学术论文

      电-气混联综合能源系统概率能量流分析

      Probabilistic Energy Flow Analysis in Integrated Electricity and Natural-gas Energy systems

      摘要:
      由电力系统(electric power systems,EPS)、天然气系统(natural-gas systems,NGS)之间的耦合与互联构成的综合能源系统(integrated energy systems,IES),对于构建经济、环保、高效的能源系统至关重要.同时,由于IES中大量的不确定因素,有必要将不确定建模技术应用于IES分析.该文将广泛应用于EPS的概率潮流的概念推广到IES的概率能量流分析中,计及了 EPS、NGS 之间 3 方面的耦合: 1)燃气轮机组;2)电力驱动加压站;3)能源集线器.在IES稳态能量流的基础上,考虑了电、气、热负荷以及风电场出力的不确定性,并采用蒙特卡罗模拟法求解IES概率能量流.算例分析表明,NGS(或 EPS)中不确定性因素会对EPS(或 NGS)的概率能量流产生影响;同时 NGS 能量流方程线性化精度明显低于EPS.
      Abstract:
      Integrated energy systems (IES), consisting of the coupling and interactions between electric power systems (EPS) and natural-gas systems (NGS), are expected to play an important role in constructing the economic, eco-friendly, and efficient energy systems. Meanwhile, due to the fact that IES are confronted with a wide range of uncertainties, it is essential to take advantage of uncertainty modeling techniques to analyze IES. In this paper, the concept of probabilistic load flow, which has been widely applied in EPS, was extended to IES probabilistic energy flows analysis. Three aspects of coupling between EPS and NGS are considered: 1) gas-fired generators; 2) electric-driven compressors; and 3) energy hubs. Based on the models of IES steady energy flows, the proposal is solved by Monte Carlo simulation with the consideration of uncertainties of electric, gas and heat loads and wind farms output power. Finally, test results demonstrate that the uncertainties in NGS (or EPS) do have effects on EPS (or NGS) probabilistic energy flows. Further, the accuracy of linearizing NGS energy flow equations is obvious lower than EPS.
      作者: 陈胜 [1] 卫志农 [1] 孙国强 [1] 王丹 [2] 孙永辉 [1] 臧海祥 [1] 朱瑛 [1]
      Author: CHEN Sheng [1] WEI Zhinong [1] SUN Guoqiang [1] WANG Dan [2] SUN Yonghui [1] ZANG Haixiang [1] ZHU Ying [1]
      作者单位: 可再生能源发电技术教育部工程研究中心(河海大学),江苏省南京市,210098 智能电网教育部重点实验室(天津大学),天津市南开区,300072
      刊 名: 中国电机工程学报 ISTICEIPKU
      年,卷(期): 2015, 35(24)
      分类号: TM744
      在线出版日期: 2016年2月25日
      基金项目: 国家自然科学基金项目(51277052,51407125,51507052, 51507050). Project Supported by National Natural Science Foundation of China