Real-Time Framework for Energy Management System of a Smart Microgrid Using Multiagent Systems

Netto, Roberto S.; Ramalho, Guilherme; Bonatto, Benedito Donizeti; Carpinteiro, O.A.S.; Souza, Antônio Carlos Zambroni de; Oliveira, Denisson Q.; Braga, Rodrigo Aparecido da Silva

doi:10.20944/preprints201801.0113.v1

Cited by 9 publications

(5 citation statements)

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“…Furthermore MAS based control schemes for MG are found to be effective [30,31]. A real time framework for SMG control using MAS is presented in [32]. These studies clearly outline that the synchronization and coordination among agents are important issues in the shared and connected information power infrastructure.…”

Section: Literature Overviewmentioning

confidence: 94%

A multi-agent system approach for optimal microgrid expansion planning under uncertainty

Mishra¹,

Bordin²,

Tomasgård³

et al. 2019

International Journal of Electrical Power & Energy Systems

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Power system planning for modern distribution networks is undergoing a change because of distributed power generation and grid ancillary services. The vast electricity retail utility industry with many distribution network operators plans generation and transmission expansion planning for determining optimal investment decisions. This paper addresses this planning problem in a decentralized and distributed context.This paper introduces a coordinated decision making approach for optimal investments in generation and transmission expansion planning problems for distribution networks. The distribution networks are further classified into microgrids. Considering an agent as the functional information exchanging entity just like an energy meter with the objective to coordinate the expansion decisions of participants; a novel math-heuristic optimization model Coordinated Microgrid is presented. To simulate the coordination of information a multi-agent-system based coordinated decision making method is adopted and the value of coordination is investigated. The evolutionary vertical sequencing protocol, a heuristic method, is developed and implemented to simulate the coordination process among agents on the top level. The proposed protocol produces smart permutations of microgrids for coordination. On the bottom level, a two-stage chance-constrained stochastic MILP formulation for investment decisions with operational uncertainties is modelled. For market clearing a nodal-pricing scheme is adopted that maintains the Nash equilibrium among and across the microgrids for energy transactions. The proposed model is tested with consumption, network configuration data from three islands in west-coast of Norway. The models are solved to optimality and results lead to the observations that the value of coordination lies in profit increment of individual microgrid. The novel protocol proposed demonstrates an advantage of retrieving smart permutations from combinations of microgrids. In summary, CoMG is a novel expansion planning model for optimal investments in modern power distribution networks.

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Section: Literature Overviewmentioning

confidence: 94%

A multi-agent system approach for optimal microgrid expansion planning under uncertainty

Mishra¹,

Bordin²,

Tomasgård³

et al. 2019

International Journal of Electrical Power & Energy Systems

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“…Papers about GTEP problems in distribution network have been divided into two categories: the use of centralized [13][14][15][16][17] and decentralized [18][19][20][21][22][23][24][25] management in planning problem. Centralized planning is based on the central planner's viewpoint.…”

Section: Mgs In Distribution Gridmentioning

confidence: 99%

“…Operational costs are summed over stochastic scenarios s multiplied by their probabilities Ω s . The decisions to meet the demand ds were restricted to be higher than or equal to the probability of meeting the demand Ω dem in all scenarios S in Equation (25). Each SMG should always satisfy self-sufficiency limit.…”

Section: Modeling Of Objective Functionmentioning

confidence: 99%

Multi‐agent decentralized microgrids planning considering long‐term demand response model

Nemati

Hosseini

2021

Intl J of Energy Research

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Demand-side management resources, such as demand response programs (DRPs) are useful options for the reduction of energy cost according to the viewpoint of department of energy. Utilizing these resources in long-term studies like generation and transmission expansion planning (GTEP) needs longterm modeling. In this article, the GTEP was developed considering long-term model of DRPs using a cooperative game theory approach to minimize the total cost of microgrids (MGs). A two-level decision-making method was used to develop this model. On the top level, investment decisions were cooperatively made by MGs and a stochastic chance-constrained mixed integer linear programming formulation was modeled for investment decisions with operational uncertainties on the bottom level. The self-sufficiency index was also considered that guarantees supply of sensitive loads in islanding mode. Effec-

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“…In decision making, by cognitive intelligence conducts and altering the environment freely (might be either online/offline), while in actions, arrangements of the agents affect the system either by software or hardware actions, which work together and will lead to achieving a comprehensive global objective. MAS has been widely used for integration of power systems, power system reconfiguration, restoration, and management of electrical power in MGs [40,41].…”

Section: Advanced Energy Management System For the Dmgmentioning

confidence: 99%

Architecture of a Microgrid and Optimal Energy Management System

Khan¹,

Wang²,

Xiong³

et al. 2020

Multi Agent Systems - Strategies and Applications

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With the growing population trends, the demand for electricity is accelerating rapidly. The policy planners and developers have great focus to utilize renewable energy resources (RERs) to encounter the scarcity of energy since they offer benefits to the environment and power systems. At present, the energy generation is evolving into a smart distribution system that assimilates several energy resources assuring to generate clean energy, to have reliable operational procedures, and to enhance the energy supervision and management arrangements. Therefore, the model of a distributed microgrid (DMG) with optimal energy management strategies based on multi-agent systems (MASs) technique has been focused in this chapter. Distributed energy resources (DER) have been considered for the generation of electrical power to fulfill the consumer's load demands. Thus, a fully controlled architecture of a grid along with concept of MAS and its development platforms, implementation, and operational procedures have been discussed in detail. In addition, agent's operations and their coordination within the MG arrangements have been focused by considering the supervision of the entire system autonomously. Moreover, optimal procedures of a microgrid (MG) energy supervision and power distribution system have also been presented considering the cost control and optimal operations of the entire MG at the distributed level.

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Real-Time Framework for Energy Management System of a Smart Microgrid Using Multiagent Systems

Cited by 9 publications

References 0 publications

A multi-agent system approach for optimal microgrid expansion planning under uncertainty

A multi-agent system approach for optimal microgrid expansion planning under uncertainty

Multi‐agent decentralized microgrids planning considering long‐term demand response model

Architecture of a Microgrid and Optimal Energy Management System

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