基于演变虚拟净负荷的新型电力系统日前优化调度

肖白, 于海洋, 焦明曦, 王大亮, 张大弛, 姚狄, 辛昊阔

电力建设 ›› 2025

PDF(688 KB)
PDF(688 KB)
电力建设 ›› 2025

基于演变虚拟净负荷的新型电力系统日前优化调度

  • 肖白1, 于海洋1, 焦明曦2, 王大亮2, 张大弛3, 姚狄3, 辛昊阔3
作者信息 +

Day-ahead Optimal Dispatch of New Power System Based on Evolving Virtual Net Load

  • XIAO Bai1, YU Haiyang1, JIAO Mingxi2, WANG Daliang2, ZHANG Dachi3, YAO Di3, XIN Haokuo3
Author information +
文章历史 +

摘要

【目的】针对新型电力系统中源荷不确定性给制定调度计划带来的不利影响,以及全额保障性收购可再生能源电量的消纳问题,提出一种基于演变虚拟净负荷的新型电力系统日前优化调度方法。【方法】首先,利用Informer模型对风光出力和负荷的时间序列进行场景预测。然后,在虚拟净负荷基础上定义了演变虚拟净负荷,并计算电力系统中的演变虚拟净负荷。最后,考虑系统的运行特性,以保障性收购可再生能源电量为基础,以包含各机组运行成本和碳排放成本在内的系统总成本最小为目标,以系统灵活性约束条件反映源荷不确定性的需求,建立基于演变虚拟净负荷的新型电力系统日前优化调度模型。【结果】通过实例分析表明,与其它调度方法相比,所提方法能有效提高系统应对源荷不确定性波动的能力,降低碳排放成本和促进可再生能源发电项目上网电量的消纳。【结论】所提方法能够同时兼顾可再生能源上网电量保障性收购与市场化竞价激励,平衡政策要求与企业经济性需求;且在保障系统安全运行的同时,通过优化机组发电成本与碳收益,能够实现经济性与低碳性的双重提升。

Abstract

[Objective] Aiming at the adverse effects of source-load uncertainty in the new power system on the formulation of scheduling plans and the consumption of renewable energy power in full-guaranteed acquisition, this paper introduces a day-ahead optimal dispatch method that is founded on the concept of evolving virtual net load. [Methods] Firstly, the Informer model is used to generate the time series of wind power and load. Then, the evolution virtual net load is defined on the basis of the virtual net load, and the evolution virtual net load in the power system is calculated. Finally, considering the operating characteristics of the system, based on the guaranteed acquisition of renewable energy power, with the goal of minimizing the total system cost including the operating cost and carbon emission cost of each unit, the system flexibility constraint condition is used to reflect the demand of source-load uncertainty, and a new day-ahead optimal scheduling model of power system based on evolutionary virtual net load is established. [Results] The actual example analysis shows that compared with other scheduling models, the proposed method can effectively improve the system's ability to cope with source-load uncertainty fluctuations, reduce carbon emission costs and promote the consumption of on-grid electricity for renewable energy power generation projects. [Conclusions] The proposed method can balance the policy requirements and the economic needs of enterprises by taking into account both the guaranteed purchase of renewable energy online electricity and the market-oriented bidding incentives. While ensuring the safe operation of the system, the dual improvement of economy and low carbon can be achieved by optimizing the power generation cost and carbon income of the unit.

关键词

新型电力系统 / 全额保障性收购可再生能源电量 / Informer / 演变虚拟净负荷 / 日前优化调度 / 源荷不确定性 / 灵活性

Key words

new power system / full security acquisition of renewable energy power / Informer / evolving virtual net load / day-ahead optimal dispatching / source-load uncertainty / flexibility

引用本文

导出引用
肖白, 于海洋, 焦明曦, 王大亮, 张大弛, 姚狄, 辛昊阔. 基于演变虚拟净负荷的新型电力系统日前优化调度[J]. 电力建设. 2025
XIAO Bai, YU Haiyang, JIAO Mingxi, WANG Daliang, ZHANG Dachi, YAO Di, XIN Haokuo. Day-ahead Optimal Dispatch of New Power System Based on Evolving Virtual Net Load[J]. Electric Power Construction. 2025
中图分类号: TM73   

