  With the development of Internet of Things (IoT) and big data technology, the
data value is increasingly explored in multiple practical scenarios, including
electricity transactions. However, the isolation of IoT data among several
entities makes it difficult to achieve optimal allocation of data resources and
convert data resources into real economic value, thus it is necessary to
introduce the IoT data sharing mode to drive data circulation. To enhance the
accuracy and fairness of IoT data sharing, the heterogeneity of participants is
sufficiently considered, and data valuation and profit allocation in IoT data
sharing are improved based on the background of electricity retail. Data
valuation is supposed to be relevant to attributes of IoT data buyers, thus
risk preferences of electricity retailers are applied as characteristic
attributes and data premium rates are proposed to modify data value rates.
Profit allocation should measure the marginal contribution shares of
electricity retailers and data brokers fairly, thus asymmetric Nash bargaining
model is used to guarantee that they could receive reasonable profits based on
their specific contribution to the coalition of IoT data sharing. Considering
the heterogeneity of participants comprehensively, the proposed IoT data
sharing fits for a large coalition of IoT data sharing with multiple
electricity retailers and data brokers. Finally, to demonstrate the
applications of IoT data sharing in smart grids, case studies are utilized to
validate the results of data value for electricity retailers with different
risk preferences and the efficiency of profit allocation using asymmetric Nash
bargaining model.
