Abstract
Distributed energy resources (DERs), including renewable energy resources (RESs) and electric vehicles (EVs), have a significant impact on distribution systems because they can cause bi-directional power flow in the distribution lines. Thus, the voltage regulation and thermal limits of the distribution system to mitigate from the excessive power generation or consumption should be considered. The focus of this study is on a control strategy for DERs in low-voltage DC microgrids to minimize the operating costs and maintain the distribution voltage within the normal range based on intelligent scheduling of the charging and discharging of EVs, and to take advantage of RESs such as photovoltaic (PV) plants. By considering the time-of-use electricity rates, we also propose a 24-h sliding window to mitigate uncertainties in loads and PV plants in which the output is time-varied and the EV arrival cannot be predicted. After obtaining a request from the EV owner, the proposed optimal DER control method satisfies the state-of-charge level for their next journey. We applied the voltage sensitivity factor obtained from a load-flow analysis to effectively maintain voltage profiles for the overall DC distribution system. The performance of the proposed optimal DER control method was evaluated with case studies and by comparison with conventional methods.
Highlights
In recent decades, the concept of a DC microgrid has been proposed to improve the local reliability and flexibility of electric power systems comprising distributed energy resources (DERs), AC and/or DC loads, and energy-storage units [1,2,3]
We propose a control method for DERs such as renewable energy sources (RESs) and electric vehicles (EVs) that can be implemented in the energy-management system (EMS) for a DC microgrid
The proposed optimal control strategy was formulated using mixed-integer linear programming (MILP) in the 24-h horizontal with 1-h sliding steps. Information such as load and PV power forecasting, ToU-based time-varying electricity price, EV arrival and departure time, and initial and departure SoC of EVs can be updated at each time interval to implement the optimization process
Summary
The concept of a DC microgrid has been proposed to improve the local reliability and flexibility of electric power systems comprising distributed energy resources (DERs), AC and/or DC loads, and energy-storage units [1,2,3]. In [7], the authors formulated an optimal power flow problem using a genetic algorithm to minimize the total operation cost of a DC microgrid while considering real-time pricing. The authors in [18,19] proposed a voltage-control algorithm by coordinating the main AC/DC converter and DER scattering in a distribution system They calculated voltage sensitivity factors (VSFs) based on the solution of load-flow analysis to calculate the relevant power injection or absorption to compensate for the voltage problems. We can calculate the required amount of Energies 2021, 14, 992 power injection/curtailment for the DERs by considering line losses and voltage drops in the distribution lines This method can be applied to both radial and mesh networks. The EMS for the DC microgrid (MG-EMS) communicates with the other entities in the DC microgrid via an ethernet connection, which allows the MG-EMS to monitor and control the charging and discharging actions of a connected EV battery, as well as the PV power generation and/or the load shedding
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