Pumping system optimization tool

Pumping systems account for over 20 % of all electricity consumption in European industry. Optimization and correct design of such systems is important and there is a reasonable amount of unrealized energy saving potential in old pumping systems. The energy efficiency and therefore also the energy consumption of a pumping system heavily depends on the correct dimensioning and selection of devices. In this work, a graphical optimization tool for pumping systems is developed in Matlab programming language. The tool selects optimal pump, electrical motor and frequency converter for existing pumping process and calculates the life cycle costs of the whole system. The tool could be used as an aid when choosing the machinery and to analyze the energy consumption of existing systems. Results given by the tool are compared to the results of laboratory tests. The selection of pump and motor works reasonably well, but the frequency converter selection still needs development

An Error-Localization, Validation and Optimization Tool for Embedded Code Augmentation: an Architecture Oriented Approach

Embedded systems are usually designed for a single or a specified set of tasks. This specificity means the system design as well as its hardware/software development can be highly optimized. Embedded software must meet the requirements such as high reliability operation on resource-constrained platforms, real time constraints and rapid development. This necessitates the adoption of static machine codes analysis tools running on a host machine for the validation and optimization of embedded system codes, which can help meet all of these goals. This could significantly augment the software quality and is still a challenging field.Embedded systems are usually designed for a single or a specified set of tasks. This specificity means the system design as well as its hardware/software development can be highly optimized. Embedded software must meet the requirements such as high reliability operation on resource-constrained platforms, real time constraints and rapid development. This necessitates the adoption of static machine codes analysis tools running on a host machine for the validation and optimization of embedded system codes, which can help meet all of these goals. This could significantly augment the software quality and is still a challenging field.Embedded systems are usually designed for a single or a specified set of tasks. This specificity means the system design as well as its hardware/software development can be highly optimized. Embedded software must meet the requirements such as high reliability operation on resource-constrained platforms, real time constraints and rapid development. This necessitates the adoption of static machine codes analysis tools running on a host machine for the validation and optimization of embedded system codes, which can help meet all of these goals. This could significantly augment the software quality and is still a challenging field.Embedded systems are usually designed for a single or a specified set of tasks. This specificity means the system design as well as its hardware/software development can be highly optimized. Embedded software must meet the requirements such as high reliability operation on resource-constrained platforms, real time constraints and rapid development. This necessitates the adoption of static machine codes analysis tools running on a host machine for the validation and optimization of embedded system codes, which can help meet all of these goals. This could significantly augment the software quality and is still a challenging field.This dissertation contributes to an architecture oriented code validation, error localization and optimization technique assisting the embedded system designer in software debugging, to make it more effective at early detection of software bugs that are otherwise hard to detect, using the static analysis of machine codes. The focus of this work is to develop methods that automatically localize faults as well as optimize the code and thus improve the debugging process as well as quality of the code.Validation is done with the help of rules of inferences formulated for the target processor. The rules govern the occurrence of illegitimate/out of place instructions and code sequences for executing the computational and integrated peripheral functions. The stipulated rules are encoded in propositional logic formulae and their compliance is tested individually in all possible execution paths of the application programs. An incorrect sequence of machine code pattern is identified using slicing techniques on the control flow graph generated from the machine code.An algorithm to assist the compiler to eliminate the redundant bank switching codes and decide on optimum data allocation to banked memory resulting in minimum number of bank switching codes in embedded system software is proposed. A relation matrix and a state transition diagram formed for the active memory bank state transition corresponding to each bank selection instruction is used for the detection of redundant codes. Instances of code redundancy based on the stipulated rules for the target processor are identified.This validation and optimization tool can be integrated to the system development environment. It is a novel approach independent of compiler/assembler, applicable to a wide range of processors once appropriate rules are formulated. Program states are identified mainly with machine code pattern, which drastically reduces the state space creation contributing to an improved state-of-the-art model checking. Though the technique described is general, the implementation is architecture oriented, and hence the feasibility study is conducted on PIC16F87X microcontrollers. The proposed tool will be very useful in steering novices towards correct use of difficult microcontroller features in developing embedded systems.

Developing an optimization tool for evaluating the transmission system expansion

The transmission system is responsible for connecting the power generators to consumers safely and reliably, its constant expansion is necessary to transport increasing amounts of electricity. In order to help the power systems engineers, an optimization tool for optimize the expansion of the transmission system was developed using the modeling method of the linearized load flow and genetic. This tool was designed to simulate the impact of different scenarios on the cost of transmission expansion. The proposed tool was used to simulate the effects of the presence of distributed generation in the expansion of a fictitious transmission system, where it was found a clear downward trend in investment required for the expansion of the transmission system taking account of increasing levels of distributed generation.

