S. M. Hoseini, N. Vasegh, A. Zangeneh,
Volume 16, Issue 2 (6-2020)
Abstract
In this paper, a robust local controller has been designed to balance the power for distributed energy resources (DERs) in an islanded microgrid. Three different DER types are considered in this study; photovoltaic systems, battery energy storage systems, and synchronous generators. Since DER dynamics are nonlinear and uncertain, which may destabilize the power system or decrease the performance, distributed robust nonlinear controllers are designed for the DERs. They are based on the Lyapunov stabilization theory and super-twisting integral sliding mode control which guarantees system stability and optimality simultaneously. The reference signals for each DER are generated by a supervisory controller as a power management system. The controllers proposed in this work are robust, have fast response times, and most importantly, the control signals satisfy physical system constraints. The designed controller stability and effectiveness are also verified using numerical simulations.
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.
