Power quality improving with virtual flux-based voltage source line converter

Line converters have become an attractive AC/DC power conversion solution in industrial applications. Line converters are based on controllable semiconductor switches, typically insulated gate bipolar transistors. Compared to the traditional diode bridge-based power converters line converters have many advantageous characteristics, including bidirectional power flow, controllable de-link voltage and power factor and sinusoidal line current. This thesis considers the control of the lineconverter and its application to power quality improving. The line converter control system studied is based on the virtual flux linkage orientation and the direct torque control (DTC) principle. A new DTC-based current control scheme is introduced and analyzed. The overmodulation characteristics of the DTC converter are considered and an analytical equation for the maximum modulation index is derived. The integration of the active filtering features to the line converter isconsidered. Three different active filtering methods are implemented. A frequency-domain method, which is based on selective harmonic sequence elimination, anda time-domain method, which is effective in a wider frequency band, are used inharmonic current compensation. Also, a voltage feedback active filtering method, which mitigates harmonic sequences of the grid voltage, is implemented. The frequency-domain and the voltage feedback active filtering control systems are analyzed and controllers are designed. The designs are verified with practical measurements. The performance and the characteristics of the implemented active filtering methods are compared and the effect of the L- and the LCL-type line filteris discussed. The importance of the correct grid impedance estimate in the voltage feedback active filter control system is discussed and a new measurement-based method to obtain it is proposed. Also, a power conditioning system (PCS) application of the line converter is considered. A new method for correcting the voltage unbalance of the PCS-fed island network is proposed and experimentally validated.

Distributed ControlArchitecture of Power Electronics Building-Block-Based Frequency Converters

The increasing power demand and emerging applications drive the design of electrical power converters into modularization. Despite the wide use of modularized power stage structures, the control schemes that are used are often traditional, in other words, centralized. The flexibility and re-usability of these controllers are typically poor. With a dedicated distributed control scheme, the flexibility and re-usability of the system parts, building blocks, can be increased. Only a few distributed control schemes have been introduced for this purpose, but their breakthrough has not yet taken place. A demand for the further development offlexible control schemes for building-block-based applications clearly exists. The control topology, communication, synchronization, and functionality allocationaspects of building-block-based converters are studied in this doctoral thesis. A distributed control scheme that can be easily adapted to building-block-based power converter designs is developed. The example applications are a parallel and series connection of building blocks. The building block that is used in the implementations of both the applications is a commercial off-the-shelf two-level three-phase frequency converter with a custom-designed controller card. The major challenge with the parallel connection of power stages is the synchronization of the building blocks. The effect of synchronization accuracy on the system performance is studied. The functionality allocation and control scheme design are challenging in the seriesconnected multilevel converters, mainly because of the large number of modules. Various multilevel modulation schemes are analyzed with respect to the implementation, and this information is used to develop a flexible control scheme for modular multilevel inverters.

Modeling and Control of the Power Conversion Unit in a Solid Oxide Fuel Cell Environment

In this doctoral thesis, a power conversion unit for a 10 kWsolid oxide fuel cell is modeled, and a suitable control system is designed. The need for research was identified based on an observation that there was no information available about the characteristics of the solid oxide fuel cell from the perspective of power electronics and the control system, and suitable control methods had not previously been studied in the literature. In addition, because of the digital implementation of the control system, the inherent characteristics of the digital system had to be taken into account in the characteristics of the solid oxide fuel cell (SOFC). The characteristics of the solid oxide fuel cell as well the methods for the modeling and control of the DC/DC converter and the grid converter are studied by a literature survey. Based on the survey, the characteristics of the SOFC as an electrical power source are identified, and a solution to the interfacing of the SOFC in distributed generation is proposed. A mathematical model of the power conversion unit is provided, and the control design for the DC/DC converter and the grid converter is made based on the proposed interfacing solution. The limit cycling phenomenon is identified as a source of low-frequency current ripple, which is found to be insignificant when connected to a grid-tied converter. A method to mitigate a second harmonic originating from the grid interface is proposed, and practical considerations of the operation with the solid oxide fuel cell plant are presented. At the theoretical level, the thesis discusses and summarizes the methods to successfully derive a model for a DC/DC converter, a grid converter, and a power conversion unit. The results of this doctoral thesis can also be used in other applications, and the models and methods can be adopted to similar applications such as photovoltaic systems. When comparing the results with the objectives of the doctoral thesis, we may conclude that the objectives set for the work are met. In this doctoral thesis, theoretical and practical guidelines are presented for the successful control design to connect a SOFC-based distributed generation plant to the utility grid.

