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AUTHOR(S): Pothula Jagadeesha, M. Mohamed Thameem Ansarib, M. Saiveerrajuc
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ABSTRACT A model with a combination of cogeneration and generation photovoltaic power is designed for enhancing the capability of photoelectric absorption. The initial step of the model includes using a “time-of-use price strategy” for guiding the users for changing their electricity consumption patterns to participate in the demand response, hence establishing the demand response model. Next the MATLAB Environment Meta Heuristic Optimization Algorithms of Genetic Algorithm (GA), Particle Swarm Optimization Algorithm (PSO) and Ant Colony Algorithms (ACO) was applied with an aim of reducing the price of the operation of the micro-grid to achieve economic dispatching. The model includes, the constraints of power balance equation, energy storage unit operation, as well as the heat storage. The last part of the research details the results, depicting enhanced levels of consumption of photo-electric energy with the proposed model with comparison of Three Algorithms and also produces economic benefits from using the microgrid. |
KEYWORDS Demand Response, time-of-use electricity price, energy storage, cogeneration, Genetic Algorithm (GA), Particle Swarm Optimization Algorithm (PSO) , Ant Colony Optimization Algorithm (ACO) |
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Cite this paper Pothula Jagadeesha, M. Mohamed Thameem Ansarib, M. Saiveerrajuc. (2022) Meta Heuristic Optimization Based Renewable Energy Penetration Enhancement in Microgrid with Demand Response. International Journal of Power Systems, 7, 15-26 |
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