Post on 03-Nov-2020
Development of methods and tools responding to the needs of energy transition:
PSI perspective
S. Hirschberg, P. Burgherr, E. Panos 14.9.2017
Renewable energy changes the electricity system
Source: http://ilsr.org/challenge-reconciling-centralized-v-decentralized-electricity-system/
Main challenges in electricity modelling but very important to model the full energy system since (1)
electricity is fundamental for the overall efficiency improvement; (2) necessary for optimal (with view to
efficiency, cost, climate protection goals, etc.) allocation of electricity to specific demand sectors:
Distinguishing between centralized and decentralized generation
Representing electricity grid from high to low voltage
Identifying storage options and new business models, e.g. prosumers
Capturing the intra-annual variability of renewable generation and demand
Assessing interactions between demand and supply
SCCER-SoE Annual Conference 2016 3
Methods, Models and Databases
Ecoinvent Database
Impact Pathway Approach
Integration:Multi-Criteria Decision Analysis
ENSAD Database
Risk Assessment
> 12’000 processes > 32’000 accidents
Life Cycle Assessment
Oil
(conventional,
unconventional)
Refinary
Natural Gas
(conventional,
unconventional)
Biomass
(1st & 2nd
generation, waste)
Renewables
(Hydro, Wind,
Solar, Geo)
Uranium
Coal
(Lignite,
Anthracens)Biofuels
Production
Synfuel
Productions
T&D
Power Plants
Heat plants
Hydrogen
productionT&D
T&D
T&D
Residential/Commercial
Thermal
Residential/Commercial
Appliances
Industry Thermal
Industry Specific
Personal Car Transport
Other Surface
Transport
Aviation
Non-commercial
Biomass
T&D
T&D
Non-Energy Use /
Feedstocks
T&D
T&D
Swiss TIMES energy systems model Bilevel Electricity Market Model
Technology Data
Technology Database
27.09.2017 SCCER-SoE Annual Conference 2016 4
New Technologies
Sustainability Criteria
Sou
rce:
Hirs
chbe
rg e
t al.,
200
7&20
08
Criterion
RESOURCES
Energy Resources
Mineral Resources (Ores)
CLIMATE CHANGE
IMPACT ON ECOSYSTEMS
Impacts from Normal Operation
Impacts from Severe Accidents
WASTES
Special Chemical Wastes stored in Underground Depositories
EN
VIR
ON
ME
NT
AL
DIM
EN
SIO
N
Medium and High Level Radioactive Wastes to be stored in Geological Repositories
IMPACTS ON CUSTOMERS
Price of Electricity
IMPACTS ON OVERALL ECONOMY
Employment
Autonomy of Electricity Generation
IMPACTS ON UTILITY
Financial Risks
EC
ON
OM
IC D
IME
NS
ION
Operation
SECURITY/RELIABILITY OF ENERGY PROVISION
Political Threats to Continuity of Energy Service
Flexibility and Adaptation
POLITICAL STABILITY AND LEGITIMACY
Potential of Conflicts induced by Energy Systems.
Necessity of Participative Decision-making Processes
SOCIAL AND INDIVIDUAL RISKS
Expert-based Risk Estimates for Normal Operation
Expert-based Risk Estimates for Accidents
Perceived Risks
Terrorist Threat
QUALITY OF RESIDENTIAL ENVIRONMENT
Effects on the Quality of Landscape
SO
CIA
L D
IME
NS
ION
Noise Exposure
Society
Environment
Economy
North
Today‘s
generation
South/East
Tomorrow‘s
generation
Society
Environment
Economy
North
Today‘s
generation
South/East
Tomorrow‘s
generation
• Energy systems models are the main tool for assessing long-term transformation strategies
• The STEM model represents the Swiss energy system from resource extraction to end-uses
• It is a bottom-up cost optimization model with long time horizon (2015 – 2100)
• It has high hourly resolution and high technological detail (> 350 processes/technologies)
• Significant development has been done in STEM to respond to the electricity sector’s challenges
The Swiss TIMES energy systems model (STEM)
Swiss TIMES Energy system Model (STEM)
Fuel supply
module
Fuel
distribution
module
Demand modulesElectricity supply
module
Resource module
Electricity import
Uranium
Natural gas
Hydrogen
Electricity export
Electricity
Gasoline
Diesel
Renewable· Solar
· Wind
· Biomass
· Waste
Electricity
storage
Hydro resource· Run-of rivers
· Reservoirs
CO2
Demand
technologies
Residential- Boiler
- Heat pump
- Air conditioner
- Appliances
Services
Industires
Hydro plants
Nuclear plants
Natural gas
GTCC
Solar PV
Wind
Geothermal
Other
Taxes &
Subsidies
Fuel cell
Energy
service
demands
Person
transportat
ion
Lighting
Motors
Space
heating
Hot water
Oil
Transport
Car fleetICE
Hybrid vehicles
PHEV
BEV
Fuel cell
Bus
Rail
Ma
cro
eco
no
mic
drive
rs (
e.g
., p
op
ula
tion
, G
DP
, flo
or
are
a, vk
m)
Inte
rna
tion
al e
ne
rgy
price
s (o
il, n
atu
ral g
as,
ele
ctrici
ty, ...)
Te
chn
olo
gy
cha
ract
eriza
tion
(E
ffic
ien
cy, lif
etim
e, co
sts,…
)
Re
sou
rce
po
ten
tial (
win
d, so
lar,
bio
ma
ss, …
.)
