Wind Energy Resources Research Articles

Evaluation of Low-Carbon Economic Efficiency under Industrial Clustering and Study of Regional Differences, Taking Xinjiang as an Example

As a major resource region, Xinjiang is both China’s energy security base and an important hub connecting Asia and Europe. Following the country’s call for carbon emission reduction, the Xinjiang government proposes to accelerate the construction of eight major industrial clusters in 2023. The concept of sustainable development is also reflected in the industrial clusters in areas such as new energy. In this study, we combined panel data from 14 regions and cities in Xinjiang from 2006 to 2020 and analyzed the synergy between the development of industrial clusters, carbon emissions, and economic growth using a coupling coordination degree model. Subsequently, we used the super-efficiency slack-based measure (SE-SBM) and Dagum’s Gini coefficient to analyze the spatial disequilibrium of efficiency measures and efficiency cases. The results show the following: (1) Overall, the industrial clusters, carbon emissions, and economic growth in the 14 regions and cities of Xinjiang are not well coordinated. The best reported level has been medium coordination, but there exists a certain degree of correlation among the three. (2) Low-carbon economic efficiency under the influence of industrial clusters in the 14 regions and cities shows significant regional differences. The regions and cities with low-carbon economic efficiency greater than 0.8, which is significantly better than the other regions in terms of efficiency, are all located in northern Xinjiang. (3) During the study period, the overall regional difference in low-carbon economic efficiency under industrial clusters in Xinjiang decreased from 0.183 to 0.17. However, the regional differences were still large. The conclusions indicate that policies for industrial clusters in Xinjiang can promote industrial development, and there may be a correlation between them and the low-carbon economy. This will effectively contribute to local sustainable development. However, overall regional differences are significant, and the degree of coordination is low. Therefore, we suggest that the government can share the advantages of development by constructing cross-regional cooperation platforms. At the same time, the Xinjiang government should make full use of the rich local wind and solar energy resources and explore a low-carbon path toward transforming the traditional energy industry. It can also be seen that industrial clusters in Xinjiang can effectively promote local sustainable development.

Gradient pyramid mechanism and Nelder-Mead simplex enhanced Colony Predation Algorithm for optimal power flow problems

The escalating human energy demand, particularly in the realm of electricity consumption, imposes a substantial burden on power system planning, resulting in the emergence of the optimal power flow (OPF) problem. To address this challenge, researchers have implemented a Flexible AC Transmission System (FACTS) in modern power systems to optimize network congestion. This paper presents a new application of the Colony Predation Algorithm (CPA) in the domain of Optimal Power Flow (OPF) through the introduction of an enhanced Colony Predation Algorithm (PNMCPA). PNMCPA incorporates the gradient pyramid mechanism and the Nelder-Mead simplex (NMs), marking the first utilization of CPA in the OPF field. The proposed approach presents a novel hierarchical gradient pyramid mechanism that combines the approximate gradient descent method with the construction of a pyramid fall rate, thereby optimizing the population as a whole within a framework that enhances population diversity. Additionally, the NMs algorithm is employed to optimize the optimal set of solutions for the population, thereby accelerating the convergence efficiency of the algorithm. The primary objective of this study is to optimize multiple factors, including the generation cost and transmission loss of the power system when multiple FACT components are present. Utilizing the Weibull probability density function, the model captures the uncertain and unstable nature of wind energy resources, encompassing direct, penalty, and standby costs. The proposed algorithm is applied to the IEEE30 bus test system, and the experimental results demonstrate that PNMCPA achieves a final optimization cost of 806.0132 $/h, surpassing other optimization algorithms. Concerning the power loss matter within the bus system, the PNMCPA algorithm significantly effectively mitigates total power loss, reducing from 1.44 MW to 1.41 MW instead of the initial CPA and substantially enhancing convergence speed. Empirical simulation outcomes clearly endorse PNMCPA as a highly efficient approach to tackling optimal power flow problems in the presence of multiple FACTS devices. The significant advancements presented in this paper mark a significant contribution to the field, offering a novel and superior solution to optimize power systems in the face of escalating energy demands.

