In this paper, a generalized double-shell framework for the optimal design of systems managed optimally according to different criteria is developed. Optimal design is traditionally carried out by means of minimum capital and management cost formulations and does not typically consider optimized operation. In this paper, the optimized multiobjective management is explicitly considered into the design formulation. The quality of each design solution is indeed defined by the evaluation of operational costs and capital costs. Besides, the assessment of the operational costs term is deduced by means of the solution of a multiobjective optimization problem. Each design solution is evaluated using the outcomes of a multiobjective optimization run: a Pareto hyper-surface in the n-dimensional space of the operational objectives. In the literature, commonly the evaluation of each design solution is carried out based on an approximate evaluation of the operational costs, not considering the real multiobjective optimized management. In this paper, such assessment is carried out using a suitable convergence indicator typically used for multiobjective optimization algorithms. The application is devoted to the problem of optimal sizing of distributed energy resources in medium voltage or low voltage microgrids. For this problem, the identification of the multiple operational impacts comes along with the solution of the optimal unit commitment of distributed generators. After the introductory section, the problem formulation is presented and an interesting application of the considered approach to the design of distributed energy sources in a microgrid is shown. © 2005-2012 IEEE.

A generalized framework for optimal sizing of distributed energy resources in micro-grids using an indicator-based swarm approach

Graditi, G.
2014-01-01

Abstract

In this paper, a generalized double-shell framework for the optimal design of systems managed optimally according to different criteria is developed. Optimal design is traditionally carried out by means of minimum capital and management cost formulations and does not typically consider optimized operation. In this paper, the optimized multiobjective management is explicitly considered into the design formulation. The quality of each design solution is indeed defined by the evaluation of operational costs and capital costs. Besides, the assessment of the operational costs term is deduced by means of the solution of a multiobjective optimization problem. Each design solution is evaluated using the outcomes of a multiobjective optimization run: a Pareto hyper-surface in the n-dimensional space of the operational objectives. In the literature, commonly the evaluation of each design solution is carried out based on an approximate evaluation of the operational costs, not considering the real multiobjective optimized management. In this paper, such assessment is carried out using a suitable convergence indicator typically used for multiobjective optimization algorithms. The application is devoted to the problem of optimal sizing of distributed energy resources in medium voltage or low voltage microgrids. For this problem, the identification of the multiple operational impacts comes along with the solution of the optimal unit commitment of distributed generators. After the introductory section, the problem formulation is presented and an interesting application of the considered approach to the design of distributed energy sources in a microgrid is shown. © 2005-2012 IEEE.
2014
microgrids;indicator based evolutionary algorithm;Glow-worm optimization;planning;NSGA-II
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12079/2464
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