Optimization of a Micro Grid Operation under Uncertainty Using Model Predictive Controller

International Journal of Research and Innovation in Applied Science (IJRIAS) | Volume VI, Issue VI, June 2021|ISSN 2454-6194

Optimization of a Micro Grid Operation under Uncertainty Using Model Predictive Controller

Bakare Kazeem¹, Ngang Bassey Ngang²*, Akaninyene Michael Joshua³, Ude Kingsley Okechukwu^4
1,²Department of Electrical and Electronic Engineering, Enugu State University of Science and Technology,(ESUT),Nigeria
^3,4Department of Electrical Engineering, Enugu State University of Science and Technology. (ESUT), Nigeria.
*Corresponding Author

Abstract-This paper presents the Optimization of a microgrid operation under Uncertainty using Model Predictive Controller. Instability in power supply in our society and the country at large has led to the liquidation of many establishments that solely depended on power for their daily activities. This instability in power supply observed in the country can be overcome by optimization of a microgrid operation under uncertainty using model predictive control. This was done in this manner, characterizing the microgrid operation, determining the threats in microgrid operation, designing a model predictive controller rule base that will eradicate the threats in microgrid operation thereby enhancing its operation, training ANN in this rule base for effective eradication of its operational threats thereby enhancing its operational efficiency, designing a Simulink model for optimization of a microgrid operation under uncertainty using model predictive control and validating and justifying the operational efficiency of a microgrid with and without MPC. The stability of the conventional approach occurred at a coordinate of (0.4, 5) through (0.4, 10), while that of using fuzzy controller occurred at a coordinate of (1.109, 5) through (1.109, 5). On the other hand using ANN controller stabilities at coordinates of (1.16, 5) through (1.16, 5) and that when MPC is used stabilizes at a coordinate of (1.223, 5) through (1.223, 5). With these results, it showed that optimization of a microgrid operation under uncertainty using model predictive control (MPC) gave the highest power system stability when compared with the other three like conventional, fuzzy, and Artificial Neural Network (ANN).

Keyword-optimization, microgrid, operation, Uncertainty, model predictive controller

I.INTRODUCTION

Optimization of a micro grid under uncertain situations using a Model predictive controller is considered in this work. The advent of micro-grids has more advantages when combining rapidly growing renewable energies the stochastic nature of renewable energies and variable power demand have created many challenges like unstable voltage/frequency and complicated power management and interaction with the utility grid. The research and development success made Recently about predictive control with its fast transient response and flexibility to accommodate different constraints has facilitated the implementation in a wider scale of the adoption of the model called predictive control (MPC) in individual and interconnected micro grids, including both converter-level and grid-level control strategies applied to three

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