Search results for "Glow-worm optimization"

showing 2 items of 2 documents

A Generalized Framework for Optimal Sizing of Distributed Energy Resources in Micro-Grids Using an Indicator-Based Swarm Approach

2014

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 usin…

Optimal designMathematical optimizationEngineeringNSGA-IIbusiness.industrymicrogridsPareto principleGlow-worm optimizationindicator based evolutionary algorithmMulti-objective optimizationComputer Science ApplicationsSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaSettore ING-IND/31 - ElettrotecnicamicrogridPower system simulationControl and Systems EngineeringDistributed generationmicrogrids;indicator based evolutionary algorithm;Glow-worm optimization;planning;NSGA-IICapital costMicrogridplanningElectrical and Electronic EngineeringbusinessActivity-based costingInformation SystemsIEEE Transactions on Industrial Informatics
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A double-shell design approach for multiobjective optimal design of microgrids

2010

This work develops a new double shell approach to optimal design for multi-objective optimally managed systems. The cost of each design solution can be defined by the evaluation of operational issues and capital costs. In most systems, the correct definition of operational issues can be deduced by means of the solution of a multi-objective optimization problem. The evaluation of each design solution must thus be deduced using the outcome of a multi-objective optimization run, namely a Pareto hyper-surface in the n-dimensional space of operational objectives. In the literature, the design problem is usually solved by considering a single objective formulation of the operational issue. In thi…

Optimal designSettore ING-IND/33 - Sistemi Elettrici Per L'EnergiaMathematical optimizationOptimization problemPower system simulationComputer sciencePareto principleCapital costmicrogrids multiobjective optimization glow-worm optimizationMulti-objective optimizationOutcome (game theory)Evolutionary computation
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