Multi-Objective Optimization Scheduling Method Considering Peak Regulating Market Transactions for Energy Storage - New Energy - Thermal Power
Li Junhui1, An Chenyu1, Li Cuiping1, Zhang Jingxiang1, Liu Ruitong2
1. Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 China; 2. Electric Power Research Institute of State Grid Liaoning Electric Power Co. Ltd Shenyang 110006 China
Abstract：Large scale new energy access poses challenges to power grid peak shaving. How to improve the grid connection rate of new energy while taking into account the economic benefits of peak shaving resources has become an important problem that needs to be solved urgently. Therefore, this paper proposes a multi-objective optimization dispatching method of energy storage new energy thermal power under the electricity market environment, which considers the abandonment of wind and light. This paper first designs the trading mechanism of energy storage new energy thermal power peak shaving market according to the current peak shaving policy, and establishes a new energy trading power model, a bidding model and a thermal power bidding model based on the current peak shaving rules, with the wind abandonment rate and light abandonment rate as the benchmark. Secondly, through bilateral transactions between new energy, energy storage and thermal power, with the bid winning power of new energy and system peak shaving cost as multiple objectives, the output of thermal power units, bid winning power of new energy, energy storage charging and discharging power and clearing price are optimized. In order to verify the effectiveness of the above control strategies, this paper takes a region in Northeast China as an example, and conducts numerical simulation by selecting typical daily system operation data. The specific conclusions are as follows: First of all, this paper constructs a new energy trading power model and a new energy quotation model for the situation of new energy abandoning wind and light. The model can fully reflect the trading willingness of new energy stations in each period and improve the enthusiasm of new energy stations to participate in the peak shaving market by taking the wind abandonment rate and light abandonment rate in each period as the benchmark. Secondly, by setting up three scenarios to verify, compared with the market model of “unilateral transaction of thermal power units” in Scenario 1 and the market model of “bilateral transaction of new energy thermal power” in Scenario 2, the optimal dispatching strategy proposed in this paper reduces the wind abandonment rate and light abandonment rate of typical new energy stations by 4.21%, 5.26%, 1.77% and 2.25% respectively, and the new energy consumption capacity of the power system is significantly improved. Finally, the optimized dispatching strategy proposed in this paper can improve the economic benefits of peak shaving of market players while reducing the wind abandonment rate and light abandonment rate: in typical days, the net cost of peak shaving of thermal power units decreases by 56 100 CNY compared with the "thermal power unilateral" trading mode, and the net income of wind farms and photovoltaic power plants increases by 305 200 CNY and 90 100 CNY respectively. At the same time, when the net income of energy storage participating in market transactions is converted to the full life cycle, the cost coverage rate can reach 212.94%, and the economic benefits of market players for peak shaving can be significantly improved.
李军徽, 安晨宇, 李翠萍, 张靖祥, 刘芮彤. 计及调峰市场交易的储能-新能源-火电多目标优化调度[J]. 电工技术学报, 2023, 38(23): 6391-6406.
Li Junhui, An Chenyu, Li Cuiping, Zhang Jingxiang, Liu Ruitong. Multi-Objective Optimization Scheduling Method Considering Peak Regulating Market Transactions for Energy Storage - New Energy - Thermal Power. Transactions of China Electrotechnical Society, 2023, 38(23): 6391-6406.
