新型电力系统与综合能源

考虑经济性与碳排放的电-气综合能源系统多目标规划

展开
  • 1.国网山东省电力公司潍坊供电公司, 山东 潍坊 261000
    2.山东大学 电气工程学院, 济南 250061
    3.丹麦科技大学 电气工程学院,丹麦 灵比 2800
朱海南(1987-),高级工程师,博士,从事电网运行与控制研究;E-mail:hainanzhu@mail.sdu.edu.cn.

收稿日期: 2021-12-16

  修回日期: 2022-01-06

  录用日期: 2022-02-07

  网络出版日期: 2023-01-06

基金资助

国网山东省电力公司科技项目(520604200003);国家重点研发计划(2018YFA0702200)

Multi-Objective Planning of Power-Gas Integrated Energy System Considering Economy and Carbon Emission

Expand
  • 1. State Grid Weifang Power Supply Company, Weifang 261000, Shandong, China
    2. School of Electrical Engineering, Shandong University, Jinan 250061, China
    3. Department of Electrical Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark

Received date: 2021-12-16

  Revised date: 2022-01-06

  Accepted date: 2022-02-07

  Online published: 2023-01-06

摘要

为加速电-气系统快速、经济的低碳转型,构建了一种综合考虑经济性成本与碳排放量的电-气综合能源系统多目标随机优化规划模型.首先建立电-气网络与相关设备的数学模型,并运用场景法表征电、气负荷与光伏出力的不确定性.其次建立综合考虑系统经济性成本和碳排放量两个指标的混合整数二次约束规划(MIQCP)模型,对电网馈线、气网管道、变电站、配气站、燃气机组、电转气装置、光伏及储能装置进行统筹规划.最后,构建算例验证模型的可行性及有效性.结果表明:在不同的目标函数权重选择下,模型可以充分考虑电-气网络线路与多种综合能源设备间的耦合关系,获得整体最优的规划方案.

本文引用格式

朱海南, 王娟娟, 陈兵兵, 张厚望, 陈健, 吴秋伟 . 考虑经济性与碳排放的电-气综合能源系统多目标规划[J]. 上海交通大学学报, 2023 , 57(4) : 422 -431 . DOI: 10.16183/j.cnki.jsjtu.2021.513

Abstract

In order to accelerate the rapid and economic low-carbon transformation of the power-gas system, a multi-objective stochastic optimization programming model for the whole equipment of the power-gas system was established, which comprehensively considered the economic cost and carbon emissions. First, the mathematical model of the electric-gas network and related equipment was established, and the uncertainty characteristics of the electric and gas loads and photovoltaic output were analyzed by using the scenario method. Next, a mixed-integer quadratically constrained programming (MIQCP) model considering the economic cost and carbon emissions of the system was established. An overall planning was made for power feeders, gas network pipelines, substations, gas distribution stations, gas units, power-to-gas devices, photovoltaic, and energy storage devices. Finally, a numerical example was built to verify the feasibility and effectiveness of the model. The results show that the model can fully consider the coupling relationship between power-gas network lines and a variety of comprehensive energy equipment under different weight choices of objective function, and obtain the overall optimal planning scheme.

