ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
Università di Pavia, Facoltà di Ingegneria
SISTEMI DI TECNOLOGIE ENERGETICHE E
MODELLI DI PROGRAMMAZIONE ECONOMICA
G.C. Tosato – <[email protected]>
Pavia, 13 Maggio 2002 - Dipartimento Ingegneria Elettrica,
Aula Seminari, Piano C, - via Ferrata, 1
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
ARGOMENTI
1.
2.
SETTORE ENERGETICO: PROBLEMATICHE
------------------------------------------DESCRIZIONE QUANTITATIVA: ELEMENTI E
VARIABILI DEL SISTEMA, INVENTARI
3.
SISTEMA: IDENTIFICAZIONE DELLE CORRELAZIONI,
SPIEGAZIONE DEGLI EVENTI
4.
MODELLI: RAPPRESENTAZIONE DEL SISTEMA,
PROIEZIONI E VALUTAZIONI
-----------------------------------------GENERATORI DI MODELLI TECNOLOGICI
5.
6.
DOMANDE; ESEMPI: Modelli e scenari, Confronto di
opzioni tecnologiche, Valutazione di politiche e misure
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
1 - Settore energia: domande strutturali
• Che problemi ci riserva nel suo sviluppo? Riserve
sufficienti? Costi compatibili? Inquinamento? Sviluppo
sostenibile o no? Equità intergenerazionale?
• Quanto siamo lontani dalla sostenibilità?
• Quanto costa mitigare i cambiamenti climatici?
• Che distanza fra prezzi attuali e costi sostenibili?
• Quanto e come investire per cambiare rotta? ricerca?
• Quale equilibrio di lungo termine tra sistema
energetico e resto del sistema economico? Tra paesi
più e meno sviluppati? Equità internazionale?
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
2a - Nodi: tecnologie energetiche
Quale spazio per migliorare l’efficienza / il costo di
produzione? (ingegnere, tecnico)
•
Settori
•
Parametri di caratterizzazione
•
Fonti di DB tecnologici
•
Esempio: IKARUS (Germany)
•
Essempio: EM (World Bank)
5
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
Settori
RESOURCES
PRODUCTION (Supply)
ENERGY
TECHNOLOGIES
ENDUSE (Demand)
Mining
Residential/Service
Transformation
Industry
Conversion
Transportation
Transport & Distr
Cross - sectors
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
Parametri di caratterizzazione
GENERAL
TECHNICAL
ECONOMIC
ENVIRONMENTAL
LABOUR & MAT. REF.
technology
techn. sector
data quality
technical availability
commercial availab.
prototype
commercialization
market share
av. size
existing capacity
construction time
technical life
max. availability
av. availability
energy input
energy output
currency
costs
- investiment
- fixed o&m
- variable o&m
- fuel
- total ex. fuel
- total incl. fuel
- decommiss.
GHG emissions
solid waste
liquid waste
gaseous waste
acustic impact
land use
materials
- steel
- concrete
-…
-…
labour
- construction
- operation
title
autor
editor
type
year
access
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
Esempio di caratterizzazione
CO2
CO2-EQUIVALENTE
g/kWh
g/kWh
957,4
143,2
840
-
MONETA
INVESTIMENTO
FISSI ANNUI
VARIABILI NON FUEL
FUEL
TOT NON FUEL
TOT
$
$/KW
$/KW/a
$/kWh
$/kWh
$/kWh
$/kWh
1994
1800
45
0,003
0,028
0,072
1993
1404
39
0,003
0,033
PFBC, CC
COSTI
NOTE
Convenzionale a carbone
RIFERIMENTO
LOCAZIONE
INPUT PRINCIPALE
OUT PUT PRINCIPALE
POTENZA INSTALLATA
DURATA DI UTILIZZAZIONE
RENDIMENTO
MW
h/a
%
EM database (1995)
generica
carbone
energia elettrica
300
5000
37
Min. fur Wirtschaft, 1990
Germania
carbone
energia elettrica
642
39,6
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
Data Bases
IKARUS - Germany: + LP optimization / sectoral simul.models
CO2DB - IIASA, Vienna: linked to simulation models
EM - World Bank: linked to simulation models
IPCC/TI - USA: mitigation technologies inventory
DECADES - IAEA, Vienna: elc tch + energy chains
GREENTIE - IEA, Paris: DB on technology providers
MARKAL country DBs, linked to optimisation models
other in UK, NL, USA, etc.
