Decentralised coordination of power system operation using dual evolutionary programming

This paper proposes a decentralised coordination framework for operating power systems with dispersed generation and energy storage. It then develops a novel decentralised approach for calculating the system optimal operation of resources with intertemporal links. The method combines elements of dynamic programming with evolutionary programming. Each power system resource evolves a ´future benefit´ function that describes the impact of its own possible decisions on future power system operation. This ´dual evolutionary programming´ approach can handle complex resource models and objective functions. It is shown to be computationally faster than discrete dynamic programming for a number of power system problems with multiple storage resources