Energy Storage Technoecon Final Report_Revised March 2014

Comparison of battery, compressed air and power to gas
energy storage technologies in the Alberta context
Puneet Mannana
, Greg Badenb
, Leonard Oleinb
, Caitlin Brandona
, Brent Scorfielda
,
Nahid Nainib
, Jake Chengb
a
Alberta Innovates – Technology Futures, b
BECL and Associates Ltd
Techno-economics of
Energy Storage
Contact:
Puneet Mannan
Alberta Innovates – Technology Futures
Phone: (780) 450-5380
Email: Puneet.Mannan@albertainnovates.ca
November 19, 2013, revised March 24, 2014

Final Report
Version 1.0 Oct 17th
, 2011
Disclaimer
This Report was prepared as an accounting of work conducted by Alberta Innovates –
Technology Futures (AITF). All reasonable efforts were made to ensure that the work conforms
to accepted scientific, engineering and environmental practices, but AITF makes no
representation and gives no other warranty with respect to the reliability, accuracy, validity or
fitness of the information, analysis and conclusions contained in this Report. Any and all implied
or statutory warranties of merchantability or fitness for any purpose are expressly excluded.
The reader acknowledges that any use or interpretation of the information, analysis or
conclusions contained in this Report is at his/her own risk. Reference herein to any specified
commercial product, process or service by trade name, trademark, manufacturer or otherwise
does not constitute or imply and endorsement or recommendation by AITF.
This report is intended to add to the understanding of the technical and economic aspects of
energy storage. This report does not represent Government of Alberta policy, nor does it
anticipate or imply any future policy direction of the Government of Alberta.
Any authorised copy of this report distributed to a third party shall include an
acknowledgement that the report was prepared by AITF and shall give appropriate credit to
AITF and the authors of the report.
AITF confirms that the Alberta Department of Energy (ADOE) is entitled to make such additional
copies of this Report as ADOE may require, but all such copies shall be copies of the entire
Report. ADOE shall not make copies of any extracts of this Report without the prior written
consent of AITF.
Copyright AITF 2013. All rights reserved.

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ACKNOWLEDGEMENTS
This study was funded by the Alberta Department of Energy (ADOE) and the project team
gratefully acknowledges ADOE’s support for advancing the understanding of energy storage in
Alberta. The team is thankful to Christopher Holly, Susan Carlisle and their colleagues from the
ADOE for reviewing the report and providing valuable feedback.
Thanks also to Dave Teichroeb (Enbridge), Lorry Wilson (Rocky Mountain Power), Jan van
Egteren (Rocky Mountain Power) and Rob Harvey (Hydrogenics) for their technical guidance
throughout the project.

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EXECUTIVE SUMMARY
This Alberta Department of Energy funded study provides a techno-economic comparison of three
energy storage technologies – sodium sulphur batteries, compressed air storage and power to gas –
operating in conjunction with two wind power generating facilities under two operating strategies in the
Alberta electricity market. These energy storage technologies were selected for their maturity over a
broad range of applications from transmission and distribution grid support, to load shifting and bulk
power management, and well documented technical and operating parameters. The combination of two
operating strategies, Behind-the-Fence and Merchant, along with each technology and wind power
generating facility resulted in sixteen different scenarios or cases for modelling. The results of each case
were compared to a Base Case, the wind farm operating without energy storage, to determine the
revenue changes resulting from the modelled operation of the energy storage technology. In addition a
number of sensitivity cases were developed to further explore aspects of the results from sixteen
modelled cases.
The study used actual hourly wind production data from the Wintering Hills and the Castle River wind
power generating facilities. These wind farms were selected because they represent regions with
different wind characteristics. Wintering Hills is an 88-megawatt (MW) wind power generating facility
located in south-central Alberta. In 2012, Wintering Hills produced about 292 gigawatt hours (GWh) of
electricity resulting in a capacity factor of about 38 per cent. In addition to achieving one of the highest
capacity factors of all the wind power facilities in the province, Wintering Hills was also one of the most
consistent producing wind facilities in Alberta. Castle River is a 44 MW generating facility that in 2012
produced about 110 GWh of electricity, yielding a capacity factor of about 29 per cent. The Castle River
wind facility energy production was highly variable with a coefficient of variation of 1.1 versus Wintering
Hills with a coefficient of 0.9.
Hindcast mathematical models were prepared to analyse the economic benefit to a wind farm with
energy storage and a merchant energy storage operator. The model used actual market data for 2012
and inserted the energy storage facilities into the historical setting, and adjusted the historical electricity
prices to account for that insertion using a supply merit order curve for the historic electricity price. The
hindcast approach allowed for the retention of unique characteristics of the Alberta market price
volatility and the underlying correlation between wind generation and market prices. However, the
hindcast approach did introduce some distortion in the electricity market price (a price depression effect
which increases as more stored energy is withdrawn), but that distortion was kept to a small level by
limiting the energy storage facilities to 30 MW of charging and discharging capacity and by adjusting the
hourly market price for the effects of charging and discharging the energy storage capacity.
To model the dynamic effects of charging and discharging of an energy storage facility on the hourly
market price, a representative merit order curve was developed based on a sampling of 2012 merit
order curves. The merit order curve was used to calculate an adjustment to the hourly market price
resulting from the energy storage operation. The effect of withdrawing a quantity of electricity from
storage thereby increasing the hourly supply of electricity, reduced the hourly market price, and the
effect of injecting energy into storage was to increase hourly demand for electricity resulting in an
increase in the hourly market price.
The storage operations strategy was determined using a switch price – the price at which the preference
to charge switches to a preference to discharge and vice versa. The switch price was calculated each

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hour of the modelled year by an algorithm that used as inputs, the expected inventory level, current
average cost of inventory, and variable operating costs. The effect of the algorithm was as the inventory
level declined, the switch price increased up to a maximum price of $80 per MWh. Conversely, as
inventory levels rose the switch price declined, but never below the sum of the inventory cost and
variable cost. If the hourly price for electricity was less than the switch price, the model injected
electricity into storage; and, if the hourly price for electricity was greater than the sum of switch price
and the variable operating cost, the model discharged electricity from storage.
Behind-the-Fence operations strategy assumes that (1) the storage facility was controlled by the wind
farm operator; (2) the operator did not purchase any electricity from the grid; and (3) the combination
of storage discharge and wind output was constrained by the contracted transmission capacity at 50
MW. Merchant operations strategy assumes that (1) the storage facility was controlled by the operator
of a co-located 50 MW wind power generating facility; (2) the operator was free to buy or sell electricity
from or to the grid or from the co-located wind power facility; and (3) the combination of storage
discharge and wind output was constrained by the contracted transmission capacity of 50 MW. To
simplify the analysis, transmission charges were dealt with separately as a sensitivity case.
All the modelled cases shared these parameters: (1) the storage facility was co-located with 50 MW
wind power facility and shared 50 MW of transmission system access capacity with the wind power
generating facility; (2) 30 MW of charging and discharging capacity; and (3) 210 MWh of storage
capacity or seven hours of storage when charging or discharging at full capacity. For the storage
modelling exercise, the hourly output from each of the wind power generating facilities were
normalised to reflect an installed generating capacity of 50 MW. The process of normalising the
generating capacity for each wind power generating facility resulted in two hourly data sets with
Wintering Hills effectively producing about 168 GWh at an average price of $46.59/MWh and Castle
River producing about 143 GWh at an average price of $36.43/MWh.
The study has shown that co-locating an energy storage facility at a wind power generation facility
results in an increase in total revenues for the wind operator. Under the Behind-the-Fence operating
strategy, the selling prices achieved from storing electricity during low priced hours and withdrawing
and selling the stored electricity during higher priced hours were at a minimum 28 per cent higher to a
maximum of 50 percent higher than the average base cases selling prices for the modelled wind power
generating facilities. The higher selling prices were partially offset by losses and auxiliary energy
requirements related to the operation of each of the energy storage technologies reviewed, resulting in
net revenue changes of between 2 per cent and 45 per cent.
Wintering Hills realised the overall highest revenues in all cases using the Behind-the-Fence operating
strategy and in all but one case, achieved the largest percentage increase in revenues. The Castle River
case using the Behind-the-Fence operating strategy and a CAES energy storage system achieved a
slightly higher revenue increase (45.2%) on a percentage basis than the comparable case for Wintering
Hills (43.0%). The reasons for the slightly better percentage increase in revenue for Castle River are likely
related to variability of the Castle River output and the characteristic of a CAES energy storage facility,
which produces more energy, through the use of natural gas, than it stores. The modelled CAES energy
storage facility at Wintering Hills was likely constrained a few more hours due to the 50 MW
transmission capacity limit than the modelled CAES facility at Castle River was.
Similarly, under the Merchant operating strategy selling prices were between 30 per cent and 93 per
cent higher than the average selling prices in the base cases and resulted, after losses and auxiliary
energy requirements, in net revenue increases of between 9 per cent and 105 per cent compared to
base case revenues. In all of the cases modelled using the Merchant operating strategy the Wintering

