Roof Mounted Wind Turbines Research Articles

Interference effect on flow features and aerodynamic mechanism over the roof between two tall buildings

Interference effect of an upwind building on flow features and wind power potential over roof of principal building was investigated through numerical simulations. Flow features were examined at different wind directions and spacing ratios (d/B = 2, 3, 4, 5, and 6), and associated aerodynamic mechanisms were analyzed. Turbulence intensity was less affected by interfering building than mean velocity. d/B exerted a more important impact on mean velocity at θ = 0° and 180° than those at oblique wind directions. The isolated building had large power potential at leeward locations due to strong flow separation at θ = 0° compared with principal building. The largest skew angle βmax fluctuated greatly with roof locations (from −15° to 80°) of isolated building at θ = 0°. In comparison, βmax over principal building changed slightly with roof locations (from −16° to 3°) due to smooth flow separation and reattachment at θ = 0°. Effect of d/B on the largest wind energy and hub height of roof-mounted wind turbines depended on θ. Recommendations for the siting of HAWTs on roofs were finally provided.

Influence of position and wind direction on the performance of a roof mounted vertical axis wind turbine

The ideal position for a roof mounted wind turbine is investigated experimentally in a wind tunnel. The set-up consists of two cube-shaped buildings. A Savonius (drag driven) vertical axis wind turbine is placed on one of the buildings and its position is varied. Three different locations on the cube and two different turbine heights are examined. Wind from five directions is simulated to obtain a holistic characterization of the problem. The performance of the turbine is evaluated directly through measurements of the converted power. This is complemented by measurements of the surface pressure on the cubes to gain insight into the flow field. A central position on the building was found to maximize the power output for a uniform wind rose, independent of the turbine height. Placing the turbine higher above the roof increased performance for wind normal to the faces of the buildings, while a lower position showed slight advantages for the other wind directions. Overall improved performance for the roof mounted wind turbine was observed compared to the same turbine without a cube present.

Estimating Urban Wind Speeds and Wind Power Potentials Based on Machine Learning with City Fast Fluid Dynamics Training Data

Wind power is known as a major renewable and eco-friendly power generation source. As a clean and cost-effective energy source, wind power utilization has grown rapidly worldwide. A roof-mounted wind turbine is a wind power system that lowers energy transmission costs and benefits from wind power potential in urban areas. However, predicting wind power potential is a complex problem because of unpredictable wind patterns, particularly in urban areas. In this study, by using computational fluid dynamics (CFD) and the concept of nondimensionality, with the help of machine learning techniques, we demonstrate a new method for predicting the wind power potential of a cluster of roof-mounted wind turbines over an actual urban area in Montreal, Canada. CFD simulations are achieved using city fast fluid dynamics (CityFFD), developed for urban microclimate simulations. The random forest model trains data generated by CityFFD for wind prediction. The accuracy of CityFFD is investigated by modeling an actual urban area and comparing the numerical data with measured data from a local weather station. The proposed technique is demonstrated by estimating the wind power potential in the downtown area with more than 250 buildings for a long-term period (2020–2049).

CFD simulation for pedestrian comfort and wind safety in VIT campus for wind resource management

Recent researches on Computational Wind Engineering (CWE) studies widely focus on wind pressure coefficients and wind flow field for the aerodynamic design of buildings, urban planning and dispersion studies. Nowadays, CWE had been widely used for identifying the critical wind locations on the field for warning the pedestrians as well as harnessing the wind. Hence, highly functional regions like universities are currently equipping micro wind turbines, and roof-mounted wind turbines to meet their demands. This study focused on exploiting the wind flow conditions around the premises and wind force characteristics of the buildings situated at VIT Chennai premises for effective utilization of wind energy and determining the hot spots of unfavourable wind. By introducing CFD simulation earlier into the design process, it is easy to assess the wind resource conditions, pedestrian safety and comfort. However, the accuracy and reliability of CFD simulations can easily be compromised. For this reason, several sets of best practice guidelines have been developed in the past decades. Based on the best practices, this work presents the CFD simulation and framework for evaluating pedestrian comfort and possible areas to commission small wind turbines in the VIT campus. The simulations for assessing the wind flow conditions are carried out based on the k-∊ realizable turbulent model with high-quality grid-based convergence. The preliminary results can ensure wind comfort, safety and wind resources with CFD and add to enriched wind environmental quality in living.

