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Energy 41 (2012) 483e490

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Energy

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A GIS-based model to calculate the potential for transforming conventionalhydropower schemes and non-hydro reservoirs to pumped hydropower schemes

Niall Fitzgerald a,1, Roberto Lacal Arántegui b,*, Eamon McKeogh a,c, Paul Leahy a,c

a Sustainable Energy Research Group, School of Engineering, University College Cork, Irelandb Institute for Energy and Transport, Joint Research Centre, Westerduinweg 3, NL-1755 LE Petten, The NetherlandscUniversity College Cork, Beaufort Laboratory, Ringaskiddy, Co. Cork, Ireland

a r t i c l e i n f o

Article history:Received 13 August 2011Received in revised form7 February 2012Accepted 19 February 2012Available online 22 March 2012

Keywords:Energy storageGeographical information systemsTurkeyRenewable energyDamsHydropower

Abbreviations: AMSL, (elevation) above mean sea lInformation on the Environment; CLC, CORINE Land CModel; DSI, General Directorate of State HydraGeographical information system; GRanD, Global ReICOLD, International Commission on Large Dams; Pstorage; SRTM, Shuttle Radar Topography MissionEducational, Scientific and Cultural Organisation.* Corresponding author. Tel.: þ31 224 565390; fax:

E-mail addresses: fitzgerald.niall@googlemail.comarantegui@ec.europa.eu (R. Lacal Arántegui), e.mckpaul.leahy@ucc.ie (P. Leahy).

1 Present address: Nualight Europe, Cork Business PIreland.

0360-5442/$ e see front matter � 2012 Elsevier Ltd.doi:10.1016/j.energy.2012.02.044

a b s t r a c t

The substantial increase in power generation from variable renewable sources has led to renewedinterest in energy storage. Pumped hydropower remains the only mature and widely-adopted utility-scale energy storage technology. However, the selection and development of new pumped hydropowersites is heavily influenced by physical constraints such as terrain, as well as non-physical considerationssuch as the proximity of proposed reservoirs to settlements or environmentally or culturally sensitivesites. Hence, transforming existing reservoirs to pumped hydropower schemes is often considerablyeasier than developing completely new schemes. A model is proposed to calculate theoretical potentialof a large area for the development of pumped hydropower schemes from existing conventionalhydropower stations and from non-hydropower reservoirs. The methodology combines a new databaseof existing dams and reservoirs with a digital terrain model to identify suitable reservoirs for trans-formation, applies several constraints to eliminate unfeasible sites, then calculates the realisablepotential in terms of power output and energy storage. The model is tested by applying it to the case ofTurkey to produce country-level estimates of the theoretical and realisable potential for such trans-formations. In excess of 3800 GWh of realisable energy storage potential was identified from over 400sites in the country.

� 2012 Elsevier Ltd. All rights reserved.

1. Introduction

The share of electrical power generated from renewable sourcesis growing throughout most of the world. Much of this growth iscoming from variable generators such as photovoltaics or wind. Inthe 27 countries of the European Union, wind generation capacityincreased approximately tenfold to 64 GW in the decade from 1998to 2008 [1]. This rapid, ongoing expansion of renewable generation

evel; CORINE, Coordination ofover; DEM, Digital Elevationulic Works (Turkey); GIS,servoir and Dam (database);HES, Pumped hydro energy; UNESCO, United Nations

þ31 224 565600.(N. Fitzgerald), roberto.lacal-eogh@ucc.ie (E. McKeogh),

ark, Model Farm Road, Cork,

All rights reserved.

has refocused attention on energy storage as a means to accom-modate a higher contribution of power generated from such vari-able sources, and this is recognised in such high-level documents asthe EC’s Energy Roadmap 2050 which states “Storage technologiesremain critical. Storage is currently often more expensive thanadditional transmission capacity, gas backup generation capacity,while conventional storage based on hydro is limited” [2] (p. 10).

