Heuristic optimization of state-of-charge feedback controller parameters for output power dispatch of hybrid photovoltaic/battery energy storage system

Muhamad Zalani Daud, Azah Mohamed, Ahmad Asrul Ibrahim, M. A. Hannan

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Output power fluctuation of photovoltaic (PV) sources is a problem of practical significance to utilities. To mitigate its impacts, particularly on a weak electricity network, a battery energy storage (BES) system can be used to smooth out and dispatch the output to the utility grid on an hourly basis. This paper presents an optimal control strategy of BES state-of-charge feedback (SOC-FB) control scheme used for output power dispatch of PV farm. The SOC-FB control parameters are optimized by using heuristic optimization techniques such as genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) in Matlab. In addition, an improved BES model is developed in PSCAD/EMTDC software package, in which GA is used to evaluate the optimal parameters. The studied multi-objective optimization problem also considers the evaluation of the optimal size of the BES. The performance of the proposed optimal SOC-FB control scheme is validated by comparing the results obtained from Matlab and PSCAD/EMTDC and with results from previous works. Finally, the best set of parameters are used to further validate the proposed method by using data obtained from the actual output of a grid-connected PV system. © 2013 Elsevier Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)15-25
Number of pages12
JournalMeasurement: Journal of the International Measurement Confederation
DOIs
Publication statusPublished - 01 Jan 2014
Externally publishedYes

Fingerprint

heuristics
Energy storage
Feedback control
Feedback
Controllers
genetic algorithm
Genetic algorithms
photovoltaic system
Multiobjective optimization
Software packages
Particle swarm optimization (PSO)
Farms
electricity
Electricity
farm
software
energy storage
battery
parameter

All Science Journal Classification (ASJC) codes

  • Building and Construction
  • Energy(all)
  • Mechanical Engineering
  • Management, Monitoring, Policy and Law

Cite this

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abstract = "Output power fluctuation of photovoltaic (PV) sources is a problem of practical significance to utilities. To mitigate its impacts, particularly on a weak electricity network, a battery energy storage (BES) system can be used to smooth out and dispatch the output to the utility grid on an hourly basis. This paper presents an optimal control strategy of BES state-of-charge feedback (SOC-FB) control scheme used for output power dispatch of PV farm. The SOC-FB control parameters are optimized by using heuristic optimization techniques such as genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) in Matlab. In addition, an improved BES model is developed in PSCAD/EMTDC software package, in which GA is used to evaluate the optimal parameters. The studied multi-objective optimization problem also considers the evaluation of the optimal size of the BES. The performance of the proposed optimal SOC-FB control scheme is validated by comparing the results obtained from Matlab and PSCAD/EMTDC and with results from previous works. Finally, the best set of parameters are used to further validate the proposed method by using data obtained from the actual output of a grid-connected PV system. {\circledC} 2013 Elsevier Ltd. All rights reserved.",
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AU - Mohamed, Azah

AU - Ibrahim, Ahmad Asrul

AU - Hannan, M. A.

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AB - Output power fluctuation of photovoltaic (PV) sources is a problem of practical significance to utilities. To mitigate its impacts, particularly on a weak electricity network, a battery energy storage (BES) system can be used to smooth out and dispatch the output to the utility grid on an hourly basis. This paper presents an optimal control strategy of BES state-of-charge feedback (SOC-FB) control scheme used for output power dispatch of PV farm. The SOC-FB control parameters are optimized by using heuristic optimization techniques such as genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) in Matlab. In addition, an improved BES model is developed in PSCAD/EMTDC software package, in which GA is used to evaluate the optimal parameters. The studied multi-objective optimization problem also considers the evaluation of the optimal size of the BES. The performance of the proposed optimal SOC-FB control scheme is validated by comparing the results obtained from Matlab and PSCAD/EMTDC and with results from previous works. Finally, the best set of parameters are used to further validate the proposed method by using data obtained from the actual output of a grid-connected PV system. © 2013 Elsevier Ltd. All rights reserved.

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