Abstract

The fast depletion of fossil fuels and the growing awareness of the need for environmental protection have led us to the energy crisis. Positive development has been achieved since the last decade by the collective effort of scientists. In this regard, renewable energy sources (RES) are being deployed in the power system to meet the energy demand. The microgrid concept (AC, DC) is introduced, in which distributed energy resources (DERs), the energy storage system (ESS) and loads are interconnected. DC microgrids are appreciated due to their high efficiency and reliability performance. Despite its significant growth, the DC microgrid is still relatively novel in terms of grid architecture and control systems. In this context, an energy management system (EMS) is essential for the optimal use of DERs in secure, reliable, and intelligent ways. Therefore, this paper strives to shed light on DC microgrid architecture, control structure, and EMS. With an extensive literature survey on EMSs’ role, different methods and strategies related to microgrid energy management are covered in this article. More attention is centered on the EMS for DC microgrids in terms of size and cost optimization. A very concise analysis of multiple optimization methods and techniques has been presented exclusively for residential applications.

Highlights

  • The global energy demand exponentially increases as the world population rises

  • Pascual et al [12] proposed an energy management system (EMS) for a residential microgrid system consisting of PV panels, a wind turbine (WT), and a battery connected to the main grid

  • This paper has reviewed several critical issues regarding DC microgrids in residential applications, including their architecture design, communication technologies, control structure and EMS

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Summary

A Review of DC Microgrid Energy Management Systems

Sadaqat Ali 1, *, Zhixue Zheng 1, * , Michel Aillerie 1, * , Jean-Paul Sawicki 1 , Marie-Cécile Péra 2,3 and Daniel Hissel 2,3. FCLAB, Centre National de la Recherche Scientifique (CNRS), F-90010 Belfort, France

Introduction
Physical Architecture
Communication Technologies
Control Structure
Energy Management Based on Classical Methods
Iterative Algorithms
Linear Programming Methods
Stochastic and Robust Programming Methods
Model Predictive Control Methods
Energy Management Based on Artificial Intelligence Methods
Fuzzy Logic Methods
Neural Network Methods
Evolutionary Computation
Existing Software Tools and Sardware Components for Microgrid EMS
Software Tools
Hardware Components
Energy Management Strategies Analysis
Objective
Findings
Discussion
Conclusions
Full Text
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