Keywords

Small-scale turbine; micro-wind turbine; rural building mounted turbine; suburb building mounted turbine; urban building mounted turbine; pole mounted turbines; trial observations

19.1 Introduction

This chapter deals with micro and small wind turbines. Micro-wind turbines are typically defined as having a rated power up to 1.5 kWp (where p refers to peak power) and their most widely used application is in yachts for battery charging. Small wind turbines are rated between 1.5 and 100 kWp and are generally free standing, pole or tower mounted turbines. Small wind turbines at the lower end of this range are sometimes used in off-grid systems, but turbines above 20 kWp are almost always grid connected (Fig. 19.1). The majority of micro and small wind turbines are horizontal axis three blade designs. Vertical axis small wind turbines (VAWT) represent a small fraction of the market despite their claimed performance benefits over horizontal axis turbines particularly in relation to turbulent wind response.

This chapter focuses on small wind turbines in the United Kingdom over the past decade (2005–15), which represents a period of “boom and bust” for building mounted micro-wind turbines in particular. The sector was trying to break out from yacht battery charging to the emerging grid connected micro-generation sector during this period (Figs. 19.2–19.5).

Grid connected micro-generation carries high-upfront capital costs, which is often the key barrier to commercial uptake. To encourage “early adopter” take up of a new technology, grants are often initially used to cover a fraction of the capital cost. Later as the market penetration of a technology grows, more radical policy approaches such as enabling businesses to apply enhanced capital allowances to micro-generation investment or feed in tariffs may emerge [2,3].

Grant subsidies are, however, not without their problems. Whilst they enable micro-generation technologies to become visible to the public and so encourage wider take-up, as a subsidy they financially reward installation of a system and not generation. This is a fundamental weakness of grant subsidies; it risks rapid deployment of a technology with potentially limited regard to the long-term performance. Poor energy yield performance is to the detriment of primarily the turbine owner but also to the grant funder in the longer term. The installer, however, has already been paid and whilst reputational damage may occur, this may take several years to emerge and will affect the wider industry.

In the case of micro-wind turbines, the predictive performance problem is exacerbated by the fact that the wind resource at a site is very difficult to quantify with any level of confidence without undertaking prior measurements. Field measurements are expensive to undertake, even placing an anemometer in an appropriate location for 6–12 months would cost at least £1000. This cost alone would make most micro-wind turbines financially unattractive. For installers undertaking site wind measurements also delays the actual deployment of the turbine and the installer payment.

Guidance documents in the United Kingdom at this time [4,5] stated that the threshold wind speeds should be 5 m s⁻¹ for installation. The primary data source for this information was the Numerical Objective Analysis Boundary Layer (NOABL) wind speed modeling tool [6] and underlying UK weather station dataset. The NOABL tool was developed as a wind resource assessment for large-scale onshore wind turbines located in clean air, rural locations. The modeling interpolates wind speeds from meteorological weather stations across the entire UK assuming rural land form with no obstructions throughout. If NOABL is used to assess wind speeds without the use of correction factors to account for built form density, it will significantly overestimate the wind speed resource. The tool was never developed with micro-wind turbines as the application but it has become the starting point for site resource assessment and this was part of the problem in the United Kingdom.

In 2008 the British Wind Energy Association (BWEA), now RenewablesUK, published its annual report of the state of the micro-wind industry [7]. It is instructive to look at some of the data published for this year in terms of the claimed typical load factors for small wind turbines and market projections. In the United Kingdom, large onshore wind farms have an average load factor of around 28% with offshore wind farms around 38% [8]. The 2008 BWEA report provides average Annual Energy Production (AEP) data, which corresponds to load factors of 10% and 17% for building mounted and small pole mounted wind turbines, respectively. The building mounted turbine market was predicted to grow by over 400% to about 11,700 turbines annum⁻¹ in the United Kingdom from 2007 to 2009 as highlighted in Fig. 19.6.

B&Q, a major DIY (Do-It-Yourself) retailer started to sell a 1.0 kWp wind turbine, the WS1000, produced by Windsave Ltd. in 2006. The micro-wind turbine was sold as a complete, fully installed system (turnkey solution of turbine, grid connected inverter and wiring). The total cost of the B&Q Windsave system was £1498 fully installed.