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Hills cases achieved the highest overall revenues compared to the Castle River cases. Somewhat
unanticipated, the more variable wind power generation facility, Castle River, realised the largest
percentage revenue improvement from following the Merchant operating strategy for each of the
energy storage technologies.
The application of supply transmission service (STS) and demand transmission service (DTS) charges will
reduce the incremental net revenues associated with operation of an energy storage facility as modelled
by the study. Especially for the merchant storage facilities all electricity purchased from the grid and
stored will be subject to the DTS charges and when the same energy is withdrawn and sold, the energy
will be subject to STS charges. The tariffs charged in this case will result in double charging or what is
sometimes referred to as “rate pancaking”. However, in a CAES facility using natural gas, some
incremental quantity of electricity is generated over what was originally stored which would attract the
application of STS charges.
Two sensitivity cases were developed to examine the potential revenue improvements that could be
gained from participation in the Alberta operating reserve (OR) markets. The first scenario was based on
the Wintering Hills Merchant Battery case and participation in the active regulating reserve market for
the AM Super Peak block. The second scenario was based on the same Wintering Hills case and
participation in the standby spinning reserve market for the On Peak block. Overall, the opportunity to
participate in the OR markets was found to be attractive to energy storage operators, even though some
opportunities in the hourly energy market are forgone. The Wintering Hills Merchant Battery case was
chosen for modelling participation in both the active regulating reserve and standby spinning reserve
market, despite the fact that the current rules for spinning reserve limit participation only to generators,
to avoid introducing any uncertainty in results by using two different storage technologies. There is no
reason to believe the results for CAES or Power-to-Gas would be materially different from those
observed for batteries.
The introduction of the dynamic pricing (adjusting the hourly market price to account for the effects of
charging and discharging energy storage capacity) reduced the value of storage for the modelled
sensitivity cases. On a per unit basis, dynamic pricing had an impact on the value of storage of $5.59 per
MWh compared to static or unadjusted pricing. Dynamic pricing also reduced the average pool price by
$2.04 per MWh.
Increasing the storage capacity of the modelled cases does result in increased revenues, up to a point.
This study indicates that electricity market price volatility and shape of the supply merit curve appear to
be the key drivers for storage technology selection, sizing of energy storage capacity and charging and
discharging capacity.
Price volatility is a measure of how quickly prices change in a market that affects the value of storage
capacity and the value of injection and discharge capacity. As an example, a market with relatively low
price volatility, and characterised by higher winter and summer prices and lower prices in the interim
months would favour the bulk storage technologies – CAES and Power-to-Gas – with lower unit costs for
storage capacity. In the same market, storage capacity and charging and discharging capacity would
likely be sized to allow as much as a month of continuous discharging at the peak discharge rate.
Conversely, markets characterised by high price volatility, like Alberta, favour storage technologies that
can switch quickly from charging to discharging and that have lower charging and discharging costs. The
optimum storage capacity in Alberta for the current market size and characteristics appears to be about
three days at the peak discharge rate. Increasing the storage capacity beyond a few days results in
higher costs and the stored energy does not get sold because the higher market prices do not persist

ALBERTA INNOVATES – TECHNOLOGY FUTURES PAGE V
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long enough to allow the stored energy to be withdrawn. Increasing the discharge capacity also does not
appear to help as was found in one of the sensitivity case analysis.
Increasing the discharge capacity increases the potential available supply of electricity in any hour. The
larger the discharge capacity, the larger the dampening effect on market prices. The analysis of effects
of dynamic pricing showed that for Castle River dynamic pricing reduced the value of storage by over
$5.00/MWh. The discharge capacity of Castle River cases analysed was 30 MW so it is reasonable to
expect that the effect of increasing the discharge capacity from 30 MW to 300 MW would likely be
greater than $5.00/MWh.
The study concludes that:
1. Wind generation facilities whose electricity output varies considerably day-to-day may benefit from
installing energy storage capacity behind-the-fence of the wind facility.
2. Merchant energy storage may be the most attractive option for developing energy storage capacity
in Alberta.
3. The optimal storage capacity for a merchant energy storage facility appears to be about seventy
hours of capacity at the peak discharge rate.
4. Based on the simplified present value of revenue cash flows, publicly available capital cost for the
considered technologies and selling price of natural gas during the analysis period, CAES has the
most financially attractive business case for energy storage in Alberta.
5. The operating reserve markets are attractive markets for energy storage operators.
This study did not explore many of the other important aspects of energy storage, some of which could
be of special interest for Alberta as well as candidates for future work1
. For example, certain energy
storage configurations (e.g., adiabatic CAES and power-to-gas) could be candidates for lowering the
carbon intensity of energy production in Alberta. Diesel power generation with energy storage could be
explored for remote applications. Power-to-gas provides opportunities for interplay between electricity,
gas and heat markets, and how energy storage could optimally play in those markets is yet to be
understood. Power-to-gas generates an energy vector, hydrogen, which could be channelled into
different value propositions (transportation and heating fuel, and chemicals production) and those value
propositions could be explored within the Alberta context.
1
Impacts related to electricity market operation and rules and transmission and distribution infrastructure are
being considered by the Alberta Electric System Operator.

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TABLE OF CONTENTS
Acknowledgements.......................................................................................................................... i
Executive Summary..........................................................................................................................ii
TABLE OF CONTENTS......................................................................................................................vii
LIST OF TABLES................................................................................................................................ix
LIST OF FIGURES...............................................................................................................................x
1. Introduction............................................................................................................................ 1
1.1 Current study objectives and scope ............................................................................................1
2 Benefits of energy storage..................................................................................................... 4
3 The Alberta electricity market............................................................................................... 5
3.1 Update.........................................................................................................................................5
3.2 Current market rules ...................................................................................................................6
4 Storage technologies under evaluation ................................................................................ 7
4.1 Rationale for selection.................................................................................................................7
4.2 Sodium-Sulphur Batteries............................................................................................................8
4.2.1 Description ..............................................................................................................................8
4.2.2 Cost..........................................................................................................................................8
4.3 Compressed Air Energy Storage ..................................................................................................9
4.3.1 Description ..............................................................................................................................9
4.3.2 Costs......................................................................................................................................11
4.4 Power to gas..............................................................................................................................11
4.4.1 Description ............................................................................................................................11
4.4.2 Cost........................................................................................................................................14
5 Model Description................................................................................................................ 15
5.1 Methodology .............................................................................................................................15
5.1.1 Bid and Offer Strategy...........................................................................................................15
5.1.2 Prices.....................................................................................................................................16
5.1.3 Effects on Hourly Clearing Price............................................................................................17
5.1.4 Wind Power Facility Selection...............................................................................................19
5.1.5 Storage operation .................................................................................................................20
5.2 Modelling Parameters...............................................................................................................20
5.2.1 Description of model cases ...................................................................................................20
5.2.2 NaS Battery............................................................................................................................21
5.2.3 CAES ......................................................................................................................................23
5.2.4 Power to Gas 1 ......................................................................................................................24
5.2.5 Power to Gas 2 ......................................................................................................................25
5.2.6 Sensitivity Cases ....................................................................................................................26
6 Results................................................................................................................................... 30
6.1 Modelled Cases..........................................................................................................................30

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6.1.1 NaS Battery Cases..................................................................................................................30
6.1.2 Compressed Air Energy Storage............................................................................................33
6.1.3 Power-to-Gas 1......................................................................................................................36
6.1.4 Power-to-Gas 2......................................................................................................................37
6.2 Sensitivity Cases.........................................................................................................................39
6.2.1 Transmission Demand and Supply Charges ..........................................................................39
6.2.2 Operating Reserve Market....................................................................................................41
6.2.3 Increased Storage..................................................................................................................42
6.3 Comparison to the 2011 Study Results .....................................................................................45
6.4 Simple Cashflow Analysis ..........................................................................................................46
7 Discussions............................................................................................................................ 47
7.1 Overall .......................................................................................................................................47
7.1.1 Effects of the Behind-the Fence and Merchant Operating Strategies..................................47
7.2 NaS Battery Energy Storage.......................................................................................................47
7.3 CAES...........................................................................................................................................48
7.4 Power-to-Gas 1..........................................................................................................................48
7.5 Power-to-Gas 2..........................................................................................................................49
7.6 Transmission Demand and Supply Charges...............................................................................49
7.7 Increased Storage......................................................................................................................50
7.8 Capital Costs ..............................................................................................................................51
8 Conclusions........................................................................................................................... 52
9 Recommendations ............................................................................................................... 53
10 References ............................................................................................................................ 54
11 Appendices ............................................................................................................................. 1
A. Alberta’s electricity market..................................................................................................... 1
A.1. Alberta Electric System Overview................................................................................................1
A.2. Market Structures........................................................................................................................1
A.3. Demand .......................................................................................................................................2
A.4. Supply ..........................................................................................................................................3
A.5. Wholesale Electricity Market.......................................................................................................4
A.6. Market Operation........................................................................................................................5
A.7. Pool Prices ...................................................................................................................................6
A.8. Potential Value of Wind plus Energy Storage in the Energy Market...........................................6
A.9. Ancillary Services Markets...........................................................................................................8
A.9.1. Operating Reserve Products ...................................................................................................8
A.9.2. Operating Reserve Market....................................................................................................10
B. CCEMC Backgrounder ............................................................................................................. 1
C. TransCanada Gas Quality Specifications................................................................................. 1
D. Power to Gas Announcement................................................................................................. 1

