Mountain Wind Research Articles

Lateral bearing capacity of cone-shaped hollow foundation by using limit equilibrium method

The cone-shaped hollow reinforced concrete foundation (CHRF) is an innovative type of mountain wind turbine foundation. Model tests were carried out to investigate the bearing behaviour of CHRFs under monotonic lateral loading. Results show that the lateral bearing capacity of the CHRF increases with the increasing diameter and height of the foundation, whereas it decreases significantly with an increase in loading eccentricity. The CHRF rotates about the rotation centre during loading, and the rotation centre is located at an embedded depth of 0.55–0.65 times the foundation height and is 0.15–0.18 times the diameter of the foundation away from its centreline in the ultimate state. Moreover, the distributions of earth pressures along the sidewall of the CHRF represent that the sidewall of the CHRF in the loading direction is the central part for bearing lateral loads. A formula for estimating the lateral bearing capacity of the CHRF is proposed in terms of the limit equilibrium method and is verified by model test results. It is found that the relative error ranges from 7.99 to 17.2%, and the average relative error is 12.7%, indicating that the theoretical model is applicable to predict the lateral bearing capacity of the CHRF.

Observational Signal of the Interaction Between Mountain–Plain Wind and Urban Breeze Under Weak Synoptic Systems

AbstractValley winds and urban breezes induced by thermal circulation have been the subject of numerous studies; however, their interactions deserve further observational study under different geographical conditions globally. We propose quantitative criteria for analysis of observations, including identification of valley and mountain–plain wind episodes, determination of the direction and duration of valley winds, and exclusion of suspect cases induced by strong synoptic systems. We selected a subset of 345 valley wind days that occurred during 2013–2015 in Hangzhou, China. Valley winds in the study area occur mainly in autumn and early winter (annual frequency: 32%). To the west (east) of the urban center of Hangzhou are small mountains (is a plain). At night, the directions of mountain–plain circulation and urban thermal circulation are consistent in the region from the mountains to western parts of the city, resulting in a strengthened mountain wind at the surface. Their interaction also delays the reversal of the mountain wind to the plain wind in the morning, and slightly advances the reversal of the plain wind to the mountain wind in the evening. Conversely, in the plain area to the east of Hangzhou, the interaction delays the time of reversal of the plain wind to the mountain wind in the evening. Our results indicate that interactions between the urban breeze and local thermal circulations could have distinct impact on the environment of the city and surrounding areas, and thus they should be taken into consideration in relation to urban planning and management.

Cable-car measurements of vertical aerosol profiles impacted by mountain-valley breezes in Lushan Mountain, East China

In-situ field observations of vertical aerosol profiles for one month in complex terrain (Lushan Mountain, China) were carried out using a cable car, which resolved detailed vertical distributions of mountain aerosols with low-cost operation. Cable-car observations were conducted during the early morning and late afternoon, when mountain and valley winds dominated, respectively. The diurnal aerosol variations at the top and foot of Lushan Mountain were analyzed based on environmental and meteorological stations. The observations indicated that the mountain-valley breezes notably impacted the mountain-area aerosol distribution under weak weather conditions. More uniform aerosol profiles for the afternoon than the morning, with their decreasing rates of PM2.5 (particles with diameters less than 2.5 μm) were 1.64 and 2.28 μg m−3/100 m, respectively. The PM2.5/PM10 ratio at the mountain top increased from 0.69 to 0.81, and that at the mountain base decreased from 0.75 to 0.70 from morning to afternoon. The PM2.5 concentration decreased in and around Lushan Mountain from daytime to nighttime, with the impacted diameter of the 300-m topography line being smaller than ~5 km, while the concentration increased in Jiujiang City. The relative decreasing rate of PM2.5 was higher at the mountain top site (~20%) than at the base site (~2%) from daytime to nighttime. Moreover, uniform aerosol profiles could have been caused by regional transport through a relatively strong low-level synoptic flow (~5 m s−1) and the mountain's dynamic lifting effect.

