Hari Bhaskaran Anangapal, Bastin Jeyaraj, Kirubakaran Victor
{"title":"印度近海风电场容量密度优化--案例研究","authors":"Hari Bhaskaran Anangapal, Bastin Jeyaraj, Kirubakaran Victor","doi":"10.1007/s10668-024-05278-x","DOIUrl":null,"url":null,"abstract":"<p>A significant challenge in offshore wind energy is understanding and reducing wake losses from wind farms, which can affect downstream turbine efficiency by 10–20% and determine the optimal capacity of wind farms within a defined area. This study aimed to determine the optimal wind farm capacity density in offshore subzone B<sub>1</sub>, which is off the coast of Tamil Nadu, India. The objectives include maximizing the installable offshore wind capacity, achieving the highest possible annual energy production or capacity utilization factor (CUF), maintaining array losses below 10%, and minimizing the levelized cost of energy (LCoE). The methodology involves analysing the ERA5 reanalysis of wind data, assessing various wind farm capacity densities (3–7 MW/km²), and evaluating the impact on turbine spacing, array losses, and LCoE. This study revealed a significant correlation between the wind farm capacity density and the LCoE, indicating an upwards trend in the LCoE with increasing capacity density. An optimal density of 5.17 MW/km² was identified for subzone B<sub>1</sub>, accommodating 72 turbines with a total capacity of 1080 MW and an LCoE of Rs. 8.86/kWh. This configuration balances energy production and costs while providing critical information for future offshore wind projects in the region. This study underscores the importance of strategic turbine placement and continuous innovation in wind energy research.</p>","PeriodicalId":540,"journal":{"name":"Environment, Development and Sustainability","volume":"58 1","pages":""},"PeriodicalIF":4.7000,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization of India’s offshore wind farm capacity density - a case study\",\"authors\":\"Hari Bhaskaran Anangapal, Bastin Jeyaraj, Kirubakaran Victor\",\"doi\":\"10.1007/s10668-024-05278-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>A significant challenge in offshore wind energy is understanding and reducing wake losses from wind farms, which can affect downstream turbine efficiency by 10–20% and determine the optimal capacity of wind farms within a defined area. This study aimed to determine the optimal wind farm capacity density in offshore subzone B<sub>1</sub>, which is off the coast of Tamil Nadu, India. The objectives include maximizing the installable offshore wind capacity, achieving the highest possible annual energy production or capacity utilization factor (CUF), maintaining array losses below 10%, and minimizing the levelized cost of energy (LCoE). The methodology involves analysing the ERA5 reanalysis of wind data, assessing various wind farm capacity densities (3–7 MW/km²), and evaluating the impact on turbine spacing, array losses, and LCoE. This study revealed a significant correlation between the wind farm capacity density and the LCoE, indicating an upwards trend in the LCoE with increasing capacity density. An optimal density of 5.17 MW/km² was identified for subzone B<sub>1</sub>, accommodating 72 turbines with a total capacity of 1080 MW and an LCoE of Rs. 8.86/kWh. This configuration balances energy production and costs while providing critical information for future offshore wind projects in the region. This study underscores the importance of strategic turbine placement and continuous innovation in wind energy research.</p>\",\"PeriodicalId\":540,\"journal\":{\"name\":\"Environment, Development and Sustainability\",\"volume\":\"58 1\",\"pages\":\"\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2024-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environment, Development and Sustainability\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1007/s10668-024-05278-x\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environment, Development and Sustainability","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1007/s10668-024-05278-x","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Optimization of India’s offshore wind farm capacity density - a case study
A significant challenge in offshore wind energy is understanding and reducing wake losses from wind farms, which can affect downstream turbine efficiency by 10–20% and determine the optimal capacity of wind farms within a defined area. This study aimed to determine the optimal wind farm capacity density in offshore subzone B1, which is off the coast of Tamil Nadu, India. The objectives include maximizing the installable offshore wind capacity, achieving the highest possible annual energy production or capacity utilization factor (CUF), maintaining array losses below 10%, and minimizing the levelized cost of energy (LCoE). The methodology involves analysing the ERA5 reanalysis of wind data, assessing various wind farm capacity densities (3–7 MW/km²), and evaluating the impact on turbine spacing, array losses, and LCoE. This study revealed a significant correlation between the wind farm capacity density and the LCoE, indicating an upwards trend in the LCoE with increasing capacity density. An optimal density of 5.17 MW/km² was identified for subzone B1, accommodating 72 turbines with a total capacity of 1080 MW and an LCoE of Rs. 8.86/kWh. This configuration balances energy production and costs while providing critical information for future offshore wind projects in the region. This study underscores the importance of strategic turbine placement and continuous innovation in wind energy research.
期刊介绍:
Environment, Development and Sustainability is an international and multidisciplinary journal covering all aspects of the environmental impacts of socio-economic development. It is also concerned with the complex interactions which occur between development and environment, and its purpose is to seek ways and means for achieving sustainability in all human activities aimed at such development. The subject matter of the journal includes the following and related issues:
-mutual interactions among society, development and environment, and their implications for sustainable development
-technical, economic, ethical and philosophical aspects of sustainable development
-global sustainability - the obstacles and ways in which they could be overcome
-local and regional sustainability initiatives, their practical implementation, and relevance for use in a wider context
-development and application of indicators of sustainability
-development, verification, implementation and monitoring of policies for sustainable development
-sustainable use of land, water, energy and biological resources in development
-impacts of agriculture and forestry activities on soil and aquatic ecosystems and biodiversity
-effects of energy use and global climate change on development and sustainability
-impacts of population growth and human activities on food and other essential resources for development
-role of national and international agencies, and of international aid and trade arrangements in sustainable development
-social and cultural contexts of sustainable development
-role of education and public awareness in sustainable development
-role of political and economic instruments in sustainable development
-shortcomings of sustainable development and its alternatives.