Journal of Shandong University(Engineering Science) ›› 2024, Vol. 54 ›› Issue (6): 156-166.doi: 10.6040/j.issn.1672-3961.0.2023.259

• Electrical Engineering • Previous Articles    

Coordinated short-term source-grid-storage expansion planning based on refined operation simulation

CHEN Yinfeng1, XIAO Jinyu2, HOU Jinming2, JIANG Han2, ZHAO Xiaoling2, SHI Xiaohan1*   

  1. 1.School of Electrical Engineering, Shandong University, Jinan 250061, Shandong, China;
    2. Global Energy Interconnection Group Co., Ltd., Beijing 100031, China
  • Published:2024-12-26

PDF (PC)

6

CLC Number: 

  • TM715
[1] 李晖, 刘栋, 姚丹阳. 面向碳达峰碳中和目标的我国电力系统发展研判[J]. 中国电机工程学报, 2021, 41(18): 6245-6259. LI Hui, LIU Dong, YAO Danyang. Analysis and reflection on the development of power system towards the goal of carbon emission peak and carbon neutrality[J]. Proceedings of the CSEE, 2021, 41(18): 6245-6259.
[2] 黎博, 陈民铀, 钟海旺, 等. 高比例可再生能源新型电力系统长期规划综述[J]. 中国电机工程学报, 2023, 43(2): 555-581. LI Bo, CHEN Minyou, ZHONG Haiwang, et al. A review of long-term planning of new power systems with large share of renewable energy[J]. Proceedings of the CSEE, 2023, 43(2): 555-581.
[3] 鲁宗相, 李海波, 乔颖. 含高比例可再生能源电力系统灵活性规划及挑战[J]. 电力系统自动化, 2016, 40(13): 147-158. LU Zongxiang, LI Haibo, QIAO Ying. Power system flexibility planning and challenges considering high proportion of renewable energy[J]. Automation of Electric Power Systems, 2016, 40(13): 147-158.
[4] 孙东磊, 赵龙. 基于学习理论的含光储联合系统的输电网双层规划[J]. 山东大学学报(工学版), 2020, 50(4): 90-97. SUN Donglei, ZHAO Long. Bi-level planning of transmission network with solar-storage combination system based on learning theory[J]. Journal of Shandong University(Engineering Science), 2020, 50(4): 90-97.
[5] 王建学, 李清涛, 王秀丽, 等. 大规模新能源并网系统电源规划方法[J]. 中国电机工程学报, 2020, 40(10): 3114-3124. WANG Jianxue, LI Qingtao, WANG Xiuli, et al. A generation expansion planning method for power systems with large-scale new energy[J]. Proceedings of the CSEE, 2020, 40(10): 3114-3124.
[6] 孙东磊, 鉴庆之, 李智琦, 等. 源网协调的电力系统均匀性规划[J]. 山东大学学报(工学版), 2022, 52(5): 92-101. SUN Donglei, JIAN Qingzhi, LI Zhiqi, et al. Power system uniformity planning based on source network coordination[J]. Journal of Shandong University(Engineering Science), 2022, 52(5): 92-101.
[7] CHEN X, LÜ J, MCELROY M B, et al. Power system capacity expansion under higher penetration of renewables considering flexibility constraints and low carbon policies[J]. IEEE Transactions on Power Systems, 2018, 33(6): 6240-6253.
[8] 王良缘, 江岳文, 王杰. 考虑参与多市场交易的电网侧储能优化配置[J]. 电网与清洁能源, 2020, 36(11): 30-38. WANG Liangyuan, JIANG Yuewen, WANG Jie. Optimization of grid-side energy storage considering multi-market transaction[J]. Power System and Clean Energy, 2020, 36(11): 30-38.
[9] 张振宇, 王文倬, 张小奇, 等. 基于电力系统承载力指标的新能源装机规划方法[J]. 电网技术, 2021, 45(2): 632-639. ZHANG Zhenyu, WANG Wenzhuo, ZHANG Xiaoqi, et al. Renewable energy capacity planning based on carrying capacity indicators of power system[J]. Power System Technology, 2021, 45(2): 632-639.