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LIST OF TABLES
TABLE 1: SUMMARY OF MODELLED CASES .................................................................................................................21
TABLE 2: NAS BATTERY CASES - OPERATIONAL RESULTS ............................................................................................30
TABLE 3: NAS BATTERY CASES - FINANCIAL RESULTS ..................................................................................................30
TABLE 4: NAS BATTERY CASES - EFFICIENCY RESULTS .................................................................................................32
TABLE 5: CAES CASES - OPERATIONAL RESULTS ..........................................................................................................33
TABLE 6: CAES CASES - FINANCIAL RESULTS................................................................................................................33
TABLE 7: COMPARISON OF REVENUES AND PRODUCTION – CASTLE RIVER CAES......................................................35
TABLE 8: COMPARISON OF REVENUES AND PRODUCTION – WINTERING HILLS CAES ...............................................35
TABLE 9: CAES CASES – EFFICIENCY RESULTS ..............................................................................................................36
TABLE 10: POWER-TO-GAS 1 - OPERATIONAL RESULTS ..............................................................................................36
TABLE 11: POWER-TO-GAS 1 - FINANCIAL RESULTS ....................................................................................................36
TABLE 12: POWER-TO-GAS 1 - EFFICIENCY RESULTS ...................................................................................................37
TABLE 13: POWER-TO-GAS 2 - OPERATIONAL RESULTS ..............................................................................................37
TABLE 14: POWER-TO-GAS 2 - FINANCIAL RESULTS ....................................................................................................38
TABLE 15: POWER-TO-GAS 2 - EFFICIENCY RESULTS ...................................................................................................38
TABLE 16: WINTERING HILLS BATTERY BEHIND-THE-FENCE CASE WITH STS ..............................................................39
TABLE 17: CASTLE RIVER CAES BEHIND-THE-FENCE CASE WITH STS...........................................................................40
TABLE 18: WINTERING HILLS BATTERY MERCHANT CASE ...........................................................................................40
TABLE 19: CASTLE RIVER CAES MERCHANT CASE........................................................................................................41
TABLE 20: OPERATING RESERVE MARKET SENSITIVITY RESULTS – WINTERING HILLS BATTERY MERCHANT CASE....41
TABLE 21: INCREASED STORAGE CAPACITY SENSITIVITY RESULTS – WINTERING HILLS CAES MERCHANT CASE........42
TABLE 22: INCREASED STORAGE CAPACITY SENSITIVITY RESULTS – WINTERING HILLS POWER-TO-GAS 1 MERCHANT
CASE ...................................................................................................................................................................43
TABLE 23: COMPARISON OF BATTERY RESULTS FOR CASTLE RIVER ...........................................................................45
TABLE 24: SIMPLE CASHFLOW ANALYSIS.....................................................................................................................46

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LIST OF FIGURES
1
FIGURE 1: LOCATION OF WIND FACILITIES....................................................................................................................1
FIGURE 2: SYSTEM BOUNDARY FOR THE MODEL..........................................................................................................2
FIGURE 3: ENERGY STORAGE OPERATING CASES MODELLED ......................................................................................3
FIGURE 4: E.ON POWER-TO-GAS FACILITY.............................................................13
FIGURE 5: DISTRIBUTION OF HOURLY ELECTRICITY PRICE - 2012 ...............................................................................16
FIGURE 6: DAILY NATURAL GAS PRICES - 2012............................................................................................................17
FIGURE 7: TYPICAL ALBERTA SUPPLY MERIT ORDER CURVE .......................................................................................18
FIGURE 8: DETERMINING THE ADJUSTED MARKET PRICE...........................................................................................19
FIGURE 9: NAS BATTERY ENERGY BALANCE ................................................................................................................22
FIGURE 10: AUXILIARY ENERGY REQUIREMENT ..........................................................................................................22
FIGURE 11: CAES ENERGY BALANCE ............................................................................................................................23
FIGURE 12: POWER-TO-GAS ENERGY BALANCE ..........................................................................................................25
FIGURE 13: POWER-TO-GAS 2 ENERGY BALANCE .......................................................................................................26
FIGURE 14: CASTLE RIVER BATTERY CASES OCTOBER 22 - 24 ....................................................................................31
FIGURE 15: WINTERING HILLS BATTERY CASES OCTOBER 22 – 24..............................................................................32
FIGURE 16: CASTLE RIVER CAES CASES OCTOBER 22 - 24............................................................................................34
FIGURE 17: WINTERING HILLS CAES CASES OCTOBER 22 - 24.....................................................................................34
FIGURE 18: PTG 1 SENSITIVITY CASES – UTILIZATION OF INCREASED ENERGY STORAGE CAPACITY ..........................44
FIGURE 19: PTG 1 SENSITIVITY CASES – UTILIZATION OF INCREASED ENERGY STORAGE CAPACITY ..........................44

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1. INTRODUCTION
Energy storage technologies convert electricity into other forms of energy that can be stored
and retrieved on demand. Energy can be stored, as chemical energy in the case of batteries; as
potential energy in the case of pumped hydro; as kinetic energy in the case of flywheels; as
compressible potential energy in the case of compressed air; and as chemical energy and
compressible potential energy in the case of power-to-gas (PtG). This study presents the results
of a modelling exercise using three energy storage technologies – power-to-gas, sodium sulphur
batteries and compressed air, co-located at two existing wind generation facilities under two
operating strategies within the Alberta electricity market.
PtG requires a special note at the very outset. It is a novel energy storage technology where
excess electricity is used to produce hydrogen through electrolysis of water. Hydrogen gas can
be stored by injection into either the natural gas pipeline system or geological structures, and
converted back into electricity or it can be delivered to consumers as low-carbon heat or low-
carbon transportation fuel. The potential also exists to use PtG to link the growing hydrogen
demand, for oil refining/upgrading. Section 5.0 provides a summary of the modelled
technologies and their energy storage operating cases.
1.1 CURRENT STUDY OBJECTIVES AND SCOPE
This study expanded on the scope of the 2011 study by AITF – Energy Storage: Making
Intermittent Power Dispatchable (Andy Reynolds,
et al.), (hereinafter referred to as the 2011 study) –
which looked at the relative maturity of various
energy storage technologies, reviewed Alberta’s
energy and ancillary services markets, and
conducted financial analysis for determining
effective storage operating rules and cost-benefits
for pursuing the opportunities identified for a wind
farm. The objective of the current study is to
advance the techno-economic understanding of
selected energy storage technologies in the Alberta
context.
Key differences between the 2011 study and the
current study are described in the following
paragraphs.
The current study uses actual hourly wind
production data from the Wintering Hills and the
Castle River wind generation facilities (Figure 1) and
hourly market prices from 2012. The previous
study used data from the Castle River and Chin
Chute wind power generating facilities and hourly Figure 1: Location of Wind Facilities

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market prices from 2007 to 2010. Chin Chute was replaced with Wintering Hills to capture the
effects of the revenue of wind profile for a location other than the area where the majority of
the operating wind generation facilities in Alberta are located, i.e., the Pincher Creek –
Medicine Hat region in southern Alberta.
The current study considers both Behind-the-Fence and Merchant operations of three different
storage technologies – the sodium-sulphur battery, compressed air energy storage and power
to gas – whereas, the previous study considered only behind-the-fence operation of two
storage technologies (batteries and compressed air). Comparison of both Merchant and
Behind-the-Fence energy storage allows for a more complete exploration of the value of
storage within the Alberta electricity market.
The Behind-the-Fence operation assumes that the energy storage operation is co-located with a
wind power generating facility and buys electricity only from that wind power generating
facility for storing. Whereas, the Merchant operation assumes the energy storage facility, even
though co-located at the wind power generating facility, is controlled by an independent entity
that buys and sells electricity to capture price arbitrage or other electricity market
opportunities. The Merchant operator buys electricity off the grid or under contract with a wind
or other renewable energy facility. The modelling of the Merchant operation provides insight
into the potential revenues and costs of an independent energy storage operator, an entity that
does not exist in the Alberta electricity market currently. The Base Case models the wind power
generating facility without energy storage.
This study aims to define and quantify the value of PtG, battery and compressed air energy
storage technologies in the Alberta electricity market. Mathematical modelling is used to
determine the potential value of each energy storage option. Figure 2 shows the boundary for
the mathematical model.
Figure 2: System Boundary for the Model
Electricity
(Fossil fuel,
Hydro, etc.)
Electricity
(Wind
generated)
Merchant
Operation
Behind the
Fence
Operation
Electric
Grid Conversion
Technology Energy Storage
(Limited
capacity)
Electricity
Generation
Other
Applications
Performance
Indicators
Financial
GHG
Benefits
Other
Indicators
Modelling
Boundary

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For each wind facility eight energy storage operating cases are considered as shown in Figure 3
below. Additional cases are included as the sensitivity cases of some of the operating cases.
Figure 3: Energy Storage Operating Cases Modelled
Two versions of PtG are examined – one version models hydrogen being stored in an
underground storage cavern and being used in a fuel cell to generate electricity and the other
version models hydrogen being transported and stored in a natural gas storage facility and
burned in a conventional natural gas-fired combined cycle generation facility. Specific details on
each modelled case are presented in Section 5.
The study and modelling parameters adhered to the rules and processes of the Alberta
electricity market and performance limits of each of the storage technologies. Furthermore,
offers to sell or bids to purchase electricity were based on the information that would have
normally been available to a storage operator at the time the operator would have submitted
an offer or bid. In fact, the switch price mechanism, described in Section 5, used the current
hour valuation of the inventory and inventory level to calculate hourly offers and bids and not a
forecast of the future hourly price. If the actual market price in any hour was less than the
switch price the operator was deemed to have purchased electricity and if the market price was
higher than the switch price the operator was deemed to have sold electricity.
The presented cases are not optimised in the sense of what a generation developer would
normally do to build a business case for an energy storage project that achieves a maximum
return at an acceptable level of risk. Instead, the case results provide an indication of the
potential value (in terms of revenue) of energy storage in the Alberta electricity market when
combined with intermittent generating resources such as wind power.
The sensitivity cases explore the potential incremental returns from participation in the
operating reserve markets and increasing the size of the storage capacity. Two examples of the
potential of incremental revenues available to energy storage operators from participation in