[1] 国家能源局. 2020 年上半年风电并网运行情况[R/OL]. [2020-07-31]. http://www.nea.gov.cn/2020-07/31/c_ 139254298.htm. [2] 麻秀范, 王戈, 朱思嘉, 等. 计及风电消纳与发电集团利益的日前协调优化调度[J]. 电工技术学报, 2021, 36(3): 579-587. Ma Xiufan, Wang Ge, Zhu Sijia, et al.Coordinated day-ahead optimal dispatch considering wind power consumption and the benefits of power generation group[J]. Transactions of China Electrotechnical Society, 2021, 36(3): 579-587. [3] 鲁宗相, 李海波, 乔颖. 高比例可再生能源并网的电力系统灵活性评价与平衡机理[J]. 中国电机工程学报, 2017, 37(1): 9-20. Lu Zongxiang, Li Haibo, Qiao Ying.Flexibility evaluation and supply/demand balance principle of power system with high-penetration renewable electricity[J]. Proceedings of the CSEE, 2017, 37(1): 9-20. [4] 李丰, 张粒子. 大规模风电跨省消纳与交易机制的研究[J]. 电力自动化设备, 2013, 33(8): 119-124. Li Feng, Zhang Lizi.Accommodation and transaction mechanism of transprovincial large-scale wind power[J]. Electric Power Automation Equipment, 2013, 33(8): 119-124. [5] 国家发展改革委.关于深圳市开展输配电价改革试点的通知[EB/OL]. (2014-10-23)[2020-04-03].https:www.jiaheu.com/topic/234546.html. [6] 胡朝阳, 毕晓亮, 王珂, 等. 促进负备用跨省调剂的华东电力调峰辅助服务市场设计[J]. 电力系统自动化, 2019, 43(5): 175-182. Hu Zhaoyang, Bi Xiaoliang, Wang Ke, et al.Design of peak regulation auxiliary service market for East China power grid to promote inter-provincial sharing of negative reserve[J]. Automation of Electric Power Systems, 2019, 43(5): 175-182. [7] 王鹏远. 考虑风电并网影响的调峰辅助服务市场机制研究[D]. 北京: 华北电力大学(北京), 2018. [8] 尚瑨, 邰能灵, 刘琦, 等. 采用区间控制的蓄电池储能电站调峰运行控制策略[J]. 电工技术学报, 2015, 30(16): 221-229. Shang Jin, Tai Nengling, Liu Qi, et al.Load shifting scheme of battery energy storage system based on interval controlling[J]. Transactions of China Electrotechnical Society, 2015, 30(16): 221-229. [9] 王萧博, 黄文焘, 邰能灵, 等. 一种源-荷-储协同的电热微网联络线功率平滑策略[J]. 电工技术学报, 2020, 35(13): 2817-2829. Wang Xiaobo, Huang Wentao, Tai Nengling, et al.A tie-line power smoothing strategy for microgrid with heat and power system using source-load-storage coordination control[J]. Transactions of China Electrotechnical Society, 2020, 35(13): 2817-2829. [10] 麻秀范, 陈静, 余思雨, 等. 计及容量市场的用户侧储能优化配置研究[J]. 电工技术学报, 2020, 35(19): 4028-4037. Ma Xiufan, Chen Jing, Yu Siyu, et al.Research on user side energy storage optimization configuration considering capacity market[J]. Transactions of China Electrotechnical Society, 2020, 35(19): 4028-4037. [11] 李军徽, 张嘉辉, 李翠萍, 等. 参与调峰的储能系统配置方案及经济性分析[J]. 电工技术学报, 2021, 36(19): 4148-4160. Li Junhui, Zhang Jiahui, Li Cuiping, et al.Configuration scheme and economic analysis of energy storage system participating in grid peak shaving[J]. Transactions of China Electrotechnical Society, 2021, 36(19): 4148-4160. [12] 李铁, 李正文, 杨俊友, 等. 计及调峰主动性的风光水火储多能系统互补协调优化调度[J]. 电网技术, 2020, 44(10): 3622-3630. Li Tie, Li Zhengwen, Yang Junyou, et al.Coordination and optimal scheduling of multi-energy complementary system considering peak regulation initiative[J]. Power System Technology, 2020, 44(10): 3622-3630. [13] 崔杨, 周慧娟, 仲悟之, 等. 考虑广义储能与火电联合调峰的日前-日内两阶段滚动优化调度[J]. 电网技术, 2021, 45(1): 10-20. Cui Yang, Zhou Huijuan, Zhong Wuzhi, et al.Two-stage day-ahead and intra-day rolling optimization scheduling considering joint peak regulation of generalized energy storage and thermal power[J]. Power System Technology, 2021, 45(1): 10-20. [14] 李军徽, 张嘉辉, 穆钢, 等. 储能辅助火电机组深度调峰的分层优化调度[J]. 