Two-Stage Transaction Optimization for Electric Vehicle Charging Piles Applying Blockchain Technology

doi:10.12204/j.issn.1000-7229.2021.12.011

Abstract

Abstract:

In order to solve the problem of trust between charging transaction subjects caused by the large-scale development of electric vehicles, this paper proposes a two-stage transaction optimization method for electric vehicle charging piles applying blockchain technology. Firstly, a two-stage transaction optimization framework for electric vehicle charging piles is designed. Then, in order to avoid the impact of overload on the safe and stable operation of the grid, the two-way trading market and P2P trading market are introduced with the capacity margin of the power grid as the constraint. The method performs charging rights transactions between charging stations, and builds an optimization model for the grid and electric vehicle charging pile transactions. Secondly, in order to reduce the deviation penalty cost of charging stations and guide electric vehicle owners to charge in an orderly manner, an optimization model based on demand response is built for the transactions between charging piles and the users. Finally, a simulation scenario is taken as an example to verify the validity of the model. The results of calculation examples show that the two-stage transaction optimization model based on blockchain technology can increase the revenue of the charging station and reduce the peak-to-valley difference of the system.

Key words: blockchain, electric vehicle, transaction optimization, two-way transaction, P2P transaction

CLC Number:

TM73

ZHAO Sixiang, WANG Yachao, JU Hanji, HU Tianshu, CHU Fengming. Two-Stage Transaction Optimization for Electric Vehicle Charging Piles Applying Blockchain Technology[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(12): 93-103.

Figures/Tables 13

Fig.1 Two-stage transaction optimization framework for electric vehicle charging piles

Table 1 Allocation result of initial reputation values

Table 2 Electricity purchase price of charging station from the grid

Fig.2 Typical daily base load curve of the system

Table 3 Allocation result of initial charging rights

Table 4 Results of two-way transaction

Table 5 Scenarios setting

Fig.3 Changes in the revenue of charging stations

Fig.4 Comparison of electric vehicle time-of-use price

Fig.5 Comparison of load curves in regional scenarios

Table 6 Comparison of electricity sales revenue of charging stations under different scenarios

Fig.6 Sensitivity analysis of charging price threshold

Fig.7 The influence of reputation value setting on charging stations and car owners

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