A multi-objective optimization model for sizing decisions of a grid-connected photovoltaic system

Ahmed M. Attia; Ahmad Al Hanbali; Haitham H. Saleh; Omar G. Alsawafy; Ahmed M. Ghaithan; Awsan Mohammed

doi:10.1016/j.energy.2021.120730

A multi-objective optimization model for sizing decisions of a grid-connected photovoltaic system

Ahmed M. Attia^*, Ahmad Al Hanbali, Haitham H. Saleh, Omar G. Alsawafy, Ahmed M. Ghaithan, Awsan Mohammed

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

18 Scopus citations

Abstract

Greenhouse gasses are by-products of using fossil fuels to generate energy. It is known that climate change is caused by an increase in greenhouse gasses in the Earth's atmosphere. Solar energy is a renewable energy source that is an environmentally friendly resource for generating power. The photovoltaic (PV) system is a well-established technology for transforming solar energy into electric power. Sizing-decisions of a PV system is a strategic decision-making process that has a long-term impact on the project. This work proposes a multi-objective optimization (MOO) model for sizing-decisions of a grid-connected PV system. The objectives consider the economic aspect in terms of minimizing the project lifespan costs and non-economic aspects, including maximizing system reliability and reducing CO2 emissions. The sizing decisions are the number of PV panels, the amount of energy purchased from the main grid, and the amount of energy supplied to the main grid. In addition to a binary variable for an either-or decision, either purchase or supply from the grid. The model generates Pareto-optima to assist the decision-maker in assessing trade-offs between alternatives. A case study based on monthly demand for the residential area at King Fahd University of Petroleum & Minerals (KFUPM) is provided to clarify the practicality of the model. It is found that 1713 PV modules are required to meet annual demand at an annual cost of M$1.61 over 25 years.

Original language	English
Article number	120730
Journal	Energy
Volume	229
DOIs	https://doi.org/10.1016/j.energy.2021.120730
State	Published - 15 Aug 2021

Bibliographical note

Funding Information:
The authors would like to express their gratitude to King Fahd University of Petroleum and Minerals (KFUPM) and King Abdullah City for Atomic and Renewable Energy (K.A.CARE) for providing the necessary data for this study.

Publisher Copyright:
© 2021 Elsevier Ltd

Keywords

Capacity planning
Multi-criteria decision making
Multi-objective optimization
Photovoltaic system

ASJC Scopus subject areas

Civil and Structural Engineering
Building and Construction
Modeling and Simulation
Renewable Energy, Sustainability and the Environment
Fuel Technology
Energy Engineering and Power Technology
Pollution
Energy (all)
Mechanical Engineering
Industrial and Manufacturing Engineering
Management, Monitoring, Policy and Law
Electrical and Electronic Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.energy.2021.120730

Cite this

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title = "A multi-objective optimization model for sizing decisions of a grid-connected photovoltaic system",

abstract = "Greenhouse gasses are by-products of using fossil fuels to generate energy. It is known that climate change is caused by an increase in greenhouse gasses in the Earth's atmosphere. Solar energy is a renewable energy source that is an environmentally friendly resource for generating power. The photovoltaic (PV) system is a well-established technology for transforming solar energy into electric power. Sizing-decisions of a PV system is a strategic decision-making process that has a long-term impact on the project. This work proposes a multi-objective optimization (MOO) model for sizing-decisions of a grid-connected PV system. The objectives consider the economic aspect in terms of minimizing the project lifespan costs and non-economic aspects, including maximizing system reliability and reducing CO2 emissions. The sizing decisions are the number of PV panels, the amount of energy purchased from the main grid, and the amount of energy supplied to the main grid. In addition to a binary variable for an either-or decision, either purchase or supply from the grid. The model generates Pareto-optima to assist the decision-maker in assessing trade-offs between alternatives. A case study based on monthly demand for the residential area at King Fahd University of Petroleum & Minerals (KFUPM) is provided to clarify the practicality of the model. It is found that 1713 PV modules are required to meet annual demand at an annual cost of M$1.61 over 25 years.",

keywords = "Capacity planning, Multi-criteria decision making, Multi-objective optimization, Photovoltaic system",

author = "Attia, {Ahmed M.} and {Al Hanbali}, Ahmad and Saleh, {Haitham H.} and Alsawafy, {Omar G.} and Ghaithan, {Ahmed M.} and Awsan Mohammed",

note = "Funding Information: The authors would like to express their gratitude to King Fahd University of Petroleum and Minerals (KFUPM) and King Abdullah City for Atomic and Renewable Energy (K.A.CARE) for providing the necessary data for this study. Publisher Copyright: {\textcopyright} 2021 Elsevier Ltd",

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AU - Attia, Ahmed M.

AU - Al Hanbali, Ahmad

AU - Saleh, Haitham H.

AU - Alsawafy, Omar G.

AU - Ghaithan, Ahmed M.

AU - Mohammed, Awsan

N1 - Funding Information: The authors would like to express their gratitude to King Fahd University of Petroleum and Minerals (KFUPM) and King Abdullah City for Atomic and Renewable Energy (K.A.CARE) for providing the necessary data for this study. Publisher Copyright: © 2021 Elsevier Ltd

PY - 2021/8/15

Y1 - 2021/8/15

N2 - Greenhouse gasses are by-products of using fossil fuels to generate energy. It is known that climate change is caused by an increase in greenhouse gasses in the Earth's atmosphere. Solar energy is a renewable energy source that is an environmentally friendly resource for generating power. The photovoltaic (PV) system is a well-established technology for transforming solar energy into electric power. Sizing-decisions of a PV system is a strategic decision-making process that has a long-term impact on the project. This work proposes a multi-objective optimization (MOO) model for sizing-decisions of a grid-connected PV system. The objectives consider the economic aspect in terms of minimizing the project lifespan costs and non-economic aspects, including maximizing system reliability and reducing CO2 emissions. The sizing decisions are the number of PV panels, the amount of energy purchased from the main grid, and the amount of energy supplied to the main grid. In addition to a binary variable for an either-or decision, either purchase or supply from the grid. The model generates Pareto-optima to assist the decision-maker in assessing trade-offs between alternatives. A case study based on monthly demand for the residential area at King Fahd University of Petroleum & Minerals (KFUPM) is provided to clarify the practicality of the model. It is found that 1713 PV modules are required to meet annual demand at an annual cost of M$1.61 over 25 years.

AB - Greenhouse gasses are by-products of using fossil fuels to generate energy. It is known that climate change is caused by an increase in greenhouse gasses in the Earth's atmosphere. Solar energy is a renewable energy source that is an environmentally friendly resource for generating power. The photovoltaic (PV) system is a well-established technology for transforming solar energy into electric power. Sizing-decisions of a PV system is a strategic decision-making process that has a long-term impact on the project. This work proposes a multi-objective optimization (MOO) model for sizing-decisions of a grid-connected PV system. The objectives consider the economic aspect in terms of minimizing the project lifespan costs and non-economic aspects, including maximizing system reliability and reducing CO2 emissions. The sizing decisions are the number of PV panels, the amount of energy purchased from the main grid, and the amount of energy supplied to the main grid. In addition to a binary variable for an either-or decision, either purchase or supply from the grid. The model generates Pareto-optima to assist the decision-maker in assessing trade-offs between alternatives. A case study based on monthly demand for the residential area at King Fahd University of Petroleum & Minerals (KFUPM) is provided to clarify the practicality of the model. It is found that 1713 PV modules are required to meet annual demand at an annual cost of M$1.61 over 25 years.

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ER -

A multi-objective optimization model for sizing decisions of a grid-connected photovoltaic system

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

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