Abstract
In this paper, a multi-cluster-based particle swarm optimization (MC-PSO) algorithm for photovoltaic (PV) maximum power point tracking (MPPT) is proposed to promote the MPPT performance in the partial shading condition. During the tracking process, each PV module is viewed as a particle and the PV modules with similar characteristics are put into the same cluster. The particles in the same cluster can refer the information to each other to realize the MPPT in the partial shading condition. In addition, multiple sampling points can be obtained at the same time to avoid the misjudgement problem during insolation changing rapidly. Thus, the tracking speed is also improved. The simulation results used by MATLAB is done and compared with the perturbation and observation (P&O) MPPT algorithm. The accuracy of MPPT of the proposed MC-PSO is improved to 96.3% in the partial shading condition. Finally, a 2.1kW prototype is implemented to verify the feasibility. The generated energy using the proposed method compared to the conventional P&O method is increased about 13.3%.
| Original language | English |
|---|---|
| Title of host publication | 2015 IEEE 2nd International Future Energy Electronics Conference, IFEEC 2015 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781479976577 |
| DOIs | |
| Publication status | Published - 2015 Dec 18 |
| Event | 2nd IEEE International Future Energy Electronics Conference, IFEEC 2015 - Taipei, Taiwan Duration: 2015 Nov 1 → 2015 Nov 4 |
Other
| Other | 2nd IEEE International Future Energy Electronics Conference, IFEEC 2015 |
|---|---|
| Country | Taiwan |
| City | Taipei |
| Period | 15-11-01 → 15-11-04 |
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All Science Journal Classification (ASJC) codes
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Electrical and Electronic Engineering
Cite this
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Multicluster-based particle swarm optimization algorithm for photovoltaic maximum power point tracking. / Chen, Wei Ru; Chen, Liang-Rui; Wu, Chia Hsuan; Lai, Ci Min.
2015 IEEE 2nd International Future Energy Electronics Conference, IFEEC 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7361493.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Multicluster-based particle swarm optimization algorithm for photovoltaic maximum power point tracking
AU - Chen, Wei Ru
AU - Chen, Liang-Rui
AU - Wu, Chia Hsuan
AU - Lai, Ci Min
PY - 2015/12/18
Y1 - 2015/12/18
N2 - In this paper, a multi-cluster-based particle swarm optimization (MC-PSO) algorithm for photovoltaic (PV) maximum power point tracking (MPPT) is proposed to promote the MPPT performance in the partial shading condition. During the tracking process, each PV module is viewed as a particle and the PV modules with similar characteristics are put into the same cluster. The particles in the same cluster can refer the information to each other to realize the MPPT in the partial shading condition. In addition, multiple sampling points can be obtained at the same time to avoid the misjudgement problem during insolation changing rapidly. Thus, the tracking speed is also improved. The simulation results used by MATLAB is done and compared with the perturbation and observation (P&O) MPPT algorithm. The accuracy of MPPT of the proposed MC-PSO is improved to 96.3% in the partial shading condition. Finally, a 2.1kW prototype is implemented to verify the feasibility. The generated energy using the proposed method compared to the conventional P&O method is increased about 13.3%.
AB - In this paper, a multi-cluster-based particle swarm optimization (MC-PSO) algorithm for photovoltaic (PV) maximum power point tracking (MPPT) is proposed to promote the MPPT performance in the partial shading condition. During the tracking process, each PV module is viewed as a particle and the PV modules with similar characteristics are put into the same cluster. The particles in the same cluster can refer the information to each other to realize the MPPT in the partial shading condition. In addition, multiple sampling points can be obtained at the same time to avoid the misjudgement problem during insolation changing rapidly. Thus, the tracking speed is also improved. The simulation results used by MATLAB is done and compared with the perturbation and observation (P&O) MPPT algorithm. The accuracy of MPPT of the proposed MC-PSO is improved to 96.3% in the partial shading condition. Finally, a 2.1kW prototype is implemented to verify the feasibility. The generated energy using the proposed method compared to the conventional P&O method is increased about 13.3%.
UR - http://www.scopus.com/inward/record.url?scp=84962415179&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84962415179&partnerID=8YFLogxK
U2 - 10.1109/IFEEC.2015.7361493
DO - 10.1109/IFEEC.2015.7361493
M3 - Conference contribution
BT - 2015 IEEE 2nd International Future Energy Electronics Conference, IFEEC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
ER -