IET Generation Transmission & Distribution · 2013 · 103 citations · 27 references
EngineeringMathematicsEnergy SystemsOptimizationRenewable Energy IntegrationDistributed Energy ResourcesDistribution Network PlanningPower Grid AnalysisPower OptimizationPower System DesignPower SystemsDistribution SystemsMixed-integer Nonlinear ProgrammingMixed-integer OptimizationParticle Swarm OptimizationPower Network OptimizationPower System OptimizationPower System PlanningVoltage
Distributed generation (DG) has been becoming more well‐known in the power sector because of its ability in power loss reduction, low investment cost, increase reliability, and most significantly, to exploit renewable‐energy resources. In this study, a multi‐objective index‐based approach for optimally determining the placement and size of multi‐DG units in distribution systems, including the voltage rise phenomenon is proposed. The proposed approach considers a wide range of technical aspects such as the total real power losses in the system, the voltage profile, the mega volt ampere intake by the grid, the DG quantity and the greenhouse gases emission. A novel hybrid population‐based algorithm with the combination of particle swarm optimisation (PSO), and gravitational search algorithm (GSA) is introduced. To reveal the validity of the hybrid PSO‐GSA, an analysis is carried out on 69‐bus systems then compared with results obtained by pre‐combined methods. The outcomes verify that the proposed algorithm is efficient, robust, and capable of handling mixed integer nonlinear optimisation problem.
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James Kennedy, R.C. Eberhart · 2002 · 47.5K citations
Riccardo Poli, James Kennedy, Tim Blackwell · Swarm Intelligence · 2007 · 21.4K citations
GSA: A Gravitational Search Algorithm
Esmat Rashedi, Hossein Nezamabadi–pour, Saeı̈d Saryazdi · Information Sciences · 2009 · 7.3K citations