  This paper, for the first time, proposes a joint electricity and data trading
mechanism based on cooperative game theory. All prosumers first submit the
parameters associated with both electricity and data to the market operator.
The operator utilizes the public and prosumers' private data to forecast the
distributed renewable generators (DRGs) and quantify the improvement driven by
prosumers' private data in terms of reduced uncertainty set. Then, the operator
maximizes the grand coalition's total payoff considering the uncertain
generation of DRGs and imputes the payoff to each prosumer based on their
contribution to electricity and data sharing. The mathematical formulation of
the grand coalition is developed and converted into a second order cone
programming problem by using an affinepolicy based robust approach. The
stability of such a grand coalition is mathematically proved, i.e., all
prosumers are willing to cooperate. Furthermore, to address the scalability
challenge of existing payoff imputation methods in the cooperative game, a two
stage optimization based approach is proposed, which is converted into a mixed
integer second order cone programming and solved by the Benders decomposition.
Case studies illustrate all prosumers are motivated to trade electricity and
data under the joint trading framework and the proposed imputation method
significantly enhances the scalability.
