Modified Particle Swarm Optimization Applied to Integrated Demand Response and DG Resources Scheduling

The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. This paper proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the operation costs of a virtual power player that manages the resources in a distribution network and the network itself. Resources include the DER available in the considered time period and the energy that can be bought from external energy suppliers. Network constraints are considered. The proposed approach uses Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310 consumers and 548 distributed generators. The obtained solutions are compared with a deterministic approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.

Otimização de placas compósitas laminadas utilizando redes neuronais e enxames de partículas

Trabalho Final de mestrado para obtenção do grau de Mestre em engenharia Mecância

Application-Specific Modified Particle Swarm Optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding the management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Particle swarm optimization for two-connected networks with bounded rings

The Two-Connected Network with Bounded Ring (2CNBR) problem is a network design problem addressing the connection of servers to create a survivable network with limited redirections in the event of failures. Particle Swarm Optimization (PSO) is a stochastic population-based optimization technique modeled on the social behaviour of flocking birds or schooling fish. This thesis applies PSO to the 2CNBR problem. As PSO is originally designed to handle a continuous solution space, modification of the algorithm was necessary in order to adapt it for such a highly constrained discrete combinatorial optimization problem. Presented are an indirect transcription scheme for applying PSO to such discrete optimization problems and an oscillating mechanism for averting stagnation.

Generating Aesthetically Pleasing Images in a Virtual Environment using Particle Swarm Optimization

This research focuses on generating aesthetically pleasing images in virtual environments using the particle swarm optimization (PSO) algorithm. The PSO is a stochastic population based search algorithm that is inspired by the flocking behavior of birds. In this research, we implement swarms of cameras flying through a virtual world in search of an image that is aesthetically pleasing. Virtual world exploration using particle swarm optimization is considered to be a new research area and is of interest to both the scientific and artistic communities. Aesthetic rules such as rule of thirds, subject matter, colour similarity and horizon line are all analyzed together as a multi-objective problem to analyze and solve with rendered images. A new multi-objective PSO algorithm, the sum of ranks PSO, is introduced. It is empirically compared to other single-objective and multi-objective swarm algorithms. An advantage of the sum of ranks PSO is that it is useful for solving high-dimensional problems within the context of this research. Throughout many experiments, we show that our approach is capable of automatically producing images satisfying a variety of supplied aesthetic criteria.

Characterizing Dynamic Optimization Benchmarks for the Comparison of Multi-Modal Tracking Algorithms

Population-based metaheuristics, such as particle swarm optimization (PSO), have been employed to solve many real-world optimization problems. Although it is of- ten sufficient to find a single solution to these problems, there does exist those cases where identifying multiple, diverse solutions can be beneficial or even required. Some of these problems are further complicated by a change in their objective function over time. This type of optimization is referred to as dynamic, multi-modal optimization. Algorithms which exploit multiple optima in a search space are identified as niching algorithms. Although numerous dynamic, niching algorithms have been developed, their performance is often measured solely on their ability to find a single, global optimum. Furthermore, the comparisons often use synthetic benchmarks whose landscape characteristics are generally limited and unknown. This thesis provides a landscape analysis of the dynamic benchmark functions commonly developed for multi-modal optimization. The benchmark analysis results reveal that the mechanisms responsible for dynamism in the current dynamic bench- marks do not significantly affect landscape features, thus suggesting a lack of representation for problems whose landscape features vary over time. This analysis is used in a comparison of current niching algorithms to identify the effects that specific landscape features have on niching performance. Two performance metrics are proposed to measure both the scalability and accuracy of the niching algorithms. The algorithm comparison results demonstrate the algorithms best suited for a variety of dynamic environments. This comparison also examines each of the algorithms in terms of their niching behaviours and analyzing the range and trade-off between scalability and accuracy when tuning the algorithms respective parameters. These results contribute to the understanding of current niching techniques as well as the problem features that ultimately dictate their success.

Analysis and Optimization of Machining Process Using Evolutionary Algorithms

To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.