Pumped hydro energy storage (PHES) is currently the mostfeasible option for large-scale storage [3,4] with 100 GWof installedcapacity worldwide, greatly exceeding that of compressed-airstorage (CAES), which has only two installations in the worldwith a total capacity of 0.4 GW [5]. A PHES scheme operates byexploiting the difference in height between two water bodies tostore potential hydraulic energy. Energy is stored by pumpingwater from the lower reservoir to the upper reservoir, and isrecovered by releasing the stored water from the upper reservoirthrough a turbine coupled to a generator. Modern PHES plants mayachieve round-trip efficiencies of more than 75% [6]. Deane et al. [7]reviewed existing pumped hydropower facilities and over7000MWof new and proposed developments in Europe, Japan andthe USA and observed that the majority of the proposed plants

N. Fitzgerald et al. / Energy 41 (2012) 483e490484

were in Europe, and that a wide variation in capital costs for PHESwas reported throughout the world.

In many instances, development costs and adverse environ-mental effects can be reduced by using existing reservoirs in thedevelopment of new PHES schemes. If an existing hydropowerreservoir is used, it can be transformed to a PHES scheme by theaddition of a penstock and an upper reservoir at a suitable locationnearby, if one exists, and the upgrade of the existing generatingplant and the incorporation of pumping capabilities. If the existingreservoir is not the location of a hydropower station, the addition ofcompletely new pumping and generation plant, as well as penstockand second reservoir, will be required.

The scope for new hydropower developments in Europe islimited, largely due to environmental considerations. However,transforming existing reservoir sites to PHES is likely to have lowerenvironmental impact and is thus more realisable. Analyses of theoverall hydropower potential of regions are available for differentscales of plant (e.g. small, medium and large hydro), but not fortransformation -to our knowledge- other than at a regional scale.

The aim of this study is to develop, implement and testa methodology for assessing the total potential capacity that can becreated in a large area by transforming suitable existing reservoirsites (including both hydropower and non-hydropower reservoirs)into PHES by adding a second reservoir (normally at a higherelevation) plus penstock and pumping equipment. The intentionwith developing this methodology is to ensure that it can eventu-ally be applied at European level to provide a consistent, continent-wide approach to estimating the potential for transformation ofexisting dams to PHES.

Models based on digital elevation maps (DEMs) and Geograph-ical Information Systems (GIS) are well-suited to identifyingpotential sites for hydropower plants. Dudhani et al. [8] used imageprocessing techniques to extract information from remotely-senseddata to assess small hydropower potential in mountainous areas ofIndia. Larentis et al. [9] implemented an algorithm to search existingdrainage networks for suitable sites for potential new hydropowerdam locations. A GIS-based model developed by Connolly et al. [10]is capable of identifying suitable sites for pumped hydropowerdevelopment from digital terrain maps. The model is very accuratebut the accuracy comes at the cost of high computation time, whichincreases greatly with the size of the study area. Thereforea different, more scalable, methodology was needed for this study.

Turkeywas chosen as the country onwhich to test the model forseveral reasons. Firstly, Turkey has a large installed conventionalhydropower capacity across a large geographical area [11].Secondly, existing municipal reservoirs in the country have alreadybeen identified as potential sites for hydropower installations [12].Furthermore, there is a significant wind energy resource in Turkey,with a theoretical potential estimated at 160 TWh per annum [13].Information on constraints to development is readily available, andDSI, the Turkish General Directorate of State Hydraulic Works,provides data on dams which is useful for cross-checking dataobtained from other sources.