Power Data Preprocessing Method of Mountain Wind Farm Based on POT-DBSCAN

Power Data Preprocessing Method of Mountain Wind Farm Based on POT-DBSCAN

XE112-2000 Wind Turbine Yaw Strategy With Adaptive Yaw Speed Using DEL Look-Up Table

With the increasing capacity of wind turbines, the importance of the yaw system has gradually become more prominent. The supervisory control and data acquisition (SCADA) system of XEMC Windpower Co., Ltd. is used in this paper to analyze the yaw data of the No. 5 wind turbine of Baozhong Mountain Wind Farm in Hunan Province. In order to evaluate the power generation and the damage equivalent load (DEL) of the yaw bearing during the yaw process, an economic model predictive control (EMPC) yaw strategy based on light detection and ranging (LIDAR) was proposed. EMPC takes the yaw error and wind speed as the disturbance of the cost function (CF) at the same time by establishing the yaw bearing DEL look-up table in advance. Discrete adaptive yaw speed control set is proposed to adapt to different wind conditions sets. Finally, the effectiveness of EMPC is verified using the model of XE112-2000 wind turbine in simulation software Bladed.

A foehn-induced haze front in Beijing: observations and implications

Abstract. Despite frequent foehns in the Beijing–Tianjin–Hebei (BTH) region, there are only a few studies of their effects on air pollution in this region, or elsewhere. Here, we discuss a foehn-induced haze front (HF) event using observational data to document its structure and evolution. Using a dense network of comprehensive measurements in the BTH region, our analyses indicate that the foehn played an important role in the formation of the HF with significant impacts on air pollution. Northerly warm–dry foehn winds, with low particulate concentration in the northern area, collided with a cold–wet polluted air mass to the south and formed an HF in the urban area. The HF, which is associated with a surface wind convergence line and distinct contrasts of temperature, humidity and pollutant concentrations, resulted in an explosive growth of particulate concentration. As the plain–mountain wind circulation was overpowered by the foehn, a weak pressure gradient due to the different air densities between air masses was the main factor forcing advances of the polluted air mass into the clean air mass, resulting in severe air pollution over the main urban areas. Our results show that the foehn can affect air pollution through two effects: direct wind transport of air pollutants, and altering the air mass properties to inhibit boundary layer growth and thus indirectly aggravating air pollution. This study highlights the need to further investigate the foehn and its impacts on air pollution in the BTH region.

Data‐driven modeling for fatigue loads of large‐scale wind turbines under active power regulation

AbstractAdvanced control methods for coordinatively optimizing active power dispatch and fatigue load distribution of wind turbines (WTs) in mountain wind farms, require the fatigue load modeling that has not been fully studied. This study proposes a data‐driven modeling method for fatigue loads of large‐scale WT under active power regulation. Firstly, load simulations based on Monte Carlo approach are conducted to overcome the uncertainty of fatigue load caused by turbulent wind. Subsequently, the target components of WT are selected according to the fatigue load dataset distribution at various power setpoints and the sensitivity to active power. Specifically, the Jarque–Bera statistic is used to evaluate the distribution characteristics of datasets; the single‐value processing determines the valid value through the maximum probability of the Gaussian kernel density distribution of the dataset; the Morris screening is employed to select the valid value with high sensitivity to active power regulation. Afterwards, arbitrary polynomial chaos expansion and support vector regression are performed to establish the data model of fatigue loads, respectively. Finally, the proposed method is applied into a 1.5‐MW commercial WT model designed by the manufacturer through the Bladed software. The obtained data‐driven model establishes a basis of simultaneously optimizing active power dispatch and fatigue load distribution, making it possible to reduce energy cost in mountain wind farms.

A comparative study of mesoscale flow-field modelling in an Eastern Alpine region using WRF and GRAMM-SCI

Recently, the mesoscale model GRAMM-SCI has been further developed to make use of the freely available global ERA5 reanalysis dataset issued by the ECMWF. In this study, first results are discussed for the federal state of Styria, which is situated in the eastern Alps of Austria. Additional simulations were made with the mesoscale model WRF, which serve as a benchmark in this work. The model runs covered one week in summer and another one in winter dominated by fair weather conditions. These were characterized by the development of complex mountain wind systems in the Alps, which play an important role for the dispersion of pollutants. Regarding the bias and the root mean square error both models perform very well in comparison with existing studies for Alpine areas and are able to capture the main features of observed surface flows such as valley-wind systems or katabatic flows at slopes. In addition, observed calm wind conditions at many stations during the winter period were reproduced by the models. However, the correct simulation of wind directions in these conditions was found to be extremely challenging. Existing model quality criteria for wind direction seem to be too strict for low-wind-speed conditions. Therefore, based on theoretical and empirical considerations, a new model evaluation benchmark for wind direction is proposed, which takes into account the random nature of horizontally meandering flows in stagnant weather situations.

