1. Investments to Reduce Power System Risk from Gas System Dependence
Industrial & Manufacturing Systems Engineering
Investments to Reduce Power System Risk from Gas System Dependence
Sarah M. Ryan and Dan Hu
For presentation in “Electricity systems of the future: incentives, regulation and analysis for efficient investment”
Isaac Newton Institute for Mathematical Sciences, Cambridge
19 March 2019

2. Outline Conclusions Symptoms of vulnerability to risk
Risk quantification in economic terms
Optimization-based simulation
Input distributions estimated from real data
Not-so-real power grid combined with gas system
Use of risk metrics to evaluate alternative risk-mitigation strategies
Dual-fuel capability
Increased gas storage
Conclusions

3. Growth of Variable Renewable Generation
Gas units provide the needed flexibility for increasing renewables
Source: US Energy Information Administration, Annual Energy Outlook 2019

4. Asymmetric Electric-Gas Dependence
35%
35%
Source: US Energy Information Administration, Annual Energy Outlook 2019

5. Interruptible Contracts for Gas

6. Winter, 2019, US Upper Midwest
17C

7. Winter, 2018, Eastern US Gas Prices

8. Winter, 2018, Eastern US Electricity Prices

9. Winter, 2014, New England Prices
*natural gas price is average of MA delivery points
electric energy prices ($/MWh)
natural gas prices ($/MMBtu)
DAM price
RTM price
natural gas price*
Source: ISO-NE
Data are measured from the original figure and thus may not be exact.

10. Model and Methods
Optimization-based simulation to investigate dispatch cost under:
limits on availability of gas from interruptible contracts, combined with
high spot prices for gas, correlated with
demand for electricity
Hard to find good data:
available gas varied parametrically
electric demand and gas spot price modeled probabilistically
Some gas-fired generators procure gas in firm contracts but many do not. They have lower priority than other gas users and may have to buy gas on the spot market instead.

11. sources of uncertainty renewable sources output
Problem Setting
Net load
sources of uncertainty
Power system
Dispatch
cost
conventional
units availability
load
renewable sources output
gas availability
gas spot price
economic dispatch
(ED)

12. Dispatch Linear Program
Min Total daily dispatch cost
Gas costs from interruptible contracts and the spot market
Production cost of non-gas generators
Net cost of gas flows from storage
Penalties for non-served/excess electricity or gas
s.t. Usual constraints given unit commitment, plus
Limit on availability of contracted gas
Gas balance
Limits on flows to/from storage
DC approximation of transmission constraints

13. Impact of Gas Price Uncertainty and Constrained Gas Availability on Dispatch Cost
Sources of uncertainty
(Net) load
Economic Dispatch Model
Min daily dispatch cost, subject to
Usual dispatch constraints
Limit on gas available from interruptible contracts
Load uncertainty only
Load & gas price uncertainty
Gas spot price
Monte Carlo simulation schemes:
ED-PE: Economic dispatch (ED) with uncertain electric load and gas price Point Estimate
ED-PD: ED with joint electric load and gas price Probability Distribution

14. Risk Quantification Procedure
Estimate joint distribution of electricity load and gas spot price
Risk measure (CVaR)

15. Gas Spot Price and Electric Load Jointly Depend on Weather
Procedure for estimating joint distribution, illustrated for ISO-NE in winter
Cluster days based on average hourly temperature
Fit bivariate Normal distribution to transformed data
Estimate mean vector and covariance matrix in each cluster
Algonquin Citygate gas price & Electric load in Connecticut (CT) zone

16. Clusters of Winter Days
K-means clustering results
-> We chose 4 segments
Coldest
Cold

17. Daily Gas Price & Daily Load in CT
Coldest Days
Cold Days

18. Joint Distributions of Log-Transformed Data
Coldest Days
Cold Days

19. Histograms of 106 Bivariate Samples
Coldest Days
Cold Days

20. Synthetic System for Simulation
Modified IEEE 24-bus system
Modified Belgian 20-node gas system
Nodes and buses linked by gas-fired generators
Load and weather data provided by ISO-NE
Load in CT scaled to match total and allocated to buses as in IEEE system
Gas spot price data from Algonquin citygate
Demand for gas by non-electric users same as in Belgian system
Units committed and gas transportation schedules optimized in pre-processing step
One persistent challenge was obtaining relevant data, especially for the gas system

21. Impact of Gas Price Uncertainty and Constrained Gas Availability on Dispatch Cost
Coldest Days
Economic Dispatch Model
Min daily dispatch cost, subject to
Usual dispatch constraints
Limit on gas available from interruptible contracts
Available gas (constraint rhs) varied systematically
ED-PE: Economic dispatch (ED) with load marginal distribution and gas price Point Estimate
ED-PD: ED with joint electric load and gas price Probability Distribution

22. Impact of Gas Price Uncertainty and Constrained Gas Availability on Dispatch Cost
Cold Days
Economic Dispatch Model
Min daily dispatch cost, subject to
Usual dispatch constraints
Limit on gas available from interruptible contracts
Available gas (constraint rhs) varied systematically
ED-PE: Economic dispatch (ED) with load marginal distribution and gas price Point Estimate
ED-PD: ED with joint electric load and gas price Probability Distribution

23. Distances Between Cost Distributions for Various Availability Levels of Contracted Gas
Coldest Days
Cold Days
Wasserstein distance

24. Generation Mixes Adjusted to “Bomb Cyclone,” January 2018
EIA Today in Energy, January 23, 2018
What if more gas storage capacity had been available?

25. Alternative Risk-Mitigation Strategies: Simple Engineering Economic Estimates
1. Dual-Fuel Capability
2. Additional Gas Storage
Dual-fuel conversion for a unit in New England estimated to cost $3.15M
Dispatch model modified to include fuel-switching in the optimization
Same investment could be used to build and fill a gas storage facility with capacity 106Mcf
Dispatch model modified to include this additional storage

26. Probability Metric Comparison
Coldest Days
Adding gas storage reduces risk (impact of uncertainty in gas price) more than same $ investment in dual-fuel conversion in cold weather
Cold Days
Moderate Days

27. Conditional Value at Risk (CVaR) of the ED-PD Dispatch Cost Distributions
Dispatch cost w/dual-fuel
Dispatch cost w/storage
CVaRDual-Fuel
CVaRStorage
Pause here: how to reduce risk?

28. CVaR of the ED-PD Cost Distribution
Coldest Days
Adding gas storage reduces risk of high dispatch cost more than same $ investment in dual-fuel conversion
Cold Days
Moderate Days

29. Conclusions
Procedure to quantify the impact of gas spot price uncertainty on system operator’s electric energy purchase cost under restricted availability of contracted gas
Correlated electric load and gas spot price based on weather
Monte Carlo simulation of daily dispatch
Risk metrics to quantify difference in dispatch cost distribution with/without gas price uncertainty
Numerical study illustrates the procedure
Results indicate that gas storage mitigates risk more than dual-fuel conversion for the same dollar investment

30. Future Work
Generate joint distributions of gas price and electric load on hourly rather than daily basis
Represent contracted gas availability probabilistically rather than in a sensitivity study
More realistic numerical test cases that represent the actual gas network supplying an actual power system
… all these extensions require more and better data!

31. Acknowledgment
This material is based upon work supported by the Power Systems Engineering Research Center (PSERC) in collaboration with George Gross, University of Illinois Urbana-Champaign.