Energy management systems of grid-connected photovoltaic generation with energy storage system using particle swarm optimization

Nowadays, Renewable Energy System (RES) like Photovoltaic (PV) widely used to increase energy generation. Solar PV installation as a Distributed Generation (DG) on the utility scale is commercially feasible, particularly for residential applications. This energy available abundantly and considered c...

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Main Author: Shamsuddin, Noor Ilham
Format: Thesis
Language:English
Published: 2021
Subjects:
Online Access:http://eprints.utm.my/id/eprint/99498/1/NoorIlhamShamsuddinMKE2021.pdf
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spelling my-utm-ep.994982023-02-27T07:53:27Z Energy management systems of grid-connected photovoltaic generation with energy storage system using particle swarm optimization 2021 Shamsuddin, Noor Ilham TK Electrical engineering. Electronics Nuclear engineering Nowadays, Renewable Energy System (RES) like Photovoltaic (PV) widely used to increase energy generation. Solar PV installation as a Distributed Generation (DG) on the utility scale is commercially feasible, particularly for residential applications. This energy available abundantly and considered clean energy that harnessed and transformed the radiant light energy generated by the sun into electric current. However, the best use of solar energy has been prevented by nature or weather mismatches between. the maximum of solar PV generation and usual residential load. In residential, the PV output is not fully utilized when the load is at the minimum (off-peak load). The wastage of power occurs due to PV excess generation during off peak load and causes an increase in the cost of electricity consumption. To optimize load demands and power flow in the connected grid, RES need to be scheduled. The Battery Energy Storage System (BESS) stores the excess power generated in peak hours and returns it to the system when there is not enough PV. While the energy management system (EMS) is required in operating renewable energy sources connected to a grid to ensure the renewable energy power is fully utilized. Therefore, this project to design the EMS strategy for the network that cooperating PV and BESS. This focused on PV modelling for improved EMS and the designation of storage devices. Optimize the PV size as well to reduce power consumption from the main grid. In this project, MATLAB Software was used to implement the Particle Swarm Optimization (PSO) technique. BESS capacity and PV size are acquired in accordance with the energy dispatch stored in the BESS. This strategy can reduce grid power generation by implementing EMS in the operation of existing residential PV with BESS. 2021 Thesis http://eprints.utm.my/id/eprint/99498/ http://eprints.utm.my/id/eprint/99498/1/NoorIlhamShamsuddinMKE2021.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:149819 masters Universiti Teknologi Malaysia Faculty of Engineering - School of Electrical Engineering
institution Universiti Teknologi Malaysia
collection UTM Institutional Repository
language English
topic TK Electrical engineering
Electronics Nuclear engineering
spellingShingle TK Electrical engineering
Electronics Nuclear engineering
Shamsuddin, Noor Ilham
Energy management systems of grid-connected photovoltaic generation with energy storage system using particle swarm optimization
description Nowadays, Renewable Energy System (RES) like Photovoltaic (PV) widely used to increase energy generation. Solar PV installation as a Distributed Generation (DG) on the utility scale is commercially feasible, particularly for residential applications. This energy available abundantly and considered clean energy that harnessed and transformed the radiant light energy generated by the sun into electric current. However, the best use of solar energy has been prevented by nature or weather mismatches between. the maximum of solar PV generation and usual residential load. In residential, the PV output is not fully utilized when the load is at the minimum (off-peak load). The wastage of power occurs due to PV excess generation during off peak load and causes an increase in the cost of electricity consumption. To optimize load demands and power flow in the connected grid, RES need to be scheduled. The Battery Energy Storage System (BESS) stores the excess power generated in peak hours and returns it to the system when there is not enough PV. While the energy management system (EMS) is required in operating renewable energy sources connected to a grid to ensure the renewable energy power is fully utilized. Therefore, this project to design the EMS strategy for the network that cooperating PV and BESS. This focused on PV modelling for improved EMS and the designation of storage devices. Optimize the PV size as well to reduce power consumption from the main grid. In this project, MATLAB Software was used to implement the Particle Swarm Optimization (PSO) technique. BESS capacity and PV size are acquired in accordance with the energy dispatch stored in the BESS. This strategy can reduce grid power generation by implementing EMS in the operation of existing residential PV with BESS.
format Thesis
qualification_level Master's degree
author Shamsuddin, Noor Ilham
author_facet Shamsuddin, Noor Ilham
author_sort Shamsuddin, Noor Ilham
title Energy management systems of grid-connected photovoltaic generation with energy storage system using particle swarm optimization
title_short Energy management systems of grid-connected photovoltaic generation with energy storage system using particle swarm optimization
title_full Energy management systems of grid-connected photovoltaic generation with energy storage system using particle swarm optimization
title_fullStr Energy management systems of grid-connected photovoltaic generation with energy storage system using particle swarm optimization
title_full_unstemmed Energy management systems of grid-connected photovoltaic generation with energy storage system using particle swarm optimization
title_sort energy management systems of grid-connected photovoltaic generation with energy storage system using particle swarm optimization
granting_institution Universiti Teknologi Malaysia
granting_department Faculty of Engineering - School of Electrical Engineering
publishDate 2021
url http://eprints.utm.my/id/eprint/99498/1/NoorIlhamShamsuddinMKE2021.pdf
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