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the operating reserve market are modelled. While the exercise is not a complete analysis, the
two examples provide an indication of the potential revenues available from participation in the
regulating reserve and standby spinning reserve markets. The effects of expanding the energy
storage capacity are examined in four examples, two of which are based on compressed air
storage and two based on power-to-gas.
The current study models the effects of selling stored electricity on the hourly market price,
whereas, the previous study did not consider the dynamic effects of storage on electricity price.
The effects of selling stored electricity from a single energy storage facility (such as the ones
modelled in this study) are not, in an overall sense, found to be that significant on the hourly
market price. A greater penetration of energy storage capacity in the supply mix will likely
dampen the hourly price volatility and reduced the frequency of extreme high and low hourly
prices. However, the effort to model the price effect does represent an improvement over the
previous study.
In short, this study is intended to provide insights to developers, renewable generation owners
and operators and policy makers of the benefits and costs of the application of energy storage
in the Alberta electricity market.
2 BENEFITS OF ENERGY STORAGE
What differentiates energy storage technologies from typical generation or load and makes
them valuable is the ability to quickly switch from behaving like a generator to behaving like a
load in response to market price signals. The 2011 AITF study identified benefits to wind power
generators from the use of behind-the-fence energy storage to allow generators to “time-shift”
energy sales from low priced hours to higher priced hours. Various studies (e.g. Eyer, J. and
Corey, G., 2010) have identified benefits from energy storage applicable to virtually all
segments of the electric supply chain. Beyond time shifting, energy storage facilities are able to
supply virtually all forms of ancillary services from active regulation to stand-by load shedding
and black start. Energy storage can also be strategically located to reduce transmission
congestion and defer investment in new transmission or distribution capacity. All that said, so
far no new unique ancillary services have been developed based on energy storage
technologies. Energy storage will, no doubt bring new competitors and operating strategies to
the ancillary services markets.
Energy storage is also widely recognised as the enabling technology for integrating the
electricity generated by intermittent renewables with the electric grid. It was the ability of
energy storage technologies to balance the intermittency of renewable generation that was
initially recognised. What this study shows is that energy storage technologies can also improve
the economic returns of intermittent renewable generation. The combination of renewably
generated electricity and energy storage could be one of the options for reducing the
greenhouse gas emission intensity of power generation in Alberta and elsewhere.

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3 THE ALBERTA ELECTRICITY MARKET
3.1 UPDATE
Since the previous dispatchability study was completed in 2011, a number of changes have
occurred in the Alberta’s electricity market. Some significant changes that require mention
within the context of the current study are:
 Installed wind power generating capacity increased from just under 800 MW to
almost 1,100 MW, an increase of 40 per cent over two years. At the same time, total
installed generating capacity increased by about 1,300 MW or 10 per cent.
 The Alberta Electric System Operator (AESO) initiated a review of market rules and
standards applicable to energy storage facilities with intent of identifying changes
that may be required to ensure energy storage facilities have fair and equal access to
the Alberta electricity market. Subsequently in June 2013, the AESO issued a paper
detailing issues identified during its initial evaluation of energy storage integration.
Following up on the issues paper, the AESO seeking industry input, set up a working
group to provide input on the issues and ideas for changes that will form the basis of
a discussion paper to be issued in 2014.
 From a technology demonstration perspective, Suncor Energy and Teck were
selected by the Climate Change and Emissions Management Corporation (CCEMC) to
receive about $9 million in funding for a proposed three megawatt / six point nine
megawatt-hour battery energy storage facility at the companies’ Wintering Hills
Wind Power Project. The proposed project will test the feasibility of shifting power
from off-peak periods to on-peak periods and participation in the ancillary service
markets. A copy of the CCEMC announcement can be found in Appendix C.
 Enbridge is actively pursuing PtG projects in Alberta.
 System Access Service Requests (SASR) have been filed with the Alberta Electric
System Operator (AESO) for three energy storage projects:
 the previously mentioned Wintering Hills Battery Project;
 AltaLink Investment Limited Partnership’s battery energy storage for wind
integration (8.5 MWh of storage capable of supplying up to 20 MW (+/- 10 MW) of
regulating reserve and 12 MW of spinning reserve).
 Rocky Mountain Power’s proposed Alberta Saskatchewan Intertie Storage (ASISt)
project, which will include 150 MW of compressed air energy storage capacity, to
be located in the Lloydminster area along the Alberta Saskatchewan border.

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3.2 CURRENT MARKET RULES
The Alberta electricity market rules, technical standards and tariffs do not recognise the unique
attributes of energy storage technologies. Other than for a few more recent changes, the rules
and technical standards predate the latest advances in energy storage technologies. The AESO
has recognised by way of the issues paper and the energy storage working group that some of
the rules, technical standards and tariff may need to be changed to ensure it abides by its
duties to operate a fair, efficient and openly competitive market with respect to energy storage
developments.
The current AESO tariff would require a transmission grid-connected Merchant energy storage
facility operating in Alberta to be treated as both a generator and a load, and hence subject to
the demand transmission service tariff (DTS) and supply transmission service tariff (STS). For a
transmission grid connected Behind-the-Fence energy storage facility located within the fence
of an operating wind power generating project, the wind power generating facility will pay the
STS tariff for electricity delivered directly to the grid and the energy storage facility will pay the
STS for electricity that is stored and delivered at a later time to the grid. Since, a Behind-the-
Fence energy storage facility will not purchase electricity from the grid it will not pay a DTS
charge. The effects of the tariff charges on both Merchant and Behind-the-Fence energy
storage facilities were modelled and are presented in Section 6.
Given that at this time there are three energy storage projects under development in Alberta,
there is some urgency for the AESO to deal with any barriers that might unfairly reduce or
restrict participation by these projects in the energy and operating reserve markets.

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4 STORAGE TECHNOLOGIES UNDER EVALUATION
This section briefly describes the selected storage technologies and their technical parameters.
4.1 RATIONALE FOR SELECTION
The technologies chosen for this study were:
1. Sodium sulphur battery (NaS)
2. Compressed air energy storage (CAES)
3. Power to gas (PtG)
The rationale for selecting these technologies remains essentially the same as the 2011 study:
selecting technologies that are reasonably mature for grid scale implementation, and for which
the technical and operating constraints are well documented. Additionally, the selected
technologies represent a broad range of application areas from transmission and distribution
grid support, to load shifting and bulk power management.
NaS is a relatively small-scale storage technology that has been deployed in a number of
projects worldwide. NaS batteries exhibit asymmetry in parasitic thermal loads that results in
lower overall efficiencies compared to other newer battery technologies such as lithium ion.
CAES on the other hand is a well understood, large-scale storage system technology. The CAES
system components (e.g. compressors, turbines etc.) are generally mature technologies. One
aspect that is unique about conventional CAES operations is the exposure to natural gas price
risk. NaS and CAES are by far the two storage technologies of greatest planned future
deployment (Bloomberg, 2011; quoted in Reynolds A., et al, 2011).
PtG is a newer energy storage concept. The individual technical components of the PtG route,
which uses electrolysis to produce hydrogen and then converts the produced hydrogen, after
blending with natural gas, back to electricity, are technically mature. Continuous improvements
are underway for more efficient electrolysers and turbines that could use hydrogen directly.
The technologies for using hydrogen for generating electricity directly (i.e. fuel cells, or
reversible solid oxide fuel cells) are at various stages of technical maturity. PtG was selected
because it is the only technology that could have multiple value propositions:
 injecting hydrogen into natural gas system and using it for its heating characteristics
as a blend with natural gas;
 using the produced hydrogen for industrial applications (for bitumen upgrading and
as a precursor chemical etc.) to lower the emissions;
 injecting hydrogen into natural gas storage facility and later withdrawing the
hydrogen mixed with natural gas to fuel a combined cycle generator; and
 storing the hydrogen and withdrawing it later to use in a fuel cell to generate
electricity.