Mean Squared Residue Based Biclustering Algorithms for the Analysis of Gene Expression Data

Computational Biology is the research are that contributes to the analysis of biological data through the development of algorithms which will address significant research problems.The data from molecular biology includes DNA,RNA ,Protein and Gene expression data.Gene Expression Data provides the expression level of genes under different conditions.Gene expression is the process of transcribing the DNA sequence of a gene into mRNA sequences which in turn are later translated into proteins.The number of copies of mRNA produced is called the expression level of a gene.Gene expression data is organized in the form of a matrix. Rows in the matrix represent genes and columns in the matrix represent experimental conditions.Experimental conditions can be different tissue types or time points.Entries in the gene expression matrix are real values.Through the analysis of gene expression data it is possible to determine the behavioral patterns of genes such as similarity of their behavior,nature of their interaction,their respective contribution to the same pathways and so on. Similar expression patterns are exhibited by the genes participating in the same biological process.These patterns have immense relevance and application in bioinformatics and clinical research.Theses patterns are used in the medical domain for aid in more accurate diagnosis,prognosis,treatment planning.drug discovery and protein network analysis.To identify various patterns from gene expression data,data mining techniques are essential.Clustering is an important data mining technique for the analysis of gene expression data.To overcome the problems associated with clustering,biclustering is introduced.Biclustering refers to simultaneous clustering of both rows and columns of a data matrix. Clustering is a global whereas biclustering is a local model.Discovering local expression patterns is essential for identfying many genetic pathways that are not apparent otherwise.It is therefore necessary to move beyond the clustering paradigm towards developing approaches which are capable of discovering local patterns in gene expression data.A biclusters is a submatrix of the gene expression data matrix.The rows and columns in the submatrix need not be contiguous as in the gene expression data matrix.Biclusters are not disjoint.Computation of biclusters is costly because one will have to consider all the combinations of columans and rows in order to find out all the biclusters.The search space for the biclustering problem is 2 m+n where m and n are the number of genes and conditions respectively.Usually m+n is more than 3000.The biclustering problem is NP-hard.Biclustering is a powerful analytical tool for the biologist.The research reported in this thesis addresses the problem of biclustering.Ten algorithms are developed for the identification of coherent biclusters from gene expression data.All these algorithms are making use of a measure called mean squared residue to search for biclusters.The objective here is to identify the biclusters of maximum size with the mean squared residue lower than a given threshold. All these algorithms begin the search from tightly coregulated submatrices called the seeds.These seeds are generated by K-Means clustering algorithm.The algorithms developed can be classified as constraint based,greedy and metaheuristic.Constarint based algorithms uses one or more of the various constaints namely the MSR threshold and the MSR difference threshold.The greedy approach makes a locally optimal choice at each stage with the objective of finding the global optimum.In metaheuristic approaches particle Swarm Optimization(PSO) and variants of Greedy Randomized Adaptive Search Procedure(GRASP) are used for the identification of biclusters.These algorithms are implemented on the Yeast and Lymphoma datasets.Biologically relevant and statistically significant biclusters are identified by all these algorithms which are validated by Gene Ontology database.All these algorithms are compared with some other biclustering algorithms.Algorithms developed in this work overcome some of the problems associated with the already existing algorithms.With the help of some of the algorithms which are developed in this work biclusters with very high row variance,which is higher than the row variance of any other algorithm using mean squared residue, are identified from both Yeast and Lymphoma data sets.Such biclusters which make significant change in the expression level are highly relevant biologically.

Tele Algodón, una televisión escolar.

