| 引用本文: | 魏震波,郭毅,魏平桉,黄宇涵,方涛.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): |
| WEI Zhenbo,GUO Yi,WEI Ping'an,HUANG Yuhan,FANG Tao.Distribution robust expansion planning model for integrated natural gas and electric power systems considering transmission switching[J].Electric Power Automation Equipment,2021,41(2): |
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| 摘要: |
| 针对综合能源系统扩展规划模型多采用随机优化处理系统负荷需求增长不确定性问题，且场景信息缺失，易造成随机优化结果经济性与可参考性低的情况，提出一种以系统综合成本最小为目标函数、考虑传输线重构的两阶段电气综合能源系统分布鲁棒扩展规划模型。第一阶段为考虑综合能源负荷预测和传输线重构的扩展规划模型；第二阶段为计及机组调整出力与天然气能流的综合能源负荷需求不确定条件下的分布鲁棒模型，其中不确定概率分布集合采用1-范数约束。所提模型采用列与约束生成算法求解，并在IEEE-RTS24节点与比利时20节点系统中进行校验。结果表明分布鲁棒模型能够在对象信息量较少或不足的情况下基于较大置信区间范围提供灵活决策方案，应对综合能源负荷需求不确定性问题更具优势。 |
| 关键词: 电气综合能源系统 负荷需求增长 分布鲁棒 列与约束生成算法 数据驱动 扩展规划 |
| DOI：10.16081/j.epae.202012016 |
| 分类号:TM715;TK01 |
| 基金项目: |
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| Distribution robust expansion planning model for integrated natural gas and electric power systems considering transmission switching |
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WEI Zhenbo1, GUO Yi1, WEI Ping'an1, HUANG Yuhan1, FANG Tao2
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1.School of Electrical Engineering, Sichuan University, Chengdu 610065, China;2.State Grid Sichuan Electric Power Company, Chengdu 610041, China
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| Abstract: |
| As for stochastic optimization is commonly used to deal with the uncertainty of load demand growth in the expansion planning model of integrated natural gas and electric power systems, and the loss of scene information, these may result in uneconomic or conservative decisions. Based on this, a two-stage distribution robust expansion planning model for integrated natural gas and electric power systems is established, which takes the overall cost of system as objective function and considers transmission switching. In the first stage, the expansion planning model is constructed by considering integrated energy load forecasting and transmission switching. In the second stage, the distribution robust model is constructed under the condition of uncertain integrated energy load demand, which takes the regulation of units’ output and natural gas flow into account, and the uncertain probability distribution set adopts 1-norm constraint. The proposed model is solved by column and constraint generation algorithm, and its effectiveness is verified by IEEE-RTS24-bus system and Belgian 20-node system. The results show that the distribution robust model can provide flexible decision-making schemes based on a larger confidence interval when the information is limited, and it is superior in dealing with the uncertainty problem of load demand growth. |
| Key words: integrated natural gas and electric power systems load demand growth distribution robust column and constraint generation algorithm data-driven expansion planning |