Atmospheric Drivers of Melt on Larsen C Ice Shelf: Surface Energy Budget Regimes and the Impact of Foehn

AbstractRecent ice shelf retreat on the east coast of the Antarctic Peninsula has been principally attributed to atmospherically driven melt. However, previous studies on the largest of these ice shelves—Larsen C—have struggled to reconcile atmospheric forcing with observed melt. This study provides the first comprehensive quantification and explanation of the atmospheric drivers of melt across Larsen C, using 31‐months' worth of observations from Cabinet Inlet, a 6‐month, high‐resolution atmospheric model simulation and a novel approach to ascertain the surface energy budget (SEB) regime. The dominant meteorological controls on melt are shown to be the occurrence, strength, and warmth of mountain winds called foehn. At Cabinet Inlet, foehn occurs 15% of the time and causes 45% of melt. The primary effect of foehn on the SEB is elevated turbulent heat fluxes. Under typical, warm foehn conditions, this means elevated surface heating and melting, the intensity of which increases as foehn wind speed increases. Less commonly—due to cooler‐than‐normal foehn winds and/or radiatively warmed ice—the relationship between wind speed and net surface heat flux reverses. This explains the seemingly contradictory results of previous studies. In the model, spatial variability in cumulative melt across Larsen C is largely explained by foehn, with melt maxima in inlets reflecting maxima in foehn wind strength. However, most accumulated melt (58%) occurs due to solar radiation in the absence of foehn. A broad north‐south gradient in melt is explained by the combined influence of foehn and non‐foehn conditions.

Evaluating the Ability of FARSITE to Simulate Wildfires Influenced by Extreme, Downslope Winds in Santa Barbara, California

Extreme, downslope mountain winds often generate dangerous wildfire conditions. We used the wildfire spread model Fire Area Simulator (FARSITE) to simulate two wildfires influenced by strong wind events in Santa Barbara, CA. High spatial-resolution imagery for fuel maps and hourly wind downscaled to 100 m were used as model inputs, and sensitivity tests were performed to evaluate the effects of ignition timing and location on fire spread. Additionally, burn area rasters from FARSITE simulations were compared to minimum travel time rasters from FlamMap simulations, a wildfire model similar to FARSITE that holds environmental variables constant. Utilization of two case studies during strong winds revealed that FARSITE was able to successfully reconstruct the spread rate and size of wildfires when spotting was minimal. However, in situations when spotting was an important factor in rapid downslope wildfire spread, both FARSITE and FlamMap were unable to simulate realistic fire perimeters. We show that this is due to inherent limitations in the models themselves, related to the slope-orientation relative to the simulated fire spread, and the dependence of ember launch and land locations. This finding has widespread implications, given the role of spotting in fire progression during extreme wind events.

Surface Turbulent Fluxes during Persistent Cold-Air Pool Events in the Salt Lake Valley, Utah. Part II: Simulations

AbstractRealistically representing the land–atmosphere interactions during persistent cold-air pools (PCAPs) is critical in simulating the strength of PCAPs, where uncertainties in simulating the PCAP strength will impact the ability to model the poor air quality. To quantify the model performance for land–atmosphere exchange, measurements of surface turbulent and radiative energy fluxes during two PCAPs, one weak and one strong, in Utah were compared with simulations from the Weather Research and Forecasting (WRF) Model. The results show that the WRF Model simulated the surface energy fluxes well in the weak PCAP case and that the performance degraded in the strong PCAP case. The significantly overestimated surface sensible heat flux H and latent heat flux (LE) in the strong PCAP were related, in part, to the overestimated net radiation and soil moisture and unsuitable turbulence parameterizations. The simulation using the Mellor–Yamada–Nakanishi–Niino planetary boundary layer scheme produced the least bias in both net radiation and surface turbulent fluxes for the strong PCAP case, which is expected because of the local higher-order (2.5) turbulence closure scheme. The surface exchange coefficient (CH), a crucial variable used to calculate H, was overall overestimated by the WRF Model. The underestimation of the nondimensional vertical temperature gradient in the Monin–Obukhov stability function was responsible for the overestimated CH, where the stability functions deviate significantly from expected values from observations for the stable atmospheric boundary layer. Our study highlights the need to improve the flux–profile parameterizations under stable conditions over complex terrain by including impacts due to mountainous terrain, such as surface radiative flux divergence and the diurnal mountain wind system.

