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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.


Switching operations of solar hostel agent (SHA).
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fig11: Switching operations of solar hostel agent (SHA).

Mentions: Every hour based on the solar power and load values the optimal distributed energy management is implemented by the strategic action of agents. By using multiagent system implemented in JADE, the runtime efficiency of the solar microgrid is improved. Thus, dynamic energy management and demand side management are done for all the possible scenarios in this case study. The individual switching action of all the agents is analyzed. For example, the switching action of the solar hostel agent (SHA) in critical load case study is shown in Figure 11. Here the switch SH-LH is always on as the local load LHP is always supplied by SHP. Initially from 0th to 1st hour, the department and hostel solar powers (SDP and SHP) are 200 kW more than the corresponding load demand and so the department and hostel batteries are charged. The solar hostel agent charges its battery BH by switching on SH-BH and after BH gets fully charged the power is given to grid by switching SH-GRD. From 5th to 6th hours, department load requires 300 kW but the available solar power is 200 kW. So the 100 kW deficiency in the department is managed by 200 kW excess in the hostel unit. The hostel unit gives 100 kW to the department load and the remaining 100 kW is used to charge the hostel battery first and then the department battery. Here SHA switches on its local load (LHP) and also switches on SH-LD to give 100 kW deficiency in the department load. The remaining 100 kW is used to charge its battery (BH) by switching on SH-BH. After hostel battery gets fully charged, the switch SH-BH is switched off and SH-BD is switched on to charge the department battery (BD). Similarly, the switching actions of all the agents are observed. The switching operation of the department solar agent is shown in Figure 12. Here SD-LD switch is always on as department load is always connected to the department solar power. From 2nd to 3rd hours, there is deficiency of 100 kW in the hostel solar in supplying to hostel load. So it receives 100 kW from department solar through SD-LH switch. In the 6th hour, it is again switched on to manage the deficiency in hostel solar unit. In the first hour, the excess power in the department solar is used to charge department battery by switching on SD-BD till it gets fully charged and then the power is given to grid by switching on SD-GRD. It is again switched on from 6th hour till it gets fully charged and then the power is given to grid by switching on SD-GRD. In the 9th hour, it is switched on again to charge as there is excess power in the department solar unit and then it is given to grid through SD-GRD. Simulation output of all the components of the solar microgrid is observed and the actions are verified. The Simulink model output can be given for real-time physical action through Intelligent Electronic Devices (IED) and Program Logic Controllers (PLC). Thus, microgrid quickly adapt to environment dynamics improving stability and reliability. Multiagent system is exploited for microgrid automation through cyber physical system and scaled up using cloud computing concept for larger benefits. Advanced SCADA uses MAS to meet the challenges due to increased penetration of renewable energy resources.


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

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

Switching operations of solar hostel agent (SHA).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

fig11: Switching operations of solar hostel agent (SHA).
Mentions: Every hour based on the solar power and load values the optimal distributed energy management is implemented by the strategic action of agents. By using multiagent system implemented in JADE, the runtime efficiency of the solar microgrid is improved. Thus, dynamic energy management and demand side management are done for all the possible scenarios in this case study. The individual switching action of all the agents is analyzed. For example, the switching action of the solar hostel agent (SHA) in critical load case study is shown in Figure 11. Here the switch SH-LH is always on as the local load LHP is always supplied by SHP. Initially from 0th to 1st hour, the department and hostel solar powers (SDP and SHP) are 200 kW more than the corresponding load demand and so the department and hostel batteries are charged. The solar hostel agent charges its battery BH by switching on SH-BH and after BH gets fully charged the power is given to grid by switching SH-GRD. From 5th to 6th hours, department load requires 300 kW but the available solar power is 200 kW. So the 100 kW deficiency in the department is managed by 200 kW excess in the hostel unit. The hostel unit gives 100 kW to the department load and the remaining 100 kW is used to charge the hostel battery first and then the department battery. Here SHA switches on its local load (LHP) and also switches on SH-LD to give 100 kW deficiency in the department load. The remaining 100 kW is used to charge its battery (BH) by switching on SH-BH. After hostel battery gets fully charged, the switch SH-BH is switched off and SH-BD is switched on to charge the department battery (BD). Similarly, the switching actions of all the agents are observed. The switching operation of the department solar agent is shown in Figure 12. Here SD-LD switch is always on as department load is always connected to the department solar power. From 2nd to 3rd hours, there is deficiency of 100 kW in the hostel solar in supplying to hostel load. So it receives 100 kW from department solar through SD-LH switch. In the 6th hour, it is again switched on to manage the deficiency in hostel solar unit. In the first hour, the excess power in the department solar is used to charge department battery by switching on SD-BD till it gets fully charged and then the power is given to grid by switching on SD-GRD. It is again switched on from 6th hour till it gets fully charged and then the power is given to grid by switching on SD-GRD. In the 9th hour, it is switched on again to charge as there is excess power in the department solar unit and then it is given to grid through SD-GRD. Simulation output of all the components of the solar microgrid is observed and the actions are verified. The Simulink model output can be given for real-time physical action through Intelligent Electronic Devices (IED) and Program Logic Controllers (PLC). Thus, microgrid quickly adapt to environment dynamics improving stability and reliability. Multiagent system is exploited for microgrid automation through cyber physical system and scaled up using cloud computing concept for larger benefits. Advanced SCADA uses MAS to meet the challenges due to increased penetration of renewable energy resources.

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.