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Multiagent Systems Based Modeling and Implementation of Dynamic Energy Management of Smart Microgrid Using MACSimJX.

Raju L, Milton RS, Mahadevan S - ScientificWorldJournal (2016)

Bottom Line: The microgrid environment variables are captured through sensors and given to agents through MATLAB/Simulink and after the agent operations in JADE, the results are given to the actuators through MATLAB for the implementation of dynamic operation in solar microgrid.Autonomous demand side management is implemented for optimizing the power exchange between main grid and microgrid with intermittent nature of solar power, randomness of load, and variation of noncritical load and grid price.These dynamics are considered for every time step and complex environment simulation is designed to emulate the distributed microgrid operations and evaluate the impact of agent operations.

View Article: PubMed Central - PubMed

Affiliation: SSN College of Engineering, Chennai, Tamil Nadu 603110, India.

ABSTRACT
The objective of this paper is implementation of multiagent system (MAS) for the advanced distributed energy management and demand side management of a solar microgrid. Initially, Java agent development environment (JADE) frame work is used to implement MAS based dynamic energy management of solar microgrid. Due to unstable nature of MATLAB, when dealing with multithreading environment, MAS operating in JADE is linked with the MATLAB using a middle ware called Multiagent Control Using Simulink with Jade Extension (MACSimJX). MACSimJX allows the solar microgrid components designed with MATLAB to be controlled by the corresponding agents of MAS. The microgrid environment variables are captured through sensors and given to agents through MATLAB/Simulink and after the agent operations in JADE, the results are given to the actuators through MATLAB for the implementation of dynamic operation in solar microgrid. MAS operating in JADE maximizes operational efficiency of solar microgrid by decentralized approach and increase in runtime efficiency due to JADE. Autonomous demand side management is implemented for optimizing the power exchange between main grid and microgrid with intermittent nature of solar power, randomness of load, and variation of noncritical load and grid price. These dynamics are considered for every time step and complex environment simulation is designed to emulate the distributed microgrid operations and evaluate the impact of agent operations.

No MeSH data available.


Functionality of an agent.
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Related In: Results  -  Collection


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fig2: Functionality of an agent.

Mentions: In MAS, several autonomous and intelligent entities called agents are working in collaboration to achieve the overall goal of a system. Agents have four behavioral attributes, autonomy, social, proactive, and reactive. Autonomy refers to the principle that agents can operate on their own to meet their goals without the need for human guidance. Agents are proactive, that is, the ability to take the initiative rather than acting simply in response to their environment. Agent can cooperate with other agents for coordinated action. In order to cooperate, agents need to possess social ability, that is, the ability to interact with other agents with some communication language like Agent Communication Language (ACL). Agents are reactive to changes in environment. Reasoning, optimizing, controlling and learning are the inherent characteristics of an agent, as shown in Figure 2. For agent systems to be truly smart, they would have to learn as they react and/or interact with their external environment.


Multiagent Systems Based Modeling and Implementation of Dynamic Energy Management of Smart Microgrid Using MACSimJX.

Raju L, Milton RS, Mahadevan S - ScientificWorldJournal (2016)

Functionality of an agent.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4834404&req=5

fig2: Functionality of an agent.
Mentions: In MAS, several autonomous and intelligent entities called agents are working in collaboration to achieve the overall goal of a system. Agents have four behavioral attributes, autonomy, social, proactive, and reactive. Autonomy refers to the principle that agents can operate on their own to meet their goals without the need for human guidance. Agents are proactive, that is, the ability to take the initiative rather than acting simply in response to their environment. Agent can cooperate with other agents for coordinated action. In order to cooperate, agents need to possess social ability, that is, the ability to interact with other agents with some communication language like Agent Communication Language (ACL). Agents are reactive to changes in environment. Reasoning, optimizing, controlling and learning are the inherent characteristics of an agent, as shown in Figure 2. For agent systems to be truly smart, they would have to learn as they react and/or interact with their external environment.

Bottom Line: The microgrid environment variables are captured through sensors and given to agents through MATLAB/Simulink and after the agent operations in JADE, the results are given to the actuators through MATLAB for the implementation of dynamic operation in solar microgrid.Autonomous demand side management is implemented for optimizing the power exchange between main grid and microgrid with intermittent nature of solar power, randomness of load, and variation of noncritical load and grid price.These dynamics are considered for every time step and complex environment simulation is designed to emulate the distributed microgrid operations and evaluate the impact of agent operations.

View Article: PubMed Central - PubMed

Affiliation: SSN College of Engineering, Chennai, Tamil Nadu 603110, India.

ABSTRACT
The objective of this paper is implementation of multiagent system (MAS) for the advanced distributed energy management and demand side management of a solar microgrid. Initially, Java agent development environment (JADE) frame work is used to implement MAS based dynamic energy management of solar microgrid. Due to unstable nature of MATLAB, when dealing with multithreading environment, MAS operating in JADE is linked with the MATLAB using a middle ware called Multiagent Control Using Simulink with Jade Extension (MACSimJX). MACSimJX allows the solar microgrid components designed with MATLAB to be controlled by the corresponding agents of MAS. The microgrid environment variables are captured through sensors and given to agents through MATLAB/Simulink and after the agent operations in JADE, the results are given to the actuators through MATLAB for the implementation of dynamic operation in solar microgrid. MAS operating in JADE maximizes operational efficiency of solar microgrid by decentralized approach and increase in runtime efficiency due to JADE. Autonomous demand side management is implemented for optimizing the power exchange between main grid and microgrid with intermittent nature of solar power, randomness of load, and variation of noncritical load and grid price. These dynamics are considered for every time step and complex environment simulation is designed to emulate the distributed microgrid operations and evaluate the impact of agent operations.

No MeSH data available.