1. Pan-Canadian Wind Integration Study (PCWIS) Prepared by: GE Energy Consulting, Vaisala , EnerNex, Electranix, Knight Piésold
Olga Kucherenko

2. Contents Introduction and background Data Sources Study Scenarios
Study Assumptions
Examples and Details
Key Results
Sensitivity Analysis

3. Introduction and background
Main purpose of the study:
Analyze the implications of integrating large amounts of wind power in the Canadian electrical system
Developing a database of chronological wind data for potential wind sites
Improved understanding of the operational challenges and opportunities
Improved understanding of the operational and production costs and benefits of high wind penetration in Canada

4. Introduction and background
Project team
5 companies involved
GE Energy Consulting - Overall project leadership, production cost simulation and reliability analysis
Vaisala - Wind profile and forecast data
EnerNex - Wind plant data assembly and management, statistical analysis, regulation/reserve requirements
Electranix - Transmission reinforcement design
Knight Piésold - Canadian hydropower resource data and modeling

5. Introduction and background
Main tasks:
Model Development
Develop wind speed data, wind profiles, reserve requirements
Identify and design transmission reinforcements
System studies and Scenario Analysis
Additional analysis (sensitivity, sub-hourly, statistical)

6. Introduction and background
Focus areas

7. Data sources
Massive amount of data used (generation, transmission load profiles, wind profiles, etc.)
The study used both publicly available and confidential data to model the interconnected power grids

8. Data sources
Developed wind power profiles for both existing and future wind plants were based on wind speed and meteorological data ( individual 2 km square grid cells,10-minute time intervals, 3 calendar years (2008 to 2010).
Forecast data: day-ahead wind forecast

9. Study Scenarios
4 scenarios with penetration levels from 5% to 35% of annual system load energy
5% BAU - 5% Business As Usual
20% DISP – 20% Dispersed wind resources
20% CONC – 20% Concentrated wind resources
35% TRGT – wind resources concentrated in targeted provinces with 35% wind penetration.

10. Study Scenarios 5% BAU - 5% Business As Usual
Existing wind plants + new under construction
Benchmark for how grid operations will change with increased penetration

11. Study Scenarios 20% DISP – 20% Dispersed wind resources
Includes the sites from the 5% BAU scenario + best additional sites in each province to get to 20% of annual energy demand

12. Study Scenarios 20% CONC – 20% Concentrated wind resources
Includes the sites from the 5% BAU scenario + additional wind plants in regions with highest capacity factor

13. Study Scenarios
35% TRGT – wind resources concentrated in targeted provinces
Based on 20% DISP scenario + targeting more wind plants in provinces with high thermal generation

14. Study Assumptions Power grids were modeled to represent year 2025
System load was derived from 2013 data to year 2023, and then escalated for 2 more years
Model included two major North-American interconnections with full transmission systems
All existing conventional generation units were included in the model + new ones being under construction
Study neglects seasonal variability of hydro resources (normal operating conditions assumed)
Each province modelled as a separate balancing area

15. Load and Wind Profiles
Many statistical evaluations were done on load and wind profiles
For example: Average daily load and wind profiles by season

16. Load and Wind Profiles 20% DISP scenario Highest load in the winter
Wind profiles: more energy in fall and winter
-> Positive influence of the capacity value

17. Transmission System Reinforcement
New transmission resources required with increase in wind generation
Existing and additional transmission capacities for study scenarios:

18. Transmission System Reinforcement
Incremental Transmission Capacity Additions

19. Transmission System Reinforcement
Estimated costs for transmission reinforcements and annual reductions system-wide

20. Grid operation Canada is a net exporter of energy in all scenarios.
With increase of wind penetration coal and gas generation decreases, however exports to USA increase.

21. Grid operation: Annual generation by provinces

22. Key Results
With adequate transmission system reinforcements and additional reserves Canadian power system will not have any major difficulties operating at 20% and 35% wind penetration levels.
In 20% and 35% scenarios wind energy replaced gas and coal-fired generation – economic benefits

23. Key Results
No significant advantage to put more wind power plants into places with slightly higher capacity factors -> better add more wind generation to the provincial load centers, where energy would be used.
The Canadian wind resource is excellent and shows capacity factors above 36% for the sites considered in the study.

24. Key Results
To limit the curtailment inter-area transmission reinforcements are required.
The combination of wind and hydro provides good energy resource for Canada and more opportunities to increase exports to USA.
Important to ensure the flexibility of hydro resources

25. Key Results
Wind energy has a value (avoided cost) of about $47/MWh in the 35% TRGT scenario when compared to the 5% BAU scenario.
By the 35% TRGT scenario, the required additional transmission capacity costs of $3.7 billion are recovered by a $1.5 billion annual reduction in system-wide production costs
-> payback period of less than three years.

26. Key Results
Wind energy reduces the thermal generation operational costs. Compared to the 5% BAU scenario, the 35% TRGT scenario will result in savings of around $3.5 billion per year.
Wind energy enhances wind energy export opportunities. Compared to the benchmark scenario, the 35% TRGT scenario will result in increased net export revenues by about $3.6 billion per year, where 46% would come from wind energy.

27. Key Results
High wind penetration allows significant CO2 emission reductions. Under the 35% TRGT scenario, 32 million metric tons of CO2 are avoided annually.

28. Sensitivity analysis
Determine how much study scenarios would change if some data assumptions were changed
Extent of transmission reinforcement
Market price of natural gas
Wind energy forecasts
Extent of coal plant retirements
Operational practices for scheduling of hydro generation resources
Additional transmission interconnections
Distributed energy resources
Penetration of wind energy in the USA etc.

29. Sensitivity analysis
Extent of transmission reinforcement: very little influence
Market price of natural gas: energy price follows natural gas prices
Wind energy forecasts: day-ahead used for base case scenarios. If used 4-hour-ahead forecasts – possible to reduce energy production costs

30. Sensitivity analysis
Hydro Scheduling: hydro energy is scheduled according to a day-ahead wind and load forecast. If wind forecasts are not used in hydro scheduling - production costs increase significantly (C$100M/year for 5% BAU scenario and C$494M/year for 20% DISP scenario).
Reasons to use flexible hydro generation to compensate errors in forecasts.

31. Sensitivity analysis
Distributed PV: with increase of production without sufficient transmission capacity leads to curtailment -> changes in operating and transmission reinforcement will likely be required.

32. Limitations
Carbon tax not included (if implemented – shift from gas to coal generation)
Evaluation of intra-provincial transmission required (connecting additional wind power plants to local high-voltage transmissions system) not included
Detailed long-term regional transmission expansion planning is beyond the scope of the study

33. Thank you for your attention!