A comparative analysis of wind resource parameters using WAsP and windPRO

This paper investigates the accuracy of the wind resource estimation for a site in a central India region using a latest licensed version of WAsP 11 and windPRO 3.1. Whole one year measured met mast wind data has been taken using anemometer and wind vane at 10 m and 25 m height, respectively above ground level. The digitized elevation and roughness model of the corresponding site shows the roughness class 4 (roughness length 1.2525 m). The wind data has been extrapolated up to 80 m height by using power and log law models which provide the power density near about 120 W/m². As per the micro sitting guidelines for the virtual wind farm installation 5D X 7D mapping has been selected which Indicates the total power output by installing 8 Vestas V-90 1.8 MW wind turbine from WAsP is 31.561 GWh and from windPRO is 28.083 GWh.     

Performance evaluation of a horizontal axis wind turbine in operation

The operation of modern horizontal axis wind turbine (HAWT) includes a number of important factors, such as wind power (P), power coefficient (C_P), axial flow induction factor (a), rotational speed (Ω), tip speed ratio (λ), and thrust force (T). The aerodynamic qualities of these aspects are evaluated and discussed in this study. For this aim, the measured data are obtained from the Sebenoba Wind Energy Power Plant (WEPP) that is located in the Sebenoba region in Hatay, Turkey, and a wind turbine with a capacity of 2 MW is selected for evaluation. According to the results obtained, the maximum turbine power output, maximum power coefficient, maximum axial flow induction factor, maximum thrust force, optimum rotational speed, probability density of optimum rotational speed, and optimum tip speed ratio are found to be 2 MW, 30%, 0.091, 140 kN, 16.11 rpm, 46.76%, and 7, respectively. This study has revealed that wind turbines must work under optimum conditions in order to extract as much energy as possible for approaching the ideal limit.     

Environmental management framework for wind farm siting: Methodology and case study

This paper develops an integrated framework to evaluate land suitability for wind farm siting that combines multi-criteria analysis (MCA) with geographical information systems (GIS); an application of the proposed framework for the island of Lesvos, Greece, is further illustrated. A set of environmental, economic, social, and technical constraints, based on recent Greek legislation, identifies the potential sites for wind power installation. Furthermore, the area under consideration is evaluated by a variety of criteria, such as wind power potential, land cover type, electricity demand, visual impact, land value, and distance from the electricity grid. The pair-wise comparison method in the context of the analytic hierarchy process (AHP) is applied to estimate the criteria weights in order to establish their relative importance in site evaluation. The overall suitability of the study region for wind farm siting is appraised through the weighted summation rule. Results showed that only a very small percentage of the total area of Lesvos could be suitable for wind farm installation, although favourable wind potential exists in many more areas of the island.     

Availability estimation of a multi-state wind farm in fuzzy environment

Wind is one of the fastest growing renewable energy resources in the electric power system. Availability of wind energy is volatile in nature due to the stochastic behavior of wind speed and non-linear variation of the wind power curve of wind turbine generator. Because of this impression and uncertainty, the availability estimation of wind power has become a challenging issue. In this paper, Markov Fuzzy Reward technique has been proposed for finding out the reliability of wind farm by assessing the availability of wind power. According to this technique, availability of the wind power has been estimated considering wind farm and demand both as a multi-state system. In addition to the availability, different reliability indices such as the number of absolute failures, mean time to deficiency, and probability of failures of a wind farm have been assessed in a time horizon, which can provide useful information for the power system planner at wind farm installing stage. A comparison of this study reveals the efficacy of the proposed Markov Fuzzy Reward approach over the conventional Markov Reward approach.     

Large-scale baseload wind power in China

This paper presents a novel strategy for developing wind power in large-scale (multi-GW) wind farms in China. It involves combining oversized wind farms, large-scale electrical storage and long-distance transmission lines to deliver 'baseload wind power' to distant electricity demand centers. Baseload wind power is typically more valuable to the electric utility than intermittent wind power, so that storage can be economically attractive even in instances where the cost per kWh is somewhat higher than without storage.
The prospective costs for this approach to developing wind power are illustrated by modifying an oversized wind farm at Huitengxile, Inner Mongolia. The site has an average power density of 580 W/m² at 50 m hub heights and is located 500 km north of Beijing. Using locally mass-produced wind turbines there are good prospects that wind power would be cost-competitive with coal power, on a lifecycle cost basis, while providing substantial net environmental benefits.
Finally, the institutional challenges related to the prospect of large-scale wind energy development are addressed. Especially important are policies aimed at developing the capacity for mass production of as much of this technology in China as is feasible. Promising instruments for speeding up the introduction of this technology include: (i) international joint ventures between foreign vendors and developers and Chinese manufacturers; and (ii) wind resource development concessions.     

