Operational optimisation of a tidal barrage across the Mersey estuary using 0-D modelling

Ocean Engineering 66 (2013) 69–81

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Operational optimisation of a tidal barrage across the Mersey estuary using 0-D modelling G.A. Aggidis n, D.S Benzon Lancaster University Renewable Energy Group, Engineering Department, Engineering Building, Bailrigg, Lancaster, Lancs LA1 4YR, UK

art ic l e i nf o

a b s t r a c t

Article history: Received 27 November 2012 Accepted 30 March 2013 Available online 10 May 2013

With the operational lifetime of a tidal barrage stretching up to 120 years, it is important to be able to change the level of energy generation with varying trends in energy demand. Unlike other technologies, the energy generation level and sequence of a tidal barrage can be significantly altered without any physical change to the barrage by varying only the operational parameters. In order to explore this, a computational model which calculates the energy generation for a barrage across the Mersey estuary was developed. The model uses cutting edge double regulated turbine technology and bathymetric data and explores how this can be achieved without changing the physical parameters of the barrage. The derived results were compared to previous studies and found to match and exceed the results of past predictions. & 2013 Elsevier Ltd. All rights reserved.

Keywords: Renewable Energy Turbines Tidal power Tidal barrage Tidal range 0-D modelling

1. Introduction An important tool in assessing the feasibility of a tidal barrage project is a tidal barrage model, which can be used to calculate the potential energy generation under a variety of operating conditions with the investigation of physical and operational parameters. An accurate tidal barrage model requires data including tidal data, bathymetric data and manufacturer data on turbine flow, speed and efficiency in order to make accurate predictions of flow, power and energy. Each set of information is manipulated and included in the computational model calculations, and where possible, improvements made in the accuracy and reliability of the calculations. The modes of operation are explored further carrying out optimisations of the starting head, for ebb generation and ebb generation with pumping. The results of testing carried out are displayed with a variety of fixed and variable input parameters and are compared to previous studies of barrages in the same location with the same physical parameters. The results of this investigation will form the foundation for future parametric analyses using the same computational model.

2. Background The Mersey estuary (Fig. 1) has been the focus for tidal power schemes going as far back as 1981 when Marinetech North West n

Corresponding author. Tel.: +44 1524 593052. E-mail address: [email protected] (G.A. Aggidis).

0029-8018/$ - see front matter & 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.oceaneng.2013.03.019

investigated the potential for tidal power in the estuary (Peel Energy, 2010), followed by Mersey Barrage Company (MBC) (1992) conducting further studies between 1988 and 1992. The most recent study, undertaken by PEEL energy and The Northwest Regional Development Agency (NWDA) began in 2006 with a pre-feasibility study examining the options available for tidal power generation. This was followed by a full feasibility study which started in 2009 with the assessment of a long list of applicable technologies which was eventually narrowed down to a shortlist, with particular focus on tidal barrage options. This study has since been completed and the results are available through their website (Peel Energy, 2010). 2.1. Overview of components required The computational model used in this paper is a 0-D, backward difference, non-optimising model and includes ebb generation with direct pumping at high tide. The construction of this model requires tidal patterns for the Mersey estuary and bathymetric data for the estuary basin. This can be used to map the estuary basin bathymetry in a number of ways, giving the volume of the estuary at different stages of the tidal cycle and thus, the potential energy available from the enclosed body of water (Aggidis and Feather, 2012). Cutting edge turbine hill charts for double regulated bulb turbines provided by Andritz Hydro are used to calculate the flow and power generated from a selected turbine at different flow rates and heads (Aggidis and Feather, 2012). Bulb turbines were chosen as they are used widely across the world in low-head tidal power schemes and are one of the most efficient turbines for low head applications (Krompholz, 2008).

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Fig. 1. 1:50,000 Scale OS Map of the Mersey estuary (ESRI, 2009).

Tidal Curve Using 4 Main Constituents 10 9 8 7 Height(m)

This information provides the input into MatLab to create a model which will give an accurate representation of the energy generated from a tidal barrage at different stages of operation with variable head heights, turbine diameters and number of turbines. The model is designed with dynamic assumptions in mind, creating a model for a barrage which is adaptable to changes in government policy, energy demand, environmental policies and the estuary environment. In this way, the model will be applicable to a tidal barrage which will be in place for around a century and, in its design, adaptable to changes.

