Proposal of a novel mixed integer linear programming model for site selection of a wind power plant based on power maximization with use of mixed type wind turbines

Abstract

Several methods that have been developed to obtain energy, which is indispensable for life and whose necessity has increased geometrically in the course of time, are no longer sustainable. Therefore, human being has headed towards sustainable alternative energy sources. Wind has been one of the most interested renewable energy sources for human as of the beginning of the 20th century. This study focuses on one of the most important work items at the establishment phase of this important energy source, power plant site selection. Within the scope of linear programming perspective, two models were presented based on mixed integer linear programming. The first model provides employment of single-type wind turbine on the selected site, whereas the second model, which was developed within the current study, aims additional increase in total power output by allowing employment of multiple-type wind turbine on the selected site. The same region showed up as the most appropriate site to establish wind power plant as a result of both models of the study.

Standardizing the factors used in wind farm site suitability models: A review

“…Siting factors classified as environmental or technical often serve as constraints, such as limited development in protected wildlife areas [ 104 , 155 , 164 ], land that is too elevated or steep [ 79 , 140 , 142 ], or areas with insufficient wind speeds [ 123 , 139 , 178 ]. Similarly, economic siting factors like land leasing and maintenance costs are often incorporated into WiFSS models within a subset of equations that calculate cost competitiveness of candidate wind farm sites [ 122 , 165 , 177 , 200 , 214 ], hence their common classification.…”

“…Table 2 b shows that, of the 21 offshore WiFSS studies, six (29%) studies that included Distance to Shipping Lanes did not classify their siting factors [ 176 , 178 , 183 , 184 , 190 , 215 ]. Of these six studies, Wu et al [ 190 ] and Zhang et al [ 215 ] are non-GIS-based approaches (of the 32 non-GIS-based studies in this review, eight studies did not classify their siting factors [ 186 , [204] , [205] , [206] , [207] , 212 , 214 , 216 ], and eight studies classified only some of them [ 100 , 190 , 194 , 196 , 197 , 199 , 203 , 215 ]). The other four studies that included Distance to Shipping Lanes are GIS-based, despite Tercan et al [ 178 ] stressing the importance of having technical, economic, environmental, and social criteria for evaluating potential offshore wind farm sites.…”

“… Inconsistent implementation of constraints. Table 3 suggests a common set of constraints employed by WiFSS studies, such as a minimum wind speed [ 123 , 167 , 185 , 195 , 214 ], limiting wind farm construction in protected areas [ 71 , 74 , 78 , 143 , 154 ], a minimum distance from urban centers [ 149 , 152 , 161 , 181 , 213 ], to name a few. However, the magnitude of these common constraints varies widely.…”

“…This difference presents a planning risk, knowing the negative impacts of improper wind farm siting on avian species [ 61 , 62 ]. The decision to implement siting factors for either constraint or evaluation may be motivated by usage of these factors in prior studies, and/or the modelers' objectives, for example, the evaluation of wind resources in remaining locations after applying all other siting factors as constraints [ 162 , [164] , [165] , [166] , [167] , 214 ].…”

Determining Factors and Scenarios of Influence on Consumer Migration from the Regulated Market to the Deregulated Electricity Market

“…Energy consumption in the world continues to grow considerably [1,2], and electricity represents the highest rate of this growth [3]. Justified by the growth of the world population, development of urbanization, industrialization, and technologies [4]. Data from the U.S. Energy Information Administration estimates that by 2050 worldwide there will be an increase of approximately 49% in energy use, with Asia being the more expressive growth [5].…”