参考文献

[1] 康重庆, 杜尔顺, 郭鸿业, 等. 新型电力系统的六要素分析[J]. 电网技术, 2023, 47(5): 1741-1750.
KANG Chongqing, DU Ershun, GUO Hongye, et al.Primary exploration of six essential factors in new power system[J]. Power System Technology, 2023, 47(5): 1741-1750.
[2] 黄河, 王建学, 肖云鹏, 等. 新型电力系统电力电量平衡分析关键技术与研究框架[J]. 电力建设, 2024, 45(9): 1-12.
HUANG He, WANG Jianxue, XIAO Yunpeng, et al.Key technologies and research framework for the power and energy balance analysis in new-type power systems[J]. Electric Power Construction, 2024, 45(9): 1-12.
[3] 李浩然, 姚方, 宋显锦. 计及源荷不确定性的综合能源系统协同优化策略[J]. 分布式能源, 2024, 9(5): 32-40.
LI Haoran, YAO Fang, SONG Xianjin.Collaborative optimization strategy for integrated energy system considering uncertainties in source and load[J]. Distributed Energy, 2024, 9(5): 32-40.
[4] 南斌, 姜春娣, 董树锋, 等. 计及源荷不确定性的综合能源系统日期-日内协调优化调度[J]. 电网技术, 2023, 47(9): 3669-3683.
NAN Bin, JIANG Chundi, DONG Shufeng, et al.Day-ahead and intra-day coordinated optimal scheduling of integrated energy system considering uncertainties in source and load[J]. Power System Technology, 2023, 47(9): 3669-3683.
[5] Xiao Bai, Wang Jialiang, Xiao Zhiwen, et al.Power source flexibility margin quantification method for multi-energy power systems based on blind number theory[J]. CSEE Journal of Power and Energy Systems, 2023, 9(6): 2321-2331.
[6] 国家发展改革委. 全额保障性收购可再生能源电量监管办法[EB/OL]. (2024-03-18) [2024-09-09]. https://www.ndrc.gov.cn/xxgk/zcfb/fzggwl/202403/t20240315_1364966.html.
National Development and Reform Commission. Regulatory measures on the full guaranteed purchase of renewable energy electricity[EB/OL]. (2024-03-18) [2024-09-09]. https://www.ndrc.gov.cn/xxgk/zcfb/fzggwl/202403/t20240315_1364966.html.
[7] 张妍, 冷媛, 尚楠, 等. 考虑碳排放需求响应及碳交易的电力系统双层优化调度[J]. 电力建设, 2024, 45(5): 94-104.
ZHANG Yan, LENG Yuan, SHANG Nan, et al.Bi-level optimal scheduling of power system considering carbon demand response and carbon trading[J]. Electric Power Construction, 2024, 45(5): 94-104.
[8] 闫振靖, 李皓然, 杨欣可, 等. 基于不确定性分析与电价波动的电-氢-热综合能源系统分析[J]. 高压电器, 2024, 60(7): 69-77.
YAN Zhenjing, LI Haoran, YANG Xinke, et al.Analysis of electric-hydrogen-thermal integrated energy system based on uncertainty analysis and electricity tariff fluctuation[J]. High Voltage Apparatus, 2024, 60(7): 69-77.
[9] 刘海涛, 仲聪, 马佳伊, 等. 考虑条件风险价值和阶梯碳交易的综合能源系统优化调度[J]. 电测与仪表, 2024, 61(4): 100-108.
LIU Haitao, ZHONG Cong, MA Jiayi, et al.Optimal dispatching of integrated energy system considering conditional value at risk and ladder carbon trading[J]. Electrical Measurement & Instrumentation, 2024, 61(4): 100-108.
[10] 李娟, 王玲, 孙康杰, 等. 考虑风电不确定性和有功无功联合调整的两阶段优化调度[J]. 东北电力大学学报, 2023, 43(3): 72-81.
LI Juan, WANG Ling, SUN Kangjie, et al.Two-stage optimal dispatch considering uncertainty of wind power and joint regulaiton of active and reactive power[J]. Journal of Northeast Electric Power University, 2023, 43(3): 72-81.
[11] 鲁肖龙, 潘淼, 鞠立伟, 等. 考虑碳捕集和电转气的热电联合虚拟电厂调度优化模型[J]. 电力建设, 2023, 44(8): 107-117.
