A Survey on Microgrid Energy Management Considering Flexible Energy Sources

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.

Optimal Management of the Energy Flows of Interconnected Residential Users

“…In the last few years, several EMS approaches were investigated. For example, Shayeghi et al [25] classified EMSs as (i) nonrenewable based, (ii) energy storage system based, (iii) demand-side management based and (iv) hybrid system based. Instead, Dehghanpour et al [26] identified three different categories, namely centralized, distributed and hybrid control.…”

Hierarchical Energy Management System for Microgrid Operation Based on Robust Model Predictive Control

“…An important aspect for optimal EMSs is uncertainty-in this case of the prediction profiles of available renewable energy and end-user consumption [19]. One common paradigm for handling uncertainty is robust optimization, which uses uncertainty sets and combines a worst-case analysis with min-max formulations to obtain optimal solutions that are robust against variations in a parameter with respect to a nominal value (optimal worst-case scenario) [20].…”

Distributed Ledger Technologies for Peer-to-Peer Local Markets in Distribution Networks

“…This is due to the development of strategic policies and regulations, such as market liberalization and decarbonization plans, that are stimulating the decommissioning of large fossil fuel-powered power plants, and the adoption of local measures for grid management [2,3] that are capable of better integrating the deployment of renewable sources. Therefore, the future power system requires the exploitation of the flexibility offered by all of the involved parties to obtain a reliable and cost-effective power supply [1,5,6]. However, a paradigmatic change of the power system operation from a top-down to a bottom-up approach implies a shift in responsibilities from centralized authorities towards decentralized entities, encouraging the interaction of all the grid users.…”