Abstract
Renewable energy sources have recently been integrated into microgrids that are in turn connected to electric vehicle (EV) charging stations. In this regard, the optimal planning of microgrids is challenging with such uncertain generation and stochastic charging/discharging EV models. To achieve such ambitious goals, the best sites and sizes of photovoltaic and wind energy units in microgrids with EV are accurately determined in this work using an optimization technique. This proposed technique considers 1) generation profile uncertainty in photovoltaic and wind energy units as well as the total load demand, 2) photovoltaic and wind generation units' DSTATCOM operation capability, and 3) various branch and node constraints in the microgrid. Most importantly, the possible EV requirements are also taken into account, including initial and predetermined state of charge (SOC) arrangements, arrival and departure hours, and diverse regulated and unregulated charging strategies. A bi-level metaheuristic-based solution is established to address this complex planning model. The outer level and inner-level functions optimize renewable energy sources and EV decision variables. Sub-objectives to be optimized voltage deviations as well as grid power. The results demonstrate the effectiveness of the introduced method for planning renewable energy sources and managing EV to effectively achieve autonomous microgrids.
Highlights
Renewable energy sources (RESs) are being more widely used around the world
The possible electric vehicles (EVs) requirements are taken into account, including initial and predetermined state of charge (SOC) arrangements, arrival and departure hours, and diverse regulated and unregulated charging strategies
The PV units can be allocated in Zone 1, Zone 2, and Zone 3 while the wind turbine (WT) can be allocated in Zone 4, Zone 5, and Zone 6
Summary
Renewable energy sources (RESs) are being more widely used around the world. Global policies to minimize greenhouse gas emissions drive this trend, but innovations in future electrical power generation technologies are anticipated [1,2,3]. The optimization model considers EV operation restrictions such as various charging control schemes of EVs, including controlled and uncontrolled charging strategies This technique takes into account generation profile intermittency in photovoltaic and wind energy systems, as well as overall load demand, DSTATCOM operating ability of inverter-based photovoltaic and wind generation stations, and various branch and node constraints in the microgrid. EV conditions, such as initial and predetermined state of charge (SOC) arrangements, arrival and departure hours, and various controlled and uncontrolled charging strategies, are considered To solve this multipart planning model accurately, we established a bi-level metaheuristic-based optimization approach. The conclusions show that the proposed approach for planning renewable energy sources and controlling EVs effectively achieves autonomous microgrids with photovoltaic, wind, and EV charging stations
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