wind power in power systems (ackermann/wind power in power systems) || wind power and storage

21

Wind Power and Storage

Aidan Tuohy and Mark O’Malley

21.1 Introduction

As wind power increases significantly on electrical grids, its variability and uncertainty, which

are underlying characteristics, will impact on the ability of system operators to balance supply

and demand. This requires an additional need for flexible resources which can be used to meet

the increased variability of the system and react to forecast uncertainty (Holttinen et al., 2009).

This is not new – systems have always managed variability and uncertainty (El-Sharkawi,

2009); however, wind power increases the net load variability. Flexible resources already exist

in many systems: quick-acting dispatchable plant (such as open-cycle gas turbines (OCGTs)),

flexible demand (i.e. interruptible load programmes) and storage, particularly pumped

hydroelectric storage.

This chapter considers storage for power systemswith significant wind power generation, as

a possible option to better integrate large amounts of wind into the grid. First, the different

storage technologies and their main characteristics are examined. Then, the main uses of

storage to integrate wind are examined; storage can be used to manage variability, reduce the

need for transmission expansion, andmitigate short-term fluctuations, support system stability,

and ‘firm’ output from a wind plant. Some of these may not be complementary; others will be.

Additionally, somemay not be the best usage of storage. Examples are given of studies carried

out to assess the usage of storage to integratewind, and there is a discussion of the research that

needs to be done, both in terms of storage technology improvement to facilitate wider

deployment of the resource, and grid modelling to better represent some of the benefits

storage can bring to the electrical power grid.

21.2 Storage Technologies

This section examines the types of storage that could be used in combination with wind power

generation. Here, only electrical energy storage, where energy is taken from the grid and used

to charge a store, before being discharged later, is considered; gas storage and large hydro dams

Wind Power in Power Systems, Second Edition. Edited by Thomas Ackermann.� 2012 John Wiley & Sons, Ltd. Published 2012 by John Wiley & Sons, Ltd.

without pump-back facilities are not considered.1 In recent years, there has been much

development in newer forms of storage, or improving existing technologies. This, together

with increased wind penetrations worldwide, is causing an increase in the interest of using

storage technologies in the electrical grid. This subsection gives an overview of the different

storage technologies and how theymay be expected to contribute to a gridwith high amounts of

wind power. Figure 21.1 shows the possible applications for different storage technologies,

based on discharge time and system power. For integration of wind generation, power quality,

load shifting and bulk power management are the factors that are most important. At present,

many of the technologies are expensive and do not perform well enough in terms of efficiency

and lifetime to contribute significantly to grid support. Round-trip efficiency – that is, the ratio

of electricity in to electricity out over a cycle – is an important characteristic; better round-trip

efficiencies mean reduced losses and, therefore, more economic operation of the storage. For

many storage applications, the size of the charging unit (in megawatts) is similar to the size in

the discharge/generating unit.

21.2.1 Pumped Hydro Storage

This is by far the most mature of the main storage technologies, with over 90% of storage

installed worldwide being pumped hydro (Deane et al., 2010); in the developed world, most of

the geologically suitable, cost-effective sites have been developed. This technology operates by

pumping water into a reservoir when prices are low (e.g. wind generation is to be curtailed

in the case of high wind penetrations) and then generating when prices are high; in the case of

1 For a discussion of hydrogen storage, see Chapter 44.

Figure 21.1 Storage applications; acronyms are explained in text. Reproduced from Electric Energy

Storage Technology Options: AWhite Paper Primer on Applications, Costs and Benefits, Electric Power

Research Institute, PaloAlto, CA: 1020676, 2010with permission fromElectric Power Research Institute

466 Wind Power in Power Systems

non-market-based systems this would be done to reduce costs instead of price arbitrage.

Pumped storage can be a high-power (e.g. Bath County in the USA has an installed capacity of

2772MW), high-energy resource (can generate continuously for a number of hours), making it

particularly suitable to integrate wind variability on the hourly time frame, as well as support

the system with ancillary services. It can be used for arbitrage/variability and uncertainty

management, ancillary services, quick response times and more efficient operation of

conventional plant. In much of the developed world, pumped storage is already mature, to

the point that very little suitable geological features remain that could be used in this manner,

unless sites previously deemed unsuitable become more valuable due to an increased demand

for pumped storage. Pumped storage round-trip efficiencies of up to 80% can be achieved

(Electric Power Research Institute, 2010). Conventional pumps and turbines are used for the

pump and generator, and these can be variable or fixed speed; often, a reversible pump is used,

meaning the same (or approximately the same) sized pump and generator. Certain existing

hydropower facilities can be converted into pumped storage through the addition of pumps,

giving thempump-back facilities so they can be used as either conventional hydro generators or

pumped storage plants.

21.2.2 Compressed Air Energy Storage (CAES)

This technology uses the potential energy of compressed air to drive turbines. Air is pumped

into a suitable underground cavern (e.g. salt cavern) or manmade structure (above or below

ground). To extract the stored energy, compressed air is heated, expanded and directed through

a high-pressure turbine that captures some of the energy in the compressed air. The air is then

mixedwith fuel and combusted, with the exhaust expanded through a low-pressure gas turbine.

The turbines are connected to an electrical generator (Electric Power Research Institute, 2010).

This type of CAES utilizes a gas turbine; essentially, the expanded air is mixed with gas to

produce a highly efficient gas turbine. There are currently two facilities of this type in theworld:

in Huntorf, Germany (290MW, built in 1978), and Alabama, USA (110MW, built in 1991).

There are plans to buildmore (e.g. the 270MW Iowa Stored Energy Park), which promise to be

more efficient. Many possible CAES plant locations are in areas with high wind potential (e.g.

the US Midwest), meaning reduction in curtailment or deferral of transmission investment.

Research is also being done on adiabatic CAES, which would not need additional energy input

from natural gas, this becoming a pure storage unit. CAES has similar characteristics to

pumped storage in terms of what it offers the grid; that is, arbitrage/variability and uncertainty

management, ancillary services, quick response times and more efficient operation of

conventional plant. It also has the advantage of a separate compressor and generator, allowing

both to be sized independently.