9
Struttura dei dati in IKARUS
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
Esempio: IKARUS, Germania
Processo (tecnologia)
Schema di impianto
Dati relativi alla tecnologia selezionata
1
0
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
Data structure in EM
Products (fuels)
EM, World Bank
Processes (technologies)
Emissioni
Composition (fuels)
Costs (technologies)
Costs (fuels)
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
2b - Flussi: statistiche e bilanci energetici
Quanto costa l’energia alla nazione? Quanto
inquina? (statistico, economista)
• Statistiche energetiche nazionali (enr_ita2.xls)
• Statistiche energetiche (ex: IEA, ENERDATA)
• Bilancio Energetico Nazionale (MAP/DGERM)
• Bilanci Energetici di sintesi (ex: IEA)
• Bilanci energetici di dettaglio (ex: IEA)
• Matrici Input / Output (generali, energetiche)
ITALY
Code
I
-
s érie
GENERAL
pib
in
at
at
c urrent
DELLE
15/mar/2001
money
pric es ,
pric es ,
of
IS TA T
nat ional
in
FO NTI
oil
of
oil
oil
Unit
of
1970
of
of
of
of
of
of
of
of
1971
67178
1972
221
54005
124800
MICA
MICA
s ec tMI
ors
CA
K t oe
K t oe
K t oe
K t oe
K t oe
K t oe
K t oe
K t oe
K t oe
K t oe
K t oe
K t oe
K t oe
K t oe
K t oe
93300
8903
21443
4948
4100
5315
0
14380
78
196
313
0
18603
2466
740
2802
97198
9238
21001
5485
3979
5397
0
15061
91
195
317
0
20860
2323
593
2851
1973
79810
548947
384
48611
328093
229
54381
132000
1974
96738
586660
410
59175
350568
245
54751
139800
1975
122198
616932
431
74461
363647
254
55111
139100
1976
138632
601477
420
87075
365486
255
55441
133000
1977
174869
640624
448
107799
384552
269
55718
142400
1978
214398
662420
463
131895
399949
280
55955
140600
1979
253536
686482
480
154336
412906
289
56155
144100
1980
309834
726409
508
189671
442414
309
56318
149200
1981
387669
756197
529
241358
467517
327
56416
147030
1982
464030
760366
531
289137
474627
332
56502
143590
1983
545124
761991
533
342500
480312
336
56639
139980
1984
633436
769370
538
396138
483621
338
56836
139530
725760
790036
552
452431
493167
345
57005
143490
132928
138784
139867
133700
142359
142169
143240
149335
145296
143810
141097
139435
142659
102884
108019
106306
101251
107817
105458
108165
111327
107794
105790
103042
102305
104922
9866
20871
6501
4104
5694
0
17291
109
143
323
0
22790
2758
521
3110
10589
21834
7073
4450
6641
0
18661
124
134
325
0
22949
3615
483
3388
11026
21941
7897
4776
6899
0
17375
174
107
334
0
21940
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379
3542
10817
17652
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253
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362
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21615
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303
3662
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9348
4487
7269
0
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298
47
438
0
21754
6717
296
3966
12281
17798
9509
4398
7450
0
20523
256
38
448
0
19092
7094
273
4188
12767
16242
9314
4520
7596
0
21721
250
42
455
0
20962
7911
240
4505
12855
16971
9325
4487
7361
0
23640
250
48
465
0
20679
7982
259
4805
13782
15994
9163
4676
8077
0
23633
257
2
460
0
19441
8558
292
5010
13701
14161
8724
5142
7798
0
23606
258
0
443
0
18268
8799
297
5205
13895
12715
7976
5411
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0
24430
259
0
455
0
17297
9057
307
5552
13833
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0
24496
257
0
462
0
17140
9643
275
5620
14615
10972
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0
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486
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273
5933
s ec t ors
s ec t ors CE S E N
res identCE
ial
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CE S E N
CE S E N
res ident ial
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of
of
CE S E N
agric ult ure
MICA
