A Generalized Method for Rightsizing the Design of a Hybrid Microgrid

Daniel Reich ()
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Daniel Reich: Department of Operations Research, Naval Postgraduate School, 1 University Circle, Monterey, CA 93943, USA

Energies, 2025, vol. 18, issue 7, 1-15

Abstract: As the demand for sustainable and resilient energy systems grows, providing planners with effective tools for microgrid design becomes increasingly important. This research addresses the need for such tools by introducing a new method for distributed energy resource sizing in microgrid capacity planning. The planning process begins with a comprehensive assessment of the required capacity based on a given set of power load requirements. Rather than providing a single solution, as is common in related works, the sizing method introduced in this paper efficiently identifies a wide range of microgrid design options that satisfy the stated power needs. The benefit of this multi-solution approach is that it allows decision makers to consider vastly different possibilities, such as varying levels of renewables and battery storage, and weigh trade-offs between these potential designs before selecting one or more solutions for further detailed design planning. The proposed method is constructed as a three-step heuristic search procedure: (1) an exhaustive search identifies an initial set of candidate solutions; (2) a global binary search builds a diverse set of microgrid design options; and (3) a local linear search refines those options. A computational experiment is presented to demonstrate the method’s effectiveness at identifying diverse solutions sets and its computational tractability. The results show that increasing the number of capacity levels considered per distributed energy resource from 11 to 41 increases the size and diversity of the microgrid design set; however, further increasing the number of capacity levels beyond that point is not beneficial. The method presented is implemented and released in Microgrid Planner, an open source software platform.

Keywords: microgrid; sizing; simulation; decision support system; renewable energy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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