An Innovative Stochastic Multi-Agent-Based Energy Management Approach for Microgrids Considering Uncertainties

In microgrids a major share of the energy production comes from renewable energy sources such as photovoltaic panels or wind turbines. The intermittent nature of these types of producers along with the fluctuation in energy demand can destabilize the grid if not dealt with properly. This paper presents a multi-agent-based energy management approach for a non-isolated microgrid with solar and wind units and in the presence of demand response, considering uncertainty in generation and load. More specifically, a modified version of the lightning search algorithm, along with the weighted objective function of the current microgrid cost, based on different scenarios for the energy management of the microgrid, is proposed. The probability density functions of the solar and wind power outputs, as well as the demand of the households, have been used to determine the amount of uncertainty and to plan various scenarios. We also used a particle swarm optimization algorithm for the microgrid energy management and compared the optimization results obtained from the two algorithms. The simulation results show that uncertainty in the microgrid normally has a significant effect on the outcomes, and failure to consider it would lead to inaccurate management methods. Moreover, the results confirm the excellent performance of the proposed approach.

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A Critical Assessment of Demand Response Programs Applied for Optimal Energy Management in Microgrids

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b1123.0782s719 ◽

2019 ◽

Vol 8 (2S7) ◽

pp. 344-349

Keyword(s):

Energy Management ◽

Demand Response ◽

Power Flow ◽

Renewable Energy Sources ◽

Weather Condition ◽

Optimal Energy ◽

Autonomous Mode ◽

Optimal Energy Management ◽

Demand Response Programs ◽

Microgrid Energy Management

Microgrid Energy Management is done to optimize microgrid performance. Power from Wind Turbines (WT) and Photo Voltaic (PV) modules into a microgrid addresses both factors of environmental concerns as well as sustainable energy production. Point of coupling with utility main grid is disconnected when microgrid functions in autonomous mode and it enhances steady microgrid operation when traditional grids face blackouts. Clean and renewable energy sources being easily affected by variation in weather condition, so taking into account of this uncertainty is essential while formulating power flow problem which can be done through demand response programs. This paper aims to investigate results obtained from research of several researchers scrutinizingly and analyzed critically for optimal energy management in microgrids using demand response programs. This paper also highlights the worthy findings of possible areas of research that would enhance the use of demand side management through demand response programs in microgrids.

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Multi-agent based distributed control architecture for microgrid energy management and optimization

Energy Conversion and Management ◽

10.1016/j.enconman.2016.01.011 ◽

2016 ◽

Vol 112 ◽

pp. 288-307 ◽

Cited By ~ 92

Author(s):

M. Reyasudin Basir Khan ◽

Razali Jidin ◽

Jagadeesh Pasupuleti

Keyword(s):

Energy Management ◽

Distributed Control ◽

Control Architecture ◽

Agent Based ◽

Multi Agent ◽

Microgrid Energy Management

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A Review of DC Microgrid Energy Management Systems Dedicated to Residential Applications

Energies ◽

10.3390/en14144308 ◽

2021 ◽

Vol 14 (14) ◽

pp. 4308

Author(s):

Sadaqat Ali ◽

Zhixue Zheng ◽

Michel Aillerie ◽

Jean-Paul Sawicki ◽

Marie-Cécile Péra ◽

...

Keyword(s):

Energy Management ◽

Energy Demand ◽

High Efficiency ◽

Renewable Energy Sources ◽

Storage System ◽

Positive Development ◽

Extensive Literature ◽

Dc Microgrid ◽

Dc Microgrids ◽

Microgrid Energy Management

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.

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Multi-agent based simulation for Microgrid energy management

8th International Conference on Power Electronics - ECCE Asia ◽

10.1109/icpe.2011.5944680 ◽

2011 ◽

Cited By ~ 4

Author(s):

Mao Meiqin ◽

Dong Wei ◽

Liuchen Chang

Keyword(s):

Energy Management ◽

Agent Based Simulation ◽

Agent Based ◽

Multi Agent ◽

Microgrid Energy Management

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Intelligent Control of Battery Energy Storage for Multi-Agent Based Microgrid Energy Management

Energies ◽

10.3390/en6104956 ◽

2013 ◽

Vol 6 (10) ◽

pp. 4956-4979 ◽

Cited By ~ 33

Author(s):

Cheol-Hee Yoo ◽

Il-Yop Chung ◽

Hak-Ju Lee ◽

Sung-Soo Hong

Keyword(s):

Energy Storage ◽

Energy Management ◽

Intelligent Control ◽

Battery Energy Storage ◽

Agent Based ◽

Multi Agent ◽

Battery Energy ◽

Microgrid Energy Management

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Multi-objective energy management in microgrids with hybrid energy sources and battery energy storage systems

Protection and Control of Modern Power Systems ◽

10.1186/s41601-019-0147-z ◽

2020 ◽

Vol 5 (1) ◽

Cited By ~ 25

Author(s):

