MIXOPTIM: A MONTE CARLO SIMULATION TOOL FOR THE EVALUATION AND

Transcription

1 TECHNICAL WORKSHOP: DYNAMIC NUCLEAR FUEL CYCLE MIXOPTIM: A MONTE CARLO SIMULATION TOOL FOR THE EVALUATION AND OPTIMIZATION OF AN ELECTRICITY MIX Axel Laureau Post-doctoral position CEA Cadarache MIXOPTIM team: CEA - B. Bonin, G. Krivtchik, A. Laureau, H.Safa CNRS - E. Merle IRSN - O. Jacquet, J. Miss, Y. Richet 1 7 JUILLET 2016

2 OUTLINE I. ELECTRICITY MIX II. MIXOPTIM - GENERAL APPROACH - MIX STUDY - SCENARIOS III. ONGOING DEVELOPMENTS - ENERGY STORAGE - OPTIMIX PROJECT - NEEDS PROGRAM 2

3 ELECTRICITY MIX Context: the power demand must be satisfied different ways to produce energy 3

4 ELECTRICITY MIX Context: the power demand must be satisfied different ways to produce energy Consumption Demand [GW] [source : RTE ] 3

5 ELECTRICITY MIX Context: the power demand must be satisfied different ways to produce energy Consumption Demand [GW] january Demand [GW] june [source : RTE ] 3

6 ELECTRICITY MIX Context: the power demand must be satisfied different ways to produce energy Consumption Controllable source Demand [GW] [GW] gas run of river nuclear january Demand [GW] june [source : RTE ] 3

7 ELECTRICITY MIX Context: the power demand must be satisfied different ways to produce energy Consumption Controllable source Demand [GW] [GW] gas run of river nuclear january run of river june Demand [GW] june [GW] lake Pumped Storage Power Station [source : RTE ] 3

8 ELECTRICITY MIX Context: the power demand must be satisfied different ways to produce energy Demand [GW] Consumption [GW] gas Controllable source run of river nuclear [GW] Fatal source solar wind sum january run of river june Demand [GW] june [GW] lake Pumped Storage Power Station [source : RTE ] 3

9 ELECTRICITY MIX Context: the power demand must be satisfied different ways to produce ener gy [GW] Demand [GW] nuclear gas run of river january june [GW] Demand [GW] run of river wind june june january Pumped Storage Power Station 3 sum lake [source : RTE ] solar Fatal source [GW] [GW] Controllable source Consumption

10 availability factor january run of river kp load factor run of river [GW] Demand [GW] gas??? usually, the k p values are assumed lake june june [B. Bonin, H. Safa, A. Laureau, E. Merle-Lucotte, J. Miss, Y. Richet, MIXOPTIM: a tool for the evaluation and the optimization of the electricity mix in a territory, Eur. Phys. J. Plus, 129, 198,2014 ] Pumped Storage Power Station [source : RTE] how can we make a simple tool able to take into account the expansion of the fatal sources and the interactions between sources? june 4 sum Mixoptim [GW] kd nuclear [GW] Context: the power demand must be satisfied different ways to produce ener gy Ongoing studies: increasing renewable par t in the mix! Consumption Controllable source Fatal source fatal production complex to model solar wind demand 2015 the production of conventional sources depends on the availability of other sources [GW] Demand [GW] ELECTRICITY MIX january

11 MIXOPTIM - GENERAL APPROACH Objective: predict the behavior of a non-existing electricity mix using an existing mix The production chronicles reflect past events, changing one source production affect the others [GW] gas run of river nuclear 5

12 MIXOPTIM - GENERAL APPROACH Objective: predict the behavior of a non-existing electricity mix using an existing mix The production chronicles reflect past events, changing one source production affect the others [GW] gas run of river nuclear while the availability chronicles are almost an intrinsinc charateristic of the sources 5 Wind availability law

13 MIXOPTIM - GENERAL APPROACH production max: 130 GW demand max: 100 GW 6

14 MIXOPTIM - GENERAL APPROACH Wind probablity law 10 GW installed production max: 130 GW demand max: 100 GW 6

15 MIXOPTIM - GENERAL APPROACH 3 GW 30% Wind probablity law 10 GW installed 3 GW production max: 130 GW demand max: 100 GW 6

