Working with TIMES and Monte Carlo in a Policy Setting

Transcription

1 Wrking with TIMES and Mnte Carl in a Plicy Setting 72TH SEMI-ANNUAL ETSAP MEETING, ETH Zürich, Switzerland, December 11, 2017 Kristffer S. Andersen, Advisr, Danish Energy Agency and PhD student, Technical University f Denmark December 18, 2017 Page 1

2 IntERACT Integrated Energy and Ecnmic Tl Technlgical Explicitness TIMES-DK Develpers: General Equilibrium Feedback CGE Behaviural Realism December 18, 2017 Page 2

3 Agenda 1. Why cnsider uncertainty 2. Implementing uncertainty in the IntERACT mdel 3. Wrking with uncertainty in a plicy setting December 18, 2017 Page 3

4 IntERACT: Tw ptimizing criterias 1. Determine least cst lw carbn transitin pathways 2. Minimize csts f pathway uncertainty related t: Investment cst Fuel and emissin prices Plicy Behavir Cst Pathway A Pathway B December 18, 2017 Page 4

5 Why we cnsider uncertainty Externally 1. Means f quantifying the uncertainty assciated with a plicy prpsal 2. Facilitates dialgue with stakehlders as it prvide additinal insight int a cmplex mdel (pening the black bx) Internally 1. A means f testing the mdel and identifying pssible weakness in assumptin and mdel structure 2. Gives a higher degree f cnfidence in the mdel December 18, 2017 Page 5

6 Agenda 1. Why cnsider uncertainty 2. Implementing uncertainty in the IntERACT mdel 3. Wrking with uncertainty in a plicy setting December 18, 2017 Page 6

7 Recnciling Engineers and Ecnmists TIMES-DK Energy System Mdel Change in demand fr energy services Price f energy services Energy subsidies and taxes Change in capital intensity CGE General Equilibrium Mdel TIMES-DK Optimizes Danish energy system twards Ecnmic sectrs Pwer and district heat sectr Residential sectr Transprt sectr Electricity exchange with neighburing cuntries 32 time slices CGE mdel 20 ecnmic sectr One husehld Gvernment Freign trade Sft-link 12 Ecnmic sectrs Pwer and district heating sect Residential sectr December 18, 2017 Page 7

8 Husehld Heat Services in TIMES-DK Heat services are measured as Mm2 in the mdel The building are split in befre and after 1972 and in multi-stry (multi strey+nn-detached) and detached (detached+farm huses) In the current versin we d nt assume any rebund effect n heat demand frm chaning the price f heat service IntERACT TIMES-DK 8

9 Industry structure i TIMES-DK Fuel input Electricity District heating Cal Natural gas Diesel Fuel il Slid bimass Bigas Bifuels Taxes and subsidies Sectr and energy service specific Cnversin technlgies Sectr and energy service specific Savings ptentials Sectr and energy service specific 12 Ecnmic sectrs Capacity cnstraints Sectr and energy service specific Energy services demand High temperature (>150 C) Medium temperature (<150 C) Rm heat Electric mtrs and cling Light and IT Tractr services etc (agriculture sectr nly) Frk lifts Agriculture, frestry, fishing, gravel & stne Fd, beverages, tbacc industry Chemical industry (excl manufacture f basic metals) Metals, machinery and transprt equipment industry Cement and bricks, glass and ceramics Other cmmdity prductin Whlesale and retail trade Private service industries (incl supprt fr transprtatin and pstal activities) Public services industries Cnstructin Other utilities Mtr vehicles - purchase and repair Sectr specific demand drivers frm CGE mdel 18. december 2017 Side 9

10 IntERACT: Iteratin rutine TIMES -> CGE Electricity and district heat prductin and prices Fuel use supply sectr (%TIMESbaseline%.gdx) Tp-dwn assumptins: Grwth assumptins, elasticities, macr clsure. IntERACT cckpit (MS Excel) Defining baseline and alternative scenaris CGE reference Baseline scenari ( ) Baseline (iteratin) TIMES-DK Baseline scenari Bttm-up assumptins: ChseTIMES scenari CGE->TIMES Adjusted demand prjectin (%ZZ-CGE_Linking%.dd) TIMES -> CGE Electricity and district heat prices, fuel mix, subsidies and taxes (%TIMESscenari%.gdx) CGE prductivity indicies CGE alternative Alternative scenaris Alternative scenaris (iteratin) TIMES-DK Alternative scenari Reprt ( ) CGE->TIMES Adjusted demand prjectin (%ZZ-CGE_Linking%.dd) 10

11 IntERACT: Mnte Carl rutine 1. Define the prces and/r cmmdity sets fr which uncertainty is t be cnsidered 2. Define the uncertainty distributin(s) in R 3. Start lp in R, where each lp-iteratin draws samples frm the uncertainty distributin(s). i. Write the draws int a dd-file used by TIMES ii. Run IntERACT iteratin rutine inside R i. Baseline ii. Plicy iii. Save relevant utput in R 4. Lk at results

12 2) Define Uncertainty Distributin 1) Define MnteCarlPRC(PRC) 3) Run R lp, draw frm distributin and write the draw int dd-file ACT_EFF(REG,ALLYEAR,PRC,"ACT",ALL_TS)$MnteCarlPRC(PRC) = ACT_EFF(REG,ALLYEAR,PRC,"ACT",ALL_TS)*0.97 Save relevant utput in R

13 Agenda 1. Why cnsider uncertainty 2. Implementing uncertainty in the IntERACT mdel 3. Wrking with uncertainty in a plicy setting December 18, 2017 Page 13

14 Wrking with uncertainty in a plicy setting Reduce tax n electricity fr heating in rder t incentivize the adptin f heat-pumps fr rm-heat in husehlds and industry. Hw des uncertainty with t the cst effectiveness f heat pump and market price f electricity affect the adaptin f heat pumps in IntERACT? December 18, 2017 Page 14

15 Wrking with uncertainty (timeline) September Early Octber Late Octber Nvember # f sensitivity Iteratins # f sensitivity input parameters # f scenaris # f IntERACT iteratins by each scenari # f IntERACT mdel iteratins # f hurs December 18, 2017 Page 15

16 Husehld demand respnse frm a reductin in tax n electricity fr heat (PJ) Bimass Electricity District heat Natural gas Olie Slar heat Preliminary results based n IntERACT v December 18, 2017 Page 16

17 Husehld and industry electricity demand respnse fllwing different levels f reductin in tax n electricity fr heat (PJ) Husehld Industry Bimass Electricity District heat IntERACT v Natural gas Olie Slar heat Preliminary results based n IntERACT v December 18, 2017 Page 17

18 Take ways 1. Sensitivity analysis n TIMES can be implemented fairly easy in R, which allws fr a high degree f flexibility in bth in input variatin and visualsatin f results. 2. Using uncertainty analysis has prven t be a key tl bth internally fr mdel testing and externally fr quantifying plicy uncertainty. 3. Further wrk fcus n hw t develp and refine the use f sensitivity analysis in the IntERACT mdel. December 18, 2017 Page 18