SONG Zhihui;TIAN Junjian;NI Zhanshi;LIN Qizhao;

• 1:School of Information Engineering
• 2:Guizhou Open University(Guizhou Vocational Technology Institute)
• 3:Department of Thermal Science and Energy Engineering
• 4:University of Science and Technology of China

Abstract：

The combined dispatching and operation of wind-solar-thermal-storage is an important path to help the thermal power industry achieve carbon peaking and carbon neutrality goals. In order to cope with the impact of renewable energy output uncertainty on the power system, a set of uncertain parameters of wind power and photovoltaic power output was constructed to minimize the total operating cost as the optimization goal, and a two-stage robust optimization model was established to optimize the scheduling of the combined wind-solar-thermal-storage system. The uncertainty optimization problem was decoupled into a first stage involving deterministic parameters and a second stage involving uncertain variables. In the first stage, the start-up and shutdown state of thermal power units and charging and discharging state of energy storage equipment were solved based on the predicted output of renewable energy. In the second stage, as a flexible regulation stage, the output power of each equipment under the worst scenario after disturbance occurs was solved, and the column constraint generation algorithm was used to calculate with examples. The results show that the model can effectively smooth the net load fluctuation and relieve the peak load pressure of thermal power units through reasonable energy abandonment and energy storage. Compared with the deterministic optimization model, the increase in operating cost obtained from the solution of the uncertainty optimization model indicates that the robust optimization considering the uncertainty of renewable energy has a higher conservative degree. At the same time, the greater the deviation of renewable energy output, the smaller the increase in operating cost compared with the deterministic optimization, effectively reducing the interference of renewable energy output deviation on system economy.

Key Words： wind-solar-thermal-storage;coal-fired power generation;carbon emission;two-stage;robust optimization;operation

Abstract:

Keywords:

Foundation: 国家重点研发计划资助项目(2021YFF0601000);; 2024年度贵州开放大学(贵州职业技术学院)、贵州远程教育基地、贵州远程教育学会课题资助项目(2024ZD04)

Authors: SONG Zhihui;TIAN Junjian;NI Zhanshi;LIN Qizhao;

