Assessment of Plug-in Electric Vehicles Charging on Distribution Networks
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Assessment of Plug-in Electric Vehicles Charging on Distribution Networks Master Thesis Defense - Tsz Kin (Marco) Au Committee Chair: Committee Co-Chair: Committee Member: Dr. M. Ortega-Vazquez Dr. M. El-Sharkawi Dr. D. Kirschen Presentation Outline I. II. III. IV. V. Introduction of PEV The developed tool for investigating the impact of PEV Test system characteristic Test result Conclusion 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 2 Presentation Outline I. II. III. IV. V. Introduction of PEV The developed tool for investigating the impact of PEV Test system characteristic Test result Conclusion 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 3 Technological Impacts of PEVs Potential benefits: • Lower operating cost than combustion engine vehicles: 3.7 vs. 16.7 cents • On road CO2 emission will be lower • V2G and ancillary services provide business opportunities Problems: • • • • 10% penetration = additional 300 GWh per day in the U.S. Increase grid losses Reduce system spare generation and harder to schedule maintenance Poorer voltage profile and transformer overloading in weakly meshed distribution networks 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 4 What causes poor voltage profile and transformer overloading? Line impedance Coincidence between PEV charge time and system peak load Poor voltage profile and overload transformer Lack of interconnection 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 5 Presentation Outline I. II. III. IV. V. Introduction of PEV The developed tool for investigating the impact of PEV Test system characteristic Test result Conclusion 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 6 Monte Carlo Simulation • Suitable for analysis when Read data and uncertainties present initialize parameters • 4 uncertainties needed to be address: – – – – Charging time Battery state of charge (SOC) Charging method Customer load variation • 7 major functional blocks • Each trail represent 24 hours 6/5/2012 Generate random scenarios Run deterministic system Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 7 1. Data Processing and Initialization • 34,000+ drivers’ behavior from CMAP, which consists of their to-work and to-home arrival times. • Electric vehicle parameters – Battery capacity – Energy consumption per unit distance • Distribution network conductor parameters • Average power consumption and load type at each node – Residential area – Commercial area 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 8 2. PEV Penetration and Charging Points πππ‘ππ ππ’ππππ ππ πππ π πππππ ππΈπ ππΈπ πππππ‘πππ‘πππ = πππ‘ππ ππ’ππππ ππ πππ π πππππ π£πππππππ Charge at home or at work? Type 1: Charge at home only Type 2: Charge at home and work 33.33% 66.67% 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 9 3. PEV’s Arrival Time • PEV drivers will charge their vehicles anytime at their convenience • Their arrival times affect the charge profile • Drivers’ behaviors varies from day to day, which creates uncertainty • Must model the uncertainty in order to simulate its effect to the power system 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 10 3. PEV’s Arrival Time Inverse transformation for random number generation • Map rand(0,1) → actual distribution 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 11 4. PEV’s Battery State of Charge • Commute distance have an effect on the battery state of charge • A driver’s commute distance although is similar everyday, it may vary sometime, which causes uncertainty • Must model this uncertainty in order to simulate its effect to the power system • Convert commute distance to battery state of charge (SOC) πππΆ = π΅ππ‘π‘πππ¦ πΆππ. (πππ) − πΆππππ’π‘π π·ππ π‘. (ππππ) × 0.34 πππ/ππππ 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 12 4. PEV’s Battery State of Charge Percentage (%) 19.19 22.95 16.67 13.77 9.37 6.07 4.59 2.69 4.70 Commute Distance Distribution Percentage (%) 25 20 15 Quantile Function of Commute Distance Commute Distance (Mile) Commute distance (miles) 0 – 4.0 4.1 – 8.0 8.1 – 12.0 12.1 – 16.0 16.1 – 20.6 20.1 – 24.0 24.1 – 28.0 28.1 – 32.0 32.1 + 35 30 25 20 15 10 5 0 -5 0 y = 353.04x5 - 725.13x4 + 526.87x3 - 140.15x2 + 22.691x - 0.0038 R² = 0.9997 0.2 10 0.4 0.6 Probability 0.8 1 5 0 Commute Distance (Mile) 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 13 5. PEV Charge Profile • Computed individually based on arrival time, battery state of charge, and charging method # ππ ππΈπ πππ‘ππ πΆπππππ πππππππππ = ππ,ππ π Power (kW) 8 6 4 2 0 0 2 4 6 8 10 12 14 16 Hour 18 20 22 24 26 28 30 0 2 4 6 8 10 12 14 16 Hour 18 20 22 24 26 28 30 Power (kW) 8 6 4 2 0 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 14 6. Customer Load Profile • Varies from day to day • The variation is assumed to be Gaussian distributed: π πππ’π ,π‘π = 1 πππ’π ,π‘π 2π π −π΄π£ππππ’π ,π‘π ) 1 (π − β ππ’π ,π‘π 2 2 π ππ’π ,π‘π ππππ π΄π£ππππ’π ,π‘π = ππ‘π¦ππ,π‘π × π΄π£ππππ’π 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 15 7. Running Power Flow Analysis for the Distribution System • Cannot use Newton-Raphson based methods • Distribution networks characteristic: – High R/X ratio → Decoupled and fast decoupled methods won’t work – Weakly meshed, sparse network → Newton-Raphson method won’t work • Forward-backward sweep method is used 