Integrating E-mobility(EVs) E with Smart Grid Prof. Jia Hongjie hjjia@tju.edu.cn Key Laboratory of Smart Grid of Ministry of Education, School of Electrical Engineering & Automation Tianjin University, China, 372
Outline Research Backgrounds Interaction between EV and Grid What we have done Future Work
Research Background Serious Haze in Beijing 22.2% caused by automobiles 数据来源 : 人民网 十问雾霾 系列篇之五 http://auto.people.com.cn/n/213/21/c98363-243482.html 3
Research Background EV Development in China 21 First 863 Program of EV 28 EVs for Beijing Olympic Games 29 Demonstration Project Ten Cities-One Thousand EVs Main EV Manufacturers in China 212 12th Five-Year Plan of EV Technology 21 Pilot Programs: Subsidies for Purchase New-Energy Vehicles at 5 Cities
Research Background Time Node By 212 By 215 By 215 By 22 By 22 By 22 Work China is expected Assuming to reach 5K the charging production capacity in EV sector. The target for power the number is 1kW, of EV simultaneous in China is between 5, and 1 million. charging power would reach 5 million kw (5GW) 17 charging stations and!!! 3 million of charging poles will be ready. The Chinese government decreed that 5 million EVs will be traveling the nation's roads. According to banking giant HSBC, China will equate to 35% of the global EV market. According to a report from the New Energy Vehicle Development Program drafted by the National Development & Reform Commission and the Ministry of Science & Technology, China will require new energy vehicles to account for 5% of total auto making capacity.
Research Background SGCC has set up a 3-Stage charging infrastructure plan (Now under stage II) III 22 216 II 211 29 I 3-stage charging Infrastructure plan of SGCC
Outline Research Backgrounds Interaction between EV and Grid What we have done Future Work
Interaction between EV and Grid Demand side Opportunity & Challenge Generation side Energy Flow Energy Flow.. As load (V1G) New growth point of electricity Load shaping As smart storage system (V2G) Reduce system reverse Improve utility ratio of facilities Reduce cost on fossil fuel Ancillary Service Frequency response Emergency Power Supply Improve system stability/power quality Support intermittent renewable sources
Interaction between EV and Grid Power system planning, evaluation and upgrading Adequate system reserve Power system stability Power supply quality Standard formulation & relevant policies
Outline Research Backgrounds Interaction between EV and Grid What we have done Future Work
Research Basis Interaction between transportation and power systems Intelligent Transportation System (ITS) EVs charging location EVs start charging time EVs daily travel distance GIS, GPS Origin-Destination Analysis Information Flow Our Researches Smart Grid Planning and Evaluation Distribution system planning evaluation tool based on EV characteristics, user daily transportation behavior, etc. Operation Voltage stability analysis and preventive control Coordination between EVs and large scale wind farms Modeling Planning Stability Energy Storage for MG Title Unit Commitment in here Management System Demonstration Project
Research I: : Battery Model Research I General Battery Model
Research I: : Battery Model A Simple Controlled Voltage Source In Series With A Constant Resistance Internal Resistance Ibatt Assumption: Constant Charging Current E Controlled Voltage Source Vbatt V batt E A exp( B it ) R i K Q Q it Q EE K AexpBit Qit it t P E i K i Q Q it Ai exp( B it) R i 2
Research I: : Battery Model V batt P K Q E A exp( B it ) R i Q it E K i Q Q it i Ai exp( B it) R i 2 Dumb Smart V2G Charge Curve of Electric Vehicles Q: Battery i: Battery Current Capacity R: Internal E: Constant Resistance K: Polarisation Voltage A: Exponential Voltage Zone Amplitude B: Exponential Zone Time Constant Inverse Typical Discharge Curve Q Battery Capacity Random Statistical Survey Data Sampling from EVs Market Advantages of GBM 1.Simple, few parameters; 2.Modeling for different kinds of batteries; 3.Exactly describing batteries external characteristic of EVs
Research II: E-EPPE EPP Research II An Efficient Power Plant of EV Aggregation (E-EPP) EPP)
Research II: E-EPPE EPP Natural Coal-fired Generators Nuclear Power Plants Tianjin Efficient Power Plant of EVs Residential Customers Rooftop Solar Plug-in Electric Vehicles Hydro power plants Transmission & Distribution Lines Wind Farms Solar Farms New Challenge 8, 8, 7, 7, Power in kw 6, 5, 4, 3, 2, Supply Supply Demand Demand Power in kw 6, 5, 4, 3, 2, 1, 1, 1-Jan-6 2-Jan-6 3-Jan-6 4-Jan-6 5-Jan-6 Time 1-Jan-6 2-Jan-6 3-Jan-6 4-Jan-6 5-Jan-6 Time
Research II: E-EPPE EPP Battery SoC t_charge Probability Density.25.2.15.1.5 Probability Density HBW&HBO NHB 2 4 6 8 1 12 14 16 18 d/km Probabilty Density.15.1.5.15.1.5 Battery Capacity of L7e.2 Starting Time of Traveling.15.1 Batteries for Evs.5.7 HBW HBO NHB.6 Probability HBW HBO NHB Probability 3 4 6 8 1 12 14 15 Battery Capacity (KWh).5.4.3 Probability.5.4.3.2.1 Battery Capacity of N1 Nickel-cadmium.5.2 24 48 72.1 96 12 144 Time (min) Finishing Time of Traveling 9.6 15 2 25 3 35 4 Battery Capacity (KWh) Lead-acid Lithium-ion L7e M1 N1 N2 Nickel-metal-hydride 1 2 3 4 5 6 72 Battery Capacity (KWh) 24 48 72.5-.1 96.1-.15.15-.2 12.2-.25.45-.5 144.5-.55.8-.85 Time (min) Energy Consumption (KWh/km) Probability Probability.3.2.1.15.1 Battery Capacity of M1 Battery Capacity of N2 51 6 7 8 9 1 11 12 Battery Capacity (KWh)
Research II: : E-EPPE EPP
Research II: E-EPPE EPP Unit Commitment for Wind Farms E-EPP k P / P P / P i, j G L G L Wi Wj Wi W j, m L L L L Wj Cm Wj C P L k Wj i, j PWi P k P Cm G j, m Cj
Research II: E-EPPE EPP 1 2222222222 Chargin 444 New Upper/Lower Boundary Target Power Actual Power Probability 1.8.6.4.2 EPP Response (MW) 5-5 96 12 144 With V2G.1.2.3.4.5 SoC.6.7.8-1 24 48 72 Time (min) SoC Variation.9 1 Probability Density.8.6.4-15 24 48.3 72 96 12 144 Time (min).4 Without V2G.2 SOC Distribution -2-15 -1-5 5 1 15 2 G1 Output Variation on Minute-Scale (MW) Probability.4.2.1.1.2.3.4.5 Probability Density.3.2.1 48 96 72 Time (min).6 SoC.7.8 24.9-2 1-15 -1-5 5 1 15 2 G12 Output Variation on Minute-Scale (MW) 12 144