DOI: 10.13226/j.issn.1006-6772.LC24021901

References：

• [1] 李咸善，杨拯，李飞，等.基于梯级水电调节的风光水联盟与区域电网联合运行优化调度策略[J].中国电机工程学报，2023,43(6):2234-2248.LI Xianshan,YANG Zheng,LI Fei,et al.Optimization scheduling strategy for joint operation of wind-solar-water power alliance and regional power grid based on cascade hydropower regulation[J].Proceedings of the CSEE,2023,43(6):2234-2248.
• [2] 王瑞林，孙杰，洪慧.可再生能源与燃煤发电集成互补系统综述[J].洁净煤技术，2022,28(11):10-18,4.WANG Ruilin,SUN Jie,HONG Hui.Review on integration of renewable energy and coal-fired power generation[J].Clean Coal Technology,2022,28(11):10-18,4.
• [3] 国家发展改革委.国家能源局关于推进电力源网荷储一体化和多能互补发展的指导意见[EB/OL].[2024-02-10].https://www.ndrc.gov.cn/xxgk/zcfb/ghxwj/202103/t20210305_1269046.html.
• [4] 宋妍萌，芮钧，赵宇.风光水火储多能互补双层优化调度研究[J].中国农村水利水电，2024(3):34-40,49.SONG Yanmeng,RUI Jun,ZHAO Yu.Research on bi-Level optimal scheduling of wind-PV-hydro-thermal-storage multi-energy complementary systems[J].China Rural Water and Hydropower,2024(3):34-40,49.
• [5] 陈奥洁，周云海，石亮波，等.考虑需求响应和含储火电参与深度调峰的电力系统随机优化调度[J].科学技术与工程，2023,23(3):1087-1095.CHEN Aojie,ZHOU Yunhai,SHI Liangbo,et al.Stochastic optimal scheduling of power system considering demand response and participation of thermal power with storage in deep peak shaving[J].Science Technology and Engineering,2023,23(3):1087-1095.
• [6] 吕海鹏，希望·阿不都瓦依提，孟令鹏.计及源-荷预测不确定性的微电网双级随机优化调度[J].电力自动化设备，2022,42(9):70-78.LYU Haipeng,XIWANG·Abuduwayiti,MENG Lingpeng.Two-level stochastic optimal scheduling of microgrid considering uncertainty of source-load prediction[J].Electric Power Automation Equipment,2022,42(9):70-78.
• [7] 易琛，任建文，戚建文.考虑需求响应的风电消纳模糊优化调度研究[J].电力建设，2017,38(4):127-134.YI Chen,REN Jianwen,QI Jianwen.Fuzzy optimal dispatch of wind power consumption considering demand response[J].Electric Power Construction,2017,38(4):127-134.
• [8] CHEN L M,TANG H L,WU J K,et al.A robust optimization framework for energy management of CCHP users with integrated demand response in electricity market[J].International Journal of Electrical Power & Energy Systems,2022,141:108181.
• [9] 崔杨，周慧娟，仲悟之，等.考虑源荷两侧不确定性的含风电电力系统低碳调度[J].电力自动化设备，2020,40(11):85-93.CUI Yang,ZHOU Huijuan,ZHONG Wuzhi,et al.Low-carbon scheduling of power system with wind power considering uncertainty of both source and load sides[J].Electric Power Automation Equipment,2020,40(11):85-93.
• [10] 李志伟，赵书强，刘金山.基于相关机会目标规划的电力系统优化调度研究[J].中国电机工程学报，2019,39(10):2803-2816.LI Zhiwei,ZHAO Shuqiang,LIU Jinshan.Optimal scheduling of power system based on dependent-chance goal programming[J].Proceedings of the CSEE,2019,39(10):2803-2816.
• [11] 刘兴华，耿晨，谢胜寒，等.考虑光伏发电不确定性的日前火电-光伏经济调度[J].系统仿真学报，2022,34(8):1874-1884.LIU Xinghua,GENG Chen,XIE Shenghan,et al.Day ahead thermal-photovoltaic economic dispatch considering uncertainty of photovoltaic power generation[J].Journal of System Simulation,2022,34(8):1874-1884.
• [12] 李长宇，唐文秀.基于数据驱动的多微电网互联系统分布鲁棒运行优化[J].智慧电力，2022,50(5):1-8.LI Changyu,TANG Wenxiu.Distributed robust operation optimization of multi-microgrid interconnection system based on data driven[J].Smart Power,2022,50(5):1-8.
• [13] 黄勤坤，邱瑜，王飞，等.考虑多重不确定性的虚拟电厂随机优化调度[J].电网与清洁能源，2022,38(11):8-16,26.HUANG Qinkun,QIU Yu,WANG Fei,et al.Stochastic optimal scheduling of virtual power plants considering multiple uncertainties[J].Power System and Clean Energy,2022,38(11):8-16,26.
• [14] WANG L,LI Q,SUN M,et al.Robust optimisation scheduling of cchp systems with multi-energy based on minimax regret criterion[J].Institution of Engineeing and Technology,2016,10:2194-2201.
• [15] 彭春华，谢鹏，詹骥文，等.基于改进细菌觅食算法的微网鲁棒经济调度[J].电网技术，2014,38(9):2392-2398.PENG Chunhua,XIE Peng,ZHAN Jiwen,et al.Robust economic dspatch of microgrid using improved bacterial foraging algorithm[J].Power System Technology,2014,38(9):2392-2398.
• [16] 于丹文，杨明，翟鹤峰，等.鲁棒优化在电力系统调度决策中的应用研究综述[J].电力系统自动化，2016,40(7):134-143,148.YU Danwen,YANG Ming,ZHAI Hefeng,et al.An overview of robust optimization used for power system dispatch and decision-making[J].Automation of Electric Power Systems,2016,40(7):134-143,148.
• [17] AGHAMOHAMADI M,MAHMOUDI A.From bidding strategy in smart grid toward integrated bidding strategy in smart multi-energy systems,an adaptive robust solution approach[J].Energy,2019,183:75-91.
• [18] 林俐，田欣雨.基于火电机组分级深度调峰的电力系统经济调度及效益分析[J].电网技术，2017,41(7):2255-2263.LIN Li,TIAN Xinyu.Analysis of deep peak regulation and its benefit of thermal units in power system with large scale wind power integrated[J].Power System Technology,2017,41(7):2255-2263.
• [19] 张保衡.调峰机组热应力及疲劳寿命[J].中国电机工程学报，1986,6(2):3-15.ZHANG Baoheng.Thermal stress and life expenditure of steam turbine eotor for cycling service[J].Proceedings of the CSEE,1986,6(2):3-15.
• [20] ROSEWATER D M,COPP D A,NGUYEN T A,et al.Battery energy storage models for optimal control[J].IEEE Access,2019,7:178357-178391.
• [21] ABDI H,MOHAMMADI-IVATLOO B,JAVADI S,et al.Ene-rgy storage systems[M]//Distributed generation systems.Amsterdam:Elsevier,2017:333-368.
• [22] BERTSIMAS D,SIM M.The price of robustness[J].Operation Research,2004,52(1):95-122.
• [23] 朱嘉远，刘洋，许立雄，等.考虑风电消纳的热电联供型微网日前鲁棒经济调度[J].电力系统自动化，2019,43(4):40-48.ZHU Jiayuan,LIU Yang,XU Lixiong,et al.Robust day-ahead economic dispatch of microgrid with combined heat and power system considering wind power accommodation[J].Automation of Electric Power Systems,2019,43(4):40-48.
• [24] 陈灵敏.用户能源系统优化配置与运行策略研究[D].广州：广东工业大学，2021.
• [25] 光伏发电站功率预测系统技术要求[R].北京：中国电力企业联合会，2013.
• [26] 李雄威，王昕，徐家豪，等.考虑火电深度调峰的风光火储系统分层优化调度模型[J].油气与新能源，2023,35(6):74-81.LI Xiongwei,WANG Xin,XU Jiahao,et al.A hierarchical optimal scheduling model of wind-photovoltaic-thermal-energy storage system considering deep peak shaving of thermal power[J].Petroleum and New Energy,2023,35(6):74-81.
• [27] 卢沛.基于新能源最优消纳率与需求响应的风光水火储多能互补优化调度[D].西安：西安理工大学，2024.
• [28] 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.