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This paper considers the economic dispatch problem for a network of powergenerating units communicating over a strongly connected, weight-balanceddigraph. The collective aim is to meet a power demand while respectingindividual generator constraints and minimizing the total generation cost. Wedesign a distributed coordination algorithm consisting of two interconnecteddynamical systems. One block uses dynamic average consensus to estimate theevolving mismatch in load satisfaction given the generation levels of theunits. The other block adjusts the generation levels based on the optimizationobjective and the estimate of the load mismatch. Our convergence analysis showsthat the resulting strategy provably converges to the solution of the dispatchproblem starting from any initial power allocation, and therefore does notrequire any specific procedure for initialization. We also characterize thealgorithm robustness properties against the addition and deletion of units(capturing scenarios with intermittent power generation) and its ability totrack time-varying loads. Our technical approach employs a novel refinement ofthe LaSalle Invariance Principle for differential inclusions, that we alsoestablish and is of independent interest. Several simulations illustrate ourresults.

Initialization-free distributed coordination for economic dispatch under varying loads and generator commitment