6 5 4 3

3. Barrage model building blocks

2

3.1. Tidal data

1

In 1867 William Thompson, the 1st Baron Kelvin devised a method of reduction of tides by Fourier harmonic analysis (Hardisty, 2009). This works under the principle that no matter how complex the sinusoidal tidal variation, it can be broken down into the sum of a series of simple sinusoids (referred to as tidal constituents) usually represented by the cosine function. Each tidal constituent will have a period of oscillation based on the celestial forcing which gives rise to it (VIMS, 2012). The height of each constituent is given by the formula H ¼ a cosωt

ð1Þ

where a, is the amplitude of the constituent and ω is the speed of rotation or period of oscillation. The four primary constituents (M2, S2, K1, O1) where used to generate the tidal curve. M2 is the principle lunar semidiurnal constituent, S2 is the principle solar semidiurnal constituent, K1 is the luni-solar declinational diurnal constituent and O1 is the lunar

0

0

0.5

1

1.5

2

2.5

Time (hours)

3

3.5

4

4.5 4

x 10

Fig. 2. Tidal response over one month using the four primary constituents provided by Admiralty (2011).

declinational diurnal constituent. The amplitude, a, and the corresponding speed, ω, for each constituent were provided by Admiralty (2011) and using Eq. (1), a tidal curve for the Mersey at Eastham could be plotted (Fig. 2). These constituents were used to generate a tidal curve which could be incorporated into the model over a chosen time period. 3.2. Bathymetric data Bathymetric data is required in order to calculate the enclosed volume of water within the basin with the change in water level at

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the barrage as a result of the tides. The volume calculations made in this model were carried out using depth sounding data for the entire estuary from SeaZone Solutions Ltd (ESRI, 2009).

Fig. 3. Raw XYZ Global Lat-Long data© SeaZone Solutions Limited, 2005 [032011.001].

Fig. 4. Colour scaled, smoothed TIN surface for the entire estuary, Z factor¼25 (ArcScene)© SeaZone Solutions Limited, 2005 [032011.001].

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Using ArcGIS (Watson and Philip, 1985), it was possible to accurately map the basin bathymetry using this data (Fig. 3). The XYZ data were converted into a grid using a feature of ArcGIS called TIN (triangular irregular networks) (Watson and Philip, 1985). TIN Grids are a means of representing surface morphology, created by triangulating a set of digital points or vertices. ArcGIS TIN gridding utilises the Delaunay triangle criterion which ensures that no vertex lies inside the circumcircles of the triangles created, eliminating long narrow triangles and improving the capability of capturing linear features that play an important role in a surface (ESRI, 2009). The gridded data with a depth colour scaling and a scaling up of the Z component by 25 to better represent the morphology is shown in Fig. 4. In order to now calculate the volume enclosed at various depths about the ODN, (ordinance Datum Newly) a set of flat surfaces were created at 1 m depth intervals in order to represent the water surface within the estuary at each water height measured at the barrage location. In order to account for the slight gradient of the water surface moving downstream, nine transects were taken across the basin (Fig. 5), and for each transect the average depth was recorded from the profile graph by exporting the zonal statistics. Once an average depth is calculated for each transect, the inverse distance weighting (IDW) function is used to interpolate a surface which follows the mean depth points (Watson and Philip, 1985). A range of IDW surfaces were created based on the IDW slope at varying heights about the ODN at the tidal barrage. These surfaces accurately simulate the water level at each depth which will vary over the tidal cycle. The water surface at mean sea level is shown below as the IDW surface at the barrage ODN (Fig. 6). Finally, In order to calculate the enclosed volume over a range of barrage water heights, the ArcGIS Cut/Fill function was used (ESRI, 2009). This calculated the volume required to fill the basin from the TIN grid to a range of IDW surfaces at varying depths. This produces a table of values from MSL−6 to MSL+6 showing the

Fig. 5. Transects and points used for IDW© SeaZone Solutions Limited, 2005 [032011.001].

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enclosed volume of the estuary at each depth. This data can then be used to create a depth/area curve, with a 3rd degree polynomial curve fit (Fig. 7). The bathymetric data has been compared with studies of the bathymetric evolution of the Mersey estuary carried out by Proudman Oceanographic Laboratories, and found to be concurrent (Lane, 2004). The depth/volume curve can be combined with the tidal curve to accurately calculate the volume of water entering and leaving the basin over time.

