This study focuses on the real-time operation of a microgrid (MG). A novel approximate dynamic programming based spatiotemporal decomposition approach is developed to incorporate efficient management of distributed energy storage systems into MG real-time operation while considering uncertainties in renewable generation. The original dynamic energy management problem is decomposed into single-period and single-unit sub-problems, and the value functions are used to describe the interaction among the sub-problems. A two-stage procedure is further designed for the real-time decisions of those sub-problems. In the first stage, empirical data is utilised offline to approximate the value functions. Then in the second stage, each sub-problem can make immediate and independent decision in both temporal and spatial dimensions to mitigate adverse effects of intermittent renewable generation in a MG. No central operator intervention is required, and the near optimal decisions can be obtained at a very fast speed. Case studies based on a six-bus MG and an actual island MG are conducted to demonstrate the effectiveness of the proposed algorithm.
In this paper, we propose a bi-level, real-time economic dispatch method of a virtual power plant (VPP), including various distributed energy resources (DERs). Considering the different interests of VPPs and a system operator, the real-time economic dispatch of VPPs is described as a bi-level programming problem, where a system operator dispatches VPPs based on the price incentive mechanism on the upper level, and the VPPs provide response according to the optimal control of their DERs on the lower level. Considering the uncertainties of DERs and loads, the decision risks of a system operator on the upper level and VPPs on the lower level are further dealt with by the fuzzy chance constrained programming, such that they can make reasonable decisions according to their own preferred risks. The mapping method and the bilevel optimization method are also presented as the solutions for the proposed model. In this way, the fuzzy chance constraints and objective functions of both levels are transformed into deterministic forms and, then, are calculated dispersedly. As a result, the calculation burden of a system operator and the information privacies of VPPs all can be treated availably. The case studies verify the effectiveness of the proposed method in the end. INDEX TERMS Virtual power plant, real-time economic dispatch, price incentive scenario, uncertainty, hybrid algorithm. II. BI-LEVEL REAL-TIME ECONOMIC DISPATCH MODEL OF VPP CONSIDERING UNCERTAINTY A. BRIEF INTRODUCTION OF BI-LEVEL PROGRAMMING
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