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Dive into the research topics where Leo Raju is active.

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Featured researches published by Leo Raju.


international conference electrical energy systems | 2016

Advanced energy management in virtual power plant using multi agent system

Leo Raju; Kaviya Appaswamy; Janani Vengatraman; Antony Amalraj Morais

The objective of this paper is to develop a Multi Agent System (MAS) for advanced distributed energy management of a solar-wind interconnected micro-grid. This grid connected micro-grid also contains two solar Photo Voltaic (PV) systems, two Wind Turbines each contains a local consumer, a solar PV system and a battery unit. We also consider a Diesel Power Plant that provides considerable power. So, Initially we measure the load patterns, solar power, wind power generated in the two solar and wind units. Then we use Multi Agent System for advanced distributed energy management of this solar-wind micro-grid with smart grid frame work. We develop a simulation model in Java Agent Development Environment (JADE) for distributed, dynamic energy management, which considers the intermittent nature of solar power, wind power, randomness of load, dynamic pricing of grid and variation of critical loads and choose the best possible action every hour to stabilize and optimize the solar micro-grid. Furthermore, MAS increases the operational efficiency, due to decentralised approach and reduced timings. Thus MAS in solar micro-grid energy management leads to economic and environmental optimization. Simulated operation of solar generators and loads are studied by performing simulations under all possible agent objectives. Outcome of the simulation studies proves the effectiveness of proposed MAS in distributed energy management of solar-wind interconnected micro-grid.


The Scientific World Journal | 2016

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

Leo Raju; R. S. Milton; Senthilkumaran Mahadevan

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.


international conference on intelligent systems and control | 2016

Multi agent systems based distributed control and automation of micro-grid using MACSimJX

Leo Raju; R. S. Milton; Senthilkumaran Mahadevan

The objective of this paper is to develop a model for distributed automation of micro-grid using Multi Agent System(MAS) for the advanced control and distributed energy management of a solar micro-grid. A grid connected solar micro-grid model, which contains two solar Photo Voltaic (PV) systems, one in department and other in hostel, each contains a local consumer, a solar PV system and a battery, is modelled in Simulink. Due to unstable nature of MATLAB, when dealing with multi threading environment, MAS operating in Java Agent Development Environment(JADE) is linked with the MATLAB using a middleware, Multi Agent Control using Simulink with Jade extension (MACSimJX). MACSimJX allows the solar micro-grid system designed with MATLAB to be controlled by solar micro-grid agents for realizing the advantages of decentralized approach of MAS. All the agents of solar micro-grid components are programmed in JADE and the results of the coordinated action of these agents are sent to the environment for distributed control and automation of the hardware. JADE leverages the advantage of MAS by its inherent features and hence the operational efficiency of solar micro-grid is further increased. Also the power exchange between main grid and solar micro-grid is optimized by effetive demand side management. Simulation is designed to evaluate impact of autonamous operations of agents.


Archive | 2018

Advanced Energy Management of a Micro-grid Using Arduino and Multi-agent System

Leo Raju; Antony Amalraj Morais; R. S. Milton

The objective of this paper is to develop Arduino-based multi-agent system (MAS) for advanced distributed energy management of a solar-wind micro-grid. High penetration of renewable energy resources needs new coordination and control approaches to meet the stochastic nature of the environment and dynamic loadings. We use multi-agent system for advanced distributed, autonomous energy management of micro-grid to dynamically and flexibly adapt to the changes in the environment as renewable energy resources are intermittent in nature. We consider that a micro-grid which contains two systems each contains solar photo voltaic (PV) system, wind generator system, local consumer, and a battery. We develop a simulation model using Java Agent Development Environment (JADE) in Eclipse IDE for dynamic energy management, which considers the intermittent nature of solar power, randomness of load, dynamic pricing of grid, and variation of critical loads, and choose the best possible action every hour to stabilize and optimize the micro-grid. Furthermore, environment variables are sensed through Arduino Mega micro-controller and given to agents of MAS. The agents take the strategic action, and the resulting actions are reflected in the LED outputs which can be readily deployed in the actual field. MAS increases responsiveness, stability, flexibility, and fault tolerance, thereby increasing operational efficiency and leading to economic and environmental optimization. All the smart grid features are tested using JADE simulations and practically verified through Arduino micro-controller to make micro-grid into smart micro-grid.