To stimulate the micro-generation sector, United Kingdom launched the Low Carbon Buildings Programme [9] in April 2006, funding projects across four streams: households, communities, medium scale, and large scale. In total the government funded £91×10⁶ (£91 million) of micro-generation demonstration projects. In relation to small wind, 940 wind turbines (0.5–50 kWp) were installed through LCBP (total wind turbine grant value £4.7×10⁶ (£4.7 million)), representing 4.9% of all micro-generation installations and 5.1% of the total budget.

It is instructive to consider what the 2008 report BWEA claimed typical load factors [7] would mean for the economics of such a Windsave turbine.

$\begin{array}{ll}\mathrm{Annual}\mathrm{generation}(\mathrm{kW}\mathrm{h})\hfill & =\mathrm{Load}\mathrm{factor}(\%/100)\times \mathrm{rated}\mathrm{power}(\mathrm{kW})\hfill \\ \hfill & \times \mathrm{hours\; in\; the\; year}\\ \hfill & =0.10\times 1.0\times 8760=876\mathrm{kWh}{\mathrm{a}}^{-1}\hfill \end{array}$

Considering the standard electricity tariff of 12p/kWh this generates an avoided import value of £105/annum.

With an LCBP grant of £500 on proof of installation, this would give a simple payback time of less than 10 years at a discount rate of 0%. At the time, residential solar photovoltaic (PV) systems were in comparison far more expensive at around £8000 for a 3 kWp system. There was also no feed in tariff in place at this point in the United Kingdom. In addition, an outlay of £1500 was seen by the micro-generation industry as a more affordable “discretionary” purchase for early adopters, compared with the far higher cost in 2006 of a home PV system.

By 2006, the micro-wind turbine market was growing rapidly in the United Kingdom, primarily driven by companies such as B&Q’s selling of the Windsave WS1000 turbine. However, concerns began to emerge about the claimed energy performance figures of turbines, especially in the built environment. The WarwickWindTrial study of 26 turbines in locations ranging from “theoretically poor” to “theoretically excellent” produced an average load factor of 4.1% in [10] 2009. The BWEA’s 2008 published average load factor figures of 10% (building mounted) and 17% (pole mounted) started to look very optimistic. B&Q suspended the selling of micro-wind turbines in February 2009 following the WarwickWindTrial report, pending the findings of the larger national micro-wind trial undertaken by the Energy Saving Trust [11].

In July 2009 the National Micro-wind Trial report, “Location, Location, Location: Domestic small-scale wind field trial report” was released [11]. B&Q offered all micro-wind turbine customers a full refund and free decommissioning of their system. Windsave, the supplier to B&Q filed for bankruptcy in September 2009 when B&Q effectively ended their relationship with them.

The 2008 BWEA Small wind systems report uses the assumption that building mounted or off-grid (on a boat) turbines (up to 1.5 kW) have an average load factor of 10% [7]. There is no differentiation in load factor regardless of the application. The assumed load factor increases to 17% for free standing, pole mounted turbines, but again is regardless of the application (1.5–10 kW).

This EST micro-wind field trial was established to address a number of key questions:

19.2 The Fundamental Concern for Micro-Wind: The Wind Resource

The fundamental issue for micro-wind is the wind resource. It does not matter if a micro-wind turbine is able to rapidly respond to changing wind speeds or work well in turbulent wind if the overall wind resource is poor. To illustrate this issue, the example of the wind resource on the roof of a University of Southampton (UoS) building is considered (Fig. 19.7, weather station highlighted as yellow square). Southampton is located on the South Coast of the United Kingdom, it is a port city of around 250 000 people. The University is located to the north of the city in an urban area (orange square in Fig. 19.7). The weather station is on the top of a three storey building on the main campus. The prevailing wind is from the South West in the United Kingdom and in this direction the land falls away at the site as the campus is on a slope. The roof of the building would be considered to be fairly unobstructed in the prevailing wind direction for an urban environment (yellow arc in Fig. 19.7).

NOABL provides the predicted wind speed for any 1 km grid square in the United Kingdom at 45 m, 25 m, and 10 m above ground level (AGL). These wind speeds are for clean air, unobstructed terrain. The University of Southampton NOABL 1 km grid square reference 445,111 (SU4511), NOABL output: 45 m AGL=6.5 m s⁻¹ 25 m AGL=6.0 m s⁻¹, 10 m AGL=5.2 m s⁻¹

The NOABL-MCS correction factor [4] for the University of Southampton weather station anemometer would be 0.35×NOABL=1.8 m s⁻¹, to account for built up location and an anemometer height of 2 m above the roof. This would correspond to a building mounted turbine where the turbine blade tip comes within 2 m of the roof during a rotation (dense urban 35% correction factor, see Table 19.1).

