Summary
Motivated by the increasing transition from fossil fuel–based centralized systems to renewable energy–based decentralized systems, we consider a bi‐objective investment planning problem of a grid‐connected decentralized hybrid renewable energy system. In this system, solar and wind are the main electricity generation resources. A national grid is assumed to be a carbon‐intense alternative to the renewables and is used as a backup source to ensure reliability. We consider both total cost and carbon emissions caused by electricity purchased from the grid. We first discuss a novel simulation‐optimization algorithm and then adapt multi‐objective metaheuristic algorithms. We integrate a simulation module to these algorithms to handle the stochastic nature of this bi‐objective problem. We perform extensive comparative analysis for the solution approaches and report their performances in terms of solution time and quality based on well‐known measures from the literature.
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