scholarly journals Wind Energy Development in India and a Methodology for Evaluating Performance of Wind Farm Clusters

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Sanjeev H. Kulkarni ◽  
Tumkur Ramakrishnarao Anil ◽  
Rajakumar Dyamenally Gowdar
Keyword(s):  
Wind Energy ◽  
Power Plants ◽  
Wind Farm ◽  
Pairwise Comparison ◽  
Wind Farms ◽  
Analytic Hierarchy ◽  
Healthy Environment ◽  
Indian State ◽  
Wind Energy Development ◽  
Hierarchy Process

With maturity of advanced technologies and urgent requirement for maintaining a healthy environment with reasonable price, India is moving towards a trend of generating electricity from renewable resources. Wind energy production, with its relatively safer and positive environmental characteristics, has evolved from a marginal activity into a multibillion dollar industry today. Wind energy power plants, also known as wind farms, comprise multiple wind turbines. Though there are several wind-mill clusters producing energy in different geographical locations across the world, evaluating their performance is a complex task and is an important focus for stakeholders. In this work an attempt is made to estimate the performance of wind clusters employing a multicriteria approach. Multiple factors that affect wind farm operations are analyzed by taking experts opinions, and a performance ranking of the wind farms is generated. The weights of the selection criteria are determined by pairwise comparison matrices of the Analytic Hierarchy Process (AHP). The proposed methodology evaluates wind farm performance based on technical, economic, environmental, and sociological indicators. Both qualitative and quantitative parameters were considered. Empirical data were collected through questionnaire from the selected wind farms of Belagavi district in the Indian State of Karnataka. This proposed methodology is a useful tool for cluster analysis.

scholarly journals Wealth of Wind and Visitors: Tourist Industry Attitudes towards Wind Energy Development in Iceland

Land ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 693
Author(s):  
Anna Dóra Sæþórsdóttir ◽  
Margrét Wendt ◽  
Edita Tverijonaite
Keyword(s):  
Land Use ◽  
Wind Energy ◽  
Wind Turbines ◽  
Wind Farm ◽  
Service Providers ◽  
Wind Farms ◽  
Energy Development ◽  
Tourism Industry ◽  
Land Use Conflicts ◽  
Wind Energy Development

The interest in harnessing wind energy keeps increasing globally. Iceland is considering building its first wind farms, but its landscape and nature are not only a resource for renewable energy production; they are also the main attraction for tourists. As wind turbines affect how the landscape is perceived and experienced, it is foreseeable that the construction of wind farms in Iceland will create land use conflicts between the energy sector and the tourism industry. This study sheds light on the impacts of wind farms on nature-based tourism as perceived by the tourism industry. Based on 47 semi-structured interviews with tourism service providers, it revealed that the impacts were perceived as mostly negative, since wind farms decrease the quality of the natural landscape. Furthermore, the study identified that the tourism industry considered the following as key factors for selecting suitable wind farm sites: the visibility of wind turbines, the number of tourists and tourist attractions in the area, the area’s degree of naturalness and the local need for energy. The research highlights the importance of analysing the various stakeholders’ opinions with the aim of mitigating land use conflicts and socioeconomic issues related to wind energy development.

Integrated AHP-BPNN Model for Wind Farm Investment Evaluation

2014 ◽  
Vol 541-542 ◽  
pp. 966-971
Author(s):  
Xiang Feng Zhang ◽  
Tian Yu Liu ◽  
Bin Jiao
Keyword(s):  
Wind Farm ◽  
Evaluation Method ◽  
Back Propagation ◽  
Wind Farms ◽  
Back Propagation Neural Network ◽  
Analytic Hierarchy ◽  
Farm Investment ◽  
Hierarchy Process ◽  
Power Project ◽  
Bpnn Model

The construction of wind farms grows quickly in China. It is necessary for stakeholders to estimate investment costs and to make good decisions about a wind power project by making a budget for the investment. This paper proposed an evaluation method by integrating the analytic hierarchy process (AHP) with back-propagation neural network (BPNN) to evaluate wind farm investment. In the AHP-BPNN model, the AHP method is used to determine the factors of wind farm investment. The factors with high importance are reserved while those with low importance are eliminated, which can decrease the number of inputs of the BPNN. The experiment results show that the integrated model is feasible and effective.