21.2.3 Battery Storage

Battery storage encompasses many different technologies, mostly differentiated by different

chemical properties. These include lead–acid, nickel–cadmium, nickel–metal hydride, lith-

ium-ion, sodium–sulfur, and sodium–nickel chloride. These technologies vary in terms of

energy density, cost, efficiency and lifetime, but their main use is providing power for power

quality applications, short-term fluctuation reduction and some ancillary services or trans-

mission deferral. Some have higher energy density and can, therefore, also act over the longer

range time scale, as shown in Figure 21.1.Another type of battery, the ‘flow’ battery,which uses

Wind Power and Storage 467

a liquid electrolyte, is primarily made up of two different chemistries: vanadium redox and

zinc–bromine. These have higher energy density and, therefore, aremore suited to time shifting

or arbitrage, while still offering the benefits of other batteries in terms of very quick response.

Battery storageworldwide is continually improving in terms of efficiency, lifetime and costs

(Electric Power Research Institute, 2010). Currently, costs per kilowatt-hour are expensive

compared with thermal plant, or even pumped hydro or compressed air storage. In addition,

lifetime can be affected significantly by the cycling of batteries. Therefore, while they are

currently used in niche applications (to avoid certain transmission build outs in remote areas or

for power quality in weak grids), there has not been widespread deployment.

21.2.4 Flywheel

Flywheels store energy in a rotating mass; they typically have short discharge times, but can

ramp up very quickly, making them useful for power quality and frequency response. There are

currently several flywheels in operational or advanced planning stage (for example, a 20MW

flywheel system in the New York Independent System Operator footprint in the USA),

generally in areas where frequency or short-term markets are of high value (Electric Power

Research Institute, 2010). They are not suitable for longer term needs, such as management of

variability and uncertainty over longer (greater than 10min) time frames. They are also

commonly used in wind–diesel systems, and have been proposed to be used to better integrate

wind and solar photovoltaic (PV) in distribution networks.

21.3 Storage for Wind Integration

Wind power production tends to be variable and does not necessarily coincide with demand,

either at time of day or time of year (some systems tend to have higher wind during high-

demand seasons, others do not). Therefore, additional variability is introduced to the

balancing of supply and demand. While it is true that, when considered over a larger area,

the variability is decreased, there still remains some additional net load variability which

must be balanced, as discussed in the Preface and Chapter 6. Storage seems ideal to balance

this variability due to the fact that it can ramp up and down quickly, has a large range of

operation and can increase net demand as well as lower it, making it ideal to store energy at

times when wind is high but demand is low. It should be noted that storage is best utilized as

a system resource rather than employing a storage unit solely to smooth the output of a

single wind farm or small group of wind farms, as it is the net load (total demand minus

wind generation) which needs to be balanced on each system, rather than output from one

wind farm; this is limited by the amount of transmission available to transfer energy to and

from the storage and wind farms.

However, storage is both expensive and inefficient – generally, at least 20% (depending on

type of storage) of energy is lost in the round trip between charging and generatingwith storage.

Any new storage will either have to be pumped hydro in less-suited sites than those already

developed, or one of the newer storage technologies, which, with the possible exception of

CAES, are both expensive and inefficient. It is clear that, with more wind, storage becomes

more attractive; it is not clear, however, if the additional variability and uncertainty will justify

storage until very high penetrations are seen. This subsection first outlines the possible

applications storage could have in a high wind system; a literature review of current status

in regard to studies follows, together with greater detail on results from two studies.


21.3.1 Applications of Storage with High Wind

The following applications of storage can be seen to support integration of wind power.

Integration of wind power has been discussed in earlier chapters, from a system point of view

(listed here in order of the relevant time horizon):

. Long-term seasonal storage. For most regions, demand and wind are both seasonal. In

many, the time of year when wind is highest does not coincide with the time when load is

highest. Therefore, storage could potentially be utilized to bridge this gap, and move the

energy from a time when high winds are prevalent (i.e. in shoulder periods in spring and

autumn) to those times when it could be best utilized to reduce the need for the building

of new peaking units (i.e. summer in certain systems). However, the amount of storage (in

megawatt-hours) for this type of application would need to be extremely high to ensure

that there would be energy in store; this type of application is more relevant to gas storage

or large hydro reservoirs rather than the electrical energy storage of the kind discussed in

the previous subsection. This application would also compete with the daily arbitrage,

described next. The difference in wind output (as a percentage of total demand) would

have to vary quite significantly over multiple months to make this application worth-

while; for example, it would need to be worthwhile moving power from the summer to the

winter or vice versa. Alternatively, if the size of the store makes up a very small part of

capital costs (i.e. if megawatt-hours are very cheap to build compared with megawatts,

for example in a large hydro reservoir with pump-back storage facilities), this may be

attractive. Efficiency would also have to be maintained over a long period; that is, leakage

of energy would need to be very small.. Daily time shifting of output. Storage is used to ‘move’ wind power from times when it

is generated to times when it is better utilized from a system economic viewpoint. This is

similar to the previous application, except that here the time frame over which storage is

extends from a few hours to less than 2 weeks. This generally means storing energy (either

wind energy or cheap base load power) during the night, when net load is typically lowest and

using the following day when load is highest. It is best done from a system point of view, that

is, multiple benefits where, for example, storage is used to maintain conventional plant at a

more efficient output, and to reduce curtailment of wind power. For this to be effective, the

storage would need to be able to store and generate multiple hours’ worth of energy (i.e. the

total number of megawatt-hours which can be stored divided by the megawatts charging/

discharging capacity). Additionally, system operation would need to consider the usage of

storage, to ensure it is filling and emptying at opportune times. Large-scale bulk storage

connected to the transmission network would seem to be most useful for this type of

operation. It would be best utilized in any size of grid, as both small and large systems will

need this flexibility with high wind. However, small systems would likely see a greater need,

as demand and wind will be more variable and the smaller number of units on the system

would make it more difficult to balance supply and demand. On the other hand, larger

systems may have a large number of inflexible units which cannot be turned off for a short

time and, therefore, have a higher minimum demand above which curtailment occurs. This

curtailment reduction would be the major benefit if using storage instead of, say, a quick-

acting gas turbine. Essentially, this application is used to reduce balancing costs as discussed

in Chapter 17, which are generally described as the additional costs wind energy causes in a

system due to theway it affects operation of other units due to its variability and uncertainty;

see also for example Holttinen et al., 2009.


. Management of uncertainty. As wind power production cannot be perfectly forecast in

advance, there is a need for additional reserves to be carried to cater for this uncertainty.

These can be carried by conventional plant; however, with more wind generation on the

system, the costs of doing so by having more units online will become very expensive and

may increase emissions (Denny andO’Malley, 2006). Therefore, storage could be utilized to

ramp up quickly and carry these reserves, thereby letting the system operatemore efficiently.

