| 引用本文: | 赵曰浩,鞠平.考虑供气约束与净负荷预测误差的电-气综合能源系统调度策略[J].电力自动化设备,2022,42(7): |
| ZHAO Yuehao,JU Ping.Scheduling strategy of integrated electricity and gas system considering constraint of gas supplying and prediction error of net power load[J].Electric Power Automation Equipment,2022,42(7): |
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| 摘要: |
| 当前电-气综合能源系统调度存在天然气供气流量波动性较大、调整次数过多等问题，导致配气系统调峰压力较大。为此建立天然气供气模型，包含供气流量调整幅度、方向、总次数等约束；对天然气系统标幺制进行推导，通过合理选择基准值可对天然气系统的相关参数进行合理放缩变换，以便观察分析；用高斯混合模型对净负荷预测误差概率分布进行精确拟合，基于此提出考虑天然气供气约束和净负荷预测误差的电-气综合能源系统调度策略，并采用数据驱动的机会约束规划来处理净负荷预测随机性。最后，通过算例验证所提策略的有效性，仿真结果表明所提策略可明显降低天然气供气流量波动，保障系统的可靠经济运行。 |
| 关键词: 电-气综合能源系统 供气流量 高斯混合模型 净负荷 预测误差 数据驱动 |
| DOI：10.16081/j.epae.202205042 |
| 分类号:TM73;TK01 |
| 基金项目:国家自然科学基金资助项目(51837004, U2066601) |
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| Scheduling strategy of integrated electricity and gas system considering constraint of gas supplying and prediction error of net power load |
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ZHAO Yuehao1, JU Ping1,2
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1.College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China;2.College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
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| Abstract: |
| At present, there are some problems about the scheduling of the integrated electricity and gas system, such as large fluctuation of gas supplying flow and excessive adjustment times, etc.,which leads to serious challenge for peak shaving of gas distribution system. For that, the natural gas supplying model is built, which includes the constraints of adjustment amplitude, adjustment direction, total adjustment times of gas supplying flow, etc. Then, the per unit of natural gas system is derived. The related parameters of natural gas system can be zoomed reasonably with the reasonable base value for observation and analysis. Furthermore, the Gaussian mixture model is used to fit the probability distribution about the prediction error of the net power load accurately. On this basis, the scheduling strategy of the electricity and gas system considering constraint of gas supplying flow and prediction error of net power load is proposed. The data-driven chance constraint programming is adopted to solve the randomness of prediction error of the net power load. Finally, the effectiveness of the proposed strategy is validated by the case study, and simulative results show that the proposed strategy can obviously reduce the fluctuation of gas supplying flow, and ensure the safe and economic operation of system. |
| Key words: integrated electricity and gas system gas supplying flow Gaussian mixture model net power load prediction error data-driven |