Table 19.1

NOABL MCS3003, Issue 2.0 (2010) Wind Speed Correction Factors for Level of Urbanization of a Site and Proximity of a Turbine to Roof and Nearest Obstructions

NOABL correction classification	Proximity of turbine to roof or nearest obstruction	Lowest point of turbine above roof (m)	NOABL wind speed scaling factor
Rural
Open country with occasional houses and trees		12	100%
		7	94%
		2	86%
		0	82%
Low-rise urban/suburban
Typically town/village situations with other buildings well-spaced		6	67%
		4	61%
		2	53%
		0	39%
Dense Urban
City centers of most closely spaced four-storey buildings or higher		10	56%
		5	51%
		3	44%
		1	35%

Source: Scaling factors derived from data given in Harris RI, Deaves DM. The structure of strong winds. Wind engineering in the eighties, Proc. CIRIA Conference, London, November 12–13; 1980.

The Microgeneration Installation Standard MIS3003 issue 2.0 [4] has three wind speed categories as shown in Table 19.1. The 2015 revision [12] increased this to five essentially splitting the rural category into three, to provide better prediction in the key rural sector and providing better hub-height correction. The underlying scaling factor analysis remains unchanged and relates to the work of Harris and Deaves in 1980 [13]. The stated threshold wind speed for installing a micro-wind turbine is 5.0 m s⁻¹, which this site achieves as a NOABL estimate, although with urbanization correction applied this estimate is reduced to 1.8 m s⁻¹. Fig. 19.8 compares a NOABL wind speed average as a Weibull distribution with a shape factor of two with the observed wind speed data over a 12 month period. The observed wind speed has an average of 2.35 m s⁻¹ and fits well to a Weibull distribution with a shape factor of two. This one graph serves to highlight the issue for micro-wind, uncorrected clean air wind speeds are not appropriate and should not be used.

Fig. 19.9 compares the predicted yield of a Windsave WS1000 turbine if mounted at the position of the University of Southampton anemometer in terms of the NOABL wind speed and the measured anemometer. The power curve for the WS1000 turbine has been applied to the wind speed cubed but with no cut-in or cut-out speed has been applied. The predicted energy output is shown as a binned distribution of the wind speed cubed (0.5 m s⁻¹ bin width). The NOABL wind speed gives an estimated annual yield of 836 kWh a⁻¹, compared to 94 kWh that can be achieved for the actual wind resource. In reality the WS1000 turbine has a cut-in speed of 4.5 m s⁻¹ so the potential generation is around a half of the estimated 836 kWh.

This analysis does not consider the power requirements of the inverter, which is a further complication for grid connected systems in particular. In the United Kingdom there are specific performance characteristics that inverters must comply with, for grid connection. Systems less than 16 A phase⁻¹ (3.68 kWp single phase) follow guidance under Engineering Recommendation G83/2 (2012), (Recommendations for the Connection of Type Tested Small-scale Embedded Generators (Up to 16 A per Phase) in Parallel with Low-Voltage Distribution Systems [14]. Systems above 16 A need to be compliant to G59 [15]. In the case of G83/2 there is a requirement that a minimum reconnection period of 20 seconds occurs when an inverter senses the grid voltage and frequency within accepted limits. Therefore an inverter must always be synchronized with the utility grid to be able to immediately export generated power. In the case of PV, there is always enough DC power on even the dullest of days from a PV array to power the inverter and keep it synchronized. Micro-wind is more problematic; if the wind is infrequent and gusty, the inverter may be off and may not complete its synchronization cycle in time to export the potential generation from a gust. For this reason, a micro-wind inverter may take its synchronization power from the utility grid rather than the DC side as is the case with PV. In some of the field trial examples shown in this chapter, this can actually lead to a “negative load factor” where, in extreme cases, the parasitic load of the turbine is actually greater than the annual generation (see case study example of an Urban Building Mounted Turbine, Fig. 19.22). If we consider that an inverter might have a parasitic AC load of up to 10 W, this would correspond to approximately 88 kWh a⁻¹, which in the case of the University of Southampton’s example given earlier and Fig. 19.9, would cancel out all theoretical generation.