Again, storage technologies that can offer power very quickly for time scales fromminutes to

approximately 6 h are those which would be suited to this.. Transmission curtailment reduction. Wind power is often located far from demand (e.g. in

the USA, the Midwest region has very good resources), but most demand is near the coasts;

therefore, large amounts of transmission will need to be built. This is expensive and often

encounters public opposition. Therefore, there may be wind curtailment due to the lines

being sized too small. This could be overcome by upgrading or building new transmission, or

by employing storage near the site of generation. In certain areas storage may be more

economical than building new transmission (or the only possible option if transmission

cannot be built). For this type of operation to be useful, storagewould again need to be large,

as energy may need to be stored for long periods of time; this is similar to seasonal storage

described above, but for a more specific purpose. The size of the storage relative to the wind

power and transmission linewill also be important – to best use this type of storage, thewind

plant and storage should be optimized together to ensure correct sizing. This application is

likely to be more useful in large systems or those where two separate markets operate, and

one has a highly variable price profile, which can be taken advantage of by the wind and

storage plant (Denholm and Sioshansi, 2009).. Reduction of (short-term) fluctuations/power quality support. Wind power plants often

fluctuate quite significantly on a shorter time scale than that examined for the time-shifting

purpose outlined above (i.e. in the seconds to minutes time scale), especially when

considered on a local level – when considered over a large area, this variation is smoothed

out. These fluctuations could cause significant issues, particularly if connected to weaker

parts of the transmission network or the distribution network. Reactive power provision and

voltage stability may be affected, as discussed in Chapter 38. Storage could be used to

smooth the outputs in wind power on these short time scales and, therefore, alleviate some of

these issues. In general, this type of operationwould be done by very quick storage units,with

less of an emphasis on the ability to store energy and more on the ability to produce power

quickly in both directions when needed. Therefore, different technologies may be used to

provide this service. Small-scale storage connected on the distribution network would be

most useful for this application, as it is generally a local issue, which is likely to be more

significant in smaller systems, where the dispersion of wind power is reduced and the effect

on the net load of wind variability is highest.. Grid frequency support. As discussed in Chapters 6 and 27, with high wind penetration

(>30% penetration by energy), maintaining inertia on the system becomes an important

issue for system operators (Mullane andO’Malley, 2005), due to the small or zero inertia that

wind plants will be able to offer (unless equipped with the relevant power electronics to

provide frequency response, as discussed inMiller et al., 2010). In systemswith wind power,

maintaining frequency after disturbances may become more difficult, as shown in Eir-

Grid, 2010. As conventional plant is generally backed off to provide the ancillary services

needed to maintain frequency, storage may offer this service, which would allow other plant

to either operate closer tomaximum efficiency or to be switched off. The quick response time

of storagewould then be utilized to provide ancillary services; there is also the likelihood that


very quick response storage (e.g. flywheels) may reduce the total demand for response, as it

can react quicker than conventional plant. Therefore, power on demand is most important

here, whereas the ability to maintain output for a relatively short (1 h or so) period of time is

also important. This is an area of active research, with research currently focusing on how

much of this type of response may be needed on a given electrical grid and how it can be

provided. The above applications of storage for integration of wind power can be seen to vary

over time scale, system size and location of storage on the network (i.e. transmission or

distribution connected, local to the plant or system connected). Therefore, different

technologies may be suitable for different applications, as described in the literature survey

later in the chapter. Certain technologies will be useful for all or most types of applications,

while others will only be useful for certain applications. In addition, while some of these

applications may complement each other (a storage unit providing time-shifting-type

support may also be good for frequency support, assuming very quick ramping periods),

others may compete against each other. For example, if a storage unit is used to reduce

transmission congestion or avoid upgrading or building new transmission, it may not also

be possible to use it to operate the system in a more efficient way for time shifting and

arbitrage, due to a possible presence of transmission congestion.

It can be seen from the applications described above that adding wind generation capacity to a

power system does not result in any new applications for storage; rather, it increases the

possibleways storage can justify itself in the grid. For example, time shiftingwould always be a

benefit of building storage (to shift nuclear power from night to day, for example), butwith high

wind generation the value of this application may be increased. Therefore, storage needs to be

considered in this context – as an additional flexible resource which can bring many benefits to

integration ofwind power, but not as a necessary resource to integratewind power. Storage, like

other enabling technologies, will have to be justified by improving system economics,

reliability or environmental performance.

21.3.2 Integration of Wind Generation with Storage: Literature Review

Storage is an expensive system resource and, therefore, needs to be properly analysed before

it is installed on systems; the benefits it can bring should outweigh the cost, whether from an

operational cost, reliability or environmental perspective, or a mixture of these. In the past

decade, there have been ample studies done examining the possibilities of using storage

technologies with wind power. Much of this has concentrated on using wind generation from

one wind power plant and maximizing profits for the wind power plant owner by utilizing

storage to provide a controllable form of generation; for example, see Garcia-Gonzalez

et al., 2008, Castronuovo and Lopes, 2004 and Brown et al., 2008. However, as mentioned

above, when examined from a system point of view, this method of utilizing storage may

not provide the maximum benefit that can be achieved from a storage source – to achieve

the maximum benefit to the system; the storage should be operated most economically for

the system.

Other studies have concentrated on the impact of storage on the power system in general.

Most of this type of research has focused on the likelihood of endogenous investment in storage

compared with other types of plant, normally combined-cycle gas turbines (CCGTs). Sullivan

et al., 2008 examined the US system and found that storage can lead to more installed wind

power capacity once there is enough wind power capacity on the grid to make its flexibility


sufficiently valuable. Swider, 2007 examined the addition of compressed air energy storage

(CAES) to the system using an endogenous investment model. This showed that, at certain

levels of wind power generation and certain capital costs, CAES can be economic in Germany

for large-scalewind power deployment, taking into account thevariable and uncertain nature of

wind. Meibom et al., 2007 and Kiviluoma and Meibom, 2010 show the benefits of using

thermal storage for wind integration, while Mathiesen and Lund, 2009 examine various

technologies for wind integration, showing that thermal storage can be very useful. Ummels

et al., 2008 examined the effect of storage on system operation in the Netherlands. It was found

that, though storage becamemore viable for the systemwith increasing levels of wind power, it

never proved to be the best option for the system examined. Further studies have also been

carried out to value storage in different regions. The results are shown to be somewhat

dependent on the given system. Loisel et al., 2010 also show an increased value for storage as

wind-generation levels increase in systems – they examined systems from 2010 to 2030. It

shows that value of storage depends on price spread and the region being examined. It was

shown that storage is more valuable in Germany than in France, and CAES is seen to be more

valuable than pumped hydro storage, mainly due to different investment costs – the net present

value (NPV) of CAES is positive in Germany by approximately 2016. This is due to a higher

penetration of variable generation in Germany. Papathanassiou and Boulaxis, 2006 examined

the operation of storage on island grids and show that storage makes a valuable contribution to

Greek islands with high wind power penetration.

