Direct Power Control of Matrix Converter Based Unified Power Flow Controllers

This paper presents the Direct Power Control of Three-Phase Matrix Converters (DPC-MC) operating as Unified Power Flow Controllers (UPFC). Since matrix converters allow direct AC/AC power conversion without intermediate energy storage link, the resulting UPFC has reduced volume and cost, together with higher reliability. Theoretical principles of DPC-MC method are established based on an UPFC model, together with a new direct power control approach based on sliding mode control techniques. As a result, active and reactive power can be directly controlled by selection of an appropriate switching state of matrix converter. This new direct power control approach associated to matrix converters technology guarantees decoupled active and reactive power control, zero error tracking, fast response times and timely control actions. Simulation results show good performance of the proposed system.

Matrix Converter-Based Unified Power-Flow Controllers: Advanced Direct Power Control Method

This paper presents a direct power control (DPC) for three-phase matrix converters operating as unified power flow controllers (UPFCs). Matrix converters (MCs) allow the direct ac/ac power conversion without dc energy storage links; therefore, the MC-based UPFC (MC-UPFC) has reduced volume and cost, reduced capacitor power losses, together with higher reliability. Theoretical principles of direct power control (DPC) based on sliding mode control techniques are established for an MC-UPFC dynamic model including the input filter. As a result, line active and reactive power, together with ac supply reactive power, can be directly controlled by selecting an appropriate matrix converter switching state guaranteeing good steady-state and dynamic responses. Experimental results of DPC controllers for MC-UPFC show decoupled active and reactive power control, zero steady-state tracking error, and fast response times. Compared to an MC-UPFC using active and reactive power linear controllers based on a modified Venturini high-frequency PWM modulator, the experimental results of the advanced DPC-MC guarantee faster responses without overshoot and no steady-state error, presenting no cross-coupling in dynamic and steady-state responses.

Simulated annealing metaheuristic to solve the optimal power flow

The optimal power flow problem has been widely studied in order to improve power systems operation and planning. For real power systems, the problem is formulated as a non-linear and as a large combinatorial problem. The first approaches used to solve this problem were based on mathematical methods which required huge computational efforts. Lately, artificial intelligence techniques, such as metaheuristics based on biological processes, were adopted. Metaheuristics require lower computational resources, which is a clear advantage for addressing the problem in large power systems. This paper proposes a methodology to solve optimal power flow on economic dispatch context using a Simulated Annealing algorithm inspired on the cooling temperature process seen in metallurgy. The main contribution of the proposed method is the specific neighborhood generation according to the optimal power flow problem characteristics. The proposed methodology has been tested with IEEE 6 bus and 30 bus networks. The obtained results are compared with other wellknown methodologies presented in the literature, showing the effectiveness of the proposed method.

Ant colony search algorithm for the optimal power flow problem

To maintain a power system within operation limits, a level ahead planning it is necessary to apply competitive techniques to solve the optimal power flow (OPF). OPF is a non-linear and a large combinatorial problem. The Ant Colony Search (ACS) optimization algorithm is inspired by the organized natural movement of real ants and has been successfully applied to different large combinatorial optimization problems. This paper presents an implementation of Ant Colony optimization to solve the OPF in an economic dispatch context. The proposed methodology has been developed to be used for maintenance and repairing planning with 48 to 24 hours antecipation. The main advantage of this method is its low execution time that allows the use of OPF when a large set of scenarios has to be analyzed. The paper includes a case study using the IEEE 30 bus network. The results are compared with other well-known methodologies presented in the literature.

Direct electroanalytical determination of fluvastatin in a pharmaceutical dosage form: batch and flow analysis

The reduction of luvastatin (FLV) at a hanging mercury-drop electrode (HMDE) was studied by square-wave adsorptive-stripping voltammetry (SWAdSV). FLV can be accumulated and reduced at the electrode, with a maximum peak current intensity at a potential of approximately 1.26V vs. AgCl=Ag, in an aqueous electrolyte solution of pH 5.25. The method shows linearity between peak current intensity and FLV concentration between 1.0 10 8 and 2.7 10 6 mol L 1. Limits of detection (LOD) and quantification (LOQ) were found to be 9.9 10 9 mol L 1 and 3.3 10 8 mol L 1, respectively. Furthermore, FLV oxidation at a glassy carbon electrode surface was used for its hydrodynamic monitoring by amperometric detection in a flow-injection system. The amperometric signal was linear with FLV concentration over the range 1.0 10 6 to 1.0 10 5 mol L 1, with an LOD of 2.4 10 7 mol L 1 and an LOQ of 8.0 10 7 mol L 1. A sample rate of 50 injections per hour was achieved. Both methods were validated and showed to be precise and accurate, being satisfactorily applied to the determination of FLV in a commercial pharmaceutical.

Power law analysis of financial index dynamics

Power law PL and fractional calculus are two faces of phenomena with long memory behavior. This paper applies PL description to analyze different periods of the business cycle. With such purpose the evolution of ten important stock market indices DAX, Dow Jones, NASDAQ, Nikkei, NYSE, S&P500, SSEC, HSI, TWII, and BSE over time is studied. An evolutionary algorithm is used for the fitting of the PL parameters. It is observed that the PL curve fitting constitutes a good tool for revealing the signal main characteristics leading to the emergence of the global financial dynamic evolution.