On the wind resource mapping of Burkina Faso

In this work, mesoscale wind resource maps, at 5-km resolution, of the country of Burkina Faso (274,200 km²) were developed using the Anemoscope and mesoscale compressible community models. Results show that the northeast region of Burkina Faso has a good wind regime at 80 m above ground level (agl), while the wind regime in other parts of the country is generally low, even at 80 m agl. In addition, the technical power potential and the potential annual energy production that can be generated from the wind in Burkina Faso are identified using analysis tools based on geographical information systems and economic constraints. Results from the technical power potential at 80 m agl show that a total of 312 MW of wind farms, generating annually a total of 741 GWh of energy, could be installed in Burkina Faso. On the other hand, a total of 4411 MW of small wind turbines (50 kW) could be installed over the territory, corresponding to an annual energy production of 7843 GWh. The Wind Atlas of Burkina Faso provides an opportunity for local stakeholders to consider wind energy for the electricity portfolio of the country.     

A convective wind resource model for Solar Vortex power generation

ABSTRACT

Climate change has increased the need for clean, nonpolluting energy sources to decrease dependence on fossil fuels. Alternative energy sources, mainly solar and horizontal wind, have been the primary focus for producing clean energy. New technologies are being developed, such as the Solar Vortex (SoV), which was developed at the Georgia Institute of Technology, and relies on a vertical wind resource to generate power. The National Renewable Energy Lab (NREL) has resource models representing solar and horizontal wind resources across the 48 United States. This research developed a vertical wind resource model that is comparable in resolution to NREL’s solar and horizontal wind resource models and uses the model for estimating power output for the SoV. This model complements NREL’s existing resource models and supports the deployment of an additional clean energy generation technology. The model was applied to Mesa, Arizona to find feasible sites for a small-scale vertical wind farm.     

Electricity systems with near-zero emissions of CO2 based on wind energy and coal gasification with CCS and hydrogen storage

Emissions from electricity generation will have to be reduced to near-zero to meet targets for reducing overall greenhouse gas emissions. Variable renewable energy sources such as wind will help to achieve this goal but they will have to be used in conjunction with other flexible power plants with low-CO₂ emissions. A process which would be well suited to this role would be coal gasification hydrogen production with CCS, underground buffer storage of hydrogen and independent gas turbine power generation. The gasification hydrogen production and CO₂ capture and storage equipment could operate at full load and only the power plants would need to operate flexibly and at low load, which would result in substantial practical and economic advantages. This paper analyses the performances and costs of such plants in scenarios with various amounts of wind generation, based on data for power demand and wind energy variability in the UK. In a scenario with 35% wind generation, overall emissions of CO₂ could be reduced by 98–99%. The cost of abating CO₂ emissions from the non-wind residual generation using the technique proposed in this paper would be less than 40% of the cost of using coal-fired power plants with integrated CCS.     

A novel wind speed forecasting model for wind farms of Northwest China

Wind resources are becoming increasingly significant due to their clean and renewable characteristics, and the integration of wind power into existing electricity systems is imminent. To maintain a stable power supply system that takes into account the stochastic nature of wind speed, accurate wind speed forecasting is pivotal. However, no single model can be applied to all cases. Recent studies show that wind speed forecasting errors are approximately 25% to 40% in Chinese wind farms. Presently, hybrid wind speed forecasting models are widely used and have been verified to perform better than conventional single forecasting models, not only in short-term wind speed forecasting but also in long-term forecasting. In this paper, a hybrid forecasting model is developed, the Similar Coefficient Sum (SCS) and Hermite Interpolation are exploited to process the original wind speed data, and the SVM model whose parameters are tuned by an artificial intelligence model is built to make forecast. The results of case studies show that the MAPE value of the hybrid model varies from 22.96% to 28.87 %, and the MAE value varies from 0.47 m/s to 1.30 m/s. Generally, Sign test, Wilcoxon’s Signed-Rank test, and Morgan--Granger--Newbold test tell us that the proposed model is different from the compared models.     

A Weibull and finite mixture of the von Mises distribution for wind analysis in Mersing,Malaysia

Studies of wind direction receive less attention than that of wind speed; however, wind direction affects daily activities such as shipping, the use of bridges, and construction. This research aims to study the effect of wind direction on generating wind power. A finite mixture model of the von Mises distribution and Weibull distribution are used in this paper to represent wind direction and wind speed data, respectively, for Mersing (Malaysia). The suitability of the distribution is examined by the R² determination coefficient. The energy analysis, that is, wind power density, only involves the wind speed, but the wind direction is vital in measuring the dominant direction of wind so that the sensor could optimize wind capture. The result reveals that the estimated wind power density is between 18.2 and 25 W/m², and SSW is the most common wind direction for this data.     

