面向沙戈荒区域新能源消纳的电力系统日前低碳调度策略

李帅虎, 欧阳中, 孙杰懿, 马瑞, 王炜宇

太阳能学报 ›› 2024, Vol. 45 ›› Issue (7) : 82-91.

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太阳能学报 ›› 2024, Vol. 45 ›› Issue (7) : 82-91. DOI: 10.19912/j.0254-0096.tynxb.2023-1861
“新型电力系统中光储规划配置及优化运行技术”专题

面向沙戈荒区域新能源消纳的电力系统日前低碳调度策略

  • 李帅虎1, 欧阳中1, 孙杰懿2, 马瑞1, 王炜宇1
作者信息 +

DAY-AHEAD LOW-CARBON DISPATCHING STRATEGY OF POWER SYSTEM FOR NEW ENERGY CONSUMPTION IN DESERT,GOBI AND DESERTIFICATION LAND

  • Li Shuaihu1, Ouyang Zhong1, Sun Jieyi2, Ma Rui1, Wang Weiyu1
Author information +
文章历史 +

摘要

针对在沙漠、戈壁、荒漠区域的新能源机组面临消纳和经济性差等问题,提出一种面向沙戈荒区域新能源消纳的电力系统日前低碳调度策略。考虑系统结构的复杂性,采用模型分层的优化方案。上层模型以需求响应(DR)调用成本最小和优化负荷与风光预测总值协方差最大为目标,旨在优化用电负荷曲线,释放电网新能源消纳潜力;下层模型通过协调风电机组、光伏机组、储能电站、火电机组以及上层模型得到的优化负荷,同时将阶梯型的碳交易成本引入到目标函数中,建立多目标“源网储荷”协同低碳调度模型,旨在提高系统运行的经济性,降低系统的碳排放量,提高新能源的消纳能力。最后基于改进的IEEE 30节点系统进行仿真测试,结果验证了模型的有效性。

Abstract

A day-ahead low-carbon dispatching strategy of power system for new energy consumption in desert, Gobi and desertification land is proposed to address the issues of poor consumption and economic efficiency of new energy units. Considering the complexity of the system structure, a model layered optimization scheme is adopted. The upper level model aims to optimize the power load curve and release the potential of new energy consumption in the power grid by minimizing the covariance between the optimized load and the total wind forecast value. By coordinating the optimized load of wind turbines, photovoltaic units, energy storage power stations, thermal power units and the upper model, the lower model introduces the carbon transaction cost of the ladder into the objective function, and establishes the multi-objective "source-grid-storage-load" collaborative low-carbon scheduling model, aiming to improve the economy of system operation, reduce the carbon emissions of the system, and improve the absorption capacity of new energy. Finally, simulation tests are carried out on the improved IEEE 30-node system, and the results verify the effectiveness of the model.

关键词

分布式发电 / 储能 / 需求响应 / 沙戈荒区域 / 新能源消纳 / “源网荷储”协同

Key words

distributed power generation / energy storage / demand response / desert / Gobi and desertification land / new energy consumption / "source network load storage" coordination

引用本文

导出引用
李帅虎, 欧阳中, 孙杰懿, 马瑞, 王炜宇. 面向沙戈荒区域新能源消纳的电力系统日前低碳调度策略[J]. 太阳能学报. 2024, 45(7): 82-91 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1861
Li Shuaihu, Ouyang Zhong, Sun Jieyi, Ma Rui, Wang Weiyu. DAY-AHEAD LOW-CARBON DISPATCHING STRATEGY OF POWER SYSTEM FOR NEW ENERGY CONSUMPTION IN DESERT,GOBI AND DESERTIFICATION LAND[J]. Acta Energiae Solaris Sinica. 2024, 45(7): 82-91 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1861
中图分类号: TM734   

