A matheuristic for design and dispatch of a utility-connected distributed energy system

James Grymes (), Alexandra Newman (), Alexander Zolan () and Dinesh Mehta ()
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James Grymes: Colorado School of Mines, Operations Research with Engineering
Alexandra Newman: Colorado School of Mines, Operations Research with Engineering
Alexander Zolan: National Renewable Energy Laboratory
Dinesh Mehta: Colorado School of Mines, Computer Science

Journal of Heuristics, 2025, vol. 31, issue 4, No 6, 52 pages

Abstract: Abstract Modeling distributed power generation systems often requires complicated mathematical expressions that present challenges for commercial optimization solvers. This paper presents a matheuristic to solve a mixed-integer optimization model that informs decisions regarding the design and dispatch of a utility-connected microgrid. We deploy a genetic algorithm to search the system design space and a linear program to solve the economic dispatch problem. The model is a component of a web tool that requires solutions within a few minutes. Our method yields objective function values within 5% of an exogenously produced optimal in fewer than 30 seconds for 90% of our test cases compared to only 10% of our test cases by a traditional optimization solver in the same amount of time.

Keywords: Optimization; Microgrid; Combined heat and power; Mixed-integer linear program; Matheuristic; Genetic algorithm (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10732-025-09567-0

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