Our company is glad to announce that we have a new publication in MDPI Mathematics: Blockchain and Double Auction-Based Trustful EVs Energy Trading Scheme for Optimum Pricing.
The paper is based on the AISTOR, FinSESco,CREATE, I-DELTA, DEFRAUDIFY, Hydro3D, FED4FIRE-SO-SHARED, AIPLAN-STORABLE, EREMI,SMARDY, STACK, ENTA, PREVENTION and by European Union’s Horizon 2020 research and innovation program under grant agreements No. 872172 (TESTBED2) and No. 101037866 (ADMATranS4MErs).
Electric vehicles (EVs) have gained prominence in smart transportation due to their unparalleled benefits of reduced carbon footprints, improved performance, and intelligent energy tradingmechanisms. These potential benefits have increased EV adoption at massive scales, but energymanagement in EVs is a critical study problem. The problem is further intensified due to the scarcityof charging stations (CSs) in near EV proximity. Moreover, as energy transactions occur over openchannels, it presents critical security, privacy, and trust issues among decentralized channels. Toaddress the open limitations of trusted energy management and optimize the pricing control amongEV entities (i.e., prosumers and consumers), the paper proposes a scheme that integrates blockchainand a truthful double auction strategy for trustful EV trading. To address the transaction scalability,we integrate an Interplanetary File System (IPFS) with a double auction mechanism handled throughthe Remix Smart Contract environment. The double auction leverages an optimal payoff conditionbetween peer EVs. To address the communication latency, we present the scheme at the backdropof Fifth Generation (5G) networks that minimizes the optimal payoff response time. The schemeis simulated against parameters such as convergence, profit for consumers, computation time, andblockchain analysis regarding node commit latency, collusion attacks, and EV energy consumption.The results indicate the scheme’s viability against traditional (non-blockchain) approaches with highreliability, scalability, and improved cost-efficiency.
Check the paper here.