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Equilibrium Modeling of Combined Heat and Power Deployment. Anand Govindarajan Seth Blumsack Pennsylvania State University USAEE Conference, Anchorage, 29 July 2013. Problem Statement.
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Equilibrium Modeling of Combined Heat and Power Deployment AnandGovindarajan Seth Blumsack Pennsylvania State University USAEE Conference, Anchorage, 29 July 2013
Problem Statement • Assess the economic potential for Combined Heat and Power (CHP) in electricity-market equilibrium framework, accounting for the impact that CHP adoption will have on electricity prices
Some Motivation • U.S. utilization of CHP is low but technical potential is vast • Utilization pathway for shale-gas supplies Current CHP capacity Technical potential for additional CHP
Basic CHP Economics • Increased efficiency of heat + electricity (adsorptive chiller can add cooling) • Avoided electricity purchases • Other benefits : reduced emissions, reliability benefits
Technical vs Economic potential • CHP investment reduces demand for grid provided power, lowering market price • At some point, incremental CHP units become uneconomical • The economic potential maybe different(less) than the technical potential
Philadelphia Case Study • We use Philadelphia, PA as a case study for our equilibrium modeling • High technical potential, high electricity prices • Transmission constrained
Supply curve modeling (Sahraei-Ardakani et al 2012) We want to identify: Thresholds where the marginal technology changes; The slope of each portion of the locational dispatch curve.
CHP Load Profiles Building-integrated CHP (BCHP) tool used to generate profiles for eight building types Electric load-following (FEL) and thermal load-following (FTL)
Energy Savings from Incremental CHP Investment in Philadelphia Assumes $4/mmBTU natural gas price
Energy Savings from Incremental CHP Investment in Philadelphia Assumes $8/mmBTU natural gas price
Conclusion: Are High Gas Prices Good for CHP? • Higher gas prices may mean more economic opportunities for CHP, otherwise economic potential is perhaps 1/3 of technical potential. • Disproportionate impacts on electricity prices relative to operational costs • FTL maybe a more economical operational strategy when fuel prices are low $4/mmBTU Gas $8/mmBTU Gas
Thank You! AnandGovindarajan axg5179@psu.edu
Life is Heaven When Gas is $7 Price separation between fuels (on $/MBTU basis) means that thresholds are easy to identify. Note: Other fuel prices – Coal $2/mmBTU; Oil $20/mmBTU
Life Ain’t a Breeze When Gas is $3 When relative fuel price differences are small, a mix of fuels/technologies can effectively be “on the margin.” Note: Other fuel prices – Coal $2/mmBTU; Oil $20/mmBTU
Estimation Procedure Classification parameters Generation i CMA-ES OLS Regression Regression Parameters / SSE Generation i-1 We want to minimize the SSE of: Choose initial parameters φ Find associated slope parameters ω using least squares Given estimates for ω and the regression SSE, choose a new set of threshold parameters φ* Repeat until convergence.
Estimating Threshold Functions Thresholds are estimated using a fuzzy logic approach to capture multiple marginal fuels: Relative fuel price threshold for having the fuzzy gap Fuzzy gap width coefficient
Example Result Wide band where gas/coal are jointly setting prices. More defined threshold between gas and oil.
Supply Curve Modeling • Philadelphia is transmission-constrained, so the available capacity of a generator is not relevant – only the amount of electricity that is deliverable to a location in the network. • Power Transfer Distribution Factor (PTDF): G2 G1 k
Piecewise Supply Curve Estimation Slope of the relevant portion of the supply curve Threshold indicator function