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A novel two stage multi-objective control strategy for optimal voltage unbalance compensation in low voltage microgrid systems consisting of inverter interfaced distributed generators (IIDGs) has been presented in this research. To ensure continuous and safe operation of the IIDGs during unbalanced voltage sags, the proposed control strategy supplies the optimal positive sequence voltage support and performs voltage unbalance compensation considering the current limitation of the inverters. The control strategy also ensures that the DGs deliver maximum allowable active power during voltage sag. The positive and negative sequence quantities of the IIDGs are controlled in such a way so that these objectives can be achieved simultaneously. The DGs are operated in coordination with each other to maintain the voltage profile as desired by the grid operator. Prioritisation of active power and unbalance compensation can be set depending upon the requirement of the customer. Under severe grid imbalance condition, the proposed technique can raise the positive sequence voltage to near nominal value from below 0.9 per unit maintaining all phase currents of DGs within safety limit.To solve the optimization problem and to generate the optimal references for the DG control unit, artificial cooperative search algorithm has been utilised. The two stage control strategy includes a local control for each DG, which coordinates with the central control to provide the optimal references for all the DGs. The multi-objective control strategy has been tested under different operating conditions and implemented in real time digital simulator to ensure the robustness and effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

• Detection and classification of faults including high impedance faults in microgrid. • Fault detection and classification from current signals at the substation. • Faulty feeder and sub-feeder identification within half cycle of post fault current signal. • Wavelet based power spectral density of current signals utilized to detect and classify fault and also identify faulty feeder. • Performance of the proposed algorithm verified under dynamic and challenging situations. The recent progress in the area of microgrid protection has led to the application of data-driven and signal processing techniques for fault detection in microgrids. The deployment of inverter interfaced distributed generators makes the traditional protection schemes ineffective. In this paper a wavelet based power spectral density (PSD) has been utilized to detect fault, identify faulty phases and locate fault in the microgrid. Wavelet based PSD decouples the frequency information from the time information and it is the optimal technique to reveal the change of distribution of harmonics in non-stationary faulty signals as for fault analysis it can consider the faulty frequency band instead of one particular harmonic. The proposed technique can detect fault and identify faulty phases by analyzing current signals from the substation only. The normalized value of PSD of three phase current signals has been considered for fault detection and probabilistic distribution of PSD has been considered for faulty phase identification. The normalized value of PSD of the current signals collected from both ends of the main feeders and one end of the non-DG sub-feeder have been used to locate the faulty feeder and sub-feeder. Appropriate threshold values have been considered to detect fault and to locate the faulty feeder. To locate faults, the technique does not require synchronized signals and thus provides a promising and economical solution for inverter interfaced microgrid. It does not require huge amount of data set for training and testing as it is essentially a threshold based technique and also does not require collection of data at high sampling rate. The proposed scheme has been extensively tested for high impedance fault (HIF), unbalanced loading, load switching, variation of DG parameters, measurement uncertainty and presence of noise in the signal with signal to noise ratio up to 10 dB. This technique provides accurate results for fault resistance from 0 Ω to 300 Ω and up to 10% measurement error. The performance of the proposed technique has been verified for feeder length variation up to 20%. Half cycle of current signal only after fault is required and three levels of wavelet decomposition has been considered. The simulation results and comparative assessment demonstrate the efficacy of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper presents an optimal cascaded three degree of freedom proportional integral (3DOF PI) controller and compares its performance with conventional proportional integral (PI) controller for load frequency control of two area deregulated power system. The 3DOF PI controller enhances the degree of freedom and gives better dynamic response. Genetic algorithm (GA) is used to get the optimal gains of the proposed controllers. In the considered two area thermal-gas-fuel cell system, the thermal system consists of a reheat turbine with appropriate generation rate constraint non linearity. Battery storage and unified power flow controller (UPFC) are also assumed to be present. The performance of the proposed controllers is evaluated under different operating conditions that take place in deregulated power market. To tackle any contract violation this article emphasizes on the ancillary services provided by electric vehicles (EVs) and distributed generations. A robustness analysis is also presented by varying parameters from their nominal values. [ABSTRACT FROM AUTHOR]