Convex Optimization of Integrated Power-Gas Energy Flow Model With Applications to Probabilistic Energy Flow

作者：Wenhao Jia, Tao Ding, Can Huang, Zekai Wang, Quan Zhou, Mohammad Shahidehpour · 发表于：IEEE Transactions on Power Systems · 年份：2020 · DOI：10.1109/tpwrs.2020.3018869 · 被引用次数：66 · 研究领域：Integrated Energy Systems Optimization、Optimal Power Flow Distribution、Hybrid Renewable Energy Systems

Energy flow calculation is a fundamental problem of the integrated power and gas system (IPGS) operation and planning. However, the nonlinear gas flow model introduces major challenges to the energy flow calculation. In this paper, we propose a tractably convex optimization model to solve the energy flow problem in IPGSs. It is demonstrated that the proposed optimization model has the same optimal solution as the original nonlinear steady energy flow model. Also, piecewise linearization is adopted to tightly linearize the nonlinear objective function of the model, which transforms the formulated convex optimization into a linear program one. Thus, the computation complexity of the proposed energy flow model is significantly reduced as compared with the existing methods. In addition, the proposed model can be extended to probabilistic energy flow estimation. Extensive case studies are conducted to validate the effectiveness of the proposed energy flow model using three IPGSs.