Combined Output Optimization Based on Blockchain for Micro-grid with Electric Vehicles

doi:10.12204/j.issn.1000-7229.2020.11.002

Abstract

Abstract:

Blockchain technology has the characteristics of decentralization, non-tampering, multi-party data sharing and common maintenance, which enables two parties that do not understand and trust each other to achieve credible and equivalent power transactions. In view of the lack of trust between vehicle owners and service providers in the charge and discharge of electric vehicles, the disorder charge and discharge of a large number of electric vehicles will cause peaks on the grids’ peak load. A mutual trust transaction architecture and scheduling strategy based on the electric vehicle alliance chain is proposed. Firstly, the white box password, smart contract, and congestion management in the blockchain are introduced to analyze the execution process of the transaction mechanism on the electric vehicle chain; Secondly, a double-layer optimal scheduling model for electric vehicles is built. The outer layer aims at encouraging the new charging peak problem aroused by encouraging to charge at low electricity prices, comprehensively considering the load variance and user creditability, optimizing the time-of-use electricity pricing strategy, and optimizing the electricity price curve export to the inner model. The inner layer aims to eliminate the problem of higher cost for the deviation of electricity, and uses the mobile energy storage characteristics of electric vehicles to achieve self-balance of power supply and demand. Finally, the differential evolutionary game combination algorithm with incentive mechanism is used to solve the problem, and the effectiveness of the proposed strategy is verified by simulation.

Key words: blockchain, microgrid, electric vehicle, combined output

CLC Number:

TM734

FU Xiaolin, WANG Hong, WANG Zhijie. Combined Output Optimization Based on Blockchain for Micro-grid with Electric Vehicles[J]. ELECTRIC POWER CONSTRUCTION, 2020, 41(11): 16-26.

Figures/Tables 18

Fig.1 Alliance chain of electric vehicles

Fig.2 Lookup table for encoding

Fig.3 Process of consortium chain module

Fig.4 Execution of the electric vehicle charging transaction model

Fig.5 Model of smart contract

Fig.6 Blockchain-based electric vehicle creditability model

Fig.7 Electric vehicle scheduling architecture based on blockchain

Fig.8 Flowchart of differential evolution game combination algorithm with incentive mechanism

Fig.9 Flowchart of optimized scheduling for electric vehicles

Table 1 Equipment parameters of Beijing Jinfeng Energy Internet Park

Table 2 Parameters of electric vehicles

Table 3 Electricity price optimization of electric vehicle charging

Fig.10 Success rate of malicious node attack

Fig.11 Time-of-use price pricing optimization

Fig.12 Optimization model of electric vehicle creditability based on block-chain

Fig.13 SOC of electric vehicle

Fig.14 Power grid load

Fig.15 Comparison of electric vehicle discharging power

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