A robust hybrid fuzzy–simulated annealing–intelligent water drops approach for tuning a distribution static compensator nonlinear controller in a distribution system. Issue 6 (2nd June 2016)

• Record Type: Journal Article
• Authors: Bagheri Tolabi, Hajar; Hosseini, Rahil; Shakarami, Mahmoud Reza
• Is Part Of: Engineering optimization. Volume 48:Issue 6(2016)
• Page Start: 999
• Page End: 1018
• Publication Date: 2016-06-02
• Subjects: DSTATCOM -- fuzzy sets -- optimization -- partial feedback linearizing controller; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2015.1080579
• Languages: English
• ISSNs: 0305-215X

Abstract

Abstract : This article presents a novel hybrid optimization approach for a nonlinear controller of a distribution static compensator (DSTATCOM). The DSTATCOM is connected to a distribution system with the distributed generation units. The nonlinear control is based on partial feedback linearization. Two proportional-integral-derivative (PID) controllers regulate the voltage and track the output in this control system. In the conventional scheme, the trial-and-error method is used to determine the PID controller coefficients. This article uses a combination of a fuzzy system, simulated annealing (SA) and intelligent water drops (IWD) algorithms to optimize the parameters of the controllers. The obtained results reveal that the response of the optimized controlled system is effectively improved by finding a high-quality solution. The results confirm that using the tuning method based on the fuzzy-SA-IWD can significantly decrease the settling and rising times, the maximum overshoot and the steady-state error of the voltage step response of the DSTATCOM. The proposed hybrid tuning method for the partial feedback linearizing (PFL) controller achieved better regulation of the direct current voltage for the capacitor within the DSTATCOM. Furthermore, in the event of a fault the proposed controller tuned by the fuzzy-SA-IWD method showed better performance than the conventional controller or the PFL controller without optimization by the fuzzy-SA-IWD method with regard to both fault duration and clearing times.