An Improved Optimization Technique for Energy Harvesting System with Grid connected Power for Green House Management

• Published in: Journal of electrical engineering & technology 2022, 17(5), , pp.2937-2949
• Main Authors: Rajaram, A., Sathiyaraj, K.
• Format: Article
• Language: English
• Subjects: Electrical Engineering; Electrical Machines and Networks; Electronics and Microelectronics; Engineering; Instrumentation; Original Article; Power Electronics; 전기공학
• ISSN: 1975-0102; 2093-7423
• DOI: 10.1007/s42835-022-01033-2

In recent days, the electricity demand is increased day by day. For reducing this fact, various sustainable resources are used. The sustainable sources used with grid-connected power for supplying external power to the user. Green house harvesting system makes the efficient harvesting and those are far from locality and offshore aqua farms. Conventional method uses wireless sensor network and RFIDs. This increased the design complexity and also increases the power loss. The existing optimization method used in this application is that Stochastic Tunnelling Particle Swarm Optimization Technique (ST-PSO). Novelty of this work implemented to enhance the performance by quantum tunnelling PSO on energy harvesting system and the hybrid resource always supply the power to the grid. Here the proposed research works on grid connected harvesting model extracts the energy from solar array and electromagnetic waves with RECTENNA. Here the rectifying antenna used to convert electromagnetic waves into the electrical energy and the PV generates power by changing irradiance and temperature. Here the optimization technique uses the Quantum Tunnelling Particle swarm optimization (QT-PSO) algorithm, which is effectively performed in PV based applications. This quantum tunnelling method is to converter the electromagnetic wave into DC power source, which is given to the grid-connected power generation circuits and it optimizes the result of energy harvesting system. The grid connected power system is used to supply the power without loss. Therefore, the proposed energy harvesting system is better than conventional systems by reducing power loss. The proposed research work is implemented in MATLAB and the model is done by SIMULINK.