Most work can, therefore, be seen to value the usage of storage for arbitrage. Other work has

concentrated on the benefit storage provides in relieving transmission congestion, as shown by

Denholm and Sioshansi, 2009: here, storage is seen to reduce curtailment, and the value of

storage compared with additional transmission is assessed. It is shown that in regions where

transmission may be expensive, this may be an option, but in general the value from storage is

not enough to justify its costs. As discussed later, markets and modelling tools may not give

proper value at present to using storage to balance out short-term variation and uncertainty in

wind power. Whether such applications will be deployed will depend on capital costs, cycle

efficiency and likely utilization (Chen et al., 2009).

As indicated above, the broad range of services provided by storage and the differences

between systems in terms of plant mix, size and variability of present or future wind power

mean that evaluation of the levels of storage which can be justified is difficult. There is no one

answer for the question ‘How much (if any) storage is justified on the grounds of net benefits

for a given megawatt of wind?’ In general, larger systems see less benefit from storage, and

increased wind penetration levels increase the value storage can bring to the system. The

efficiency of storage and the price spread (a function of the plantmix and operational costs) for

various regions are also important drivers of storage value. Multiple studies have been

conducted to examine systems with high wind penetrations; some of these are described in

Chapters 17–20. In these grid integration studies, which examine dramatically increased

installed wind compared with today, there is generally very little additional storage added;

indeed, most do not add anymore storage and the system is still projected to operate in a stable

and reliable fashion. Curtailment, even at these levels, is generally not high enough to justify

building additional storage (note that some of these studies may underestimate curtailment

due to an overoptimistic minimum generation level, underestimation of reserve needs or lack

of consideration of cycling costs). In addition, wind power increases the need for ancillary

services, but these increases can be met by conventional plant turned down from maximum

level without too much of a decrease in efficiency, or by additional flexible generation such as

OCGTs. Institutional practices to increase flexibility, such as increased consolidation or


cooperation between different balancing areas, better usage of forecasting and shorter

dispatch intervals, are often assumed to add additional flexibility to integrate wind power

in these studies.

21.4 Studies on Operation of Storage in Systems with High WindPenetration

If storage is not justified (or at least seen not to be bring net benefitswhen doing these studies) at

the levels examined in the integration studies, which are relatively high (i.e. 20% of energy in

the major US studies, or up to 40% of energy in the study for Ireland), when does it become a

more beneficial resource than additional conventional plant? It seems clear that a power system

with, for example, 100% wind penetration would be very inefficient without some storage, as

curtailment for a system would be very high without storage (assuming no interconnection or

extreme demand-sidemanagement). The incremental energy from onemoremegawatt of wind

would be so small as to not beworth building. Therefore, at these levels, storagewould seem to

make sense (in addition, demand response could also be used). This section of the chapter tries

to address the issue of when storage becomes justifiable for a power system with high installed

wind capacity, and examines the reasons behind the results. Two studies performed to analyse

the impact of storage in high wind systems are summarized. It is shown that the main driver of

installing storage should be a reduction in operating costswhich outweighs the capital costs and

inefficiencies associated with storage. This reduction in costs is driven by a reduction in

curtailment through the addition of storage.Detailed results are shown froma study on the 2020

Irish system (Tuohy andO’Malley, 2011). These are then comparedwith results froma separate

similar study on the Electric Reliability Council of Texas (ERCOT) system, performed by the

National Renewable Energy Laboratory (Denholm and Hand, 2011).

To justify the building of storage on economic terms, the Irish system in 2020 was examined

with high levels ofwind power (Tuohy andO’Malley, 2011). The Irish system currently obtains

approximately 11% of electricity generated from wind power; as a synchronous system, this is

one of the highest in the world (the Island of Crete is 15%), and the island has seen times when

instantaneous penetration has reached 50% of electricity demand. The island of Ireland,

operated as a single electricity market since 2007, and is only connected to Great Britain (GB)

through a 500MW DC interconnection. It is therefore a good test system to analyse storage

operation with high wind penetration. Current targets are for approximately 40% of energy to

come from renewable energy (34% fromwind) by 2020. Ireland currently relies heavily on fuel

imports, mainly gas and coal (62% electricity from gas in 2010). Apart from wind power, peat

energy is the other indigenous fuel, with only 343MW of installed capacity (Tuohy

et al., 2009). Security of supply is therefore a significant issue; adding storage to accommodate

wind power may increase the security of supply – however, the increased costs of doing this

need to be analysed in the context of the system as a whole.

This study utilized a stochastic unit commitment and economic dispatch tool (theWILMAR

model) to investigate the operation of a pumped hydro storage unit on the Irish system in 2020.

This study has an hourly resolution; so, as described previously, the main usage of storage that

is investigated is the application of storage for time shifting of wind output. As described later,

capturing the full value of further applications has not been covered in great detail in these types

of studies and needsmorework.Many studies, as examined inChapters 17–20, have shown that

the main effect of increased wind is on this time scale, in terms of increased reserves and

changed economic dispatch, at least until very high wind penetration levels start causing


stability issues (EirGrid, 2010). Therefore, this is the time scale of most interest in terms of

using storage to reduce integration costs.