Existing hydropower plants in Turkey account for 13,800 MWofinstalled capacity, producing on average 38,000 GWh of electricityper annum between 2005 and 2008 [14]. The total average elec-tricity generation in Turkey is 195,000 GWh per annum over thesame period [15], thus hydropower plants supplied 20% of the totaldemand. It has been estimated that only 35% of the total economicpotential for hydropower is utilised in Turkey [16]. A furtherobservation is that the large installed hydropower capacity canprovide a significant contribution to grid stabilisation, evenwithoutconsidering the additional advantages of PHES. The Turkishgovernment hopes that hydropower capacity will expand to35,000 MW by the year 2020 and has also set a target to increase

the country’s installed wind power capacity to 20,000 MW by theyear 2023 [16]. Despite possessing an excellent solar resource,plans are not yet advanced for large-scale solar photovoltaicgeneration in the country [13].

To implement the proposed methodology in a GIS model, therelevantdatamust befirst gatheredand then converted intoausableformat. Three categories of data are required: a geo-referenceddatabase of existing reservoirs; a digital terrain map to provideelevation information for existing andproposed reservoirs; andgeo-referenced data on potential constraints on PHES development. Thesubsequent sections of the paper describe the data sources, themethodology underlying the model, detailed results from a singlesite and country-level potential for PHES transformation in Turkey.

1.1. Dam and reservoir data

The International Commission on Large Dams (ICOLD) maintainsa global register of over 33,000 dams [17]. This database is compiledby accessing national data compiled by the representatives of its 82member countries. It includes hydropower dams and non-hydropower dams of structural height over 15 m and providesdetailed information on each dam listed, including damdimensions,reservoir area and volume. For hydropower dams, mean annualenergy production and rated power are also included. Being themost complete source of data on global dams, the ICOLD register ofdams forms the primary source of data on existing reservoirs for thisstudy.

In an effort to address known gaps in the existing global damand reservoir data sets, the Global Water System Project (GWSP)leads an international effort to collate the existing dam and reser-voir data sets to provide a single, geographically explicit and reli-able database. Version 1.1 of the Global Reservoir and Dam (GRanD)database includes 6862 reservoirs with a storage capacity of morethan 0.1 km3 [18]. Unlike the ICOLD database, GRanD includes geo-referenced spatial co-ordinates for each site but this field of thedatabase is far from complete: only 15% of the Turkish dams in theICOLD register are geo-referenced by GRanD, therefore theremaining 85% of dams in Turkey were geo-referenced manuallyusing Google Earth [19].

The General Directorate of State Hydraulic Works (DSI) is anagency of the Turkish government charged with developing waterand land resources. The DSI website lists all dams that are under itscontrol [20]. This list was used as a reference to verify ICOLD dataand the pictures of the dams were used while manually geo-referencing dams using Google Earth.

Data from the above sources were combined to create thedatabase of geo-referenced dams used as the starting point of themethodology described in this paper.

1.2. Terrain data

The Shuttle Radar Topography Mission (SRTM) produceda collection of remotely-sensed elevation data covering the wholeworld between 60� S and 60� N [21]. The SRTM digital elevationdata have been processed to fill spatial gaps and are published onthe CGIAR-CSI GeoPortal website. The SRTM 90m digital elevationmaps have a horizontal resolution of 90m at the equator, anda vertical resolution of 16m or better, and are available for down-load in 5� by 5� tiles. A product with 30m horizontal resolution isalso available, but limited in coverage to the continental UnitedStates. The tiles are produced from a seamless dataset to allow easymosaicking to cover larger areas [22]. The SRTM dataset has beendemonstrated to provide accurate information for catchment areaslope and area elevation, which makes it useful for this study,although the resolution is insufficient for detailed rainfall-runoff

5 km buffer placed around dam under test

N. Fitzgerald et al. / Energy 41 (2012) 483e490 485

studies [23]. An extensive campaign of validation against ground-based measurements concluded that the 90% threshold for rela-tive height errors across the Eurasian landmass was 8.7 m [24].

