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Data Valuation in Electricity Transactions with Uncertainty Considering Risk Preferences

Uncertainty is an inherent characteristic in power systems, especially under the high penetration of renewable energies, and will probably lead to economic losses of entities. With the development of data technology, acquiring related data to eliminate uncertainty and prevent from being affected by it is feasible. However, the data value depends on multiple endogenous or exogenous factors, thus data transactions are difficult to organize since the vagueness of the data valuation. Based on the scenario that wind power producers (WPPs) participating in electricity markets, the data value is defined as the profit enhancement related to the improvement of the wind power forecast and derived from the perspective of WPPs in this paper. To promote the accuracy of the data valuation, risk preferences of WPPs are taken into consideration, where the commonly used conditional value-at-risk (CVaR) is used in quantitative analysis of their perceptions of risk and the WPPs are divided into risk-neutral, risk-averse, and risk-prone WPPs. Then, the risk premium in the data value is extracted and analyzed to illustrate the impact of WPPs’ risk preferences on the data value. Finally, case studies with real wind power data are employed to indicate the feasibility and significance of the data valuation considering risk preferences.