This paper proposes a hybrid control method based on model predictive control (MPC) and
iterative learning control (ILC) for the hybrid energy storage system (HESS) in the …

Managing natural resources and air pollution has been challenging for humans for quite a
long time. A severe manifestation of natural resource mismanagement has been in the form …

Distributed generators have been widely used in modern power systems, and microgrids are
becoming a key concept for the integration of multiple distributed generators and clusters of …

Model predictive control (MPC) based on long prediction horizons can address the inherent
nonminimum phase (NMP) behavior issue of dc/dc boost converters. However, the response …

In islanding microgrids, supercapacitors (SCs) are used to compensate the transient power
fluctuation caused by sudden variations of load demand and generation power to keep the …

The rapid growth of energy demand requires progressive energy generation. This, together
with the demand for higher efficiency and flexibility, has promoted the application of power …

This article proposes an easily implementable and computationally effective model
predictive control (MPC) scheme for fuel cell dc–dc boost converter. The proposed control …

Finite control set model predictive control (FCS-MPC) has been widely used in the control of
power converters. However, for converters with multiple optimization objectives, the design …

A smart home power management system is critical for stand-alone home-photovoltaic
(HPV) with battery energy storage. Existing approaches often focus on maximizing power …

This paper presents a novel station manager algorithm for grid-connected PV-EV charging
stations, designed to address key challenges in current systems. Existing charging stations …