La escuela del centro hospitalario 'La Paz' continúa desarrollando esta experiencia lúdico-pedagógica que tiene como finalidad potenciar el uso habitual de medios audiovisuales en las aulas integradas por niños hospitalizados con enfermedades largas y crónicas. Los objetivos son: producir mensajes utilizando diferentes recursos expresivos; convertir el entorno hospitalario en un lugar accesible y próximo para que el niño mitigue su ansiedad y obtenga nuevas experiencias de aprendizaje; y acrecentar la autoestima del niño a través de un aprendizaje significativo. La actividad central del proyecto consiste en la elaboración de programas televisivos (informativos, musicales, programas culturales, etc.) y en su emisión a través de vídeos a todos los niños hospitalizados. Esta experiencia permite integrar diversas áreas curriculares, fundamentalmente lenguaje, temas transversales y medios de comunicación. La evaluación considera la experiencia muy positiva al permitir que los alumnos con problemas de movilidad participen en la experiencia a través del visionado y crítica de los programas emitidos, favoreciendo así su integración y ayudando a los enfermos a sobrellevar su estancia en el hospital. La memoria incluye, además del desarollo de dos unidades didácticas ('Los microbios patógenos de Luna' y 'Ramón y Cajal, sus estudios sobre el cerebro'), el modelo de encuesta utilizado en la evaluación de los alumnos.

Aquí cuidamos nuestro entorno. Aquí cuidamos nuestro entorno, los materiales abiertos : nuevas posibilidades de expresión y socialización en Educación infantil.

El proyecto fomenta en los niños de Educación Infantil conductas de respeto y conservación del entorno mediante la estimulación de los sentidos utilizando materiales de desecho, en concreto plástico, para realizar distintas creaciones artísticas. Los objetivos generales son: utilizar la observación, exploración y experimentación para conocer algunos objetos y situaciones de su entorno próximo; concienciar a madres y padres en temas de mejora y conservación medioambiental; y fomentar la participación e implicación de las familias en el centro. Los materiales de desecho utilizados en el aula se presentan a cada nivel educativo y posteriormente se incorporan a la dinámica de trabajo, centrada en el juego y la expresión plástica. De forma paralela en el taller con las familias los niños continúan manipulando los materiales adaptados. Entre los objetos realizados destacan: juguetes, papeleras, contenedores de pilas, objetos decorativos y figuras tridimensionales. Se ha realizado una evaluación continua de todo el proceso con reuniones de nivel y en el claustro de profesores.

Proyecto de expresión en colegios.

La experiencia, desarrollada en varios colegios, propone ampliar la formación artística de todos los alumnos del centro en horario lectivo. Los objetivos fundamentales son: introducir en la escuela las áreas de expresión artística (teatro, música, plástica); y completar la formación del profesorado. Para desarrollar la experiencia, iniciada con la programación de formación para los profesores, se utiliza una metodología eminentemente lúdica que establece agrupamientos flexibles en función de las necesidades de cada tarea. Trabaja de forma globalizadora las áreas Música, Dramatización y Plástica para lograr, sobre todo, que los alumnos tengan la posibilidad de expresar libremente su creatividad e imaginación. Así, las actividades realizadas, que cuentan con la colaboración del grupo de teatro 'Tyl-Tyl', son: juegos de atención sonora y ritmos, transformaciones imaginativas del espacio, interpretación de personajes de cuentos, aprendizaje de canciones, confección de maquetas y juegos de imitación de personajes. La valoración de la experiencia destaca, por un lado, el carácter enriquecedor (aprendizaje de técnicas y recopilación de material) del proceso de formación del profesorado y, por otro, el logro de los objetivos propuestos en cuanto a teatro, y el avance positivo en los que se refieren al área de Música y Plástica.

El viejo que leía novelas de amor.

Este proyecto pretende desarrollar una serie de contenidos de medio ambiente y multiculturalidad, desde un punto de vista interdisciplinar. Las actividades parten de la novela 'El viejo que leía poemas de amor' de Luis Sepúlveda. A través de ella se desarrollan experiencias lingüístico-literarias, geográficas, históricas, culturales y ambientales sobre la Amazonia. Se realizan trabajos de recogida de información, elaboración de informes, prácticas de laboratorio, concursos, exposiciones, conferencias y visionado de películas. La metodología potencia actitudes críticas y participativas contemplando la influencia intercultural en relación con el entorno próximo. La valoración es positiva y se ha observado motivación e implicación tanto por parte de profesores como de alumnos..

De la escuela al hospital : radio algodón.

