Electricity data valuation and game pricing for enhanced DRL-based economic dispatch

Ziming Liu, Bonan Huang, Rui Wang, Jiaqi Tian, Pengbo Du and Qiuye Sun

Energy, 2025, vol. 335, issue C

Abstract: To address the problem of acquiring high-quality data required for AI-based economic dispatch in data trading, this paper proposes a blockchain-enabled electricity data trading framework, which incorporates a comprehensive market mechanism that includes data valuation, pricing, and trading. The platform aims to facilitate the discovery of high-quality data in market transactions and enable the sharing of economic dispatch data. First, a novel valuation method is proposed to effectively assess the value attributes of electricity data, considering uncertainty, integrity, and timeliness in power system dispatching. On this basis, the market clearing price of electricity data, guided by the data valuation, is obtained through a game-theoretic approach that takes into account the supply and demand of the electricity data. Furthermore, transactions are completed using smart contracts, eliminating the need for third-party data servicers and effectively preventing data privacy leaks and realizing data trading without trust. Simulations are provided to illustrate the effectiveness of the proposed framework and mechanisms.

Keywords: Blockchain; Electricity data market; Data valuation; Data pricing mechanism; Information theory (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:335:y:2025:i:c:s0360544225035376

DOI: 10.1016/j.energy.2025.137895

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