3.3. Turbine calculations

Fig. 6. IDW surface at MSL0 at barrage location© SeaZone Solutions Limited, 2005 [032011.001].

Depth/Volume curve for Mersey Estuary

Impounded volume of estuary (m3)

8

7

x 10

A hill chart for a double regulated turbine provided by Andritz Hydro (Aggidis and Feather, 2012) was digitised and the maximum output curve was used to calculate the power generated over a variety of heads and rates of discharge (Fig. 8). The values on the hill chart can be used to calculate the power output by manipulating the following equations for flow, head and efficiency on which the model is based (Baker, 1991).

6 5

n11 ¼

4 3

Q 11 ¼

2 1

Sp  D pffiffiffiffi H Q D2 

pffiffiffiffi H

ð2Þ

ð3Þ

and

0 -6

-4

-2

0

2

4

6

Depth about ODN (m)

Fig. 7. Depth/volume curve created using ArcGIS (Watson and Philip, 1985) and SeaZone Bathymetric Data (ESRI, 2009).

SP ¼

2  60  f GP

Eq. (2) can be rearranged to give the head

Fig. 8. Andritz Hydro 3-Blade low head bulb turbine unit (Aggidis and Feather, 2012).

ð4Þ

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 H¼

 nD 2 n11

H can then be introduced into Eq. (3) to give the flow, Q pffiffiffiffi Q ¼ Q 11  D2  H

ð5Þ

above can be multiplied together to give the overall barrage system efficiency η ¼ ηh  ηp  ηt  ηw  ηg  ηa

ð8Þ

ð6Þ

The power can therefore be calculated as P¼ρgHQ η

73

4. Barrage model ð7Þ

These calculations provide good approximations of the power output of a single turbine represented by the hill chart, over a variety of different heads. As can be seen in Eq. (7), the power should increase with an increase in head; however there will be a point where a maximum head and flow is reached for the selected generator past which the turbine is no longer running efficiently (Baker, 1991). These equations do not take into account the effects of cavitation as it is assumed that the turbines will have sufficient submergence to prevent cavitation occurring. The selection of the turbine used in the project was determined by the range heads available on a Mersey tidal barrage scheme as a result of the tidal range, which can be up to 10 m at spring tide (Grant and Burgun, 2010), as well as the expected flow rates. 3.4. Barrage losses Although the main losses in the tidal barrage system are due to the turbine efficiency, there are other losses which need to be accounted for in order to generate realistic power approximations. 3.4.1. Hydraulic or turbine efficiency, ηh This was calculated as a curve varying with the unit speed, n11, using the digitised hill chart. 3.4.2. Generator efficiency, ηp Although this value will vary from manufacturer to manufacturer, for 12 MW generators, it is typically in the region of 98% or 97% (Andre, 1976). 3.4.3. Transformer efficiency, ηt Again, this will vary depending on the size of the transformer, manufacturer, cost, etc. However, based on experience with power plants of a similar scale, a typical figure of 99.5% was used (Libaux et al., 2011). 3.4.4. Water friction, ηw This efficiency is an estimate of the losses due to water friction. For a study looking at a Tidal Lagoon Power generation scheme in Swansea Bay on behalf of the Department of Trade and Industry and the Welsh Development Agency, this efficiency was given as 95% (Baker and Leach, 2006).

The barrage model created in this study works along the same principles of a 0-D, non-optimising model with the bathymetry accounting for the downstream slope of the water in the estuary (Section 3.2) and further optimisations incorporated into the model such as optimising the starting head (Section 4.3). This model works on the assumption that the water reaches and leaves the barrage instantaneously with the only flow rate affecting the basin levels being the flow through the turbines and sluices. How the structure affects the external hydrodynamics can be examined further using more sophisticated 2D or 3D modelling. The operation of a tidal barrage as implemented in the creation of a computational model with ebb generation and direct pumping at high tide can be broken down into four distinct stages for ebb generation with pumping shown in Fig. 9. The separate phases of the barrage cycle were defined in the Matlab code using logic to separate the calculations taking place at each stage and shaping the basin curve. 4.1. Basin filling This stage involves the filling of the estuary through the sluice gates and the turbines in orifice mode with the flooding of the tide (for ebb generation). The flow simulations are governed by Eq. (9). Q ¼ As C d ð2gHÞ0:5