scholarly journals Use of Analytic Hierarchy Process for Wind Farm Installation Region Prioritization–Case Study

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2284 ◽  
Author(s):  
Rômulo Lemos Bulhões ◽  
Eudemário Souza de Santana ◽  
Alex Álisson Bandeira Santos
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Wind Farm ◽  
Greenhouse Gas Emission ◽  
Wind Farms ◽  
Clean Energy ◽  
Poor Quality ◽  
Analytic Hierarchy ◽  
Hierarchy Process

Electricity generation via renewable sources is emerging as a possible solution to meet the growing demand for electricity worldwide. Additionally, the need to produce clean energy, with little or no pollutants or greenhouse gas emission is paramount. Due to these factors, wind farms are noticeably increasing in number, especially in Brazil. However, the vast size of the country and the poor quality of its infrastructure are among several factors that make it difficult for effective decision-making to accelerate the growth of this segment in Brazil. With the purpose of assisting government agencies, regulatory agencies and other institutions in this area, the use of a multi-criteria selection method called the analytic hierarchy process is proposed here to assist in decision-making and to select priority regions for implementing wind farms. This work focuses on a case study of the state of Bahia, in which 27 territories were selected for an installation priority evaluation. Computational tools were used to hierarchize these chosen territories, including Matlab, for the construction of the computational algorithm. The results indicate the priority pf the regions according to the established criteria, which allows installation locations to be mapped—these could serve as a basis for regional investment.

scholarly journals Offshore wind energy potential for Bahrain via multi-criteria evaluation

2020 ◽  
pp. 0309524X2092539
Author(s):  
Mohamed Elgabiri ◽  
Diane Palmer ◽  
Hanan Al Buflasa ◽  
Murray Thomson
Keyword(s):  
Wind Energy ◽  
Geographical Information Systems ◽  
Wind Farm ◽  
Electricity Consumption ◽  
Pairwise Comparison ◽  
Wind Farms ◽  
Offshore Wind ◽  
Geographical Information ◽  
Energy Yield ◽  
Energy Potential

Current global commitments to reduce the emissions of greenhouse gases encourage national targets for renewable generation. Due to its small land mass, offshore wind could help Bahrain to fulfil its obligations. However, no scoping study has been carried out yet. The methodology presented here addresses this research need. It employs analytical hierarchy process and pairwise comparison methods in a geographical information systems environment. Publicly available land use, infrastructure and transport data are used to exclude areas unsuitable for development due to physical and safety constraints. Meteorological and oceanic opportunities are ranked and then competing uses are analyzed to deliver optimal sites for wind farms. The potential annual wind energy yield is calculated by dividing the sum of optimal areas by a suitable turbine footprint to deliver maximum turbine number. In total, 10 favourable wind farm areas were identified in Bahrain’s territorial waters, representing about 4% of the total maritime area, and capable of supplying 2.68 TWh/year of wind energy or almost 10% of the Kingdom’s annual electricity consumption. Detailed maps of potential sites for offshore wind construction are provided in the article, giving an initial plan for installation in these locations.

scholarly journals Inter-Criteria Dependencies-Based Decision Support in the Sustainable wind Energy Management

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 749 ◽  
Author(s):  
Paweł Ziemba
Keyword(s):  
Wind Energy ◽  
Decision Problem ◽  
Wind Farm ◽  
Analytic Network Process ◽  
Decision Problems ◽  
Analytic Hierarchy ◽  
Decision Systems ◽  
Reversal Phenomenon ◽  
Network Process ◽  
Hierarchy Process

Decision problems related to the wind energy require considering many, often interrelated and dependent on each other, criteria. To solve such problems, decision systems based on Multi-Criteria Decision Analysis (MCDA) methods are usually used. Unfortunately, most methods assume independence between the criteria, therefore, their application in decision problems related to the wind energy is debatable. This paper presents the use of the Analytic Network Process (ANP) method to solve a decision problem consisting in selecting the location and design of a wind farm. The use of the ANP method allows capturing the complexity of the decision problem by taking into consideration dependencies between criteria. As part of the verification of the solution, the results of the ANP method were compared with those of the Analytic Hierarchy Process (AHP) method, which uses only hierarchical dependencies between criteria. The conducted verification showed that the inter-criteria dependencies may have a significant influence on the obtained solution. On the basis of the conducted sensitivity analysis and the research into robustness of the rankings to the rank reversal phenomenon, it has been found out that the ranking obtained with the use of the ANP is characterized by a higher quality than by means of the AHP.

