Economic impact of EVs in the Brazilian electrical distribution networks

Transcription

1 Economic impact of EVs in the Brazilian electrical distribution networks Code: Flávio T. Mariotto, Luiz C. P. Silva, Yuri G. Pinto, Fernanda C. L. Trindade 11/11/2017 1

2 Objectives Evaluation of the economic impacts of the massive use of electric vehicles resulting from the mitigation of technical impacts in the Brazilian networks distributors 11/11/2017 2

3 Introduction New demand for electric energy to the Electric Vehicles (VEs) (i) Battery Electric Vehicles (BEV) (ii) Plugins Hybrid Electric Vehicles (PHEV) Predominance of charge in home or work environment Long charging time will affect the load curve. Change the operating conditions of the distribution network (i) decrease in voltage magnitude (ii) increased voltage unbalance (iii) overload of conductors and transformers Investments to reinforcing infrastructure to mitigate technical impacts 11/11/2017 3

4 Methodology EE daily demand Violations simulation in the distribution network Adhesion of VEs Grouping by distributor Apparent penetration of VEs Investment projection and financial evaluation BEV and PHEV 11/11/2017 4

5 Adhesion of VEs Financial Factors Tax Benefits Cost of use Prices BEV VHEP VHE ICE Tendencies System Dynamics 11/11/2017 GDP TCO Market offer Non-Financial Benefits Demand growth Attenuators Autonomy Absence of public chargers Affected market percentages Potential Market Segmentation Mercado Total de Veículos Total vehicles sales p q m BEV Sales p q m PHEV Sales p q m HEV Sales - ICE Sales Bass - BEV BEV Fleet Scrapping Bass - PHEV PHEV Fleet Scrapping... ICE Fleet Scrapping 5

6 Adhesion of VEs Projection of fleet of plugins VEs In 2030: 7,7 millions (14% of light vehicles fleet of) 4,5 millions 1,2 millions 11/11/2017 6

7 Grouping by distributor Relevant Cities Criteria grouping based on GDP, GDP per capita, HDI and population. 10% of Brazilian cities (556 cities) 77% of the light vehicles fleet VEs fleet in % of the electricity distributors Distribution of VEs in the Relevant Cities Actually Adhesion proportionally to actual VEs fleet After 2024 Adhesion proportionally to actual light fleet Denatran (Adapted) BEV VEB VHEP PHVE VHE HVE Veícul Veícul Releva 11/11/2017 7

8 Consumo diário de EE (kwh) Electric energy daily demand São Paulo State Cetesb 2015 ANP (Ref 2014) Sindipeças - (Frota circ. 2015) Denatran - frota-2014 Fuel consumption by city (Gas and ethanol) Fleet by city, vehicle type and fuel Daily Km in 2016: 39,6 km Grow tx: 0,4 km/year Km by vehicle age (City SP) Cetesb 2015 (Adapted) Tendency of daily km in the Relevant Cities Daily average in 2030 to BEVs: 56 km 10,0 Vehicle efficiency (km/kwh or km/l) VEs fleet 9,0 8,0 7,0 6,0 5,0 4,0 3,0 2,0 1,0 0,0 Projection of daily energy demanded by VEs in kwh in the Relevant Cities BEV VEB PHVE VHEP 11/11/2017 8

9 Consumo diário de EE (kwh) Apparent penetration of VEs 10,0 9,0 8,0 7,0 6,0 5,0 4,0 3,0 2,0 1,0 0,0 Daily energy demanded VEs fleet VEB VHEP Absolute Penetration (Fleet VE/Consumer) Balances differences in energy demand of plugins vehicles P Ap P VHEP D VEB D ref D VEBmt P VEB D VHEP D ref D VHEPmt D ref = Daily reference charge =10,7 kwh 16% 14% 12% 10% 8% 6% 4% 2% 0% PHVE Penatração Penetration VHEP BEV Penetração Penetration VEB Apparent Penetração Penetration aparente VEs 11/11/2017 9

10 Distribution Network Violations Monte Carlo simulation of 25,000 secondary networks BEVs penetration of 10%, 20% and 30% 200 random scenarios per network (i) Position of the charging stations (ii) Initial time of each recharge from 6:00 p.m. to 9:00 p.m. (iii) Variable charging duration based on: biphasic chargers with power of 3.3 Kw daily reference charge of 10.7 kwh (daily average of 50 km) probability density with log-normal curve (iv) Load flow calculation for 24 hours 11/11/