[10] 葛晓琳, 徐轶胜, 符杨, 等. 考虑多重不确定性影响的海上风储多属性联合规划[J]. 电网技术, 2023, 47(10): 4140-4153. GE Xiaolin, XU Yisheng, FU Yang, et al. Multi-attribute joint planning of offshore wind and storage considering influence of multiple uncertainties[J]. Power System Technology, 2023, 47(10): 4140-4153.
[11] 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.
[12] DEHGHAN S, AMJADY N, CONEJO A J. Reliability-constrained robust power system expansion planning[J]. IEEE Transactions on Power Systems, 2016, 31(3): 2383-2392.
[13] 张宁, 胡兆光, 周渝慧, 等. 计及随机模糊双重不确定性的源网荷协同规划模型[J]. 电力系统自动化, 2016, 40(1): 39-44. ZHANG Ning, HU Zhaoguang, ZHOU Yuhui, et al. Source-grid-load coordinated planning model considering randomness and fuzziness[J]. Automation of Electric Power Systems, 2016, 40(1): 39-44.
[14] 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.
[15] 原一方, 尚策. 减碳中多阶段的煤电机组退役与新能源、储能规划协同[J]. 电力自动化设备, 2021, 41(9): 140-147. YUAN Yifang, SHANG Ce. Coordiantion of multi-stage renewable energy, energy storage planning and coal-fired unit retirement under carbon reduction goal[J]. Electric Power Automation Equipment, 2021, 41(9): 140-147.
[16] 杨修宇, 穆钢, 柴国峰, 等. 考虑灵活性供需平衡的源-储-网一体化规划方法[J]. 电网技术, 2020, 44(9): 3238-3246. YANG Xiuyu, MU Gang, CHAI Guofeng, et al. Source-storage-grid integrated planning considering flexible supply-demand balance[J]. Power System Technology, 2020, 44(9): 3238-3246.
[17] 张衡, 程浩忠, 张建平, 等. 高比例风电背景下计及N-1安全网络约束的发输电优化规划[J]. 中国电机工程学报, 2018, 38(20): 5929-5936. ZHANG Heng, CHENG Haozhong, ZHANG Jianping, et al. Generation and transmission expansion planning considering N-1 security constraints with high penetration of wind power[J] Proceedings of the CSEE, 2018, 38(20): 5929-5936.
[18] 史昭娣, 黄越辉, 李湃, 等. 计及深度信念网络场景生成的风/光/储协同优化规划方法[J/OL]. 电网技术.(2022-08-18)[2023-10-30]. https://kns.cnki.net/kcms/detail/11.2410.tm.20220817.0939.001.html.
[19] 付文龙, 卓庆澳, 吴月超, 等. 多能互补提供频率支撑的储能容量分布鲁棒规划方法[J/OL]. 电网技术.(2023-08-16)[2023-10-30]. https://doi.org/10.13335/j.1000-3673.pst.2023.0804.
[20] 康重庆, 姚良忠. 高比例可再生能源电力系统的关键科学问题与理论研究框架[J]. 电力系统自动化, 2017, 41(9): 2-11. KANG Chongqing, YAO Liangzhong. Key scientific issues and theoretical research framework for power systems with high proportion of renewable energy[J]. Automation of Electric Power Systems, 2017, 41(9): 2-11.
[21] 刘自发, 于寒霄, 王帅, 等. 综合考虑运行效率和弃风损失的输电网规划[J]. 电网技术, 2018, 42(3): 827-834. LIU Zifa, YU Hanxiao, WANG Shuai, et al. Transmission grid planning considering operation efficiency and wind curtailment loss[J]. Power System Technology, 2018, 42(3): 827-834.
[22] 杨修宇. 提升高风电渗透率电力系统灵活性的源-储-网协调规划方法[D]. 北京: 华北电力大学, 2021. YANG Xiuyu. Source-storage-grid coordinated planning method for improving flexibility of power system with high wind power penetration[D]. Beijing: North China Electric Power University, 2021.
[23] 谢鹏, 蔡泽祥, 刘平, 等. 考虑多时间尺度不确定性耦合影响的风光储微电网系统储能容量协同优化[J]. 中国电机工程学报, 2019, 39(24): 7126-7136. XIE Peng, CAI Zexiang, LIU Ping, et al. Cooperative optimization of energy storage capacity for renewable and storage involved microgrids considering multi time scale uncertainty coupling influence[J]. Proceedings of the CSEE, 2019, 39(24): 7126-7136.