An Analysis of the Wind Energy Potential of Elazig,Turkey

Abstract

In this study, the wind energy potential of Elazig is statistically analyzed based on hourly measured wind speed data over the five-year period from 1998 to 2002. The probability density distributions are derived from cumulative distribution functions. Two probability density functions are fitted to the measured probability distribution on a yearly basis. The wind energy potential of the location is studied based on the Weibull and Rayleigh distributions. It was found that the numerical values of both Weibull parameters (k and c) for Elazig vary over a wide range. The yearly values of k range from 1.653 to 1.878 with an average value of 1.819, while those of c are in the range of 2.757–2.994 m/s with an average value of 2.824 m/s. In addition, yearly mean wind speed and mean power density of Elazig is found as 2.79 m/s and 38.76 W/m², respectively. The wind speed distributions are represented by Weibull distribution and also by Rayleigh distribution, with a special case of the Weibull distribution for k = 2. As a result, the Rayleigh distribution is found to be suitable to represent the actual probability of wind speed data for Elazig.     

核电环境风险研究进展及管理启示

为满足快速增长的电力需求,缓解传统化石能源紧缺及其所伴随的大气污染问题,发电过程中几乎不产生常规大气污染物的核电逐渐成为我国重要的能源战略选择。但是,由于核电站在运行过程中,特别是发生重大核事故时,产生的放射性物质可能对健康造成负面影响,发展核电仍然存在较大的争议和阻力。在此背景下,需要构建科学、完善的核电风险评估与管理体系,以保障我国的核电行业健康、有序发展。在对国内外核电风险评估研究现状进行系统梳理的基础上,分析其对核电风险管理的意义,提出了我国未来构建核电风险评估与管理体系的建议。     

A wind resource assessment around large mountain masses: The speed-up effect

The wind potential around an intensely mountainous area has been studied and an experimental analysis is presented the output of which could be used in the wind farm planning procedure aiming at maximization of the wind power production output of an area. The wind speed of a chosen site of Central Greece was studied based on field measurements around a large mountainous area of Central Greece. Understanding flow in the foothills and the wider area of the mountains is of great importance for estimating wind resource in rough terrain. In this article, special focus was given to the speed-up effect and forced air flow around mountainous masses.     

The impact of electric passenger transport technology under an economy-wide climate policy in the United States: Carbon dioxide emissions,coal use,and carbon dioxide capture and storage

Plug-in hybrid electric vehicles (PHEVs) have the potential to be an economic means of reducing direct (or tailpipe) carbon dioxide (CO₂) emissions from the transportation sector. However, without a climate policy that places a limit on CO₂ emissions from the electric generation sector, the net impact of widespread deployment of PHEVs on overall U.S. CO₂ emissions is not as clear. A comprehensive analysis must consider jointly the transportation and electricity sectors, along with feedbacks to the rest of the energy system. In this paper, we use the Pacific Northwest National Laboratory's MiniCAM model to perform an integrated economic analysis of the penetration of PHEVs and the resulting impact on total U.S. CO₂ emissions. In MiniCAM, the deployment of PHEVs (or any technology) is determined based on its relative economics compared to all other methods of providing fuels and energy carriers to serve passenger transportation demands. Under the assumptions used in this analysis where PHEVs obtain 50–60% of the market for passenger automobiles and light-duty trucks, the ability to deploy PHEVs under the two climate policies modelled here results in over 400 million tons (MT) CO₂ per year of additional cost-effective emissions reductions from the U.S. economy by 2050. In addition to investments in nuclear and renewables, one of the key technology options for mitigating emissions in the electric sector is CO₂ capture and storage (CCS). The additional demand for geologic CO₂ storage created by the introduction of the PHEVs is relatively modest: approximately equal to the cumulative geologic CO₂ storage demanded by two to three large 1000 megawatt (MW) coal-fired power plants using CCS over a 50-year period. The introduction of PHEVs into the U.S. transportation sector, coupled with climate policies such as those examined here, could also reduce U.S. demand for oil by 20–30% by 2050 compared to today's levels.     

