Enabling a Transactive Distribution System via Real-Time Distributed Optimization

Increasing penetration of distributed generators and flexible loads in a distribution power system triggers the need for transactive mechanisms. This paper proposes a transactive mechanism and model that allow noncontrollable resources to trade their power deviations from schedules with elastic ones. The proposed mechanism can reveal the cost of uncertainty and the scarcity of flexibility. The proposed model is optimized in a fully distributed manner in which the welfare of each prosumer is maximized individually through information exchange between neighbors. A distributed neurodynamic algorithm is applied to handle the global constraints on supply-demand balance and limits on branch flows and voltages with guaranteed optimality and fast convergence. A case is studied on a 118-bus distribution system to demonstrate the effectiveness and efficiency of the proposed approach.