Comprehensive Analysis of Data Value and Its Properties in Electricity and Data Transactions

Abstract

Decision-making in electricity transactions is always with inevitable uncertainty, which will probably lead to economic losses of participants and mitigate the efficiency of electricity transactions. Data transactions, which can break the information barrier and promote the data circulation, aim at uncertainty elimination through data interactions and are considered a promising solution. In this paper, a general framework of electricity and data transactions considering both load-side and source-side are constructed. Electricity retailers and renewable energy producers are taken as the representative of load-side and source-side market participants who have to face and manage uncertainty. A profit curve is shown considering the imbalance between day-ahead electricity bid and real-time electricity supply/demand. Inspired by our previous work, data value, which is defined as the enhancement of economic benefits caused by data transactions, is further explored and its mathematical properties are comprehensively analyzed. Based on the Cauchy-Schwarz inequality and Kolmogorov-Smirnov test, the upper bound and possible range of data value are analytically derived. Finally, a numerical example is employed to validate the theoretical results and illustrate that appropriately utilizing the data value and its properties can help market participants make better decisions in data transactions.