Abstract:
The increasing interest for energy and the escalating of ozone depleting substances including CO2 emanation in the air, use of renewable energy has moved towards becoming progressively significant, appealing and economical. Based on the fact it is known that solar and wind energy are firmly reliant on the weather and climatic deviations. To deal with this insufficiency, the micro grid system is considered. This microgrid system is a hybrid power system that incorporates a wide range of Distributed Generation (DG) units including Fuel Cells (FCs), Diesel Generators(DGs), Wind Turbine(WTs), Photo Voltic(PV) Cell ,Battery Storage(BS) and Electric vehicles (EVs) to take full preferred standpoint of their individual and corresponding attributes, in this manner expanding the energy effectiveness, the energy uses rate and the power supply reliability of the system. Several methods have been proposed along with the different techniques. One of the most common method that is being used, is three step design frameworks for microgrid with capacity battery storage. This study proposes Artificial Bee Colony (ABC)& Particle Swarm Optimization (PSO) Techniques to minimize the cost and greenhouse gases emissions into the atmosphere. The study has two phases, in first phase the load is forecasted by using data mining and Artificial Intelligence Algorithms, i.e. Large Term Short Term Memory (LSTM) and Prophet technique based on the data available on National Aeronautics and Space Administration (NASA) Website for Specific areas. In order to minimize the Operating Cost, to get optimal fixed battery size and to reduce the gasses emission, in the second phase, we have applied Artificial Bee Colony (ABC) & Particle Swarm Optimization (PSO) technique using MATLAB software. The Results have validated that Prophet forecasting technique Under ABC algorithm is quite useful in term of economics, emission and reducing Net Present Cost (NPC).