Large-eddy simulation of upwind-hill effects on wind-turbine wakes and power performance

The present study utilizes high-fidelity large-eddy simulation (LES) to examine the upwind-hill impacts on wind-turbine wakes and power performance. Both the LES and Reynolds-Averaged Navier–Stokes (RANS) show good agreement with the experimental results of average velocity, whereas the LES exhibits great improvements in predicting turbulence characteristics. In turbine simulations, the wake half-width shows different behaviors in the hill and flat cases. The Gaussian and cosine distributions are good representations of the unskewed profiles of velocity deficit, although some discrepancies are seen around the wake edges. However, the spanwise profiles of velocity deficit become skewed in some hill cases. The non-zero pressure gradient (NZPG) model is employed to predict the velocity deficit in the wakes of a hilltop-sited turbine, and a generalized condition is proposed so that the NZPG model can work in the scenario where the pressure gradients at the turbine location or in its near wakes are not zero. Appropriately assigning initial values for the NZPG model is important for its successful use. The presence of the upwind hill has an adverse influence on the power output of the hilltop-sited turbine. The installation of wind turbines in the valley region near upwind hills is not recommended due to the limited wind-energy resources and intense turbulence levels.

Studies on the Use of Unconventional Transport Vehicles and Fuels in the Island of Crete, Greece

Several alternative vehicles and zero-carbon fuels have been developed and used to mitigate climate change, reduce the air pollution in cities and the dependence on oil resources. Their use is necessary for achieving the net-zero emissions target in the next decades. Among these vehicles are electric vehicles and vehicles with ICEs using electricity, hydrogen and bio-fuels of organic origin. The possibility of using alternative vehicles and fuels in Crete, Greece for de-carbonization of vehicles transportation has been examined. The use of electric vehicles equipped with re-chargeable electric batteries, electric vehicles equipped with fuel cells using hydrogen and vehicles with internal combustion engines using bio-fuels has been studied. The required electricity for re-charging electric batteries and for electrolytic hydrogen production can be generated from the abundant local solar and wind energy resources. Taking into account the maturity and the cost-effectiveness of the solar-PV technology as well as the wind turbine’s technology in Crete the use of electric vehicles powered by green electricity is prioritized for the green transition of the transportation sector. Bio-fuels which are used in conventional vehicles are not produced in the island. Each type of the abovementioned vehicles and fuels has several advantages and drawbacks which can accelerate or delay their use in Crete. It has been found that the green transition of vehicles transportation in the island has positive and negative economic impacts to all stakeholders. The results could be useful to policy makers, local authorities and to local stakeholders while they can assist in the development of a plan for de-carbonizing the island by 2050.

Complementarity of offshore energy resources on the Spanish coasts: Wind, wave, and photovoltaic energy

The complementarity of the solar, wind, and wave energy resource in hybrid offshore platforms has the potential to increase productivity and reduce the variability in the energy output that a single type of energy source can generate. In this study, ERA5 reanalysis is used to calculate wind, solar and wave energy resources in Spanish potential locations for offshore platforms. The results indicate that wind energy presents the largest energy resource for all Spanish offshore regions, followed by photovoltaic energy. However, taking in count the “drought periods” (periods in which no energy is obtained from any of the analysed technologies), wave energy presents an opportunity to provide a continuous flow of energy, especially in the northwestern Iberian Peninsula and the Canary Islands. The evaluation of the complementarity of the three energy sources shows that the use of hybrid platforms would not only increase energy production but also reduce variability. In terms of energy production, wind energy along with solar energy are the largest energy generators. But in terms of minimizing variability, wave energy along with solar photovoltaic energy are the most important. Thus, this study is paving the way to introduce multiple energy converters on hybrid platforms as a pathway toward more powerful and sustainable energy production.

