No abstract

In this paper, a new approach is presented to solve the electric vehicle charging coordination (EVCC) problem considering Volt-VAr control, energy storage device (ESD) operation and dispatchable distributed generation (DG) available in threephase unbalanced electrical distribution networks (EDNs). Dynamic scheduling for the EVCC is proposed through a step-by-step methodology, which solves a mixed integer linear programming (MILP) problem for the whole time period. The objective is to minimize the total cost of energy purchased from the substation and DG units, the cost of energy curtailment on electric vehicles, the cost of energy injected from the ESDs, and the cost of energy curtailment on the ESDs. The Volt-VAr control considers the management of on-load tap changers, voltage regulators, and switchable capacitors installed along the grid. Furthermore, the formulation takes into account the voltage dependence of the loads, while the steady-state operation of the unbalanced distribution systems is modeled using linear constraints. The proposed model was tested in a 178-node three-phase unbalanced EDN considering a one-day time period. Index Terms-Electric vehicle charging coordination (EVCC) problem, energy storage devices (ESDs), mixed integer linear programming (MILP), Volt-VAr control, voltage-dependent load model.

No abstract

In the distribution system, customers have increasingly use renewable energy sources and battery energy storage systems (BESS), transforming traditional loads into active prosumers. Therefore, methodologies are needed to provide prosumers with tools to optimize their investments and increase business opportunities. In this paper, a stochastic mixed integer linear programming (MILP) formulation is proposed to solve for optimal sizes of prosumer assets, considering the use of a BESS and photovoltaic (PV) units. The objective is to minimize the total cost of the system, which is defined as the combination of a solar PV system investment, BESS investment, maintenance costs of assets, and the cost of electricity supplied by the grid. The developed method defines the optimal size of PV units, the power/energy capacities of the BESS, and the optimal value for initial energy stored in the BESS. Both deterministic and stochastic approaches were explored. For each approach, the proposed model was tested for three cases, providing a varying combination of the use of grid power, PV units, and BESS. The optimal values from each case were compared, showing that there is potential to achieve more economic plans for prosumers when PV and BESS technologies are taken into account.

No abstract