The stability of the control grid is a critical prerequisite for a safe and efficient power system service. A thorough knowledge of the effects of the power system volatility is essential for the effective study and control of power systems. This paper presents the simulation outcome of a multimachine power network implemented by a wind farm (WF) utilizing a static synchronous compensator (STATCOM) for better stability control objectives. A similarly aggregated double-fed induction generator (DFIG) powered by a gearbox analogy with an equally aggregated wind turbine (WT) determines the operating output of the wind farm. A proportional–integral–derivative controller (PID)-based damping controller, PID including Fuzzy Logic Controller (FLC), and an adaptive network-based fuzzy inference system (ANFIS) controller of the proposed SATCOM are intended to add sufficient damping properties to the dominating modes of the examined system during diverse working circumstances. To assess the feasibility of the suggested control schemes, a frequency-domain method concentrated on a linearized mathematical structure layout utilizing a time-domain strategy centered on a nonlinear configuration of the device that is subjected to severe fault on the attached bus was carried out consistently. A STATCOM damping controller is configured using the ANFIS method to apply appropriate damping properties to the device’s decisive modes being evaluated under various test conditions. From the findings of the comparative simulation, it can be inferred that the suggested STATCOM along with the planned ANFIS is seen as comparable to STATCOM with PID and STATCOM with PID plus FLC to increase the stability of the studied device.
A novel feature selection method based on a decision tree (J48) for price forecasting is proposed in this work. The method uses a genetic algorithm along with a decision tree classifier to obtain the minimum number of features giving an optimum forecast accuracy. The usefulness of the proposed approach is established through the performance test of the forecaster using the feature selected by this approach. It is found that the forecast with the selected feature consistently out-performed than that having larger feature set.
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