Branch and bound algorithm for transmission network expansion planning using DC model

This paper presents an algorithm to solve the network transmission system expansion planning problem using the DC model which is a mixed non-linear integer programming problem. The major feature of this work is the use of a Branch-and-Bound (B&B) algorithm to directly solve mixed non-linear integer problems. An efficient interior point method is used to solve the non-linear programming problem at each node of the B&B tree. Tests with several known systems are presented to illustrate the performance of the proposed method. ©2007 IEEE.

Heuristic algorithm to solve the short term transmission network expansion planning

In this paper, a method for solving the short term transmission network expansion planning problem is presented. This is a very complex mixed integer nonlinear programming problem that presents a combinatorial explosion in the search space. In order to And a solution of excellent quality for this problem, a constructive heuristic algorithm is presented in this paper. In each step of the algorithm, a sensitivity index is used to add a circuit (transmission line or transformer) or a capacitor bank (fixed or variable) to the system. This sensitivity index is obtained solving the problem considering the numbers of circuits and capacitors banks to be added (relaxed problem), as continuous variables. The relaxed problem is a large and complex nonlinear programming and was solved through a higher order interior point method. The paper shows results of several tests that were performed using three well-known electric energy systems in order to show the possibility and the advantages of using the AC model. ©2007 IEEE.

Neural network approach for surface roughness prediction in surface grinding

Several systems are currently tested in order to obtain a feasible and safe method for automation and control of grinding process. This work aims to predict the surface roughness of the parts of SAE 1020 steel ground in a surface grinding machine. Acoustic emission and electrical power signals were acquired by a commercial data acquisition system. The former from a fixed sensor placed near the workpiece and the latter from the electric induction motor that drives the grinding wheel. Both signals were digitally processed through known statistics, which with the depth of cut composed three data sets implemented to the artificial neural networks. The neural network through its mathematical logical system interpreted the signals and successful predicted the workpiece roughness. The results from the neural networks were compared to the roughness values taken from the worpieces, showing high efficiency and applicability on monitoring and controlling the grinding process. Also, a comparison among the three data sets was carried out.

Variable speed refrigeration system with HPF input rectifier stage

This paper is based on the analysis and implementation of a new drive system applied to refrigeration systems, complying with the restrictions imposed by the IEC standards (Harmonic/Flicker/EMI-Electromagnetic Interference restrictions), in order to obtain high efficiency, high power factor, reduced harmonic distortion in the input current and reduced electromagnetic interference, with excellent performance in temperature control of a refrigeration prototype system (automatic control, precision and high dynamic response). The proposal is replace the single-phase motor by a three-phase motor, in the conventional refrigeration system. In this way, a proper control technique can be applied, using a closed-loop (feedback control), that will allow an accurate adjustment of the desirable temperature. The proposed refrigeration prototype uses a 0.5Hp three-phase motor and an open (Belt-Drive) Bitzer IY type compressor. The input rectifier stage's features include the reduction in the input current ripple, the reduction in the output voltage ripple, the use of low stress devices, low volume for the EMI input filter, high input power factor (PF), and low total harmonic distortion (THD) in the input current, in compliance with the IEC61000-3-2 standards. The digital controller for the output three-phase inverter stage has been developed using a conventional voltage-frequency control (scalar V/f control), and a simplified stator oriented Vector control, in order to verify the feasibility and performance of the proposed digital controls for continuous temperature control applied at the refrigerator prototype. ©2008 IEEE.

A true programmable HPF hybrid three-phase rectifier

In this paper is proposed and analyzed a digital hysteresis modulation using a FPGA (Field Programmable Gate Array) device and VHDL (Hardware Description Language), applied at a hybrid three-phase rectifier with almost unitary input power factor, composed by parallel SEPIC controlled single-phase rectifiers connected to each leg of a standard 6-pulses uncontrolled diode rectifier. The digital control allows a programmable THD (Total Harmonic Distortion) at the input currents, and it makes possible that the power rating of the switching-mode converters, connected in parallel, can be a small fraction of the total average output power, in order to obtain a compact converter, reduced input current THD and almost unitary input power factor. The proposed digital control, using a FPGA device and VHDL, offers an important flexibility for the associated control technique, in order to obtain a programmable PFC (Power Factor Correction) hybrid three-phase rectifier, in agreement with the international standards (IEC, and IEEE), which impose limits for the THD of the AC (Alternate Current) line input currents. Finally, the proposed control strategy is verified through experimental results from an implemented prototype. ©2008 IEEE.

