Centralized Photovoltaic Heliostat Field Layout and Optical Perception Optimization Based on Improved Dung Beetle Optimization Algorithm

Bin Liu; Chengyu Jiang; Biguang Kong; Jiayu Wu; Junwei Yang

doi:10.46604/ijeti.2024.13683

Authors

Bin Liu Nujiang Power Supply Bureau; Yunnan Power Grid Company Market Department, Yunnan Power Grid Co., Ltd, Kunming, China
Chengyu Jiang Yunnan Power Grid Company Market Department, Yunnan Power Grid Co., Ltd, Kunming, China/Faculty of Civil Aviation and Aeronautical, Kunming University of Science & Technology, Kunming, China/Longshine Technology Group Co., Ltd, Wuxi, China
Biguang Kong Nujiang Power Supply Bureau, Yunnan Power Grid Co., Ltd, Kunming, China
Jiayu Wu Faculty of Transportation Engineering, Kunming University of Science & Technology, Kunming, China/Longshine Technology Group Co., Ltd, Wuxi, China
Junwei Yang Longshine Technology Group Co., Ltd, Wuxi, China

DOI:

https://doi.org/10.46604/ijeti.2024.13683

Keywords:

heliostat field, dung beetle optimization algorithm, crossover strategy, random walk strategy

Abstract

The gradual depletion of fossil fuels underscores the pressing need for technological advancements in renewable energy. These technologies are essential to address the inefficiencies in power generation from heliostat fields. This paper proposes an innovative heliostat field layout model aimed at significantly enhancing the efficiency of photovoltaic power generation. By carefully optimizing the positioning, height, and size of the heliostats, the model results in a substantial increase in annual heat output. Additionally, an improved Dung Beetle optimization algorithm (RCDBO) is introduced, which integrates random walk and cross strategy to enhance solving efficiency and accuracy while effectively avoiding premature convergence. Simulations demonstrate that the proposed algorithm achieves a 3% increase in efficiency compared to the traditional DBO algorithm, confirming the superiority of the RCDBO algorithm.

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