基于高维粒子群和多群体遗传算法的定日镜场优化设计

Q3 Engineering

EAI Endorsed Transactions on Energy Web Pub Date : 2024-04-05 DOI:10.4108/ew.5653

Yiwen Huang

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引用次数: 0

摘要

简介：塔式定日镜场是一种新型能源转换方式，具有能源效率高、灵活性强、可持续发展和环境友好等优点。目标：通过对塔式定日镜电场的研究和改进，使其成为一种新型的能源转换方式：通过对塔式定日镜场的研究和改进，促进太阳能利用技术的发展。方法：本文采用单目标优化、高维粒子群算法和多组遗传算法对塔式定日镜场进行计算和优化。结论：本文模型能够合理地解决问题，具有较强的实用性和较高的效率，但高维粒子群算法由于容易得到局部最优解，因此可以引入混沌映射来增加搜索空间的随机性，提高算法的全局搜索能力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Optimization design of heliostat field based on high-dimensional particle swarm and multiple population genetic algorithms

INTRODUCTION: Tower-type heliostat field is a new type of energy conversion, which has the advantages of high energy efficiency, flexibility and sustainability and environmental friendliness. OBJECTIVES: Through the research and improvement of the tower heliostat field to promote the development of solar energy utilization technology. METHODS: In this paper, we calculate and optimize the tower heliostat field by using single objective optimization, high-dimensional particle swarm algorithm and multiple group genetic algorithm. RESULTS: In this case of question setting, average annual optical efficiency is 0.6696; average annual cosine efficiency is 0.7564; annual average shadow occlusion efficiency is 0.9766; average annual truncation efficiency is 0.9975; average annual output thermal power is 35539.1747W; mean annual output thermal power per unit area is 0.5657W.The optimal solution after the initial optimization of the algorithm is that the total number of mirror fields is 6,384 pieces, and the average annual output power per unit area is 530.6W. CONCLUSION: The model of this paper can reasonably solve the problem and has strong practicability and high efficiency, but high dimensional particle swarm algorithm due to easily get local optimal solution, so can introduce the chaotic mapping to increase the randomness of the search space, improve the global search ability of the algorithm.

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来源期刊

EAI Endorsed Transactions on Energy Web Energy-Energy Engineering and Power Technology

CiteScore

2.60

自引率

0.00%

发文量

审稿时长

10 weeks

期刊介绍： With ICT pervading everyday objects and infrastructures, the ‘Future Internet’ is envisioned to undergo a radical transformation from how we know it today (a mere communication highway) into a vast hybrid network seamlessly integrating knowledge, people and machines into techno-social ecosystems whose behaviour transcends the boundaries of today’s engineering science. As the internet of things continues to grow, billions and trillions of data bytes need to be moved, stored and shared. The energy thus consumed and the climate impact of data centers are increasing dramatically, thereby becoming significant contributors to global warming and climate change. As reported recently, the combined electricity consumption of the world’s data centers has already exceeded that of some of the world''s top ten economies. In the ensuing process of integrating traditional and renewable energy, monitoring and managing various energy sources, and processing and transferring technological information through various channels, IT will undoubtedly play an ever-increasing and central role. Several technologies are currently racing to production to meet this challenge, from ‘smart dust’ to hybrid networks capable of controlling the emergence of dependable and reliable green and energy-efficient ecosystems – which we generically term the ‘energy web’ – calling for major paradigm shifts highly disruptive of the ways the energy sector functions today. The EAI Transactions on Energy Web are positioned at the forefront of these efforts and provide a forum for the most forward-looking, state-of-the-art research bringing together the cross section of IT and Energy communities. The journal will publish original works reporting on prominent advances that challenge traditional thinking.