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

An approach of optimal sensitivity applied in the tertiary loop of the automatic generation control

This paper proposes an approach of optimal sensitivity applied in the tertiary loop of the automatic generation control. The approach is based on the theorem of non-linear perturbation. From an optimal operation point obtained by an optimal power flow a new optimal operation point is directly determined after a perturbation, i.e., without the necessity of an iterative process. This new optimal operation point satisfies the constraints of the problem for small perturbation in the loads. The participation factors and the voltage set point of the automatic voltage regulators (AVR) of the generators are determined by the technique of optimal sensitivity, considering the effects of the active power losses minimization and the network constraints. The participation factors and voltage set point of the generators are supplied directly to a computational program of dynamic simulation of the automatic generation control, named by power sensitivity mode. Test results are presented to show the good performance of this approach. (C) 2008 Elsevier B.V. All rights reserved.

A new three-phase low THD power supply with high-frequency isolation and 60V/200A regulated DC output

This work proposes a new isolated high power factor 12kW power supply based on an 18-pulse transformer arrangement. Three full-bridge converters are used for isolation and to balance the DC-link currents, without current sensing or a current controller. The topology provides a regulated DC output with a very simple control strategy. Simulation and experimental results are presented in this paper.

Robust control applied to power flow control in single-phase inverter with LCL filter, using droop control and D-stability

This paper proposes a new methodology to control the power flow between a distributed generator (DG) and the electrical power distribution grid. It is used the droop voltage control to manage the active and reactive power. Through this control a sinusoidal voltage reference is generated to be tracked by voltage loop and this loop generates the current reference for the current loop. The proposed control introduces feed-forward states improving the control performance in order to obtain high quality for the current injected to the grid. The controllers were obtained through the linear matrix inequalities (LMI) using the D-stability analysis to allocate the closed-loop controller poles. Therefore, the results show quick transient response with low oscillations. Thus, this paper presents the proposed control technique, the main simulation results and a prototype with 1000VA was developed in the laboratory in order to demonstrate the feasibility of the proposed control. © 2012 IEEE.

Decoupled reference generator for shunt active filters using the conservative power theory

Based on the framework of the Conservative Power Theory (CPT), this paper proposes some compensation strategies for shunt current compensators. CPT current decompositions result in several current-related terms associated with specific load characteristics, such as power consumption, energy storage, unbalances and load nonlinearities. These current components are decoupled (orthogonal) from each other and are used here to define different compensation strategies, which can be selective in minimizing particular effects of disturbing loads. Compensation strategies for single- and three-phase four-wire circuits are also considered. Simulated and experimental results are described to validate the possibilities and performance of the proposed strategies. © 2013 Brazilian Society for Automatics - SBA.

Multi-task control strategy for grid-tied inverters based on conservative power theory

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

DC-DC Power Converters Featuring Wide-Bandgap Devices

This work focuses on the design of high-efficient DC-DC converters based on WBG power devices. The first objective is the development of an isolated bidirectional converter for the distribution network of future electrical aircrafts. A SiC-based Dual Active Bridge converter is designed and fabricated. Control strategies for individual and parallel operations are investigated and implemented into a FPGA platform. Experimental results on 1.2kW 270V/28V prototype are presented to confirm the proper behavior of the proposed solution. The second project belongs to the field of photovoltaic systems and aims to develop a three-port converter with multiple power elements interfacing capability. A GaN-based Triple Active Bridge has been designed, regarding both the controller and the hardware realization.

Real-time load-side control of electric power systems

Two trends are emerging from modern electric power systems: the growth of renewable (e.g., solar and wind) generation, and the integration of information technologies and advanced power electronics. The former introduces large, rapid, and random fluctuations in power supply, demand, frequency, and voltage, which become a major challenge for real-time operation of power systems. The latter creates a tremendous number of controllable intelligent endpoints such as smart buildings and appliances, electric vehicles, energy storage devices, and power electronic devices that can sense, compute, communicate, and actuate. Most of these endpoints are distributed on the load side of power systems, in contrast to traditional control resources such as centralized bulk generators. This thesis focuses on controlling power systems in real time, using these load side resources. Specifically, it studies two problems.

(1) Distributed load-side frequency control: We establish a mathematical framework to design distributed frequency control algorithms for flexible electric loads. In this framework, we formulate a category of optimization problems, called optimal load control (OLC), to incorporate the goals of frequency control, such as balancing power supply and demand, restoring frequency to its nominal value, restoring inter-area power flows, etc., in a way that minimizes total disutility for the loads to participate in frequency control by deviating from their nominal power usage. By exploiting distributed algorithms to solve OLC and analyzing convergence of these algorithms, we design distributed load-side controllers and prove stability of closed-loop power systems governed by these controllers. This general framework is adapted and applied to different types of power systems described by different models, or to achieve different levels of control goals under different operation scenarios. We first consider a dynamically coherent power system which can be equivalently modeled with a single synchronous machine. We then extend our framework to a multi-machine power network, where we consider primary and secondary frequency controls, linear and nonlinear power flow models, and the interactions between generator dynamics and load control.