[24] 姜惠兰, 安星, 王亚微, 等. 基于改进NSGA2算法的考虑风机接入电能质量的多目标电网规划[J]. 中国电机工程学报, 2015, 35(21): 5405-5411. JIANG Huilan, AN Xing, WANG Yawei, et al. Improved NSGA2 algorithm based multi-objective planning of power grid with wind farm considering power quality[J]. Proceedings of the CSEE, 2015, 35(21): 5405-5411.
[25] GOMES P V, SARAIVA J T. Hybrid genetic algorithm for multi-objective transmission expansion planning[C] //2016 IEEE International Energy Conference(ENERGYCON). Leuven, Belgium: IEEE, 2016: 7514131.
[26] DEB K, PRATAP A, AGARWAL S, et al. A fast and elitist multi-objective genetic algorithm: NSGA-Ⅱ[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182-197.
[27] ZHUO Z Y, DU E S, ZHANG N, et al. Cost increase in the electricity supply to achieve carbon neutrality in China[J]. Nature Communications, 2022, 13: 3172.
[1] SUN Donglei, JIAN Qingzhi, LI Zhiqi, HAN Xueshan, WANG Mingqiang, CHEN Bo, FU Yimu. Power system uniformity planning based on source network coordination [J]. Journal of Shandong University(Engineering Science), 2022, 52(5): 92-101.
[2] Wensheng LI, Xian WANG, Yuanze MI, Yongji CAO, Xiaoming LIU, Hengxu ZHANG, Zihan LIU. Method for generation planning with the temporal and spatial correlation of wind and solar power [J]. Journal of Shandong University(Engineering Science), 2022, 52(1): 111-119.
[3] Xiaoming LIU,Yini CONG,Wenbo LI,Yutian LIU. Comprehensive decision-making method for large-scale photovoltaic system integrated to receiving-end power grid [J]. Journal of Shandong University(Engineering Science), 2019, 49(4): 115-122.
[4] LI Sun, WANG Chao, ZHANG Guilin, XU Zhigen, CHENG Tao, WANG Yiyuan, WANG Ruiqi. Short-term power load forecasting based on support vector regression [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(6): 52-56.
[5] JI Xingquan, HAN Guozheng, LI Kejun, FU Rongrong, ZHU Yanghe. Application of improved K-means clustering algorithm based on density in distribution network block partitioning [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(4): 41-46.
[6] YU Songqing, HOU Chenghao, SUN Yingtao. Power demand forecasting in Shandong province with system dynamics [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2015, 45(6): 91-98.
[7] SUN Donglei, SUN Keqi, YANG Jinye, CAO Yongji, YUAN Zhenhua, LIU Dong, ZHANG Hengxu. Power system optimal dispatch considering the requirements of flexibility [J]. Journal of Shandong University(Engineering Science), 2022, 52(1): 120-127.
[8] GE Weichun, LI Zhao, ZHAO Dong, LI Zhenyu, YE Qing, FU Yu, YU Na. Comprehensive benefits analysis of power supply side of regional power grid with electrode-type electric boiler [J]. Journal of Shandong University(Engineering Science), 2020, 50(5): 90-98.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright 2018 © Editorial office of Journal of Shandong University (Engineering Science)
Supported by Beijing Magtech Co.Ltd