This article proposes a two-stage optimization strategy for solving the voltage-var optimization (VVO) problem considering stochastic penetration of plug-in electric vehicles (PEVs) to unbalanced, three-phase power di...
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This article proposes a two-stage optimization strategy for solving the voltage-var optimization (VVO) problem considering stochastic penetration of plug-in electric vehicles (PEVs) to unbalanced, three-phase power distribution networks (PDN). The optimization strategy considers the prospect of forced active power curtailment at a minimized level, bidirectional PEVs activities. It also includes simple tap operations of shunt capacitor banks, online tap changing transformers, and voltage regulators to achieve optimal economic gain while satisfying the VVO operational constraints. The first stage aims for the optimal decomposition of the PDN into well-defined, cross-checked smaller partitions via a proposed community-based detection particle swarm optimization algorithm. The second stage incorporates a mixed-integer linear programming formulation to solve the VVO problem per partition level. This is done considering the nonlinearity and nonconvexity of the electrical system via applied approximation. This reduces the complexity and computational burdens that usually arise in solving the problem on a larger scale. The proposed two-stage strategy was tested on the modified IEEE 123 bus system with various case scenarios. Economical operation of the PDN is achieved during peak demand hours while maintaining a safe operation within the VVO problem.
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