scholarly journals Offshore Wind Energy Potential for Bahrain via Multi-criteria Evaluation

2020 ◽  
Author(s):  
Diane Palmer ◽  
Mohamed Elgabiri ◽  
Hanan Al Buflasa ◽  
Murray Thomson
Keyword(s):  
Wind Energy ◽  
Geographical Information Systems ◽  
Wind Farm ◽  
Electricity Consumption ◽  
Pairwise Comparison ◽  
Wind Farms ◽  
Offshore Wind ◽  
Geographical Information ◽  
Energy Yield ◽  
Energy Potential

Current global commitments to reduce emissions of greenhouse gases encourage national targets for renewable generation. Due to its small land mass, offshore wind could help Bahrain to fulfill its obligations. However, no scoping study has yet been carried out. The methodology presented here addresses this research need. It employs Analytical Hierarchy Process and pairwise comparison methods in a Geographical Information Systems environment. Publicly available land use, infrastructure and transport data are used to exclude areas unsuitable for development due to physical and safety constraints. Meteorological and oceanic opportunities are ranked, then competing uses are analyzed to deliver optimal sites for wind farms. The potential annual wind energy yield is calculated by dividing the sum of optimal areas by a suitable turbine footprint, to deliver maximum turbine number. Ten favourable wind farm areas were identified in Bahrain’s territorial waters, representing about 4% of the total maritime area, and capable of supplying 2.68 TWh/yr of wind energy or almost 10% of the Kingdom’s annual electricity consumption. Detailed maps of potential sites for offshore wind construction are provided in the paper, giving an initial plan for installation in these locations.

scholarly journals Elaboration of a Wind Energy Potential Map in Morocco using GIS and Analytic Hierarchy Process

2020 ◽  
Vol 10 (4) ◽  
pp. 6068-6075
Author(s):  
F. Elmahmoudi ◽  
O. E. K. Abra ◽  
A. Raihani ◽  
O. Serrar ◽  
L. Bahatti
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Energy Potential ◽  
Analytic Hierarchy ◽  
Potential Map ◽  
Wind Energy Potential ◽  
Wind Farm Location ◽  
Location Map ◽  
Hierarchy Process ◽  
Selection Of

The construction of a wind power generation center starts by the selection of a suitable wind farm location. The selection includes six factors, namely wind speed, slope, land use, distance from the power lines, distance from the roads, and distance from populated areas which have been integrated into QGIS by weights calculated using the Analytical Hierarchy Process (AHP) approach. As a result of this study, the areas having very high wind potentiality have been identified and a best wind farm location map has been prepared. The map, using the overlay function in GIS, exhibits the most and least suitable areas for the location of wind farms in Morocco. The approach could help identify suitable wind farm locations in other areas using their geographic information.

Wind energy potential assessment in western Mediterranean

2020 ◽  
Author(s):  
Platon Patlakas ◽  
Christos Stathopoulos ◽  
Ariadni Gavriil ◽  
George Galanis ◽  
George Kallos
Keyword(s):  
Wind Energy ◽  
Power Plants ◽  
Wind Farm ◽  
Structural Characteristics ◽  
Wind Farms ◽  
Western Mediterranean ◽  
Offshore Wind ◽  
Energy Potential ◽  
Safety Level ◽  
Marine Area

