Optimization of power flow with energy storage using genetic algorithms

This paper applies genetic algorithms to optimize the operation of a transmission network with energy storage capabilities, to optimize its costs, which include both generation and storage costs, for cases when the data inherent to the system is assumed to be perfectly known. The problem is formulated through the DC optimal power flow equations, including losses across the transmission lines, therefore allowing solutions regarding the network generation costs to be obtained, with and without storage. In this way, the financial impact inherent to the usage of energy storage can be derived. Since we are dealing with a large combinatorial problem, the search throughout the solution space was done by means of the Genetic Algorithms. The solutions consist of the storage device's charging or discharging rate at which it must be operating during each sub-interval considered for the simulations. The results delivered by the GA have proven the profitability of including energy storage capabilities in the transmission network of São Miguel (Portugal) and the usefulness of such algorithm in a real world application.

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