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An Optimized EV Charging Model Considering TOU price and SOC curve

An Optimized EV Charging Model Considering TOU price and SOC curve. Authors: Y. Cao, S. Tang, C. Li, P. Zhang, Y. Tan, Z. Zhang and J. Li Presenter: Nan Cheng 2013.8.14. Outline. Introduction. Optimal Model for EV Charging. Case Study. Conclusion.

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An Optimized EV Charging Model Considering TOU price and SOC curve

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  1. An Optimized EV Charging Model Considering TOU price and SOC curve Authors: Y. Cao, S. Tang, C. Li, P. Zhang, Y. Tan, Z. Zhang and J. Li Presenter: Nan Cheng 2013.8.14

  2. Outline • Introduction • Optimal Model for EV Charging • Case Study • Conclusion

  3. Introduction (1) • EV charging loads increase in the near future • Negative impacts on stability • Risk system operations and management • 200 million EV in China in 2050 with charge load 330 MkW. • Three ways for EV-friendly access the power grid • V2G • Energy management equipment • Electricity pricing (Customers respond to price)

  4. Introduction (2) • Regulated electricity market (China) • Electricity remain unchanged once decided. • Catalog price, stepwise power tariff & time-of-use (TOU) price • TOU price varies in different periods of a day. • This paper: • Proposes an optimized charging model to adjust charging power and time based on TOU and SOC • Reduce the cost of costumers • Balance load demand

  5. Problem Description • Formulate optimized charging scheme with a specific starting time and ending time • Consider TOU price • Consider SOC curve to determine the charging constraints • Aim to minimize cost + peak clipping & valley filling

  6. Objective Function • : starting time of charging • : duration of charging • : unit price at time t • : charging power at time t

  7. Constraints • : maximum power set by EV user • : maximum power EV charger can output • : maximum allowed charging power to protect the battery based on the current state of charge.

  8. Constraints SOC v.s. maximum charging power

  9. Algorithm (1) • The optimized model is discretized: T is divided into N periods, each with length .

  10. Algorithm (2) • A heuristic algorithm is proposed • i and j are ascending sorted sequences, i.e., • Energy q is optimal step for the algorithm, the corresponding power step .

  11. Algorithm (3)

  12. Case Study - Setting Initial SOC distribution:

  13. Case Study – Results (1) Single EV Multiple EVs

  14. Case Study – Results (2)

  15. Conclusions • Response to TOU can reduce EV charging cost and meet the demand response requirements in regulated market.

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