Hybrid three-phase HPF rectifier with programmable input current THD, using FPGA device and VHDL language

In this paper is proposed and analyzed a digital hysteresis modulation using a FPGA (Field Programmable Gate Array) device and VHDL (Hardware Description Language), applied at a hybrid three-phase rectifier with almost unitary input power factor, composed by parallel SEPIC controlled single-phase rectifiers connected to each leg of a standard 6-pulses uncontrolled diode rectifier. The digital control allows a programmable THD (Total Harmonic Distortion) at the input currents, and it makes possible that the power rating of the switching-mode converters, connected in parallel, can be a small fraction of the total average output power, in order to obtain a compact converter, reduced input current THD and almost unitary input power factor. Finally, the proposed digital control, using a FPGA device and VHDL, offers an important flexibility for the associated control technique, in order to obtain a programmable PFC (Power Factor Correction) hybrid three-phase rectifier, in agreement with the international standards (IEC, and IEEE), which impose limits for the THD of the AC (Alternate Current) line input currents. The proposed strategy is verified by experiments. © 2008 IEEE.

Environmental evaluation of cogeneration scenarios in sugar industry

The development of new techniques that allow the analysis and optimization of energy systems bearing in mind environmental issues is indispensable in a world with finite natural resources and growing demand of energy. Among the energy systems that deserve special attention, cogeneration in the sugar industry must be pointed out, because it uses efficiently a common fuel for generation of useful heat and power. Within this frame, thermoeconomical optimization - 2nd Law of Thermodynamics analysis by exergy function and economic evaluation of the thermal system - gradually is taking importance as a powerful tool to assist to the decision making process. Also, the explicit consideration of environmental issues offers a better way to explore trade-offs between different aspects to support the decisions that must be made. In this work it is used the technique of Life Cycle Analysis (LCA) which allows to consider environmental matters as an integral part of the problem, in opposite to most of the environmental approaches that only reduce residuals generation , without taking into account impacts associated to other related processes. On the other hand, the consideration of environmental issues in optimization of energy systems is a novel and promissory contribution in the state of the art of energy optimization and LCA. The system under study is a sugar plant of Tucumán (Argentina) given the particular importance that this industry had inside the regional economy of the Argentinean Northwest. Although cogeneration comes being used a while ago in sugar industry, being the main objective the generation of heat and as secondary objective the electric power generation and mechanic power to cover several needs of working machineries, to the date it is no available a versatile tool that allows to analyze economical feasible alternatives bearing in mind environmental issues. At sugar plants, steam is generated in boilers using as fuel bagasse - cellulosic fiber waste obtained crushing the sugar cane- and it is used to give useful heat and shaft work to the plant, but it can also be used to generate electricity with export opportunities to the electrical network. The great number of process alternatives outlines a serious decision making problem in order to take advantage of the resources. Although the problem turns out to be a mixed non-linear problem (MINLP), the main contribution of this work is the development of a hybrid strategy to evaluate cogeneration alternatives that combines optimization approaches with environmental indicators. This powerful tool for its versatility and robustness to analyze cogeneration systems, will be of great help in the decision making process, because of their easy implementation to analyze the kind of problems presented in the sugar industry.

Monitoring the dressing operation in the grinding process

This work was based on a methodology of development and experimentation, and involved monitoring the dressing operation by processing the acoustic emission and electric power signals to detect the optimal dressing moment. Dressing tests were performed in a surface grinding machine with an aluminium grinding wheel. Dressing analysis software was developed and used to process the signals collected earlier in order to analyse not only the dressing parameters but also the software's ability to indicate the instant when the dressing operation could be concluded. Parameters used in the study of burn in grinding were implemented in order to ascertain if they would also prove efficient in monitoring dressing. A comparative study revealed that some parameters are capable of monitoring the dressing operation. It was possible to verify the parameters effectiveness that today are utilised in burning to monitor dressing as well as to create new parameters for monitoring this operation. Copyright © 2009, Inderscience Publishers.

Back to school with tablets embedded in digital desks

A digital-desk pilot program, named One Laptop Per Child (OPLC), in Brazil uses a unique display design to provide an interactive interface developed to enhance education and minimize ergonomic concerns. The one-to-one computer strategy as proposed by Nicholas Negroponte is a way of circumventing the tragedy of the locked computer lab because it gives children full access to computers anytime. The OLPC program has focused on a solution that minimizes power consumption, which also limits the display's maximum size and processor performance because the LCD backlights are responsible for a significant part of the power consumption in laptops. The government has also developed a new type of low-cost tablet that is based on a resistive principle. High transparencies can be obtained in the 90% range in the tablet, while robustness is guaranteed by the outstanding tribological characteristics of Sn02 on glass.