Design of a Seawater Desalination System with Two-Stage Humidification and Dehumidification Desalination Driven by Wind and Solar Energy

The paper presents a wind–photovoltaic-thermal hybrid-driven two-stage humidification and dehumidification desalination system for remote island regions lacking access to electricity and freshwater resources. By conducting an analysis of the wind and solar energy resources at the experimental site, a suitable wind power station and photovoltaic power station are constructed. The performance of the wind–solar complementary power generation system is then evaluated based on factors such as output power, seawater desalination load power, battery compensation output, system energy consumption, and water production costs. A variable step gradient disturbance method based on the power–duty ratio is proposed for tracking the maximum power point (MPPT) of wind power generation. The output power of the photovoltaic power generation system is optimized, employing a fuzzy logic control (FLC) method to track the MPPT of photovoltaic power generation. This approach effectively addresses the issues of slow speed and low accuracy encountered by traditional MPPT algorithms in tracking the maximum power point (MPP) of both photovoltaic and wind power generations. In order to ensure that the desalination system can operate stably under different weather conditions, eight working modes are designed, and a programmable logic controller (PLC) is used to control the system, which provides a guarantee for stable water production. Experimental results demonstrate that the system exhibits stable performance, achieving a maximum water output of 80.63 Kg/h and daily water yield is 751.32 Kg, the cost of desalination equipment is 1.4892 USD/t.

Analysis of NREL-5MW wind turbine wake under varied incoming turbulence conditions

The offshore environment is an ideal site for wind farm development as it offers abundant wind energy resources. Investigating offshore wind turbine wake under different turbulence conditions is essential for enhancing energy generation efficiency and promoting sustainable development. This paper utilizes a synthetic turbulence method called Discretizing and Synthesizing Random Flow Generation (DSRFG) to generate four categories of turbulence environments based on International Electrotechnical Commission design requirements for offshore wind turbines. A standalone NREL offshore 5-MW baseline wind turbine is then simulated using the actuator line method coupled with large eddy simulation. Proper Orthogonal Decomposition is employed to analyze the wake characteristics under different incoming turbulence conditions. For the overall wake behaviors, the flow mode, in which some tip vortices flow back towards the hub, become more significant with higher incoming turbulence intensity. Those vortices disturb the turbine and result in unfavorable effects. Meanwhile, when the detailed characteristics of the wake are studied, each primary mode experiences an increase in the number of small-scale vortices with higher incoming turbulence intensity. It results from the interaction between the wake and outer flow, which accelerates wake recovery and benefits the downstream turbine.

Geospatial Analysis of Wind Energy Siting Suitability in the East African Community

Site investigation is essential for developing and constructing a dependable and effective wind engineering project. Also, the kinetic energy of moving air, used to drive a wind turbine, produces electricity. Having seen the shortage of previous studies on wind energy sites’ suitability across Africa and having read about the abundance of untapped wind energy resources in the East African region, this paper used Geographical Information System (GIS), multi-criteria, and Analytic Hierarchy techniques to provide a geospatial analysis of wind energy technology siting suitability in Eastern African Community Countries. Different data were acquired and processed from numerous open-access databases (Global Wind atlas, Regional Center for Mapping of Resources for Development (RCMRD), African Geoportal, East African community website, and Energy data Info.org). The results reveal Kenya has large parts of its land areas highly appropriate for wind energy siting (15.26%) and 1.55% of its land classified as unsuitable for wind energy generation. The rates of suitability and unsuitability were respectively 26.57% and 4.87% for Burundi, 20.6% and 10.21% for Rwanda, 20.39% and 10.44% for Tanzania, and 4.65% and 27.15% for South Sudan. The findings also show that East Africa exhibits moderate levels of wind energy siting suitability, with an estimated average of around 37.27% of its land area moderately suitable for wind energy technology installation, covering thousands of square kilometers. The study is advantageous to academia and industry-related personnel engaged in renewable energy-related activities in other African countries with similar topographies.