MICA
MICA
agric ult ure
MICA
agric ult ure
of
of
ot hers
MICA
CE S E N
CE S E N
CE S E N
ot hers
ot hers
of
ot hers
CE S E N
CE S E N
MICA
ENERGIA
373
44091
53832
120100
s ec
MI
t ors
CA
s ec t ors
ot her
of
of
res ident ial
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1535
1213
1086
1028
822
669
662
619
553
606
697
650
599
577
624
K t oe
13232
15167
16937
17272
16461
16221
16392
14174
15789
15476
14666
13760
13030
12915
12743
K t oe
K t oe
K t oe
K t oe
K t oe
K t oe
K t oe
K t oe
1829
612
1681
1535
1754
2
0
95
2182
474
1849
1213
1976
2
0
100
2467
416
2026
1086
2014
2
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100
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386
2206
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2
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0
223
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650
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0
254
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224
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577
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11
0
263
7582
219
3833
624
1939
12
0
265
agric ult ure
ot hers
of
non
for
non
energy
non
energy
18°c
degree
c oeff.
K t oe
K t oe
K t oe
K t oe
K t oe
K t oe
K t oe
energy
MICA
us esK t oe
us es
MICA
us es
MICA
E UR
day s ,
c oeff.
c onv
ers ion
bas e E
18°c
NE A
K t oe
K t oe
degree
degree
116
146
831
0
507
0
3717
139
119
902
0
8516
5677
1713
437
2155
0
3839
289
105
985
0
7711
6197
1735
367
1994
0
3624
585
97
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0
7220
6941
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362
2209
0
3292
882
75
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0
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6408
1801
399
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58
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0
5766
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369
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0
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1656
57
1240
0
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6115
1884
341
2100
0
2740
1785
53
1303
0
5093
5896
1665
312
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0
3013
2066
47
1399
0
5561
5308
1940
297
2142
0
2865
2089
51
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0
5093
5780
2162
299
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0
2587
2288
59
1551
0
4203
3844
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308
2273
0
2398
2372
56
1608
0
3927
5652
1732
230
2062
0
2174
2442
54
1716
0
4087
4362
1507
272
1977
0
2118
2600
51
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5443
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233
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2804
53
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0
3202
5626
1883
257
2164
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2066
2061
2078
2093
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2069
2081
2082
2072
2080
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10200
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E DELLE RIS O RS E MINERARIE
za
Boz
0
3617
7813
5943
1751
2120
2099
k c al/ k g
k c al/ k g
DEL COM M ERCIO E DELL'ARTIGIANATO
DI
72994
534071
367
k
MICA
MICA
MICA
MICA
ot her
s ec t ors
ot her
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agric ult ure
of
MICA
MICA
t rans port
MICA
t rans port
t rans port
ot her
res ident ial
of
of
E CUS 213
of 1985
ref
119799
erenc e 124132
c limat e
indus t ry
t rans port
ot her
of
of
agric ult ure
ot hers
for
energies
K t oe
MICA
MICA
MICA
indus t ry
indus t ry
t rans port
of
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of
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produc t s
for
