Power system controller tuning considering stochastic variations

Electrical power systems are vulnerable to external disturbances, such as short circuits, that can lead to damage on the equipments and even blackouts. In order to improve the system response to external disturbances, the generators of the power system are equipped with automatic controllers devised to maintain the generators working on a constant operating condition. The tuning of the controllers is performed assuming the system loads do not have time-dependent variations, but such assumption is not realistic as the power system loads are stochastically changing due to the switching on and o of every device (PCs, TVs, cellphones, etc.) connected to it. This work proposes two new methods for the tuning of the generator controllers which takes into account the stochastic nature of the system loads. More speci cally, this work proposes two new methods for the tuning of the governors and AVRs of the power system generators: one focused on the steady state response and the other focused on the fault response. First, the system response as a function of the controller parameters is calculated. As the power system is under the e ect of stochastic loads, the resulting system response is stochastic. Then, a stochastic objective function which measures the quality of the system response is de ned. Each tuning method uses a di erent objective function. Finally, the objective function is optimized using the metaheuristic Cuckoo Search, which is used for global optimization problems and can be used to optimize stochastic functions. The method was tested in di erent benchmark systems showing better system responses