Hierarchical MAS Based Control Strategy for Microgrid

Xiao, Zhe; Li, Tinghua; Huang, Minjuan; Ji-hong, Shi; Yang, Jingjing; Jiang, Yu; Wu, Wei

doi:10.3390/en3091622

Cited by 55 publications

(41 citation statements)

References 24 publications

(20 reference statements)

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“…One of the most important inputs to this DI scenario is the disaggregated load forecasting, which allows smart elements in the grid to react in advance to the demand. Microgrids use techniques with Multi-Agent Systems for island mode operation [6,7] and for strategic control [8]. Similarly, [9] present a new nonintrusive energy monitoring method using ANN.…”

Section: New Distributed Intelligence Elements In the Gridmentioning

confidence: 99%

Short-Term Load Forecasting for Microgrids Based on Artificial Neural Networks

et al. 2013

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Received : 28 November 2012; in revised form: 18 February 2013 / Accepted: 20 February 2013 / Published: 5 March 2013 Abstract: Electricity is indispensable and of strategic importance to national economies. Consequently, electric utilities make an effort to balance power generation and demand in order to offer a good service at a competitive price. For this purpose, these utilities need electric load forecasts to be as accurate as possible. However, electric load depends on many factors (day of the week, month of the year, etc.), which makes load forecasting quite a complex process requiring something other than statistical methods. This study presents an electric load forecast architectural model based on an Artificial Neural Network (ANN) that performs Short-Term Load Forecasting (STLF). In this study, we present the excellent results obtained, and highlight the simplicity of the proposed model. Load forecasting was performed in a geographic location of the size of a potential microgrid, as microgrids appear to be the future of electric power supply.

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Section: New Distributed Intelligence Elements In the Gridmentioning

confidence: 99%

Short-Term Load Forecasting for Microgrids Based on Artificial Neural Networks

et al. 2013

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“…The main functions of the agent are described as follows:  Detect power imbalance and collect operation and control data;  Exchange data with neighbors for distributed information processing;  Discover the global information including the active total power imbalance P IB as in Equation (13) the total cost coefficient K T F as in Equation (10) and the total amount of flexible loads C T FL as in Equation (11);  Make local evaluation of the cost index as in Equation (10), the capacity index as in Equation (11) and comprehensive weight as in Equation (12).…”

Section: Flowchart Of the Proposed Multiagent-based Distributed Load mentioning

confidence: 99%

“…Thus, the distributed scheme seems like a better solution for the islanded microgrids [10]. Multiagent system is one of the most popular solutions for distributed load shedding [11][12][13]. The multiagent-based distributed load shedding schemes have been studied to maintain the supply-demand balance of an islanded microgrid [14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Multiagent-Based Distributed Load Shedding for Islanded Microgrids

Jiang

Jing

2014

Energies

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This paper addresses a multiagent-based distributed load shedding scheme to restore frequency for the microgrids during islanded operation. The objective of the proposed scheme is to realize a distributed load shedding considering its associated cost and the capacity of the flexible loads. There are two advantages of the proposed scheme: (1) it is a distributed scheme using average-consensus theorem, which can discover the global information when only communications between immediate neighboring agents are used, moreover it can meet the requirements of plug-and-play operations more easily than a centralized scheme; (2) it is a new adaptive load shedding through the comprehensive weights which take into accounts the cost of load shedding and the capacity of flexible loads, these comprehensive weights are evaluated locally by making use of the adaptability and intelligence characteristics of agents. Simulation results in power systems computer aided design (PSCAD) illustrate the validity and adaptability of the proposed load shedding scheme.

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“…Since Professor Lasseter proposed the concept of the microgrid in 2001 [1], many technologies such as power control [2][3][4][5], protection schemes [6,7], simulators, and field tests [8][9][10] for microgrids have been studied. In addition, multiagent system applications have been studied for efficient and economic control and operation of microgrids [11][12][13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

A Communication Framework in Multiagent System for Islanded Microgrid

Kim

Lim

2012

International Journal of Distributed Sensor Networks

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Microgrids are integrated energy systems consisting of interconnected loads and distributed energy sources which as a system can operate in parallel with the grid or in an island mode. By fault occurrence in the connected power system or geographical isolation, microgrids operate in the islanded mode. In the islanded mode, microgrids should be operated to meet a power balance between supply and demand without power trade. In recent years, multiagent systems have been proposed to provide intelligent energy control and management systems in microgrids. In this paper, we design a communication framework to control and operate distributed sources and loads in the islanded microgrids. The framework reliably delivers microgrid control frame between agents by employing wireless mesh network as an advanced topology of the wireless sensor network. From results of experiments, we show that our framework outperforms other conventional one, with respect to the rate of success on the transmission of frames among agents.

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Hierarchical MAS Based Control Strategy for Microgrid

Cited by 55 publications

References 24 publications

Short-Term Load Forecasting for Microgrids Based on Artificial Neural Networks

Short-Term Load Forecasting for Microgrids Based on Artificial Neural Networks

Multiagent-Based Distributed Load Shedding for Islanded Microgrids

A Communication Framework in Multiagent System for Islanded Microgrid

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