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pric
M*10**3
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nat ional
305212
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at
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in
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hous eholds
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hous eholds
of
of
populat ion
day s ,
Dies el
Res idual
BILANCIO
ENERGETICO
NAZIONALE
1999
ultima modif ica:
nat ional
c ons t ant
c ons t ant
c ons umpt ion
c ons umpt ion
c ons umpt ion
primary
primary
final
elec t ric it y
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
B unk ers
Cons umpt ion
Cons umpt ion
Cons umpt ion
Degree
Normaliz ed
gz lun
folun
M INISTERO DELL'INDUSTRIA
GENERALE
S ourc e
DATA
GDP
GDP
P riv
at e
P riv
at e
P riv
at e
Res ident
Tot al
Tot al
Tot al
Tot al
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
Cons umpt ion
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Cons umpt ion
pet c fagr
gaz c fagr
c hac fagr
elec fagr
v
apc fagr
ot hc fagr
pet c fdv
r
gaz c fdv
r
c hac fdv
r
elec fdv
r
v
apc fdv
r
ot hc fdv
r
pet s o
pet c fnen
gaz c fnen
c hac fnen
dj
djref
DIREZIO NE
Tit le
GDP
pibx x
pibec u85
c pr
c prx x
c prec u85
pop
t oc c p
t oc c pc c
t oc c f
elc c f
pet c find
gaz c find
c hac find
elec find
v
apc find
ot hc find
pet c ft ra
gaz c ft ra
c hac ft ra
elec ft ra
v
apc ft ra
ot hc ft ra
pet c fret
gaz c fret
c hac fret
elec fret
v
apc fret
ot hc fret
pet c fres
gaz c fres
c hac fres
elec fres
v
apc fres
ot hc fres
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
DB statistiche energetiche
base content of most energy data bases:
•socio - economic - land use data, maps (?)
•energy balances, flows data, prices, indicators,
•balances, capacity and reserves, etc.
•energy related environment data, indicators,
by country (or region), year, fuel, sector, unit, etc
main providers (free or at some cost)
• International Energy Agency, Paris
• Energy Information Administration, Washington
• EUROSTAT, Luxemburg
• ENERDATA s.a., Grenoble, France
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
3 - Correlazioni nel sistema
Quale fenomeno spiega la situazione attuale, in termini di
flussi, tecnologie, etc.? (economista dell’energia)
• Analisi econometriche
– Macro
– Micro
• Analisi dei fattori
– Globale
– Settoriale
• Reference energy system:
– Bilanci dei flussi di energia e materiali
– Bilanci delle tecnologie
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
3a -Relazione econometrica base
• Ln(TPES(t)) =
–
–
–
–
•
•
•
•
A+
B * Ln(GDP(t)) C * ln (Pr(t)) +
D*t
TPES = Consumo naz. Di energia primaria eq.
GDP = prodotto interno lordo
Pr = prezzo medio dell’energia
T = anno; B, C = elasticità; D = miglioram. tecn
1
5
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
G=Pop*(Gdp/Pop)*(En/Gdp)*(Fos/En)*(CO2/Fos)
=P*W*E* F * C
Energy Service
G:
P:
W:
E:
F:
C:
Carbon Intensity
CO2 Emissions
Population
per capita Gross Domestic Product
energy intensity of the GDP
share of fossil fuels on Total Primary Energy Supply
carbon intensity of fossil fuel mix
3b -Analisi dei fattori: identità di Kaya
1
6
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
3b -Analisi dei fattori settoriale (IEA,99)
G = k(wk*Ak * i (Si * Ii *  jFij))
Energy Service
Carbon Intensity
G : CO2 Emissions
w : Weighting factor: 1990 emissions in sector k
A : Activity in Sector k
S : Structure in Sector k (sub-sector i share of sector activity)
I : Energy Intensity in sub-sector i
F : Carbon Content of fuel j used in sub-sector i
Represents Changes in: 1) supply efficiency,
2) supply fuel mix
3) end-use fuel switch
1
7
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
3b - Analisi dei fattori, esempio (IEA,99)
1975-1990
1990-1995
1995-2000
2000-2010 Baseline
2000-2010 Target
Average % change per yr.
