Model coupling across scales An introduction to methodological - PowerPoint PPT Presentation

Model coupling across scales An introduction to methodological aspects related to model coupling Mitglied der Helmholtz-Gemeinschaft 04. December 2014 | Heidi U. Heinrichs

Agenda Flexibility  Definition  Needs  Approaches  Model coupling  Energy system models  Types  Dimensions  Mitglied der Helmholtz-Gemeinschaft Challenges & limits  Conclusions  Institute for Energy and Climate Research 1 Systems Analysis and Technology Evaluation (IEK-STE)

Flexibility… „… ability to respond to – and to balance – supply and demand under rapid and large imbalances...“ [Gracceva & Zeniewski, 2014] “…expresses the extent to which a power system can modify electricity production or consumption in response to variability, expected or otherwise.” [IEA, 2011] Mitglied der Helmholtz-Gemeinschaft [IEA, 2012] Different definitions of flexibility of energy systems exist. Institute for Energy and Climate Research 2 Systems Analysis and Technology Evaluation (IEK-STE)

The need to address flexibility Past High share of thermal power plants = sufficient flexibility Increasing share of volatile renewable energy sources Trend (RES) = (short- and long-term) uncertainties Mainly forecast deviations (i.e. wind feed-in, electricity Source exchange, end-use demand, fuel prices) Demand response, grid and storage expansion, excess Options capacity, curtailment of RES Mitglied der Helmholtz-Gemeinschaft Previous sources of flexibility decrease. New sources and options need to be taken into account in analysis approaches. Institute for Energy and Climate Research 3 Systems Analysis and Technology Evaluation (IEK-STE)

Approaches to address flexibility (Basic) heuristics Model coupling Specific indicators Availability factors Energy system Loss of Load    model Probability (LOLP) Reserve factors  Unit commitment Loss of Load Function of RES    /dispatch model Expectation (LOLE) penetration level Macroeconomic Magnetic & kinetic Operating reserve    models reserves (H mag , requirements H kin ) Mitglied der Helmholtz-Gemeinschaft focus on model coupling including the systems here: perspective (= energy system model) Institute for Energy and Climate Research 4 Systems Analysis and Technology Evaluation (IEK-STE)

Typical characteristics of energy system models Full energy system  Technology-rich (bottom-up)  Medium- to long-term, multiple period time horizon  Aggregation  Temporal = time slices (i.e. from 6 to 144)  Spatial = limited number of regions  Mitglied der Helmholtz-Gemeinschaft No direct account of short-term uncertainties possible. Institute for Energy and Climate Research 5 Systems Analysis and Technology Evaluation (IEK-STE)

Types of model coupling Unidirectional Iterative   model A model B model A model B More than 2 Semi (derive heuristics)   Mitglied der Helmholtz-Gemeinschaft model A model B model C model A model B Institute for Energy and Climate Research 6 Systems Analysis and Technology Evaluation (IEK-STE)

Types of model coupling – example I Unidirectional  TIMES PLEXOS Case study: Ireland, 2020  Motivation of coupling: accepting that one specific modelling  tool cannot model everything Results:  Mitglied der Helmholtz-Gemeinschaft Crosschecking the technical appropriateness  Most important technical constraint = start costs  Institute for Energy and Climate Research 7 Systems Analysis and Technology Evaluation (IEK-STE)

Types of model coupling – example I Mitglied der Helmholtz-Gemeinschaft [Deane et al., 2012] Institute for Energy and Climate Research 8 Systems Analysis and Technology Evaluation (IEK-STE)

Types of model coupling – example II Iterative + more than 2  EV-PEN/LVP PERSEUS-EU PERSEUS-DE Case study: Germany, until 2030  Motivation of coupling: to cover divergent trends and their  interdependencies Mitglied der Helmholtz-Gemeinschaft Results:  Equilibria between electricity costs & EV market share and  between national & European power plant expansions Institute for Energy and Climate Research 9 Systems Analysis and Technology Evaluation (IEK-STE)

Types of model coupling – example II EV electricity demand electricity imports and exports of DE EV load shifting potential CO 2 certificate prices .  Electric mobility model Energy system model PERSEUS-EMO* EU 1 incl. ETS 2 EU EV market penetration DE + T-grid mobility surveys passenger road transport technical EV potential economic EV potential EV market penetration Mitglied der Helmholtz-Gemeinschaft electricity and power plant CO 2 certificate prices expansion in DE *PERSEUS-EMO: Program Packages for Emission Reduction Strategies for Energy Use and Supply – Electric Mobility, [Heinrichs, 2013] 1 EU: only those countries who mainly influences the German energy system, 2 ETS: Emission Trading System Institute for Energy and Climate Research 10 Systems Analysis and Technology Evaluation (IEK-STE)