Experimental investigation of wind characteristics and wind energy potential over rooftops: Effects of building parameters

In this study, the wind flow characteristics and wind energy potential over the flat rooftops of tall buildings were investigated systematically via wind tunnel testing. The effects of building parameters such as the building height ratio (Hr ​= ​3, 5, and 7) and the building width ratio (Wr ​= ​1, 2, and 3) were examined. Due to symmetry, the experiments were conducted up to 90° wind direction in a simulated boundary layer flow in increments of 22.5°. For a given building, a 3 ​× ​3 array of points was set on the roof plan and stretched vertically up to a height of z ​= ​2H, H for building height. The vertical wind profiles over the rooftops showed similar patterns at various locations and wind directions. The maximum wind energy amplification factor Cw,max generally increased with Wr and Hr, but it was far more sensitive to Wr than to Hr. The Cw,max values ranged from 1.6 to 2.7, which suggests the great potential for a large wind energy yield over rooftops. However, hub heights from z/H ​= ​1.02 to 1.19 demonstrated much lower values than those given in the literature. This study provides valuable experimental data for the guidance of roof-mounted wind turbines.

A framework for preliminary large-scale urban wind energy potential assessment: Roof-mounted wind turbines

Urban wind energy can provide a decentralized local source of energy for residential areas and reduce the cost of energy by avoiding the losses/costs of long-distance energy transmission. In this perspective, a preliminary assessment of urban wind energy is highly desired by turbine developers, investors and policy makers. However, given the large number of parameters involved, predictions of the wind energy potential in urban areas are very challenging. The present paper, therefore, intends to present a straightforward framework to provide a preliminary and large-scale assessment of the urban wind energy potential, i.e. at city or country scales, for roof-mounted turbines. The framework is based on four main steps: (i) collecting the building data, i.e. the number of potential candidate high-rise buildings and their height and rooftop surface area; (ii) obtaining the annual mean wind speed statistics at the height of these buildings and sorting the building data based on these statistics; (iii) obtaining the turbine characteristics and determining the average number of turbines per building roof; (iv) calculating the annual energy production (AEP). The application of the framework is then illustrated at the country scale for the Netherlands. In this case, the urban wind energy potential is assessed by considering the installation of 18,156 small wind turbines on the roofs of 1513 existing high-rise buildings in 12 major cities in the Netherlands, yielding an annual energy production of 150.1 GWh.

Monitoring and Modeling Roof-Level Wind Speed in a Changing City

Results of an observational campaign and model study are presented demonstrating how the wind field at roof-level in the urban area of Vienna changed due to the construction of a new building nearby. The investigation was designed with a focus on the wind energy yield of a roof-mounted small wind turbine but the findings are also relevant for air dispersion applications. Wind speed profiles above roof top are simulated with the complex fluid dynamics (CFD) model MISKAM (Mikroskaliges Klima- und Ausbreitungsmodell, microscale climate and dispersion model). The comparison to mast measurements reveals that the model underestimates the wind speeds within the first few meters above the roof, but successfully reproduces wind conditions at 10 m above the roof top (corresponding to about 0.5 times the building height). Scenario simulations with different building configurations at the adjacent property result in an increase or decrease of wind speed above roof top depending on the flow direction at the upper boundary of the urban canopy layer (UCL). The maximum increase or decrease in wind speed caused by the alternations in building structure nearby is found to be in the order of 10%. For the energy yield of a roof-mounted small wind turbine at this site, wind speed changes of this magnitude are negligible due to the generally low prevailing wind speeds of about 3.5 m s−1. Nevertheless, wind speed changes of this order could be significant for wind energy yield in urban areas with higher mean wind speeds. This effect in any case needs to be considered in siting and conducting an urban meteorological monitoring network in order to ensure the homogeneity of observed time-series and may alter the emission and dispersion of pollutants or odor at roof level.