Assessing the Reliability and Optimizing Input Parameters of the NWP-CFD Downscaling Method for Generating Onshore Wind Energy Resource Maps of South Korea

Assessing the Reliability and Optimizing Input Parameters of the NWP-CFD Downscaling Method for Generating Onshore Wind Energy Resource Maps of South Korea

Research on Wind Turbine Location and Wind Energy Resource Evaluation Methodology in Port Scenarios

Wind energy is widely distributed in China as a renewable energy source. Aiming to alleviate the issues resulting from fossil fuel consumption faced by developing and developed countries (e.g., climate change) and to meet development needs, this study innovatively proposed methods for the location selection of wind farms and wind turbines in port areas based on the fuzzy comprehensive evaluation method. Considering that the wind turbine location is crucial to wind power generation, this paper focuses on locating wind turbines within a specific set of sea ports. The primary objectives of this paper are to evaluate the potential of wind power generation under different port scenarios and develop a method for assessing the potential of wind energy resources in wind farm areas. Firstly, a method is proposed for identifying the boundaries of wind farms in the port areas and locating wind turbines at sea ports. Furthermore, this study used the National Aeronautics and Space Administration (NASA) wind speed database to test the proposed method with the real-world wind power projects of the Ports of Tianjin, Shanghai, Xiamen, Shenzhen, and Hainan, which are top ports within five major coastal port clusters in China. It is found that the potential power generation capacity of the wind power farms at the above ports is 30.71 GWh, 19.82 GWh, 16.72 GWh, 29.45 GWh, and 24.42 GWh, respectively. Additionally, sensitive results for different types of wind turbines are conducted in the following experiment. The results of this study are fundamental for enriching the research of evaluating wind energy resources of sea ports and promoting the development and use of clean energy in practical environments. Further, the method proposed in this study is essential for optimizing the location and construction of wind turbines, which may help ports in adopting a low-carbon and green development path, thereby mitigating air pollution, and promoting sustainable development.

Hybrid Power Systems Planning with Geographical Information System Models

This paper presents planning models for hybrid distributed generation systems, as well as the results corresponding to a distribution system planning problem obtained using a new computational tool based on a Geographic Information System, GIS. This computational tool is a powerful instrument for analyzing energy resources and energy conversion technologies that can be used for the distribution networks expansion. It has been used in the economic evaluation of energy produced by hybrid systems. Thus, suitable models and techniques have initially been applied to obtain maps of solar and wind energy resources in a user defined area and maps of costs for hybrid systems, identifying the geographical locations that offer the best economic potential in distributed generation with renewable hybrid systems, supported (or not) with fuel to supply internal-combustion electric generators. Accurate evaluations of the cost of the produced energy need the use of geographic distributed costs corresponding to refuelling, installation and maintenance of the hybrid system. The developed software tool is flexible, appropriate for studying different scenarios, and enables geographical analysis of the economic competitiveness of the hybrid systems with different distributed generation resources (photovoltaic, wind, hydraulic or biomass energy systems), and it is suitable to study the optimal expansion of existing power distribution networks (isolated hybrid systems versus connected ones).

Numerical simulation and projection of wind resources in the northern South China Sea

High-resolution assessment of future wind resources is crucial for formulating appropriate energy strategies. However, the response of offshore wind energy to changing climate remains inconclusive. This study uses bias-corrected CMIP6 and time-varying sea surface temperature data to drive the Weather Research and Forecasting (WRF) model and project future changes in wind energy resources in the northern South China Sea (SCS) under SSP2–4.5 and SSP5–8.5 scenarios for 2050 and 2100. The findings indicate that wind resources in the waters north of 18°N in the northern SCS generally show an increased change, with greater wind resources in 2100 than in 2050. The SSP5–8.5 scenario exhibits a more significant increase than the SSP2–4.5 scenario. The future wind energy changes in the western and eastern nearshore waters of Guangdong, where numerous offshore wind power plants are currently established, are largely consistent with the overall change in the northern SCS. Nevertheless, there may be a decreased change in future wind resources in the central and eastern regions of the SCS.