Select regions with average elevation 150 m above or below the existing dam

Calculate slope inside buffer

Select areas with slope between 0 and 5 degrees

Calculate average elevation in each selected area

Select second reservoir site with largest energy storage capacity

Select areas satisfying minimum reservoir area criterion

repeat for all dams

Calculate areas of selected regions

Calculate volumes and storage capacities of potential second reservoirs

1.3. Environmental constraints data

The Coordination of Information on the Environment (CORINE)initiative of the European Commission has produced a land coverdataset from remotely-sensed data for the European Union andneighbouring countries known as CORINE Land Cover (CLC). TheCORINE land cover data for Turkey has been extracted from the CLC2006 European dataset in 100 m raster format and is used togenerate GIS layers for the inhabited areas and river/lake features[25]. Land cover classes 40 and 41 (water courses; water bodies)were interpreted as river or lake features, while land cover classes 1,2 and 3 (continuous urban fabric; discontinuous urban fabric; andindustrial/commercial units) were used to identify inhabited areas.The inhabited areas are applied as constraints in themodel,wherebypotential transformation sites are eliminated from the final calcu-lation of realisable potential if they overlapwith these. The river andlake features are primarily used for illustration purposes whengenerating maps of transformation sites, but they were also used insome cases to cross-check dam locations from the dam database.

Rail and road data layers were obtained from the DIVA-GISwebsite [26]. DIVA-GIS also provides political boundary data, whichwas used to select the area of Turkey from the total area covered bythe mosaic of SRTM terrain tiles. Another potential constraint iswhere proposed sites intersect transmission lines. As movingtransmission lines is expensive and disruptive, it would generallybe avoided in the course of a reservoir development. As it was notpossible to source sufficiently accurate geo-referenced data for gridinfrastructure, this constraint was not considered in the study. A listof United Nations Educational, Scientific and Cultural Organisation(UNESCO) World Heritage sites was downloaded from the UNESCOwebsite [27]. Although co-ordinates for the sites are not providedby UNESCO, it was possible to manually geo-reference the sitesusing Google Maps. A list of wetland sites protected under theRAMSAR convention was incorporated as a further constraint [28].

Apply constraints

Theoretical Potential

Realisable Potential

Fig. 1. Flowchart illustrating the methodology for selecting the second reservoir siteand calculating theoretical and realisable potentials.

2. Methodology

The methodology consists of taking an existing reservoir andanalysing the surrounding topography for a suitable site for a newreservoir in order to transform the scheme to PHES.

Table 1 details the parameters that have been assumed for theGIS model and Fig. 1 illustrates the overall design of the method-ology. A modular design was preferred, which allows for easyapplication of the model to different regions, and for substitution ofdata layers if new data becomes available. Terrain data, for example,can be replaced by more accurate local sources if they are availablefor specific regions.

Table 1Model parameters and constraints data.

Transformation topography & physical characteristics

Minimum volume of existing reservoir 1,000,000 m3

Maximum distance between existing reservoir andpotential reservoir site

5 km

Minimum head 150 mMaximum slope of second reservoir area 5 degreesAssumed minimum new, second reservoir surface area 70,000 m2

Minimum distance from new reservoir to inhabited sites 500 mMinimum distance from new reservoir to existing

transportation infrastructure200 m

Minimum distance from new reservoir to an UNESCO site 5 km

Firstly, existing dams are selected from the geo-referenced damdatabase described in Section 1.1. Properties including dam locationand reservoir volumeare extracted from thedatabase for each site tobe examined. Similar to [9], the algorithm does not simply seeka second reservoir site tomaximise the head between the two sites,but a circular search region surrounding the existing site is defined.The buffer distance parameter is used to define the search radiusfrom the existing dam to potential second reservoir sites. A distanceof 5 km is chosen as an acceptable maximum distance between twoPHES reservoirs, based on knowledge of existing schemes in Europe.