Study on the Pollution Characteristics and Sources of Ozone in Typical Loess Plateau City

Ground-level ozone is a secondary pollutant produced by photochemical reactions and it adversely affects plant and human health. Taiyuan City, a typical city on the loess plateau, is suffering from severe ozone pollution. We utilized the data from eight national environmental monitoring sites of Taiyuan, including concentrations of O3 and nitric oxide, and meteorological factors, such as air temperature and wind, to study the pollution characteristics and sources of ozone (O3) in Taiyuan in 2018. Results show that during 2018, the maximum value and 90th percentile of the maximum 8-h running average of O3 concentration were 257 μg/m3 and 192 μg/m3, respectively. There were 72 days where the O3 concentration exceeded the standard in 2018, which were mainly during April to August. The O3 concentration increased from March, reached a high level in April through August, and decreased significantly from September. The O3 concentrations displayed a typical “single peak” diurnal variation, which was high during the day with peak at around 13:00–15:00 and low at night. From April to August, the O3 concentrations at Jinyuan was the highest, followed by Xiaodian and Taoyuan, and the O3 concentrations at Shanglan and Nanzhai were the lowest. When the O3 concentration exceeded the standard value, Jinyuan contributed the most to the O3 pollution of Taiyuan, followed by Taoyuan and Xiaodian. High temperature and pressure, south and southwest winds can lead to an increase in O3 concentration. The O3 pollution in the Taiyuan urban area is caused by local generation, and the transportation of polluted air masses containing oxides of nitrogen (NOx) and volatile organic compounds (VOCs) emitted by industries, such as the coking and steel plants in counties of Jinzhong City in southern Taiyuan, and Qingxu County, and some counties in Lyuliang City to the southwest. In addition, the mountain winds and low nitric oxide concentration are the main reasons for the increase of O3 concentration, often observed in Shanglan at night.

Experimental Study on Wake Evolution of a 1.5 MW Wind Turbine in a Complex Terrain Wind Farm Based on LiDAR Measurements

To study the wake development characteristics of wind farms in complex terrains, two different types of Light Detection and Ranging (LiDAR) were used to conduct the field measurements in a mountain wind farm in Hebei Province, China. Under two different incoming wake conditions, the influence of wind shear, terrain and incoming wind characteristics on the development trend of wake was analyzed. The results showed that the existence of wind shear effect causes asymmetric distribution of wind speed in the wake region. The relief of the terrain behind the turbine indicated a subsidence of the wake centerline, which had a linear relationship with the topography altitudes. The wake recovery rates were calculated, which comprehensively validated the conclusion that the wake recovery rate is determined by both the incoming wind turbulence intensity in the wake and the magnitude of the wind speed.

Capacity of Cone‐Shaped Hollow Flexible Reinforced Concrete Foundation (CHFRF) in Sand under Horizontal Loading

The cone‐shaped hollow flexible reinforced concrete foundation (CHFRF) is an innovative type of mountain wind turbine foundation, which outperforms the regular mountain wind turbine foundation in reducing the steel and concrete and protecting the surrounding vegetation for the cavity absorbs soil obtained from excavating the foundation pit. Moreover, the rubber layer installed between the wall of CHFRF and the surrounding ground increases foundation flexibility and releases the larger overturning moment induced by wind. The rubber layer is made of alternately laminated rubber and steel. The objectives of this research are to study the lateral bearing behaviors of the CHFRF under monotonic and cyclic lateral loading in sand by model tests and FEM simulations. The results reveal that the CHFRF rotates during loading; and, in the ultimate state, the rotation center is located at a depth of approximately 0.6–0.65 times the foundation height and is 0.15–0.18 times the diameter of the foundation away from its centerline as well. The lateral bearing capacity of the CHFRF improves with the increase of embedded depth and vertical load applied to the foundation. Moreover, compared to the CHFRF without the rubber layer, the rubber layer can reduce the earth pressure along the wall of CHFRF by 22% and decrease the deformed range of the soil surrounding the foundation, revealing that it can reduce the loads transferred to the surrounding soil for extending the service life of the foundation. However, the thickness and stiffness of the rubber layer are important factors influencing the lateral bearing capacity and the energy dissipation of the foundation. Moreover, it should be noted that the energy dissipation mainly comes from the steel of the rubber layer rather than rubber.

