Boyle G. (Ed.) Renewable Electricity and the Grid: The Challenge Of Variability

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Accompanying this range of renewable resources is a range of resource-specific

characteristics: for example, the ability to store biomass and waste before

conversion to electricity provides a high degree of control over the timing of

electricity production. By contrast, energy from tidal currents is very

predictable; however, it is not possible to control the timing of tides and, there-

fore, the pattern of electricity production at individual tidal sites.

By assessing the underlying resource properties, renewable electricity

generators can be broadly classified into two categories: those such as landfill

gas, biomass or hydro, where their pattern of electricity generation can be

controlled (dispatchable capacity); and those such as wind, wave, tidal and

solar resources, where the pattern of generation is dependent upon external

factors (non-dispatchable or variable-output capacity). The ability to control

the electricity generation of dispatchable renewables is analogous to the oper-

ation of conventional generating capacity, such as coal, gas and nuclear

capacity. Variable generation represents a departure from this conventional

operation of generating capacity since it is the speed of the wind (or height and

period of the waves, velocity of the tidal current, etc.) that determines the level

of generation at any particular time.

The UK’s renewable electricity portfolio currently includes a combination

of both dispatchable and variable-output renewables, with dispatchable

renewables being responsible for over 75 per cent of renewable electricity

generation (see Figure 3.1). While wind power, both onshore and offshore,

provides almost all variable generation from renewables, it is currently

responsible for less than one quarter of total renewable energy production.

Given that renewable electricity (including large-scale hydro) accounted for

around 4 per cent of UK electricity, variable-output renewables were

responsible for less than 1 per cent of UK electricity generation in 2005 (DTI,

2006a).

The contribution of variable-output renewables to renewable electricity

generation, and to overall electricity supply in the UK, is expected to increase

into the future. The Renewables Obligation currently supports a renewable

electricity target of 15.4 per cent electricity generation by 2015, with support

for renewable electricity generation continuing until 2027 (UK Parliament,

2006). However, it has been proposed that the Renewables Obligation be

expanded to 20 per cent of electricity generation by 2020 and potentially

modified to include targeted support for under-represented resources through

a ‘banding’ mechanism (DTI, 2006b). Forecasts for 2020 suggest that wind

power will represent around 70 per cent of renewable electricity generation

(see Figure 3.2), while the inclusion of electricity generation from wave and

tidal stream resources will see total variable-output renewable electricity

supply account for over three-quarters of renewable electricity, and around 15

per cent of total electricity generation (The Carbon Trust and DTI, 2003).

Given such scenarios for future renewable electricity generation, and the

desire of government to target funding at emerging renewable technologies, it

will become increasingly important for the electricity supply properties of

variable-output renewables to be known. And while wind power is forecast to

dominate this sector of renewable generation, the emergence of other variable-

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Renewable Resource Characteristics and Network Integration 57

Co-firing with

fossil fuels

Landfill gas

Small scale

hydro

Offshore wind

Onshore wind

Solid waste, sewage,

sludge and other

Source: DTI (2006a)

Figure 3.1 Contribution of different renewable resources to total renewable

electricity generation in the UK in 2005 (excludes large-scale hydro)

Small hydro

Biomass

Landfill gas

Tidal stream

Wave

Wind

Source: The Carbon Trust and DTI (2003)

Figure 3.2 Forecast contribution of different renewable resources to total

renewable electricity generation in the UK in 2020 (excludes large-scale

hydro)

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output technologies suggests that the characteristics and interaction of a

diversified portfolio of variable-output renewables will be valuable in under-

standing their interaction with demand patterns and network integration.

CHARACTERISTICS

The electricity production characteristics of variable renewables reflect the

availability, or change in availability, of the underlying ‘fuel’ being used to

generate electricity. In the UK, wind power is expected to develop rapidly into

the dominant method for supplying renewable energy, meaning that the UK

wind resource will be important in determining the characteristics of electricity

supplied by this resource. Much of the network modelling work carried out on

the UK electricity network has reflected this expectation by evaluating the

impact of a 20 per cent wind power scenario (Dale et al, 2004; Mott

MacDonald, 2004; Anderson, 2006). With the emergence of wave and tidal

power systems, an understanding of the underlying characteristics of these

resources will also be required.

This chapter presents an overview of the patterns of energy production from

UK wind, wave and tidal stream renewable resources, the variability of supply

associated with each resource, the relationship between electricity generation

and demand patterns, and the impact that large-scale electricity generation

could have on the net electricity demand pattern to be met by conventional

generators.

