potential of flexible resources[J]. Electric Power, 2022, 55 (10): 124- 131.
15	赵军, 张敏, 张世锋, 等. 计及碳交易和新能源不确定性的多微电网合作运行优化策略[J]. 中国电力, 2023, 56 (5): 62- 71.
	ZHAO Jun, ZHANG Min, ZHANG Shifeng, et al. Optimization strategy of multi-microgrid cooperative operation considering carbon trading and renewable energy uncertainties[J]. Electric Power, 2023, 56 (5): 62- 71.
16	廖婧. 新能源电力系统的源网荷多资源调峰策略研究[D]. 长沙: 湖南大学, 2021.
	LIAO Jing. Research on multi-resource peak regulation strategy of source-grid-load in renewable energy power system[D]. Changsha: Hunan University, 2021.
17	赵波, 李得民, 吴在军, 等. 基于100%绿色能源供电目标的海岛微电网群容量优化配置[J]. 中国电机工程学报, 2021, 41 (3): 932- 945.
	ZHAO Bo, LI Demin, WU Zaijun, et al. Capacity optimal sizing of island microgrid clusters based on the target of 100% green energy power supply[J]. Proceedings of the CSEE, 2021, 41 (3): 932- 945.
18	寇凌峰, 季宇, 吴鸣, 等. 多能互补系统全寿命周期优化配置方法[J]. 中国电力, 2020, 53 (12): 75- 82.
	KOU Lingfeng, JI Yu, WU Ming, et al. Optimal configuration of multi-energy complementary system considering full life cycle[J]. Electric Power, 2020, 53 (12): 75- 82.
19	刘联涛, 刘飞, 吉平, 等. 储能参与新能源消纳的优化控制策略[J]. 中国电力, 2023, 56 (3): 137- 143.
	LIU Liantao, LIU Fei, JI Ping, et al. Research on optimal control strategy of energy storage for improving new energy consumption[J]. Electric Power, 2023, 56 (3): 137- 143.
20	代倩, 张健, 吴俊玲, 等. 基于多分区时序生产模拟的省级电网差异化储能规划方法[J]. 中国电力, 2022, 55 (11): 21- 28.
	DAI Qian, ZHANG Jian, WU Junling, et al. Differentiated energy storage planning method of provincial power grids based on multi-partition time series production simulation[J]. Electric Power, 2022, 55 (11): 21- 28.
21	窦东, 王雁宇, 李欣, 等. 蒙西地区储能技术经济性优化配置研究[J]. 中国电力, 2022, 55 (8): 52- 63.
	DOU Dong, WANG Yanyu, LI Xin, et al. Techno-economically optimal configuration of energy storage for western Inner Mongolia[J]. Electric Power, 2022, 55 (8): 52- 63.
22	开赛江, 谭捷, 孙谊媊, 等. 考虑容量约束的储能规模化应用商业模式评价[J]. 中国电力, 2022, 55 (4): 203- 213, 228.
	KAI Saijiang, TAN Jie, SUN Yiqian, et al. Evaluation of business mode for large-scale energy storage applications considering capacity constraints[J]. Electric Power, 2022, 55 (4): 203- 213, 228.
23	李相俊, 马会萌, 姜倩. 新能源侧储能配置技术研究综述[J]. 中国电力, 2022, 55 (1): 13- 25.
	LI Xiangjun, MA Huimeng, JIANG Qian. Review of energy storage configuration technology on renewable energy side[J]. Electric Power, 2022, 55 (1): 13- 25.
24	孙启星, 张超, 李成仁, 等. “碳达峰、碳中和” 目标下的电力系统成本及价格水平预测[J]. 中国电力, 2023, 56 (1): 9- 16.
	SUN Qixing, ZHANG Chao, LI Chengren, et al. Prediction of power system cost and price level under the goal of "carbon peak and carbon neutralization"[J]. Electric Power, 2023, 56 (1): 9- 16.
25	刘纯, 黄越辉, 石文辉, 等. 新能源电力系统生产模拟[M]. 北京: 中国电力出版社, 2019: 1–61, 81–110.
26	辛保安. 新型电力系统构建方法论研究[J]. 新型电力系统, 2023, 1 (1): 1- 18.
	XIN Baoan. Research on the methodology of constructing new power systems[J]. New Type Power Systems, 2023, 1 (1): 1- 18.
27	郭剑波, 王铁柱, 罗魁, 等. 新型电力系统面临的挑战及应对思考[J]. 新型电力系统, 2023, (1): 32- 43.
	GUO Jianbo, WANG Tiezhu, LUO Kui, et al. Development of new power systems: challenges and solutions[J]. New Type Power Systems, 2023, (1): 32- 43.
28	冯双磊, 胡菊, 宋宗朋, 等. 新能源资源评估与中长期电量预测[M]. 北京: 中国电力出版社, 2019: 122–159.
29	丁明, 楚明娟, 毕锐, 等. 基于序贯蒙特卡洛随机生产模拟的风电接纳能力评价方法及应用[J]. 电力自动化设备, 2016, 36 (9): 67- 73.
	DING Ming, CHU Mingjuan, BI Rui, et al. Wind power accommodation capability evaluation based on sequential Monte Carlo probabilistic production simulation and its application[J]. Electric Power Automation Equipment, 2016, 36 (9): 67- 73.

