Abstract

Aggregation of distributed generations (DGs) along with energy storage systems (ESSs) and controllable loads near power consumers has led to the concept of microgrids. However, the uncertain nature of renewable energy sources such as wind and photovoltaic generations, market prices and loads has led to difficulties in ensuring power quality and in balancing generation and consumption. To tackle these problems, microgrids should be managed by an energy management system (EMS) that facilitates the minimization of operational costs, emissions and peak loads while satisfying the microgrid technical constraints. Over the past years, microgrids’ EMS have been studied from different perspectives and have recently attracted considerable attention of researchers. To this end, in this paper a classification and a survey of EMSs has been carried out from a new point of view. EMSs have been classified into four categories based on the kind of the reserve system being used, including non-renewable, ESS, demand-side management (DSM) and hybrid systems. Moreover, using recent literature, EMSs have been reviewed in terms of uncertainty modeling techniques, objective functions (OFs) and constraints, optimization techniques, and simulation and experimental results presented in the literature.

Highlights

  • There are strong incentives to utilize distributed generations (DGs) for reducing greenhouse gases, improving power system efficiency as well as its reliability, competitive energy policies and postponement of transmission and distribution system upgrading [1]

  • This paper provides the literature review of microgrid energy management system (EMS) by classifying the existing articles into four categories as follows: (1)

  • This paper provides a compendium on the modeling uncertainties associated with microgrid

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Summary

Introduction

There are strong incentives to utilize distributed generations (DGs) for reducing greenhouse gases, improving power system efficiency as well as its reliability, competitive energy policies and postponement of transmission and distribution system upgrading [1]. Microgrids often often face face difficulties difficulties in in supplying supplying demand demand due due to to the the lack lack of of sufficient sufficient energy energy generation sources. This obstacle is caused by intermittent nature of loads and renewable energy generation sources. (EMS) is is necessary necessary to tackle this this problem. Table [6,7,8,9,10,11,12,13].

Objective
Category 1
Category 2
Category 3
Category 4
Prediction
Prediction of Uncertain into the following two categories
Uncertainty Modeling
Stochastic Methods
Fuzzy Method
Robust Optimization Method
Mathematical Formulation of EMS
Objective Functions
Constraints
Optimization Techniques of a Microgrid Performed by an EMS
Mathematical Methods
SNOPT Solver
Gurobi Optimizer
Microgrid Test Systems
EMS Simulation Scenarios
Conclusions
Methods and Optimization
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