It is with these performance concerns in mind that the UK’s National Micro-wind Field Trial became established building on the work of the WarwickWindTrials [10]. Under the UK’s National Micro-Wind Trial nine different types of turbines were assessed; five building mounted and four pole mounted (Table 19.1). These turbines had predominantly either been installed through the Low Carbon Buildings Programme [9] or were Windsave turbines purchased through B&Q. Table 19.1 shows the specifications of the turbines and it is interesting to note that there is no specific wind speed at which manufacturers choose to rate their turbine. A total of 64 building mounted and 22 pole mounted turbines were monitored for a period of 12 months across urban, suburban, and rural locations (Table 19.2).

In addition to the fully monitored sites of UK’s National Micro-wind Field Trial, monthly generation readings from an additional 68 micro-wind turbines were provided to the trial. Building mounted and pole mounted turbines are considered separately in the next two sections. The UK’s National Micro-wind Field Trial study forms the basis of the data presented here and further information can be found in two Energy Policy publications by the authors [16,17].

19.3 Building Mounted Turbines

Fig. 19.10 shows the distribution of building mounted wind turbines in the United Kingdom for the national micro-wind field trial. Five case study sites are highlighted: Southampton (Dense Urban), South East London (Dense Urban), Felixstowe (Low-rise urban/suburban), King’s Lynn (Rural), and Silsoe (Rural).

It is instructive to compare the manufacturer’s published power curves of the various building mounted turbines with a commonly used large-scale turbine of the period, a 1.8 MW Vestas V90. Peak efficiencies at realistic wind speeds for operation (above 4 m s⁻¹) are around 40% and as you would expect are lower than that of the large V90 turbine (45%) and occur at a lower wind speed (Fig. 19.11). The corresponding AEP is shown in Fig. 19.12. The Windsave WS1000 is predicted to generate about 900 kWh a⁻¹ for an average annual wind speed of 5 m s⁻¹. It is interesting to note that this AEP is similar to that of 1 kWp of roof mounted PV in the South of the United Kingdom [18], but obviously at higher capital cost that the micro-wind turbine.

The initial data monitoring testing for the field trial was undertaken at Silsoe in Bedfordshire. An industrial shed surrounded by low lying fields was used to assess the performance of a WS1000 turbine (Fig. 19.13).

Silsoe is not in a particularly windy location in the United Kingdom, with a stated NOABL wind speed of 4.6 m s⁻¹. The site is classified as rural and has a 2010 MIS3003 MCS 0.82 correction factor (3.8 m s⁻¹). Fig. 19.14 compares the 5 minute average anemometer measurements with turbine power over a period of four winter months (periods of highest wind speeds). The power curve shown is interpolated from the measured dataset and shows close agreement with the manufacturer’s published data. It is interesting to note the scatter in power points above 5 minute average wind speeds of 11 m s⁻¹. This is where, over a 5 minute period the peak wind speed may exceed the cut-out speed of 15 m s⁻¹ leading to a loss of output.

The measured wind speed distribution and turbine performance over a 12 month period (March 2008–February 2009) is shown in Figs. 19.13 and 19.15, respectively. The overall generation was 244 kWh (103 kWh m⁻² swept area), with an average wind speed of 3.4 m s⁻¹. This corresponds to a load factor of 2.8 %.

The data monitoring at the Silsoe site was reconfigured to record 1 second interval data of wind speed and power to assess the speed of response of the WS1000 turbine. Fig. 19.16 shows the wind speed and turbine power output over an example 300 s period. There is a clear correlation between wind speed and power output suggesting the response of the turbine is indeed fast of the order of seconds. If one compares the Turbulent Intensity, TI, defined as the (standard deviation of wind speed over a 10 minute period)/(average wind speed over a 10 minute period), over a 10 minute period with the output of the turbine, this rapid response is evident (Fig. 19.16).

Periods of high turbulent intensity corresponds to rapid changes in wind speed. The energy (proportional to wind speed cubed) in 10 minutes of high TI will be larger than for a low TI period. This is illustrated in Fig. 19.17, where the power output of the turbine as a function of TI (low and high) is shown. High TI periods produce greater power output from the turbine than periods of lower TI with the same average wind speed. The performance benefit of high TI reduces at higher wind speeds as it increases the probability of the cut-out wind speed (15 m s⁻¹) being reached in that 10 minute period.

19.3.1 Rural Building Mounted Turbine

• Fig. 19.18 shows a rural class site [4] building mounted turbine near King’s Lynn. The prevailing wind is from the South West with an average wind speed of 3.65 m s⁻¹. The NOABL [6] and NOABL-MCS (2010) [4] wind speed estimates for the site are 5.0 and 4.3 m s⁻¹, respectively. The measured load factor, including inverter power draw was 3.1% over a 12 month monitoring period (Fig. 19.19).

