Concentrator shape optimization using particle swarm optimization for solar concentrating photovoltaic applications

Rehman, Naveed ur; Uzair, Muhammad

doi:10.1016/j.renene.2021.12.015

Cited by 8 publications

(2 citation statements)

References 32 publications

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“…PSO and ACA are used to optimise robots. Among them, PSO is used for global path planning of robots and ACA is used for local path planning of robots [14][15]. PSO is a simple and effective optimisation algorithm that has wide applications in various types of functions.…”

Section: A Improved Pso For Global Path Planningmentioning

confidence: 99%

Path Planning of Agricultural Information Collection Robot Integrating Ant Colony Algorithm and Particle Swarm Algorithm

Wu,

Chen,

Liu

2024

IEEE Access

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Faced with complex and ever-changing environmental conditions in the agricultural field, efficient agricultural information gathering is crucial for optimising agricultural output. Therefore, a new path planning algorithm combining ant colony algorithm and particle swarm optimization is proposed in this study. The aim is to achieve fast and accurate path planning for agricultural information gathering robots in diverse agricultural environments. The global search ability of particle swarm optimization algorithm in finding optimal paths and the local search advantage of ant colony algorithm in obstacle avoidance are used to optimise the movement strategy of robots in agricultural environments. The research results showed that the global path planning distance of this method was 19.328m. The execution time was 0.97s. In local path planning, the proposed algorithm had a fitness function value of 30.123 when the number of iterations reached 53. In mixed path planning, the proposed algorithm reduced the movement time by 3.2s. The conclusion shows that the algorithm proposed in this study has high applicability and efficiency in practical applications, providing an effective strategy for path planning of agricultural information gathering robots. It has important practical significance for promoting the development of intelligent agriculture.

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Section: A Improved Pso For Global Path Planningmentioning

confidence: 99%

Path Planning of Agricultural Information Collection Robot Integrating Ant Colony Algorithm and Particle Swarm Algorithm

Wu,

Chen,

Liu

2024

IEEE Access

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“…They are typically controlled by the Arduino microcontroller and serve as switches to turn these devices on or off as needed. 10.…”

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confidence: 99%

Sun Tracing Solar Panel in Two Axis Using Arduino and Servo Motors

Somani

2024

IJSREM

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In the contemporary context, the variability in climatic changes has reached critical levels. These changes stem from both natural phenomena and human-induced activities, notably global warming and the emission of greenhouse gases, which are significantly impacting climatic conditions worldwide. Over the past decade, there has been a notable surge in the demand for reliable and abundant electrical energy sourced from renewable energy alternatives. This shift towards renewable energy is pivotal in addressing energy crises faced by many countries. Governments have initiated measures to reduce reliance on conventional energy sources while actively promoting the adoption of renewable energy sources such as hydro and solar power. Solar power, in particular, stands out as a prominent renewable energy source. With the sun being an abundant and inexhaustible source of energy, solar power holds immense potential. The solar energy received by the Earth is estimated to be approximately 1.8*10^11 MW. To harness this energy efficiently, maximizing the absorption of solar power by photovoltaic systems is imperative. Research indicates that employing a dual-axis tracking system, as opposed to a fixed system, can substantially increase power output by 40% to 60%. Solar energy systems have witnessed significant advancements over the past few decades and are now widely utilized for various household and industrial applications. These systems typically rely on solar collectors designed to capture the sun's energy and convert it into either electrical power or thermal energy. The efficacy of such systems hinges on the ability to capture solar energy effectively. Consequently, developing tracking schemes capable of aligning with the sun's trajectory throughout the day, year-round, has garnered considerable attention in research and development initiatives. This emphasis on enhancing solar energy capture underscores the importance of innovation and technological advancements in the renewable energy sector. By harnessing the vast potential of solar power and optimizing its utilization through advanced tracking systems, societies can mitigate reliance on fossil fuels, combat climate change, and foster sustainable development pathways.

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Concentrating photovoltaic systems: a review of temperature effects and components

Zou,

Qin,

Liu

et al. 2023

J Therm Anal Calorim

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Concentrator shape optimization using particle swarm optimization for solar concentrating photovoltaic applications

Cited by 8 publications

References 32 publications

Path Planning of Agricultural Information Collection Robot Integrating Ant Colony Algorithm and Particle Swarm Algorithm

Path Planning of Agricultural Information Collection Robot Integrating Ant Colony Algorithm and Particle Swarm Algorithm

Sun Tracing Solar Panel in Two Axis Using Arduino and Servo Motors

Concentrating photovoltaic systems: a review of temperature effects and components

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