Multi-Agent System for Distributed Energy Microgrid: Simulation and Hardware-in-the-Loop Physical Model

The technology of intelligent Multi-Agent System (MAS) has radically altered the way in which complex, distributed, open systems are conceptualized. This chapter presents the application of multi-agent technology to design and deployment of a distributed, cross platform, secure multi-agent framework to model a restructured energy market, where multi players dynamically interact with each other to achieve mutually satisfying outcomes. Apart from the security implementations, some of the best practices in Artificial Intelligence (AI) techniques were employed in the agent oriented programming to deliver customized, powerful, intelligent, distributed application software which simulates the new restructured energy market. The AI algorithm implemented as a rule-based system yielded accurate market outcomes.

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Fuzzy-Based Multi-Agent System for Distributed Energy Management in Smart Grids

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems ◽

10.1142/s0218488516500355 ◽

2016 ◽

Vol 24 (05) ◽

pp. 781-803 ◽

Cited By ~ 8

Author(s):

Bharat Menon Radhakrishnan ◽

Dipti Srinivasan ◽

Rahul Mehta

Keyword(s):

Energy Management ◽

Smart Grids ◽

Test System ◽

Small Scale ◽

Multi Agent System ◽

Distributed Energy ◽

Agent System ◽

Renewable Sources ◽

Distributed Energy Management ◽

Multi Agent

Energy Management Systems have become an imperative aspect of smart grids, owing to the enormous challenges imposed due to real-time pricing, distributed generation and integration of intermittent renewables. Due to the uncertainty associated with renewable sources and prominent fluctuations in the load demand, it is extremely important to maintain the overall energy balance in such grids. In this paper, the distributed energy management is achieved using a Multi-agent System which provides a flexible and reliable solution to control and manage smart grids. Adaptive fuzzy systems are designed to instill intelligent decision making capability in the agents of multi-agent system. When renewable sources are inadequate, the sustainability of the system is not guaranteed and multi-agent system is capable of deciding the mode of operation such that the system reliability and performance is not compromised. The proposed algorithm maintains power balance in the system and also sustains desired values for the State of Charge of storage units in order to guarantee extended battery life. The Energy management system also implements a cost optimization algorithm based on the Particle Swarm Optimization technique, to minimize operating costs and maximize profits earned by the grid. The proposed energy management algorithm is tested and validated on a practical test system which inherits most of the features of a small-scale smart grid.

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Multi-Agent System with Plug and Play Feature for Distributed Secondary Control in Microgrid—Controller and Power Hardware-in-the-Loop Implementation

Energies ◽

10.3390/en11123253 ◽

2018 ◽

Vol 11 (12) ◽

pp. 3253 ◽

Cited By ~ 15

Author(s):

Tung-Lam Nguyen ◽

Efren Guillo-Sansano ◽

Mazheruddin Syed ◽

Van-Hoa Nguyen ◽

Steven Blair ◽

...

Keyword(s):

Frequency Control ◽

Test Case ◽

Hardware In The Loop ◽

Multi Agent System ◽

Centralized Control ◽

Secondary Control ◽

Plug And Play ◽

Agent System ◽

Promising Alternative ◽

Multi Agent

Distributed control and optimization strategies are a promising alternative approach to centralized control within microgrids. In this paper, a multi-agent system is developed to deal with the distributed secondary control of islanded microgrids. Two main challenges are identified in the coordination of a microgrid: (i) interoperability among equipment from different vendors; and (ii) online re-configuration of the network in the case of alteration of topology. To cope with these challenges, the agents are designed to communicate with physical devices via the industrial standard IEC 61850 and incorporate a plug and play feature. This allows interoperability within a microgrid at agent layer as well as allows for online re-configuration upon topology alteration. A test case of distributed frequency control of islanded microgrid with various scenarios was conducted to validate the operation of proposed approach under controller and power hardware-in-the-loop environment, comprising prototypical hardware agent systems and realistic communications network.

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