Day-ahead promised load as alternative to real-time pricing

Real-time pricing (RTP) enables different grid parties to benefit from a continuous flow of information, usually suggesting the transfer of original or modified whole-sale market prices to the end-user. The closed-loop nature of RTP makes it vulnerable to both instability and unreliability, due to issues such as inadvertent time delays, fluctuating prices, and cyber attacks. In this paper, we present an alternative mechanism to avoid destabilization and improve demand-prediction. The former is achieved with preventing the end-user from a direct interaction with the whole-sale market, while the latter is addressed by the concept of a day-ahead promised load. We show mixed-integer linear programming (MILP) formulation of the proposed method, both for the optimization phase required to generate the promised load and for the real-time operation of the end-user energy systems, which results in a low computation time for the optimization process. The performance of the proposed method is investigated based on the measurements from a commercial building.