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Ontario needs major private sector investment in non-fossil fuel Distributed electricity Generation, natural gas co-generation and Energy Storage to meet the electricity supply shortage and the required reduction in CO2 emissions that are anticipated during the next decade.
ELECTRICITY GENERATION PROBLEMS:
Most of Ontario's electricity is presently generated by conventional hydro-electric dams or by large thermal-electric generating stations. Most of the rivers with sites that are suitable for large hydro-electric dams have already been harnessed. Fossil fuel thermal-electric generators are a problem because they are large sources of the man made CO2 that causes global warming. Nuclear thermal-electric generators have proven to be quite expensive, need to be base loaded, and have complex safety and waste management issues. All thermal-electric generators reject large amounts of heat that significantly alters the local environment. In order to obtain electricity without the aforementioned problems attempts are being made to use distributed renewable electricity generation.
DISTRIBUTED ELECTRICITY GENERATION:
Distributed electricity generation involves taking advantage of economic and environmentally acceptable sources of energy for electricity generation wherever and whenever they occur. Unconstrained distributed electricity generation has an output power versus time profile that is determined by available sun light, available (wind velocity)^3 and available river flow. Adoption of intermittent distributed generation generally triggers a requirement for additional transmission to deliver balancing power when the output of the intermittent generator is low.
RELIABILITY OF DISTRIBUTED ELECTRICITY GENERATION:
The reliability of an electricity system with distributed generation rests on there being a large number of statistically independent distributed generators with energy storage that collectively provide sufficient average power to meet both the local area grid load and the energy storage system losses. On-going voltage regulation requires control of energy storage and sheddable load as well as some generation constraint. To minimize dependence on long distance transmission local generation should be operated to approximately equal local load. The process of matching local generation to local load requires excess generation capacity and controlled generation constriant.
As intermittent unconstrained generation is added to the electricity system balancing sheddable load, energy storage and constrained generation should also be added to the electricity system. In the absence of these balancing components the distributed generation must be heavily constrained to achieve load following. This generation constraint reduces each generator's average power output by about 33%. Further generation constraint, typically up to about 50%, is necessary to provide a safety margin to allow for an unplanned generation outage at a time of near peak electricity load.
The generation constraint requirement can be met by requiring all distributed generators to constrain their outputs according to a specified negative slope output power versus voltage curve. However, implementation of this generation constraint methodology requires acceptance by the parties of appropriate contract terms.
Introduction of unconstrained intermittent generation leads to a loss of energy revenue by existing load following generators. This is a financially intolerable state of affairs that has yet to be adequately addressed by the Independent Electricity System Operator (IESO).
Capacity Factor and load factor based electricity rates should be used to encourage use of energy storage for leveling generation and load profiles. To the extent that energy storage does not achieve generation and load profile matching, then generation and/or load under dispatch control must be used to achieve the required profile matching. The economics of distributed generation depend on how well the distributed generation output matches the local load profile. If seasonal energy storage is required to match the generation and load profiles the cost can be prohibitively large.
An issue that has not been adequately addressed by the IESO is requiring distributed generators to be self excited to reduce their dependence on other generation for voltage regulation, reactive power and black start.
DISTRIBUTED GENERATION TYPES:
Two significant sources of distributed generation energy are wind and solar generation. It is helpful to examine the costs of both types of distributed generation. The mathematical development for other forms of distributed generation is analogous.
The IESO has determined that the value of unconstrained land based wind energy is about $.115 / kWh.
When statistically independent unconstrained distributed generation is constrained to follow the actual Ontario load profile the average generator output is reduced by a factor of 0.674. Hence the average cost of wind energy increases to:
(1 / 0.674) X $.115 / kWh = $.1706 / kWh
The transmission/distribution and regulatory costs are additional.
The power output from a wind generator is proportional to (wind velocity)^3. Hence, doubling the wind velocity increases the power output by a factor of 8. The available wind energy is proportional to the time averaged value of (wind velocity)^3.