电网技术, 2019, 43(11): 3961-3970. Li Junhui, Zhang Jiahui, Mu Gang, et al.Hierarchical optimization scheduling of deep peak shaving for energy-storage auxiliary thermal power generating units[J]. Power System Technology, 2019, 43(11): 3961-3970. [15] 史普鑫, 史沛然, 王佩雯, 等. 华北区域电力调峰辅助服务市场分析与运行评估[J]. 电力系统自动化, 2021, 45(20): 175-184. Shi Puxin, Shi Peiran, Wang Peiwen, et al.Analysis and operation evaluation of power peak-shaving ancillary service market in North China[J]. Automation of Electric Power Systems, 2021, 45(20): 175-184. [16] 索瑞鸿, 陈杏, 宋依群, 等. 计及源荷双边性能指标的市场交易模型[J]. 电力自动化设备, 2019, 39(2): 173-180. Suo Ruihong, Chen Xing, Song Yiqun, et al.Trading model considering bilateral performance indexes of generation and load[J]. Electric Power Automation Equipment, 2019, 39(2): 173-180. [17] 韩小齐, 刘文颖, 庞清仑, 等. 考虑日前现货市场风险的电力负荷参与系统调峰控制模型[J]. 电力系统保护与控制, 2022, 50(17): 55-67. Han Xiaoqi, Liu Wenying, Pang Qinglun, et al.Peak shaving control model of power load participation system considering day-ahead spot market risk[J]. Power System Protection and Control, 2022, 50(17): 55-67. [18] 任景, 薛晨, 马晓伟, 等. 源荷联动调峰辅助服务市场两阶段模型[J]. 电力系统自动化, 2021, 45(18): 94-102. Ren Jing, Xue Chen, Ma Xiaowei, et al.Two-stage model of peak regulation ancillary service market with source-load interaction[J]. Automation of Electric Power Systems, 2021, 45(18): 94-102. [19] 罗桓桓, 程中林, 孙婧卓, 等. 储热参与调峰辅助集中交易市场模式及优化认购模型[J]. 电力系统自动化, 2019, 43(24): 187-193. Luo Huanhuan, Cheng Zhonglin, Sun Jingzhuo, et al.Market mode and optimal subscription model of peak regulation auxiliary centralized trading with heat storage[J]. Automation of Electric Power Systems, 2019, 43(24): 187-193. [20] 孙辉, 范轩轩, 胡姝博, 等. 虚拟电厂参与日前电力市场的内外协调竞标策略[J]. 电网技术, 2022, 46(4): 1248-1262. Sun Hui, Fan Xuanxuan, Hu Shubo, et al.Internal and external coordination bidding strategy of virtual power plant participating in day-ahead power market[J]. Power System Technology, 2022, 46(4): 1248-1262. [21] 张明理, 张娜, 武志锴, 等. 日前电能市场与深度调峰市场联合出清模型[J]. 中国电力, 2022, 55(2): 138-144. Zhang Mingli, Zhang Na, Wu Zhikai, et al.Joint clearing model of day-ahead energy market and down regulation service market for accommodation of renewable energy[J]. Electric Power, 2022, 55(2): 138-144. [22] 田亮, 谢云磊, 周桂平, 等. 基于两阶段随机规划的热电机组深调峰辅助服务竞价策略[J]. 电网技术, 2019, 43(8): 2789-2798. Tian Liang, Xie Yunlei, Zhou Guiping, et al.Deep peak regulation ancillary service bidding strategy for CHP units based on two-stage stochastic programming[J]. Power System Technology, 2019, 43(8): 2789-2798. [23] 徐帆, 葛朝强, 吴鑫, 等. 区域电网省间调峰辅助服务的市场机制与出清模型[J]. 电力系统自动化, 2019, 43(16): 109-115. Xu Fan, Ge Zhaoqiang, Wu Xin, et al.Market mechanism and clearing model of inter-provincial peak regulation ancillary service for regional power grid[J]. Automation of Electric Power Systems, 2019, 43(16): 109-115. [24] 罗桓桓, 王昊, 葛维春, 等. 考虑报价监管的动态调峰辅助服务市场竞价机制设计[J]. 电工技术学报, 2021, 36(9): 1935-1947, 1955. Luo Huanhuan, Wang Hao, Ge Weichun, et al.Design of dynamic peak regulation ancillary service market bidding mechanism considering quotation supervision[J]. Transactions of China Electrotechnical Society, 2021, 36(9): 1935-1947, 1955. [25] 叶泽, 李湘旗, 姜飞, 等. 考虑最优弃能率的风光火储联合系统分层优化经济调度[J]. 电网技术, 2021, 45(6): 2270-2280. Ye Ze, Li Xiangqi, Jiang Fei, et al.Hierarchical optimization economic dispatching of combined wind-PV-thermal-energy storage system considering the optimal energy abandonment rate[J]. Power System Technology, 2021, 45(6): 2270-2280.
2023, Vol. 38 