省级电网数量	类别	低出力年累计时长/h	单次持续时间/h
省级电网数量	类别	低出力年累计时长/h	最大	最小
20	风电＜10%	154.25	28.75	0.25
	光伏＜10%	2507.75	16.75	0.25
	风+光＜10%	1095.00	17.50	0.25
	风电＜5%	1.50	1.50	1.50
	光伏＜5%	2089.25	15.75	0.25
	风+光＜5%	30.25	14.50	3.25
5	风电＜10%	1022.50	36.75	0.25
	光伏＜10%	2239.50	17.75	0.25
	风+光＜10%	2899.25	36.25	0.25
	风电＜5%	237.00	25.75	0.25
	光伏＜5%	1721.00	16.25	0.25
	风+光＜5%	750.75	16.00	0.25
1	风电＜10%	2787.75	129.75	0.25
	光伏＜10%	1936.75	18.75	0.25
	风+光＜10%	2718.00	66.50	0.25
	风电＜5%	1507.75	82.50	0.25
	光伏＜5%	1444.25	15.50	0.25
	风+光＜5%	1512.75	18.75	0.25

省级电网数量	类别	低出力年累计时长/h	单次持续时间/h
省级电网数量	类别	低出力年累计时长/h	最大	最小
20	风电＜10%	154.25	28.75	0.25
	光伏＜10%	2507.75	16.75	0.25
	风+光＜10%	1095.00	17.50	0.25
	风电＜5%	1.50	1.50	1.50
	光伏＜5%	2089.25	15.75	0.25
	风+光＜5%	30.25	14.50	3.25
5	风电＜10%	1022.50	36.75	0.25
	光伏＜10%	2239.50	17.75	0.25
	风+光＜10%	2899.25	36.25	0.25
	风电＜5%	237.00	25.75	0.25
	光伏＜5%	1721.00	16.25	0.25
	风+光＜5%	750.75	16.00	0.25
1	风电＜10%	2787.75	129.75	0.25
	光伏＜10%	1936.75	18.75	0.25
	风+光＜10%	2718.00	66.50	0.25
	风电＜5%	1507.75	82.50	0.25
	光伏＜5%	1444.25	15.50	0.25
	风+光＜5%	1512.75	18.75	0.25

省级电网数量	类别	最大	最小	平均
20	日负荷峰谷差率/%	31.2	10.6	20.8
20	日均负荷率/%	94.2	83.8	90.8
5	日负荷峰谷差率/%	40.0	14.3	24.1
5	日均负荷率/%	93.8	79.6	89.8
1	日负荷峰谷差率/%	39.5	9.5	19.9
1	日均负荷率/%	96.0	79.3	90.9

省级电网数量	类别	最大	最小	平均
20	日负荷峰谷差率/%	31.2	10.6	20.8
20	日均负荷率/%	94.2	83.8	90.8
5	日负荷峰谷差率/%	40.0	14.3	24.1
5	日均负荷率/%	93.8	79.6	89.8
1	日负荷峰谷差率/%	39.5	9.5	19.9
1	日均负荷率/%	96.0	79.3	90.9

省级电网数量	年负荷峰谷差率/%	持续时间/h（占比/%）
省级电网数量	年负荷峰谷差率/%	＞90%最大负荷	＞95%最大负荷
20	52.7	332.25（3.8）	84.75（0.99）
5	66.2	391.00（4.5）	146.00（1.7）
1	65.7	288.00（3.3）	86.75（0.97）