LU Xiaolong, PAN Miao, JU Liwei, et al.Dispatching optimization model of combined heat and power virtual power plant considering carbon capture and power-to-gas[J]. Electric Power Construction, 2023, 44(8): 107-117.
[12] 潘崇超, 侯孝旺, 金泰, 等. 计及阶梯碳交易和可再生能源不确定性的综合能源系统低碳研究[J]. 电测与仪表, 2024, 61(10): 8-16.
PAN Chongchao, HOU Xiaowang, JIN Tai, et al.Low carbon research on integrated energy system considering the tiered carbon trading and the uncertainties of renewable energy[J]. Electrical Measurement & Instrumentation, 2024, 61(10): 8-16.
[13] 杨迪, 吕云彤, 冀明, 等. 考虑售电合作商投资共享储能的光伏消纳研究[J]. 供用电, 2024, 41(11): 105-113.
YANG Di, LÜ Yuntong, JI Ming, et al.Research on PV consumption considering electric energy sales partner-owned investing in share enery storage[J]. Distribution & Utilization, 2024, 41(11): 105-113.
[14] 马文祚, 夏周武. 考虑新能源不确定性的电网运营商多时间尺度鲁棒交易[J]. 山东电力技术, 2024, 51(8): 49-58.
MA Wenzuo, XIA Zhouwu.Multi-time scale robust trading of power grid operators considering new energy uncertainty[J]. Shandong Electric Power, 2024, 51(8): 49-58.
[15] 吕小红, 刘维, 刘克恒, 等. 虚拟电厂供需侧双层协调自适应鲁棒优化调度[J]. 全球能源互联网, 2024, 7(4): 431-442.
LYU Xiaohong, LIU Wei, LIU Keheng, et al.Two-layer coordinated adaptive robust optimal scheduling on supply and demand side of virtual power plant[J]. Journal of Global Energy Interconnection, 2024, 7(4): 431-442.
[16] 许青, 张龄之, 梁琛, 等. 基于联合时序场景和改进TCN的高比例新能源电网负荷预测[J]. 广东电力, 2024, 37(1): 1-7.
XU Qing, ZHANG Lingzhi, LIANG Chen, et al.Load forecasting of high proportion new energy grid based on joint time series scenario and improved TCN[J]. Guangdong Electric Power, 2024, 37(1): 1-7.
[17] WANG Qianfan, GUAN Yangpei, WANG Jianhui.A chance-constrained two-stage stochastic program for unitcommitment with uncertain wind power output[J]. IEEE transactions on Power Systems, 2012, 27(1): 206-215.
[18] 刘德伟, 郭剑波, 黄越辉, 等. 基于风电功率概率预测和运行风险约束的含风电场电力系统动态经济调度[J]. 中国电机工程学报, 2013, 33(16): 9-15.
LIU Dewei, GUO Jianbo, HUANG Yuehui, et al.Dynamic economic dispatch of wind integrated power system based on wind power probabilistic forecasting and operation risk constraints[J]. Proceedings of the CSEE, 2013, 33(16): 9-15.
[19] QADRDAN M, WU J, JENKINS N, et al.Operating strategies for a GB integrated gas and electricity network considering the uncertainty in wind power forecasts[J]. IEEE Transactions on Sustainable Energy, 2014, 5(1): 128-138.
[20] 杨贤东, 袁旭峰, 熊炜, 等. 考虑源荷不确定性的风光火储系统低碳经济调度[J]. 智慧电力, 2022, 50(8): 22-29, 53.
YANG Xiandong, YUAN Xufeng, XIONG Wei, et al.Low-carbon economic dispatch of wind-solar-fired-storage system considering source-load uncertainty[J]. Smart Power, 2022, 50(8): 22-29, 53.
[21] 李雪玲, 刘洋, 李振伟, 等. 基于气象分型改进构造不确定集的多微网低碳鲁棒经济调度[J]. 电力建设, 2023, 44(8): 142-156.
LI Xueling, LIU Yang, LI Zhenwei, et al.Robust low-carbon economic dispatch of multiple microgrids based on improved uncertainty set of meteorological classification[J]. Electric Power Construction, 2023, 44(8): 142-156.