Production Cycle Optimization: Defining the Market Potential for a New Planning Tool

An optimization tool has been developed to help companies to optimize their production cycles and thus improve their overall supply chain management processes. The application combines the functionality that traditional APS (Advanced Planning System) and ARP (Automatic Replenishment Program) systems provide into one optimization run. A qualitative study was organized to investigate opportunities to expand the product’s market base. Twelve personal interviews were conducted and the results were collected in industry specific production planning analyses. Five process industries were analyzed to identify the product’s suitability to each industry sector and the most important product development areas. Based on the research the paper and the plastic film industries remain the most potential industry sectors at this point. To be successful in other industry sectors some product enhancements would be required, including capabilities to optimize multiple sequential and parallel production cycles, handle sequencing of complex finishing operations and to include master planning capabilities to support overall supply chain optimization. In product sales and marketing processes the key to success is to find and reach the people who are involved directly with the problems that the optimization tool can help to solve.

A cost optimization-based design of precast concrete floors using genetic algorithms

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Development of Shape-Optimization Tools for the Aerodynamic Design of Turbomachinery Blades

The aim of this work is to develop an automated tool for the optimization of turbomachinery blades founded on an evolutionary strategy. This optimization scheme will serve to deal with supersonic blades cascades for application to Organic Rankine Cycle (ORC) turbines. The blade geometry is defined using parameterization techniques based on B-Splines curves, that allow to have a local control of the shape. The location in space of the control points of the B-Spline curve define the design variables of the optimization problem. In the present work, the performance of the blade shape is assessed by means of fully-turbulent flow simulations performed with a CFD package, in which a look-up table method is applied to ensure an accurate thermodynamic treatment. The solver is set along with the optimization tool to determine the optimal shape of the blade. As only blade-to-blade effects are of interest in this study, quasi-3D calculations are performed, and a single-objective evolutionary strategy is applied to the optimization. As a result, a non-intrusive tool, with no need for gradients definition, is developed. The computational cost is reduced by the use of surrogate models. A Gaussian interpolation scheme (Kriging model) is applied for the estimated n-dimensional function, and a surrogate-based local optimization strategy is proved to yield an accurate way for optimization. In particular, the present optimization scheme has been applied to the re-design of a supersonic stator cascade of an axial-flow turbine. In this design exercise very strong shock waves are generated in the rear blade suction side and shock-boundary layer interaction mechanisms occur. A significant efficiency improvement as a consequence of a more uniform flow at the blade outlet section of the stator is achieved. This is also expected to provide beneficial effects on the design of a subsequent downstream rotor. The method provides an improvement to gradient-based methods and an optimized blade geometry is easily achieved using the genetic algorithm.

Integration of modular process simulators under the Generalized Disjunctive Programming framework for the structural flowsheet optimization

The optimization of chemical processes where the flowsheet topology is not kept fixed is a challenging discrete-continuous optimization problem. Usually, this task has been performed through equation based models. This approach presents several problems, as tedious and complicated component properties estimation or the handling of huge problems (with thousands of equations and variables). We propose a GDP approach as an alternative to the MINLP models coupled with a flowsheet program. The novelty of this approach relies on using a commercial modular process simulator where the superstructure is drawn directly on the graphical use interface of the simulator. This methodology takes advantage of modular process simulators (specially tailored numerical methods, reliability, and robustness) and the flexibility of the GDP formulation for the modeling and solution. The optimization tool proposed is successfully applied to the synthesis of a methanol plant where different alternatives are available for the streams, equipment and process conditions.

Fault tolerant embedded systems design by multi-objective optimization

The design of fault tolerant systems is gaining importance in large domains of embedded applications where design constrains are as important as reliability. New software techniques, based on selective application of redundancy, have shown remarkable fault coverage with reduced costs and overheads. However, the large number of different solutions provided by these techniques, and the costly process to assess their reliability, make the design space exploration a very difficult and time-consuming task. This paper proposes the integration of a multi-objective optimization tool with a software hardening environment to perform an automatic design space exploration in the search for the best trade-offs between reliability, cost, and performance. The first tool is commanded by a genetic algorithm which can simultaneously fulfill many design goals thanks to the use of the NSGA-II multi-objective algorithm. The second is a compiler-based infrastructure that automatically produces selective protected (hardened) versions of the software and generates accurate overhead reports and fault coverage estimations. The advantages of our proposal are illustrated by means of a complex and detailed case study involving a typical embedded application, the AES (Advanced Encryption Standard).

