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• W2096448144 abstract "This paper presents a new computational technique in composite generation and transmission expansion planning considering reliability and cost assessment. The proposed procedure incorporates a virtual database in order to hedging the repetitive calculation by optimisation solver. Since generation and transmission expansion planning is a large scale, mixed-integer, nonlinear and non-convex optimisation task, the proposed technique accelerates the convergence time and reduces computational burden. The composite generation and transmission expansion planning problem is represented as a multi-objective optimisation problem. The virtual database-supported non-dominated sorting genetic algorithm (VDS-NSGA-II) is applied due to comparative assessment potential and good handling of the non-convex problems and non-commensurable objective functions. The virtual database eliminates the repetitive computational efforts in both reliability and hourly operational assessments. In this study, the expected energy not served at hierarchical level II is taken into account as a reliability index, whereas the entire system cost, including annually operational and investment costs, is considered as another objective function. The incidence matrix-based DC optimal power flow is adopted to reflect transmission flow constraint in a framework in which the disconnected bus problem would be handled in both objective functions. To numerically evaluate the efficiency of the proposed method, simulation results on a simple three-bus test system and the modified IEEE 24-bus reliability test system are provided. In spite of huge computation burden at HL-II reliability assessment, the results indicate high efficiency of the proposed VDS-NSGA-II." @default.
• W2096448144 created "2016-06-24" @default.
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• W2096448144 date "2013-08-09" @default.
• W2096448144 modified "2023-10-12" @default.
• W2096448144 title "An augmented NSGA-II technique with virtual database to solve the composite generation and transmission expansion planning problem" @default.
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• W2096448144 doi "https://doi.org/10.1080/0952813x.2013.815280" @default.
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