• N.Vani Annapurna Bhavani

Gain scheduling has proven to be a successful design methodology in many engineering applications. The idea is to construct a global feedback control system for a time-varying and/or nonlinear plant from a collection of local linear time-invariant designs. However, in the absence of a sound analysis, these designs come with no guarantees on the robustness, performance, or even nominal stability of the overall gain scheduled design. We present such an analysis for one type of gain scheduled system, namely, a linear parameter-varying plant scheduling on its exogenous parameters. This class of systems are important since it can be shown that gain scheduled control of nonlinear plants takes the form of a linear parameter-varying plant where the parameter is actually a reference trajectory or some endogenous signal such as the plant output.Local and distributed power generation is increasingly reliant on renewable power sources, e.g., solar (photovoltaic or PV) and wind energy. The integration of such sources into the power grid is challenging, however, due to their variable and intermittent energy output. To effectively use them on a large scale, it is essential to be able to predict power generation at a fine grained level. We describe a novel Bayesian ensemble methodology involving three diverse predictors. Each predictor estimates mixing coefficients for integrating PV generation output profiles but captures fundamentally different characteristics.Therefore, we added another energy storage unit and adopted gain-scheduling control technique as the droop controls for sharing the outputs. Here, we used a new voltage control method that combines fuzzy control with gain-scheduling control technique in order to accomplish both power sharing and energy management simultaneously. In this paper, electric-double-layer capacitors (EDLC) were used as the energy storage unit, and each dc/dc converter of EDLC controlled the dc distribution voltage when the system was operated under an intentional islanding mode. The simulation results demonstrate the effectiveness of the proposed adaptive GS-PID and show that this approach can achieve a good maximum power operation under any conditions such as different levels of solar radiation and PV cell temperature for varying PV sources.

Photovoltaic Energy Conversion System (PECS); Voltage Sourced Inverter (VSI),DC power systems,gain-scheduling control.

"Gain Scheduling Technique and Distribution Voltage Control for DC-Microgrids", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 12, page no.110-115, December-2017, Available :http://www.jetir.org/papers/JETIR1712024.pdf

"Gain Scheduling Technique and Distribution Voltage Control for DC-Microgrids", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 12, page no. pp110-115, December-2017, Available at : http://www.jetir.org/papers/JETIR1712024.pdf