It is appropriate to identify reasonably flat sites where it wouldbe possible to construct a reservoir, as it may be difficult for prac-tical reasons to construct a reservoir on strongly sloping sites.Therefore, areas within the buffer with slopes between 0 and 5� are

N. Fitzgerald et al. / Energy 41 (2012) 483e490486

then selected (Fig. 2). The average elevationwithin the buffer area iscalculated. A value of 5� has been chosen as a maximum acceptableslope of the topography for a potential second reservoir site.Although the slopes of actual sites are likely to be lower, the valuehas been kept large in order to avoid ruling out areas of complextopography which may possess mean slopes of up to 5� but whichmay still be suitable due to the presence of features below theresolution of the digital terrain map.

The slope alone is not enough information to define a potentialtransformation site. The area where the slope criterion is satisfiedalso needs to be defined. A minimum area of 70,000 m2 has beenchosen for the construction of a new reservoir. This was calculatedas follows. We have limited the minimum reservoir capacity to beexamined in this study to 1,000,000m3. Given a further assumptionthat the average depth of the reservoir is 20 m, the area of thereservoir would need to be 50,000m2. The latter assumption agreesbroadly with the average depth of existing hydropower reservoirsin Turkey which was calculated as 30 m (from ICOLD reservoir areaand volume figures). As most of these reservoirs are flooded rivervalleys it seems reasonable to assume that potential second reser-voir sites for PHES schemes would tend to be less deep. Theminimum area of 70,000 m2 was chosen as it is assumed that anarea of 20,000 m2 would be needed for the construction of thedams and other civil works.

The head parameter is used to define the minimum elevationdifference between the existing dam and the potential dam site,and a minimum head of 150 m has been chosen, based on analysisof existing PHES sites in the database. The average elevation of thearea for potential site is used and compared with the elevation ofthe existing dam. Any of the remaining areas within the searchbuffer satisfying the slope criterion with average elevation at least150 m above or below the existing reservoir are then selected. At

Fig. 2. Areas identified by the model w

this stage, there may be several candidate sites for a secondreservoir within the buffer zone. Therefore, a means of selecting thebest of these candidate sites is required, based on some criterion.Candidate sites are ranked by energy storage capacity in GWh, andthe site of highest capacity is selected. The process is then repeatedfor all the dams in the database. Aggregating the results obtainedfor all dams results in the theoretical potential.

The potential hydraulic energy available in a body of water isdefined as follows:

E ¼ rghVm (1)

where:

E ¼ energy available (Joules)r ¼ density (kg/m3) (1019 kg/m3 for water)g ¼ acceleration of gravity (9.81 m/s2)h ¼ falling height, head (m)V ¼ volumem ¼ generation efficiency (90% assumed)

Constraints are then applied to each site selected in order toeliminate unfeasible sites, resulting in the realisable potential. Abuffer of 5 km around each UNESCO sitewas applied as a constraint.A minimum distance of 500 m to any inhabited site was alsoimposed, and a 200 m exclusion buffer was placed around roadsand railway lines. The buffers are comparable to those used inwindenergy developments in Europe. The RAMSAR website onlyprovides a latitude and longitude co-ordinate for each of the 13sites in Turkey, but does not provide shapefiles indicating theboundaries of the protected sites. Therefore, a large buffer of 20 kmwas placed around each site. No other constraints were included forthe Turkish example, but the modular design of the methodology

ith slope between 0 and 5 degrees.

Fig. 3. Map of Turkey showing elevation, dam locations and constraints data layers used by the model.

Fig. 4. Elevation histogram of existing dams in Turkey, with a reservoir capacity of1,000,000 m3 or greater.

N. Fitzgerald et al. / Energy 41 (2012) 483e490 487

makes it straightforward to incorporate new categories ofconstraints. For example, the model is capable of applying trans-mission line constraints but these were excluded in this case due tothe lack of sufficiently accurate data in the public domain.