Inverse dynamics based predictive control for unified power flow controllers without DC bus

This paper presents a new predictive digital control method applied to Matrix Converters (MC) operating as Unified Power Flow Controllers (UPFC). This control method, based on the inverse dynamics model equations of the MC operating as UPFC, just needs to compute the optimal control vector once in each control cycle, in contrast to direct dynamics predictive methods that needs 27 vector calculations. The theoretical principles of the inverse dynamics power flow predictive control of the MC based UPFC with input filter are established. The proposed inverse dynamics predictive power control method is tested using Matlab/Simulink Power Systems toolbox and the obtained results show that the designed power controllers guarantees decoupled active and reactive power control, zero error tracking, fast response times and an overall good dynamic and steady-state response.

Linear and sliding-mode control design for matrix converter-based unified power flow controllers

This paper presents the design and compares the performance of linear, decoupled and direct power controllers (DPC) for three-phase matrix converters operating as unified power flow controllers (UPFC). A simplified steady-state model of the matrix converter-based UPFC fitted with a modified Venturini high-frequency pulse width modulator is first used to design the linear controllers for the transmission line active (P) and reactive (Q) powers. In order to minimize the resulting cross coupling between P and Q power controllers, decoupled linear controllers (DLC) are synthesized using inverse dynamics linearization. DPC are then developed using sliding-mode control techniques, in order to guarantee both robustness and decoupled control. The designed P and Q power controllers are compared using simulations and experimental results. Linear controllers show acceptable steady-state behaviour but still exhibit coupling between P and Q powers in transient operation. DLC are free from cross coupling but are parameter sensitive. Results obtained by DPC show decoupled power control with zero error tracking and faster responses with no overshoot and no steady-state error. All the designed controllers were implemented using the same digital signal processing hardware.

Matrix converter as unified power flow controller: design and implementation of decoupled direct power controllers

This paper presents the design and implementation of direct power controllers for three-phase matrix converters (MC) operating as Unified Power Flow Controllers (UPFC). Theoretical principles of the decoupled linear power controllers of the MC-UPFC to minimize the cross-coupling between active and reactive power control are established. From the matrix converter based UPFC model with a modified Venturini high frequency PWM modulator, decoupled controllers for the transmission line active (P) and reactive (Q) power direct control are synthesized. Simulation results, obtained from Matlab/Simulink, are presented in order to confirm the proposed approach. Results obtained show decoupled power control, zero error tracking, and fast responses with no overshoot and no steady-state error.

Information flow analysis using data-dependent logical propositions

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

A type system for value-dependent information flow analysis

Information systems are widespread and used by anyone with computing devices as well as corporations and governments. It is often the case that security leaks are introduced during the development of an application. Reasons for these security bugs are multiple but among them one can easily identify that it is very hard to define and enforce relevant security policies in modern software. This is because modern applications often rely on container sharing and multi-tenancy where, for instance, data can be stored in the same physical space but is logically mapped into different security compartments or data structures. In turn, these security compartments, to which data is classified into in security policies, can also be dynamic and depend on runtime data. In this thesis we introduce and develop the novel notion of dependent information flow types, and focus on the problem of ensuring data confidentiality in data-centric software. Dependent information flow types fit within the standard framework of dependent type theory, but, unlike usual dependent types, crucially allow the security level of a type, rather than just the structural data type itself, to depend on runtime values. Our dependent function and dependent sum information flow types provide a direct, natural and elegant way to express and enforce fine grained security policies on programs. Namely programs that manipulate structured data types in which the security level of a structure field may depend on values dynamically stored in other fields The main contribution of this work is an efficient analysis that allows programmers to verify, during the development phase, whether programs have information leaks, that is, it verifies whether programs protect the confidentiality of the information they manipulate. As such, we also implemented a prototype typechecker that can be found at http://ctp.di.fct.unl.pt/DIFTprototype/.

S-system parameter estimation for noisy metabolic profiles using newton-flow analysis.

Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.

Production Flow Analysis - cases from manufacturing and service industry

Production flow analysis (PFA) is a well-established methodology used for transforming traditional functional layout into product-oriented layout. The method uses part routings to find natural clusters of workstations forming production cells able to complete parts and components swiftly with simplified material flow. Once implemented, the scheduling system is based on period batch control aiming to establish fixed planning, production and delivery cycles for the whole production unit. PFA is traditionally applied to job-shops with functional layouts, and after reorganization within groups lead times reduce, quality improves and motivation among personnel improves. Several papers have documented this, yet no research has studied its application to service operations management. This paper aims to show that PFA can well be applied not only to job-shop and assembly operations, but also to back-office and service processes with real cases. The cases clearly show that PFA reduces non-value adding operations, introduces flow by evening out bottlenecks and diminishes process variability, all of which contribute to efficient operations management.