Cost Driven Optimization of Microgrid Under Environmental Uncertainties Using Different Improved PSO Models
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This paper presents a micro grid generation scheduling model using Non-linear Decreasing Inertia Weight Particle Swarm Optimization (NDIW-PSO) and Time Varying Acceleration Co-efficient Particle Swarm Optimization (TVAC-PSO) techniques. Here energy management in micro grid is done in presence of renewable energy sources such as wind and solar power. In this research work, implementation of Demand Response (DR) schedules are carried out as incentive based payment i.e., on offered price packages. In the typical microgrid, different power components including Wind Turbine (WT), Photovoltaic (PV) cell, Micro-Turbine (MT), Fuel Cell (FC), battery hybrid power source and responsive loads are used. Analytical approaches and case studies are conducted for obtaining minimum operating costs and comparative studies are carried out without demand response participation and with demand response participation respectively. The results obtained represent the superiority of the proposed approach for effective generation scheduling in micro grids.
KeywordsNon-linear decreasing inertia weight particle swarm optimization Generation scheduling Demand response Micro grids
The authors express gratitude towards the Department of Power Engineering, Jadavpur University for providing facilities for carrying this research work.
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