The All Island Grid (AIGS) Study Portfolio 5, slightly modified (see below), was used as a

base case (Ecofys, 2008). This has 6GW of wind installed (currently about 1.5 GW) and a

peak demand of 9.6 GW. Interconnection to GB is assumed to be 1GW (currently it is

500MW). Fuel prices and data on conventional plant are taken from Ecofys, 2008. Carbon

price of D30/t is assumed (sensitivities are carried out on this). The base system (which is

assumed to have no storage – existing storage in Ireland is removed) was changed in twomain

ways: addition of storage and addition of wind generation. First, storage is added by removing

conventional plant such that the reliability of the system stays the same, or at least close to the

assumed reliability in the base case (8 h loss of load expectation). In the simulations carried

out here, 500MWof storage is assumed to replace 500MWof conventional plant in the future

plantmix. As the Irish system ismainly gas based, and only gas plants andwind generation are

expected to be built between now and 2020, the choices are to replace either a CCGT or

OCGTs. For most of the studies, a combination of A 103MW OCGT unit and A 400MW

CCGT unit are chosen to be replaced. Two methods of unit commitment and economic

dispatch are assumed. The first assumes wind power production to be perfectly forecastable;

this gives the best case for system production costs, but is unrealistic as it does not consider

uncertainty. The other method used was a stochastic optimization; this is based on the model

described inMeibom et al., 2011 andTuohy andO’Malley, 2009, which optimizes units based

on weighted scenarios of forecasted wind generation and load for each optimization period.

This is shown in Tuohy and O’Malley, 2009 to give the lowest production costs when wind

forecast uncertainty is included. Compared with the casewith perfect foresight, it should give

more realistic results for usage of storage, as the uncertainty of wind power should imply

greater usage of storage due to its flexibility.

The efficiency of the storage is assumed to be 78% (based on numbers of newer pumped

storage efficiencies). It has 10 h of energy storage (i.e. 5 GWh), which is on the high side of how

much energy is generally provided in new pumped hydro units – current Irish pumped storage

has 5 h of energy. While the results here are most suited to pumped hydro, CAES, battery or

flywheel storage with a similar amount of energy would perform the sameway; pumped hydro

is considered to be the most economic technology to have such a large storage capacity. This

storage unit was added to the system for five different levels of installedwind capacity, from the

base case of 6GW to 12GW, in 1.5 GW steps. If nowind generation were curtailed, this would

provide 34–68%of energy (i.e. current 2020 target to double this, assuming no additional losses

and similar high-capacity-factor wind sites). As with storage, when wind generation is added,

other units are removed to ensure reliability is maintained. This is done by using the capacity

credit of wind generation, taken from previous work done (Doherty et al., 2006) and

extrapolated to higher levels of wind capacity. As wind capacity increases, the incremental

capacity credit decreases (Keane et al., 2011a), so that the amount ofmegawattswhich could be

removed at 12GWof wind generation is significantly less than that which can be removed at

6GW. More details on the methodology used are given in Tuohy and O’Malley, 2011.

21.4.1 Curtailment

The main advantage of using storage, from a wind integration perspective, is that it reduces

curtailment. Curtailment levels in a system are mainly based on the minimum generation

level of the system. Wind energy is only partly dispatchable (it can be dispatched down but

needs to be curtailed before being able to be dispatched up) and does not contribute inertia


(recent developments show that wind turbines may be able to provide inertia through power

electronics – this is assumed not to be used in this study). This will mean there needs to be a

minimum number of large conventional generating units online, to provide flexibility tomeet

changes inwind output and ensure sufficient system inertia. Therefore, curtailmentwill occur

when the wind generation is greater than demand, less the minimum generation level of the

system (as defined by minimum number of conventional generators online), plus any export

capacity from the system. Curtailment due to transmission congestion is not examined here;

the systemmodelled does not include the transmission system for Ireland (a similar approach

is taken in scheduling generation in the Irish market).

Figure 21.2 shows the curtailment of wind power versus the penetration of wind (by energy)

for the system. Here, the difference between storage and no storage cases is seen to increase as

wind penetration increases. As stated previously, 34% of energy corresponds to 6GWinstalled

wind, while 68%would correspond to 12GWif all wind capacity could be used; as can be seen,

12GW only ends up with approximately 57% of energy from wind if there is no storage.

Storage can be seen to reduce curtailment significantly. Figure 21.2 implies that it would to be

difficult in practice for the system to reach greater than 60% of annual energy from wind

generation without storage or very high levels of wind installed. This would be expected, as

wind is as likely to be high during the night when it would bewasted at high installed levels. As

can be seen, assuming perfect foresight underestimates the curtailment of wind power – the

curtailment shown for stochastic results is more realistic, as they include wind power

uncertainty. This shows the importance of including wind power uncertainty when assessing

the usage of curtailment – storage is seen as being more beneficial when wind power

uncertainty is included. Curtailment is very low at lower installed wind levels; this is due

to the fact that the Irish system is already flexible, due to its status as an island system. The

simulations were also carried out for an increased carbon price – this did not significantly

change curtailment levels.

Figure 21.2 Curtailment of wind power versus wind energy penetration, for stochastic and perfect

foresight assumptions. Curves (top to bottom) are stochasticwith andwithout storage and perfectwith and

without storage


Figure 21.3 shows the amount of additional installed wind generation needed in the system

examined, if there were no storage, to reach a given penetration level. This means that, for

example, to reach 50% penetration, an additional 200MW of installed wind is needed if no

storage is present on the system. It could be seen that, at low penetration targets, similar

amounts of installedwind are needed regardless ofwhether the systemhas storage; it is not until

higher levels of penetration that storage will reduce the amount needed for a given target.

A similar study to that performed herewas performed by theUSNational Renewable Energy

Laboratory (Denholm and Hand, 2011). This examined the ERCOT system with high

penetration of variable renewables (wind and solar PV) to analyse curtailment levels.

Compared with the Irish system, ERCOT is far larger (peak demand of 65GW versus

approximately 10GW in the Irish 2020 system examined here). Additionally, the wind in

Texas is higher on average during the night, compared with during the day for the Irish system;

this will make it somewhat more difficult to integrate efficiently. A significant concept

examined in their work relates to the minimum turn-down generation level of the system,

termed system flexibility here. This relates to the minimum turn-down level of the system; for

example, 80% flexibility indicates that the system can generate at 20% of maximum demand.

This is a simple way to capture system flexibility, without needing the detailed unit

commitment and economic dispatch modelling as used in the Irish study examined. If

maximum demand is 10GW, curtailment will only start happening if wind generation is

greater than 2GW over demand; 100% system flexibility means curtailment only starts

happening when wind is greater than demand. Figure 21.4 shows curtailment for different

flexibilities, as a percentage of wind power, for different penetration levels. This should be

compared with Figure 21.2 to show difference with the Irish system examined above. It can be

seen by comparingwith Figure 21.2 that the Irish systemexamined above is similar to the 100%

flexibility curve, with lower curtailment than seen in Figure 21.4 for the lower flexibility

situations; that is, those when flexibility is assumed less than 100%. This is expected, as the

Irish system is relatively flexible,withmanyunits able to operate significantly belowmaximum

generation; additionally, the Irish system has higher averagewind output during the day instead

of at night as in the ERCOT system.