ð9Þ

where the sluice gate area as well as free run area of the turbines are included in As , C d is the coefficient of drag expressed as a scalar and H is the head in metres. 4.2. Hold period There are two distinct hold periods during the operational cycle of a tidal barrage in ebb generation mode with or without pumping, indicated by the flat section of the basin curve (Fig. 9). These are the hold period before generation, and the hold period after generation. The former is controlled by the starting head, the primary variable in barrage optimisation. When the difference between the sea and barrage level reaches this value, generation begins. The latter is controlled by the minimum turbine generating

3.4.5. Gear box/drive train efficiency, ηg As with the previously mentioned losses, the gearbox losses will vary from turbine to turbine, depending on the type of gear, material, friction, temperature etc. A study done by a UK turbine supplier, ‘NHT Engineering’ looks at the various losses in a bulb turbine unit, giving an average gearbox efficiency of 97.2% (Taylor, 2008). 3.4.6. Turbine availability, ηa This refers to the losses based on the availability of all the turbines for power generation throughout the barrage lifecycle. Although this value varies depending on the potential problems with the turbines as well as maintenance requirements, a loss of 5% is usually used (Baker and Leach, 2006). All the losses described

Fig. 9. Phases of tidal barrage operation in generalised ebb mode with pumping.

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head, supplied by the manufacturer usually taking a value between 1 m and 2 m (1.2 m in this study). When the head reaches this value generation stops and the barrage level remains constant until filling takes place, and the cycle repeats.

the new volume added to the basin level, increasing the head until the set pumping head is reached.

5. Starting head optimisation 4.3. Generation The generation phase uses an iterative approach, combining the bathymetric calculations covered in 3.2 with the hill chart equations in Section 3.3. In a simplified explanation, the synchronous speed is used to calculate the unit speed and flow which can be used with a starting head to calculate the total flow through the barrage in a set time interval. Using the bathymetric data, this decrease in volume can be used to calculate the drop in estuary water level giving the new head across the barrage and the process repeated. For each iteration, the power can be calculated from the flow and head difference using Eq. (7) and this can be summed over the time period to give the overall energy extracted from the barrage. Fig. 10 shows a flow chart with the breakdown of the equations used to calculating the flow through the turbines and the associated power and energy.

4.4. Pumping The pumping phase uses the same iterative approach as in Section 4.3, with the use of double regulated turbines; direct pumping can be used (Hilliaret and Weisrock, 1986). This involves the use of turbines as pumps by adjusting the runner blade and guide vane angles. The calculations for this phase of the barrage cycle are therefore made using the same hill chart maximum output curve as for generation, with a scaled down maximum power output. The change in volume is calculated in the same iterative manner with

As mentioned in Section 4.2, the starting head is the primary operational optimisation which can be carried out on a tidal barrage without changing any of the physical barrage parameters. The optimum starting head will vary from barrage to barrage depending on a number of physical parameters including the size and number of turbines, sluicing characteristics etc, however for a fixed set of physical parameters, it can be dependant primarily on the tidal range which varies from cycle to cycle (Libaux et al., 2011). For effective optimisation of the starting head, a relationship needs to be defined between the starting head and the tidal range, setting the starting head to the optimum value at the start of each cycle. This was achieved by simulating the generation of electricity over a single tidal cycle of set range, for a specified barrage configuration, at a series of starting heads until the optimum starting head for maximum electricity generation is reached. The process is then repeated for a variety of tidal cycles of varying ranges from spring to neap tide. For each cycle, the optimum starting head can be found and plotted against the tidal range. This was done for each barrage configuration over 30 cycles and plotted using Matlab with a 5th degree polynomial curve fitting. The optimum starting head curve generated for the 700 MW PEEL/ NWDA barrage ebb generation comparison discussed in Section 6.4 is shown in Fig. 11. Using the equation for the fitted curve, the optimum starting head is calculated at the start of each cycle based on the measured tidal range. This optimisation was built into the model allowing maximum energy calculations to be made with an optimised starting head as well as allowing calculations with a fixed starting head to be made.