Memoria de la creación y organización de una emisora de radio (radio algodón) dirigida a todos los niños hospitalizados de tres a dieciséis años que requieren atención psicopedagógica. Los objetivos planteados son: potenciar la imaginación y la creatividad; fomentar la investigación de las diferentes áreas escolares (Matemáticas, Lengua, etc.); desarrollar la expresión oral y escrita; favorecer la socialización; y lograr una actitud activa y participativa. La experiencia consiste por una parte en la elaboración de programas en directo para la escuela en los que un grupo de niños confecciona los guiones y anima a sus compañeros a colaborar mediante poemas, anuncios, recetas, etc., mientras ofrecen música y noticias. Por otra parte, para los niños que no pueden acudir al aula se graban una serie de cintas que se distribuyen por las habitaciones en las que se les propone que participen en las actividades del programa por escrito (concursos de preguntas y respuestas, adivinanzas, recitaciones, interpretación de refranes, etc.) y a través del buzón de sugerencias. La evaluación señala que la experiencia ha propiciado la integración de niños de diferentes lugares y culturas y les ha ayudado a sobrellevar su estancia en el hospital. La memoria incluye además de un resumen del contenido de las cintas grabadas y algunos guiones de los programas en directo, una serie de artículos publicados sobre radio algodón.

La práctica psicomotriz como elemento integrador.

El proyecto, que se dirige no sólo a los alumnos de la zona sino también a los niños procedentes del internado-residencia, propone potenciar mediante la práctica psicomotriz, la personalidad, la integración y la interrelación y cohesión del grupo. De esta manera, los objetivos son: lograr una mayor interacción entre alumnos externos e internos; conseguir la integración de los niños con Necesidades Educativas Especiales; acortar y mejorar el período de adaptación; potenciar la expresividad psicomotriz; y favorecer la interacción adulto-niño y grupo-adulto. La experiencia consiste en la creación de tres espacios en la sala de psicomotricidad que representan el itinerario evolutivo flexible de la sesión. Así, en cada una distinguimos: la fase del placer-sensomotor donde se trabaja con espalderas, toboganes, puentes de salto con colchonetas, pelotas, balancines, etc.; la fase de las grandes construcciones y el juego simbólico, sobre todo tipo 'casa'; y la fase de distanciamiento emocional dedicada a juegos de construcciones con maderas, dibujos, modelado, etc. Cada sesión empieza y termina con una fase de reagrupación en la que se proponen actividades que por una parte faciliten el acercamiento e inicio del proceso; y por otra, ayuden al análisis y reflexión del trabajo realizado. La experiencia se considera interesante, tanto desde el punto de vista profesional por la aplicación de una dinámica de trabajo nueva, como desde el punto de vista educativo al alcanzar los alumnos los objetivos propuestos..

Aplicación del proyecto Harvard de desarrollo de la inteligencia.

Experiencia piloto de aplicación del proyecto 'Harvard' de desarrollo de la inteligencia en el Colegio Público Beato Simón de Rojas con la colaboración del EOEP de Móstoles. Se trata de un programa compensatorio para dotar al alumnado de estrategias cognitivas que mejoren su rendimiento escolar y sus actitudes. Los objetivos son: modificar la estructura de pensamiento; transferir las habilidades adquiridas tanto al currículum como al área de la personalidad; potenciar la acción tutorial; y dinamizar las relaciones intergrupales. Del programa, que consta de seis sesiones, sólo se ha aplicado la primera (Fundamentos de razonamiento) debido a la amplitud del mismo. La experiencia se realiza en cuatro grupos de sexto de EGB, utilizando los dos restantes como grupos de control. El desarrollo de cada sesión comienza con el repaso de los aspectos ya trabajados para luego pasar a la entrega de fichas para cada alumno (ejercicios sobre observación, clasificación, ordenamiento, analogía y razonamiento espacial), y las instrucciones de uso para su realización colectiva en la pizarra o mediante verbalización. Finalmente se pone en común el trabajo llevado a cabo. La evaluación mide el rendimiento académico y la generalización de las habilidades trabajadas mediante fichas de calificaciones, escalas de observación, registros de conductas y encuestas sobre el clima social.