A multi-time-scale autonomous energy trading framework within distribution networks based on blockchain

Yiqian Wu, Xuan Zhang and Hongbin Sun

Applied Energy, 2021, vol. 287, issue C, No S0306261921001070

Abstract: The deregulation of the power industry leads to a deeper penetration of prosumers directly participating in electricity transactions. Local energy trading can mobilize social cooperation and enhance the resilience within the trading system. In this paper, a blockchain-based multi-time-scale autonomous energy trading system within distribution networks is introduced and evaluated. The energy trading mechanism consists of three stages: the day-ahead stage focuses on main load dispatching and on/off decisions; the real-time stage corrects the prediction errors; the energy trading stage completes energy tracking and employs a model predictive control strategy to mitigate uncertainties and improve system performance. From the space perspective, energy management is conducted hierarchically and distributively by central and building energy management systems. For the scheduling process, the heterogeneous consumer preferences, load characteristics and demand flexibility are reflected in the system model. Regarding the clearing process, the nodal clearing prices are determined based on loss allocation, and the settlement results are recorded through blockchain onto the distributed ledgers. Finally, the proposed autonomous energy trading mechanism is verified on the IEEE 13-bus distribution network and investigated with sensitivity analysis.

Keywords: Energy trading; Optimal power flow; Distributed optimization; Model predictive control; Loss allocation; Blockchain (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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DOI: 10.1016/j.apenergy.2021.116560

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