ArcGIS 9.3 software (ESRI, USA) has been used to implement themodel to analyse the potential to transform existing hydro andnon-hydro dams into PHES. The model builder feature of the soft-ware was used, and several functions from toolboxes availablewithin ArcGIS were incorporated in the model. SRTM data are usedin themodel to calculate the elevation abovemean sea level (AMSL)of existing reservoir sites by importing the shapefile containingdams manually geo-referenced in Google Earth. Then, by runningthe extract tool in ArcGIS to combine the geo-referenced dams withtheir respective SRTM elevations, the elevation of each dammay becalculated. This method was preferred to extracting elevation datadirectly from Google Earth in order to maintain consistency withthe elevation of the potential second reservoir sites, which arederived solely from SRTM data. However, subsequent cross-checking between Google Earth and SRTM indicated that eleva-tions derived from both sources were in good agreement. The slopeof the area inside the search buffer is calculated using the slope tooland the average elevation within the buffer area is calculated usingthe zonal statistics tool.

3. Results and discussion

A total of 612 reservoirs inTurkeyare above 1,000,000m3 in capacityand were incorporated in the database and subsequently analysed bythe GIS model (Fig. 3). The distribution of elevations of these dams(Fig. 4) shows that a large proportion are between 0 and 400 m AMSLand between 801 and 1200mAMSL. From these reservoirs, the analysisshowed a theoretical potential of 4372 GWh in 448 sites.

3.1. Realisable potential

The realisable potential results from the application of theenvironmental constraints listed in Section 1.3 to the theoretical

potential. This resulted in the loss of four transformation sites withan associated loss of 555 GWh of energy storage. The total numberof realisable potential sites is thus 444with a total energy storage of3817 GWh.

3.2. Sensitivity analyses

As the size of the search buffer surrounding the existing dam isone of the key parameters of the model, it was decided to examinethe sensitivity of the number of identified transformation sites andthe theoretical energy storage potential to this parameter. There-fore, the model was re-run for values of the search buffer lyingbetween the specified value of 5 km and a value of 1 km. Decreasingthe buffer size is likely to reduce the number of transformation sitesand the potential, but may lead to more economically feasible sites,due to the reduction in the length of penstock required for a PHESscheme. The results of the analysis are presented in Fig. 5 and Fig. 6.Each instance of the search buffer size, from 5 km down to 1 km islabelled as a ‘scenario’ in the figures, with Scenario 5 indicatinga 5 km buffer, Scenario 4 a buffer of 4 km etc.

Fig. 6 shows the relationship of the total number of trans-formation sites and the realisable potential to the buffer size. Both

Fig. 5. Turkey’s realisable potential, number of potential sites and total energy storagecapacity as a function of the second reservoir search buffer size.

Table 2Energy storage capacities of two transformation possibilities for the sample site.

Dam name Existingreservoirvolume (m3)

Candidatesecondreservoirarea (m2)

Candidatesecond reservoirvolume (m3)

Head(m)

Storedenergy(GWh)

Karacaören II 48,000,000 1,106,519 22,130,381 613 34Karacaören II 48,000,000 116,761 2,335,216 549 3

N. Fitzgerald et al. / Energy 41 (2012) 483e490488

quantities fall off rapidly as the search buffer is reduced, withalmost none of the sites falling within 1 km of the existing dams.Fig. 6 displays scheme average head and the average storagecapacity as a function of the search buffer size. As the search bufferis reduced from 5 km to 1 km, the average head of the schemesreduces from 280 m to 160 m. The average energy storage falls offdue to the reduction in head and a reduction in the areas of theselected second reservoirs as the search buffer is reduced.

The sensitivity of the realisable transformation potential to twoother key model parameters was investigated. Values of 100 m,200 m and 300 m were applied as the minimum head differencebetween the existing dam and the second reservoir site (in additionto the default value of 150 m). Different values of the upper limit ofthe slope of the second reservoir site were also applied. In additionto the default value of 5�, the results were recalculated for slopevalues of 3� and 7�. The results of these two sensitivity tests arepresented in Table 3.

