This paper presents a novel nature-inspired multi-objective optimization algorithm. The method extends the glowworm swarm particles optimization algorithm with algorithmical enhancements which allow to identify optimal pareto front in the objectives space. In addition, the system allows to specify constraining functions which are needed in practical applications. The framework has been applied to the power dispatch problem of distribution systems including Distributed Energy Resources (DER). Results for the test cases are reported and discussed elucidating both numerical and complexity analysis.
Riva Sanseverino, E., Di Silvestre, M.L., Gallea, R. (2013). Pareto-optimal Glowworm Swarms Optimization for Smart Grids Management. In Anna I. Esparcia-Alcázar (a cura di), Applications of Evolutionary Computation (pp. 22-31). Berlin : Springer [10.1007/978-3-642-37192-9_3].
Pareto-optimal Glowworm Swarms Optimization for Smart Grids Management
RIVA SANSEVERINO, Eleonora;DI SILVESTRE, Maria Luisa;GALLEA, Roberto
2013-01-01
Abstract
This paper presents a novel nature-inspired multi-objective optimization algorithm. The method extends the glowworm swarm particles optimization algorithm with algorithmical enhancements which allow to identify optimal pareto front in the objectives space. In addition, the system allows to specify constraining functions which are needed in practical applications. The framework has been applied to the power dispatch problem of distribution systems including Distributed Energy Resources (DER). Results for the test cases are reported and discussed elucidating both numerical and complexity analysis.
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