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Multi-stage Robust Scheduling for Community Microgrid with Energy Storage

Journal of Modern Power Systems and Clean Energy 2023年第6期11卷 1923-1934页

作者： Ye Tang Qiaozhu Zhai Jiexing Zhao IEEE Systems Engineering Institute MOEKLINNS LabXi’an Jiaotong UniversityXi’an 710049China

Energy storage devices can effectively balance the uncertain load and significantly reduce electricity costs in the community microgrids(C-MGs) integrated with renewable energy sources. Scheduling of energy storage is a multi-stage decision problem in which the decisions must be guaranteed to be nonanticipative and multi-stage robust(all-scenario-feasible). To satisfy these two requirements, this paper proposes a method based on a necessary and sufficient feasibility condition of scheduling decisions under the polyhedral uncertainty set. Unlike the most popular affine decision rule(ADR) based multistage robust optimization(MSRO) method, the method proposed in this paper does not require the affine decision assumption, and the feasible regions(the set of all feasible solutions) are not reduced, nor is the solution quality affected. A simple illustrative example and real-scale scheduling cases demonstrate that the proposed method can find feasible solutions when the ADR-based MSRO fails, and that it finds better solutions when both methods succeed. Comprehensive case studies for a real system are performed and the results validate the effectiveness and efficiency of the proposed method.

关键词： Community microgrid short-term scheduling energy storage nonanticipativity polyhedral uncertainty set

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A Two-stage Adaptive Robust Model for Residential Micro-CHP Expansion Planning

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Journal of Modern Power Systems and Clean Energy 2021年第4期9卷 826-836页

作者： Fatemeh Teymoori Hamzehkolaei Nima Amjady Bahareh Bagheri Department of Electrical Engineering Semnan UniversitySemnanIran

This paper addresses the planning problem of residential micro combined heat and power (micro-CHP) systems (including ‎micro-generation units, auxiliary boilers, and thermal storage tanks) considering the associated technical and economic factors. Since the accurate values of the thermal and electrical loads of this system cannot be exactly predicted for the planning horizon, the thermal and electrical load uncertainties are modeled using a two-stage ‎adaptive robust optimization method based on a ‎polyhedral uncertainty set. A solution method, which is composed of column-and-constraint generation (C&CG) algorithm ‎and block coordinate descent (BCD) method, is proposed to efficiently solve this adaptive robust optimization model. Numerical results ‎from a practical case study show the effective performance of the proposed adaptive robust model for residential micro-CHP planning and its solution method.

关键词： Micro combined heat and power(micro-CHP)planning two-stage adaptive robust optimization model block coordinate descent method polyhedral uncertainty set

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