(2) Two-timescale voltage control: The voltage of a power distribution system must be maintained closely around its nominal value in real time, even in the presence of highly volatile power supply or demand. For this purpose, we jointly control two types of reactive power sources: a capacitor operating at a slow timescale, and a power electronic device, such as a smart inverter or a D-STATCOM, operating at a fast timescale. Their control actions are solved from optimal power flow problems at two timescales. Specifically, the slow-timescale problem is a chance-constrained optimization, which minimizes power loss and regulates the voltage at the current time instant while limiting the probability of future voltage violations due to stochastic changes in power supply or demand. This control framework forms the basis of an optimal sizing problem, which determines the installation capacities of the control devices by minimizing the sum of power loss and capital cost. We develop computationally efficient heuristics to solve the optimal sizing problem and implement real-time control. Numerical experiments show that the proposed sizing and control schemes significantly improve the reliability of voltage control with a moderate increase in cost.

Flexible Power Control of Photovoltaic Plants Connected to Distribution Networks

This paper presents a system to control the power injected by a photovoltaic (PV) plant on the receiving network. This control is intended to mitigate some of the negative impacts that these units may produce on such networks, while increasing the installed power of the plant. The controlled parameters are the maximum allowed value of injected active power and the corresponding power factor, whose setpoints values may be fixed or dynamic. The developed system allows a local and a remote control. The injected power and the corresponding power factor may be set by following a predetermined profile or by real time adjustments to fulfill specific operation constraints on the receiving network. The system acts by adjusting the control parameters on the PV inverters. The main goal of the system is, in the end, to control the PV plant, ensuring the accomplishment of technical constraints and, at the same time, maximizing the installed power of the PV plant, which may be an important issue concerning the economic performance of such plants

Expression of genes related to muscle plasticity after strength and power training regimens

The purpose of our study was to compare the effects of 8-week progressive strength and power training regimens on strength gains and muscle plasticity [muscle fiber hypertrophy and phenotype shift, mammalian target of rapamycin (mTOR), regulatory-associated protein of mTOR (RAPTOR), rapamycin-insensitive companion of m-TOR (RICTOR), calcineurin and calcipressin gene expression]. Twenty-nine physically active subjects were divided into three groups: strength training (ST), power training (PT) and control (C). Squat 1 RM and muscle biopsies were obtained before and after the training period. Strength increased similarly for both ST and PT groups (P < 0.001). Fiber types I, IIa and IIb presented hypertrophy main time effect (P < 0.05). Only type IIb percentage decreased from pre- to post-test (main time effect, P < 0.05). mTOR and RICTOR mRNA expression increased similarly from pre- to post-test (P < 0.01). RAPTOR increased after training for both groups (P < 0.0001), but to a greater extent in the ST (P < 0.001) than in the PT group. 4EBP-1 decreased after training when the ST and PT groups were pooled (P < 0.05). Calcineurin levels did not change after training, while calcipressin increased similarly from pre- to post-test (P < 0.01). In conclusion, our data indicate that these training regimens produce similar performance improvements; however, there was a trend toward greater hypertrophy-related gene expression and muscle fiber hypertrophy in the ST group.

Real-Time Voltage Regulation in Power Distribution System Using Fuzzy Control

Two different fuzzy approaches to voltage control in electric power distribution systems are introduced in this paper. The real-time controller in each case would act on power transformers equipped with under-load tap changers. Learning systems are employed to turn the voltage-control relays into adaptive devices. The scope of this study has been limited to the power distribution substation, and the voltage measurements and control actions are carried out on the secondary bus. The capacity of fuzzy systems to handle approximate data, together with their unique ability to interpret qualitative information, make it possible to design voltage-control strategies that satisfy the requirements of the Brazilian regulatory bodies and the real concerns of the electric power distribution companies. Fuzzy control systems based on these two strategies have been implemented and the test results were highly satisfactory.

Power Electronics Didactic Modules for Direct Current Machine Control

Several didactic modules for an electric machinery laboratory are presented. The modules are dedicated for DC machinery control and get their characteristic curves. The didactic modules have a front panel with power and signal connectors and can be configurable for any DC motor type. The three-phase bridge inverter proposed is one of the most popular topologies and is commercially available in power package modules. The control techniques and power drives were designed to satisfy static and dynamic performance of DC machines. Each power section is internally self-protected against misconnections and short-circuits. Isolated output signals of current and voltage measurements are also provided, adding versatility for use either in didactic or research applications. The implementation of such modules allowed experimental confirmation of the expected performance.