Incorporating Flexibility into Long-term Energy System Models

Transcription

1 Workshop on Short term versus long term energy planning Considering temporal trade-offs in decarbonisation pathways University College London, 28 April 2016 Incorporating Flexibility into Long-term Energy System Models Dr. Manuel WELSCH Planning and Economic Studies Section International Atomic Energy Agency Vienna Dr. Francesco GARDUMI Politecnico di Milano Milano International Atomic Energy Agency

2 Model Enhancements Addressing Short-term Dynamics in Long-term Models Long-term energy system models cannot incorporate daily operation of power plants Related short-term constraints may significantly impact longer term investments But constraints like ramping rates, start-up costs, minimum stable generation, efficiency curves, etc., are usually not considered Long term optimisation model was enhanced to capture the impacts of variability 2

3 Model Enhancements System Security Operating Reserve Primary & secondary, upward & downward reserve Specific reserve contributions based on ramping rates can be defined for any technology, also demand-side Minimum stable generation levels considered Minimum level of spinning reserve can be defined Cycling constraints: changes of online capacity and generation from one time slice to another can be limited No mixed-integer programming introduced Model enhancements documented in detail 3

4 Model Enhancements First Results of a Test Case (Capacity Mix in 2040) 4

5 Irish Case Study Background Comparative UCC study using TIMES & PLEXOS by Paul Deane & friends (Energy 42, ) Modelled Irelands 16% renewable energy target -> 40% renewable electricity generation by 2020 Set up OSeMOSYS like Irish TIMES model (12 time slices). Then added detail taken from the Plexos model (8760 time slices), but maintained 12 time slices Technically feasible maximum wind penetration rates are expected to range between 60 80% of the load Extending the time horizon to 2050, GHG reductions of 80% below

6 Irish Case Study OSeMOSYS results in shades of green, TIMES-PLEXOS results in shades of blue. 6

7 Irish Case Study Results for 2050 Optimised capacities based on enhanced OSeMOSYS model 7

8 Irish Case Study Results for 2050 Annual generation of the modelled power plant types 8

9 Irish Case Study Results for 2050 Deviation of capacities, discounted costs and emissions from enhanced OSeMOSYS model 9

10 The following slides present Power Plant Flexibility Considerations Enhancements by Dr. Francesco Gardumi Dr. Francesco GARDUMI Politecnico Milano Milano 10

11 Model Enhancements Power Plant Flexibility Objective To predict future energy mix considering costs and benefits of flexible power plant operation Relevance Utilities (Enel S.p.A.): Study on feasibility of flexible power plant configurations and how they would impact cash flows Cyprus Government and European Commission: Study on assessing impact of high renewable penetration in isolated systems 3 Code enhancements 1. Costs of power plant start-ups 2. Load dependent fuel consumption 3. Refurbishments to increase flexibility 11

12 Model Enhancements 1) Costs of power plant start-ups Existing model Online / Spinning Capacity calculated Constraint on changes in online capacity No explicit consideration of start-up costs New formulation Introduced cost proportional to difference of spinning capacity between consecutive time slices (ramp or start cost) C UnitCost SpinningCapacity SpinningCapacity starts,t t t 1 From utility data 12

13 Model Enhancements Efficiency % Efficiency % 2) Load dependent fuel consumption Existing models (looking at 1 time interval) Fuel consumption (FC) FC = SC load linear Efficiency (η) η = load / FC constant Where: SC = specific consumption for 1 unit of output at max cap New formulation Additional term in FC proportional to load partialisation Fuel consumption (FC) FC = SC load + + k (Nominal load load) linear Efficiency (η) η = load / FC nonlinear Real Load % Existing models Load % Real Modified model Where: k = proportionality factor (calculated to reproduce efficiency at minimum load from thermodynamic model) 13

14 Model Enhancements 3) Refurbishments to increase flexibility Existing models Characteristics of a technology defined a priori, cannot be retrofitted New formulation Introduced possibility for model to choose whether to change characteristics or not, as a function of a discrete set of possible configurations TotalInstalledCapacity ResidualCapacity + AccumulatedNewCapacity y y y min +AccumulatedRetrofittedCapacity - AccumulatedWithdrawnCapacity y y CapitalInvestment = CapitalCost NewCapacity + CostOfRetrofit RetrofittedCapacity y y y y y 14

