May 11, The role of electric mobility in future Energy Systems Dr. ir. Zofia Lukszo With collaboration with dr. Remco Verzijlbergh Section Energy and Industry Technology, Policy and

Content Why electric mobility? Responsive demand Are the goals of many actors involved the same? What about the environment? Why EVs can be compared to cold storage warehouses? What can we learn from looking at different price scenario’s? Future work May 11, 20152

Future energy systems Old schedule generation to meet demand New schedule demand to meet generation e.g. electric mobility

Electric mobility How can electric mobility contribute to a more sustainable transportation & electrical power system and on the same time align the interests of its relevant actors? See: Remco Verzijlbergh, The Power of Electric Vehicles, PhD Thesis TU Delft, 2013,

Why electric mobility - CO 2 emission air quality, noise polluttion

Energy usage households +/- 10 kWh

Power sector complex socio-technical system

Standard Household Profile

Estimation of the expected energy usage of EVs Data from Mobility Research Netherlands Ministry of Transport, Public Works and Water Management, “Mobiliteitsonderzoek Nederland (in Dutch)” Available: Average: ~34 km ~ 90% < 100km

Charging scenario's and network load Based on real life data

Network load:100 houses and 50 EVs May 11, Price control Load Control Imbalance Control Separate EV demand profiles

Electric mobility in a city – city of Utrecht Load flow analysis shows: 10% electric mobility  24% overloaded Reference case (merely organic growth)  19% overloaded See E.J. Kleiwegt, Electric Mobility: on the Road to Energy Transition: A technical and actor assessment of social costs of electric mobility, Master Thesis, TU Delft,

Example – city of Utrecht Use calculations for critical component map Green/Yellow/ Red locations for installing charging stations

Merit order vs emission – two cases May 11, D A

CO 2 emissions of EV charging as a function of CO 2 price May 11, ADAD

Dispatch profiles for different vehicles scenarios May 11,

Charging strategy based on predicted price May 11,

Negative price? Conventional, wind and solar power and spot prices for the German system on June 16th 2013.

Responsive demand – cold storage Old schedule generation to meet demand New schedule demand to meet generation e.g. with a cold storage warehouse

Matching renewable energy and demand response through price System model: Cold store has PV generation on site PV production known in advance Pays price C in (t) for energy, receives C out (t) Temperature upper bound T max Goal: Investigate relations between demand response strategy of a cold store and electricity prices & Evaluate different pricing regimes on optimal energy use

Physical model of cold store Heat balance Incoming heat Outgoing heat Discretized in time Resulting equation for T dynamics

System model Cold store has PV generation on site PV production known in advance Pays price C in (t) for energy, receives C out (t) Temperature upper bound T max

Optimization formulation constraints Objective function

Compare cold store with EV optimization problem Optimization problem State dynamics

Price scenarios A: flat tariff B: flat double tariff C: day-night tariff D: APX based real time tariff E: APX based real time tariff, high solar penetration

Optimal cooling trajectory depends strongly on tariff structure. Local use of PV energy depends on tariffs Most 'value' of control in case with high solar penetration. The effective use of demand response requires the right tariff structure Comparison

New plans

NWO URSES - CaPP Project Design, Management and Control Systems for multi- modal, detachable decentral sustainable energy systems Car as Power Plant as a multi-modal system (power, transport, gas/hydrogen, heat) ICT and business models for CaPP Detachable decentral = fuel cell cars

NWO URSES – CaPP Project design, assess and analyse the fuel cell car as power plant (CaPP) in integrated transport and energy systems investigate and design robust control systems of CaPP- based smart energy systems explore effective incentive and organizational structures for the emergence of CaPP integrated energy and transport systems

May 11,

PhD wanted ! CaPP

Most urgent question How to reduce uncertainty for actors in the energy chain by developing the science and tools that are needed for smart energy systems? May 11,

May 11,