Across the range of head values, the highest energy storagepotential occurs with a minimum head criterion of 150 m. Above150 m, the greater selectivity of the criterion reduces the overallenergy storage potential. With a 100 m minimum head difference,the overall storage potential is slightly lower than at 150 m. Thisresult is thought to be an effect of the sequence of the model’soperations, where sites are selected based on head difference priorto the calculation of reservoir areas (Fig. 1). In some cases, secondreservoir sites with larger areas but lower average heads may beselected when the 100 m criterion is applied. Due to the averagingof the elevation over the site’s area, the resulting calculated energystorage may be lower than that of a partially overlapping smallersite identified under the 150 m criterion.

Table 3 also indicates that the results are sensitive to the slopecriterion, with a considerable increase in overall transformationpotential as the criterion is relaxed from 3� to 5� to 7�.

Fig. 6. PHES scheme head and average storage capacity as a function of the secondreservoir search buffer size, averaged overall sites.

3.3. Sample site analysis

In order to demonstrate and validate the methodology, theanalysis of a sample site is presented prior to applying the meth-odology to the whole country. The existing dam is the Karacaören IIstructure, located 189 m above sea level near the town of Bucak, intheBurdur regionof southwesternTurkey. The structurehas aheightof 49 m and impounds up to 48,000,000 m3 of water. The reservoircovers an area of 2,340,000 m2. An existing 47 MW hydropowerplant produces 206 GWh of electricity per annum on average, andthe reservoir is also used for irrigation purposes [17,20]. The modelidentified two potential second reservoir sites (Fig. 7). The locationof the existing Karacaören II dam is indicated by the white circle,with the adjacent white area illustrating the existing reservoir area(as extracted from CORINE Land Cover data). An area to the west ofthe dam (labelled 1 in the figure) shows a potential second reservoirarea that meets the requirements specified in Table 1, and the arealabelled 2 in the figure shows the site that has been selected as themost suitable location of the second reservoir, as it has the largestenergy storage. This site is shown in bold in Table 2 along with itscalculated storage of 34 GWh, based on the estimated upper reser-voir volume.

3.4. Limitations

The realisable potential is highly sensitive to construction costs,which are presently outside of the model’s scope. The wide range($470/kW to $2170/kW) quoted by Deane et al. [7] is indicative ofthe site and project-specific nature of PHES development costs. Oneof the difficulties in estimating costs for transformation projects isthe fact that only total project costs are generally reported, withdetailed costs for components (e.g. penstock, power plant)unavailable. A sample of these data provided by Kraja�ci�c et al. [29]for a PHES project in the island of Krk (Croatia) is presented in Fig. 8.The total cost for a 10 MW, two pumps and turbines system is16.8 MV.

The model as currently implemented is well-suited to identi-fying potential second reservoir sites based on the construction ofimpounding embankments on relatively flat sites, due to theinclusion of the slope constraint. It is possible that in some cases,a suitable second reservoir could be created by constructing bya barrage in a deep, steeply sloping valley. This type of site wouldnot pass the slope constraint, and anyway it would change anessential part of this work: assessing PHES potential with a low

Table 3Summary of sensitivity tests of realisable energy storage potential to (a) headdifference and (b) upper reservoir slope threshold parameters.

(a) Minimum head difference (m) Total storage potential (GWh)100 3759150 3817200 2593300 1576

(b) Maximum upper reservoir site slope (degrees)3 12225 38177 5383

Fig. 7. Turkish sample transformation site analysis.

N. Fitzgerald et al. / Energy 41 (2012) 483e490 489

environmental impact. In effect PHES developments at such siteswould involve closing a torrent or a larger water course whichwould have the same kind of environmental impacts as theconstruction of new hydropower plant.

