In this paper, an optimal power dispatch problem on a 24-h basis for distribution systems with distributed energy resources (DER) also including directly controlled shiftable loads is presented. In the literature, the optimal energy management problems in smart grids (SGs) where such types of loads exist are formulated using integer or mixed integer variables. In this paper, a new formulation of shiftable loads is employed. Such formulation allows reduction in the number of optimization variables and the adoption of real valued optimization methods such as the one proposed in this paper. The method applied is a novel nature-inspired multiobjective optimization algorithm based on an original extension of a glowworm swarm particles optimization algorithm, with algorithmic enhancements to treat multiple objective formulations. The performance of the algorithm is compared to the NSGA-II on the considered power systems application.

Graditi, G., Di Silvestre, M.L., Gallea, R., Riva Sanseverino, E. (2015). Heuristic-based shiftable loads optimal management in smart micro-grids. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 11(1), 271-280 [10.1109/TII.2014.2331000].

Heuristic-based shiftable loads optimal management in smart micro-grids

DI SILVESTRE, Maria Luisa;GALLEA, Roberto;RIVA SANSEVERINO, Eleonora
2015

Abstract

In this paper, an optimal power dispatch problem on a 24-h basis for distribution systems with distributed energy resources (DER) also including directly controlled shiftable loads is presented. In the literature, the optimal energy management problems in smart grids (SGs) where such types of loads exist are formulated using integer or mixed integer variables. In this paper, a new formulation of shiftable loads is employed. Such formulation allows reduction in the number of optimization variables and the adoption of real valued optimization methods such as the one proposed in this paper. The method applied is a novel nature-inspired multiobjective optimization algorithm based on an original extension of a glowworm swarm particles optimization algorithm, with algorithmic enhancements to treat multiple objective formulations. The performance of the algorithm is compared to the NSGA-II on the considered power systems application.
Settore ING-IND/33 - Sistemi Elettrici Per L'Energia
http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=9424
Graditi, G., Di Silvestre, M.L., Gallea, R., Riva Sanseverino, E. (2015). Heuristic-based shiftable loads optimal management in smart micro-grids. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 11(1), 271-280 [10.1109/TII.2014.2331000].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/129323
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