Wind power potential assessment of roof mounted wind turbines in cities

A new methodology to evaluate performance and energy output of roof mounted wind turbines in cities is presented. The methodology combines Computational Fluid Dynamics (CFD) and meteorological data related to a city to assess the energy production of turbine placement on the roof of a building located in a city. The interaction between a Darrieus turbine and a building when the turbine is placed on the roof-top is analysed based on CFD and an accurate power curve is generated. Afterwards, energy yield calculations of this Darrieus turbine placed at each of the 4 corners of a building are performed for both a low and high density urban environments. The energy yield calculations are based on modelling actual regions of a city, followed by simulation of the wind for 8 directions and coupling CFD results with meteorological wind data to obtain an accurate estimate of the energy output. Simulation results indicate that energy production in high density urban environments is significantly reduced due to local wind behaviour.

Computational fluid dynamic analysis of roof-mounted vertical-axis wind turbine with diffuser shroud, flange, and vanes

Advances in wind power and tidal power have matured considerably to offer clean and sustainable energy alternatives. Nevertheless, distributed small-scale energy production from wind in urban areas has been disappointing because of very low efficiencies of the turbines. A novel wind turbine design — a seven-bladed Savonius vertical-axis wind turbine (VAWT) that is horizontally oriented inside a diffuser shroud and mounted on top of a building — has been shown to overcome the drawback of low efficiency. The objective this study was to analyze the performance of this novel wind turbine design for different wind directions and for different guide vanes placed at the entrance of the diffuser shroud. The flow field over the turbine and guide vanes was analyzed using computational fluid dynamics (CFD) on a 3D grid for multiple tip-speed ratios (TSRs). Four wind directions and three guide-vane angles were analyzed. The wind-direction analysis indicates that the power coefficient decreases to about half when the wind is oriented at 45° to the main axis of the turbine. The analysis of the guide vanes indicates a maximum power coefficient of 0.33 at a vane angle of 55°.

Numerical investigation of the optimum wind turbine sitting for domestic flat roofs

The power capacity of roof mounted wind turbines is dependent on several factors which influence its energy yield. In this paper, an investigation has been carried out using Computational Fluid Dynamics (CFD) to determine flow distribution and establish an optimum mounting location for a small wind turbine on a domestic flat roof. The realisable k-ε and SST k-ω turbulence models were compared to establish their consistency with one another with respect to the physical domain. Nine mounting locations were considered for a pole mounted wind turbine. Three windward positions on the upwind side of the flat surfaced building were considered as viable locations for mounting the small wind turbine. Out of the three windward locations, the central upwind (1,0) mounting position was seen to be producing the highest velocity of 5.3 m/s from the available ambient velocity which was 4 m/s. Therefore, this mounting location provided the highest extractable power for the wind turbine. Conclusively, wind properties along with the mounting locations can play a significant role in either enhancing or diminishing the small wind turbine's performance on a domestic flat roof.

Numerical Investigation of Wind Conditions for Roof-Mounted Wind Turbines: Effects of Wind Direction and Horizontal Aspect Ratio of a High-Rise Cuboid Building

From the viewpoint of installing small wind turbines (SWTs) on rooftops, this study investigated the effects of wind direction and horizontal aspect ratio (HAR = width/length) of a high-rise cuboid building on wind conditions above the roof by conducting large eddy simulations (LESs). The LES results confirmed that as HAR decreases (i.e., as the building width decreases), the variation in wind velocity over the roof tends to decrease. This tendency is more prominent as the angle between the wind direction and the normal vector of the building’s leeward face with longer roof edge increases. Moreover, at windward corners of the roof, wind conditions are generally favorable at relatively low heights. In contrast, at the midpoint of the roof's windward edge, wind conditions are generally not favorable at relatively low heights. At leeward representative locations of the roof, the bottoms of the height range of favorable wind conditions are typically higher than those at the windward representative locations, but the favorable wind conditions are much better at the leeward representative locations. When there is no prevailing wind direction, the center of the roof is more favorable for installing SWTs than the corners or the edge midpoints of the roof.

