Stability Constrained Optimal Power Flow in a Practical Balancing Market

Abstract

Stability constrained optimal power flow (SCOPF) has become increasingly important in modern power systems operation. The work presented in this paper describes a genetic algorithm (GA) based approach for tackling the SCOPF problem emerging in the UK electricity balancing market. The SCOPF problem is defined as optimizing the generation combination of balancing mechanism (BM) units to maintain the balance of generation and demand in the system subject to the physical limits of the BM units and the removal of stability constraints imposed by credible contingencies. Generation output levels of BM units, as the control variables for the solution to the problem, were put in the GA chromosomes. A properly constructed GA, employing feasible plane mapping of the genome, is used to determine the optimal generation combination. The proposed approach was tested on a reduced UK transmission system model with multiple contingencies taken into account at the same time. The simulation results demonstrate that the GA is capable of finding the optimal or sub-optimal solution based on which the power system being operated is absolutely stable against the specified contingencies. Numerical simulation results are presented.