Fig. 10. Generation and energy calculation flow chart.

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Fig. 11. Fifth degree polynomial curve fitted to optimum starting head against tidal range data for 700 MW barrage in ebb generation mode.

6. Comparisons with previous studies

6.2. Mersey Barrage Company (MBC) (1992)—700 MW barrage

There have been several studies assessing the potential for tidal range energy extraction on the Mersey estuary using a variety of different models, barrage parameters and operational modes. The Department of Energy carried out a study in DoEn and UKAEA (1984) followed by Mersey Barrage Company (MBC) (1992), the ‘Joule’ Project by the University of Liverpool and Proudman Oceanographic Laboratories in Burrows et al. (2009a) and the Peel Energy Limited and Northwest Regional Development Agency feasibility study in Libaux et al. (2011). The results from each of these studies have been compared to results generated using the model described in this paper. For each comparison, the same physical parameters were used including the number, size and power rating of each turbine; the number and size of the sluice gates and the location of the barrage (unless specified otherwise). The operational parameters were also changed to match the parameters used in each study. The parameters used for each comparative study and the results are discussed below and detailed further in Appendix A.1.

This study used 28 Kaplan turbines, having 8 m diameter runners, 25 MW power output rotating at a synchronous speed of 62.5 rpm with 47 channel sluices 17 m wide. The feasibility study carried out calculations for both ebb generation and ebb generation with flood pumping.

6.1. DoEn and UKAEA (1984)—621 MW barrage This study used 27 turbines, 7.6 m diameter each, rotating at 57.7 rpm with 18 sluice gates 12 m by 12 m. The study focuses on Ebb only generation with a maximum annual energy generation of 1320 GW h (DoEn and UKAEA, 1984). Using the same physical parameters, barrage location and optimum starting heads, this study gave an annual energy generation of 1360 GW h, an increase of 4.6%. It should be noted that the bathymetric data used in the 1984 study was not as accurate as data presently available, and the bathymetry used gave higher energy values. By accounting for this, the energy values in this study would be even greater than the DoEn study. The reason for this is largely due to the turbine hill chart used in this study and is discussed further in the conclusion.

6.2.1. Ebb generation only This used an optimum starting head and gave an annual energy generation of 1200 GW h (Mersey Barrage Company (MBC), 1992). Under the same operating conditions and barrage location, this study calculated an annual energy generation of 1274 GW h, an increase of 6.0%. 6.2.2. Ebb generation with flood pumping This used an optimum starting head giving an annual energy generation of 1390 GW h; however, the pumping head is unknown and a value of 1.6 m as in Libaux et al. (2011) study was used. Under these operating conditions, a net annual energy generation of 1519 GW h was calculated, producing a 9.3% increase. 6.3. University of Liverpool ‘Joule’ 2009—621 MW barrage This study used the same barrage conditions as DoEn and UKAEA (1984) study with an optimum starting head and minimum operating head of 1 m, exploring both ebb generation and flood generation with and without pumping (Burrows et al., 2009b).

6.3.1. Ebb generation only This gave an annual energy generation of 1070 GW h. Using the same barrage conditions and location 1302 GW h was calculated annually, indicating a 21.7% increase.

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6.3.2. Ebb generation with flood pumping This used flood pumping at high tide to a head of 1 m and gave an annual energy generation of 1130 GW h. Using the same conditions in this study, a net annual energy generation of 1420 GW h was calculated, this is a 25.69% increase. Although this study uses accurate LiDAR bathymetric data, the study is broad and less technically based than other studies using turbine characteristics from 1980 with low efficiencies and utilising sluicing coefficients of unity, giving lower energy calculations (Libaux et al., 2011).

of the current study to avoid Devil's Bank (Peel Energy, 2010), also increasing the size of the impounded area and the resulting energy calculations. These are analysed further below.

