Genetic algorithms for optimal reactive power compensation on the national grid system

This work proposes an Integer-coded, multiobjective Genetic Algorithm (IGA) applied to the full Reactive-power Compensation Planning (RCP) problem considering both intact and contingent operating states. The IGA is used to simultaneously solve both the siting problem-optimization of the installation of new devices-and the operational problem-optimization of preventive transformer taps and the controller characteristics of dynamic compensation devices. The aim is to produce an optimal siting plan that does not violate any system or operational constraint and is optimal in terms of the voltage deviation from the ideal and the cost incurred through the installation and use of reactive power compensation devices. This multiobjective problem is solved through the use of Pareto optimality. The developed algorithm is tested on the IEEE 30-bus system and on a reduced practical system that was developed with the cooperation of the National Grid. The algorithm is validated via the comparison with the SCORPION software package, which is a Linear Programming-based (LP) planning tool developed and used by the National Grid for the England and Wales transmission system. This work demonstrates that the IGA is superior to the LP-based method, both in terms of system conditions and installation and utilization cost when fixed and dynamic compensation devices are being sited; the system performance is optimized via the adjustment of tap settings and controller characteristic across multiple operating states.