Evaluating the effectiveness of signal timing optimization based on microscopic simulation evaluation

The optimization of the timing parameters of traffic signals provides for efficient operation of traffic along a signalized transportation system. Optimization tools with macroscopic simulation models have been used to determine optimal timing plans. These plans have been, in some cases, evaluated and fine tuned using microscopic simulation tools. A number of studies show inconsistencies between optimization tool results based on macroscopic simulation and the results obtained from microscopic simulation. No attempts have been made to determine the reason behind these inconsistencies. This research investigates whether adjusting the parameters of macroscopic simulation models to correspond to the calibrated microscopic simulation model parameters can reduce said inconsistencies. The adjusted parameters include platoon dispersion model parameters, saturation flow rates, and cruise speeds. The results from this work show that adjusting cruise speeds and saturation flow rates can have significant impacts on improving the optimization/macroscopic simulation results as assessed by microscopic simulation models.

A hybrid probabilistic criterion for market-based transmission expansion planning

Market-based transmission expansion planning gives information to investors on where is the most cost efficient place to invest and brings benefits to those who invest in this grid. However, both market issue and power system adequacy problems are system planers’ concern. In this paper, a hybrid probabilistic criterion of Expected Economical Loss (EEL) is proposed as an index to evaluate the systems’ overall expected economical losses during system operation in a competitive market. It stands on both investors’ and planner’s point of view and will further improves the traditional reliability cost. By applying EEL, it is possible for system planners to obtain a clear idea regarding the transmission network’s bottleneck and the amount of losses arises from this weak point. Sequentially, it enables planners to assess the worth of providing reliable services. Also, the EEL will contain valuable information for moneymen to undertake their investment. This index could truly reflect the random behaviors of power systems and uncertainties from electricity market. The performance of the EEL index is enhanced by applying Normalized Coefficient of Probability (NCP), so it can be utilized in large real power systems. A numerical example is carried out on IEEE Reliability Test System (RTS), which will show how the EEL can predict the current system bottleneck under future operational conditions and how to use EEL as one of planning objectives to determine future optimal plans. A well-known simulation method, Monte Carlo simulation, is employed to achieve the probabilistic characteristic of electricity market and Genetic Algorithms (GAs) is used as a multi-objective optimization tool.

Using siting algorithms in the design of marine reserve networks

Using benthic habitat data from the Florida Keys (USA), we demonstrate how siting algorithms can help identify potential networks of marine reserves that comprehensively represent target habitat types. We applied a flexible optimization tool-simulated annealing-to represent a fixed proportion of different marine habitat types within a geographic area. We investigated the relative influence of spatial information, planning-unit size, detail of habitat classification, and magnitude of the overall conservation goal on the resulting network scenarios. With this method, we were able to identify many adequate reserve systems that met the conservation goals, e.g., representing at least 20% of each conservation target (i.e., habitat type) while fulfilling the overall aim of minimizing the system area and perimeter. One of the most useful types of information provided by this siting algorithm comes from an irreplaceability analysis, which is a count of the number of, times unique planning units were included in reserve system scenarios. This analysis indicated that many different combinations of sites produced networks that met the conservation goals. While individual 1-km(2) areas were fairly interchangeable, the irreplaceability analysis highlighted larger areas within the planning region that were chosen consistently to meet the goals incorporated into the algorithm. Additionally, we found that reserve systems designed with a high degree of spatial clustering tended to have considerably less perimeter and larger overall areas in reserve-a configuration that may be preferable particularly for sociopolitical reasons. This exercise illustrates the value of using the simulated annealing algorithm to help site marine reserves: the approach makes efficient use of;available resources, can be used interactively by conservation decision makers, and offers biologically suitable alternative networks from which an effective system of marine reserves can be crafted.

Planeamento e optimização em redes celulares móveis auto-geridas assentes em LTE

O objectivo deste trabalho consiste em avaliar os benefícios das Self Organizing Networks (SON), no que concerne ao planeamento e optimização de redes Long Term Evolution (LTE), não só através do seu estudo, como também através do desenvolvimento e teste de algoritmos, que permitem avaliar o funcionamento de algumas das suas principais funções. O estudo efectuado sobre as SON permitiu identificar um conjunto de funções, tais como a atribuição automática de Physical Cell Id (PCI), o Automatic Neighbour Relation (ANR) e a optimização automática de parâmetros de handover, que permitem facilitar ou mesmo substituir algumas das tarefas mais comuns em planeamento e optimização de redes móveis celulares, em particular, redes LTE. Recorrendo a um simulador LTE destinado à investigação académica, em código aberto e desenvolvido em Matlab®, foi desenvolvido um conjunto de algoritmos que permitiram a implementação das funções em questão. Para além das funções implementadas, foram também introduzidas alterações que conferem a este simulador a capacidade de representar e simular redes reais, permitindo uma análise mais coerente dos algoritmos desenvolvidos. Os resultados obtidos, para além de evidenciarem claramente o benefício dos algoritmos desenvolvidos, foram ainda comparados com os obtidos pela ferramenta profissional de planeamento e optimização Atoll®, tendo-se verificado a franca proximidade de desempenho em algumas das funções. Finalmente, foi desenvolvida uma interface gráfica que permite o desenho, configuração e simulação de cenários, bem como a análise de resultados.