Multivariate statistical air mass classification for the high-alpine observatory at the Zugspitze Mountain, Germany

Abstract. To assist atmospheric monitoring at high-alpine sites, a statistical approach for distinguishing between the dominant air masses was developed. This approach was based on a principal component analysis using five gas-phase and two meteorological variables. The analysis focused on the Schneefernerhaus site at Zugspitze Mountain, Germany. The investigated year was divided into 2-month periods, for which the analysis was repeated. Using the 33.3 % and 66.6 % percentiles of the first two principal components, nine air mass regimes were defined. These regimes were interpreted with respect to vertical transport and assigned to the BL (recent contact with the boundary layer), UFT/SIN (undisturbed free troposphere or stratospheric intrusion), and HYBRID (influences of both the boundary layer and the free troposphere or ambiguous) air mass classes. The input data were available for 78 % of the investigated year. BL accounted for 31 % of the cases with similar frequencies in all seasons. UFT/SIN comprised 14 % of the cases but was not found from April to July. HYBRID (55 %) mostly exhibited intermediate characteristics, whereby 17 % of the HYBRID class suggested an influence from the marine boundary layer or the lower free troposphere. The statistical approach was compared to a mechanistic approach using the ceilometer-based mixing layer height from a nearby valley site and a detection scheme for thermally induced mountain winds. Due to data gaps, only 25 % of the cases could be classified using the mechanistic approach. Both approaches agreed well, except in the rare cases of thermally induced uplift. The statistical approach is a promising step towards a real-time classification of air masses. Future work is necessary to assess the uncertainty arising from the standardization of real-time data.

Identifying Key Controls on Storm Formation over the Lake Victoria Basin

Abstract The Lake Victoria region in East Africa is a hot spot for intense convective storms that are responsible for the deaths of thousands of fishermen each year. The processes responsible for the initiation, development, and propagation of the storms are poorly understood and forecast skill is limited. Key processes for the life cycle of two storms are investigated using Met Office Unified Model convection-permitting simulations with 1.5 km horizontal grid spacing. The two cases are analyzed alongside a simulation of a period with no storms to assess the roles of the lake–land breeze, downslope mountain winds, prevailing large-scale winds, and moisture availability. While seasonal changes in large-scale moisture availability play a key role in storm development, the lake–land-breeze circulation is a major control on the initiation location, timing, and propagation of convection. In the dry season, opposing offshore winds form a bulge of moist air above the lake surface overnight that extends from the surface to ~1.5 km and may trigger storms in high CAPE/low CIN environments. Such a feature has not been explicitly observed or modeled in previous literature. Storms over land on the preceding day are shown to alter the local atmospheric moisture and circulation to promote storm formation over the lake. The variety of initiation processes and differing characteristics of just two storms analyzed here show that the mean diurnal cycle over Lake Victoria alone is inadequate to fully understand storm formation. Knowledge of daily changes in local-scale moisture variability and circulations are keys for skillful forecasts over the lake.

Cone-shaped hollow flexible reinforced concrete foundation (CHFRF) – Innovative for mountain wind turbines

This paper presents an innovative type of mountain wind turbine foundation, namely, the cone-shaped hollow flexible reinforced concrete foundation (CHFRF). It consists of a top plate, a base plate and a side wall that are made of reinforced concrete. The cavity of the CHFRF is filled with rubble and soil directly from the excavation for the CHFRF, which means that it can absorb the spoil. A rubber layer is placed beneath the CHFRF to increase the foundation flexibility to resist cyclic and dynamic loadings and to increase the bearing capacity. The great advantages of the CHFRF are the reduction in the usage of concrete and steel and the protection of the vegetation around the wind turbine, compared with conventional mountain wind turbine foundations that are solid structures. It is verified through model tests and a numerical simulation that the CHFRF can provide higher lateral bearing capacity in comparison to the regular circular gravity-based foundation under the same foundation diameter and height, and that the bearing capacity is increased by approximately 33.5% accordingly. It is also found that the rubber layer can effectively reduce the accumulated rotation of the CHFRF under cyclic loading. The accumulated rotation of the CHFRF with a rubber layer having a thickness of 4 mm is decreased by about 50% compared to that of the CHFRF with a rubber layer having a thickness of 2 mm. In addition, the volume of concrete used for the CHFRF is only one-fifth of that used for the circular gravity-based foundation. Therefore, the CHFRF outperforms regular mountain wind turbine foundations.