A nonlinear model for the long-term hydro-thermal generation scheduling problem over multiple areas with transmission constraints

This paper presents a nonlinear model with individual representation of plants for the centralized long-term hydrothermal scheduling problem over multiple areas. In addition to common aspects of long-term scheduling, this model takes transmission constraints into account. The ability to optimize hydropower exchange among multiple areas is important because it enables further minimization of complementary thermal generation costs. Also, by considering transmission constraints for long-term scheduling, a more precise coupling with shorter horizon schedules can be expected. This is an important characteristic from both operational and economic viewpoints. The proposed model is solved by a sequential quadratic programming approach in the form of a prototype system for different case studies. An analysis of the benefits provided by the model is also presented. ©2009 IEEE.

Harmonic, reactive and unbalance compensation by means of CPT framework

This paper presents possible selective current compensation strategies based on the Conservative Power Theory (CPT). This recently proposed theory, introduces the concept of complex power conservation under non-sinusoidal conditions. Moreover, the related current decompositions results in several current terms, which are associated with a specific physical phenomena (power absorption P, energy storage Q, voltage and current distortion D). Such current components are used in this work for the definition of different current compensators, which can be selective in terms of minimizing particular disturbing effects. The choice of one or other current component for compensation directly affects the sizing and cost of active and/or passive devices and it will be demonstrated that it can be done to attend predefined limits for harmonic distortion, unbalances and/or power factor. Single and three-phase compensation strategies will be discussed by means of the CPT Framework. Simulation and experimental results will be demonstrated in order to validate their performance. © 2009 IEEE.

A specialized genetic algorithm to solve the short term transmission network expansion planning

In this paper, the short term transmission network expansion planning (STTNEP) is solved through a specialized genetic algorithm (SGA). A complete AC model of the transmission network is used, which permits the formulation of an integrated power system transmission network expansion planning problem (real and reactive power planning). The characteristics of the proposed SGA to solve the STTNEP problem are detailed and an interior point method is employed to solve nonlinear programming problems during the solution steps of the SGA. Results of tests carried out with two electrical energy systems show the capabilities of the SGA and also the viability of using the AC model to solve the STTNEP problem. © 2009 IEEE.

Modelo AC para el despacho combinado de contratos bilaterales y bolsa de energía considerando restricciones de seguridad

Reliability is a key aspect in power system design and planning. Maintaining a reliable power system is a very important issue for their design and operation. Under the new competitive framework of the electricity sector, power systems find ever more and more strained to operate near their limits. Under this new scenario, it is crucial for the system operator to use tools that facilitate an energy dispatch that minimizes possible power cuts. This paper presents a mathematical model to calculate an energy dispatch that considers security constraints (single contingencies in transmission lines and transformers). The model involves pool markets and fixed bilateral contracts. Traditional methodologies that include security constraints are usually based in multistage dispatch processes. In this case, we propose a single-stage model that avoids the economic inefficiencies which result when conventional multi-stage dispatch approaches are applied. The proposed model includes an AC representation of the transport system and allows calculating the cost overruns incurred in due to reliability restrictions. We found that complying with fixed bilateral contracts, when they go above certain levels, might lead to congestion problems in transmission lines.

Specialized genetic algorithm for transmission network expansion planning considering reliability

This paper presents a methodology to solve the transmission network expansion planning problem (TNEP) considering reliability and uncertainty in the demand. The proposed methodology provides an optimal expansion plan that allows the power system to operate adequately with an acceptable level of reliability and in an enviroment with uncertainness. The reliability criterion limits the expected value of the reliability index (LOLE - Loss Of Load Expectation) of the expanded system. The reliability is evaluated for the transmission system using an analytical technique based in enumeration. The mathematical model is solved, in a efficient way, using a specialized genetic algorithm of Chu-Beasley modified. Detailed results from an illustrative example are presented and discussed. © 2009 IEEE.

Fast non-technical losses identification through Optimum-Path Forest

Fraud detection in energy systems by illegal consumers is the most actively pursued study in non-technical losses by electric power companies. Commonly used supervised pattern recognition techniques, such as Artificial Neural Networks and Support Vector Machines have been applied for automatic commercial frauds identification, however they suffer from slow convergence and high computational burden. We introduced here the Optimum-Path Forest classifier for a fast non-technical losses recognition, which has been demonstrated to be superior than neural networks and similar to Support Vector Machines, but much faster. Comparisons among these classifiers are also presented. © 2009 IEEE.