Guanhong Dai
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Guanhong Dai has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Qianhan Chen
School of Automation, Guangdong University of Technology, Guangzhou 510006, China
1 shared publication - Xiaoqiang Li
School of Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, China
1 shared publication - Yangyu Chen
School of Automation, Guangdong University of Technology, Guangzhou 510006, China
1 shared publication - Yu Wang
School of Automation, Guangdong University of Technology, Guangzhou, China
1 shared publication - Zhan Shen
Southeast University
1 shared publication
Latest Publications
- Open Access
A Collaborative Optimization Strategy for Photovoltaic Array Layout Based on the Lemur Optimization Algorithm
The performance of large-scale photovoltaic (PV) power plants is strongly influenced by array layout parameters including module tilt angle, azimuth angle, and row spacing. These geometric variables jointly determine solar irradiance geometry, shading losses, and land-use efficiency, affecting annual energy yield and levelized cost of electricity. To achieve multi-objective comprehensive optimization of array layout parameters for a PV power generation system, a collaborative optimization strategy for PV array layout based on the lemur optimization (LO) algorithm is proposed in this paper. The method couples the Perez anisotropic irradiance model with a dynamic shading irradiance geometric model to simulate the effective insolation, incorporating land availability, shading thresholds, and maintenance access requirements. In addition, the LO algorithm is employed to solve resulting nonlinear and constrained problems, enabling an efficient global search across large parameter spaces. The case studies in Lianyungang, Dalian, and Fuzhou City show that the proposed scheme based on the LO algorithm improves annual energy yield compared with the existing optimization schemes, providing new theoretical methods and engineering application paths for the optimal layout of PV arrays.
Open AccessA Collaborative Optimization Strategy for Photovoltaic Array Layout Based on the Lemur Optimization Algorithm
The performance of large-scale photovoltaic (PV) power plants is strongly influenced by array layout parameters including module tilt angle, azimuth angle, and row spacing. These geometric variables jointly determine solar irradiance geometry, shading losses, and land-use efficiency, affecting annual energy yield and levelized cost of electricity. To achieve multi-objective comprehensive optimization of array layout parameters for a PV power generation system, a collaborative optimization strategy for PV array layout based on the lemur optimization (LO) algorithm is proposed in this paper. The method couples the Perez anisotropic irradiance model with a dynamic shading irradiance geometric model to simulate the effective insolation, incorporating land availability, shading thresholds, and maintenance access requirements. In addition, the LO algorithm is employed to solve resulting nonlinear and constrained problems, enabling an efficient global search across large parameter spaces. The case studies in Lianyungang, Dalian, and Fuzhou City show that the proposed scheme based on the LO algorithm improves annual energy yield compared with the existing optimization schemes, providing new theoretical methods and engineering application paths for the optimal layout of PV arrays.