Renewable power generation is the key to decarbonizing the electricity system. Wind power is the fastest-growing renewable source of electricity in the United States. However, expanding wind capacity often faces local opposition, partly due to a perceived visual disamenity from large wind turbines. Here, we provide a US-wide assessment of the externality costs of wind power generation through the visibility impact on property values. To this end, we create a database on wind turbine visibility, combining information on the site and height of each utility-scale turbine having fed power into the U.S. grid, with a high-resolution elevation map to account for the underlying topography of the landscape. Building on hedonic valuation theory, we statistically estimate the impact of wind turbine visibility on home values, informed by data from the majority of home sales in the United States since 1997. We find that on average, wind turbine visibility negatively affects home values in an economically and statistically significant way in close proximity ([Formula: see text]5 miles/8 km). However, the effect diminishes over time and in distance and is indistinguishable from zero for larger distances and toward the end of our sample.
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http://dx.doi.org/10.1073/pnas.2309372121 | DOI Listing |
Heliyon
December 2024
Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan, 430074, China.
This study explores the optimization and performance of a hybrid energy system combining a geothermal heat pump (GHP) with a wind turbine in Izmir, Turkey. Utilizing a 4E (Energy, Exergy, Economic, and Exergoenvironmental) analysis approach, the system aims to enhance winter heating efficiency. Geothermal heat pumps leverage the Earth's consistent temperatures for heating and cooling, offering a sustainable alternative to traditional energy sources.
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January 2025
School of Control and Computer Engineering, North China Electric Power University, Beijing, 102206, China.
China's wind power generation is rich in resources and mature technology, but has the problems of harsh power generation environment, high operation and maintenance costs due to complex operating conditions, and serious consequences of failures. For this reason, this paper proposes a more efficient defect identification method for wind turbine blades that have the longest downtime due to faults. Firstly, starting from the characteristics that the blade defects are darker than the surrounding and distributed in block or point shape, the blade images taken by UAV cruise are processed by grey scaling, filtering, histogram equalization and Grab-cut foreground segmentation.
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January 2025
School of Electrical Engineering, Nanjing Vocational University of Industry Technology, Nanjing, 210023, China.
Transitioning to a power system heavily reliant on renewable wind energy involves more than just replacing conventional fossil-fuel-based power plant with wind farms, the wind energy must be able to meet the requirement of voltage establishment and power balance. It is believed that the self synchronized voltage source control of DFIG wind turbine generator is one of the possible solutions to realize virtual inertia and is helpful to increase the frequency stability of power system, thus is meaningful in the transformation of the power system dominated by renewable energy. Plenty of research has been conducted on the self synchronized voltage source control strategy in steady state, but few research is focused on the soft grid integration, which is a complicated process involving wind turbine control and power converter control.
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January 2025
Department of Mechanical Engineering, Kerman Branch, Islamic Azad University, Kerman, Iran.
This article introduces an innovative multipurpose system that integrates a solar power plant with a coastal wind farm to generate refrigeration for refinery processes and industrial air conditioning. The system comprises multiple wind turbines, solar power plants, the Kalina cycle to provide partial energy for the absorption refrigeration cycle used in industrial air conditioning, and a compression refrigeration cycle for propane gas liquefaction. An extensive energy and exergy analysis was conducted on the proposed system, considering various thermodynamic parameters such as the solar power plant's energy output, the absorption chiller's cooling load, the electricity generated by the turbines, the wind turbines' power output, and the energy efficiency and exergy of each cycle within the system.
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January 2025
Electrical Computer and Control Engineering Department, Faculty of Engineering, Suez Canal University, Ismailia, 41522, Egypt.
This study presents a novel optimization algorithm known as the Energy Valley Optimizer Approach (EVOA) designed to effectively develop six optimal adaptive fuzzy logic controllers (AFLCs) comprising 30 parameters for a grid-tied doubly fed induction generator (DFIG) utilized in wind power plants (WPP). The primary objective of implementing EVOA-based AFLCs is to maximize power extraction from the DFIG in wind energy applications while simultaneously improving dynamic response and minimizing errors during operation. The performance of the EVOA-based AFLCs is thoroughly investigated and benchmarked against alternative optimization techniques, specifically chaotic billiards optimization (C-BO), genetic algorithms (GA), and marine predator algorithm (MPA)-based optimal proportional-integral (PI) controllers.
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