V. V. S. N. Murty ◽

Ashwani Kumar

Keyword(s):

Renewable Energy ◽

Energy Storage ◽

Energy Management ◽

Demand Response ◽

Renewable Energy Sources ◽

Energy Sources ◽

Optimal Energy ◽

Simulation Results ◽

Battery Energy ◽

Microgrid Energy Management

AbstractMicrogrid with hybrid renewable energy sources is a promising solution where the distribution network expansion is unfeasible or not economical. Integration of renewable energy sources provides energy security, substantial cost savings and reduction in greenhouse gas emissions, enabling nation to meet emission targets. Microgrid energy management is a challenging task for microgrid operator (MGO) for optimal energy utilization in microgrid with penetration of renewable energy sources, energy storage devices and demand response. In this paper, optimal energy dispatch strategy is established for grid connected and standalone microgrids integrated with photovoltaic (PV), wind turbine (WT), fuel cell (FC), micro turbine (MT), diesel generator (DG) and battery energy storage system (ESS). Techno-economic benefits are demonstrated for the hybrid power system. So far, microgrid energy management problem has been addressed with the aim of minimizing operating cost only. However, the issues of power losses and environment i.e., emission-related objectives need to be addressed for effective energy management of microgrid system. In this paper, microgrid energy management (MGEM) is formulated as mixed-integer linear programming and a new multi-objective solution is proposed for MGEM along with demand response program. Demand response is included in the optimization problem to demonstrate it’s impact on optimal energy dispatch and techno-commercial benefits. Fuzzy interface has been developed for optimal scheduling of ESS. Simulation results are obtained for the optimal capacity of PV, WT, DG, MT, FC, converter, BES, charging/discharging scheduling, state of charge of battery, power exchange with grid, annual net present cost, cost of energy, initial cost, operational cost, fuel cost and penalty of greenhouse gases emissions. The results show that CO2 emissions in standalone hybrid microgrid system is reduced by 51.60% compared to traditional system with grid only. Simulation results obtained with the proposed method is compared with various evolutionary algorithms to verify it’s effectiveness.

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A Survey on Microgrid Energy Management Considering Flexible Energy Sources

Energies ◽

10.3390/en12112156 ◽

2019 ◽

Vol 12 (11) ◽

pp. 2156 ◽

Cited By ~ 27

Author(s):

Hossein Shayeghi ◽

Elnaz Shahryari ◽

Mohammad Moradzadeh ◽

Pierluigi Siano

Keyword(s):

Energy Management ◽

Renewable Energy Sources ◽

Uncertainty Modeling ◽

Optimization Techniques ◽

Point Of View ◽

Energy Sources ◽

Market Prices ◽

Distributed Generations ◽

Peak Loads ◽

Microgrid Energy Management

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.

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An Intelligent Multi Agent based Approach for Autonomous Energy Management in a Microgrid

Electric Power Components and Systems ◽

10.1080/15325008.2021.1937390 ◽

2021 ◽

pp. 1-14

Author(s):

Sujil Areekkara ◽

Rajesh Kumar ◽

Ramesh C Bansal

Keyword(s):

Energy Management ◽

Agent Based ◽

Multi Agent

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Energy Management System for Hybrid Microgrids

Electrotehnica, Electronica, Automatica ◽

10.46904/eea.21.69.2.1108003 ◽

2021 ◽

Vol 69 (2) ◽

pp. 21-30

Author(s):

Nasreddine ATTOU ◽

Sid-Ahmed ZIDI ◽

Mohamed KHATIR ◽

Samir HADJERI

Keyword(s):

Energy Management ◽

Electricity Market ◽

Management System ◽

Energy Demand ◽

Renewable Energy Sources ◽

Supply And Demand ◽

Energy Sources ◽

Variable Load ◽

Energy Management System ◽

Price Variation

Energy management in grid-connected Micro-grids (MG) has undergone rapid evolution in recent times due to several factors such as environmental issues, increasing energy demand and the opening of the electricity market. The Energy Management System (EMS) allows the optimal scheduling of energy resources and energy storage systems in MG in order to maintain the balance between supply and demand at low cost. The aim is to minimize peaks and fluctuations in the load and production profile on the one hand, and, on the other hand, to make the most of renewable energy sources and energy exchanges with the utility grid. In this paper, our attention has been focused on a Rule-based energy management system (RB EMS) applied to a residential multi-source grid-connected MG. A Microgrid model has been implemented that combines distributed energy sources (PV, WT, BESS), a number of EVs equipped with the Vehicle to Grid technology (V2G) and variable load. Different operational scenarios were developed to see the behaviour of the implemented management system during the day, including the random demand profile of EV users, the variation in load and production, grid electricity price variation. The simulation results presented in this paper demonstrate the efficacy of the suggested EMS and confirm the strategy's feasibility as well as its ability to properly share power among different sources, loads and vehicles by obeying constraints on each element.

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