Optimal Sizing of Fixed Battery Storage in V2G Integrated Microgrid under Uncertain Conditions (T-0444) (MFN 8326)

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dc.contributor.author Noor Aziz, 01-244162-014
dc.date.accessioned 2019-05-24T05:18:37Z
dc.date.available 2019-05-24T05:18:37Z
dc.date.issued 2018
dc.identifier.uri http://hdl.handle.net/123456789/8763
dc.description Supervised By Dr. Asad Waqar en_US
dc.description.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). en_US
dc.language.iso en en_US
dc.publisher Electrical Engineering, Bahria University Engineering School Islamabad en_US
dc.relation.ispartofseries MS EE;T-0444
dc.subject Electrical Engineering en_US
dc.title Optimal Sizing of Fixed Battery Storage in V2G Integrated Microgrid under Uncertain Conditions (T-0444) (MFN 8326) en_US
dc.type MS Thesis en_US


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