Optimal sizing of PV/wind/diesel hybrid microgrid system using multi-objective self-adaptive differential evolution algorithm

Microgrid systems, such as solar photovoltaic (PV) power and wind energy, integrated with diesel generators are promising energy supplies and are economically feasible for current and future use in relation to increased demands for energy and depletion of conventional sources. It is thus important t...

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Veröffentlicht in:Renewable energy Jg. 121; S. 400 - 411
Hauptverfasser: Ramli, Makbul A.M., Bouchekara, H.R.E.H., Alghamdi, Abdulsalam S.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.06.2018
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ISSN:0960-1481, 1879-0682
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Abstract Microgrid systems, such as solar photovoltaic (PV) power and wind energy, integrated with diesel generators are promising energy supplies and are economically feasible for current and future use in relation to increased demands for energy and depletion of conventional sources. It is thus important to optimize the size of hybrid microgrid system (HMS) components, including storage, to determine system cost and reliability. In this paper, optimal sizing of a PV/wind/diesel HMS with battery storage is conducted using the Multi-Objective Self-Adaptive Differential Evolution (MOSaDE) algorithm for the city of Yanbu, Saudi Arabia. Using the multi-objective optimization approach, the objectives are treated simultaneously and independently, thereby leading to a reduction in computational time. One of the main criteria to consider when designing and optimizing the HMS is the energy management strategy, which is required to coordinate the different units comprising the HMS. The multi-objective optimization approach is then used to analyze the Loss of Power Supply Probability (LPSP), the Cost of Electricity (COE), and the Renewable Factor (RF) in relation to HMS cost and reliability and is tested using three case studies involving differing house numbers. Results verify its application in optimizing the HMS and in its practical implementation. In addition, optimization results using the proposed approach provided a set of design solutions for the HMS, which will assist researchers and practitioners in selecting the optimal HMS configuration. Moreover, it is important to select optimally sized HMS components to ensure that all load demands are met at the minimum energy cost and high reliability. •Optimal sizing of PV/wind/diesel hybrid system with battery storage was analyzed.•The analysis was done using MOSaDE algorithm for the city of Yanbu, Saudi Arabia.•The energy management strategy is the main criteria to design and optimize the HMS.•The multi-objective optimization approach was used to analyze the cost and reliability.•HMS components are selected to meet the minimum energy cost and high reliability.
AbstractList Microgrid systems, such as solar photovoltaic (PV) power and wind energy, integrated with diesel generators are promising energy supplies and are economically feasible for current and future use in relation to increased demands for energy and depletion of conventional sources. It is thus important to optimize the size of hybrid microgrid system (HMS) components, including storage, to determine system cost and reliability. In this paper, optimal sizing of a PV/wind/diesel HMS with battery storage is conducted using the Multi-Objective Self-Adaptive Differential Evolution (MOSaDE) algorithm for the city of Yanbu, Saudi Arabia. Using the multi-objective optimization approach, the objectives are treated simultaneously and independently, thereby leading to a reduction in computational time. One of the main criteria to consider when designing and optimizing the HMS is the energy management strategy, which is required to coordinate the different units comprising the HMS. The multi-objective optimization approach is then used to analyze the Loss of Power Supply Probability (LPSP), the Cost of Electricity (COE), and the Renewable Factor (RF) in relation to HMS cost and reliability and is tested using three case studies involving differing house numbers. Results verify its application in optimizing the HMS and in its practical implementation. In addition, optimization results using the proposed approach provided a set of design solutions for the HMS, which will assist researchers and practitioners in selecting the optimal HMS configuration. Moreover, it is important to select optimally sized HMS components to ensure that all load demands are met at the minimum energy cost and high reliability.
Microgrid systems, such as solar photovoltaic (PV) power and wind energy, integrated with diesel generators are promising energy supplies and are economically feasible for current and future use in relation to increased demands for energy and depletion of conventional sources. It is thus important to optimize the size of hybrid microgrid system (HMS) components, including storage, to determine system cost and reliability. In this paper, optimal sizing of a PV/wind/diesel HMS with battery storage is conducted using the Multi-Objective Self-Adaptive Differential Evolution (MOSaDE) algorithm for the city of Yanbu, Saudi Arabia. Using the multi-objective optimization approach, the objectives are treated simultaneously and independently, thereby leading to a reduction in computational time. One of the main criteria to consider when designing and optimizing the HMS is the energy management strategy, which is required to coordinate the different units comprising the HMS. The multi-objective optimization approach is then used to analyze the Loss of Power Supply Probability (LPSP), the Cost of Electricity (COE), and the Renewable Factor (RF) in relation to HMS cost and reliability and is tested using three case studies involving differing house numbers. Results verify its application in optimizing the HMS and in its practical implementation. In addition, optimization results using the proposed approach provided a set of design solutions for the HMS, which will assist researchers and practitioners in selecting the optimal HMS configuration. Moreover, it is important to select optimally sized HMS components to ensure that all load demands are met at the minimum energy cost and high reliability. •Optimal sizing of PV/wind/diesel hybrid system with battery storage was analyzed.•The analysis was done using MOSaDE algorithm for the city of Yanbu, Saudi Arabia.•The energy management strategy is the main criteria to design and optimize the HMS.•The multi-objective optimization approach was used to analyze the cost and reliability.•HMS components are selected to meet the minimum energy cost and high reliability.
Author Alghamdi, Abdulsalam S.
Bouchekara, H.R.E.H.
Ramli, Makbul A.M.
Author_xml – sequence: 1
  givenname: Makbul A.M.
  surname: Ramli
  fullname: Ramli, Makbul A.M.
  email: mramli@kau.edu.sa
  organization: Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
– sequence: 2
  givenname: H.R.E.H.
  surname: Bouchekara
  fullname: Bouchekara, H.R.E.H.
  email: bouchekara.houssem@gmail.com
  organization: Laboratory of Electrical Engineering of Constantine, LGEC, Department of Electrical Engineering, University of Freres Mentouri Constantine, 25000 Constantine, Algeria
– sequence: 3
  givenname: Abdulsalam S.
  surname: Alghamdi
  fullname: Alghamdi, Abdulsalam S.
  organization: Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
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Differential evolution algorithm
Renewable energy
PV
Optimization
Hybrid system
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Snippet Microgrid systems, such as solar photovoltaic (PV) power and wind energy, integrated with diesel generators are promising energy supplies and are economically...
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SubjectTerms algorithms
batteries
case studies
diesel engines
Differential evolution algorithm
economic feasibility
electricity
energy
energy costs
generators (equipment)
Hybrid system
Optimization
Renewable energy
Saudi Arabia
solar energy
wind
Wind energy
wind power
Title Optimal sizing of PV/wind/diesel hybrid microgrid system using multi-objective self-adaptive differential evolution algorithm
URI https://dx.doi.org/10.1016/j.renene.2018.01.058
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