There have been various claims relating to the frequency of bird impacts with wind turbines. A method that has been successfully used to keep birds away from sail boats is to attach a flapping plastic streamer to the mast. It is believed that this method will also work with wind turbines, albeit at a slight cost in turbine efficiency.
A fundamental problem with wind generation in Ontario is that the average power output in the winter is about twice the average power output in the summer. In the summer there can be periods as long as ten days when the wind velocity is low and almost all the energy requirements must be met from energy storage. In the winter there can be periods as long as five days when the wind velocity is low and almost all the energy requirements must be met from energy storage. The experimental data published in Section 6.1 of the Ontario Wind Integration Study shows that the minimum energy storage required to smooth out week to week variations in wind output is about 480 kWh for a 10 kW peak output wind generator.
WIND GENERATION ENERGY STORAGE SYSTEM ASSUMPTIONS:
1. A representative unconstrained wind generator has a peak output of 10 kW, a winter month average output of 4 kW and a summer month average output of 2 kW.
2. The adjacent energy storage system is rated for a maximum input of 8 kW and a maximum output of 4 kW.
3. The amount of energy storage required to smooth the output of a 10 kW peak output wind generator is 480 kWh.
A major component of the energy storage system cost is the cost of the chemicals used to store the energy. Assume that the chemical system used for energy storage is sodium-sulfur-nickel chloride (Na-S-NiCl2).The characteristics of this electrochemical storage are set out at: Na-S-NiCl2 Electro-Chemical Energy Storage.
The cost of the chemical inventory is about:
$25.00 / kWh X 480 kWh = $12,000
The chemical inventory could be contained in a battery casing assembly worth another $2000 and associated with a 6 kW inverter worth $6000, for a total energy storage system cost of:
$12000 + $2000 + $6000 = $20,000
ENERGY STORAGE LOSSES:
Assume that 60% of the energy input to storage is recoverable.
Let G = average wind generator power output
Assume that almost all of the unconstrained wind generated energy goes into storage.
Then if the storage efficiency is 0.6 the net energy output is:
Hence the storage energy loss is:
(1 - .60)G = .40 G
Hence if an unconstrained wind generator has an average output of 0.30 X the peak output, with the storage system the average output will decrease to:
0.30 X 0.60 X (peak output) = 0.18 X (peak output).
The annual net electricity output from the combined wind generator and energy storage system is:
10 kW X 8766 hour X .18 = 15,778.8 kWh / year
The energy storage system capital cost in (year / kWh) is:
$20,000 / (15,778.8 kWh / year) = $1.2675 year / kWh
With 7.34 year amortization this capital cost increases the cost of wind generation by:
($1.2675 year / kWh) / 7.34 year = $.1726 / kwh
The cost of the unconstrained wind generated electrical energy is:
$.115 X (1.00 / 0.6) = $.1917/ kWh
Hence the total price of winter weighted load following electicity from wind generation with about a week of energy storage is:
$.1917 / kwh + $.1726 / kWh = $.3642 / kwh
The cost of storage / annual average kW is:
$20,000 / 1.8 kw = $11,111.11 / kW
The comparable cost for new nuclear electricity generation is about $12,000 / kW.
To follow the daily load variation the nuclear system might be constrained by .674, so that its cost per average kW becomes:
($12000 / kW) / .674 = $17,804 / average kW output
Hence the cost of nuclear generation with load following constraint is similar to the cost of wind generation with load following energy storage. However, nuclear generation has the advantage that it better meets the peak load in the summer. Wind generation with energy storage has the long term advantage that it better meets a peak load in the winter.
Under the aforementioned costing assumptions, on a per average kW basis the costs of nuclear generation and the costs of wind generation are similar, and the choice between them should be made based on the shape of the seasonal monthly average electricity load profile and on the cost of the required transmission. A load profile with winter consumption twice summer consumption points to wind generation. A flat load profile points to nuclear generation. A summer peaking load profile points to nuclear generation. Onn average wind generation requires much longer transmission than does nuclear generation. Hence, except in exceptional circumstances, nuclear generation generally is less expensive than wind generation.