6.4.1. Ebb generation only Using the same barrage conditions as in the 2010 study and an optimised starting head gave an output of 1050 GW h annually. Under the same conditions, an annual energy output of 1259 GW h UK electricity consumption 01 Jan- 31 Jan 2009 60

6.4. PEEL/NWDA 2010/2011—700 MW barrage

55

Power Consumed (GW)

The first study undertaken was for a 700 MW barrage with the same size and number of turbines as in Mersey Barrage Company (MBC) (1992) study using bulb units and 18 sluice gates 12 m by 12 m. This study began with simple ebb generation with a fixed starting head of 3.9 m and the same barrage location as used in this study. This gave an annual energy generation of 900 GW h. The reason for this low figure was due to operation interruptions resulting in missed low tidal range cycles (Libaux et al., 2011). By altering the code slightly this model could be programmed to skip the same low tide cycles, thus allowing for a more accurate comparison (Fig. 12). Using these conditions, an annual energy output of 1088 GW h which is an increase of 20.9%. The studies which took place in 2011 used an optimum starting head which prevented tidal cycles being skipped, giving more realistic energy predictions. These studies did however change the location of the barrage to 300 m downstream

50

45

40

35

30 0

1000

2000

3000

4000

5000

Ebb Generation mode with Flood Pumping, Illustrating Change in Sea and Basin Level

Water Depth (m)

0

0

500

1000

1500

2000

2500

3000

3500

4000

0.1 hour iterations Sea Level

7

x 10

Barrage Level

Total Power Generated

8

Power Generated (W)

6 5 4 3 2 1 0

0

500

1000

1500

7000

Fig. 13. UK electricity consumption over a month in 2009 (National Grid, 2011).

5

-5

6000

Time in 0.1 hour intervals

2000

2500

3000

3500

4000

0.1 hour iterations Turbining Power

Pumping Power

Fig. 12. Fifteen day cycle using operating conditions for PEEL/NWDA 900 GW h 2010 study.

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was calculated using the model discussed in this paper, an increase of 19.9%. The possible reasons behind this difference in energy output are discussed further in the conclusion.

6.4.2. Ebb generation with flood pumping This used the same barrage conditions as the previous study with a pumping head of 1.6 m and the optimised starting head giving an annual energy generation of 1342 GW h. Using the same operating conditions, a net annual energy generation of 1508 MW h was calculated, producing a 12.4% increase in annual energy generation. It should be noted that the increase would be greater if the barrage location was changed to match the new barrage location used in these studies. The turbine calculations in this study are all based on La Rance reversible bulb turbine hill charts which were commissioned in 1966, with operating characteristics and efficiencies which are much lower than current turbine technology (Libaux et al., 2011).

77

The turbine hill chart used in this model (Fig. 8) was specially provided by Andritz Hydro for use with this model. Andritz Hydro is responsible for the turbines currently in use at the Sihwa Tidal Power Plant in South Korea, the largest tidal barrage currently in operation (Schneeberger, 2010). Ebb generation with flood pumping showed a lower net annual energy increase of 12%, compared to about 20% for ebb only generation. Due to the extensive inclusion of all the losses of the barrage for pumping as well as generation, higher pumping power consumption values were calculated, 80 GW h for this model compared to 63 GW h calculated by Peel/NWDA (Peel Energy, 2010). Using the lower pumping energy value calculated by Peel/NWDA, an increase of 14% in annual energy generated is given, and accounting for the higher impounded area of the estuary due to the location of the barrage, the actual figure is likely to be closer to 20% (Peel Energy, 2010). All the comparisons made to previous studies analysing the potential for tidal range energy from the Mersey estuary have been summarised in Appendix A.1.

Change in Sea and Basin Level Water Depth (m)

5

0

-5

0

1000

2000

3000

4000

5000

6000

7000

8000

6000

7000

8000

5000

6000

7000

8000

5000

6000

7000

8000

Power Generated (W)

0.1 hour iterations

8

x 10

Total Power Generated

8

6 4 2 0

0

1000

2000

3000

4000

5000

0.1 hour iterations

Power (W)

6

x 10

Total Electricity Demand

4

5

4

3

0

1000

2000

3000

4000

0.1 hour iterations

High or Low Power (W)

1

0.5

0

0

1000

2000

3000

4000

0.1 hour iterations Fig. 14. Continuous Ebb generation over a one month period. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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Change in Sea and Basin Level Water Depth (m)

5

0

-5

0

1000

2000

3000

4000

5000

6000

7000

8000

6000

7000

8000

5000

6000

7000

8000

5000

6000

7000

8000

0.1 hour iterations

Total Power Generated

Power Generated (W)

8

8

x 10

6 4 2 0

0

1000

2000

3000

4000

5000

0.1 hour iterations

Total Electricity Demand

4

Power (W)

6

x 10

5

4

3

0

1000

2000

3000

4000

0.1 hour iterations

High or Low Power (W)

1

0.5

0

0

1000

2000

3000

4000

0.1 hour iterations Fig. 15. Ebb generation only when electricity demand is high over a one month period.