15 2 nd Test Case Scenario Description Simplified country energy system Scenario Time domain: 2013 to 2040 night/day and 4 seasons Electricity and reserve demand: linearly increasing Price of coal / gas / CO2: 12.5 / 29 /MWh, 30 /ton, constant Min generation from RES: linearly increasing Installed capacity in 2013: none Candidate technologies: Wind turbines Coal CCGTs Capital costs [ /kw]: Variable costs [ /MWh]: Start-up costs [ /MW]: (excl. fuel) (excl. fuel) 55 15

16 Installed capacity [GW] Installed capacity [GW] 2 nd Test Case Scenario Results Costs of power plant start-ups Annual capacity with original code Annual capacity with cost of starts Year Wind Coal Gas Year Wind Coal Gas Roles of coal and gas can be completely inverted, when cost of starts accounted 16

17 Annual reserve [TWh] Annual reserve [TWh] 2 nd Test Case Scenario Results Load dependent fuel consumption Annual reserve without fuel consumption Annual reserve with fuel consumption Year Year Coal Gas Coal Gas Share of reserve provision changes significantly. Doesn t affect investment decisions of governments, but it may affect those of companies. 17

18 Cyprus Case Scenario Description Existing structure of Cyprus energy system modelled in detail Code enhancements for Cost of the starts and Variable fuel consumption introduced Time domain: from 2013 to 2040 Scenario Time slices: 63 time slices (7 seasons, work days divided in 6 parts, weekend days in 3) Demand & fuel prices: projections from national TSO CO2 prices: high bound projections from TSO (from 6.6 /tonne in 2013 to 103 in 2040) Reserve capacity demand: Min generation from RES: computed endogenously, proportional to average renewable generation no constraint All power plants existing in the island modelled Candidate new power plants: CCGT, ST, ICE, Wind, PV, CSP, Biogas, PHS, batteries 18

19 Annual reserve [GWh] Annual reserve [GWh] Cyprus Case Results Annual reserve without enhancements. Annual reserve with enhancements Year Vasilikos CCGT Vasilikos ST Vasilikos GT Dhekelia ST Dhekelia ICE Moni GT New CCGT Flow batteries Pumped hydro Year Vasilikos CCGT Vasilikos ST Vasilikos GT Dhekelia ST Dhekelia ICE Moni GT New CCGT Flow batteries Pumped hydro Higher provision by pumped hydro storage, less by steam turbines, constant by CCGTs Highly constrained scenario (by planned policies of the Government) -> Flexibility has impact on the operation of the technologies, not on the investments Capacities and generation did not change too much 19

20 Joint Conclusions Dr. Manuel WELSCH Planning and Economic Studies Section International Atomic Energy Agency Vienna Dr. Francesco GARDUMI Politecnico Milano Stockholm 20

21 Conclusions When considering RE scenarios, not considering operating reserve means wrong, unrealistic results. Long-term energy systems models which omit short-term constraints: In conventional model for Ireland, up to 23.5% of the total capacity assigned to different power plant types than when considering operating reserves. Soft-linking: two separate models have to be set-up and maintained; no overall optimisation across the two models -> identified capacity investments may not present the economically most efficient pathway Integrating operational aspects into the long-term models: 95.0% of dispatch results of Ireland model matched those of an interlinked model with a 700 times higher temporal resolution. Adding start-up costs: May significantly change the dispatch as shown in demo case 2. Four more equations is all that is needed. Adding load dependent fuel consumption: Depends on size of system, but may not significantly affect investments. Recommended if reserve provision is of interest. One more equation. Adding refurbishment option: Depends on level of detail to be considered 21

22 References F. Gardumi. A Multi-dimensional Approach to the Modelling of Power Plant Flexibility. PhD Thesis, Politecnico di Milano, Italy, S. Kesharvarzian, F. Gardumi, M. Rocco, E. Colombo, An Off-design Thermoeconomic Input-Output Analysis of a Natural Gas Combined Cycle Power Plant. Proc. of the 28th ECOS Conference. Pau, France, M. Welsch, M. Howells, M. Hesamzadeh, B. Ó Gallachóir, P. Deane, N. Strachan, et al. Ensuring Supporting Security and Adequacy in Future Energy Systems The need to enhance long-term energy system models to better treat issues related to variability. International Journal of Energy Research, M. Welsch, P. Deane, F. Rogan., et al. A Case Study on High Levels of Renewable Electricity Penetration in Ireland, Applied Energy, M. Welsch. Enhancing the Treatment of Systems Integration in Long-Term Energy Models. PhD Thesis, KTH Royal Institute of Technology, Stockholm, M. Welsch, D. Mentis, M. Howells. Long-term Energy Systems Planning: Accounting for Short-term Variability and Flexibility. Book Chapter in: Renewable Energy Integration. Elsevier,

23 Thank you for your attention 23