Abstract
Lately, the integration of renewable energy sources (e.g., photovoltaic and wind generation systems) has been raised into microgrids interconnected with plug-in electric vehicles (PEVs). Such intermittent generation and charging/discharging PEV profiles are challenging to ensure the secure and optimal operation of microgrids. In this article, an optimization approach is proposed to determine the optimal locations and sizes of photovoltaic and wind generation systems in microgrids with PEV-parking lots. The developed approach addresses 1) the uncertainty of generation profiles of photovoltaic and wind generation systems and loads; 2) the DSTATCOM feature of photovoltaic and wind generation systems; and 3) microgrid constraints. The feasible PEV conditions are also considered, i.e., initial and preset conditions of their state of charge, arriving and departing times, and various controlled/uncontrolled charging schemes. To solve the planning model, we have developed a bilevel metaheuristic-based approach. The upper-level and lower-level optimization tasks are to optimize the decision variables of renewable energy sources and PEVs, respectively. Both energy losses through the lines and energy from the main grid are considered as subobjectives to be minimized. Various simulations and study cases are performed to assess the effectiveness of the proposed approach. The outcomes show the efficacy of the proposed approach to simultaneously plan renewable energy sources and manage PEVs to form an autonomous microgrid.
Highlights
T HE penetration of renewable energy sources (RESs) is increasing year by year globally
Lately, the integration of renewable energy sources has been raised into microgrids interconnected with plug-in electric vehicles (PEV)
The merits of the proposed approach are the consideration of the uncertainty of generation profiles of PV units, wind turbine (WT) units, loads, and the DSTATCOM feature of PV and WT inverters
Summary
T HE penetration of renewable energy sources (RESs) is increasing year by year globally. To lessen the computational burden of the optimization paradigm, some present methods adopt one RES unit planning with considering only active power generation and formulate deterministic rather than probabilistic planning models Another vital demerit of many other approaches is missing the full representation of PEV batteries with their intermittent and uncertain charging and discharging profiles. The main advantages of the proposed approach include considering the following: 1) the intermittent profiles of PV and WT generation, and loads, 2) the DSTATCOM functionalities of PV and WT inverters, and 3) various constraints of the microgrid Another vital contribution is incorporating the practical PEV variables and parameters in the planning model, including arriving and departing times, initial and preset conditions of their state of charge (SOC), and different controlled /uncontrolled charging schemes. The efficacy of the proposed approach is proved to simultaneously plan renewable energy sources and manage PEV batteries while contributing to the transformation towards autonomous microgrids
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