Power Balance Control using Evolutionary Algorithm

J. Novk, P. Chalupa, and V. Bobl (Czech Republic)


Optimization techniques, evolutionary algorithms, power system stability and control, ancillary services


Modern electric power systems are large-scale systems with a complex structure comprised of interconnected networks. The balance between the generation and consumption of electricity has to be maintained at any moment. Transmission System Operator (TSO) is responsible for keeping the domestic power balance. Power reserves used to control this balance are called "ancillary services". These services are performed both by automatic control and human operator. The task of the operator is to activate proper services and their amounts. A nonlinear optimization problem is formulated that enables the ISO to make least-cost decisions for activation of ancillary services. In this contribution the optimization problem is solved via the Self-Organizing Migration Algorithm (SOMA) which belongs to the class of evolutionary algorithms. This algorithm is based on the competitive-cooperative behaviour of intelligent creatures solving a common problem. Optimization of ancillary services via SOMA is tested on two scenarios that are based on real values obtained from the Czech TSO.

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