Geological constraints are currently not considered, but couldalso be added in the future. For example, the presence of permeablebedrock, e.g. in karstic areas, may significantly add to the costs forconstruction due to the necessity to line reservoirs. Furthermore,some of the sites are likely to be located in areas subject tohydrological stress. Seismic activity is another factor which should

Fig. 8. Cost breakdown for a PHES project in Croatia.

be considered, although given that dams already exist at thetransformation sites, this may have a minor effect on the overallpotential.

In this analysis of potential for transformation the authors wereobliged to take decisions based on empirical analysis as well as ontheir own experience, with the limitations imposed by the modeland with availability of data being a key influencing factor. Becauseof the latter those decisions at times had to be arbitrary and notnecessarily match the reality in individual cases. As an example inPHES schemes such as e.g. the Velebit system in Croatia,2 thedistance between the reservoirs is notably larger than 5 km (20 kmin this case). Another of the assumptions in the design of this modelthat was challenged by the reality is that the size of the upperreservoir should not be bigger than the lower (existing) reservoir.These cases serve to illustrate that the actual figures on thepotential for PHES resulting from transformation may be largerthan those estimated by this method.

4. Conclusion

Every scenario for high penetration of renewable energy inelectricity systems highlights the need for electricity storage andputs storage as a key factor for reducing the cost of energy if therenewable electricity is of a variable nature [30]. This modellingexercise is, to the knowledge of the authors, the first approach toidentifying and quantifying the potential for transformation to

2 A similar analysis to this one was undertaken using Croatia as a case study.

N. Fitzgerald et al. / Energy 41 (2012) 483e490490

pumped hydropower storage in European countries based on oneexisting dam. However, this is high-level research and its resultsmight be some stages away from the accuracy and definitionrequired for actual individual projects. This is important becausethe ultimate goal of an exercise to quantify the potential forincreasing PHES is dual: to feed the decision-making process withsound science and to reduce the costs of transformation for allactors involved: governmental spatial planning agencies, engi-neering companies and developers of PHES.

The analysis of transformation potential for Turkey shows a totalrealisable potential of 3817 GWh of storage capacity which can becompared with the estimated peak demand of 35 GW and with the230,000 GWh of electricity generated in the country in 2010. Giventhat, to the authors’ knowledge, there are no existing PHES plants inTurkey, this potential can not be compared to any currently-installedPHES capacity. When local considerations outside the scope andresolution of the model are taken into consideration, the actualpotential is likely to be lower, but the estimates presented here provideuseful first estimates of the region’s potential for PHES developments.

The inclusion of this potential into the greater picture of theelectricity system needs some insight on how the prospective newPHES could be used to help stabilise the grid and increase theuptake of renewable energy. In effect, some of the potential PHEScould be used for intra-day balancing, i.e. pumping at night whenthere is excess electricity from baseload (coal or nuclear) plant, andgenerating during the day. Some other PHES with higher storagecapacity could be used for weekly or monthly storage if economi-cally feasible. A transformation of the Karacaoren II Dam in Turkeywith the chosen second reservoir site, with 34 GWh of storagecapacity, could be used to store electricity from excess wind ratherthan curtailing wind production. In effect, wind energy cycles maylast hours but most frequently last 3e4 days depending on the localclimatology. In electricity systems with high wind penetration andlow export capacity, windmay need to be curtailed whereas a PHESplant with large storage capacity can absorb and then release thesewind energy during peak demand and thus having the additionalenvironmental effect of avoiding the use of natural-gas peakingplant. Its storage capacity and its maximum power generation,among other factors, define which category a site falls into.

The authors recommend that themethodology presented in thispiece of research should be further developed to identify theEuropean potential for transforming existing reservoirs to PHES.

Acknowledgements

This work was carried out in the context of the EuropeanCommission Strategic Energy Technology Plan Information Systemwith the support of the Institute for Energy, Joint Research Centre ofthe European Commission and the Stokes Lectureship programmeof Science Foundation Ireland. The authors wish to thank HelenBradley and Paul Deane of UCC for assistance and the providers ofdata used in this study.

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