Dimensions of differences Temporal Spatial   … … System boundary Method   Optimization  macroeconomics Simulation  energy system Mitglied der Helmholtz-Gemeinschaft Heuristic supply distribution demand  sector sector sector …  Institute for Energy and Climate Research 11 Systems Analysis and Technology Evaluation (IEK-STE)

Dimensions of differences – example I Spatial System boundary Temporal Method Germany  grid energy system  time slices  LP  nodes electricity grid hours simulation grid IKARUS model Case study: Germany, until 2030  Motivation: to analyse the impacts of EV on the German grid  Results:  Mitglied der Helmholtz-Gemeinschaft simple heuristic for spatial distribution of new power plants  no need for new power plant sites  Institute for Energy and Climate Research 12 Systems Analysis and Technology Evaluation (IEK-STE)

Dimensions of differences – example I legend new power plant legend Gas power plants 2030 Lignite Lignite Coal Gas Coal power plants 2010 Nuclear Mitglied der Helmholtz-Gemeinschaft Lignite Gas Coal Institute for Energy and Climate Research [Linssen et al., 2012] 13 Systems Analysis and Technology Evaluation (IEK-STE)

Dimensions of differences – example II Spatial System boundary Temporal Method Germany  energy system  time slices  LP  Europe road transport years simulation COMIT PERSEUS Case study: Germany, until 2030  Mitglied der Helmholtz-Gemeinschaft Motivation: to analyse sectoral interdependencies of including  road transport in the EU ETS Results: cross sectoral efficient CO 2 abatement strategies  Institute for Energy and Climate Research 14 Systems Analysis and Technology Evaluation (IEK-STE)

Dimensions of differences – example II allowance demand of road transport, EV market penetration and electricity demand uranium hydro ‐ river/reservoir/small lignite wind ‐ on/off worldgas Freight road transport CO 2 emission trading localgas biomass/ ‐ gas/ ‐ waste worldcoal Agent from ‐ storage localcoal geothermal worldoil cc ‐ regional fuelmarket cc ‐ cc ‐ CO 2 market industrial industrial cc ‐ cc ‐ cc ‐ ZEW lignite producers heatgrid industrial indigenous regional certificate heavy ‐ / supply demand resources fuelnode fueloil cc ‐ ind. cc ‐ ind. hydro ‐ small uranium gas powergrid powergrid Agents coal wind ‐ on/off hydro ‐ river/ ‐ exp ‐ imp biomass/ oil reservoir fuel price oil companies ‐ gas/ ‐ waste geothermal logit choice cc ‐ cc ‐ cc ‐ utility cc ‐ utility cc ‐ utility green district producers producers producers fuel price fuel demand/ Agents generators heating fossil hydro nuclear neigh ‐ fuel demand/ CO 2 demand shipper, haulier CO 2 demand bouring train and IWW district ‐ districtheat heat or carrier cc ‐ utilitysupply country cc ‐ Passenger road transport cc ‐ district ‐ heat/ Agents renew ‐ cc ‐ internalgridnode heat heat ‐ transport ables smallchp households demand Class cc ‐ company external cars cc ‐ electr ‐ district ‐ cc ‐ heat ‐ MOP gridnode demand demand Class vehicles cc ‐ cc ‐ cc ‐ cc ‐ cc ‐ private car demand districtheat electricity heat pumped dc_cable ‐ car demand With: cars consumers consumers consumers storage node information flows Mitglied der Helmholtz-Gemeinschaft ZEW shipment database (Agents) heat_use electricity_use to_storage IWW inland waterways car companies MOP German Mobility Panel database regional energy carrier electricity electricity demand world market fuels heat heat demand CO 2 marginal cost [Heinrichs et al., 2014] Institute for Energy and Climate Research 15 Systems Analysis and Technology Evaluation (IEK-STE)

Challenges & limits of model coupling General: Global optimum  Convergence in iterative model coupling (bang-bang)  Computational capacity requirements (hard- & software, time)  Expertise in each modelling tool  Data basis  Obligation of confidentiality (in collaborations)  Different base years/ calibration (possibly high effort)  Mitglied der Helmholtz-Gemeinschaft Different methods (i.e. costs & end user prices)  Institute for Energy and Climate Research 16 Systems Analysis and Technology Evaluation (IEK-STE)