Intelligent Automation and Soft Computing | 2018

Application of Multi Agent Systems in Automation of Distributed Energy Management in Micro-grid using MACSimJX

Leo Raju; R. S. Milton; Senthilkumaran Mahadevan

AbstractThe objective of this paper is to monitor and control a micro-grid model developed in MATLAB-Simulink through Multi Agent System (MAS) for autonomous and distributed energy management. Since MATLAB/Simulink is not compatible with parallel operations of MAS, MAS operating in Java Agent Development Environment (JADE) is linked with MATLAB/Simulink through Multi Agent Control using Simulink with Jade extension (MACSimJX). This allows the micro-grid system designed with Simulink to be controlled by MAS for realizing the advantages of MAS in distributed and decentralized micro-grid systems. JADE agents receive environmental information through Simulink and they coordinate to take best possible action, which is reflected in MATLAB/Simulink simulations. After validation and performance evaluation through dynamic simulations, the operations of the agents at various scenarios are practically verified by using the Arduino microcontroller. These validation and verification moves MAS closer to Smartgrid appli...


2017 Second International Conference on Recent Trends and Challenges in Computational Models (ICRTCCM) | 2017

Autonomous Demand Side Management of a Micro-Grid Using Arduino and Multi-agent System

Leo Raju; Prithika Rani Muthukumar; Sajna Gokulakrishnan; Srinidhi Jagannathan

This paper aims to establish an Arduino based Multi Agent System (MAS) for progressive demand side response of asolar micro-grid. High penetration of renewable energy resources needs new coordination and control approaches to meet the stochastic nature of the environment and dynamic loadings. Here, a Multi Agent System is used for an improvised and strengthened, distributed, self-governing energy management of the micro-grid to dynamically and flexibly adapt to the changes in the environment. Our micro-grid contains two solar Photo Voltaic (PV) system, local consumer, and a battery. A simulation modelis developed in Java Agent Development Environment (JADE) for dynamic and effective energy administration, which takes an informed decision and chooses the most feasible action for every one hour interval to stabilize, sustain and enhance the solar micro-grid. Moreover, environment variables are sensed through Arduino micro controller and given to agents of MAS. The resulting actions are reflected in the LED out puts which can be readily deployed in the actual field.


2017 International Conference on Power and Embedded Drive Control (ICPEDC) | 2017

Micro-grid grid robustness management using multi agent systems

Leo Raju; Ramyaa Rathnakumar; Soundaryaa Ponnivalavan; L. D. Thavam; Antony Amalraj Morais

The aim of this paper is to develop a Multi Agent System (MAS) for robustness Management in electrical energy management of a micro-grid. We take into consideration a grid associated micro-grid which contains two systems each contains solar Photo Voltaic (PV) system, wind system, a local consumer, and a battery. Foremost we compute the load trends and solar and wind power produced in the two solar units. Following which we go on to implement grid robustness management using Multi Agent System based distributed energy management of micro-grid with smart grid structure. We develop a simulation model in Java Agent Development Environment (JADE) for dynamic model which takes into account the closely knit nature of solar power, impermanence of load, dynamic appraising of grid and variation of critical loads and choose the best possible action every hour to stabilize and optimize the micro-grid inspite of certain failures. Furthermore, MAS increases the functional efficiency and thereby maximize the power production of solar micro-grid and curtails the operational cost to minimum. Thus MAS in micro-grid leads to optimization of both capital and environmental resources. Simulated working of solar generators and loads are analysed by conducting simulations for the various agent motives. Simulation studies shows the balancing of micro- grid during the grid robustness.


