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Model Predictive Primary Control of Standalone Mixed Micro-grids
October 31, 2019 @ 3:00 pm - 4:00 pm
Date & Time : Thursday, 31 October 2019 at 03.00 p.m.
Venue: ESB 244
Name of Scholar: Puvvula SRVRSS Vidyasagar (EE14D030)
Guide: Dr. K. Shanti Swarup
Primary control of standalone micro-grids accounts for power-sharing among different DG units for various load conditions, keeping the bus voltages and system frequency within limits and their restoration during load disturbances. Model predictive controller (MPC) is one of the advanced controllers that is gaining importance as a primary controller for standalone micro-grids. The reasons for its focus are, it performs online optimization, handles the system constraints and nonlinearity well, considers the predicted behavior of the system while taking the control actions. The existing MPC designs in standalone micro-grid control are decentralized in nature with small prediction horizons and are intended for inverter micro-grids. When it comes to mixed micro-grids with both inverter DG’s and conventional synchronous DG’s, these designs lead to slow response and oscillatory behavior. Since the mixed micro-grid model is nonlinear, a centralized MPC design with a large prediction horizon leads to a non-convex nonlinear optimal control problem at each sample, which is challenging to solve online. In this talk, a centralized MPC design based on linear time-invariant and linear time-variant approximations of the nonlinear micro-grid model will be discussed. The discussion covers the MPC formulation with both conventional pulse operators and orthonormal Laguerre networks. The performance of the proposed MPC in an eight bus standalone micro-grid with one synchronous DG and one photovoltaic DG will be discussed for the load disturbance and source intermittency scenarios.