11 Mitigated Network Percentages Distribution Network Violations Main violations types Mitigated Network Percentages 9,5% 11,1% 0,6% 78,8% Conductors Transformers Magnitude de of tensão tension Sobrecarga Conductor condutores overload Desequilíbrio Voltage imbalance de tensão Sobrecarga Transformer transformador overload BEVs Penetrations Voltage magnitude violation occurs in almost 80% of the affected networks 11/11/

12 Probability by investment range Percentile (cumulative probability) Distribution Network Violations Frequency of investments to enhance conductors 10% penetration of BEVs Network with violation: Inv range Percentile Investment per network with violation (R$) 11/11/

13 Investment projection and financial evaluation 11/11/

14 Results Projection of investments in planing cycles Investimentos de adequação de rede (Milhares R$) Cycle 1 Cycle 2 Cycle 3 Ciclo 1 Ciclo 2 Ciclo 3 Rate revision Revisão tarifária Revisão tarifária Revisão tarifária Minimum Investimento mínimo Rate revision Variation Variação investimento Rate revision Investimentos de adequação de rede (Milhares R$) Cycle 1 Ciclo 1 Ciclo 2 Ciclo 3 G1 G2 G3 G4 G5 G1 G2 G3 G4 G5 G1 G2 G3 G4 G5 Investimento mínimo Variação investimento Minimum Cycle 2 Variation Cycle 3 Reference distributor All distributor in Relevant Cities Marginal investments (to those normally made by distributors) 11/11/

15 Probabilidade Results Amount of investments until 2030 to all Relevant Cities Investments frequency Investimentos Brasil 9% Average Média de R$ R$ ,15 millions Milhões 8% From De R$ 30,6 31 to a R$ 7776,9 millions Milhões 70% probabilidade 7% 70% probability Desvio padrão/média: 46% Standard deviation / mean: 46% 6% Média por consumidor de R$ 1,71 5% Average per consumer of R$ 1.71 De R$ 0,95 a R$ 2,38 4% From 70% R$ probabilidade 0.95 to R$ % probability 3% 2% 1% 0% Investment Valor investimento range (Millions (Milhões R$) 11/11/

16 Valor Presente Líquido (Milhares R$) Results Remuneração regulatória (milhares R$) Amount of regulatory revenues up to 2030 From R$ 30 million to 60 million Economic assumptions Minimum Remun. regulatória investimentos Variation Variação Remun. Regulatória Net Present Value (NPV) in 2030 From $ 2 million to 6 million ROI = 12% Financing approach /11/

17 Discussions Total investment by distributor ELETROPAULO CEMIG-D CPFL Paulista COPEL-DIS CEB-DIS LIGHT CELESC-DIS CELG-D BANDEIRANTE ELEKTRO AMPLA RGE Inv Minimum Inferior Var Variation inv Total de investimentos (Milhõies de R$) Highest distributors Amount of Investment (R$) Wide dispersion of investments (28 times) (VEs penetration and networks characteristics) Investment by consumer CEB-DIS IENERGIA CAIUÁ-D CPFL Leste Paulista COCEL ELETROPAULO CELESC-DIS RGE Energisa (CNEE) COPEL-DIS CPFL Paulista EEB CEMIG-D COOPERALIANÇA ELEKTRO CPFL Jaguari ELETROCAR CELG-D CPFL Santa Cruz CPFL Mococa Energisa (ENERSUL) Municípios Relevantes Abordagem de financiamento Average value CPFL Sul Paulista Energisa (CEMAT) EDEVP AES SUL BANDEIRANTE ELETROBRÁS RONDÔNIA Inv Minimum min. por consum Variation inv. por consum Valor médio entre as distribuidoras 0,00 1,00 2,00 3,00 4,00 5,00 6,00 7,00 8,00 Investimento por consumidor (R$) 11/11/

18 Discussions Response to the displacement time of the VE charge Encouraged for consumers to charge VEs out of peak hours Survey of consumers with EVs in California* 62% use a special PEV rate (when available from the distributor) Reduction of investment from 60% to 70% * EV Consumer Survey Dashboard 11/11/

19 Conclusions Low impact in the short term By 2030 the estimated investment amount is from R$ 0.95 to R$ 2.38 per consumer Strong investment reduction triggered by off-peak VEs charge Planning New energy demand Methods of prediction and mitigation of impacts in the distribution network Availability of capital for investments Regulation Review of prudence criteria for investments defined by the regulator Incentives to charge out-of-peak hours (Smart Charge) 11/11/

20 Acknowledgments Aneel Research project PD /2013 Technical and Commercial Insertion of Electric Vehicles in Business Fleets of the Metropolitan Region of Campinas CPFL Paulista CPqD UNICAMP (University of Campinas) 11/11/