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The potential for multiple value propositions make this technology somewhat more complex to
model and quantify.
4.2 SODIUM-SULPHUR BATTERIES
4.2.1 Description
The NaS battery is the most mature battery technology and represents the majority of existing
and planned grid-scale battery installations. For this reason, there is a large body of publicly
available information about NaS battery operation and performance to draw on for modelling
purposes. While advances have been made in alternative battery chemistries, there is currently
much less publicly available information on the operation and performance of those battery
chemistries.
The normal operating temperature range of a NaS battery is between 300 and 340 degrees
Celsius. One of the operational challenges with NaS batteries is that the charging reaction is
endothermic and the discharging reaction is exothermic, necessitating charging and discharging
limits to help maintain temperatures within the operating temperature range and an external
heat source to maintain battery temperatures as required.
NGK of Japan remains the only manufacturer of grid-scale sodium-sulphur batteries, which
were commercialised as the NaS battery in 2002. The NaS battery cells are packaged into
modules with specified AC power capacity of approximately 400 kW. Each module is thermally
insulated, and equipped with resistance heaters for temperature control. NGK reports a module
standby heating requirement of 3.4 kW for a power storage module.
Currently, the largest individual installation of NaS battery technology is 70 MW, with 490 MWh
planned for Italy in 2013. Estimates for AC-AC round trip efficiency of the NAS battery is around
80 per cent (EPRI, 2010).
4.2.2 Cost
Capital costs are in the range of $3,100-3,300/kW or $520-550/kWh (EPRI, 2010). Regular
maintenance suggested by NGK includes continuous remote monitoring, physical inspections
every 3 years, and adjustment of the module enclosure vacuum every 1,000 cycles to control
standby heat loss. Based on existing installations, NGK estimates labour of 3 hours per 400kW
module based on installations of 20 modules or greater.
The NaS operating life is affected by the depth of discharge: NGK states that 2,500 cycles are
possible with 100 per cent depth of discharge (DOD), 4,500 cycles for 90 per cent DOD, and
6,500 cycles for 65 per cent DOD. End of life costs are expected to be low. NGK estimates that
98 per cent of the NaS battery materials can be recycled.

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4.3 COMPRESSED AIR ENERGY STORAGE
4.3.1 Description
In a CAES system, energy is stored as compressed air, which is later expanded through a turbine
or a series of turbines to generate electricity. A CAES system, in the simplest terms, is
comprised of a compressor, an air storage chamber and a gas turbine generator.
Currently, there are two grid-scale CAES systems in operation: one in Huntorf, Germany (since
1986) and one in McIntosh, Alabama (since 1991). Both store air in caverns excavated in
underground salt formations. The Huntorf CAES system is capable of providing 290 MW for up
to two hours. Comparatively, the McIntosh CAES system provides 110 MW with a 26-hour
discharge time and a ramp up time of only 14 minutes.
CAES is the only storage technology, other than pumped hydro storage, that has been
demonstrated on a large scale (+100 MW). A number of new CAES projects are being
developed:
 Apex Bethel Energy Center, Texas 317 MW CAES project that is expected to initiate
construction in early 2014. Apex recently awarded Dresser Rand a contract for the
manufacture of the compression and expansion trains.
 In Larne, Northern Ireland, Gaelelectric is investigating the feasibility of developing a
CAES project.
 ADELE an adiabatic compressed air energy storage demonstration project is under
development by RWE in Germany. Construction is expected to start in 2016 with
commissioning planned for 2020.
Some of the advantages of CAES are:
 compression and generation capacity can be developed in modules and easily
expanded by adding more modules;
 energy storage capacity, which is limited by the volume and pressure of the
reservoir, can be increased relatively economically; and
 the operational flexibility allows a CAES facility to compete in both ancillary service
and energy markets.
Conventional CAES systems are diabatic where some of the heat energy generated during
compression is lost. Energy lost during compression is compensated through the use of natural
gas in the expansion phase, making CAES sensitive to the price of natural gas. Storage
efficiencies of the currently operating conventional CAES systems are reported as 42 per cent
(Huntorf) and 54 per cent (McIntosh).
Alternative compressed air techniques are being explored to minimize heat loss and improve
efficiency. The German ADELE CAES is attempting to achieve 70 per cent efficiency with an
adiabatic compression process where heat loss during compression will be stored and used
during expansion. The ADELE plant is not expected to enter production prior to 2020.

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This study used conventional CAES technology in the modelling with an estimated overall
efficiency of about 50 per cent.
4.3.1.1 Storage
Salt cavern storage of liquids (oils, naphtha, kerosene, gasoline) and liquefied hydrocarbons
(LPG) are well established and operate with “brine compensation” to manage pressure. In this
case, brine is injected into the bottom of the cavern and an equivalent amount of stored liquid
is withdrawn. For storage of gaseous hydrogen, the hydraulically compensated system would
provide pressure regulation through control of the hydraulic head. The disadvantage of brine
compensation is the requirement to store large quantities of brine on the surface. Pressure
regulation in the cavern could also be provided using ‘cushion gas,’ which is the volume of the
gas that permanently resides in the cavern as inventory for providing adequate pressure and
deliverability rates during the withdrawal of gas from the reservoir. For CAES, the US
Department of Energy (USDOE) is researching the use of supercritical carbon dioxide as the
cushion gas2
for its carbon sequestration benefit. The cost of the cushion gas inventory, the
difference between the density of hydrogen and cushion gas (tendency to mix), their tendency
to react and the need for a gas separation unit on the surface are some of the factors that
would determine if the use of cushion gas is a better alternative than hydraulic compensation.
It is however understood that there may either be no salt deposits or unsuitable salt deposits at
the wind farms selected for this study. Cavern storage has been assumed for those sites to
understand how energy storage economics will unfold in the Alberta context if that indeed was
the case.
Thinner and deeper salt deposits compared to those used in the existing CAES operations exist
in the eastern half of the province, and that reduces their functionality for cavern development.
The salt beds shallow towards the north-east. East of 111 degrees longitude, salt deposits exist
above 1 km depth; this is approaching the depths of caverns for existing CAES operations.
As well, the salt deposits in Alberta are all bedded salts. Compared to the domal salts used for
the caverns at both the Huntorf and McIntosh plants, bedded salts are thinner, and generally
less pure. Since total energy output of a CAES plant is dependent on the reservoir volume, for a
given plant design, smaller diameter caverns can be constructed in thicker salts; caverns mined
from salt domes can be tall and narrow with minimal roof spans as is the case at both the
Huntorf and McIntosh CAES facilities. Multiple caverns, or caverns with large aspect ratios are
required in thinner salt beds. Multiple caverns will increase construction cost. Large aspect
ratios exacerbate structural problems associated with material creep, which is of concern in salt
cavern stability (Bachu and Rothenburg, 2003; DeVries, 2005). The depth of salts in Alberta
(1000 - 2000 m) increases the in-situ stress. The caverns must also be really large since the salt
is thin in comparison to those used at the existing CAES plants. These two factors mean that
2
See http://techportal.eere.energy.gov/technology.do/techID=115

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maintenance of the stability of the salt cavern may be more difficult in any Albertan CAES
projects than at the existing sites.
The presence of impurities in the salt beds also complicates cavern development. Durable
impurities, such as clay lenses or anhydrite beds in the salt might further compromise the
structural integrity of the cavern by introducing inhomogeneities in the material properties of
the material hosting the cavern. They will also remain behind during solution mining of the
cavern, filling the cavern bottom with a rubble layer and reducing its effective volume. Further
complexities are caused by the presence of soluble impurities in the salt beds that may dissolve
preferentially during the solution mining (and in the pressure compensating brines, if these are
used), and lead to difficulties in controlling cavern development. The Lower and Upper Lotsberg
salts are very pure, but anhydrite layers and sylvite (potassium chloride) are common impurities
in the Prairie Evaporite (Grobe, 2000). Although the Prairie Evaporite is the most extensive salt
deposit in the province, the presence of these impurities may greatly increase the cost of
cavern development in those salts.
Based on the above considerations, any perspective CAES operations in Alberta utilising salt
reservoirs should strive to keep cavern volumes small, which means operating using a
compensated cavern design. Optimal cavern sizing requires a good understanding of the cycling
frequency of the power generation phases prior to construction; such an understanding must
be established early in any planning phase.
4.3.2 Costs
Typical overnight capital costs reported by the referenced sources for a CAES plant range from
$1,100 to $1,300 per kW of installed generating capacity. These figures are in U.S. dollars and
vary with the size and design of the plant and do not include the cost of the storage reservoir.
Storage costs vary substantially between surface and sub-surface storage with subsurface costs
reported in the range of $11 to $17 USD per kWh and surface costs in the range of $115 to
$180 USD per kWh. Obviously, the cost of subsurface storage is greatly dependent on the
subsurface geology of the site selected for the CAES facility.
4.4 POWER TO GAS
4.4.1 Description
Power to gas refers to the generation of hydrogen from electrolysis of water using electricity,
followed by the storage of the hydrogen gas and ultimately the conversion of hydrogen back to
electricity.
4.4.1.1 Electrolysis
In the past few years advances in the alkaline electrolyser technology has led to improvements
in efficiency and operating current density while reducing capital cost for a specified hydrogen
output rate. Hydrogen production volumes of 500 – 760 Nm3
/h are possible, corresponding to