[22] 刘一欣, 郭力, 王成山. 微电网两阶段鲁棒优化经济调度方法[J]. 中国电机工程学报, 2018, 38(14): 4013-4022.
LIU Yixin, GUO Li, WANG Chengshan.Economic dispatch of microgrid based on two stage robust optimization[J]. Proceedings of the CSEE, 2018, 38(14): 4013-4022.
[23] LI J H, ZHOU S, XU Y F, et al.A multi-band uncertainty set robust method for unit commitment with wind power generation[J]. International Journal of Electrical Power & Energy Systems, 2021, 131: 107125.
[24] 崔扬, 郭福音, 仲悟之, 等. 多重不确定性环境下的综合能源系统区间多目标优化调度[J]. 电网技术, 2022, 46(8): 2964-2974.
CUI Yang, GUO Fuyin, ZHONG Wuzhi, et al.Interval multi-objective optimal dispatch of integrated energy system under multiple uncertainty environment[J]. Power System Technology, 2022, 46(8): 2964-2974.
[25] 黎静华, 谢育天, 曾鸿宇, 等. 不确定优化调度研究综述及其在新型电力系统中的应用探讨[J]. 高电压技术, 2022, 48(9): 3447-3464.
LI Jinghua, XIE Yutian, ZENG Hongyu, et al.Research review of uncertain optimal scheduling and its application in new-type power systems[J]. High Voltage Engineering, 2022, 48(9): 3447-3464.
[26] 朱庆, 郑红娟, 唐子逸, 等. 基于生成对抗网络的综合能源负荷场景生成方法[J]. 电力建设, 2021, 42(12): 1-8.
ZHU Qing, ZHENG Hongjuan, TANG Ziyi, et al.Load scenario generation of integrated energy system using generative adversarial networks[J]. Electric Power Construction, 2021, 42(12): 1-8.
[27] 肖白, 张博, 王辛玮, 等. 基于组合模态分解和深度学习的短期风电功率区间预测[J]. 电力系统自动化, 2023, 47(17): 110-117.
XIAO Bai, ZHANG Bo, WANG Xinwei, et al.Short-term wind power interval prediction based on combined mode decomposition and deep learning[J]. Automation of Electric Power Systems, 2023, 47(17): 110-117.
[28] CHEN Yize, WANG Yishen, KIRSCHEN D, et al.Model-free renewable scenario generation using generative adversarial networks[J]. IEEE transactions on Power Systems, 2018, 33(3): 3265-3275.
[29] 顾洁, 刘书琪, 胡玉, 等. 基于深度卷积生成对抗网络场景生成的间歇式分布式电源优化配置[J]. 电网技术, 2021, 45(5): 1742-1751.
GU Jie, LIU Shuqi, HU Yu, et al.Optimal allocation of intermittent distributed generation based on deep convolutions generative adversarial network in scenario generation[J]. Power System Technology, 2021, 45(5): 1742-1751.
[30] 骆钊, 吴谕侯, 朱家祥, 等. 基于多尺度时间序列块自编码Transformer神经网络模型的风电超短期功率预测[J]. 电网技术, 2023, 47(9): 3527-3537.
LUO Zhao, WU Yuhou, ZHU Jiaxiangi, et al.Wind power forecasting based on multi-scale time series block auto-encoder Transformer neural network model[J]. Power System Technology, 2023, 47(9): 3527-3537.
[31] 石卓见, 冉启武, 徐福聪. 基于聚合二次模态分解及Informer的短期负荷预测[J]. 电网技术, 2024, 48(6): 2574-2583.
SHI Zhuojian, RAN Qiwu, XU Fucong.Short-term load forecasting based on aggregated secondary decomposition and Informer[J]. Power System Technology, 2023, 45(6): 2574-2583.
[32] 童宇轩, 胡俊杰, 刘雪涛, 等. 新能源电力系统灵活性供需量化及分布鲁棒优化调度[J]. 电力系统自动化, 2023, 47(15): 80-90.
TONG Yuxuan, HU Junjie, LIU Xutao, et al.Quantification of flexibility supply and demand and distributionally robust optimal dispatch of renewable energy dominated power systems[J]. Automation of Electric Power Systems, 2023, 47(15): 80-90.