16 MIXOPTIM - GENERAL APPROACH 3 GW 30% Wind probablity law 10 GW installed 3 GW priority! 86 GW production max: 130 GW demand max: 100 GW 6

17 MIXOPTIM - GENERAL APPROACH 3 GW 30% Wind probablity law 82 GW 10 GW installed 3 GW priority! 86 GW production max: 130 GW 82 GW demand max: 100 GW 82 GW 6 Consumption probablity law

18 MIXOPTIM - GENERAL APPROACH 3 GW 60E/MWh 30% Wind probablity law 82 GW Interconnection cost probablity law 10 GW installed 3 GW priority! 86 GW production max: 130 GW 82 GW demand max: 100 GW 82 GW 6 Consumption probablity law

19 MIXOPTIM - GENERAL APPROACH 30% 3 GW Wind probablity law 82 GW capacity: 7 GW export: 4 GW 60E/MWh Interconnection cost probablity law 10 GW installed 3 GW priority! 86 GW production max: 130 GW 82 GW demand max: 100 GW 82 GW 6 Consumption probablity law

20 MIXOPTIM - GENERAL APPROACH 30% 3 GW Wind probablity law 82 GW capacity: 7 GW export: 4 GW 60E/MWh Interconnection cost probablity law 10 GW installed 3 GW priority! 86 GW production max: 130 GW 82 GW demand max: 100 GW 82 GW Calculation output: energy production: who and how much CO2 production production cost (with import/export) ability to support (or not) the demand 6 Consumption probablity law

21 MIXOPTIM - GENERAL APPROACH 30% 3 GW Wind probablity law 82 GW capacity: 7 GW export: 4 GW 60E/MWh Interconnection cost probablity law 10 GW installed 3 GW 86 GW the whole procedure is repeated a large number of times and an average behavior is estimated priority! production max: 130 GW 82 GW demand max: 100 GW 82 GW Calculation output: energy production: who and how much CO2 production production cost (with import/export) ability to support (or not) the demand 6 Consumption probablity law

22 MIXOPTIM - GENERAL APPROACH Two aspects modeled: Availability law Spectral analysis Solar availability chronicle Consumption chronicle 7

23 MIXOPTIM - GENERAL APPROACH Two aspects modeled: Availability law Spectral analysis Solar availability chronicle Consumption chronicle Availability law: Represents correctly all the possible configurations Suppress the temporal aspect Probability day summer day winter night summer night winter Probability 7

24 MIXOPTIM - GENERAL APPROACH Two aspects modeled: Availability law Spectral analysis Solar availability chronicle Consumption chronicle Availability law: Represents correctly all the possible configurations Suppress the temporal aspect Probability Amplitude day summer day day winter night summer Spectral analysis Amplitude night winter Probability Spectral analysis: Represents the characteristics frequency-amplitude of the source/consumption The controllable sources must be able to counterbalance the fatal sources+consumption fluctuations Amplitude week day Amplitude Frequency [day -1 ] Frequency [day -1 ] 7 Frequency [day -1 ] Frequency [day -1 ]

25 MIXOPTIM - MIX STUDY Input file using xml format: (...) <pwr marginal_cost="10." fixed_cost="12." marginal_co2="0." fixed_co2="1.5e-3" priority_order="4" direct calculation power="63130." alias_availability_law="pwr_law"/> (...) <pwr_law> <chronicle path="data/raw/pwr_data" nb_bin_per_day="48" nb_bin_in_law="100"/> <loi_1 val=" "/> <loi_2 val=" "/> <loi_3 val=" "/> <loi_4 val=" "/> </pwr_law> (...) or use given law 8

26 Example of the French electricity mix MIXOPTIM - MIX STUDY input 9

27 Example of the French electricity mix MIXOPTIM - MIX STUDY input 10

28 MIXOPTIM - MIX STUDY French electricity mix and - 30 GW PWR without replacement (undersized park) +12% +100% 116 vs 0.02 h/year 11