7. Matching tidal barrage electricity generation to electricity demand As with the continuous cycles of the tides, the UK electricity consumption also follows a repeating pattern based on the time of day, temperature and season (Appendix A.2). When looked at over a one month period, the daily and weekly pattern becomes more apparent (Fig. 13). Using the average consumption trendline shown as the red line in Appendix A.2, it is possible to separate the times of high and low demand by their position above or below the trendline at any given time. Using this logic, it was possible to run a tidal generation cycle alongside the electricity consumption cycle, but only generating when the consumption or demand for electricity is high. Fig. 14 shows a standard one month cycle using continuous ebb generation and the corresponding electricity demand. The “high or low” curve illustrates whether the consumption is above or below the polynomial curve fitted to the data, shown in red.

This can be compared to Fig. 15 which shows a one month period with generation only taking place when the demand is high. This shows a far less continuous generation cycle with no electricity generation taking place when there is no demand. Although the actual operation of the barrage will be very different to this for environmental reasons as the water will be allowed to pass freely through the sluice gates instead of being stored in the basin, the power output during high demand will be the same, which is what is being focused on. When run over an entire year for ebb only generation, using the same conditions as in the PEEL/NWDA 700 MW barrage (Section 6.4), a decrease in annual energy generation of 26% when generating only when the demand is high. This shows that over a one year period 74% of the electricity produced is during times of high demand (Appendix A.3). This means the barrage can be operated by leaving the sluice gates open and allowing the basin to fill naturally with the ebb and flood of the tide during times of low demand and generating only when the demand is high.

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Physical Parameters

6.1. UKAEA & DoEn 1984

Operational Parameters

No. of turbines

Turbine diameter

Installed No. of Size of Capacity Sluices Sluices

27

7.6m

621MW

12m by 12m

18

Operating Mode

Starting Head (m)

Ebb only Generation

OPT

Stopping Head (m)

1.2

79

Annual Energy Production (GWh) Pumping Head (m)

Previous Study

Current Study

0

1,320

1,360

Percentage Notes: Increase

5%

Bathymetric data used not as accurate as current data, giving higher energy values.

28

8m

700MW

47

17m open channel

Ebb only Generation

OPT

1.2

0

1,200

1,274

6%

Very little is known about the operating conditions used for these calculations. The channel sluices are assumed to be submerged for the purpose of avoiding the use of weir channel flow equations.

28

8m

700MW

47

17m open channel

Ebb with flood pumping

OPT

1.2

1.6

1,390

1,519

9%

Pumping head used is unknownand may have been higher or lower changing the energy output.

7.6m

621MW

18

12m by 12m

Ebb only Generation

OPT

1

0

1,070

1,302

22%

7.6m

621MW

18

12m by 12m

Ebb with flood pumping

OPT

1

1

1,130

1,420

26%

28

8m

700MW

18

12m by 12m

Ebb only Generation

3.9

1.2

0

900

1,088

21%

6.4. PEEL/NWDA 28 2010/2011

8m

700MW

18

12m by 12m

Ebb only Generation

OPT

1.2

0

1,050

1,259

20%

28

8m

700MW

18

12m by 12m

Ebb with flood pumping

OPT

1.2

1.6

1,342*

1,508

12%

6.2. MBC 1992

27 6.3. University of Liverpool ‘Joule’ 2009 27

Turbine characteristics used are from Baker, 1980 with low efficiencies and utilising sluicing coefficients of unity, giving lower energy calculations Low tidal range cycles missing as with PEEL & NWDA calculations *Barrage location 300m downstream of location in this study, resulting bathymetry change will increase energy production as morevolume is captured

Fig. A1. Summary of previous studies and comparisons to current model results.