Final Report
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electric power consumption of approximately 2,150 – 3,534 kW. The operating temperature
range is controlled at generally between 5 – 100 degrees Celsius.
To prevent conditions that could lead to the formation of flammable gas mixtures, production
rates are typically limited to 25 – 100 per cent of the nominal range. Above the minimum
operating rate, the electrolyser operation can rapidly follow the input power and DC current.
The purity of hydrogen and oxygen produced can reach 99.9 and 99.7 volume per cent,
respectively. In order to operate safely and protect electrodes from damage, the purity of
water input to the electrolyser must be high with an electrical conductivity below 5µS/cm.
In a typical installation, several electrolyser units are connected together with additional
pressure chambers, cooling systems and control electronics. Control electronics can selectively
turn off individual electrolysers to maintain minimum operation rates on remaining “on” units.
The electrode lifetime is not strongly affected by cycling. With control electronics, the
electrolyser stacks are generally robust to fluctuating power sources and the efficiency of
operation is fairly constant over the operating range.
4.4.1.2 Storage
For this project, hydrogen storage is being considered in both salt caverns and natural gas
systems. Salt cavern storage is used in conjunction with a solid oxide fuel cell for generating
electricity and storage in the natural gas system is used with a conventional combined cycle
generator for electricity generation. For storage in the natural gas system, the energy content
of the hydrogen injected into the natural gas system would be accounted for, and the hydrogen
would be blended with the natural gas. When the hydrogen is in effect withdrawn from storage
for conversion to electricity, an amount of natural gas that would be the energy equivalent of
the amount of hydrogen that was withdrawn is used instead.
4.4.1.2.1 Salt caverns
In the UK, there have been several examples of hydrogen gas storage, including three brine
compensated salt caverns at Teeside. The caverns were at a depth of 366 metres, and stored
hydrogen at 5,000 kPa pressure for industrial chemical applications. Technical issues for
hydrogen gas storage in geological structures have been researched for over 25 years (Phillips,
1985). Geological storage of hydrogen gas is now common in fuel processing industries where
there is little requirement for gas purity.
For high purity hydrogen gas storage, Praxair has recently developed salt caverns with capacity
of 2.5 billion standard cubic feet. A process of injection into the salt cavern for storage and re-
uptake with filtration to maintain purity has been patented (Morrow J.M., Corrao M., 2006).
The hydrogen gas storage cavern is connected to Praxair’s existing 750 million standard cubic
feet pipeline for the US Gulf Coast petrochemical industry.

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4.4.1.2.2 Gas pipeline storage
Storage of hydrogen in the natural
gas pipeline has been proposed
and researched, but only recently
has been reported in operation. In
June 2013, the German power and
gas company E.ON injected
hydrogen into the natural gas
pipeline for the first time as a full
system test; plant operations
commenced in August 2013 (see
press release in Appendix D). The
company stated that regulations
allow up to five per cent hydrogen
in the natural gas pipeline.
Figure 4: E.ON Power-to-Gas Facility
In Alberta, the TransCanada Pipeline (TCPL) natural gas quality specifications do not directly
limit the amount of hydrogen that can be injected into TCPL pipeline; however, the lower limit
on the heating value limits the quantity of hydrogen that can be blended into a TCPL pipeline at
any point. For this study it is assumed that hydrogen blended up to a concentration of five per
cent with pipeline quality natural gas, which typically has a higher heating value of at least 37
MJ/m3
, to meet the TCPL quality specification of a minimum heat rate of 36 MJ/m3
. On an
operational level achieving the five per cent concentration level requires that hydrogen be
injected into a pipeline of sufficient size and flow rate to achieve the necessary dilution of the
hydrogen.
Storing hydrogen in a natural gas storage facility up to the five per cent concentration limit is
not expected to create any concerns for a storage operator.
4.4.1.2.3 Conversion of hydrogen gas to electricity
To convert hydrogen back to electricity, two methods are considered:
 contracted use of a gas-fired electricity generation plant
 use of solid oxide fuel cell
The solid oxide fuel cell (SOFC) can take pure hydrogen gas – dry or humidified. While the
sulphur tolerance level of the SOFC is higher than other fuel cell technologies; hydrogen
sulphide levels of approximately 80 ppm can cause contamination of the cell. The SOFC is
capable of handling input gases other than pure hydrogen; and, generally the cells can run on
conventional fuels such as propane, butane, methane and gasified biomass.

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The efficiency of the SOFC is generally higher than other fuel cells. The company Ceramic Fuel
Cells out of Australia3
has reported 60 per cent efficiency in their BluGen commercial cell.
The output voltage of the SOFC is sensitive to many parameters, including temperature and
pressure of the inlet gases. For connection to the grid, the SOFC requires a power conditioning
unit (PCU) to control inlet gases, regulate cell DC output voltage and provide DC-AC conversion
(Hajimolana, 2009 and Sedghisigarchi, 2004).
It is recognised that the modelled operating strategy for PtG (electricity-hydrogen-electricity)
may not be the optimal strategy from a PtG operator’s perspective. There could be more
lucrative operating options such as storing hydrogen for capturing the seasonal variability in the
demand of natural gas, or using hydrogen as a clean combustion fuel for its heating value.
These operating strategies were not modelled because of maintaining consistency in
comparison with the NaS and CAES operating strategies.
4.4.2 Cost
Given that at the time of this study, there was only one Power-to-Gas facility operating in the
world and that facility only started operating a few months ago, there is no publicly available
data on the installed capital and operating costs of a complete power-to-gas system. The
referenced sources only provided capital estimates for the power-to-gas components such as
the electrolyser, reported to cost about $1,000 per kW of capacity. For the second power to gas
case, which uses a solid oxide fuel cell, the referenced sources show capital costs ranging from
$3,000 USD per kW to as high as $8,000 USD per kW.
3
"Ceramic Fuel Cells:: BlueGen - Ceramic Fuel Cells Limited." 2010. 20 Sep. 2013
<http://www.cfcl.com.au/bluegen>

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5 MODEL DESCRIPTION
5.1 METHODOLOGY
The models were designed and built to analyse the economic benefits, to a wind power
generating facility in the case of a Behind-the-Fence storage operator, and to a Merchant
energy storage operator. As opposed to forecast models, the study models were hindcast in
that each model used actual market data and in effect inserted the energy storage facilities into
that historical setting. There are positive and negative effects from this approach. On the
positive side unique characteristics of the Alberta market price volatility are retained, along
with the underlying correlation between wind generation and market prices. On the negative
side, a certain amount of distortion is introduced, but by limiting the size of the energy storage
facilities to 30 MW of charging and discharging capacity the error is limited. Overall, the positive
effects are felt to outweigh the negative effects.
Although energy storage is recognised as providing a number of benefits to the electrical grid,
not all of the benefits were modelled in the current study. The benefits accrued from
participation in the hourly energy market and two operating reserve markets were modelled.
Rather than modelling all of the sixteen cases, participation in the operating reserve markets
was modelled by two sensitivity cases using the Wintering Hills wind power generating facility
and NaS battery energy storage facility under a Merchant operating strategy. Similarly the
effects of the transmission tariffs and increased storage capacity were modelled as sensitivity
cases using only two of the study cases. The intent of the sensitivity case was to provide an
indication of the benefits or effects of varying some of the study key parameters.
5.1.1 Bid and Offer Strategy
The key element of the storage operations strategy was the switch price, or the price at which
the preference to charge switches to a preference to discharge and vice versa. The model
effectively set a bid and offer4
price for each hour dependent on the switch price. The switch
price was calculated each hour of the modelled year by an algorithm that used as inputs, the
expected inventory level, current average cost of inventory, and variable operating costs. The
effect of the algorithm was as the inventory level declined, the switch price increased up to a
maximum price of $80 per MWh. Conversely, as inventory levels rose the switch price declined,
but never below the sum of the inventory cost and variable costs. If the hourly price for
electricity was less than the switch price, the model injected electricity into storage; and, if the
hourly price for electricity was greater than the sum of switch price and the variable operating
cost, the model discharged electricity from storage.
4
The definition of a bid price is, what a buyer is willing to pay to acquire, in the case of the study, electricity and
the offer price is what a seller is asking for in order to sell electricity.

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Offer and bid volumes took into account forecast wind output and desired storage activity. The
real time hourly market price determined the actual volume to be sold or purchased; and, the
storage operator dispatched the storage to meet the sold or purchased volume as closely as
possible.
5.1.2 Prices
Actual 2012 Alberta hourly prices for electricity and operating reserves were used in the study.
Figure 5 shows the hourly electricity prices for 2012. Over the year, electricity prices averaged
$64.32/MWh and for half of the hours settled below $25/MWh. For the remaining 4,392 hours
the average price was over $110/MWh with sixteen hours settling between $990/MWh and
$1,000/MWh, the market price cap.
Figure 5: Distribution of Hourly Electricity Price - 2012
Similarly, as required, the actual 2012 daily prices for natural gas shown in Figure 6 were used.
Since, the “Gas Day” for scheduling receipts and deliveries of natural gas is defined as a 24-hour
period starting 08:00 Mountain Time, for modelling the natural gas price applicable in any hour
was changed at 08:00 each day.

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Figure 6: Daily Natural Gas Prices - 2012
5.1.3 Effects on Hourly Clearing Price
To model the effects of storage behaviour, a representative merit order curve was developed
based on a sampling of 2012 merit order curves. The representative merit order curve shown in
Figure 7 displays all of the typical characteristics of the Alberta merit order, namely:
 zero dollar offers of 6,000 MW or more;
 a section of slowly rising offers up to an inflection point at about $90 per MWh
which occurs around the 8,000 to 8,500 MW cumulative offer point;
 beyond the inflection point at about $90 per MWh a steeply sloping section with
offers reaching $900 per MWH; and
 above $900 per MWh a tail section where the rate of increase of the offer price
begins to slow down and caps at $1,000 per MWh.