Modeling Hydraulic and Thermal Electricity Production Based on Genetic Algorithm-Time Series (GATS)

Abstract

This study deals with the estimation of electricity production from hydraulic and thermal sources using the Genetic Algorithm (GA) with time series (TS) approach. Two forms of the mathematical models are developed, of which one is exponential and the second is polynomial. The power form of the Genetic Algorithm-Time Series (GATS) model is used for the thermal electricity production. The polynomial form of the GATS is used for the electricity production from the hydraulic sources. The GATS weighting parameters are obtained by minimizing the Sum of Squared Error (SSE) between observed and estimated electricity production from both sources. Therefore, the fitness function adapted is the minimization of the SSE for use in the GA process. The application of the GATS model is correspondingly presented. Some future scenarios are made to increase the electricity production from hydraulic sources. Variations of the electricity production from thermal and hydraulic energy sources are analyzed. Future prospects of electricity production are dealt with in terms of policy changes. The GATS models are used for making scenarios for future electricity planning policy. Results also show if current trend continues, the thermal electricity production amounts to 75% of the total electricity production, which is undesirable for environmental concerns. Results also shows that if new policy is to move from the thermal to hydraulic electricity production, the hydraulic sources will meet the demand until 2020.     

Optimization of a Wind/PV Hybrid Power Generation System

This study investigates the wind and solar electricity generation availability at the Solar Energy Institute of Ege University, Izmir, Turkey. The main purpose of this study is to design an appropriate wind-PV hybrid system to cover the electricity consumption of the Institute. In order to do this, monthly average solar irradiation and wind speed data are used, which were measured, consisting of hourly records over an eight-year period from 1995–2002. Simple models were developed to determine wind, solar, and hybrid power resources per unit area. Correlations between the solar and wind power data were carried out on an hourly, daily, and monthly basis. It is shown that the hybrid system can be applied for the efficient and economic utilization of these resources.     

Automated energy management in distributed electricity systems: An EEPOS approach

The increasing capacity of distributed electricity generation brings new challenges in maintaining a high security and quality of electricity supply. New techniques are required for grid support and power balance. The highest potential for these techniques is to be found on the part of the electricity distribution grid.

This article addresses this potential and presents the EEPOS project’s approach to the automated management of flexible electrical loads in neighborhoods. The management goals are (i) maximum utilization of distributed generation in the local grid, (ii) peak load shaving/congestion management, and (iii) reduction of electricity distribution losses. Contribution to the power balance is considered by applying two-tariff pricing for electricity.

The presented approach to energy management is tested in a hypothetical sensitivity analysis of a distribution feeder with 10 households and 10 photovoltaic (PV) plants with an average daily consumption of electricity of 4.54 kWh per household and a peak PV panel output of 0.38 kW per plant. Energy management shows efficient performance at relatively low capacities of flexible load. At a flexible load capacity of 2.5% (of the average daily electricity consumption), PV generation surplus is compensated by 34–100% depending on solar irradiance. Peak load is reduced by 30% on average. The article also presents the load shifting effect on electricity distribution losses and electricity costs for the grid user.     

Integration and evaluation of a power plant with a CaO-based CO2 capture system

This paper explores the integration and evaluation of a power plant with a CaO-based CO₂ capture system. There is a great amount of recoverable heat in the CaO-based CO₂ capture process. Five cases for the possible integration of a 600 MW power plant with CaO-based CO₂ capture process are considered in this paper. When the system is configured so that recovered heat is used to replace part of the boiler heat load (Case 2), modelling not only shows that this is the system recovering the most heat of 1008.8 MW but also results in the system with the lowest net power output of 446 MW and the second lowest of efficiency of 34.1%. It is indicated that system performance depends both on the amount of heat recovery and the type of heat utilization. When the system is configured so that a 400 MW power plant is built using the recovered heat (Case 4), modelling shows that this is the system with the most net power output of 846 MW, the highest efficiency of 36.8%, the lowest cost of electricity of 54.3 €/MWh and the lowest cost of CO₂ avoided of 28.9 €/tCO₂. This new built steam cycle will not affect the operation of the reference plant which vents its CO₂ to the atmosphere, highly reducing the connection between the CO₂ capture process and the reference plant which vents its CO₂ to the atmosphere. The average cost of electricity and the cost of CO₂ avoided of the five cases are about 58.9 €/kWh and 35.9 €/tCO₂, respectively.     

阶梯小水电站开发对永定河水质影响及防治对策

随着近年工业的发展，工业对电需求量急剧增加。永定县小水电站无节制开发，已对永定河水体造成一定的污染。监测结果表明，小水电站所在的河段水质比永定河其它断面污染严重，已经满足不了永定水环境功能区划的要求。