[33] 何奇, 张宇, 邓玲, 等. 基于水电储能调节的风光水发电联合优化调度策略[J]. 广东电力, 2024, 37(3): 12-24.
HE Qi, ZHANG Yu, DENG Ling, et al.Joint optimal scheduling strategy of wind, photovoltaic and water storage power generation considering hydropower storage regulation[J]. Guangdong Electric Power, 2024, 37(3): 12-24.
[34] 王佳蕊, 孙勇, 胡枭, 等. 基于MICP的多能耦合综合能源系统可再生能源消纳能力研究[J]. 电力建设, 2023, 44(8): 157-170.
WANG Jiarui, SUN Yong, HU Xiao, et al.Research on renewable energy absorption capacity of multi-energy coupling integrated energy systems based on MICP[J]. Electric Power Construction, 2023, 44(8): 157-170.
[35] 肖白, 于龙泽, 刘洪波, 等. 基于生成虚拟净负荷的多能源电力系统日前优化调度[J]. 中国电机工程学报, 2021, 41(21): 7237-7248.
XIAO Bai, YU Longze, LIU Hongbo, et al.Day ahead optimal dispatch of multi-energy power system based on generating virtual net load[J]. Proceedings of the CSEE, 2021, 41(21): 7237-7248.
[36] 尚文强, 李广磊, 丁月明, 等. 考虑源荷不确定性和新能源消纳的综合能源系统协同调度方法[J]. 电网技术, 2024, 48(2): 517-532.
SHANG Wenqiang, LI Guanglei, DING Yueming, et al.Collaborative scheduling for integrated energy system considering uncertainty of source load and absorption of new energy[J]. Power System Technology, 2024, 48(2): 517-532.
[37] 张宁, 朱昊, 杨凌霄, 等. 考虑可再生能源消纳的多能互补虚拟电厂优化调度策略[J]. 发电技术, 2023, 44(5): 625-633.
ZHANG Ning, ZHU Hao, YANG Lingxiao, et al.Optimal scheduling strategy of multi-energy complementary virtual power plant considering renewable energy consumption[J]. Power Generation Technology, 2023, 44(5): 625-633.
[38] 王千淳, 杜欣慧, 吴莹莹, 等. 考虑碳交易的多能互补虚拟电厂优化调度运行策略[J]. 电测与仪表, 2024, 61(11): 22-30.
WANG Qianchun, DU Xinhui, WU Yingying, et al.Optimal dispatching operation strategy of multi-energy complementary virtual power plant considering carbon trading[J]. Electrical Measurement & Instrumentation, 2024, 61(11): 22-30.
[39] ZHOU Haoyi, ZHANG Shanghang, PENG Jieqi, et al.Informer: Beyond efficient transformer for long sequence time-series forecasting[C]//Proceedings of the AAAI conference on artificial intelligence, 2021, 35(12): 11106-11115.
[40] 国家发展改革委, 国家能源局. 关于2024年可再生能源电力消纳责任权重及有关事项的通知[EB/OL]. (2024-08-02) [2024-09-09]. https://www.ndrc.gov.cn/xwdt/tzgg/202408/t20240802_1392178.html.
National Development and Reform Commission, National Energy Administration. Notice on the weight of responsibility for renewable energy power consumption and related matters in2024[EB/OL]. (2024-08-02)
41 [2024-09-09]. https://www.ndrc.gov.cn/xwdt/tzgg/202408/t20240802_1392178.html.
[41] 廖望, 刘东, 巫宇锋, 等. 考虑源荷不确定性及用户响应行为的电力系统低碳经济调度[J]. 中国电机工程学报, 2024, 44(3): 905-917.
LIAO Wang, LIU Dong, WU Yufeng, et al.Low-carbon economic dispatch of power system considering source-load uncertainties and users response behavior[J]. Proceedings of the CSEE, 2024, 44(3): 905-917.

基金

国家自然科学基金重点项目(U22B20105); 国家重点研发计划项目(2017YFB0902205); 吉林省产业创新专项基金资助项目(2019C058-7)

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