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SLIDING MODE CONTROL OF CONVERTERS WITH AN INDEPENDENT NEUTRAL POINT
Title
SLIDING MODE CONTROL OF CONVERTERS WITH AN INDEPENDENT NEUTRAL POINT
Creator
Ghosh, Somsubhra
Date
2017, 2017-07
Description
With the increasing footprint of renewable energy, the drive towards a cleaner environment has consistently pushed forward the development of...
Show moreWith the increasing footprint of renewable energy, the drive towards a cleaner environment has consistently pushed forward the development of power electronics based power converters. While the basic principles of operating the power electronics in these power converters have been very effective in providing for a very efficient system, new topologies and advanced control strategies enable us to achieve a still higher efficiency, simplification and help us overcome some of the fundamental problems encountered in operation. One of the fundamental requirements of the power electronic converters is that they require a significantly large output capacitors. it is necessary to remove ripples in the rectified AC voltage. Numerous approaches have been presented in the past to overcome these issues including the addition of a ripple compensator to a conventional H-Bridge rectifier as well as using one leg of the H-Bridge itself as a neutral leg. A new controller; based on sliding mode has been proposed here to a neutral leg topology as well as the conventional H-Bridge topology of a single-phase power converter. In case of a rectifier, the ripple energy is separated and directed towards the lower split capacitor present at the neutral leg so that the upper split capacitor may have very small ripples while in case of an inverter the lower capacitor actually acts as an independently controlled DC source. all the while the capacitance is kept to be very small. The control of the two legs in the rectifier is performed independently granting the controller an extra degree of freedom and an easier extrapolation to the 3-phase implementation. The controller operates the power electronic switches to regulate the input grid current and achieve unity power factor as well as to maintain a stable DC bus voltage removing the need for any other power factor correction circuit.
M.S. in Electrical Engineering, July 2017
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SEQUENTIAL MONTE CARLO METHODS FOR PARAMETER ESTIMATION, DYNAMIC STATE ESTIMATION AND CONTROL IN POWER SYSTEMS
Title
SEQUENTIAL MONTE CARLO METHODS FOR PARAMETER ESTIMATION, DYNAMIC STATE ESTIMATION AND CONTROL IN POWER SYSTEMS
Creator
Maldonado, Daniel Adrian
Date
2017, 2017-05
Description
The estimation, operation and control of electrical power systems have always contained a degree of uncertainty. It is expected that, with the...
Show moreThe estimation, operation and control of electrical power systems have always contained a degree of uncertainty. It is expected that, with the introduction of technologies such as distributed generation and demand-side management, the ability of system operators to forecast the dynamic behavior of the system will deteriorate and as a result, the cost of keeping the system together will increase. Sequential Monte Carlo or Particle Filtering is a family of algorithms to efficiently perform inference in non-linear dynamic systems by exploiting their structure without assuming any linearity or normality structure. In this thesis we provide two novel ways of employing these algorithms for inference and control of power systems. First, we motivate the use Bayesian statistics in load modelling by introducing a novel statistical model to capture the aggregated response of a set of loads. We then use the model to characterize load with measurement data and prior information using the Sequential Monte Carlo algorithm. Second, we introduce the Model Predictive Control for power system stabilization. We present the use of the Sequential Monte Carlo algorithm as a way of solving the stochastic Model Predictive Control problem and we compare its performance to existing regulators. In addition, Model Predictive Control is applied to load shedding Finally, we test the performance of the algorithm in a large power system scenario.
Ph.D. in Electrical Engineering, May 2017
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