19.3.2 Suburban Building Mounted Turbine

Fig. 19.20 shows a coastal, suburban turbine in Felixstowe on the East coast of the United Kingdom. The NOABL [6] and NOABL-MCS (2010) [4] wind speed estimates for the site are 5.7 and 2.2 m s⁻¹, respectively. The measured wind speed was 2.83 m s⁻¹ which resulted in an annual load factor of 0.6% (Fig. 19.21).

19.3.3 Urban Building Mounted Turbine

Fig. 19.22 shows a highly urbanized site in South London. The turbine has been installed at the eaves height of the roof, whereas the wind speed anemometer is above the roof height. The NOABL and NOABL-MCS (2010) [4] wind speeds for the anemometer location are 5.0 and 1.8 m s⁻¹. The site is clearly not appropriate for micro-wind and this is reflected in the measured wind speeds and turbine output (Fig. 19.23). In this case, the parasitic AC demand of the inverter is actually greater than the generation of the turbine resulting in an overall negative load factor. If the turbine has been located at the anemometer position, the higher generation would have just exceeded the inverter power requirements over the year.

19.3.4 Summary Findings: Building Mounted Turbines

Fig. 19.24 shows the performance analysis of the building mounted turbines. It is important to note that half of the urban turbines have a negative load factor (they consume more power than they generate over the year). The best performing rural wind turbines generated around 300 kWh m⁻² a⁻¹, which corresponds to a load factor of ~8%. The field trial data has shown this very poor performance compared to the claimed typical load factor of 10%. Fig. 19.25 compares the measured wind speeds at the building mounted turbine sites with that predicted by NOABL-MCS [4]. The solid gray line shows a 1:1 (perfect) relationship between prediction and observation. For urban and rural sites there is a fairly even scatter on either side of the perfect fit line. The NOABL-MCS 2010 correction therefore appears appropriate for both Urban and Suburban sites. However, this correction merely serves to confirm that there is no wind resource in such locations. The threshold wind speed for installation of micro-wind turbine is 5.0 m s⁻¹. Only two sites in the trial achieved this design threshold, although no sites had a measured wind speed above 4.0 m s⁻¹. It appears that the NOABL-MCS 2010 [4] correction still represents an overestimate of wind resource for rural locations.

19.3.5 Field Trial Observations: Pole Mounted Turbines

Fig. 19.26 shows the location of pole mounted turbines in the UK’s National Micro-wind Trial. These are generally located on farmland in what would be considered as good wind resource locations.

The calculated manufacturer’s efficiency curves and AEP as a function of wind speed are shown in Figs. 19.27 and 19.28. All the pole mounted turbines show very similar AEP predictions for the expected wind speed ranges (4.8 m s⁻¹ annual average).

Fig. 19.29 shows a typical farm-based pole mounted turbine wind trial site. A Proven 6 kW turbine is located in a field near to the main farm buildings. Scaffold poles have been used to mount an anemometer at the same height as the turbine hub (12 m). The predominant wind speed direction is from the South West. The average wind speed of the site was 4.62 m s⁻¹ compared to NOABL [6] and NOABL-MCS 2010 [4] estimates of 7.7 and 6.8 m s⁻¹. The load factor of the site was 20.6% (Fig. 19.30).

Fig. 19.31 compares the NOABL-MCS estimate of annual generation [4] with the measured performance of pole mounted turbines in the trial. Whilst there is still a high level of variability in site-specific prediction, the overall relationship is consistent.

19.4 The Future for Micro-Wind

Pole mounted turbines were shown to perform well in the UK’s National Micro-wind Trial. An average load factor of 19% was measured with the best turbine sites having load factors in excess of 30% (Orkney Islands). Rural landowners, especially farmers are a clear market for pole mounted turbines. The groundwork installation costs such as foundations and underground cable laying can in some cases be undertaken by the farmer at marginal cost. An assessment in 2009 by the authors of the potential pole mount turbine market in the United Kingdom was based around the premise of 50 kWp being installed in each farm in the United Kingdom, which achieved a threshold wind speed [17]. For a threshold NOABL-MCS [4] wind speed of 5.0 m s⁻¹ this suggested a resource-based potential UK market of around 87,000 farm sites (achieving a load factor threshold of 17%), predominantly in Scotland.

