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, Hannan M A

Research output: Contribution to journalArticle

14 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.

Original languageEnglish
Pages (from-to)15-25
Number of pages11
JournalMeasurement: Journal of the International Measurement Confederation
Volume49
Issue number1
DOIs
Publication statusPublished - Mar 2014

Fingerprint

Heuristic Optimization
Energy Storage
Storage System
energy storage
Battery
Energy storage
electric batteries
controllers
feedback control
Charge
Feedback Control
Feedback control
Feedback
Controller
Controllers
optimization
output
Output
genetic algorithms
MATLAB

Keywords

  • Battery energy storage
  • Optimal control
  • Photovoltaic
  • Renewable energy dispatch

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Applied Mathematics

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.",
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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.

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