3%
2%
1%
0%
-1%
-2%
21% Reduction 1990-2010
(= -5% from baseline 2010)
-3%
CO2
Energy
Services
Utility
End-use
Fuel Mix
Energy
Intensity
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
3c - Reference Energy System
Imports
Exports
Other regions
Industrial
N6B
CM1
SD6
ICC
CA0
SD7
SD0
ICM
ELC
NGH
CS1
E LC
CS2
CMA
IC1
ICN
THL
ELC
NGH
ICA
CCA
SD8
ICU
CM2
ICD
SD9
CBL
N6D
ICP
ICV
ICQ
ICW
ICG
SDE
CM4
N6C
ICK
SDG
CB1
TCD
N6A
CA0
CM3
CA0
ICE
CC0
ICF
CA0
ICO
E LC
CS2
CMB
N6A
IC1
CM3
SC6
IC
ICT
SC7
ICH
CM5
ICR
N6B
COR
Electricity
Cuivre
(Millions
de tonne/
Année)
ICS
N6C
N6D
COA
NGH
SC8
ICI
SC9
ICJ
SCE
FOK
SCG
NGH
ELC
COF
ICX
NGH
N6C
ICZ
Residential
O&Gas Proc. &
Refining
Commercial
Other Processing
NGL
NGU
Transport
NG4
NG2
NGS
DNQ
DNE
DNP
NGW
NGD
NG3
NAP
STK
ORL
GAS
DBN
S24
NG5
Alberta Oil & Gas
NGA
OHS
OBS
DBO
DHU
DBP
NGA
OBS
DHV
OHS
DHP
OBI
REF
STK
OHG
OBN
REF
NGA
DBU
ASP
HFO
ORL
ORO
JTF
GSL
OSN
OBM
NGA
OLG
OIL
DBS
OLS
DLP
NGA
STK
NGS
DNS
DNR
Domestic
Sources
NG2
NGE
Non-Energy
Processing (*n) EndUse-Tech
EU-Demands
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
4 – Modelli di previsione
Modelli qualitativi / quantitativi (story lines vs. scenarios)
Caratteristiche distintive dei modelli energetici quantitativi:
- contenuto (scope) - materia: settoriale o globale;
geografico: locale, nazionale, regionale, mondiale
- approccio teorico (tipo di variabili e di equazioni)
top-down (macro) vs. bottom-up (tecnologico)
- orizzonte temporale: breve, medio, lungo
2
0
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
Short term
Top-down,
econometric
Long term
Autoregressive
Sectoral
Macroeconomic
General
equilibrium
Sectoral/
technology
End use
models
Simulation
Optimization
Bottom-up,
engineering
4 - Alcune categorie di modelli
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
5 – MARKAL: Diagramma di funzionamento
Technological database
Economic Scenario
•Base Case Demands for
energy services
MARKAL
Environmental Scenario
•Cap(s)-&-Trade
•Demand Elasticities
•Taxes, Subsidies
•Oil Price
•Sectors’ Measures
Equilibrium
•Technology Investments and Market Shares
•Emission Trajectories
•Adjusted Demands for energy services
•Marginal Values of Energy Forms (Prices)
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
5 – MARKAL: Variabili principali
•
•
•
•
•
Mining/Import/Export (r, t, c, ts)
Investment (r, t, p)
Capacity (r, t, p)
Operation (r, t, p)
Demand Loss/Increase (r, t, dm, k)
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
5 – MARKAL: Equazioni principali, 1
• Demand (r, t, dm)
– Production from all “related” end-use technologies +
Elastic variables End-use demand
Price
5 Elastic Variables
P5
P0
D
D0
Demand
• Commodity balance (r, t, c) prices
– Production  Consumption
• Process activity (r, t, p)
– Operation  Capacity  Availability Factor
• Capacity transfer (r, t, p)
– Capacity = Investments + “Residual” capacity
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
5 – MARKAL: Equazioni principali, 2
• Electricity sector
– Time-sliced balance (r, t, ts)
• Production  Consumption
– Seasonal reservoir management
• Essentially lets you specify seasonal plus an annual availability
factor
– Peaking
• Total ELC capacity  (1+ERESERVE)  Capacity needed to
meet the energy requirement
– Base load
• Total night production of Base-Load-Techs 
load-fraction  total night demand
Base-
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
5 – MARKAL: Equazioni principali, 3
• User defined constraints
– Any of the variables can be used to define a
new constraint
• Salvage
– The investment cost of “unused” technology
stock is refunded
• Objective function
– NPV of (tech costs + mining/import costs export revenues + taxes - subsidies)
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
5 – MARKAL - MACRO
Energy Costs
MARKAL
Energy
MACRO
Labor
Capital
Y
Consumption
Investment
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
5 – Variabili MACRO
•
•
•
•
•
•
•
Utility
Consumption (t)
Investment (t)
Energy costs (t)
Production (t) [Excluding energy sector]
Capital stock (t)
End-use demand (t, dm)
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
5 – Equazioni MACRO
• Utility
–  Disc-fact Log(Consumption)
• Use
– Production = Consumption + Investment +
Energy Costs
• Production
– Production = f(Energy, Capital, Labor)
• Capital accumulation
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
6a – Scenari nazionali: energia
CONSUMI DI ENERGIA (Mtep di energia primaria eq.)
