The expansion of renewable energy is continuing powerfully. Electrical system ought to transmit power with diminished loss, improved power quality, and reliability while pleasing the need of customer’s load demand. Nevertheless, owing to the exhaustion of fossil fuels and their environmental impact, the availability of quality, stable, and reliable power in developing countries is worrying. Integrating a solar-wind based microgrid to the distribution network is the more feasible and best alternative solution to gratify the customer intensifying power demand while seeing the strict environmental regulations of generating power. However, the microgrid system connected in a distribution network has diverse problems and challenges. The problems comprise the development of voltage sag and swell, voltage unbalance, and power losses because of the intermittent nature of PV and wind resources. The objective of this study is to integrate microgrid system with STATCOM (static synchronous compensator) controller to ensure the higher power flow with enhanced voltage profile and reduced power loss. MATLAB/PSAT is used to model microgrid and STATCOM controller connected to the grid. Proportional integral (PI) and fuzzy logic controllers (FLC) are also applied to control the STATCOM. The effectiveness of STATCOM with microgrid integration is tested by connecting to the main distribution system using standard IEEE 30-bus system. Finally, it was observed that STATCOM raises the capacity of the distribution line and contributes to voltage profile improvements and power loss reduction.

Use of wind power as one of renewable resources of energy has been growing quickly all over the world. Wind power generation is significantly vacillating due to the wind speed alteration. Therefore, assessment of the output power of this type of generators is always associated with some uncertainties. A precise wind power prediction aims to support the operation of large power systems or microgrids in the scope of the intraday resources scheduling model, namely with a time horizon of 5-10 minutes, and this can efficiently uphold transmission and distribution system operators to improve the power network control and management. A Shortterm ANN based wind power prediction model, for day-ahead energy management and scheduling in microgrids, is developed utilizing a real database of 12 months with 10 minutes time interval data from measured information of online supervisory control and data acquisition (SCADA) of Goldwind microgrid wind turbine system (Beijing, China) as well as Numerical Weather Prediction (NWP). The ANN predicted wind power has been compared with the actual power of Goldwind wind turbine system. The predicted wind power has shown acceptable agreement with the actual power output that has been recorded by the SCADA which confirms the robustness and accuracy of the ANN wind power forecasting model developed in this research paper.

This paper presents the design and analysis of a high performance robust controller for the Stewart platform manipulator. The controller is a variable structure controller that uses a linear sliding surface which is designed to drive both tracking and synchronization errors to zero. In the controller the model based equivalent control part of the sliding mode controller is computed in task space and the discontinuous switching controller part is computed in joint space and hence it is a hybrid of the two approaches. The hybrid implementation helps to reduce computation time and to achieve high performance in task space without the need to measure or estimate 6DOF task space positions. Effect of actuator friction, backlash and parameter variation due to loading have been studied and simulation results confirmed that the controller is robust and achieves better tracking accuracy than other types of sliding mode controllers and simple PID controller.

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