Stability constrained optimal power flow for the balancing market using genetic algorithms

Angle stability (both transient and oscillatory) is an important constraint in power system operation. The work presented in this paper describes a genetic algorithm (GA) based approach for solving the problem of angle stability constrained optimal power flow. The control parameter modeled in the chromosome of the GA is generation power of the units. The application presented here is the UK balancing market using Balancing Mechanism Units (BMUs). The BMUs put into the GA list depend on either their bid/offer price or their impact of generation change on system stability. Sensitivity factors, obtained by doing perturbations, are used to represent a BMU's impact on system stability. A novel mapping method is employed to maintain power balance. Stability constraints are dealt with as penalty cost, and their contribution to the fitness of the objective function is evaluated independently, so that the search for the optimal solution concentrates on feasible solutions. Tests on a reduced UK system show that the proposed GA is able to cope with the highly non-linear optimization problem. Numerical simulation results of the test system are presented.