This research paper presents a rate of change of frequency (RoCoF) implementation using low-cost hardware in the loop (HIL) with application to Nordic Power System (NPS). Two methods to calculate the RoCoF are presented: Incremental difference one step and Moving window (MW) or rolling window. HIL) approach is used to obtain natural noise found in the frequency signal obtained from real power devices. The low-cost HIL implementation is based on two Arduinos ® in the loop. An Arduino ® working as standalone is used to generate an analogue signal representative of one area of the NPS, a second Arduino ® in the loop contains the RoCoF calculation methods and filters. As the noise is essential affecting the RoCoF calculation, this paper analyses the effect of including lowpass filters (LPFs). Three cases are analysed: Base Case: no filter and noise signal, Case I: LPF applied to the input frequency signal, Case II: LPF at the frequency signal and LFP at the output of the RoCoF (smoothing). Results demonstrate that RoCoF calculation methods worked correctly in the HIL and using two LPFs clean the signal from the noise produced by the Arduino ® .

This research paper proposes a framework to perform (hardware in the loop) HIL simulation in real-time (RT), the framework includes steps for the formulation of the Target RT Computer and Open Source System, which are important elements in RT modelling. In order to carry out tests, the implementation of the frequency response of a single area electric power system, including primary frequency control, is proposed. The electric power system was prepared to be implemented in the RT-Lab software that is compatible with MATLAB Simulink, in order to simulate in real-time with the Opal OP4510 device. Besides, the controller was designed in Simulink to be able to implement through the Arduino programming platform; they were also connected to work in HIL in RT. The results of the simulation and performance analysis show that for the case proposed with HIL, the primary control happens within a few seconds of the frequency variation. The control helps to reestablish the balance between the generated power and power demanded, thus stabilizing the system frequency. Elements formulated using this framework were successfully used in the primary frequency control.

This research paper proposes a turbine-governor modelling technique based on equivalent FCM (Fuzzy C-Means) for a control area of an equivalent power system used for frequency response analysis. The FCM algorithm implementation is proposed to find an equivalent Fuzzy model of n turbine-governors that are in an area of the electric power system (EPS). The FCM algorithm is mainly used to generate the rules for the fuzzy model;