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!