参考文献

[1] 奚剑明, 吴瀚然. 供给侧改革中资源与能源行业去产能政策效果研究[J]. 工业技术经济, 2021, 40(1): 113-119.
[1] XI Jianming, WU Hanran. Research on the Effect of supply side reform and the de-capacity policy in resource and energy industry[J]. Journal of Industrial Technological Economics, 2021, 40(1): 113-119.
[2] UNSIHUAY C, MARANGON-LIMA J W, SOUZA A C Z D. Integrated power generation and natural gas expansion planning[C]// Hans-Bj?rn Püttgen. 2007 IEEE Lausanne Power Tech. New York, USA: IEEE, 2007: 1-6.
[3] 魏震波, 郭毅, 魏平桉, 等. 考虑传输线重构的电气综合能源系统分布鲁棒扩展规划模型[J]. 电力自动化设备, 2021, 41(2): 16-23.
[3] WEI Zhenbo, GUO Yi, WEI Ping’an, et al. Distribution robust expansion planning model for integrated natural gas and electric power systems considering transmission switching[J]. Electric Power Automation Equipment, 2021, 41(2): 16-23.
[4] 薛友, 李杨, 高滢, 等. 计及风电出力随机特性的电-气综合能源系统随机优化[J]. 电力建设, 2018, 39(12): 2-12.
[4] XUE You, LI Yang, GAO Ying, et al. Stochastic optimization in integrated electricity-gas energy systems considering stochastic characteristics of wind power outputs[J]. Electric Power Construction, 2018, 39(12): 2-12.
[5] 王芃, 刘伟佳, 林振智, 等. 基于场景分析的风电场与电转气厂站协同选址规划[J]. 电力系统自动化, 2017, 41(6): 20-29.
[5] WANG Peng, LIU Weijia, LIN Zhenzhi, et al. Scenario analysis based collaborative site selection planning of wind farms and power-to-gas plants[J]. Automation of Electric Power Systems, 2017, 41(6): 20-29.
[6] 李哲, 王成福, 梁军, 等. 计及风电不确定性的电-气-热综合能源系统扩展规划方法[J]. 电网技术, 2018, 42(11): 3477-3487.
[6] LI Zhe, WANG Chengfu, LIANG Jun, et al. Expansion planning method of integrated energy system considering uncertainty of wind power[J]. Power System Technology, 2018, 42(11): 3477-3487.
[7] GAO Y, WEN F S, WANG K, et al. Optimal collaborative planning with demand side management in integrated gas-electricity energy systems[C]// 2018 IEEE Power & Energy Society General Meeting. New York, USA: IEEE, 2018: 1-5.
[8] JING Q, DONG Z Y, ZHAO J H, et al. Low carbon oriented expansion planning of integrated gas and power systems[J]. IEEE Transactions on Power Systems, 2015, 30(2): 1035-1046.
[9] 李捷, 余涛, 潘振宁. 基于强化学习的增量配电网实时随机调度方法[J]. 电网技术, 2020, 44(9): 3321-3332.
[9] LI Jie, YU Tao, PAN Zhenning, et al. Real-time stochastic dispatch method for incremental distribution network based on reinforcement learning[J]. Power System Technology, 2020, 44(9): 3321-3332.
[10] BARAN M, WU F. Optimal sizing of capacitors placed on a radial distribution system[J]. IEEE Transactions on Power Delivery, 1989, 4(1): 735-743.
[11] ZHOU X Z, GUO C X, WANG Y F, et al. Optimal expansion co-planning of reconfigurable electricity and natural gas distribution systems incorporating energy hubs[J]. Energies, 2017, 10(1): 124.
[12] ZHANG X P, SHAHIDEHPOUR M, ALABDULWAHAB A, et al. Optimal expansion planning of energy hub with multiple energy infrastructures[J]. IEEE Transactions on Smart Grid, 2017, 6(5): 2302-2311.
[13] SALDARRIAGA C A, HINCAPIE R A, SALAZAR H, et al. A holistic approach for planning natural gas and electricity distribution networks[J]. IEEE Transactions on Power Systems, 2013, 28(4): 4052-4063.
[14] 栗然, 申雪, 钟超, 等. 考虑环境效益的分布式电源多目标规划[J]. 电网技术, 2014, 38(6): 1471-1478.
[14] LI Ran, SHEN Xue, ZHONG Chao, et al. Multi-objective planning of distributed generation considering environmental benefit[J]. Power System Technology, 2014, 38(6): 1471-1478.
[15] 胡源, 薛松, 杨素, 等. 综合能源背景下的配电网多场景规划[J]. 中国电力, 2021, 54(4): 175-184.
[15] HU Yuan, XUE Song, YANG Su, et al. Multi-scenario planning of distribution network under integrated energy background[J]. Electric Power, 2021, 54(4): 175-184.
[16] SAROJ, KAVITA. Review: Study on simple k mean and modified K mean clustering technique[J]. International Journal of Computer Science Engineering and Technology, 2016, 6(7): 279-281.
文章导航

/