Virtual power players dealing with excessive wind power situations using real time pricing

The increasing importance given by environmental policies to the dissemination and use of wind power has led to its fast and large integration in power systems. In most cases, this integration has been done in an intensive way, causing several impacts and challenges in current and future power systems operation and planning. One of these challenges is dealing with the system conditions in which the available wind power is higher than the system demand. This is one of the possible applications of demand response, which is a very promising resource in the context of competitive environments that integrates even more amounts of distributed energy resources, as well as new players. The methodology proposed aims the maximization of the social welfare in a smart grid operated by a virtual power player that manages the available energy resources. When facing excessive wind power generation availability, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. The proposed method is especially useful when actual and day-ahead wind forecast differ significantly. The proposed method has been computationally implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20310 consumers and 548 distributed generators, some of them with must take contracts.

Maximizing the Social Welfare of Virtual Power Players Operation in Case of Excessive Wind Power

The integration of growing amounts of distributed generation in power systems, namely at distribution networks level, has been fostered by energy policies in several countries around the world, including in Europe. This intensive integration of distributed, non-dispatchable, and natural sources based generation (including wind power) has caused several changes in the operation and planning of power systems and of electricity markets. Sometimes the available non-dispatchable generation is higher than the demand. This generation must be used; otherwise it is wasted if not stored or used to supply additional demand. New policies and market rules, as well as new players, are needed in order to competitively integrate all the resources. The methodology proposed in this paper aims at the maximization of the social welfare in a distribution network operated by a virtual power player that aggregates and manages the available energy resources. When facing a situation of excessive non-dispatchable generation, including wind power, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. This method is especially useful when actual and day-ahead resources forecast differ significantly. The distribution network characteristics and concerns are addressed by including the network constraints in the optimization model. The proposed methodology has been implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20.310 consumers and 548 distributed generators, some of them non-dispatchable and with must take contracts. The implemented scenario corresponds to a real day in Portuguese power system.

Desenvolvimento de sequenciador para um Problema de Roteamento de Veículos

Este projecto tem como objectivo a optimização das rotas dos técnicos de serviço após venda da Schmitt+Sohn Elevadores, associadas à realização das manutenções preventivas a cada elemento contratado à empresa (elevadores, escadas rolantes, etc). Como tal, é necessário fazer uma distribuição dos equipamentos que se encontram em carteira, por um dos técnicos que assegura a manutenção, pelos vários dias úteis de cada mês, e pelas horas de trabalho de cada dia. Apesar do técnico ter disponíveis, por dia, 8h de trabalho, apenas 6h podem ser preenchidas com manutenções preventivas. As 2h restantes são essencialmente para possíveis manutenções correctivas para as quais o técnico seja solicitado. Caso o técnico não seja contactado para resolver nenhuma avaria, essas horas podem ser utilizadas pelo mesmo para adiantar trabalho do dia seguinte, isto é, visitar já alguns dos próximos pontos de manutenção preventiva do dia seguinte, ou para compensar trabalho que esteja atrasado. De salientar que, para cada dia, as deslocações do técnico de qualquer local ao primeiro ponto de uma rota ou de regresso do último ponto de uma rota não são contabilizadas. O trabalho desenvolvido nesta dissertação pretende dar resposta ao problema apresentado pela Schmitt+Sohn Elevadores. Para isso foi desenvolvida uma heurística para a optimização das rotas dos técnicos. Esta é baseada no conceito de “vizinho mais próximo” que procura sempre o ponto que se apresenta mais perto do último ponto que foi adicionado à rota. Com base nesta metodologia, nos processos de escolha dos pontos que formam clusters, e na selecção dos pontos iniciais de cada uma das rotas diárias, a ferramenta de optimização resultante define as rotas diárias para que o percurso efectuado por cada técnico num mês seja o menor possível. São feitas alterações às rotas definidas inicialmente quando encontrados pontos de uma mesma entrada a serem visitados em dias diferentes. Isto obrigaria o técnico a fazer duas viagens ao mesmo local. Por fim, o resultado é apresentado num documento Word a ser utilizado pelo técnico como guia diário das suas deslocações aos equipamentos que necessitam de verificações periódicas. Os resultados obtidos foram comparados com as rotas que estavam a ser usadas pela empresa, tendo apresentado resultados de melhor qualidade, constatando-se a eficiência da solução criada pelo algoritmo proposto neste trabalho.