Optimization and Simulation of a Grid-Connected PV System Using Load Forecasting Methods: A Case Study of a University Building

Distributed generation represents a paradigm shift from the traditional electric grid to localized generation of electric power along with the capability of incorporating renewable energy (RE) sources into the energy mix. Responding to the need for sufficient analysis, simulation, and study of feasi...

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Main Authors: Manlapaz, Juan Glicerio C., Reyes, Dalisay M., Buensuceso, Cris Paulo L., Peña, Robert Alfie S, Parocha, Raymark, Macabebe, Erees Queen B.
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Published: Archīum Ateneo 2023
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Online Access:https://archium.ateneo.edu/ecce-faculty-pubs/149
https://drive.google.com/file/d/1fPQci6A05Rl7N83SqlzCOmRYG6qPC3jx/view?usp=sharing
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Institution: Ateneo De Manila University
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spelling ph-ateneo-arc.ecce-faculty-pubs-11432024-02-21T07:01:57Z Optimization and Simulation of a Grid-Connected PV System Using Load Forecasting Methods: A Case Study of a University Building Manlapaz, Juan Glicerio C. Reyes, Dalisay M. Buensuceso, Cris Paulo L. Peña, Robert Alfie S Parocha, Raymark Macabebe, Erees Queen B. Distributed generation represents a paradigm shift from the traditional electric grid to localized generation of electric power along with the capability of incorporating renewable energy (RE) sources into the energy mix. Responding to the need for sufficient analysis, simulation, and study of feasibility of distributed generation, this study aims to design a hybrid energy system for a university building and analyze its economic benefits. The viability of existing load forecasting methodologies for energy systems is also presented in this paper. The energy system design was determined through predictive modeling of the load profile of the building using historical data and optimization using machine learning methods, namely auto-regressive integrated moving average (ARIMA) and long short-term memory (LSTM). Simulations were run in HOMER Pro. Results show that a grid-connected solar photovoltaic (PV) system installed on the roof coupled with an energy storage system (ESS) will provide the most economic benefits because it yields a reduced cost of energy (COE) per kilowatt-hour (kWh) for the building. This study shows that in line with efforts to transition towards clean energy, hybrid energy systems using RE not only have economic benefits, but can also ensure energy security and environmental sustainability. 2023-01-01T08:00:00Z text https://archium.ateneo.edu/ecce-faculty-pubs/149 https://drive.google.com/file/d/1fPQci6A05Rl7N83SqlzCOmRYG6qPC3jx/view?usp=sharing Electronics, Computer, and Communications Engineering Faculty Publications Archīum Ateneo ARIMA cost of energy Distributed generation energy systems modeling load forecasting LSTM renewable energy technologies Electrical and Computer Engineering Electrical and Electronics Engineering
institution Ateneo De Manila University
building Ateneo De Manila University Library
continent Asia
country Philippines
Philippines
content_provider Ateneo De Manila University Library
collection archium.Ateneo Institutional Repository
topic ARIMA
cost of energy
Distributed generation
energy systems modeling
load forecasting
LSTM
renewable energy technologies
Electrical and Computer Engineering
Electrical and Electronics
Engineering
spellingShingle ARIMA
cost of energy
Distributed generation
energy systems modeling
load forecasting
LSTM
renewable energy technologies
Electrical and Computer Engineering
Electrical and Electronics
Engineering
Manlapaz, Juan Glicerio C.
Reyes, Dalisay M.
Buensuceso, Cris Paulo L.
Peña, Robert Alfie S
Parocha, Raymark
Macabebe, Erees Queen B.
Optimization and Simulation of a Grid-Connected PV System Using Load Forecasting Methods: A Case Study of a University Building
description Distributed generation represents a paradigm shift from the traditional electric grid to localized generation of electric power along with the capability of incorporating renewable energy (RE) sources into the energy mix. Responding to the need for sufficient analysis, simulation, and study of feasibility of distributed generation, this study aims to design a hybrid energy system for a university building and analyze its economic benefits. The viability of existing load forecasting methodologies for energy systems is also presented in this paper. The energy system design was determined through predictive modeling of the load profile of the building using historical data and optimization using machine learning methods, namely auto-regressive integrated moving average (ARIMA) and long short-term memory (LSTM). Simulations were run in HOMER Pro. Results show that a grid-connected solar photovoltaic (PV) system installed on the roof coupled with an energy storage system (ESS) will provide the most economic benefits because it yields a reduced cost of energy (COE) per kilowatt-hour (kWh) for the building. This study shows that in line with efforts to transition towards clean energy, hybrid energy systems using RE not only have economic benefits, but can also ensure energy security and environmental sustainability.
format text
author Manlapaz, Juan Glicerio C.
Reyes, Dalisay M.
Buensuceso, Cris Paulo L.
Peña, Robert Alfie S
Parocha, Raymark
Macabebe, Erees Queen B.
author_facet Manlapaz, Juan Glicerio C.
Reyes, Dalisay M.
Buensuceso, Cris Paulo L.
Peña, Robert Alfie S
Parocha, Raymark
Macabebe, Erees Queen B.
author_sort Manlapaz, Juan Glicerio C.
title Optimization and Simulation of a Grid-Connected PV System Using Load Forecasting Methods: A Case Study of a University Building
title_short Optimization and Simulation of a Grid-Connected PV System Using Load Forecasting Methods: A Case Study of a University Building
title_full Optimization and Simulation of a Grid-Connected PV System Using Load Forecasting Methods: A Case Study of a University Building
title_fullStr Optimization and Simulation of a Grid-Connected PV System Using Load Forecasting Methods: A Case Study of a University Building
title_full_unstemmed Optimization and Simulation of a Grid-Connected PV System Using Load Forecasting Methods: A Case Study of a University Building
title_sort optimization and simulation of a grid-connected pv system using load forecasting methods: a case study of a university building
publisher Archīum Ateneo
publishDate 2023
url https://archium.ateneo.edu/ecce-faculty-pubs/149
https://drive.google.com/file/d/1fPQci6A05Rl7N83SqlzCOmRYG6qPC3jx/view?usp=sharing
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