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 16 7. Running Power Flow Analysis for the Distribution System Forward-backward sweep method example: 7200V 1 2 3 3000’ 4000’ S2 π§ = 0.3 + π0.6 β¦/ππππ S3 π§12 = 0.1705 + π0.3409 β¦ π§23 = 0.2273 + π0.4545 β¦ π 2 = 1500 + π750 ππ + πππππ π 3 = 900 + π500 ππ + πππππ 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 17 7. Running Power Flow Analysis for the Distribution System Forward-backward sweep method example: π1 = 7376.2∠0.97 π 1 7200V π2 = 7260∠0.23 π π3 = 7200 π 2 3 3000’ 4000’ πΌ12 πΌ23 πΌ2 S2 πΌ3 S3 Forward sweep: 1) Assume voltage at node 3 is 7200V 2) Compute πΌ3 ∗ π 3 πΌ3 = = 143.0∠ − 29.0 π΄ π3 6) Compute πΌ12 πΌ12 = πΌ23 + πΌ2 = 373.9∠ − 27.3 π΄ 3) Compute πΌ23 πΌ23 = πΌ3 = 143.0∠ − 29.0 π΄ 7) Compute π1 π1 = π2 + π12 β πΌ12 = 7376.2∠0.97 π 4) Compute π2 π2 = π3 + π23 β πΌ23 = 7260.1∠0.23 π 6/5/2012 5) Compute πΌ2 ∗ π 2 πΌ2 = = 231.0∠ − 26.3 π΄ π2 8) Compute mismatch between π1 and ππ πππ πππ‘ππ = ππ − π1 = 176.2 π Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au Not satisfy! 18 7. Running Power Flow Analysis for the Distribution System Forward-backward sweep method example: π2 = 7085.4∠ − 0.68 π π1 = 7200 π 7200V 1 2 π3 = 7026.0∠ − 1.02 π 3 3000’ 4000’ πΌ12 πΌ23 S2 S3 Backward sweep: 1) Assume voltage at node 1 is 7200V, and use the line currents computed from forward sweep 2) Compute π2 π2 = π1 − π12 β πΌ12 = 7085.4∠ − 0.68 π 3) Compute π3 π3 = π2 − π23 β πΌ23 = 7026.0∠ − 1.02 π 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 19 7. Running Power Flow Analysis for the Distribution System Forward-backward sweep method example: π2 = 7087.6∠ − 1.02 π π1 = 7206.5∠0.0 π 7200V 1 2 3 3000’ 4000’ πΌ12 πΌ23 πΌ2 π3 = 7026.0∠ − 1.02 π S2 πΌ3 S3 Perform forward sweep again: 1) Use the voltage at node 3 from the backward sweep 2) Compute πΌ3 ∗ π 3 πΌ3 = = 146.5∠ − 30.1 π΄ π3 6) Compute πΌ12 πΌ12 = πΌ23 + πΌ2 = 383.0∠ − 28.3 π΄ 3) Compute πΌ23 πΌ23 = πΌ3 = 146.5∠ − 30.1 π΄ 7) Compute π1 π1 = π2 + π12 β πΌ12 = 7206.5∠0.0 π 4) Compute π2 π2 = π3 + π23 β πΌ23 = 7087.6∠ − 1.02 π 6/5/2012 5) Compute πΌ2 ∗ π 2 πΌ2 = = 236.6∠ − 27.2 π΄ π2 8) Compute mismatch between π1 and ππ πππ πππ‘ππ = ππ − π1 = 6.535 π Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au Satisfy! 20 Presentation Outline I. II. III. IV. V. Introduction of PEV The developed tool for investigating the impact of PEV Test system characteristic Test result Conclusion 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 21 Test System Characteristic Assumption: • 4000 residents • Average 2.35 people and 1.78 passenger vehicles per household • power factor = 0.9 • power factor = 0.8 • Avg. 959.5 W/household • Average power consumption: = 81.6 + 40.8j (kW+kVar) = 100 + 75j (kW+kVar) = residential area = 85 households = commercial area = 1 small shopping plaza 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 22 Test System Characteristic Charging method and scenario: • Level 1: 1.3 kW • Level 2: 3.3 kW • Level 3: 50 kW Type 1 Type 2a (charge at residential area) 15% Level 1 Level 2 85% Level 3 Type 2b (charge at commercial area) 10% Level 1 25% Level 2 75% 6/5/2012 Level 3 Level 1 30% 60% Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au Level 2 Level 3 23 Presentation Outline I. II. III. IV. V. Introduction of PEV The developed tool for investigating the impact of PEV Test system characteristic Test result Conclusion 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 24 Test Result: Voltage Violation Voltage Profile • Voltage should operate ±0.05 p.u. • Voltages at the End Buses have higher chance to suffer low voltage violation 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 25 Test Result: Voltage Violation Voltage profile confidence interval at bus 16 6/5/2012 0% Penetration 30% Penetration 50% Penetration 100% Penetration Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 26 Test Result: Voltage Violation Voltage distribution for 0% Penetration Scenario 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 27 Test Result: Voltage Violation Voltage distribution for 50% Penetration Scenario 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 28 Test Result: Voltage Violation Voltage distribution for 100% Penetration Scenario 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 29 Test Result: Transformer Load • Although transforms usually can be overloaded for short period of time with limited amount, overloading it by too much or too long will decrease its life time • Transformer overloaded: loaded above its capacity • Transformer violation: loaded 20% above its capacity 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 30 Test Result: Transformer Load Transformer load profile 6/5/2012 Transformer load distribution Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 31 Presentation Outline I. II. III. IV. V. Introduction of PEV The developed tool for investigating the impact of PEV Test system characteristic Test result Conclusion 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 32 Conclusion • Electricity for transportation? Yes or No? • PEVs impacts vary from system to system – Voltage violation: long radial networks – Substation transformer violation: Heavy load, high PEV penetration • A tool to evaluate PEVs impacts is developed 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 33 Thank you! 6/5/2012 Electrical Engineering Department - University of Washington Master Thesis Defense - Tsz Kin (Marco) Au 34
