Microgrid is a combination of distributed generators, storage systems, and controllable loads connected to low-voltage network that can operate either in grid-connected or in island mode. High penetration of power at distribution level creates such multiple microgrids. This paper proposes a two-level architecture for distributed-energy-resource management for multiple microgrids using multiagent systems. In order to match the buyers and sellers in the energy market, symmetrical assignment problem based on naive auction algorithm is used. The developed mechanism allows the pool members such as generation agents, load agents, auction agents, grid agents, and storage agents to participate in market. Three different scenarios are identified based on the supply-demand mismatch among the participating microgrids. At the end of this paper, two case studies are presented with two and four interconnected microgrids participating in the market. Simulation results clearly indicate that the agent-based management is effective in resource management among multiple microgrids economically and profitably.

Multiagent-Based Distributed-Energy-Resource Management for Intelligent Microgrids

Multi-agent systems applied for energy systems integration: State-of-the-art applications and trends in microgrids

In recent years with penetration of distributed energy sources in power systems and generation of electricity from them, controlling the stability of network has become more complicated. In this respect, different works have shown a tendency to use different methodologies to simplify the control of network stability. Nowadays, engineers divide the distribution system to many subsystems, which are called microgrid. A microgrid works in two modes: grid-connected and island mode, which require methods to control. The control methods can be divided into two forms, with communication and without communication. This paper is a short survey on controlling microgrids with distributed renewable energy resources particularly in island mode and discusses Multi-agent systems and droop characteristics.

/pdf/a-review-on-microgrid-control-techniques-55tncfrqw7.pdf

A review on microgrid control techniques

The application of Multi-Agent Systems (MAS) in electrical power systems are becoming popular due to their inherent benefits such as increased autonomy, reactivity, proactivity and social ability. This paper reviews current research on the application of multi-agent systems in microgrid schemes. The paper is mainly focused on recent developments of multi-agent systems in different aspects of microgrids such as control, market modeling, optimization and power restoration. The future directions of multi-agent systems in microgrid applications are also discussed briefly. Furthermore, this review is concluded by discussing the development of an enhanced multi-agent based distributed control framework for microgrids.

A review on multi-agent systems in microgrid applications

The objective of this paper is to design, develop and implement a multi-agent system (MAS) that provides intelligent and enables real-time management to a smart grid located at a distribution level (so called distributed smart grid). The MAS application development is discussed concerning suitable agent development framework, agent specification, agent architecture, and implementation of MAS. The paper illustrates MAS application in power systems. As faults and outages are inevitable and likely to occur in distribution systems, an efficient and fast switching operation scheme is required to detect the fault location, isolate the fault, and restore power to de-energized areas. The system under study consists of both physical (microgrid) and cyber elements (MAS). Finally, the simulation result indicates that the developed MAS for power system restoration applications can provide an effective and timely solution to manage microgrid given the existence of fault in the system.

A multi-agent based power system restoration approach in distributed smart grid

Distributed generation (DG) injects new vigor into the power system, but it sometimes brings unfavorable factors influencing the power quality of distribution network. In this paper, the Dynamic Voltage Restorer (DVR) is introduced to the distribution network to improve the power quality. In view of that the detection of voltage compensation is the key factor that influences the effect of voltage compensation, a voltage direct detection method based on mathematical morphology is proposed. Firstly, the positive-sequence voltage with harmonics can be extracted by the instantaneous sequence-component decomposer. And then the harmonics is filtered by mathematical morphology filter. Lastly, the control variable of voltage compensation needed by DVR can be calculated from the voltage direct-detecting algorithm. The simulation results show that this method has the characteristics of favorable accuracy, real-time performance and simplicity, and assures the voltage quality of load side after compensation by DVR.

http://ieeexplore.ieee.org/iel5/5508196/5514667/05515726.pdf

The application of voltage direct detection method based on mathematical morphology in distribution network with DG

Considering the operation of microgrids (MGs) composed of distributed generations (DGs) and loads, a service restoration model aiming at the restoration of the most load with giving priority to the important load power supply is built. On the basis of the proposed hierarchical control strategy, this paper builds up a multi-agent system (MAS) for service restoration of microgrid. Accordingly, the special functions and control strategies of each agent are discussed in detail. A simulation example of a particular microgrid based on the multi-agent system is performed to demonstrate that the efficiency and reliability of the microgrid can be improved by using MAS.

Multi-agent approach for service restoration of microgrid

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The application of voltage direct detection method based on mathematical morphology in distribution network with DG

Multi-agent approach for service restoration of microgrid