international conference on emerging trends in engineering and technology | 2016

Integrated energy management of micro-grid using multi agent system

Leo Raju; Immanuel Rajkumar; Kaviya Appaswamy

The objective of this paper is to develop a Multi Agent System (MAS) for the integrated energy management of a solar micro-grid. We consider a grid connected solar micro-grid which contains two solar Photo Voltaic (PV) systems each contains a local consumer, a solar PV system and a battery. First we calculate the load patterns and solar power generated in the two solar units. Then we use Multi Agent System based distributed energy management of solar micro-grid with smart grid frame work. We develop a simulation model in Java Agent Development Environment (JADE) for dynamic model which considers the intermittent nature of solar power, randomness of load, dynamic pricing of grid and variation of critical loads and choose the best possible action every hour to stabilize and optimize the solar micro-grid. Further more, MAS increases the operational efficiency and thereby maximizes the power production of solar micro-grid and minimizes the operational cost. Thus MAS in micro-grid leads to economic and environmental optimization. Simulated operation of solar generators and loads are studied by performing simulations under different agent objectives. Outcome of the simulation studies demonstrates the effectiveness of proposed MAS in distributed energy management of micro-grid.


international conference on computational intelligence and computing research | 2015

Advanced automation in energy management of micro-grid using multi agent system

Leo Raju; R. S. Milton; Antony Amalraj Morais

The objective of this paper is to implement a Multi Agent System (MAS) in Java Agent Development Environment (JADE) for the automation and optimization in advanced distributed energy management of a micro-grid. We consider two grid connected micro-grids each contains wind turbine, solar Photo Voltaic (PV) systems and load. The power generated by solar and wind along with the load variations in the two micro-grids are calculated initially and then Multi Agent System is used for distributed energy management of micro-grid, which considers the intermittent nature of solar power, randomness of load, dynamic pricing of grid and variation of critical loads and automatically choose the best possible action every hour to optimize ther micro-grid. The advantages of MAS approach is leveraged through JADE to increase the operational efficiency and thereby maximizes the power production of micro-grid and minimizes the operational cost. Thus MAS in micro-grid obviously leads to economic and environmental optimization of the micro-grid due to its inherent features. Simulated operation of the micro-grids are studied by performing simulations under different agent objectives.


Applied Mechanics and Materials | 2015

Energy Optimization of Solar Micro-Grid Using Multi Agent Reinforcement Learning

Leo Raju; R. S. Milton; S. Sakthiyanandan

In this paper, two solar Photovoltaic (PV) systems are considered; one in the department with capacity of 100 kW and the other in the hostel with capacity of 200 kW. Each one has battery and load. The capital cost and energy savings by conventional methods are compared and it is proved that the energy dependency from grid is reduced in solar micro-grid element, operating in distributed environment. In the smart grid frame work, the grid energy consumption is further reduced by optimal scheduling of the battery, using Reinforcement Learning. Individual unit optimization is done by a model free reinforcement learning method, called Q-Learning and it is compared with distributed operations of solar micro-grid using a Multi Agent Reinforcement Learning method, called Joint Q-Learning. The energy planning is designed according to the prediction of solar PV energy production and observed load pattern of department and the hostel. A simulation model was developed using Python programming.

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R. S. Milton

Sri Sivasubramaniya Nadar College of Engineering

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Antony Amalraj Morais

Sri Sivasubramaniya Nadar College of Engineering

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Senthilkumaran Mahadevan

Sri Sivasubramaniya Nadar College of Engineering

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Kaviya Appaswamy

Sri Sivasubramaniya Nadar College of Engineering

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L. D. Thavam

Sri Sivasubramaniya Nadar College of Engineering

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Prithika Rani Muthukumar

Sri Sivasubramaniya Nadar College of Engineering

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Ramyaa Rathnakumar

Sri Sivasubramaniya Nadar College of Engineering

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Sajna Gokulakrishnan

Sri Sivasubramaniya Nadar College of Engineering

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Sibi Sankar

Sri Sivasubramaniya Nadar College of Engineering

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Soundaryaa Ponnivalavan

Sri Sivasubramaniya Nadar College of Engineering

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