This paper proposes a multi-objective microgrid (MG) management approach aiming at optimizing operating cost, preserving battery health, and ensuring self-sufficiency in islanding conditions. A novel formulation of self-sufficiency in terms of time duration is proposed, and an optimized MG scheduling is obtained by using a multi-objective Genetic Algorithm (GA) and considering two different criteria to select the best trade-off solution on the Pareto front. The developed energy management strategy was tested on a small-scale residential DC MG. Daily and yearly simulation tests demonstrated the effectiveness of the proposed technique.
Multi-Objective Microgrid Management Considering Operating Costs, Battery Health, and Islanding Capability
G. La Tona;M. Luna;M. C. Di Piazza
2024
Abstract
This paper proposes a multi-objective microgrid (MG) management approach aiming at optimizing operating cost, preserving battery health, and ensuring self-sufficiency in islanding conditions. A novel formulation of self-sufficiency in terms of time duration is proposed, and an optimized MG scheduling is obtained by using a multi-objective Genetic Algorithm (GA) and considering two different criteria to select the best trade-off solution on the Pareto front. The developed energy management strategy was tested on a small-scale residential DC MG. Daily and yearly simulation tests demonstrated the effectiveness of the proposed technique.| File | Dimensione | Formato | |
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