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Figure 7: Typical Alberta Supply Merit Order Curve
The merit order curve was used to calculate an adjustment to the hourly market price resulting
from the energy storage operation. The effect of withdrawing a quantity of electricity from
storage thereby increasing the hourly supply of electricity was to reduce the hourly market
price, and the effect of injecting energy into storage was to increase hourly demand for
electricity resulting in an increase in the hourly market price.
The following explains how the Supply Merit Order Curve was used during an hour in which
electricity was injected into storage to determine the adjusted hourly market price:
1. Each hour the model would determine the deemed offer volume by using the actual
hourly market price and the corresponding offer volume, which is shown on Figure 8 as
the path defined from A to B to C.
2. The quantity of energy would be added to the deemed offer volume, shown as line C to
D
3. The new market price was determined by selecting the corresponding market price for
the combined deemed offer volume and injected quantity, shown as line D to E.
A similar procedure was used to determine the adjusted market price in the hour in which
energy was withdrawn from storage. The only difference being instead of adding the quantity
of energy withdrawn from storage to the deemed offer volume, the withdrawn quantity is
subtracted from the deemed offer volume. The path defined as F to G to H to D to E in Figure 8,
displays the process.

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Figure 8: Determining the Adjusted Market Price
5.1.4 Wind Power Facility Selection
Wintering Hills is an 88-megawatt (MW) wind power generating facility located in south-central
Alberta. In 2012, Wintering Hills produced about 292 gigawatt hours (GWh) of electricity
resulting in a capacity factor of about 38 per cent. In addition to achieving one of the highest
capacity factors of all the wind power facilities in the province, Wintering Hills was also one of
the most consistent producing wind facilities in Alberta. Castle River is a 44 MW generating
facility that in 2012 produced about 110 GWh of electricity, yielding a capacity factor of about
29 per cent. The Castle River wind facility energy production was highly variable with a
coefficient of variation5
of 1.1 versus Wintering Hills with a coefficient of 0.9.
For the storage modelling exercise, the hourly output from each of the wind power generating
facility was normalised to reflect an installed generating capacity of 50 MW. The process of
normalising the generating capacity for each wind power generating facility resulted in two
hourly data sets with Wintering Hills effectively producing about 168 GWh at an average price
of $46.59/MWh and Castle River producing about 143 GWh at an average price of
$36.43/MWh.
5
Coefficient of variation is a measure of the dispersion of a frequency distribution and is calculated as the ratio of
the standard deviation of a distribution to the mean of the distribution. The higher the value of the coefficient, the
greater is the dispersion of the wind farm output.

Final Report
, 2011
5.1.5 Storage operation
 Behind-the-Fence operations strategy assumes the:
o storage facility is controlled by the wind farm operator;
o operator does not purchase any electricity from the grid;
o combination of storage discharge and wind output is constrained by the contracted
transmission capacity at 50 MW; and
o operator only pays the STS tariff according to the existing AESO rules.
 Merchant operations strategy assumes the:
o storage facility is controlled by the operator of a co-located 50 MW wind power
generating facility;
o operator is free to buy or sell electricity from or to the grid or from the co-located
wind power facility;
o combination of storage discharge and wind output is constrained by the contracted
transmission capacity of 50 MW; and
o operator pays both the STS and DTS tariffs according to the existing AESO rules.
5.2 MODELLING PARAMETERS
5.2.1 Description of model cases
All the modelled cases shared the following parameters:
 the storage facility is co-located with 50 MW wind power facility and shares 50 MW
of transmission system access capacity with the wind power facility;
 30 MW of charging and discharging capacity; and
 210 MWh of storage capacity or seven hours of storage when charging or
discharging at full capacity.
Table 1, overleaf, provides a summary of each model case for comparison.

Final Report
, 2011
Table 1: Summary of Modelled Cases
Scenario
Energy Storage
Technology
Case
Behind-the-Fence NaS Battery Wintering Hills - Behind-the-Fence - Battery
Castle River - Behind-the-Fence - Battery
CAES Wintering Hills - Behind-the-Fence - CAES
Castle River - Behind-the-Fence - CAES
Power-to-Gas 1 Wintering Hills - Behind-the-Fence - P2G1
Castle River - Behind-the-Fence - P2G1
Power-to-Gas 2 Wintering Hills - Behind-the-Fence - P2G2
Castle River - Behind-the-Fence - P2G2
Merchant NaS Battery Wintering Hills - Merchant – Battery
Castle River - Merchant – Battery
CAES Wintering Hills - Merchant – CAES
Castle River - Merchant – CAES
Power-to-Gas 1 Wintering Hills - Merchant - P2G1
Castle River - Merchant - P2G1
Power-to-Gas 2 Wintering Hills - Merchant - P2G2
Castle River - Merchant - P2G2
5.2.2 NaS Battery
In addition to the common storage charging, discharging and total capacities, the NaS battery
cases were also based on the following parameters:
 The depth of discharge (DOD) was limited to not more than 90 per cent of the total
energy storage capacity; or, in other words, the operator did not discharge the
batteries down to a point where there was less than 21 MWh in storage;
 The co-located wind power generating facility consistent with the transmission grid
requirements produces an AC signal that had to be converted to DC for charging the
batteries; and similarly with discharging, the battery energy had to be converted
from DC to AC;
 Battery efficiency was assumed to be 85 per cent;
 Inverter efficiency was assumed to be 95 per cent for AC to DC and for DC to AC
conversion; and
 Overall cycle efficiency was estimated to be about 77 per cent.
The limit on discharging was consistent with the manufacturer’s direction and will extend the
expected battery life to 4,500 charging and discharging cycles.
Figure 9 below is a diagram of the energy flows for the modelled battery system based on the
parameters described above. The system shown in Figure 9 is very simple, as are all battery
systems, consisting of an inverter to convert the incoming electricity from AC to DC current and

Final Report
, 2011
an outgoing inverter to convert energy withdrawn from the batteries from DC to AC current.
The AC-to-AC efficiency of the NaS battery operations described in the modelled cases is about
77 per cent, excluding auxiliary energy. The overall efficiency did vary from case to case as the
auxiliary energy load varied with the frequency and depth of the charging cycle.
Figure 9: NaS Battery Energy Balance
The auxiliary energy requirements for heating the battery to maintain battery temperatures
within the recommended operating range were modelled on an hourly basis using the equation
(of best fit) shown in the Figure 10 below. The graph was used in the 2011 study and is based
on a number of sources including “Sodium Sulfur Energy Storage and Its Potential to Enable
Further Integration of Wind (Wind-to-Battery Project) Xcel Energy Renewable Development
Fund Contract #RD3-12” (Himelic, J., Novachek F. 2010).
Figure 10: Auxiliary Energy Requirement

Final Report
, 2011
For modelling the auxiliary energy load was treated as a cost and not a parasitic load and
therefore the auxiliary energy requirements were priced using the adjusted hourly market price
and shown as a cost in the model results. The auxiliary energy loads were not deducted from
the energy delivered or received from the transmission grid.
5.2.3 CAES
Figure 11: CAES Energy Balance
Figure 11 above shows a similar (to NaS) energy balance for a CAES system. The modelled CAES
system is obviously more complex than a battery system. The following paragraphs provide a
simple description of the system that the CAES models were based upon.
The air compressor compresses air in several stages from atmospheric pressure to the pressure
required for injection of the air into the storage cavern. Since compressing air causes the
temperature of the gas to increase, there is a small requirement for cooling to keep the air
temperature within the operating range of the compressor.
As required, the compressed air is withdrawn from the storage cavern to generate electricity.
The model shown in Figure 11 generates electricity by expanding the air in two stages. During
the first expansion stage the air pressure is reduced to a level suitable for a gas turbine, while at
the same time recovering energy from the expanding air through the use of a turbo expander-
generator. The temperature of expanding air will drop and to prevent the possibility of any
water vapour contained in the air from freezing, the air is heated. Fortunately the gas turbine
used in the second expansion stage produces a significant quantity of waste heat. The model, in
effect, uses the hot exhaust from the gas turbine to heat the expanding air.
In the second expansion phase, the compressed air is mixed with natural gas; and, the mixture
is ignited in a gas turbine that drives a generator. The gas turbine used in a CAES system is
different than all other gas turbines in that the inlet compressor section that is normally used to
compress air is not needed and for modelling purposes was removed. The compressor section
of a standard gas turbine consumes one-half to two-thirds of a gas turbine’s mechanical output.

Final Report
, 2011
Without the inlet compressor, the CAES gas turbine heat rate6
is about 35 per cent lower than a
high efficiency natural gas-fired combined cycle generating plant.
The use of natural gas results in a CAES system generating more electricity than what is actually
stored. The modelled CAES system yielded about 1.3 MWh for every MWh consumed
compressing air. On average, the round-trip efficiency of the modelled CAES system is about 49
per cent.
The following parameters were used in the CAES models:
 30 MW air compression capacity;
 brine compensated salt cavern storage at a depth of 1,300 metres;
 cavern operating pressure of 13 MPa;
 injection/withdrawal air flow of 172,000 kg/hour;
 injection surface pressure of 11.5 MPa;
 discharge surface pressure of about 10 MPa;
 an initial expansion-generation stage to reduce the air pressure from 10 MPa to 0.23
MPa;
 a natural gas requirement of about 170 GJ/hour during hours when the gas turbine
is operating;
 actual daily natural gas prices for each gas day; and
 gas turbine heat rate 4.5 GJ/MWh HHV
5.2.4 Power to Gas 1
Figure 12 below, shows the energy balance for the Power-to-Gas 1 system. The Power-to-Gas 1
system starts with an electrolyser that splits water into hydrogen and oxygen. The oxygen is
vented and the hydrogen is captured and compressed to the normal operating pressure of the
TransCanada Alberta system. As already described in the preceding section on CAES,
compressing a gas causes the temperature of the gas to increase; and similar to compressing
air, there is a small requirement for cooling hydrogen to keep the hydrogen temperature within
the operating range of the compressor. Once in the pipeline the hydrogen is, in effect, delivered
to a natural gas storage facility. In reality, the hydrogen once injected into the pipeline likely
never reaches the natural gas storage facility. The operator of the Power-to-Gas facility is
instead credited with a quantity of energy entitling the operator to withdraw that quantity from
the natural gas storage facility. The model assumes that in responses to hourly electricity
6
Heat rate is the ratio of the natural gas consumed by the gas turbine to the output of the generator coupled to
the gas turbine. A gas turbine –generator set that consumes 750 GJ of natural gas per hour and produces 100
MWh of electricity has a heat rate of 7.5 GJ/MWh.

