Abstract
The design and implementation of appropriate advanced control strategies is a key factor for the effective integration of micro-grids into the electrical network. In view of this, the study proposes an Adaptive Model-Based Horizon Control technique in the bid to addressing issues related to the Energy Management System in micro-grid operations. The main objective of the energy management system is to balance energy generation and demand through energy storage, so as to optimize the operation of the micro-grid with high penetrations of renewable energy sources. This paper further investigates the impacts of considering the prediction of disturbances on the performance of the Energy Management System based on the adaptive model predictive control algorithm in order to improve the operating costs of the micro-grid with hybrid-energy storage systems. The adaptive model predictive control algorithm solves the energy optimization problem in a renewable energy-based micro-grid with various types of energy storage systems that exchange energy with the host grid. More so, this optimization problem is resolved at each sampling period in order to determine the minimum running costs while satisfying demand and taking into account technical and physical constraints. The simulation results under different conditions have demonstrated how the use of an adaptive model predictive control based energy management system can enhance micro-grid operation, provided there is effective forecasting, and consequently minimized the running operating costs of micro-grid. More so, it is evident in the cost function, J, obtained from the three scenarios conducted, that the perfect knowledge of the disturbance prediction is essential for effective micro-grid operations.
Highlights
We solved the Energy Management System (EMS)-based energy optimization problem in a renewable energy micro-grid, which comprises of generation sources (Photovoltaic, PV, Wind turbine, WT), lead-acid battery, fuel cell, Proton Exchange Membrane (PEM) electrolyser, and an external grid using the adaptive model predictive control (AMPC) control algorithm
The simulations, show how the AMPC was able to adjust to different scenarios, offering a reasonable solution for power-sharing among the DERs and taking into account both the physical and operational constraints and the optimization of the operational criteria imposed on it
This study has demonstrated how the use of an AMPC-based EMS can enhance micro-grid operation, provided there is effective forecasting
Summary
A careful review of the previous studies shows that, despite the use of MPCs in energy systems and industries [5], the consideration of measurable disturbance as well as an appropriate control technique, which is of great importance in addressing all the prevailing uncertainties of micro-grid operation, has not been extensively discussed. An advanced control strategy was proposed in this study, i.e., an Adaptive Model-Based Receding Horizon Control technique, mainly for the effective integration of micro-grids into the electrical network; permits the integration of the information on the disturbances prediction, improves the system flexibility and operational reliability and address issues related to the Energy Management System (EMS) in micro-grid operations. The impact of considering the prediction of disturbances on the performance of the Energy Management System (EMS) based on the Adaptive Model Predictive Control (AMPC) algorithm to improve the operating costs of the micro-grid with hybrid-energy storage systems was investigated.
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