{"id":{"repo_id":"ttu","oai_identifier":"oai:ttu-ir.tdl.org:2346/106808"},"canonical_url":"https://search.dev.ndltd.org/etd/ttu/oai:ttu-ir.tdl.org:2346/106808","repository":{"repo_id":"ttu","name":"Texas Technology University","base_url":"https://ttu-ir.tdl.org/server/oai/request"},"display":{"title":"Evaluating the Effect of Splitting Wind Farms in Multiple Sites and Developing a Model to Select the Best Locations to Install Wind Farms","abstract":"As the large-scale wind power is connected to the grid, challenges are brought to the security and stability operation of the power system, and therefore it is very important to know how we can get more power from regional multiple wind sites by installing wind farms in them. Since there are many important factors affecting the sites selection to install wind farms this research investigates the effect of splitting wind farms on several factors as contrasted with a single wind farm site and explores the reasons to support distributing wind farm over large areas into multiple sites. Texas is a national leader in the wind energy industry and ranks first in the country for both installed and under construction wind capacity. Moreover, wind data for sites in Texas are available. Therefore, Texas is selected as case study for this research. Wind data of five sites in Texas have been gathered for this study. First, wind data is gathered for two years (2012-2013) with time steps of one hour. Second, power outputs for all sites are estimated using the power curve formula and SIEMENS SWT-3.0-101 wind turbine. Finally, the effects of different factors on single and multiple wind farms are explored and compared. Then, using the results from last section, a model is developed to prioritize sites and rank them based on multiple criteria which are computed during this research. The results suggested splitting wind farms might have advantages over a wind farm with a single site. The results implied that a wind farm with two sites meets the higher amount of customer's demand, reduces the size of the backup conventional generator, and decreases the number of field shut down and power variability. Second part of results demonstrated the important criteria and method, which affect the decision making to prioritize sites and. It also showed the best solution or the best pair to install wind farm, which can be changed by changing the criteria and their weights.","abstract_html":"As the large-scale wind power is connected to the grid, challenges are brought to the security and stability operation of the power system, and therefore it is very important to know how we can get more power from regional multiple wind sites by installing wind farms in them. Since there are many important factors affecting the sites selection to install wind farms this research investigates the effect of splitting wind farms on several factors as contrasted with a single wind farm site and explores the reasons to support distributing wind farm over large areas into multiple sites. Texas is a national leader in the wind energy industry and ranks first in the country for both installed and under construction wind capacity. Moreover, wind data for sites in Texas are available. Therefore, Texas is selected as case study for this research. Wind data of five sites in Texas have been gathered for this study. First, wind data is gathered for two years (2012-2013) with time steps of one hour. Second, power outputs for all sites are estimated using the power curve formula and SIEMENS SWT-3.0-101 wind turbine. Finally, the effects of different factors on single and multiple wind farms are explored and compared. Then, using the results from last section, a model is developed to prioritize sites and rank them based on multiple criteria which are computed during this research. The results suggested splitting wind farms might have advantages over a wind farm with a single site. The results implied that a wind farm with two sites meets the higher amount of customer's demand, reduces the size of the backup conventional generator, and decreases the number of field shut down and power variability. Second part of results demonstrated the important criteria and method, which affect the decision making to prioritize sites and. It also showed the best solution or the best pair to install wind farm, which can be changed by changing the criteria and their weights.","abstract_has_math":false,"creators":["Naderi, Nazanin"],"institution":"Texas Tech University","degree_name":"Doctor of Philosophy","degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Smith, Milton","Kobza, John"],"committee_chairs":[],"committee_members":["Beruvides, Mario","Smith, James"],"year":2015,"date_issued":"2015-12","date_published":"2015-12","updated_at":"2026-07-24T05:04:54Z","subjects":[],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2346/106808","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Smith, Milton","Kobza, John"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Beruvides, Mario","Smith, James"]},{"key":"dc:creator","label":"Author","values":["Naderi, Nazanin"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-03-30T14:59:52Z"]},{"key":"dc:date.issued","label":"Date","values":["2015-12"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Texas Tech University"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/2346/106808"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["As the large-scale wind power is connected to the grid, challenges are brought to the security and stability operation of the power system, and therefore it is very important to know how we can get more power from regional multiple wind sites by installing wind farms in them. Since there are many important factors affecting the sites selection to install wind farms this research investigates the effect of splitting wind farms on several factors as contrasted with a single wind farm site and explores the reasons to support distributing wind farm over large areas into multiple sites. Texas is a national leader in the wind energy industry and ranks first in the country for both installed and under construction wind capacity. Moreover, wind data for sites in Texas are available. Therefore, Texas is selected as case study for this research. Wind data of five sites in Texas have been gathered for this study. First, wind data is gathered for two years (2012-2013) with time steps of one hour. Second, power outputs for all sites are estimated using the power curve formula and SIEMENS SWT-3.0-101 wind turbine. Finally, the effects of different factors on single and multiple wind farms are explored and compared. Then, using the results from last section, a model is developed to prioritize sites and rank them based on multiple criteria which are computed during this research. The results suggested splitting wind farms might have advantages over a wind farm with a single site. The results implied that a wind farm with two sites meets the higher amount of customer's demand, reduces the size of the backup conventional generator, and decreases the number of field shut down and power variability. Second part of results demonstrated the important criteria and method, which affect the decision making to prioritize sites and. It also showed the best solution or the best pair to install wind farm, which can be changed by changing the criteria and their weights."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Evaluating the Effect of Splitting Wind Farms in Multiple Sites and Developing a Model to Select the Best Locations to Install Wind Farms"]}]}],"canonical_facts":{"dc:contributor.advisor":["Smith, Milton","Kobza, John"],"dc:contributor.committeemember":["Beruvides, Mario","Smith, James"],"dc:creator":["Naderi, Nazanin"],"dc:date.accessioned":["2026-03-30T14:59:52Z"],"dc:date.issued":["2015-12"],"dc:description.abstract":["As the large-scale wind power is connected to the grid, challenges are brought to the security and stability operation of the power system, and therefore it is very important to know how we can get more power from regional multiple wind sites by installing wind farms in them. Since there are many important factors affecting the sites selection to install wind farms this research investigates the effect of splitting wind farms on several factors as contrasted with a single wind farm site and explores the reasons to support distributing wind farm over large areas into multiple sites. Texas is a national leader in the wind energy industry and ranks first in the country for both installed and under construction wind capacity. Moreover, wind data for sites in Texas are available. Therefore, Texas is selected as case study for this research. Wind data of five sites in Texas have been gathered for this study. First, wind data is gathered for two years (2012-2013) with time steps of one hour. Second, power outputs for all sites are estimated using the power curve formula and SIEMENS SWT-3.0-101 wind turbine. Finally, the effects of different factors on single and multiple wind farms are explored and compared. Then, using the results from last section, a model is developed to prioritize sites and rank them based on multiple criteria which are computed during this research. The results suggested splitting wind farms might have advantages over a wind farm with a single site. The results implied that a wind farm with two sites meets the higher amount of customer's demand, reduces the size of the backup conventional generator, and decreases the number of field shut down and power variability. Second part of results demonstrated the important criteria and method, which affect the decision making to prioritize sites and. It also showed the best solution or the best pair to install wind farm, which can be changed by changing the criteria and their weights."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["https://hdl.handle.net/2346/106808"],"dc:title":["Evaluating the Effect of Splitting Wind Farms in Multiple Sites and Developing a Model to Select the Best Locations to Install Wind Farms"],"dc:type":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy"],"thesis:institution_name":["Texas Tech University"]},"updated_at":"2026-07-24T05:04:54Z"}