Accelerating parameter estimation for photovoltaic models via parallel particle swarm optimization

Jieming Ma; Ka Lok Man; T. O. Ting; Nan Zhang; Sheng Uei Guan; Prudence W.H. Wong

doi:10.1109/IS3C.2014.56

Accelerating parameter estimation for photovoltaic models via parallel particle swarm optimization

Jieming Ma
, Ka Lok Man
, T. O. Ting
, Nan Zhang
, Sheng Uei Guan
, Prudence W.H. Wong

Xi'an Jiaotong-Liverpool University

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

8 Citations (Scopus)

Abstract

Bio-inspired metaheuristic algorithms have been widely proposed to estimate parameters of photovoltaic (PV) models in recent years due to its ability to handle nonlinear functions regardless of the derivatives information. However, these algorithms normally utilize multiple agents/particles in the search process, and it takes much time to search the possible solutions in the whole search domain by sequential computing devices. This paper proposes parallel particle swarm optimization (PPSO) method to extract and estimate the parameters of a PV model. The algorithm is implemented in OpenCL and is executed on Nvidia multi-core GPUs. From the simulation results, it is observed that the proposed method is capable of accelerating the computational speed with the same accuracy in comparison to sequential particle swarm optimization (PSO).

Original language	English
Title of host publication	Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014
Publisher	IEEE Computer Society
Pages	175-178
Number of pages	4
ISBN (Print)	9781479952779
DOIs	https://doi.org/10.1109/IS3C.2014.56
Publication status	Published - 2014
Event	2nd International Symposium on Computer, Consumer and Control, IS3C 2014 - Taichung, Taiwan, Province of China Duration: 10 Jun 2014 → 12 Jun 2014

Publication series

Name	Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014

Conference

Conference	2nd International Symposium on Computer, Consumer and Control, IS3C 2014
Country/Territory	Taiwan, Province of China
City	Taichung
Period	10/06/14 → 12/06/14

Keywords

OpenCL
PV power generation
Photovoltaic (PV)
heterogeneous computing
parallel computing
parameter estimation
particle swarm optimization (PSO)

Access to Document

10.1109/IS3C.2014.56

Cite this

Ma, J., Man, K. L., Ting, T. O., Zhang, N., Guan, S. U., & Wong, P. W. H. (2014). Accelerating parameter estimation for photovoltaic models via parallel particle swarm optimization. In Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014 (pp. 175-178). Article 6845488 (Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014). IEEE Computer Society. https://doi.org/10.1109/IS3C.2014.56

Ma, Jieming ; Man, Ka Lok ; Ting, T. O. et al. / Accelerating parameter estimation for photovoltaic models via parallel particle swarm optimization. Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014. IEEE Computer Society, 2014. pp. 175-178 (Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014).

@inproceedings{208cac508c6745219116e92023e67b6a,

title = "Accelerating parameter estimation for photovoltaic models via parallel particle swarm optimization",

abstract = "Bio-inspired metaheuristic algorithms have been widely proposed to estimate parameters of photovoltaic (PV) models in recent years due to its ability to handle nonlinear functions regardless of the derivatives information. However, these algorithms normally utilize multiple agents/particles in the search process, and it takes much time to search the possible solutions in the whole search domain by sequential computing devices. This paper proposes parallel particle swarm optimization (PPSO) method to extract and estimate the parameters of a PV model. The algorithm is implemented in OpenCL and is executed on Nvidia multi-core GPUs. From the simulation results, it is observed that the proposed method is capable of accelerating the computational speed with the same accuracy in comparison to sequential particle swarm optimization (PSO).",

keywords = "OpenCL, PV power generation, Photovoltaic (PV), heterogeneous computing, parallel computing, parameter estimation, particle swarm optimization (PSO)",

author = "Jieming Ma and Man, \{Ka Lok\} and Ting, \{T. O.\} and Nan Zhang and Guan, \{Sheng Uei\} and Wong, \{Prudence W.H.\}",

year = "2014",

doi = "10.1109/IS3C.2014.56",

language = "English",

isbn = "9781479952779",

series = "Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014",

publisher = "IEEE Computer Society",

pages = "175--178",

booktitle = "Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014",

note = "2nd International Symposium on Computer, Consumer and Control, IS3C 2014 ; Conference date: 10-06-2014 Through 12-06-2014",

}

Ma, J , Man, KL, Ting, TO, Zhang, N, Guan, SU & Wong, PWH 2014, Accelerating parameter estimation for photovoltaic models via parallel particle swarm optimization. in Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014., 6845488, Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014, IEEE Computer Society, pp. 175-178, 2nd International Symposium on Computer, Consumer and Control, IS3C 2014, Taichung, Taiwan, Province of China, 10/06/14. https://doi.org/10.1109/IS3C.2014.56

Accelerating parameter estimation for photovoltaic models via parallel particle swarm optimization. / Ma, Jieming ; Man, Ka Lok; Ting, T. O. et al.
Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014. IEEE Computer Society, 2014. p. 175-178 6845488 (Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - Accelerating parameter estimation for photovoltaic models via parallel particle swarm optimization

AU - Ma, Jieming

AU - Man, Ka Lok

AU - Ting, T. O.

AU - Zhang, Nan

AU - Guan, Sheng Uei

AU - Wong, Prudence W.H.

PY - 2014

Y1 - 2014

N2 - Bio-inspired metaheuristic algorithms have been widely proposed to estimate parameters of photovoltaic (PV) models in recent years due to its ability to handle nonlinear functions regardless of the derivatives information. However, these algorithms normally utilize multiple agents/particles in the search process, and it takes much time to search the possible solutions in the whole search domain by sequential computing devices. This paper proposes parallel particle swarm optimization (PPSO) method to extract and estimate the parameters of a PV model. The algorithm is implemented in OpenCL and is executed on Nvidia multi-core GPUs. From the simulation results, it is observed that the proposed method is capable of accelerating the computational speed with the same accuracy in comparison to sequential particle swarm optimization (PSO).

AB - Bio-inspired metaheuristic algorithms have been widely proposed to estimate parameters of photovoltaic (PV) models in recent years due to its ability to handle nonlinear functions regardless of the derivatives information. However, these algorithms normally utilize multiple agents/particles in the search process, and it takes much time to search the possible solutions in the whole search domain by sequential computing devices. This paper proposes parallel particle swarm optimization (PPSO) method to extract and estimate the parameters of a PV model. The algorithm is implemented in OpenCL and is executed on Nvidia multi-core GPUs. From the simulation results, it is observed that the proposed method is capable of accelerating the computational speed with the same accuracy in comparison to sequential particle swarm optimization (PSO).

KW - OpenCL

KW - PV power generation

KW - Photovoltaic (PV)

KW - heterogeneous computing

KW - parallel computing

KW - parameter estimation

KW - particle swarm optimization (PSO)

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U2 - 10.1109/IS3C.2014.56

DO - 10.1109/IS3C.2014.56

M3 - Conference Proceeding

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T3 - Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014

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BT - Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014

PB - IEEE Computer Society

T2 - 2nd International Symposium on Computer, Consumer and Control, IS3C 2014

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ER -

Ma J , Man KL, Ting TO, Zhang N, Guan SU, Wong PWH. Accelerating parameter estimation for photovoltaic models via parallel particle swarm optimization. In Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014. IEEE Computer Society. 2014. p. 175-178. 6845488. (Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014). doi: 10.1109/IS3C.2014.56

Accelerating parameter estimation for photovoltaic models via parallel particle swarm optimization

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