An Optimized EV Charging Model Considering TOU price and SOC curve

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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. - PowerPoint PPT Presentation

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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 Cheng2013.8.14

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

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

Objective Function

– : starting time of charging– : duration of charging– : unit price at time t– : charging power at time t

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.

Constraints

SOC v.s. maximum charging power

Algorithm (1)

The optimized model is discretized: T is divided into N periods, each with length .

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 .

Algorithm (3)

Case Study - Setting

Charging curve Distribution of start time

TOU price

Initial SOC distribution:

Case Study – Results (1)

Single EV Multiple EVs

Case Study – Results (2)

15

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

Conclusions

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