Wind Energy Assessment in Forested Regions Based on the Combination of WRF and LSTM-Attention Models

In recent years, the energy crisis has become increasingly severe, and global attention has shifted towards the development and utilization of wind energy. The establishment of wind farms is gradually expanding to encompass forested regions. This paper aims to create a Weather Research and Forecasting (WRF) model suitable for simulating wind fields in forested terrains, combined with a long short-term time (LSTM) neural network enhanced with attention mechanisms. The simulation focuses on capturing wind characteristics at various heights, short-term wind speed prediction, and wind energy assessment in forested areas. The low-altitude observational data are obtained from the flux tower within the study area, while high-altitude data are collected using mobile radar. The research findings indicate that the WRF simulations using the YSU boundary layer scheme and MM5 surface layer scheme are applicable to forested terrains. The LSTM model with attention mechanisms exhibits low prediction errors for short-term wind speeds at different heights. Furthermore, based on the WRF simulation results, a wind energy assessment is conducted for the study area, demonstrating abundant wind energy resources at the 150 m height in forested regions. This provides valuable support for the site selection in wind farm development.

Assessing Climate Change Impacts on Wind Energy Resources over China Based on CMIP6 Multimodel Ensemble

Assessing Climate Change Impacts on Wind Energy Resources over China Based on CMIP6 Multimodel Ensemble

Short-term wind speed prediction based on improved Hilbert–Huang transform method coupled with NAR dynamic neural network model

Wind energy, as a renewable energy source, offers the advantage of clean and pollution-free power generation. Its abundant resources have positioned wind power as the fastest-growing and most widely adopted method of electricity generation. Wind speed stands as a key characteristic when studying wind energy resources. This study primarily focuses on predictive models for wind speed in wind energy generation. The intense intermittency, randomness, and uncontrollability of wind speeds in wind power generation present challenges, leading to high development costs and posing stability challenges to power systems. Consequently, scientifically forecasting wind speed variations becomes imperative to ensure the safety of wind power equipment, maintain grid integration of wind power, and ensure the secure and stable operation of power systems. This holds significant guiding value and significance for power production scheduling institutions. Due to the complexity of wind speed, scientifically predicting its fluctuations is crucial for ensuring the safety of wind power equipment, maintaining wind power integration systems, and ensuring the secure and stable operation of power systems. This research aims to enhance the accuracy and stability of wind speed prediction, thereby reducing the costs associated with wind power generation and promoting the sustainable development of renewable energy. This paper utilizes an improved Hilbert–Huang transform (HHT) using complementary ensemble empirical mode decomposition (CEEMD) to overcome issues in the traditional empirical mode decomposition (EMD) method, such as component mode mixing and white noise interference. Such an approach not only enhances the efficiency of wind speed data processing but also better accommodates strong stochastic and nonlinear characteristics. Furthermore, by employing mathematical analytical methods to compute weights for each component, a dynamic neural network model is constructed to optimize wind speed time series modeling, aiming for a more accurate prediction of wind speed fluctuations. Finally, the optimized HHT-NAR model is applied in wind speed forecasting within the Xinjiang region, demonstrating significant improvements in reducing root mean square errors and enhancing coefficient of determination. This model not only showcases theoretical innovation but also exhibits superior performance in practical applications, providing an effective predictive tool within the field of wind energy generation.

Prospects for energy supply in villages of Yakutia using wind energy resources and environmental limitations

The problems of energy supply in isolated villages of theRepublic of Sakha (Yakutia) are considered. Mapping of the resourcepotential of wind energy in the Republic of Sakha was performed. Based onthe performance modeling data of the Komai Haltec KWT300 wind turbine,the territory was zoned according to the level of wind potential. The analysisof the possibilities of energy substitution by the use of wind energy in thenorthern region of Yakutia in zones of decentralized energy supply wascarried out. Using GIS tools, a multifactorial analysis of the territory basedon the level of accessibility of power lines, transport routes and the presenceof environmental restrictions, especially nesting and bird habitats (ImportantBird Area in Republic of Sakha) was fulfilled.