Final Report
, 2011
market prices the storage operator withdraws a quantity of natural gas from the natural gas
storage reservoir for delivery at a combined cycle natural gas-fired generating facility for
conversion to electricity.
Figure 12: Power-to-Gas Energy Balance
Based on the operation of the Power-to-Gas facility described above, the overall efficiency of
the Power-to-Gas system is about 36 per cent.
The Power-to-Gas 1 system was modelled on the following parameters:
 30 MW of electrolyser capacity producing 545 kg/hour of hydrogen with a
conversion efficiency of 72 per cent HHV;
 200 kW of hydrogen compression capacity to boost the hydrogen pressure from
3,000 kPa at the outlet of electrolyser to 6,000 kPa in order to inject hydrogen into a
natural gas pipeline;
 storage of hydrogen in a natural gas storage facility;
 storage demand costs of $0.50 per GJ of stored energy and injection and withdrawal
fees of $0.02 per GJ
 withdrawal of an equivalent quantity of energy for delivery to a natural gas-fired
combined cycle power plant; and
 a natural gas-fired combined cycle generating facility efficiency of 50 per cent,
equivalent to a heat rate of 7.2 GJ/MWh HHV.
5.2.5 Power to Gas 2
Figure 13 shows the energy balance for the Power-to-Gas 2 system. The Power-to-Gas 2
system, similar to the Power-to-Gas 1 system, starts with an electrolyser. Hydrogen gas
produced by the electrolyser is compressed for injection into a storage cavern. As required,
hydrogen is withdrawn from the storage cavern and expanded through a turbo expander –
generator, to recover the energy available from expansion. Next, the hydrogen is heated in an
exchanger along with air to about 800 degrees Celsius; both the hydrogen and air are then fed
into a solid oxide fuel cell. The solid oxide fuel cell converts the energy released from the
reaction of hydrogen and oxygen in the cell to form water, into electricity. At the same time,

Final Report
, 2011
the fuel cell generates heat that the model uses to heat the incoming hydrogen and air. The
Power-to-Gas 2 system as described has an efficiency of about 30 per cent.
Figure 13: Power-to-Gas 2 Energy Balance
The Power-to-Gas 2 system was modelled on the following parameters:
 30 MW of electrolyser capacity producing 545 kg/hour of hydrogen with a
conversion efficiency of 72 per cent HHV;
 500 kW of hydrogen compression capacity to boost the hydrogen pressure from
3,000 kPa at the outlet of electrolyser to about 13,000 kPa in order to inject
hydrogen into a storage cavern;
 brine compensated salt cavern storage at a depth of 1,300 metres;
 cavern operating pressure of 13 MPa;
 injection/withdrawal air flow of 545 kg/hour;
 injection surface pressure of 13 MPa;
 discharge surface pressure of about 12.6 MPa;
 three stages of expansion-generation stage to reduce the hydrogen pressure from
about 12.6 MPa to 0.56 MPa; and
 a solid oxide fuel cell generator operating at 1,073 degrees Kelvin (about 800
degrees Celsius) with an efficiency of 60 per cent.
5.2.6 Sensitivity Cases
5.2.6.1 Transmission Demand and Supply Charges
As previously mentioned in Section 3.2, an energy storage facility operating behind-the-fence of
a wind power generating facility would have been charged for supply transmission services
(STS) during the hours that the energy storage facility delivered electricity to the Alberta
transmission grid. If the wind power generating facility was operating at the same time as the
energy storage facility was delivering energy to the grid, the STS charges would be for the total

Final Report
, 2011
quantity of electricity delivered. STS charges are calculated as, the sum over the hours in a
month of the product of the hourly market price, the delivered energy in the hour and the loss
factor, plus applicable rate riders. In Alberta, a portion of the cost of transmission system losses
is allocated to each generator connected to the transmission system through loss factors are
calculated annually for each generation facility.
A merchant energy storage facility would pay the STS charges for all energy delivered to the
transmission grid and the delivery transmission service (DTS) for all energy withdrawn from the
grid. DTS charges are calculated based on contracted demand, the metered energy and the
coincident peak factor plus a number of rate riders. The coincident peak factor is the ratio of
the metered demand coincident with the system peak demand in any month divided by the
contract demand. Since the objective of a storage operator is to buy and store energy at low
prices and low prices normally occur when system demand is lower, the coincident peak factor
which is about 75 per cent for a typical load, was set, conservatively, at 50 per cent for the
storage facility. In total the DTS charges are significantly higher than the STS charges on a per
MWh basis.
Four sensitivity cases were developed to assess the potential transmission charges related to
both the Merchant and Behind-the-Fence operations strategy cases. Two cases are based on
the Wintering Hills wind power generating facility with battery storage and two cases are based
on the Castle River wind power generating facility with CAES. For the Behind-the-Fence cases
the STS charges were calculated on an hourly basis assuming a contracted capacity of 50 MW.
For the Merchant cases the DTS charges were calculated monthly based on a contract capacity
of 30 MW, or 31.6 MW for the battery cases only to account for inverter losses, and assuming
that the substation was shared by the energy storage facility and the wind power generating
facility. The applicable 2012 loss factors and rate rider values were used in the sensitivity cases.
The results of the sensitivity cases are shown in Section 6.2.
5.2.6.2 Operating Reserve Market
Two sensitivity cases were developed to examine the potential incremental revenues available
to a NaS energy storage system from participation in the Alberta operating reserve (OR)
market. The first sensitivity case modelled participation in the active regulating reserve market
and the second case modelled participation in the standby spinning reserve market. More
details on the Operating Reserve markets are available in Appendix A.
The NaS battery energy storage system is chosen for both sensitivity cases to allow comparison
of the results of both sensitivity cases without having to adjust the results to account for the
effects of the storage technology. Currently batteries are not eligible to supply spinning reserve
in the Western Electricity Coordinating Council region, which includes Alberta. There is no
fundamental technical reason why a battery energy storage facility could not supply spinning
reserve, prohibition on eligibility is likely more to do with what is familiar practice and
experience.

Final Report
, 2011
Regulating Reserve
The first sensitivity case modelled the effects of NaS battery system operator offering 15 MW7
of regulating reserves into the OR market at the switch price8
for the AM Super Peak9
time
block. Prior to submitting the offer, the model confirmed there was sufficient energy in storage
and at least 15 MW of available transmission capacity for the three AM Super Peak hours. If the
Dispatch Price was higher than the switch price for each of the three hours of the AM Super
Peak block, the model assumed that the offer has been accepted.
When a regulating reserve offer has been accepted, the model reduces the inventory level by
15 MWh and the maximum quantity of energy that can be delivered on the transmission grid
was set at 35 MW, the difference of the 50 MW contracted transmission capacity and the 15
MW regulating reserve offer. The facility revenue was increased by the product of the Dispatch
Price times 15 MWh.
If the regulating reserve offer was accepted, the storage facility was also eligible for a directive
payment, if the AESO directed the facility to provide energy during the AM Super Peak hours.
Since there was no certainty whether the facility was going to be directed to provide energy,
the model results shown in Section 6.2 show the revenue associated with the payment of the
Dispatch Price and directive payment separately. To calculate the directive payment the model
assumed the storage facility was directed for each of the three AM Super Peak hours. The least
amount the storage facility might receive by offering regulating reserves for AM Super Peak
hours is the sum of the Dispatch Price payments; and the largest amount the energy storage
facility may receive is the sum of the Dispatch Price payment plus the directive payments.
It is important to note that the result of the offer strategy was that during some AM Super Peak
hours when the regulating reserve offer is deemed to be accepted the storage facility misses an
opportunity to sell electricity into the hourly market at a price higher than what was deemed to
have been received selling regulating reserve services. These lost opportunities were accounted
for by comparing the model results for the regulating reserve case to the case for the NaS
battery system, which assumes the system is only participating in the hourly energy market.
The results and comparison are shown in Section 6.2.
Standby Spinning Reserve
The second OR sensitivity case models the NaS battery system operator offering 10 MW into
the standby spinning reserve market. Similar to the first sensitivity case, the offer of standby
spinning reserve was made at the switch price for the sixteen-hour on-peak block. If a standby
offer was accepted, the NaS battery system operator was paid an availability payment based on
7
15 MW is the minimum offer for regulating reserve with additional offers in blocks of 5 MW each. See Appendix A
for a summary on the Alberta Ancillary Services market.
8
See section 5.1.1 for an explanation of the switch price.
9
AM Super Peak time block extends from hour ending 06:00 to hour ending 08:00 each day.

Energy Storage Technoecon Final Report_Revised March 2014

Energy Storage Technoecon Final Report_Revised March 2014

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