The influence of a cubic building on a roof mounted wind turbine

The performance of a wind turbine located above a cubic building is not well understood. This issue is of fundamental importance for the design of small scale wind turbines. One variable which is of particular importance in this respect is the turbine height above roof level. In this work, the power performance of a small wind turbine is assessed as a function of the height above the roof of a generic cubic building. A 3D Computational Fluid Dynamics model of a 10m x 10m x 10m building is used with the turbine modelled as an actuator disc. Results have shown an improvement in the average power coefficient even in cases where the rotor is partially located within the roof separation zone. This goes against current notions of small wind turbine power production. This study can be of particular importance to guide the turbine installation height on building roof tops.

Wind environment at a roof-mounted wind turbine on a peaked roof building

Knowledge of the wind resource above peaked roofs is necessary to determine whether installing small wind turbines on low-rise peaked roof buildings is feasible. The wind characteristics at a representative peaked roof barn in southern Ontario, Canada were investigated using a boundary layer wind tunnel and computational fluid dynamics. Field measurements at the barn were collected using sonic anemometers and compared with the simulation results. Wind speed amplification was confined to a region immediately above the roof and was relatively low for wind energy purposes. The presence of nearby trees or buildings adversely impacted wind speed amplification. Considering only wind-related factors, the placing of micro-wind turbines on roof peaks may be warranted. However, if sufficient space is available, it is recommended to place small turbines on a tower rather than on the peaked roof of a low-rise building.

Effect of roof shape, wind direction, building height and urban configuration on the energy yield and positioning of roof mounted wind turbines

The increasing interest among architects and planners in designing environmentally friendly buildings has led to a desire to explore and integrate renewable sources of energy. Roof mounted wind turbines is a technology that presents a high potential for integration within the built environment. However, there is a state of uncertainty regarding the feasibility of these wind turbines. This paper argues that part of this uncertainty is attributed to uninformed decisions about positioning and locating urban wind turbines. This is underpinned by lack of consideration to the accelerating effect of different roof shapes, buildings' heights and surrounding urban configurations. This paper aims to present the results of Computational Fluid Dynamics (CFD) simulations for the purpose of identifying the effect of different roof shapes on the energy yield and positioning of roof mounted wind turbines covering different buildings' heights within different urban configurations under different wind directions. Results from this investigation suggest that an increase in energy yield could be achieved which can reach 56.1% more electricity in the case of a vaulted roof if an informed wind assessment above buildings' roofs is carried out.

Numerical Simulation of the Fluid Flow around a Roof Mounted Wind Turbine

The aerodynamic performances of a roof mounted small vertical axis wind turbine are evaluated using a Computational Fluid Dynamics (CFD) code and a computer program based on the Blade Element Momentum theory. The CFD code solves the incompressible Reynolds Averaged Navier-Stokes (RANS) equations for the simulation of the flow around a building with a roof mounted wind turbine. These computations are performed with a 3D grid, assuming steady and fully turbulent flow. The CFD results are used to derive the wind velocity vector approaching the wind turbine. Then the aerodynamic performances of the roof mounted wind turbine are determined using a Multiple Stream tube Theory. Beforehand, to check the reliability of the CFD computations, the simulations of the flow around reference buildings are performed and the results are compared with reference data.

The Energy Yield of Roof Mounted Wind Turbines

The roof is a possible site for small wind turbines. This is a new but more and more accepted idea. Several Dutch companies in close cooperation with the Section Wind Energy of Delft University of Technology are busy with the design of small roof wind turbines at the moment. The important flow features for a wind turbine on the roof however are unknown. The common wind engineering knowledge is only focussed on extreme wind speeds in order to have a safe building. So, models to calculate the flow features on the roof, important for a wind turbine, have to be developed. This paper gives a first attempt to describe the flow features and guidelines necessary for siting of small wind turbines on the roof. They concern: the desirable height above the roof, the change of the undisturbed wind to the wind speed above the roof and the probability distribution of the wind speed above the roof. With use of the guidelines three example calculations are given to assist the reader in the calculation procedure.