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Data-driven optimization framework for microgrid energy management
Book chapter

Data-driven optimization framework for microgrid energy management

Mohamed Atef, Moslem Uddin, Md Masud Rana, Md Rasel Sarkar and G.M. Shafiullah
Intelligent Data-Driven Modelling and Optimization in Power and Energy Applications, pp.169-188
CRC Press, 1st
2024

Abstract

This study present a data-driven optimization framework for microgrid energy management (MEM). The framework considered demand response (DR) and uncertainties in power generation. The framework aims to improve the energy efficiency and reliability of microgrid (MG) operation by optimizing the use of energy resources. To assess the efficacy of the proposed energy management (EM) framework, several performance metrics are used. The obtained results are compared between scenarios with and without the EM strategy implementation. The findings indicate a significant decrease in fuel usage while implementing the EM approach, without encountering any unfulfilled load or capacity shortage. Investigation demonstrates that MG integrated with EM has a fuel consumption rate of 80,594 L/yr, in contrast to the absence of EM, the MG consumes 94,673 L/yr. The findings further verify the efficient utilization of excess electricity through the implementation of the EM strategy, which resulted in minimal wastage of only 0.293% compared to 2.383% in the MG lacking EM. Results indicate that the utilisation of EM leads to increased incorporation of renewable energy sources (RESs) within the MG. The proposed EM framework shows potential as a viable solution for improving the energy efficiency and reliability in MGs.

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UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

#7 Affordable and Clean Energy

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