220
Business as Usual
210
200
CASO BASE (least
cost)
190
CO2 Emission cost of
10$/ton
180
CO2 EMISSION
COST OF 50$ / ton
170
CO2 EMISSION
COST OF 100$ / ton
160
150
1990
CO2 EMISSION
COST OF 200$ / ton
1995
2000
2005
2010
2015
2020
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
6a – Scenari nazionali: emissioni
550
Emissione di CO2 da fonti energetiche, MtCO2/a
(bunkers e voli int. esclusi, secondo Guidelines
FCCC)
BAU
500
base
10$
450
50$
100$
400
200$
350
300
1990
1995
2000
2005
2010
2015
2020
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
6b - Costi complessivi di mitigazione in Italia
(GDP 0.5-1.0% al 2010, tassa eq. 80-250 $/tCO2)
100
CO2 reduction marginal cost curve (Markal Italy, 1998)
bau
80
200$/tCO2
14 years reduction costs MMLit
60
40
100$/tCO2
10$/tCO2
50$/tCO2
20
CO2 emission reductions in 2010
0
-20 0 base
20
-40
-100
60
50$/tCO2
con P&M
-60
-80
40
10$/tCO2
con P&M
80
100
200$/tCO2
con P&M
100$/tCO2
con P&M
120
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
6b -Opzioni di mitigazione ottimali: sintesi
Sector:
Renewable sources
Energy transformation
Industry
Residential and commercial
Mobility and transport
Agriculture and forestry
Wastes management
TOTAL
CO2
Mt/a
Inv.
M.Eu
Subs.
M.Eu
11.0
14.3
28.2
26.0
26.0
13.2
21.1
139.8
11400
8200
6750
5700
30300
10050
130
72530
2900
1300
800
-500
2500
7050
100
14150
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
6c - Politiche e misure di mitigazione: naz.
Economic Instruments: Liberalised Internal Market in
electricity and gas, Carbon tax, Subsidies (-, +),
Legal instruments: Codes to improve the thermal insulation
of buildings, Minimum Efficiency standards for end use
devices including cars, IPPC, traffic restrictions,
Voluntary agreements: RUE in industry/municipalities,
Energy audits in industry, services, buildings, Phase out of
the less efficient end use devices, ..
Diffusion of information: Monitoring mechanism, Energy
Labels of end use devices,
Direct investments: Energy RD&D, procurement,…
Other
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
6c - Potenziale dei meccanismi flessibili
Evaluation tool: Markal, an energy technology based
shadow price generator
The model of the Italian energy system (15000 eq.)
is run first with the Indian model (+5000 equations),
then with the model of USA + Canada (+60 Keq)
In the base scenarios, the total systems costs are minimised.
Other scenarios: with/without the Kyoto target to 2030,
Italy can/cannot purchase emission permits from India,
excluding / including purchases from USA, Canada.
