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UBC Theses and Dissertations

Optimization-based design of microgrids for critical loads May Alvarez, Jorge Alejandro

Abstract

With the increasing number of extreme weather events caused by global warming, there is an escalating need for reliable and sustainable alternatives for powering up critical loads. In recent years, microgrids with renewable generation have emerged as a promising technology for powering critical loads as they can achieve high power supply reliability and low carbon footprint. To meet the requirements of critical loads and to justify their economic viability, microgrids should be carefully planned and optimized. Existing tools for designing microgrids focus mainly on improving the design’s financial aspects by optimally sizing its energy sources; although these tools provide satisfactory results for conventional applications, they are not suitable for critical loads as reliability is not included in the design process. This work presents a new Vectorial Microgrid Optimization (VMO) design method for critical loads. The proposed VMO method improves the microgrid design by 1) incorporating the selection of the microgrid power conversion architecture and the size of the energy sources into a unified design strategy, 2) include the microgrid reliability, net present cost, and energy efficiency as the performance metrics. Multiobjective optimization is implemented as the decision-making tool to fulfill the critical load power requirements and reach the desire balance between the performance metrics. To highlight the benefits of the proposed method, an example of a critical load is analyzed to find its optimal microgrid design. The results indicate that the proposed approach produces a microgrid design with a 100 times lower downtime than those obtained with existing microgrid design tools while maintaining an energy efficiency of 93.76% and reducing the net present cost by 14%.

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Attribution-NonCommercial-NoDerivatives 4.0 International