Renewable energy-based energy conversion technologies have become more relevant due to environmental considerations even though they are intermittent in nature. As a result, the concept of microgrid and microgrid control techniques have been evolved as major areas of power system research. Among different inverter control methods, the droopbased control method is more popular in microgrid systems due to its simplicity and non-requirement of expensive communication systems. The transient performance, power-sharing accuracy and decoupling between real and reactive power are improved by modifying the natural droop control method. In this study, the selected microgrid system consists of two inverters operating in parallel, two interconnecting lines and three loads. A state-space model of the microgrid is created based on the small-signal stability and the transient response is improved by introducing virtual impedance and dynamic droop gains. The different controller parameters are optimised using particle swarm optimisation ensuring stability. Eigenvalue analysis is done to analyse stability. The analysis of the response of the system for various disturbances validates the effectiveness of the proposed controller. The strategy developed ensures improved power-sharing capability with high values of natural droop gains without compromising stability by using optimised dynamic droop gains.
Energy storage systems have established their capability to overcome the problems caused by intermittent nature of renewable sources when integrated to existing grid. Voltage and frequency control, as well as load shifting can be done using grid level storage systems incorporated with renewable sources. They can effectively serve the system as an energy sink and source. Operational use of energy storage for grid level support of a wind electric generator (WEG) is demonstrated in this study. The battery storage supported WEG along with controllers is modelled. Artificial neural network controller, which is having inherent learning capability, is developed to regulate the power flow between wind generator and utility grid. The proposed algorithm and the corresponding controller are simulated in MATLAB/Simulink and implemented in the DSP processor. The real time data exchange between Simulink and the floating point DSP processor TMSF32028335 is realised using on-board JTAG emulator. The hardware implementation using DSP processor presented in this work establishes the efficacy of the proposed control strategy for real time applications.
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