Project based analysis (Clean Development Mechanism)
calculating the marginal system cost (strategic elements to
guess which might be the price of Emission Permits)
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
6c - FlexMex:punto di vista del venditore
CO2 emissions in India in 1995: 760 MtCO2/y, and a
strong increase is expected: +100% in 2015, +200% in 2030
If the trade of emission rights is permitted, these emissions
reduce by 10% in 2010 and by 20-25% in 2020-2030
at a marginal price of 25-35 US$’96/tCO2, by investing in
Gas CC power plants instead of Coal PP
(the concepts of baseline and additionality)
The extra energy system costs are about 1.7% (investments),
the economic surplus of selling on the emission trade market
these CO2 reduction units is double (3.6% of the total s.cost)
CDM or Trade of Emission Permits?
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
6c - FlexMex: punto di vista del compratore
Which part of the national commitments is worth buying?
67% at 10-12 US$’96/tCO2 (India->Italy exchange)
52% at 25-35 US$’96/tCO2 (India->USA-Canada-Italy)
33% at 40-80 US$’96/tCO2 (Eu proposed ceiling)
0% at about 200 US$’96/tCO2
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
6 - Studi recenti
• Impact of different schemes for international flexible mechanism
for mitigation (Can-US-India-It, CH-Columbia, NL-CH-SW,
Nordic Eu countries)
• Environmental effects of reducing/removing energy subsidies or
of adding a Carbon Tax (Italy, Australia)
• National MARKAL models contribute to identify climate
change mitigation options and the evaluation of climate change
policies (Can, National Communic. to FCCC of Aus, Be, Cz, It,
Latvia, NL, Sw, Us)
• Effect of including in the energy system materials, full fuel cycle
analysis and endogenous technology learning for mitigation
strategies
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
6 - Modelli globali multiregionali
• US MARKAL+MERGE for other regions (DWI-Stanford)
• The Global Markal Macro Trade model with Endogenous
Technology Learning (PSI-IIASA)
• The SAGE Project at the US Energy Information Administration
(System to Analyse Global Energy markets) with Time Stepped
Technology Learning
• The IEA Energy Technologies Perspectives Project adds
technological insight to 2002 World Energy Outlook with a
bottom-up multiregional global model
• Multi-regional Global TIMES (NRCanada, GERAD)
• Long time horizon multiregional global model for SERF3 (Socio
Economic Research on Fusion)
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
6 - Energia e ambiente su scala locale
Under ETSAP and ALEP (Advanced Local Energy Planning, IEA
IA on Energy Conservation in Buildings and Community
Systems)
District energy grids expansion, waste management,
local
pollution vs global mitigation (local Agenda 21), energy
conservation policies in buildings, public vs private
transportation, local tax/subsidies
–
–
–
–
–
–
Germany (Mannheim,
Italy (Bologna, Torino, Aosta, Basilicata,
The Netherlands (Delft,
Sweden (Jancheping, Norcheping,
Switzerland (Geneve,
China (Hong Kong, etc.