Figure 21.3 Additional wind capacity required to meet given penetration levels when no storage is

present, compared with a case when 500MW/10 h storage is present


As can be seen in Figure 21.4, the amount of flexibility in terms of how far the system can

turn down conventional plant is very significant for reducing curtailment. Figure 21.5 shows

the level of curtailment for different hours of energy storage for different penetrations of

variable generation, with an assumption of 100% system flexibility. The addition of storage

can be seen to improve results beyond those seen by decreasing theminimum turn-down level

of the system.

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

80%70%60%50%40%30%20%10%0%

Fraction of System Electricity from Wind

Fra

ctio

n o

f W

ind

Gen

erat

ion

Cu

rtai

led

80% flexiblity (12 GW min load)

90% flexibility (6 GW min load)

100% flexibility (0 min load)

Figure 21.4 Curtailment for different ERCOT ‘system flexibilities’, with no storage. Curves (top to

bottom) are for 80%, 90% and 100% flexibility. Reproduced from Denholm and Hand (2011), with

permission from Elsevier

0%

5%

10%

15%

20%

25%

30%

35%

40%

80%70%60%50%40%30%20%

Fraction of System Electricity from Wind&Solar

Fra

ctio

n o

f V

G C

urt

aile

d

No Storage

4 hours

8 hours

12 hours

24 hours

Figure 21.5 Curtailment levels for ERCOT; different levels of energy of storage. Curves (top to bottom)

are for no storage, 4 h, 8 h, 12 h and 24 h of storage. Reproduced from Denholm and Hand (2011), with



It can be seen in Figure 21.5 that storage does not significantly help until levels above

approximately 45% of energy are reached; this is again consistent with results shown above in

Figure 21.2, suggesting that results for the Irish system examined are similar to those seen for

the ERCOT system with an assumption of 100% flexibility. This 100% flexibility would likely

not be possible due to lack of inertia in the system and other stability reasons, indicating storage

could bemore useful in the ERCOT system in reducing curtailment; this would be expected in a

system which has higher average wind output at night.

21.4.2 Costs

The above results give the amount of curtailment when the system is simulated with or without

storage. The system operating costs for these different cases are examined to find the effect of

storage in terms of its ability to change system costs; this is only done for the Irish system.

Figure 21.6 shows the annual cost savings from the addition of storage.Note that these are given

for installed wind levels as opposed to penetration; 6GW here would be 34% penetration, as

shown earlier if no wind production is curtailed.

It can be seen that operating costs are actually increased at lower levels of installed

wind power. This increase is even greater if carbon prices are increased, as increased carbon

prices put less flexible coal power on the margin. At higher levels of installed wind capacity,

carbon price makes less difference in terms of cost savings for storage at a given installed

wind level. As wind installed is increased, storage reduces costs. As wind energy would

otherwise have been curtailed, this reduces system operating costs above a certain level of

installed wind – this reduction is therefore greater than the increase in fuel consumption.

Storage can be seen to reduce operating cost less if perfect foresight is assumed. This is due to

the fact that, with perfect foresight of wind generation assumed, wind is less likely to need to

be curtailed and, therefore, the possible cost savings due to curtailment are lower. This also

shows the benefit that the flexibility of storage can bring to system – storage is flexible enough

to deal with the uncertainty of wind forecasting and, therefore, can help reduce costs on the

system. The cost savings seen in Figure 21.6 are used to assess the NPV of storage for

different installed levels of wind. This is given in Figure 21.7 for stochastic and perfect

foresight assumptions at D30/tonne, and an assumed lifetime of 20 years for storage, or the

unit it replaces.

Figure 21.6 Operating cost savings from500MW/10 h storage versus casewith no storage. Reproduced

from O’Malley and Tuohy (2011), with permission from Elsevier


As expected, lower discount rates make the additional justified costs higher for a given

installedwind capacity. However, it does not have a very significant impact on results until very

high penetration levels are reached. Figure 21.7 can be used to examine the additional costs

which can be justified for a given installed wind level. For example, at 9GWof installed wind,

approximatelyD220k/MW toD300k/MWadditional cost can be justified for storage, with 10 h

of energy store. Therefore, if CCGTs cost, for example,D600k/MW, the 10 h storage could cost

up to D900k/MW to be justified; this is lower than current estimates of nearly D1500k/MW.

The above results are given for an assumed lifetime of 20 years for both storage and the unit

it replaces. In reality, pumped hydro storage would have a longer lifetime. If 40 years

operational lifetime is assumed for storage and 20 years for a CCGT, then storage would still

be assumed to have a value after 20 years, when a CCGT would not. If a longer lifetime is

assumed, the breakeven point would occur at a lower justified cost. For example, if only

D250k were needed to be justified, then it would occur at 8.5–9 GW of installed wind in

Figure 21.7. This is lower than if longer lifetime is not considered, but still represents a very

high level of installed wind. While carbon and financing costs will impact the level, it can be

seen that they do not significantly affect the area where justification of storage is possible.

These results are not exact, but rather indicative of where storage is likely to be justifiable.

Based on current costs of storage, capital and carbon, it is likely to be between 7.5 and 11GW

in the assumed 2020 Irish system. This gives awide range, but it is also notable that it is higher

than current projections for installed wind in Ireland in 2020 and, indeed, higher than most

systems worldwide. This indicates that storage will be useful beyond 2020 in Ireland, but

possibly not justifiable in many cases before this time frame. This analysis also does not

account for existing storage in Ireland; if this were included, justification for new storage of

this size would be at even higher levels, as existing storage would already give many of the

benefits of storage for the system.

If the numbers in Figures 21.2 and 21.7 are taken as a guide, when storage is justified at

approximately 9–10GW, or 8% curtailment, then this level of curtailment is seen to happen

between 30 and 50% penetration in Figure 21.4 for the ERCOT system, indicating some

Figure 21.7 Justified capital costs for different installed wind levels. Reproduced from O’Malley and

Tuohy (2011), with permission from Elsevier


consistency in results in the two systems – the Irish system is most similar to the 100% flexible

case in Figure 21.4; thismay be due to different wind and load patterns in Ireland, wherewind is

more likely to be coincident with peak demand than in Texas.