Patterns and variability of renewable energy availability

The availability of renewable energy varies over time, with location and with

the resource being exploited. The pattern of energy availability will also

change depending upon the time scale being considered. For example, tidal

stream energy shows very little change in energy production from year to year

or month to month; however, large changes in output can occur from hour to

hour. Contrast this with wave power, where output tends to change less than

tidal stream at the hourly level, but there are significant differences at the

monthly time scale – although these are small at an inter-annual time scale (see

Table 3.1).

The variability of a resource is also affected by the level of diversification

in its development. By exploiting a resource such as wind power at a range of

sites, the variability exhibited by the aggregate output from all wind develop-

ments would be reduced. This arises as the correlation between power output

patterns at different sites decreases as the distance between the sites increases

(Giebel, 2000; Sinden, 2007). With different sites experiencing different wind

conditions at any one time, changes in power output at one site (such as an

increase in power output in response to increasing wind speed) may be

partially offset by a decrease in power output at another site on the same

network.

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Table 3.1 Relative variability of wind, wave and tidal resources

over different time periods

Resource Annual Monthly Hourly

Wind Low Medium (over the year) Low

Wave Low Medium/high (over the year) Very low

Tidal stream* Very low Very low Very high

Note: * The spring-neap tide cycle results in large changes in power output over a two-week period. However,

these changes are smoothed at the monthly time step, resulting in low variability in tidal stream electricity

production from month to month.

This smoothing characteristic is particularly apparent at short time scales (such

as hour-to-hour generation patterns): diversification is unlikely to affect the

seasonal variability of wind power unless the area over which developments

can occur is exceptionally large. At the monthly time scale, the long-term avail-

ability of renewable resources differs significantly between wind, wave and

tidal stream resources (see Figure 3.3). Wave power shows the greatest

extremes in monthly output, with energy delivery peaking in January and

February, and reaching a minimum in July. Monthly energy production from

wave power over winter is typically more than five times the average monthly

energy generation during summer months. Wind power follows a similar

seasonal pattern – an expected result, given that ocean waves form as a result

Renewable Resource Characteristics and Network Integration 59

Figure 3.3 Percentage of annual electricity generation by wind, wave

and tidal power systems occurring during each month, with long-term UK

electricity demand distribution shown for comparison (normalized to account

for differing days per month)

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of the action of wind. However, the seasonal differences in wind power are not

as extreme as those found in the wave record. Energy production from wind

power is again dominated by the winter months, with minimum production

occurring during the summer months – typical winter month energy produc-

tion is around 1.8 times higher than summer month production. Tidal stream

energy shows a very different distribution of energy production over the year,

with average monthly energy production essentially constant across the year.

The monthly trend in electrical energy demand for the UK (see Figure 3.3)

shows some similarity to the distribution of energy production from wind and

wave power systems across the year, with higher demand in winter months and

lower demand during summer months. While this trend is encouraging, elec-

tricity networks need to keep electricity supply and demand in constant

balance. The section on ‘Renewable electricity supply and demand patterns’

considers the relationship between electricity demand and energy production

from variable-output renewables.

Hour-to-hour variation in output

A key aspect of variable-output renewable resources is the rate of change in

power output over time. The rate of change in output of a wave, wind or tidal

stream electricity generator depends upon two factors – the sensitivity of the

device to changes in environmental conditions and the degree to which envir-

onmental conditions change.

60 Renewable Electricity and the Grid

Source: Nordex (2006)

Figure 3.4 Power transform curve for a typical large wind turbine

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Consider the power transform curve for a Nordex N80 wind turbine (see

Figure 3.4): power output is most sensitive to changes in wind speed between

8 metres per second (m s

–1

) and 12m s

–1

, while outside this range the sensitiv-

ity of the wind turbine to changes in wind speed reduces. Changes in wind

speed below 4m s

–1

do not result in any change in power output since there is

no energy production; at the other extreme, changes in wind speed between

14m s

–1

and 25m s

–1

do not result in changes to output as the device operates

at rated capacity across this wind speed range. Almost 90 per cent of hours

experience wind speeds between 4ms

–1

and 14ms

–1

, the speed range associated

with changes in wind power output. While the development of a diversified

wind power sector will slightly reduce the sensitivity of power output to

changes in wind speed (Sinden, 2007), it remains the case that changes in wind

speed within this range will result in changes in power output. The second

component of power-output variability is the degree to which the resource

availability changes – for example, while a change in wind speed from 8ms

–1

12ms

–1

would result in a significant increase in power output from a wind

turbine, it is the frequency with which such changes occur that ultimately

determines the variability of the electricity supply.