Wind energy only has an economic advantage over nuclear energy when serving a local electricity load that is winter weighted. Monthly energy consumption data provided by the IESO indicates that in 2006 the provincial electricity load had no winter weighting. IESO data from its generator reports indicates that during 2006 the monthly generation in Ontario in TWh was:
Jan: 13.93 TWh
Feb: 13.15 TWh
Mar: 13.75 TWh
Apr: 12.40 TWh
May: 12.49 TWh
Jun: 12.78 TWh
Jul: 14.20 TWh
Aug: 14.02 TWh
Sep: 11.96 TWh
Oct: 12.49 TWh
Nov: 11.88 TWh
Dec: 13.05 TWh
The total generation in 2006 was 156.1 TWh.
In order for the electricity consumption in Ontario to become winter weighted there must be an increase in electricity used for water heating and space heating. Such an increase might be triggered by a sustained increase in the price of fuel oil. In July 2008 the retail price of fuel oil reached $1.40 / litre plus GST without any fossil carbon emissions tax. According to NRCAN in 2006 Ontario consumed 1,068 million litres of fuel oil. The heat that is available from this fuel oil burned at 85% efficiency is:
.85 X 38.2 MJ / lit X 1,068 X 10^6 lit/year = 34.678 X 10^9 MJ / year
=34.678 X 10^9 MJ / year X 10^6 J / MJ X 1W-s/ J X 1 kW / 1000 W X 1h / 3600 s
= 9.6327 X 10^9 kWh /year
= 9.6327 TWh / year
Viewed as a fraction of total generation in Ontario this opportunity for economic wind power is about:
9.6327 TWh / 156.1 TWh = .0617 = 6.17%
This is a much smaller fraction of total generation than many wind power advocates have claimed. In order for this fraction to significantly increase the price of a kWt from natural gas must exceed the price of a kWt from electricity
A 10 kW peak output wind turbine with a capacity factor of 0.3 and an effective energy storage efficiency of 0.6, as described above, has an annual net output of:
10 kW/turbine x 8766 h/year X .3 X .60 = 15,778.8 kWh / year-turbine
Thus the maximum number of such 10 kW wind turbines that the Ontario energy system could reasonably accept is:
(9.6327 X 10^9 kWh / year) /(15,778.8 kWh / year-turbine)
= 6.1048 X 10^5 10 kW wind turbines
= 6.1048 X 10^3 1 MW wind turbines
= 6104 1 MW wind turbines
= 3052 2 MW wind turbines
If this conversion is spread over a 10 year period the annual construction rate would be:
3052 turbines / 10 years = 305.2 MW turbines per year.
This construction rate is well within industry capability.
SOLAR ELECTRICITY GENERATION:
Solar electricity generation has two major constraints. The peak output from a high efficiency solar panel aimed directly at the sun is about 0.25 kW / m^2. In southern Ontario the capacity factor of a solar panel is about 0.14. Hence in southern Ontario if a building has a roof area of 100 m^2 and the entire roof is covered with a steerable solar panel array the monthly output from the solar panel is about:
0.25 kW / m^2 X 100 m^2 X 0.14 X 730.5 h / month = 2556.75 kWh
This amount of electricity is not sufficient to meet the total energy needs of most families which are typically about:
10 kW / person X 730.5 h / month = 7350 kWh / person-month. Thus in southern Ontario a family of four needs about 10X the amount of energy that can be harvested by a high efficiency rooftop solar panel array.
In northern Canada available solar radiation is extremely seasonal. There are four months per year with almost no sunlight. Hence in northern Canada solar panels are simply not a viable way of meeting winter energy needs.
This web page last updated May 15, 2016.
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