Biofuels
Biogas
vkm-Vehicle kilometre
tkm-tonne kilometre
LGV-Light goods vehicles
HGV-Heavy good vehicles
SMR-steam methane reformer
GTCC-gas turbine combined cycle plant
Oil refinery
Process
heat
FreightsTrucks
HGV
Rail
Natural gas
Heating oil
• Each grid level is differentiated in terms of transmission cost and losses
• Different types of power plants and storage options can be connected to each level
• A linearized approximation of the power plant unit commitment problem (dispatch) is formulated
• This structure allows for capturing the effect of incentives for decentralized generation and the benefits of own consumption and/or selling excess supply to upper grid levels (prosumers)
Centralized vs decentralized supply & grid levels
Very High Voltage Grid Level 1
NuclearHydro DamsImports Exports
Distributed Power Generation
Run-of-river hydroGas Turbines CCGas Turbines OCGeothermal
High Voltage Grid Level 3
Large Scale Power Generation
Medium Voltage Grid Level 5
Wind FarmsSolar ParksOil ICEWaste Incineration
Large scale CHP district heating
Wastes, BiomassOilGasBiogasH2
Low Voltage Grid Level 7
Large Industries & Commercial
CHP oilCHP biomassCHP gasCHP wastesCHP H2Solar PVWind turbines
Commercial/Residential Generation
CHP gasCHP biomassCHP H2Solar PVWind turbines
Lead-acid batteriesNaS batteriesVRF batteries
PEM electrolysis
Pump hydro
CAES
Lead-acid batteriesNaS batteriesVRF batteries
Li-Ion batteriesNiMH batteries
PEM electrolysis
Lead-acid batteriesLi-Ion batteriesNiMH batteries
6.19.4
0
10
20
30
40
50
60
70
80
90
No gridlevels
Gridlevels
TWh
Batteries
Wind
Solar
Wood
Waste
Gas CHP
Gas Large Scale
Hydro
ELECTRICITY GENERATION MIX IN 2050
REFERENCE SCENARIO
REPRESENTATION OF CENTRALIZED/DECENTRALIZED GENERATION
AND DIFFERENT GRID LEVELS IN THE STEM MODEL
+50% increase in
Solar PV when the
prosumer concept
is represented
Grid levels 2, 4 & 6 are transformers Source: PSI/Kannan & Panos, 2017
0
500
1000
1500
2000
Climate policy costdifference
Un
dis
cou
nte
d
MC
HF/
yr.
-40
-20
0
20
40
60
80
100
1 4001 8001
Rp
./kW
h
Hours
No grid
Case 1
Case 2
Case 3
• The detailed transmission grid is mapped to an aggregated grid with 15 nodes and 319 lines
• The mapping is based on a fix disaggregation of the reduced network injections to detailed network injections, by taking into account the grid transmission constraints
• This structure allows for evaluating the impact of grid congestion on electricity supply and demand
Representation of transmission grid
7 regions + 4 nodes for At/DE/IT/FR +
4 nodes for the existing nuclear plants
REPRESENTATION OF AGGREGATED
ELECTRICITY TRANSMISSION GRID
IMPACT OF GRID CONGESTION IN MARGINAL
COSTS OF ELECTRICITY, 2050 (Reference)
No grid means no representation of grid constraints
The different cases correspond to different locations
of large gas power plants; grid expansion is limited
to 2025 plans
Marginal cost
increases due to
congestion
Congestion
occurs for about
2000 hours
IMPACT OF GRID EXPANSION IN
CLIMATE CHANGE COSTS, 2020-50
Transport is excluded in cost calculations
Climate policy
cost
+1.5 BCHF/yr
if grid is not
expanded
456789
10111213
No gridexpansion
Gridexpansion
Climate policy costs
un
dis
cou
nte
d B
CH
F/yr
.
• The variability of RES is based on the variance of mean RES production in each hour and for each typical day represented in the model over a 20-year bootstrapped sample
• This allows to assess the storage requirements to balance the RES production
• High shares of VRES require electricity storage peak capacity of ca. 30 – 50% of the installed capacity of wind and solar PV (together)
• About 13% of the excess summer VRES production is seasonally stored in P2G
Capturing the variability of renewables
VARIABILITY OF SOLAR PV GENERATION IN
A SUMMER TYPICAL DAY IN THE STEM MODEL
ELECTRICITY FROM WIND AND SOLAR PV VS INSTALLED PEAK
STORAGE CAPACITY IN DIFFERENT SCENARIOS AND YEARS
Each data point corresponds to a different long term scenario and year
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
5.5
6.0
8 10 12 14 16 18 20 22 24
GW
of
sto
rage
GW of wind and solar PV
Batteries
Pump hydro
P2G
Features of PSI’s analytical framework for comprehensive energy systems modeling• Strong technological basis
• Scope covers environmental, economic and social dimensions
• Variety of methods, models and databases
• Inter-disciplinary technology assessment coupled with system models
• Integrative approaches combining knowledge with stakeholder preferences
• Systematic approach to modeling and assessing prospective tchnologicaladvancements
• Endogenous capacity expansion
• Systematic extension of system models within a modular framework
• Representation of whole energy system with detailed modeling of demand sectors (e.g. mobility)
• Coupling of bottom-up technology rich system models with grid
• Geographic coverage (CH, Europe, China and other regions, global)
• Temporal resolution and striving for increased spatial resolution
• Ongoing developments towards integrating behavior in system models
• Continuity and expandability
9/27/2017 SCCER-SoE Annual Conference 2016 14
Acknowledgements:
Kannan Ramachandran
Tom Kober
Thank you for your attention!