Designing a Solar Photovoltaic System for Generating Renewable Energy of a Hospital: Performance Analysis and Adjustment Based on RSM and ANFIS Approaches

One of the most favorable renewable energy sources, solar photovoltaic (PV) can meet the electricity demand considerably. Sunlight is converted into electricity by the solar PV systems using cells containing semiconductor materials. A PV system is designed to meet the energy needs of King Abdulaziz...

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Autores principales:	Rami Alamoudi, Osman Taylan, Mehmet Azmi Aktacir, Enrique Herrera-Viedma
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	solar PV module performance prediction simulation self-consumption model RSM ANFIS Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/431f7d2a817c478c8e028af4c717b447
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id	oai:doaj.org-article:431f7d2a817c478c8e028af4c717b447
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spelling	oai:doaj.org-article:431f7d2a817c478c8e028af4c717b4472021-11-25T18:17:16ZDesigning a Solar Photovoltaic System for Generating Renewable Energy of a Hospital: Performance Analysis and Adjustment Based on RSM and ANFIS Approaches10.3390/math92229292227-7390https://doaj.org/article/431f7d2a817c478c8e028af4c717b4472021-11-01T00:00:00Zhttps://www.mdpi.com/2227-7390/9/22/2929https://doaj.org/toc/2227-7390One of the most favorable renewable energy sources, solar photovoltaic (PV) can meet the electricity demand considerably. Sunlight is converted into electricity by the solar PV systems using cells containing semiconductor materials. A PV system is designed to meet the energy needs of King Abdulaziz University Hospital. A new method has been introduced to find optimal working capacity, and determine the self-consumption and sufficiency rates of the PV system. Response surface methodology (RSM) is used for determining the optimal working conditions of PV panels. Similarly, an adaptive neural network based fuzzy inference system (ANFIS) was employed to analyze the performance of solar PV panels. The outcomes of methods were compared to the actual outcomes available for testing the performance of models. Hence, for a 40 MW target PV system capacity, the RSM determined that approximately 33.96 MW electricity can be produced, when the radiation rate is 896.3 W/m<sup>2</sup>, the module surface temperature is 41.4 °C, the outdoor temperature is 36.2 °C, the wind direction and speed are 305.6 and 6.7 m/s, respectively. The ANFIS model (with nine rules) gave the highest performance with lowest residual for the same design parameters. Hence, it was determined that the hourly electrical energy requirement of the hospital can be met by the PV system during the year.Rami AlamoudiOsman TaylanMehmet Azmi AktacirEnrique Herrera-ViedmaMDPI AGarticlesolar PV moduleperformance predictionsimulationself-consumption modelRSMANFISMathematicsQA1-939ENMathematics, Vol 9, Iss 2929, p 2929 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	solar PV module performance prediction simulation self-consumption model RSM ANFIS Mathematics QA1-939
spellingShingle	solar PV module performance prediction simulation self-consumption model RSM ANFIS Mathematics QA1-939 Rami Alamoudi Osman Taylan Mehmet Azmi Aktacir Enrique Herrera-Viedma Designing a Solar Photovoltaic System for Generating Renewable Energy of a Hospital: Performance Analysis and Adjustment Based on RSM and ANFIS Approaches
description	One of the most favorable renewable energy sources, solar photovoltaic (PV) can meet the electricity demand considerably. Sunlight is converted into electricity by the solar PV systems using cells containing semiconductor materials. A PV system is designed to meet the energy needs of King Abdulaziz University Hospital. A new method has been introduced to find optimal working capacity, and determine the self-consumption and sufficiency rates of the PV system. Response surface methodology (RSM) is used for determining the optimal working conditions of PV panels. Similarly, an adaptive neural network based fuzzy inference system (ANFIS) was employed to analyze the performance of solar PV panels. The outcomes of methods were compared to the actual outcomes available for testing the performance of models. Hence, for a 40 MW target PV system capacity, the RSM determined that approximately 33.96 MW electricity can be produced, when the radiation rate is 896.3 W/m<sup>2</sup>, the module surface temperature is 41.4 °C, the outdoor temperature is 36.2 °C, the wind direction and speed are 305.6 and 6.7 m/s, respectively. The ANFIS model (with nine rules) gave the highest performance with lowest residual for the same design parameters. Hence, it was determined that the hourly electrical energy requirement of the hospital can be met by the PV system during the year.
format	article
author	Rami Alamoudi Osman Taylan Mehmet Azmi Aktacir Enrique Herrera-Viedma
author_facet	Rami Alamoudi Osman Taylan Mehmet Azmi Aktacir Enrique Herrera-Viedma
author_sort	Rami Alamoudi
title	Designing a Solar Photovoltaic System for Generating Renewable Energy of a Hospital: Performance Analysis and Adjustment Based on RSM and ANFIS Approaches
title_short	Designing a Solar Photovoltaic System for Generating Renewable Energy of a Hospital: Performance Analysis and Adjustment Based on RSM and ANFIS Approaches
title_full	Designing a Solar Photovoltaic System for Generating Renewable Energy of a Hospital: Performance Analysis and Adjustment Based on RSM and ANFIS Approaches
title_fullStr	Designing a Solar Photovoltaic System for Generating Renewable Energy of a Hospital: Performance Analysis and Adjustment Based on RSM and ANFIS Approaches
title_full_unstemmed	Designing a Solar Photovoltaic System for Generating Renewable Energy of a Hospital: Performance Analysis and Adjustment Based on RSM and ANFIS Approaches
title_sort	designing a solar photovoltaic system for generating renewable energy of a hospital: performance analysis and adjustment based on rsm and anfis approaches
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/431f7d2a817c478c8e028af4c717b447
work_keys_str_mv	AT ramialamoudi designingasolarphotovoltaicsystemforgeneratingrenewableenergyofahospitalperformanceanalysisandadjustmentbasedonrsmandanfisapproaches AT osmantaylan designingasolarphotovoltaicsystemforgeneratingrenewableenergyofahospitalperformanceanalysisandadjustmentbasedonrsmandanfisapproaches AT mehmetazmiaktacir designingasolarphotovoltaicsystemforgeneratingrenewableenergyofahospitalperformanceanalysisandadjustmentbasedonrsmandanfisapproaches AT enriqueherreraviedma designingasolarphotovoltaicsystemforgeneratingrenewableenergyofahospitalperformanceanalysisandadjustmentbasedonrsmandanfisapproaches
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Designing a Solar Photovoltaic System for Generating Renewable Energy of a Hospital: Performance Analysis and Adjustment Based on RSM and ANFIS Approaches

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