Figure 21.8 shows the total operating costs (fuel and carbon) for increasingwind penetration,

with and without storage. This result may seem surprising, as storage actually increases costs

for a given penetration. However, it should be noted that this penetration level is calculated as

net wind generated as a percentage of total energy requirements, after curtailment is accounted

for. Therefore, installedwind capacitywill be different in the caseswith andwithout storage for

the same penetration. For example, at 50% penetration, 200MWof additional wind capacity is

installed, as shown earlier in Figure 21.3. The increase in cost reflects the fact that, though

storage can allow wind energy penetration to increase for a given installed level, it also has

inefficiencies in charging and generating which mean that there are increased costs for the

system. This is due to the fact that, though stored wind energy is free, other resources will also

be stored and there will be losses here. If storage were added to the system instead of replacing

CCGTs/OCGTs in the plantmix, this would not be the case and operating costs would decrease

for a given penetration. However, this would then mean that capacity savings could not be

considered; that is, storage would have to justify a far higher capital cost. Therefore, when

considering storage from an energy penetration point of view, as opposed to an installed wind

capacity point of view, the benefits it gives are in terms of reduction ofwind needed, as opposed

to operating costs. This is a different method of viewing results compared with the installed

wind capacity shown above; using thismethodmakes it easier to related results to other systems

and wind penetration targets. The data used above can be combined with that of Figure 21.3 to

examine the penetration levels at which storage is justified. This is given in Figure 21.9.

The numbers shown here are calculated by adding the savings from installed wind in

Figure 21.3 to the costs of not building the CCGTs/OCGTs and then subtracting the additional

operating costs and the capital costs of storage, while considering storage has a longer lifetime.

ACCGT lifetime of 20 years is assumed, 15 years forwind turbines and 30 years for storage and

an 8% discount rate is used for the numbers shown; this is therefore approximate and subject to

change for different parameter assumptions. However, it shows that the NPV only becomes

positive at 51% energy penetration, which is in the higher range from the justified costs by

installed wind capacity examined earlier.

Figure 21.8 Operating costs bywind penetration versuswind penetration, after curtailment is taken into

account; stochastic case


21.4.3 Operation of Storage and Effects on System

Another result worth noting from the Irish study is the change in operation seen aswind levels

are increased in the system. As explained earlier, storage is used here to reduce system

operating costs over each unit commitment period. Therefore, it will be operated to reduce

overall system costs; this will mean balancing wind, meeting peak demand, keeping other

units at their most efficient levels and reducing the difference in costs between peak and low

demands. Figures 21.10 and 21.11 respectively show average generation and average

charging by hour of day. Also included is average demand; average wind speed in Ireland

is almost the same throughout the day, with a slightly higher average output in the early

afternoon, so is not shown.

The operation of storage in Figures 21.10 and 21.11 gives some idea of why the value of

storage cannot be seen to justify its cost until high levels of wind capacity are reached. While

the difference between 12GW and 6GW shows storage operation becomes more driven by

wind generation, it is still clear that load is the main driver of storage operation. Therefore, it

will still be difficult to justify building storage until high levels of wind capacity are reached.

Storage still generates near-peak demand and charges at minimum demand; generation

increases at night with wind and charging increases during the day, but it is clear that storage

is driven by load in most days. As wind is incrementally free, it is better to use it when

–200

–100

0

100

200

300

400

500

5655545352515049

Penetration Level

Net

sav

ing

s (€

m)

Figure 21.9 NPV of savings of installed wind capacity and fuel by penetration; stochastic case

Figure 21.10 Average generation by hour of day from 500MW storage for different levels of wind

power – average demand by hour also shown. Reproduced from O’Malley and Tuohy (2011), with



generated, rather than store it and, therefore, incur inefficiencies (as is the case with using

storage in systems with lower levels or nowind – only if total costs decrease over the period of

optimization should the storage be used). This is obviously not the case when wind would

otherwise be curtailed, which is the reason for the change in operation at higher wind levels.

Additionally, there may be times when it is better to store or curtail wind energy than turn off

units (or turn down to inefficient minimum generation levels) and, therefore, storage could be

used here.

One of the reasons wind power is increasing worldwide is that it is a good way to reduce

emissions. Therefore, the Irish study also examined the change in carbon emissions for the

entire system modelled (GB and Ireland); this is given in Figure 21.12. CO2 is assumed to cost

D30/tonne in the model.

As can be seen in the figure, CO2 is actually increased when storage is added to the system;

this is due to the fact that storage, while aiding wind integration in terms of balancing and

reduction in curtailment, also makes better usage of inflexible coal units, particularly in GB,

which is then imported through the 1GW interconnection. As these can now be run at more

efficient levels, and do not need to be ramped down or switched off, CO2 is increased.

Additionally, the losses in the storage unit mean that storage can add emissions – that is, for

every 1MWh put into storage, only 0.78MWh comes out, and therefore the need for more fuel

Figure 21.11 Average charging by hour of day from500MWstorage for different levels ofwind power –

average demand by hour also shown. Reproduced from O’Malley and Tuohy (2011), with permission

from Elsevier

Figure 21.12 Change in CO2 emissions when storage added to system. Reproduced fromO’Malley and

Tuohy (2011), with permission from Elsevier


to get 1MWh than the CCGT storage is assumed to replace in this study. It is not until over

11GWof wind (over 62% penetration if wind is not curtailed) that storage actually decreases

CO2 emissions from the system, by reducing curtailment sufficiently.

Numerous sensitivities were run for this system. Here, we show one of these, based on the

units storage replaces in the plant mix, given in Figure 21.13.

Figure 21.13 shows the cost savings if storage replaces OCGTs (5� 103MW) instead of

the units assumed earlier (1� 400MW CCGT and 1� 103MW OCGT). As can be seen,

replacing the less efficient OCGTs saves more operating costs than CCGTs. This would be

expected as the OCGTs are the more flexible units, and replacing those should give more

value to the storage unit. However, Ireland is currently building both CCGTs and OCGTs,

meaning both could be considered. These cost savings would then be used with the same

method as shown earlier, to find NPV of storage savings, and therefore show the cost per

megawatt, for storage with 10 h energy, that storage needs to be lower than for a given

penetration to justify its building. Clearly, there are larger savings; however, it should also be

noted that OCGTs have a lower capital cost; therefore, the total cost that storage justifies

(which is equal to the cost of the unit it replaces plus the NPVof operating cost savings) may

be lower. So, storage justifying itself at, say,D400k/MWwhen replacing CCGTwould imply

aD1.05M/MWcapital cost of storage; this would be the equivalent of storage justifying itself

at D550k/MW if replacing OCGTs, as OCGTs would have a capital cost of D500k/MW

versus D650k/MW for CCGTs.

