Technological choices for achieving the EU-objectives on climate change and renewable energy in Belgium, a sensitivity analysis. Wouter Nijs, VITO, Belgium 16/06/2009

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ The Belgian TIMES model »Energy model »Bottom-up Linear Programming model »Maximise sum of welfare; welfare defined as sum of consumer and producer surplus »All costs are discounted to 2000 with a 4% rate. »Elastic demand »Perfect competition, perfect foresight »Subjected to technical and energy political constraints »Results: »Energy flows »Investments, costs, prices »Emissions Center for Economic Studies KULeuven

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ The Belgian TIMES model »Time horizon: »End use sectors: »Domestic »Industry »Commercial »Transport »Conversion sector: »Electricity and district heat generation »Supply of Petroleum products »Non-energetic use »Renewable energy sources »Hydrogen Center for Economic Studies KULeuven

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ The Belgian TIMES energy model The premisse = A policy scenario that examines the impact for Belgium of the EU objectives for climate change and renewable energy for 2020 (nuclear decommissioned). LP Problem Max c t x Ax ≤ b x ≥ 0 Where » ctx is the objective » x is a vector of decision variables, » Ax ≤ b is a set of inequality constraints. Center for Economic Studies KULeuven

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ The research question Direction of increasing objective

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ The research question Motivation: “The Purpose of Mathematical Programming is Insight, not Numbers.” (Arthur Geoffrion, 1976) “The best solutions to real-world problems are often different solutions than the model solution.” “Knowing what is optimal, should we forget all other technologies ?”

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ The research question “Analyse the effect of »The assumption on CCS possibilities »Price elasticities on the investments in electricity and transport technologies.”..with a focus on »The “optimal” technologies »The distance of all other technologies to this optimum

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ Handling uncertainty »Post-optimality analysis of the normal least cost optimization is used for analysing electricity and transport investments [€/MWel, €/car…] »Alternative methods: »Make scenarios »Modeling to generate alternatives (MGA) »Parametric programming »Mutliobjective optimisation / Tradeoff Analysis / Stochastic Programming »…

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ Post-optimality analysis “Post-optimality” analysis = feature of LP solver GAMS 1.“Constraint ranging” 2.“Objective ranging”: how much the objective coefficient can change without changing the optimal basis Applied on investements (objrng VAR_NCAP): »“Amount by which the investment cost needs to change before the investment choices will change” »For technologies not chosen: “The minimum amount by which OBJ will change when forcing an investment”

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ Post-optimality analysis In this example, the change in investment cost is higher than indicated by the range of post-optimality analysis Original problemProblem with one cost modification Invest in Wind Invest in Gas Invest in Wind Invest in Gas

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ Post-optimality analysis »Advantages: »A robust sensitivity analysis »No extra model runs »Very quick to predict effect of change in investment cost »Could be standardised »Challenges: »“Ceteris paribus”, only change one parameter at a time; no interdependencies (example electric car vs way of producing electricity) »Only marginal changes

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ Ranking Investments BasicTechnology is chosenNo reduced cost or surplus Non-basicTechnology is chosen at higher bound (…≤ T high ) = technology restriction Reduced surplus from marginal of bound At lower bound: (…≥ T low ) = forcing a technology or = technology not chosen, T low = 0 Reduced cost from ranging of NCAP €/kW  = 667 €/kW

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ Ranking investments Post optimality  Investment cost Profitability Index »PI = _____________________ = _______________________ PV of initial investmentINVCOST »The “distance to optimum“ = PI – 100% »PI < 100%: project creates less value than capital cost »PI > 100% : “price of constraint” »PI = [85% to 115%] = Near optimal technology PV of future cash flow INVCOST – Reduced cost

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ Scenarios »No climate policy »EU2020 NOCCS: 13% renewables in final energy, CO 2 ceiling conform non-ETS target (-15%) and CO 2 price. »EU2020: idem with CCS 1234 No climate policyx EU2020 NOCCSx EU2020xx Price elasticity-0.3 0

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ Results: No climate policy + EU2020 no CCS Car transport technologies, 2020 and 2040

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ Car transport technologies, 2020 and 2040 Results: EU2020 with CCS, elasticity -0.3 and 0

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ Results: No climate policy Electricity technologies, 2020 and 2040

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ Results: EU2020 no CCS Electricity technologies, 2020 and 2040

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ Results: EU2020 with CCS Electricity technologies, 2020 and 2040

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ Results: EU2020 with CCS, inelastic Electricity technologies, 2020 and 2040

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ Conclusions »Ranking gives extra information on technology options »The effect of a cost increase/decrease can be quickly estimated »Transport technologies: »Do not differ a lot, except H 2 and electric cars »H 2 and electric cars closer to optimum through cost reduction »Impact of EU2020, CCS and price elasticity on ranking is small »Electricity technologies: »CCS is of major importance in the ranking of technologies; not to forget is CCS on gas power plants »A low price elasticity does favor wind and solar, but not CCS »Nuclear has a PI of more than 500% in all EU2020 scenario’s »Wind is a winning technology in all EU2020 scenarios »Same is true for PV if cost reduction continues

Vertrouwelijk – © 2009, VITO NV – Alle rechten voorbehouden Belgian model Research question Method Scenarios Results 16/06/ Thank you ! Contact