2 nd E-Mobility Power System Integration Symposium 15 October 218; Stockholm, Sweden Increased Utilization of residential PV Storage Systems through locally charged Battery Electric Vehicles Dennis Huschenhöfer, Johannes Mieser, Jann Binder Zentrum für Sonnenenergie- und Wasserstoff-Forschung Baden-Württemberg (ZSW) - -
Motivation of the study First mover charge their Battery Electric Vehicles (BEVs) at home weak charging infrastructure wish to use of own-generated renewable power reduced cost of charging How much increase of the utilization of a residential PV storage system is caused by home charging? How much own consumption can be achieved? - 1 -
Study design Study of charging a BEV with local produced solar power Parameters 2 kinds of load profiles of the household 2 PV system sizes Energy content of the battery from to 14 kwh Daily driving distance according to 2 scenarios 4 charging patterns Results: Equivalent full battery cycles own-consumed energy MATLAB simulation for one year with 15 min steps - 2 -
Household load profiles Two extreme household load profiles, scaled to a energy demand of 4, kwh/a - 3 -
BEV Probabilities of arrival times and driving distances 5% 4% 5% 4% 1st BEV 2nd BEV Probability 3% 2% 3% 2% 1% 1% % 2 4 6 8 1 12 14 16 18 2 22 24 Arrival Time (h) % 1 1 2 4 65 1 2 3 Driving Distance (km) Daily vehicle use and arrival time is picked using the Monte Carlo Method - 4 -
Simplified charging process 11 Charging Power (kw) charging power 11 kw charging power 3.7 kw Arrival Time Charging duration depending on driving distance - 5 -
Modelling of a BEV one-year load profile Daily driving distance Amount of energy to be recharged Daily arrival time at home Starting point for charging Charging power (CP) 3.7 kw or 11kW One-year load profile for a BEV - 6 -
Solar Power Production and Use South facing PV system located in Southern Germany with 1, kwh/kw p (data from 211) PV System sizes of 4 and 1 kwp Batteries with to 14 kwh - 7 -
Simulated Scenarios HH w/o BEV BEV (Monte Carlo) Commuter 6 pm WE-charging Commuter Two BEVs* Electrical demand 4, kwh/a 4, kwh/a + 2,7 kwh/a 4, kwh/a + 3,45 kwh/a 4, kwh/a + 3,15 kwh/a 4, kwh/a + 4,15 kwh/a BEVs - 1 1 1 2 Daily Driving Distance Arrival Time - Charging Pattern - - km - 3 km ( 13,5 km/a) 12 a.m. - 12 p.m. daily after arrival workday: 5 km weekend: km - 3 km ( 17,25 km/a) workday: 6 p.m. weekend: 12 a.m. - 12 p.m. workday: 5 km weekend: 25km + 25km ( 15,75 km/a) weekend: 9 a.m. and 7 p.m. workday: km - 4 km** ( 2,75 km/a) workday: 11 a.m. 3 p.m.** weekend: - ** daily after arrival on the weekend daily after arrival * 1 st BEV like Commuter 6 pm ** Applies to the 2 nd BEV - 8 -
Simulation of a household evening centered, 1 kwp PV-System & 3.7 kw CP number of yearly full battery cycles 4 3 2 1 4 8 12 16 Own-ccnsumption (kwh/a) 5 4 3 2 1 w/o BEV BEV (Monte Carlo) Commuter (6 pm) Commuter (WE-charging) two BEVs 4 8 12 16 The utilization of large batteries is improved generally by the demand of the BEV but sun-shine hour charging decrease utilization - 9 -
number of yearly full battery cycles Comparison of results related to household profiles 4 3 2 1 evening centered w/o BEV BEV (Monte Carlo) Commuter (6 pm) Commuter (WE-charging) two BEVs 4 8 12 16 1 kwp PV-System & 3.7 kw CP 4 3 2 1 noon centered 4 8 12 16 Higher utilization of the battery system at the evening centered profile Increase already for small batteries at the noon centered profile - 1 -
number of yearly full battery cycles Own-ccnsumption (kwh/a) - 11 - Comparison of results related to household profiles 4 3 2 1 5 4 3 2 1 evening centered 4 8 12 16 4 8 12 16 1 kwp PV-System & 3.7 kw CP noon centered Also increase of utilization at noon centered profiles together with increasing own-consumption 4 3 2 1 5 4 3 2 1 4 8 12 16 w/o BEV BEV (Monte Carlo) Commuter (6 pm) Commuter (WE-charging) two BEVs 4 8 12 16
number of yearly full battery cycles Own-ccnsumption (kwh/a) - 12-4 3 2 1 5 4 3 2 1 Comparison of results related to charging power evening centered, 1 kw p PV-System CP = 3.7 kw 4 8 12 16 4 8 12 16 4 3 2 1 5 4 3 2 1 CP = 11 kw 4 8 12 16 w/o BEV BEV (Monte Carlo) Commuter (6 pm) Commuter (WE-charging) two BEVs 4 8 12 16 Only WE-charging with higher CP improves the utilization of all battery sizes but it has a bad effect on the own-consumption
number of yearly full battery cycles Own-consumption (kwh/a) - 13-3 2 1 Comparison of results related to charging power 3 2 1 CP = 3.7 kw 4 8 12 16 4 8 12 16 evening centered, 4 kw p PV-System 3 2 1 3 2 1 No suitable power generation to supply the demand of the BEV Utilization increase only a little bit at large batteries CP = 11 kw 4 8 12 16 w/o BEV BEV (Monte Carlo) Commuter (6 pm) Commuter (WE-charging) two BEVs 4 8 12 16
Summary Large PV systems are key to increasing own-consumption and the utilization of batteries: goal: yearly PV generation > yearly consumption 5% of own-consumption can be achieved with such PV system (1 kwp) sun-shine hour charging leads to almost 5% own-consumption even without battery For evening charging to reach 5% of own-consumption batteries of > 1 kwh are needed Higher charging power reduces own-consumption for all battery sizes less for large batteries The additional demand for charging BEV increases the utilization of large batteries in particular for evening charging - 14 -
// Energy with a future // Energy with a future // Center for Solar Energy and Hydrogen Research Baden-Württemberg // Zentrum für Sonnenenergie- (ZSW) und Wasserstoff- Forschung Baden-Württemberg (ZSW) // Dennis Huschenhöfer M.Sc. dennis.huschenhoefer@zsw-bw.de Thank you for your attention! Stuttgart: Photovoltaics, Energy Policy and Energy Carriers, Central Division Finance, Human Resources & Legal - 15 - Widderstall: Solar Test Facility Ulm: Electrochemical Energy Technologies, Main Building & elab