21.5 Discussion

The concept discussed inDenholm andHand, 2011 – that of systemflexibility – can be seen to

be the main factor in assessing the value of storage. For those systems with low flexibility,

storage will prove more valuable when integrating wind than other technologies such as

OCGTs or CCGTs. Flexibility can be seen to be dependent on existing plant mix, but also on

other resources such as demand response, interconnection to other areas and storage, as well

as the usage of these resources. The first aspect of the results to note is the fact that this work

does not examine portfolio optimization (Awerbuch, 2006); it assumes a direct choice

between storage and conventional plant. It is assumed that the wind capacity is built and then

Figure 21.13 Cost savings for storage replacing five OCGTS instead of one CCGT and one OCGT.

Reproduced from O’Malley and Tuohy (2011), with permission from Elsevier


operation of the system with and without storage is examined. This would obviously not be

the case in reality, with other flexible options, such as demand-side management, increased

interconnection with other systems, widespread deployment of electric vehicles and flexible

heat load, also being possible (Kiviluoma andMeibom, 2010). These all offer similar benefits

as storage in reducing curtailment and operating base-loaded units more effectively. A full

study would need to look at portfolio optimization while also incorporating flexible

resources, the need for flexibility and curtailment from variable generation; this would

require a tool which examines portfolio optimization and system operation together, and

which considers market impacts, operational impacts, forecasting, demand response,

stability, etc. In place of this, studies such as this one show benefits in terms of operational

fuel and carbon costs.

As gas is generally the unit on themargin in the system studied here (andmany other systems

worldwide), higher gas prices would have some impact, but it would not be expected to

significantly affect results. The difference between on peak and off peak would grow in

absolute terms, so there would be a slight advantage in storage, but not significantly different

unless prices changed dramatically. Themarginal cost difference between OCGTs and CCGTs

would increase, as would the difference betweenwindwhen on themargin and gas. As systems

do start to reach the penetration levels studied here, other aspects of system operation, such as

frequency and voltage stability as examined elsewhere in the book, may become significant

enough to hinder the growth of wind penetration (EirGrid, 2010). The levels at which storage

can be justified may be different for other systems, but are likely to still be dependent on

curtailment levels. There is also no examination here for the profitability of the storage unit –

this would be influenced by other aspects, such as market structure and transmission

infrastructure. The benefits storage provides versus conventional plant in terms of ancillary

services (due to shorter start-up time) are also not examined here, as this model is limited to

hourly resolution.

The Irish study does not examine transmission congestion relief (or transmission expansion

deferral) from storage, nor does it examine the very short-term (less than 5min) fluctuations –

reserve here is only planned to be available in the hour ahead time frame; its actual deployment

is not modelled. Therefore, the results would not be applicable everywhere, which is consistent

with the literature in this area. It will depend on system flexibility, plant mix and variability of

generation. However, it can be seen that justification at levels of energy below 20% would be

unlikely for all but the smallest island systems, while over 50% storage should be justifiable in

most systems. For example, on some Greek islands (e.g. Crete) wind power production is not

allowed go over 30–40% and is regularly curtailed. The system operator has specific concerns

about both frequency regulation and stability, and hence they implement strict penetration

limits (Katsaprakakis et al., 2007; Caralis and Zervos, 2007a). These curtailments have

stimulated interest in installing storage in Crete, which currently gets 15% of its electricity

from wind power (Caralis and Zervos, 2007b).

While transmission congestion and system flexibility will impact on the results seen

previously, and improve the justification for storage, theywill not do so dramatically. However,

other applications of storage for integration of wind will also be of value. In particular, battery

and flywheel storage, whichwill tend to be smaller in size (both energy and power) will provide

value in smoothing out short-termfluctuations. Themodels used in the studies described above,

and in general in the literature review, tend to reflect current market practices. This mainly

looks at committing and dispatching conventional resources on an hourly time frame; some

markets have 5min resolution (i.e. dispatches), but this is not reflected here – it would be

expected that these types of markets would benefit storage. Short-term storage technologies,


like batteries, generally have very quick response times (quicker than conventional plant or

pumped hydro storage), as described earlier. Therefore, these can be a very useful resource for

integration of wind, particularly in local distribution networks or in isolated grids (Delille

et al., 2010). The need for frequency response from other plant can be reduced, so this provides

value to the system. Coupled with demonstration programmes, market rules and tariffs are

gradually being introduced to incentivize the participation of new technologies (Lazarewicz

and Ryan, 2010; Rodriguez, 2010). Battery technology is an area of active research, with costs,

efficiencies and other factors, such as lifetime, being improved continuously (Electric Power

Research Institute, 2010).

21.6 Conclusions

This chapter gives an overview of the use of storage to integrate large amounts of wind

generation. Technologies for electrical energy storage are outlined; it is shown that pumped

hydro storage is currently the main storage technology. Development of CAES, battery and

flywheel storage is ongoing to improve costs, efficiency and other characteristics. The chapter

then examines applications of storage to integrate wind power. The main current usage of

storage is for energy arbitrage, peak shaving and to delay transmission build. For battery and

flywheel storage, the shorter duration for discharge means they are not as suitable for these as

pumped hydro and CAES are, and may be more suited to other applications, including

balancing of short-term fluctuations and grid support. The modelling, technology and market

developments required to ensure these types of applications are properly valued are described

in this chapter.

Themajor section in this chapter examines, first, the literature and then describes in detail the

results from a study on the Irish system to evaluate the use of storage to integrate wind. This is

compared with the results of a similar study in the USA. It is shown that, when examined on an

hourly basis, while consideringwind power uncertainty, themain benefits of storage seem to be

curtailment reduction and the fact that it allows base-load units to cycle less tomeetwind power

variability. This results in operating cost savings; when these are examined to find the level at

which the building of storage is justified, it is shown that very significant levels of wind

generation are required, in excess of 40% penetration by energy. It should be noted that storage

will also compete with other flexible technologies, such as demand response (Keane

et al., 2011b), conventional flexible gas or hydro units and increased transmission between

systems (Denny et al., 2010). The point at which storage becomes more justifiable than other

technologies will depend on the given system, based on its existing flexibility, the character-

istics of the resource and market operation.

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wind power in power systems (ackermann/wind power in power systems) || wind power and storage

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