29 MIXOPTIM - MIX STUDY French electricity mix and - 30 GW PWR + 30 GW wind + 30 GW solar +75% (+12%) +60% (+100%) 21 vs 0.02 h/year (116 vs 0.02 h/year) 12

30 Preliminary results MIXOPTIM - SCENARIOS scenario ANCRE DIV - diversification of the power sources + consumption reduction input Consumption depreciation of the MW present PWR wind solar EPR gas coal MW installation cost 13

31 Preliminary results MIXOPTIM - SCENARIOS scenario ANCRE DIV - diversification of the power sources + consumption reduction input Consumption depreciation of the MW present PWR wind solar EPR gas coal MW installation cost 13

32 Preliminary results MIXOPTIM - SCENARIOS scenario SOB - renewable priority + consumption reduction input Consumption MW present PWR wind solar EPR gas coal MW CO 2 reduced 14

33 ONGOING DEVELOPMENTS - ENERGY STORAGE DEPENDING OF SCENARIOS, MASSIVE ENERGY STORAGE WILL BE REQUIRED Generate chronicles for the storage: The fatal sources can be mixed in a macro source assumption: perfect prediction of the future production assumption (so far): no storage yield & no storage limit power ramp 0.5GW solar + 0.5GW wind + storage 0.17GWh (1h at average power) storage without storage with storage normalized chronicle only depends on the solar/wind and storage/power ratios 15

34 ONGOING DEVELOPMENTS - ENERGY STORAGE 0.5GW solar + 0.5GW wind + storage 0.17GWh (1h at average power) storage 1.7GWh (10h at average power) storage without storage with storage 16

35 ONGOING DEVELOPMENTS - ENERGY STORAGE 0.5GW solar + 0.5GW wind + storage 0.17GWh (1h at average power) storage 1.7GWh (10h at average power) Probability storage without storage day summer with storage Model the influence of storage: Probability law Spectral analysis Preliminary observation: storage = probability deviation reduction peak reduction impact on the mix? day winter night summer night winter day summer day winter night summer night winter Amplitude Amplitude Probability Amplitude Amplitude Frequency [day -1 ] Frequency [day -1 ] 16 Frequency [day -1 ] Frequency [day -1 ]

36 MIXOPTIM - MIX STUDY WITH ENERGY STORAGE French electricity mix and - 30 GW PWR + 30 GW wind + 30 GW solar + no storage +75% +60% 21 vs 0.02 h/year 17

37 MIXOPTIM - MIX STUDY WITH ENERGY STORAGE French electricity mix and - 30 GW PWR + 30 GW wind + 30 GW solar + storage: 10h rnw average power +73% (+75%) +55% (+60%) 18 Preliminary results no cost on the storage!!! 9 vs 0.02 h/year (21 vs 0.02 h/year)

38 ONGOING DEVELOPMENTS - OPTIMIX PROJECT - NEEDS PROGRAM Le projet consiste à simuler le fonctionnement d un mix électrique sur un territoire pour explorer les limites physiques d introduction des renouvelables dans le mix, du point de vue de sa capacité de suivi de charge. On se propose d utiliser pour cela le logiciel de simulation MIXOPTIM, qui fait l analyse spectrale des fluctuations de la charge, pour en déduire la capacité maximale acceptable en éolien et en solaire dans un mix, en fonction des hypothèses retenues sur les fluctuations de la demande et sur l agilité des sources pilotables présentes dans le mix. Dans un deuxième temps, on se propose de regarder comment les limites d introduction des sources renouvelables fatales déterminées dans la phase 1 sont déplacées par le stockage et l interconnexion. Il est également envisagé d étudier ce que deviennent les limites si on cesse de considérer l éolien et le solaire comme des sources fatales, et si on en fait des sources pilotables à la baisse. physical limit of renewables in the mix spectral analysis storage interconnection renewable = downwards controllable source partners: CEA CNRS IRSN Bernard Bonin Axel Laureau Henri Safa Elsa Merle Nicolas Thiollière 19 Erci Dumonteil Joachim Miss Yann Richet