UK electricity consumption 01 Jan- 31 Dec 2009

4

6

x 10

Power Consumed (MW)

5.5 5 4.5 4 3.5 3 2.5 2 0

1

2

3

4

5

Time in Hours

6

7

8

9 4

x 10

Fig. A2. Annual UK electricity consumption for 2009, with 5th degree polynomial trendline following the mean power. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

8. Conclusion The model created in this project has allowed the exploration of many factors affecting tidal barrage operation as well as making comparisons to previous models which have used less advanced turbine hill charts or dated bathymetric data. As described in Section 6, the bathymetric data used in DoEn and UKAEA (1984) study yielded larger energy values than current more accurate data suggests, a comment also noted in the ‘Joule’ study by the University of Liverpool (Burrows et al., 2009a). Focusing on the latest study instead by Peel Energy Ltd and NWDA, the outputs from this model can be fully compared and analysed. The results of this model show that for ebb only generation, the annual energy generation is around 20% greater than the Peel and NWDA

results using the same parameters and for ebb generation with pumping about 10% greater. As the entire barrage losses are sufficiently accounted for and are similar to the values used by the Peel and NWDA study the differences in energy output are unlikely to be due to these losses (Libaux et al., 2011). The bathymetric data used comprises highly accurate Digital Survey Bathymetry and the tidal constituents used were provided by Admiralty (2011), these are therefore unlikely to be the reason for the higher energy calculations. It can therefore be deduced that the increase in annual energy generation is due to the turbine hill chart used in this study. As the Peel and NWDA study uses hill charts from La Rance Tidal Power Plant, a technology over 50 years old, the performance characteristics are very different to the Andritz performance envelope being used in this model. Even though the maximum efficiency was increased to 92% for the Peel and NWDA to better match current turbine efficiencies the turbines will seldom be operating at maximum efficiency and the overall operating efficiency will still be higher for the Andritz Hill Chart (Libaux et al., 2011). It should also be noted that the chosen operating path from the hill chart in this model is the maximum output curve, which may account for a portion of the increase in energy generation. The Andritz turbine model used also operates at a higher efficiency at lower heads than the La Rance model, which will be largely responsible for the increase in energy output where the average head for an entire year is around 1.5 m. Overall, the results from comparisons in this study show that under optimum operating conditions, the use of cutting edge lowhead double regulated bulb turbine technology can improve annual energy generation by around 20%. By utilising UK electricity consumption data from the national grid, it can be seen that although the energy generation of a tidal barrage is based on the ever-changing tidal cycle, 74% of the electricity generated is during times of high demand. A further optimisation which could be carried out would be to change the mode of operation to generate maximum electricity during times

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Water Depth (m)

Change in Sea and Basin Level 5 0 -5 0

1

2

3

4

5

6

7

8

9 4

x 10

Power Generated(GW)

0.1 hour iterations Total Power Generated 0.8 0.6 0.4 0.2 0 0

1

2

3

4

5

6

7

8

Power Generated (GW)

9 4

x 10

0.1 hour iterations

Total Electricity Demand

60 50 40 30 20 0

1

2

3

4

5

6

7

8

6

7

8

0.1 hour iterations

9 4 x 10

High or Low 1 0.5 0 0

1

2

3

4

5

0.1 hour iterations

9 4

x 10

Fig. A3. Ebb generation over a 1 year period with generation only taking place when demand is high; annual energy generation: 932 GW h.

of peak demand when the income per unit of electricity generated is highest. This technology does however require supplementation from other energy sources such as pumped storage during times when demand is high but the generation cycle is out of phase. The results from the testing of this model have also shown how optimisation carried out based only on the mode of operation, can significantly change the energy generation without requiring any change to the physical parameters of the barrage. This is an important consideration when designing a barrage with a lifetime of around 120 years, during which time energy demands and government policies are likely to change affecting the mode of operation and output required by the barrage thus requiring a barrage which has a dynamic range of operating modes which can comply with these changes.

Acknowledgements The authors would like to thank Lancaster University Renewable Energy Group, Mr Anthony Hatton at Peel Energy for his invaluable assistance and experience with the Mersey Tidal Project, Mr James Bain from Hydro Power Engineering Ltd for specific generator data and SeaZone Solutions Ltd for assistance with the bathymetric data. A special thanks also to Andritz Hydro for supplying the turbine data used in this research and Mr Peter Nowicki of Andritz Hydro for providing useful data on previous studies.

Appendix Sec Figs. A.1–A.3.

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