Elevating Extreme Weather Forecasting Precision Through the NEMY Generation Framework

This paper presents an innovative methodology known as New Extreme Meteorological Years (NEMY) for comprehensively understanding extreme weather patterns. In contrast to conventional approaches, NEMY meticulously accounts for meteorological parameters, their respective weights, and explores critical factors such as intensity, duration, and the establishment of dynamic thresholds. This dynamic and adaptable framework facilitates precise simulations of extreme weather conditions. In an era characterized by climate change, where preparedness and mitigation of extreme weather impacts are imperative, this research holds paramount significance. The heart of this study revolves around the development and examination of the NEMY framework, which significantly enhances the accuracy in simulating extreme weather scenarios. It is worth emphasizing that, within the context of this paper, the consideration of both the intensity and duration of extreme weather events, as well as the meticulous discussion on the establishment of dynamic thresholds, are central to our approach. The importance of this framework extends beyond meteorology, with practical implications for assessing wind and solar energy resources. This paper not only outlines the methodology of NEMY but also vividly discusses the critical aspects of accounting for the intensity and duration of extreme weather events, as well as the nuanced process of dynamically setting thresholds. Furthermore, it demonstrates the application of NEMY in energy assessment, thereby contributing significantly to the global energy revolution. Additionally, it underscores the urgency of climate change adaptation and mitigation. The subsequent sections delve deeper into the NEMY framework’s design, testing, and potential applications, with a particular focus on the intricate considerations of extreme weather event intensity, duration, and dynamic threshold establishment.

Site suitability analysis of wind energy resources in different regions of Algeria’s southwestern highland

This paper presents a site suitability analysis for a 20 MW wind farm project in western Algeria’s highlands. The aim is to improve the quality of the electricity grid’s service and increase Algeria’s renewable energy utilization. The wind potential of three regions, Mecheria, El Kheiter, and Naâma, was evaluated using the Weibull function and the wind atlas analysis and application program (WAsP) with a ten-year database (2011-2021) at 10 m hub height. The assessment encompassed a comprehensive analysis of various wind resource parameters, including mean wind speed, prevailing direction, and power densities. In comparison to other sites, the Mecheria region has the best wind potential, with a mean annual wind speed of 6.31 m/s, a power density of 283 W/m2, and Weibull parameters A = 7.1 m/s and k = 2.02. These promising results prompted us to design a wind farm in this region using Power Wind 90/2000 kW turbine technology facing the predominant wind directions of the site, producing 103.91 GWh of total annual gross energy produced (gross AEP) and 103.75 GWh of total annual net energy produced (net AEP). Finally, it appears that the wind resources in the selected region are well-suited for electricity generation, offering a promising opportunity to reduce the country's dependence on fossil fuels.

Assessing the potential of green hydrogen production from wind power: case of microgrid

In the context of a microgrid, green hydrogen production from wind power was assessed in this paper. A Wind-Hydrogen Integrated Power Grid Model was employed to address the intermittent nature of wind energy resources. Wind power generation was analyzed and integrated with hydrogen production to contribute to sustainable energy solutions. Meticulous estimation and scenarios analysis were performed to quantify the potential of green hydrogen production capacity achievable through wind energy integration. Additionally, sensitivity analyses were conducted to enhance the understanding of the system's dynamics and potential challenges. This paper significantly contributed to the understanding of this critical aspect and paved the way for the future development of a comprehensive Energy Management System (EMS) designed to optimize energy flow between the grid, wind power generation, and the electrolyzer.

Distribution characteristics and assessment of wind energy resources in the coastal areas of Guangdong

In order to improve the efficiency, availability and economy during construction and operation of wind farms, characteristic analysis and evaluation of the regional wind energies are key components. In this paper, wind energy resource evaluation was conducted for coastal areas of Guangdong, including spatial and seasonal characteristics and overall evaluation. Results indicate that: ① Effective wind speed frequency is the highest in the seaward area of the study area, followed by the excessive area and the lowest in the landward area. The seaward area is relatively suitable for wind energy development. ② Total theoretical exploitable area in the study area is 5.15×105 MW, and the high production area is mainly concentrated in the outer sea areas. Developable areas are in the nearshore areas, and the potential development areas are in the sea-land interface and estuary areas. Annual effective wind energy density values along the coast of eastern Guangdong are larger than that of western Guangdong. Its development potential is larger than that of western Guangdong. ③ Wind energy variation coefficient has significant seasonal differences. Wind energy density in winter and spring is more stable than that in summer and autumn. Additionally, overall seasonal variation index is smaller, which can provide stable wind energy.