EWEC 2009 March 19 th

EWEC 2009 March 19th

Optimal configuration of future energy systems including road transport and vehicle-to-grid capabilities

Nina Juul, Risoe DTU – Technical University of Denmark

njua@risoe.dtu.dk

Peter Meibom, Risoe DTU – Technical University of Denmark

peme@risoe.dtu.dk

Overview

• Purpose

• Balmorel and Transport – the model

• Cases

• Results

Purpose

Adding transport to Balmorel enables analysis of:

• consequences of possibility of using electric power in transport sector

• consequences of adding vehicle-to-grid technologies

• competition between different vehicle technologies

Sketch of the Balmorel model including transport

Present power and transport system(e.g. capacities, storages, transmission lines, plants, consumption)

Scenario data(e.g. prices, demands, technology data)

Input data

Model run •maximizing social surplus•Restrictions for transport and power system

Model output:Configuration and operation of power and transport system

Power flowsCosts

Configuration and operation of the transport system (and energy system)

The energy system (Balmorel)

Input data(e.g. demand, prices, technical data, driving pattern)

Modelling assumptions

The transport model

Transport add-on in Balmorel

Power flow

Propulsion system configuration of electric drive vehicles

Power Bus

Grid connection

Storage

Generator

Engine

Electric motor

Transmission Driving Wheels

Accessory loads

Only applicable for the plug-in serial propulsion systems

Power flow

Power flow model of electric drive vehicles

Unload

StorageFrom grid

To grid

Output from engine to generator

Power Bus

a)

Applicable for PHEVs propulsion systems

Replaced with output from fuel cell for FCEVs

a) vehicles plugged in b) vehicles not plugged in

Unload

StorageBraking energy

Consumption propulsion

Consumption accessory loads

Output from engine to generator

Power Bus

b)

Model formulation

• Objective function: investments in vehicles

• Vehicle restrictions: balancing of on board storage (plugged in)

balancing of the power bus (plugged in)

supply and demand must meet

minimum and maximum capacities

• Electricity balance equation: power to grid - power from grid

Assumptions

• Communication system in place

• Vehicles are aggregated in vehicle groups

• Loading and unloading depending on vehicles plugged in (cannot exceed max storage level)

• Average driving patterns (forcing specific patterns for use of diesel)

• All vehicles leave grid with predefined storage level

Case description

Model runs:

• Denmark without transmission possibilities to neighbouring countries

• 26 selected weeks with hourly resolution (26 X 168 time steps)

• Year 2030

• Oil prices $100/barrel

• CO2 prices 40€/ton

• Road transport

• Including ICE, BEV, PHEV for persons transport

Case description

Type of vehicle

Inv. costs (€)(yearly cost)

O & M costs (€/year)

Electric storage cap. (kWh)

ICE 11,766 (1,605) 1,168 0

BEV 19,078 (2,603) 1,101 50

PHEV 15,496 (2,114) 1,168 10

Case description

Type of vehicle

yearly fixed costs (€/year)

Fuel and CO2 costs (€/year)

Difference in costs relative to the ICE (€/year)

ICE 2,773 796 -

BEV 3,704 153 288

PHEV 3,282 294 6

Scenarios

• No usage of electricity in road transport

• Integrated power and transport system with V2G facilities

• Integrated power and transport system without V2G facilities

Results

Investments in vehicles 2030

Results

Electricity generation 2030

Results

Week 9: Power exchange between grid and vehiclesvs. electricity prices (western Denmark)

€/MWh

hour

MW

Results

Net power from grid – average on hours (daily cycle)

MW

Results

Total power exchange between grid and vehicles

Region From grid (MWh) To grid (MWh) Net from grid (MWh)

Eastern Denmark

2,908,172 123,016 2,785,156

Western Denmark

3,933,367 243,592 3,689,775

Total 6,841,540 366,608 6,474,931

Conclusions

• Using electricity for transport incorporates more wind – more than what is used by the transport sector with included V2G

• Adding V2G facilities incorporates more wind even though the usage is small

Future works

• Dividing driving patterns into different profiles

• Analysis of larger energy systems e.g. Northern Europe

• Handling storage on a smaller level than vehicle group

• Storage level when leaving – variable instead of parameter

Thank you