{"title":"Reconfiguration of PV array for improved performance under different partial shading conditions using Roulette Barrel Shifter approach","authors":"Shivam Kushwaha , Ranjeet Singh , Ranjana Yadav , Vinod Kumar Yadav , Tanmay Yadav , Shivam Singh","doi":"10.1016/j.enconman.2024.119151","DOIUrl":null,"url":null,"abstract":"<div><div>This article proposes an innovative reconfiguration technique called Roulette Barrel Shifter (RBS) for Total Cross Tied (TCT) connected PV arrays. Inspired by a spinning roulette wheel and the barrel shifter from digital signal processing, it shifts or rotates input data bits by a number of bits. Unlike other methods, RBS does not require advanced maximum power point tracking devices, sensors, or complex switching mechanisms, making it more cost-effective. Simulation studies on 9 × 9 and 10 × 10 PV arrays under Partial Shading (PS) conditions, as well as experimental validation on a 5 × 5 array, demonstrate that RBS increases power by up to 15.45 % compared to TCT. The algorithm is also tested for scalability and adaptability on a large solar plant (4 MW, 2175 V, 25 × 750 PV array). For the first time, the article introduces a unique wiring loss (WL) performance metric using the k-means algorithm. Based on this metric, RBS is shown to reduce WL by up to 6.98 % compared to other recently published methods. Comparative analysis reveals that RBS reduces mismatch loss (ML) by up to 61.41 % compared to TCT, establishing its superiority over existing dynamic reconfiguration approaches in both performance and efficiency across various scales of solar arrays.</div></div>","PeriodicalId":11664,"journal":{"name":"Energy Conversion and Management","volume":"322 ","pages":"Article 119151"},"PeriodicalIF":9.9000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Conversion and Management","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0196890424010926","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
This article proposes an innovative reconfiguration technique called Roulette Barrel Shifter (RBS) for Total Cross Tied (TCT) connected PV arrays. Inspired by a spinning roulette wheel and the barrel shifter from digital signal processing, it shifts or rotates input data bits by a number of bits. Unlike other methods, RBS does not require advanced maximum power point tracking devices, sensors, or complex switching mechanisms, making it more cost-effective. Simulation studies on 9 × 9 and 10 × 10 PV arrays under Partial Shading (PS) conditions, as well as experimental validation on a 5 × 5 array, demonstrate that RBS increases power by up to 15.45 % compared to TCT. The algorithm is also tested for scalability and adaptability on a large solar plant (4 MW, 2175 V, 25 × 750 PV array). For the first time, the article introduces a unique wiring loss (WL) performance metric using the k-means algorithm. Based on this metric, RBS is shown to reduce WL by up to 6.98 % compared to other recently published methods. Comparative analysis reveals that RBS reduces mismatch loss (ML) by up to 61.41 % compared to TCT, establishing its superiority over existing dynamic reconfiguration approaches in both performance and efficiency across various scales of solar arrays.
期刊介绍:
The journal Energy Conversion and Management provides a forum for publishing original contributions and comprehensive technical review articles of interdisciplinary and original research on all important energy topics.
The topics considered include energy generation, utilization, conversion, storage, transmission, conservation, management and sustainability. These topics typically involve various types of energy such as mechanical, thermal, nuclear, chemical, electromagnetic, magnetic and electric. These energy types cover all known energy resources, including renewable resources (e.g., solar, bio, hydro, wind, geothermal and ocean energy), fossil fuels and nuclear resources.