参考文献

[1] 雒德宏. 浅谈在“沙戈荒” 大基地开发中推广“新能源+生态治理” 模式存在的难题及建议[J]. 风能, 2022(12): 56-58.
LUO D H.Discussion on the problems and suggestions of popularizing the model of “new energy+ecological governance” in the development of Shagehuang base[J]. Wind energy, 2022(12): 56-58.
[2] 肖玲娟, 蒋海波, 刘长栋. 我国沙戈荒区域新能源外送基地经济性分析[J]. 煤质技术, 2023, 38(1): 21-26.
XIAO L J, JIANG H B, LIU C D.Economic analysis of the new energy export base in the Gobi and desert areas of China[J]. Coal quality technology, 2023, 38(1): 21-26.
[3] 金力, 房鑫炎, 蔡振华, 等. 考虑特性分布的储能电站接入的电网多时间尺度源储荷协调调度策略[J]. 电网技术, 2020, 44(10): 3641-3650.
JIN L, FANG X Y, CAI Z H, et al.Multiple time-scales source-storage-load coordination scheduling strategy of grid connected to energy storage power station considering characteristic distribution[J]. Power system technology, 2020, 44(10): 3641-3650.
[4] 唐杰, 吕林, 叶勇, 等. 多时间尺度下主动配电网源-储-荷协调经济调度[J]. 电力系统保护与控制, 2021, 49(20): 53-64.
TANG J, LYU L, YE Y, et al.Source-storage-load coordinated economic dispatch of an active distribution network under multiple time scales[J]. Power system protection and control, 2021, 49(20): 53-64.
[5] 李强, 赵峰, 刘茂凯, 等. 双碳目标下面向清洁能源消纳的源网荷储协调控制[J]. 自动化与仪表, 2023, 38(7): 19-23.
LI Q, ZHAO F, LIU M K, et al.Coordinated control of source network load and storage towards clean energy consumption under the dual-carbon target[J]. Automation & instrumentation, 2023, 38(7): 19-23.
[6] 姜琦, 黄堃, 赵俊, 等. 基于遗传算法的主动配电网“源网荷储” 协调优化模型研究[J]. 电力与能源, 2020, 41(1): 1-5, 19.
JIANG Q, HUANG K, ZHAO J, et al.Study of “power-network-load-storage” coordinated optimization model for active distribution network based on genetic algorithm[J]. Power & energy, 2020, 41(1): 1-5, 19.
[7] 马燕峰, 范振亚, 刘伟东, 等. 考虑碳权交易和风荷预测误差随机性的环境经济调度[J]. 电网技术, 2016, 40(2): 412-418.
MA Y F, FAN Z Y, LIU W D, et al.Environmental and economic dispatch considering carbon trading credit and randomicity of wind power and load forecast error[J]. Power system technology, 2016, 40(2): 412-418.
[8] 卫志农, 张思德, 孙国强, 等. 基于碳交易机制的电-气互联综合能源系统低碳经济运行[J]. 电力系统自动化, 2016, 40(15): 9-16.
WEI Z N, ZHANG S D, SUN G Q, et al.Carbon trading based low-carbon economic operation for integrated electricity and natural gas energy system[J]. Automation of electric power systems, 2016, 40(15): 9-16.
[9] 安源, 郑申印, 苏瑞, 等. 风光水储多能互补发电系统双层优化研究[J]. 太阳能学报, 2023, 44(12): 510-517.
AN Y, ZHENG S Y, SU R, et al.Research on two-layer optimization of wind-solar-water-storage multi energy complementary power generation system[J]. Acta energiae solaris sinica, 2023, 44(12): 510-517.
[10] 鞠立伟, 于超, 谭忠富. 计及需求响应的风电储能两阶段调度优化模型及求解算法[J]. 电网技术, 2015, 39(5): 1287-1293.
JU L W, YU C, TAN Z F.A two-stage scheduling optimization model and corresponding solving algorithm for power grid containing wind farm and energy storage system considering demand response[J]. Power system technology, 2015, 39(5): 1287-1293.
[11] 张钦, 王锡凡, 王建学, 等. 电力市场下需求响应研究综述[J]. 电力系统自动化, 2008, 32(3): 97-106.
ZHANG Q, WANG X F, WANG J X, et al.Survey of demand response research in deregulated electricity markets[J]. Automation of electric power systems, 2008, 32(3): 97-106.
[12] 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 A J, ZHOU Y H, SHI L B, 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.
[13] 张晓辉, 闫柯柯, 卢志刚, 等. 基于碳交易的含风电系统低碳经济调度[J]. 电网技术, 2013, 37(10): 2697-2704.
ZHANG X H, YAN K K, LU Z G, et al.Carbon trading based low-carbon economic dispatching for power grid integrated with wind power system[J]. Power system technology, 2013, 37(10): 2697-2704.
[14] 王振浩, 许京剑, 田春光, 等. 计及碳交易成本的含风电电力系统热电联合调度[J]. 太阳能学报, 2020, 41(12): 245-253.
WANG Z H, XU J J, TIAN C G, et al.Combined heat and power scheduling strategy considering carbon trading cost in wind power system[J]. Acta energiae solaris sinica, 2020, 41(12): 245-253.
[15] 李旭东, 艾欣, 胡俊杰, 等. 计及碳交易机制的核-火-虚拟电厂三阶段联合调峰策略研究[J]. 电网技术, 2019, 43(7): 2460-2470.
LI X D, AI X, HU J J, et al.Three-stage combined peak regulation strategy for nuclear-thermal-virtual power plant considering carbon trading mechanism[J]. Power system technology, 2019, 43(7): 2460-2470.
[16] 安源, 苏瑞, 郑申印, 等. 计及碳交易和源-荷侧资源的综合能源系统低碳经济优化[J]. 太阳能学报, 2023, 44(11): 547-555.
AN Y, SU R, ZHENG S Y, et al.Low carbon economic optimization of integrated energy system considering carbon trading and source-load side resources[J]. Acta energiae solaris sinica, 2023, 44(11): 547-555.
[17] 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 Y, ZHOU H J, ZHONG W Z, 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.
[18] 周孟然, 王旭, 邵帅, 等. 考虑需求响应和碳排放额度的微电网分层优化调度[J]. 中国电力, 2022, 55(10): 45-53.
ZHOU M R, WANG X, SHAO S, et al.Hierarchical optimal scheduling of microgrid considering demand response and carbon emission quota[J]. Electric power, 2022, 55(10): 45-53.
[19] 包子阳, 余继周, 杨杉. 智能优化算法及其MATLAB实例[M]. 3版. 北京: 电子工业出版社, 2021.
BAO Z Y, YU J Z, YANG S.Intelligent optimization algorithm and its Matlab example[M]. 3rd ed. Beijing: Publishing House of Electronics Industry, 2021.
[20] 何嘉威. 粒子群优化算法改进及其在智能电网经济优化调度应用[D]. 南京: 南京邮电大学, 2022.
HE J W.Improvement of particle swarm optimization algorithm and its application on economic dispatching of smart grid[D]. Nanjing: Nanjing University of Posts and Telecommunications, 2022.

基金

湖南省自然科学基金面上项目(2023JJ30024); 国网湖南省电力公司科技项目(5216A522000Z)

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