7 - Il progetto ETSAP/IEA
• Present participants:
Australia, Austria, Belgium, Canada, EU, Finland, Germany,
Greece, Irland, Italy, Japan, Korea, The Netherlands, Norway,
Spain, Sweden, Switzerland, Turkey, United Kingdom, United
States
• Main goals:
- to develop modelling tools that represent different systems of energy
flows and technologies
- to improve the knowledge of global, regional, national and local energy
and environment systems
- to contribute to the energy environment debate with quantitative and
methodologically sound analyses
7 - Generatore di modelli MARKAL (1979)
(sometimes called marginal price generating model)
• fixed multi-time periods Pareto Optimal models minimising the
discounted total system cost
• energy flows and technologies (energy system only)
• single region
• with price sensitive supply curves, non price sensitive demand
curves expressed in final/useful energy terms
• time/Reference Energy System (RES) perfect foresight
• calculated trade-off curves among cost, energy security and
emissions
• 2 versions of the code: FORTRAN and OMNI
7 - Versioni del MARKAL (1980-2002)
• MARKAL Materials, can represent tens of pollutants and in
principle the whole economy
• MACRO, NLP general equilibrium version, with a single
production function
• MICRO, NLP partial equilibrium version, with demand elastic
to prices (own/cross)
• Stochastic to calculate optimal hedging strategies
• Elastic Demand, linearised partial equilibrium version
• Multi-regional, with endogenous trade
• Endogenous Technology Learning (MIP)
7 - Evoluzione del Software
• automatic creation of a reference energy system from the IEA
energy balances (TEMPLATE spreadsheets)
• projections of the demand for energy services from common
drivers and own price elasticities
• common technologies repository, with efficiencies, emissions,
materials use, costs and learning of existing and new
technologies
• multiple model shells (MUSS, Answer, VEDA FE)
• multiple model generator programs (GAMS)
• multiple LP, NLP, MIP solvers
• multiple / flexible reporting tools (VEDA BE, Answer)
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
7 - MARKAL/TIMES oggi
• variable time periods length (TIMES) competitive partial
equilibrium models maximising the discounted sum of the
consumer and producer surplus
• models flow and technologies of energy systems + materials +
wastes + pollutants + other sectors
• multi-grids, multi-regional with endogenous trade
• price sensitive supply and demand curves (free units)
• clairvoyant, or stochastic, or time-stepped
• In each market technologies with the best marginal benefit / cost
ratio are chosen, including externalities
• coded in GAMS
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
7 - Equilibrio statico
• hundreds of energy good and commodity markets are
represented (from coal to passenger*km)
• the stepwise supply and demand curves of each market are
calculated including independent investment, fixed, variable,
fuel, environment, material costs (based upon separate variables)
• the equilibrium point in each market of the RES calculates
Quantities, Prices and indicates both supply and demand
marginal technologies
• the distance from competitiveness of each technology and the
technology gaps for reaching the desired equilibrium points are
calculated by the model
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
7 - Equilibrio dinamico
The reaction of the energy system to exogenous dynamic changes
is represented in the model through
• starting point is the present stock of technologies and the
possible future availability of well defined technologies (not
upon past behaviour)
• substitution among competing and time improving processes
commodities, similar to the mechanism of optimal Von
Neumann multiple producers/multiple commodities I/O models
(not through price dependent technical coefficients of a Leontief
I/O square matrix)
• variable depreciation plans for investments
7 - Visita i siti web del gruppo …
• www.iea.org/
• www.ecn.nl/unit_bs/etsap/main.html
• www.crt.umontreal.ca/~amit/THEMODEL/
• www.ier.uni-stuttgart.de/
• www.kier.re.kr/
• www. abare.gov.au/
• www.tokai.jaeri.go.jp/
• etc.
.. o contatta i ricercatori del gruppo
•
•
•
•
•
•
•
•
•
•
•
•
Fridtjof Unander <[email protected]>, IEA desk officer
Prof. <[email protected]>
<[email protected]>
Prof. Enzo Cuomo <[email protected]>
<[email protected]>
Gary Goldstein <[email protected]>, SW coordinator
Prof Alain B. Haurie <[email protected]>
Amit Kanudia <[email protected]>
Barry Kapilow-Cohen <[email protected]'
Anna Krook <[email protected]>
Socrates Kypreos <[email protected]>
<[email protected]>
.. altri ricercatori del gruppo
•
•
•
•
•
•
•
•
•
•
•
•
Prof. Evasio Lavagno <[email protected]>
John C. Lee <[email protected]>
Prof. Richard <[email protected]>
Prof. Alan S. Manne <[email protected]>
Ken Noble <[email protected]>
Osamu Sato <[email protected]>
Chris Schlenzig <[email protected]>
Heesung Shin <[email protected]>
Prof. Shukla <[email protected]>
Peter Taylor <[email protected]>
GianCarlo Tosato <[email protected]>, project head
Phillip Tseng <[email protected]>, chairman
ENERGY TECHNOLOGIES SYSTEMS ANALYSIS PROJECT
TITOLO 1
• TESTO 1