Planning for autonomous microgrid considering component degradation and parameter variability - Guerrero, Reynaldo C. Jr.; Pedrasa, Michael Angelo A. (Quezon City College of Engineering, University of the Philippines Diliman, 2019)
Planning for microgrids involves determining the optimal sizes of the distributed energy resources (DERs). This dissertation focuses on designing these DERs considering degradation of the technology performance and the variability of the input parameters. A mixed integer linear programming (MILP)-based microgrid model is formulated that accounts for DER degradation such that battery lifetime is variable depending on the energy dispatch. In addition, a multi-year investment option is employed to minimize over-sizing on the first year. Moreover, in order to consider the variability of renewable energy sources a load, a sizing approach is developed that integrates clustering, MILP and simulation. Candidate groups of representative days that capture the variability of the parameters are selected through k-means clustering. Various clustering parameters were explored including the use of the cumulative distribution function of the parameters from the representative days as a criterion for clustering. Furthermore, different designs are generated from these groups of representative days using the aforementioned MILP-based microgrid model. All of these designs are then simulated with all historical days instead of the representative days. This simulation step computes for the net present cost and the load-not-served. The optimum design is the design that has the lowest cost but still satisfies the required availability of electricity. Analysis on intermediate results and sensitivity analyses were performed to validate the MILP-based model as well as prove that the developed sizing approach is able to yield an optimum solution. Arriving at an optimum solution was accomplished at a significantly lower runtime compared to solving an MILP with all historical days. This is achieved on two case studies that have different sets of meteorological and load data. Also, ways to assess the optimality of the solution based on the intermediate results and the technical metrics are presented. Lastly, by comparing with models that do not consider DER degradation and parameter variability, the developed sizing approach and microgrid model are shown to avoid under-estimation of the net present cost and ensure that the required energy demand is met throughout the planning horizon.
Thesis (Doctor of Philosophy in Electrical Engineering)--University of the Philippines Diliman
Keywords: Microgrids (Smart power grids)