Characteristics of intense winds in mountain area based on field measurement: Focusing on thunderstorm winds

With the development of mountain areas, more wind-sensitive infrastructures are constructed. In the design of these infrastructures, the wind loading cannot be accurately obtained from the code based on the flat area. Hence, it is of great importance to study the mountain wind characteristics. In this study, the wind field measurement was initiated in a mountain area of western China. After the examination of the measured data, two typical wind events including the thunderstorm wind and thermally developed wind are highlighted. To extract and separate these wind events, an automatic classification method is proposed. The thunderstorm wind is analyzed in order to capture the rapid variation of its maximum wind speed, mean temperature and mean humidity through the boxplot method while the analysis of thermally developed winds relies on the correlation between the mean wind speed and mean temperature. Since the thunderstorm wind is relatively more important for wind engineering, its wind characteristic is focused hereafter and analyzed in detail based on the ultrasonic anemometer data. The characteristics of the thermally developed wind and other wind will be the matter of further studies and investigations. Results show that the characteristics of the thunderstorm wind measured in the mountainous area have no significant difference in comparison with those in the flat area. Due to the limited data, the above results deserve further investigations when more measurements become available.

The Perdigão: Peering into Microscale Details of Mountain Winds

AbstractA grand challenge from the wind energy industry is to provide reliable forecasts on mountain winds several hours in advance at microscale (∼100 m) resolution. This requires better microscale wind-energy physics included in forecasting tools, for which field observations are imperative. While mesoscale (∼1 km) measurements abound, microscale processes are not monitored in practice nor do plentiful measurements exist at this scale. After a decade of preparation, a group of European and U.S. collaborators conducted a field campaign during 1 May–15 June 2017 in Vale Cobrão in central Portugal to delve into microscale processes in complex terrain. This valley is nestled within a parallel double ridge near the town of Perdigão with dominant wind climatology normal to the ridges, offering a nominally simple yet natural setting for fundamental studies. The dense instrument ensemble deployed covered a ∼4 km × 4 km swath horizontally and ∼10 km vertically, with measurement resolutions of tens of meters and seconds. Meteorological data were collected continuously, capturing multiscale flow interactions from synoptic to microscales, diurnal variability, thermal circulation, turbine wake and acoustics, waves, and turbulence. Particularly noteworthy are the extensiveness of the instrument array, space–time scales covered, use of leading-edge multiple-lidar technology alongside conventional tower and remote sensors, fruitful cross-Atlantic partnership, and adaptive management of the campaign. Preliminary data analysis uncovered interesting new phenomena. All data are being archived for public use.

Investigation of energy output in mountain wind farm using multiple-units SCADA data

The energy output characteristics of mountain wind farms are more complex and unpredictable than that of flat wind farms because of complex mountainous terrain. Some questions about the energy output characteristics of mountain wind farms are still unclear. For example, the effect of local wind resource characteristics on the energy output of mountain wind farms. In another scenario, single-unit data from Supervisory Control and Data Acquisition (SCADA) system are used to investigate the performance of wind turbines in some cases. But, single-unit SCADA data may not be very comprehensive. To fill this gap, multiple-units SCADA data of 2 MW wind turbines are used to comparatively investigate the energy characteristics of wind turbines in a mountain wind farm. The main contribution of this paper is to obtain a new and comprehensive understanding of the actual characteristics of the energy output of mountain wind farms, rather than staying in the design stage or general theoretical analysis. Specifically, the following issues, including (1) influence of wind speed on energy output, (2) influence of wind direction on energy output, (3) relationship between rotor speed and energy output, (4) power coefficient, have been discussed in depth. To overcome the influence of inherent deviation in wind speed measurement and the inertia of the wind rotor, a newly improved algorithm for calculating power coefficient is proposed. Creatively, a fast and operable data dividing method is presented, and the power coefficients of different operating regions are given. Through the investigation, the influence of local wind resource characteristics on the energy output is obtained. It is found that in the same mountain wind farm, the energy output curves of different wind turbines are different. For instance, energy outputs for four wind turbines in December 2015 are 434 MW, 614 MW, 205 MW, 255 MW, respectively.