Two-Stage Optimization Strategy for Solving the VVO Problem Considering High Penetration of Plug-In Electric Vehicles to Unbalanced Distribution Networks

• Published in: IEEE transactions on industry applications Vol. 57; no. 4; pp. 3425 - 3440
• Main Authors: Aljohani, Tawfiq, Saad, Ahmed Aly Saad, Mohammed, Osama
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-07-2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Capacitor banks; Community-based detection; Electric power distribution; Electric vehicles; Indexes; Integer programming; Linear programming; Mixed integer; mixed-integer linear programming (MILP); Optimization; Partial discharges; Particle swarm optimization; particle swarm optimization (PSO); Partitioning algorithms; Penetration; plug-in electric vehicle (PEV) integration; Reactive power; Unbalance; Voltage control; Voltage regulators; voltage-var optimization (VVO)
• ISSN: 0093-9994; 1939-9367
• DOI: 10.1109/TIA.2021.3077547

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.