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A novel Volt-VAR Optimization engine for smart distribution networks utilizing Vehicle to Grid dispatch
Affiliation:1. School of Engineering Science, Simon Fraser University (SFU), Surrey Campus, 250, 13450, 102nd Avenue, Surrey, British Columbia, Canada;2. British Columbia Institute of Technology (BCIT), 4355 Mathissi Place, Burnaby, British Columbia, Canada;1. Midcontinent ISO, 720 City Center Drive, Carmel 46032, IN, USA;2. Department of Electrical and Computer Engineering, Iowa State University, Ames 50010, IA, USA;1. GECAD – Knowledge Engineering and Decision Support Research Center – Polytechnic of Porto (IPP), R. Dr. António Bernardino de Almeida, 431, 4200-072 Porto, Portugal;2. AUTomation and Control Group – Department of Electrical Engineering, Denmark Technical University (DTU), Elektrovej, Bld 326, 2800 Lyngby, Denmark;3. INESC-ID/IST Instituto Superior Técnico – University of Lisbon, Lisbon, Portugal
Abstract:In recent years, Smart Grid technologies such as Advanced Metering, Pervasive Control, Automation and Distribution Management have created numerous control and optimization opportunities and challenges for smart distribution networks. Availability of Co-Gen loads and/or Electric Vehicles (EVs) enable these technologies to inject reactive power into the grid by changing their inverter’s operating mode without considerable impact on their active power operation. This feature has created considerable opportunity for distribution network planners to explore if EVs could be used in the distribution network as reliable VAR suppliers. It may be possible for network operators to employ some EVs as VAR suppliers for future distribution grids. This paper proposes an innovative Smart Grid-based Volt-VAR Optimization (VVO) engine, capable of minimizing system power loss cost as well as the operating cost of switched Capacitor Banks, while optimizing the system voltage using an improved Genetic Algorithm (GA) with two levels of mutation and two levels of crossover. The paper studies the impact of EVs with different charging and penetration levels on VVO in different operating scenarios. Furthermore, the paper demonstrates how a typical VVO engine could benefit from V2G’s reactive power support. In order to assess V2G impacts on VVO and test the applicability of the proposed VVO, revised IEEE-123 Node Test Feeder in presence of various load types is used as case study.
Keywords:Distribution network  Electric vehicle  Smart grid  Volt-VAR Optimization  Vehicle to Grid  Power loss
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