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dc.contributor.authorSiano, P.*
dc.contributor.authorMokryani, Geev*
dc.date.accessioned2016-09-21T15:44:30Z
dc.date.available2016-09-21T15:44:30Z
dc.date.issued2015
dc.identifier.citationSiano P and Mokryani G (2015) Evaluating the Benefits of Optimal Allocation of Wind Turbines for Distribution Network Operators. IEEE Systems Journal. 9(2): 629-638.
dc.identifier.urihttp://hdl.handle.net/10454/9223
dc.descriptionNo
dc.description.abstractThis paper proposes a hybrid optimization method for optimal allocation of wind turbines (WTs) that combines a fast and elitist multiobjective genetic algorithm (MO-GA) and the market-based optimal power flow (OPF) to jointly minimize the total energy losses and maximize the net present value associated with the WT investment over a planning horizon. The method is conceived for distributed-generator-owning distribution network operators to find the optimal numbers and sizes of WTs among different potential combinations. MO-GA is used to select, among all the candidate buses, the optimal sites and sizes of WTs. A nondominated sorting GA II procedure is used for finding multiple Pareto-optimal solutions in a multiobjective optimization problem, while market-based OPF is used to simulate an electricity market session. The effectiveness of the method is demonstrated with an 84-bus 11.4-kV radial distribution system.
dc.relation.isreferencedbyhttp://dx.doi.org/10.1109/Jsyst.2013.2279733
dc.subjectDistribution network operator; DNO
dc.subject; Genetic algorithm; GA
dc.subject; Social welfare maximisation
dc.subject; Step-controlled primal-dual interior point method
dc.subject; Wind turbines
dc.subject; Optimal power-flow
dc.subject; Interior-point method
dc.subject; Distribution-systems
dc.subject; Optimisation methods
dc.subject; Genetic algorithm
dc.subject; Generation
dc.subject; Energy
dc.titleEvaluating the Benefits of Optimal Allocation of Wind Turbines for Distribution Network Operators
dc.status.refereedYes
dc.typeArticle
dc.type.versionNo full-text available in the repository


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