Feed in tariffs have transformed the micro-generation sector in the United Kingdom. Over the past 5 years, PV has become almost ubiquitous either on household roofs or ground mounted in fields. As of May 2016, there was 10,265 MW of PV capacity in the United Kingdom across 882,440 installations. Around 40% of this capacity is in the 5–25 MWp capacity range [19]. By comparison the cumulative number of small wind turbines (<50 kW) is very small. There are 4226 turbines in the range 1.5–15 kW and 749 in the 15–50 kW range, respectively, with an overall capacity of 52 MW. For all but the windiest of sites in the United Kingdom, PV will offer a better financial return and is a lower risk investment with an established supply chain and easy resource assessment. PV has a typical load factor of ~11% in the South of the United Kingdom, whereas an excellent pole mounted small wind site might achieve ~30%, but more typically 19%. The current grid connected PV cost is around £1265 kWp⁻¹ installed (10–50 kW range 2016), [20], whereas a high quality pole mounted turbine may be £5000–7000 kWp⁻¹ fully installed.

To qualify for feed in tariffs a system must be installed by an MCS certified contractor (Micro-generation Certification Scheme, [12]. As of June 2016, the most generous Feed in Tariff in the United Kingdom was 4.32 p kWh⁻¹ for generation from PV and 8.46 p kWh⁻¹ for generation from wind [21]. The overall economics are sensitive to the level of export to the grid, and therefore “avoided import,” which has a value of ~12 p kWh⁻¹. If we were to assume a 50% level of export for the case of PV and wind [22,23], a £5000 (kWp)⁻¹ turbine would need to have a load factor of ~28% to achieve the same financial payback time (14 years in each case at 0% discount rate). The twin issues of an unstable feed in tariff policy in the United Kingdom and the rapidly falling price of PV make the market challenging for small wind. This is outlined clearly in RenewableUK’s 2014 report “Small and Medium Wind Strategy: The current and future potential of the sub-500 kW wind industry in the UK,” which states that “experience shows mounting challenges, and our industry is at a crossroads that will determine its future” [24].

19.5 Conclusions

The main lesson from the UK’s National Micro-wind Trial study is born out in its formal report title “Location, Location, Location: Domestic small-scale wind field trial report.” It is that there is simply insufficient wind resource in urban and suburban locations [11]. Deploying micro-wind turbines in these locations will lead to very poor load factors (typically 2%) and in some cases they may even be negative due to the parasitic AC power draw of the inverter.

The study suggests that horizontal axis micro-wind turbines are able to respond quickly to changes in wind speed, in essence that turbulence is not the key issue in relation to poor performance. The best performing rural building mounted turbines had load factors up to 8%, which is still less than PV in the United Kingdom. The building mounted turbine MCS correction factors for NOABL wind speeds [4] show good agreement for urban and suburban sites, but the NOABL-MCS rural value appeared high in this study.

Pole mounted turbines performed well in this study achieving the expected load factors (average 19%). The NOABL-MCS correction to wind speed for rural pole mounted turbines is far better, but still, on an individual site basis, can lead to a large over or under estimate of the resource.

For off-grid systems, wind and PV are complementary technologies having higher generation in different seasons of the year. In relation to grid connected systems, the dramatic reduction in the cost of PV, driven by generous feed in tariffs has transformed the micro-generation sector in the United Kingdom. This has made the economics of small grid connected wind much more difficult in a highly competitive market. The deployment of medium wind (100–500 kW) on rural farms is a sector, which has significant potential but is still in the very early phases of scale up in the United Kingdom. In 2014 211 turbines were deployed in the United Kingdom compared to just 18 in 2011 [1]. The long-term success of this market will depend on the feed in tariff policies in the United Kingdom and the relative cost of generation compared to PV.

Acknowledgments

This work is part of the activities of the Energy and Climate Change Division and the Sustainable Energy Research Group (www.energy.soton.ac.uk). The work presented here was undertaken as part of the United Kingdom’s National Micro-wind Trial. The field trial was developed and delivered with funding and support from a wide variety of stakeholders including the Energy Saving Trust (EST); The Scottish Government; DEFRA; B&Q; and the UK’s main energy suppliers including EDF Energy, RWE Npower, NIE Energy, Centrica plc, ScottishPower Ltd., Scottish & Southern Energy, and E.on UK. These funders were represented on the project’s advisory group and were influential in the trial’s site selection and communications.

Aspects of this work formed the basis of the 2011 PhD study of Dr. Matthew Sissons entitled “Micro-wind power in the United Kingdom: Experimental datasets and theoretical models for site-specific yield analysis” [25].