<p>Wind energy investments have met a quick growth during the last decades due to the stricter climate policies, the need for energy independence and the higher profits coming from the smaller costs of such applications. Moreover the evolution of technology leads to the characterization of more areas as suitable for energy applications. Offshore wind farms are a nice example of how to build bigger, more efficient and resistant in extreme conditions wind power plants.</p><p>The present work is focused on the determination of the suitability of an offshore marine area for the development of wind farm structures. More specifically the region of interest is the marine area on the south of France including the Gulf of Leon. For the needs of the study a 10-year database, produced employing state of the art atmospheric and wave models, is utilized. The wind and wave parameters used, have a spatial resolution of 6 km and a frequency of one hour.</p><p>Wind speed and power probability distribution characteristics are discussed in different heights throughout the domain. Particular locations are selected for a more comprehensive analysis. At the same time extreme wind and wave conditions and their 50-years return period are analyzed and used to define the safety level of the wind farms structural characteristics. The outcome could lead to a review of the area suitability for wind farm development, providing a new tool for technical/research teams and decision makers.</p>

Economic Impact of Wind Energy Development in Illinois

2016 ◽  
Vol 11 (1) ◽  
Author(s):  
David G. Loomis ◽  
Jared Hayden ◽  
Sarah Noll ◽  
James E. Payne
Keyword(s):  
Wind Energy ◽  
Wind Farm ◽  
Wind Farms ◽  
Environmental Benefits ◽  
Renewable Portfolio Standard ◽  
Full Time ◽  
Renewable Energy Resources ◽  
Full Time Equivalent ◽  
Generating Capacity ◽  
Wind Energy Development

AbstractA number of factors have contributed to the rapid growth of wind power capacity in Illinois from 50 MW in 2003 to 3,334.91 MW in 2012, including: federal and state policies, energy security, energy costs, environmental benefits, economic development opportunities, and state-specific factors. One key policy driver in Illinois was the passage of the Illinois Power Agency Act in 2007, which included a renewable portfolio standard of 25 % by 2025, 75 % of the renewable energy resources employed to meet the renewable portfolio standard were designated to wind energy. This study analyzes the economic impacts from the 23 wind projects in Illinois that exceed 50 MW of capacity. These wind projects account for 3,334.91 MW or 99 % of the state’s wind energy generating capacity. Using the JEDI input-output model, the 23 largest wind farms in Illinois created approximately 19,047 full-time equivalent jobs during construction periods with a total payroll of over $1.1 billion. In addition, approximately 814 permanent jobs in rural Illinois areas with a total annual payroll of nearly $48 million are supported. Furthermore, wind farms generated roughly $28.5 million in annual property taxes for local economies as well as $13 million annually in extra income for Illinois landowners who lease their land to wind farm developers. The lifetime total economic benefit of the 23 wind farm projects is estimated at $5.98 billion.

scholarly journals Application of a GIS-Based Fuzzy Multi-Criteria Evaluation Approach for Wind Farm Site Selection in China

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2426
Author(s):  
Mengran Li ◽  
Ye Xu ◽  
Junhong Guo ◽  
Ye Li ◽  
Wei Li
Keyword(s):  
Climate Change ◽  
Wind Energy ◽  
Site Selection ◽  
Wind Farm ◽  
Wind Farms ◽  
Climate Change Impacts ◽  
Energy Structure ◽  
Analytic Hierarchy ◽  
Evaluation Approach ◽  
Suitability Assessment

The development and utilization of wind energy has alleviated the problems of energy shortage and environmental pollution; however, it caused many negative impacts due to suboptimal site selections. This study proposes an innovative method integrating Geographic Information System (GIS), fuzzy Analytic Hierarchy Process (FAHP), and fuzzy VIšekriterijumsko KOmpromisno Rangiranje (VIKOR) for site selection of wind farms in the Wafangdian region, China. The uncertainties caused by subjective judgments of the stakeholders were tackled by the FAHP method firstly, where weight values of six criteria were identified. Next, the fuzzy VIKOR method and GIS tool were used to generate the Qi value of each location for ranking their appropriate degrees for wind energy development. The results demonstrated that the middle and upper parts of the studied area are suitable for the exploitation of wind energy, while the central and eastern areas are unfavorable. The influences exerted by various weight combinations and climate change on a site suitability assessment were examined. The resulting comparison with existing wind farms reflected the practicability and reliability of the proposed method; the estimation of climate change impacts on site selection provided the suggestion and support of a long-term plan for wind power development, and even the energy structure adjustment scheme adapted to climate change.

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