A. Karimpour, A. M. Amani, M. Karimpour, M. Jalili,
Volume 17, Issue 4 (12-2021)
Abstract
This paper studies the voltage regulation problem in DC microgrids in the presence of variable loads. DC microgrids generally include several Distributed Generation Units (DGUs), connected to electrical loads through DC power lines. The variable nature of loads at each spot, caused for example by moving electric vehicles, may cause voltage deregulation in the grid. To reduce this undesired effect, this study proposes an incentive-based load management strategy to balance the loads connected to the grid. The electricity price at each node of the grid is considered to be dependent on its voltage. This guide moving customers to connect to cheaper connection points, and ultimately results in even load distribution. Simulations show the improvement in the voltage regulation, power loss, and efficiency of the grid even when only a small portion of customers accept the proposed incentive.
Vahid Bagheri, Amir Farhad Ehyaei, Mohammad Haeri,
Volume 18, Issue 4 (12-2022)
Abstract
In distribution networks, failure to smooth the load curve leads to voltage drop and power quality loss. In this regard, electric vehicle batteries can be used to smooth the load curve. However, to persuade vehicle owners to share their vehicle batteries, we must also consider the owners' profits. A challenging problem is that existing methods do not take into account the vehicle owner demands including initial and final states of charge and arrival and departure times of vehicles. Another problem is that battery capacity of each vehicle varies depending on the type of vehicle; which leads to uncertainties in the charging and discharging dynamics of batteries. In this paper, we propose a modified mean-field method so that the load curve is smoothed, vehicle owner demands are met, and different capacities of electric vehicle batteries are considered. The simulation results show the effectiveness of the proposed method.
Nasreddine Attou, Sid-Ahmed Zidi, Samir Hadjeri, Mohamed Khatir,
Volume 19, Issue 3 (9-2023)
Abstract
Demand-side management has become a viable solution to meet the needs of the power system and consumers in the past decades due to the problems of power imbalance and peak demand on the grid. This study focused on an improved decision tree-based algorithm to cover off-peak hours and reduce or shift peak load in a grid-connected microgrid using a battery energy storage system (BESS), and a demand response scheme. The main objective is to provide an efficient and optimal management strategy to mitigate peak demand, reduce the electricity price, and replace expensive reserve generation units. The developed algorithm is evaluated with two scenarios to see the behavior of the management system throughout the day, taking into account the different types of days (weekends and working days), the random profile of the users' demand, and the variation of the energy price (EP) on the grid. The simulation results allowed us to reduce the daily consumption by about 30% to 40% and to fill up to 12% to 15% of the off-peak hours with maximum use of renewable energies, demonstrating the control system's performance in smoothing the load curve.
