A novel consensus-oriented distributed optimization scheme with convergence analysis for economic dispatch over directed communication graphs

This paper investigates a novel distributed optimization scheme for the economic dispatch problem of distributed generators (DGs) connected via directed communication links. The optimization is carried out using incremental cost (IC) consensus under the constraint of supply–demand balance while considering the capacity and ramp rate limits of the DGs. The optimality analysis has been provided via a variant of the conventional Lyapunov function for an additional term, addressing both consensus of ICs and convergence of supply–demand mismatch on directed graphs. In contrast with the previous work, the proposed algorithm is not susceptible to initial conditions of DGs, which makes it more resilient to communication failure and delay despite working under directed communication topologies. Extra limitations of capacity and ramp rate limits of DGs are taken into account by the algorithm while avoiding any supply mismatch. The simulation tests are carried on an IEEE benchmark to verify the efficacy of the proposed technique. The results indicate that the proposed technique is superior to existing traditional and distributed methods in various performance aspects.