The power output from wave and tidal stream energy devices is similarly

related to the sensitivity of the device and the degree to which the underlying

resource (i.e. wave height and period for wave power, or current velocity for

tidal stream power) fluctuates from hour to hour; however, the hour-to-hour

variability of tidal stream power output is highly dependent upon the location

and degree of resource development. In some regions, such as the Channel

Isles, the characteristics of the tidal stream resource allow for significant

smoothing of the power production pattern since the timing of peaks and mini-

mums in tidal stream current velocities varies between the different sites (see

Figure 3.5). However, other regions, such as the Pentland Firth, offer very

limited opportunities for diversification to smooth output variability as the

power production patterns from the different sites within the region are all

highly correlated (Sinden, 2005).

The difference in power output from one hour to the next for wind and

wave power output at the one-hour time step is shown in Figure 3.6 (note that

tidal stream power is not included in this graph due to the site-specific nature

of variability for this resource). Wave power shows a lower level of variability

than wind power in the UK, with a higher frequency of little or no change in

power output occurring from one hour to the next. The graph in Figure 3.6

has been truncated to show the frequency of hourly power output changes

between ±20 per cent of installed capacity – for wind power, 99.95 per cent of

all hourly changes in power output were less than 15 per cent of the installed

wind power capacity, with 46 per cent of hourly changes being equivalent to

less than 1 per cent of the installed wind power capacity. Wave power showed

a greater concentration of low-change hours, with 61 per cent of changes in

power output being equal to less than 1 per cent of the installed wave power

capacity, and with 99.975 per cent of all hourly changes in power output being

between ±20 per cent of installed capacity.

Renewable Resource Characteristics and Network Integration 61

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62 Renewable Electricity and the Grid

Note: Results are based on full development of the identified tidal resource at each site (see Black and Veatch,

2005).

Figure 3.5 Relative timing and contribution to renewable output from indi-

vidual tidal stream sites in the Channel Isles

Note: The graph is truncated to ±20 per cent of installed capacity; this shows more than 99.95 per cent of all

hourly changes.

Figure 3.6 Variability of wind and wave power output at the one-hour time

step

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RENEWABLE ELECTRICITY SUPPLY AND DEMAND

PATTERNS

Relationship between renewable energy availability and demand

While there is a natural correlation in the UK between the availability of wind

and wave power and electricity demand at a monthly time scale (see Figure

3.1), this degree of aggregation removes the inter-day variability that is present

in both demand and supply. By determining the availability of renewable

resources at an hourly time scale and comparing this availability to hourly elec-

tricity demand, a more detailed view of the availability of renewables during

different demand periods can be gained.

In the UK, wind and wave power deliver more energy during times of high

electricity demand, with periods of low electricity demand typically being asso-

ciated with significantly lower wind power output (see Figure 3.7). Wave

power shows higher average energy production during peak demand periods

than does wind power; however, this energy production tends to drop quickly

in hours with lower demand. Average energy production from tidal stream

power (see Figure 3.7) is essentially uniform across all demand hours. This

tendency for different average energy production levels at different demand

levels is highlighted in Figure 3.8, which shows the degree to which renewable

production from wind and wave power, together with demand, deviate from

the long-term average.

Renewable Resource Characteristics and Network Integration 63

Note: Average annual capacity factor is ~28 per cent for both wind and wave power, and 38 per cent for tidal

stream power.

Figure 3.7 Average wind and wave power availability (as capacity factor)

at different levels of demand

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64 Renewable Electricity and the Grid

Figure 3.8 Deviation of wind power, wave power and demand from annual

average production (and demand) levels

Source: Sinden (2007)

Figure 3.9 Distribution of hourly wind power output during peak

electricity demand

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These results do not mean that all high demand hours will experience higher

than average power output from wind and wave resources as there remains

considerable variability in the hourly output of wind power during high elec-

tricity demand hours. The actual power output that may be experienced from

these resources varies across a wide range. However, during high electricity

demand hours (the top 20 per cent of demand hours), the occurrence of low

power-output events is less than the long-term average, while medium and high

power events occur more frequently than the long-term average (see Figures

3.9 and 3.10).

Impact of renewables on demand variability

While the long-term availability of wind and wave power is broadly corre-

lated to changes in electricity demand, output variability from these resources,

together with tidal stream power, will affect the net electricity demand pattern

to be met by conventional generators. At the hourly level of demand fluctu-

ation, the development of significant renewable electricity generating capacity

will increase the hour-to-hour change in demand to be met by conventional

generators (see Figure 3.11). This impact varies both with the size of the

renewable resource development and with the composition of the renewable

capacity: where renewables deliver 5 per cent or less of total energy to the

electricity network over a year, there is little impact on net demand variability,

Renewable Resource Characteristics and Network Integration 65

Source: Sinden (2007)

Figure 3.10 Distribution of hourly wave power output during

peak electricity demand

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