Search

This paper proposes an alternative methodology to optimally design an electrical distribution system in a real urban area. A medium voltage (MV) network polygon is extracted from the web page of a distribution company (GIS platform), which serves as a comparison pattern. A redesign of the medium voltage network is made to the extracted polygon. Taking as a premise that it is a new urbanization that needs to be provided with electric power, with all the technical requirements imposed by the regulating entity, good power quality and at minimum cost. To achieve this goal, two mathematical optimization models are used. The methodology begins by delimiting the project area in a geo-referenced manner; in this area 36 possible sites are located where the distribution transformers that will provide electricity to the new urbanization can be placed. The first optimization model determines how many transformers will be installed, by means of a minimization objective function, the constraints of the model are: transformer capacity (KVA) and coverage (number of subscribers connected to the low voltage network of each transformer). Once the number of transformers to be installed and their respective geo-referenced optimal locations are determined, the model is run. The second heuristic optimization model, based on graph theory, calculates the mine spanning tree for the connection of the medium voltage electrical network, thus interconnecting the transformers of the project with the minimum distance, thus optimizing the construction cost. These optimization models are implemented and solved with Matlab and LpSolve software. The topology found with the two proposed models is electrically evaluated by running power flows with CYMEDIST software. Finally, the proposed model is evaluated by comparing the electrical parameters obtained with the electrical parameters of the polygon extracted from the GIS system of the distribution company. [ABSTRACT FROM AUTHOR]

Introduction-- A mathematical model for flexible electrical loads and energy storage system scheduling is presented in this paper, leveraged by the hourly rates according to resolution CREG 015/2018 and analyzed at the residential sector in the context of new demand curves resulting from measures against the COVID-19 pandemic. Objectives-- Three mathematical optimization models are proposed, aiming to find the lowest billing cost for the end-user through flexible load characteristics and seeking optimization through mixed-integer linear programming models. Methodology-- For the calculation of hourly rates, the mathematical formulation described in resolution CREG 015 is implemented and hourly rates are obtained in three different levels following a logic similar to the demand response schemes called Time of Use. Results-- The results obtained show that a demand response program with hourly rates effectively introduces an economic incentive during the evaluated period, through the possibility of modifying consumption patterns that reduce the payment of the electricity bill. Conclusions-- The proposed model of energy demand through scheduling selected flexible loads model and the opportunity to use the energy stored in electric vehicles generates economic benefits for the user by minimizing the cost of energy during the teleworking period in COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Mathematical Model of a Series-Parallel (SP) photovoltaic (PV) generator represents each module through an equivalent electrical circuit denominated single diode model, this model has associated a nonlinear equation system that describes the electrical behavior of SP generator. This paper presents a solution of this system using optimization methods widely using: Trust Region Dogleg and Particle swarm optimization (PSO) for solving the electrical model of PV generator operating under homogeneous or non-homogeneous conditions, changing the number of submodules and shading pattern. It has been made simulations about generators composed by 3 and 15 series submodules, operating under different partial shading conditions. Between the implemented methods, Trust Region Dogleg show a better performance than other methods, with 2 and 14 times less computation time than the reference method and PSO, respectively, and a RMSE equal or 50% lower than PSO. [ABSTRACT FROM AUTHOR]

Proper management of projects has become an element of vital importance for the solution to problems of society. In this context, there are two main objectives to be solved: the construction of project plans which may comply with the constraints of the problem and the optimization in terms of cost and time of those plans. To this end, all activities of project must be organized in such way that the constraints related to the precedence among them and the availability of renewable and non-renewable resources at each instant of time are met. The aim of this paper is to present an Estimation of Distribution Algorithm (EDA), which incorporates the handling of the constraints in the probabilistic model, for the construction of optimal or quasi-optimal project plans. For the validation of the algorithm, authors used both the PSPLib database repository for the development of the scheduling research and the databases of projects of the Repository for Research in Project Management, University of Infomatic Sciences. [ABSTRACT FROM AUTHOR]

With the simulation and optimization of a manufacturing system, the input parameters are sought to obtain the best performance of the system, considering in many cases a single objective or measure of performance. However, many decisions involve multiple criteria, usually in conflict. Currently, companies are required to improve their profitability as well as to reduce their impact on the environment and use energy rationally. In this paper, the wood products manufacturing process of a small company was studied to determine redesign alternatives, with simultaneous economic and environmental criteria. A simulation model of the system was built, which was validated and verified, and an optimization model for it in which two objectives were combined in a single function, incorporating in it the preferences of the decision makers with respect to each criterion. Results expose that combining both criteria it is possible to achieve substantial improvements in the benefit, at the same time that generating less emissions than if only the economic objective were pursued. It is concluded that simulation and optimization combining both criteria can improve economic-environmental performance in wood manufacturing systems, even in small companies. [ABSTRACT FROM AUTHOR]

Shell and tube heat exchangers (STHEs) are the most common type of heat exchangers. They are applied in many industrial facilities. The minimization of the costs of these heat exchangers is a key objective for both designers and users. The heat exchanger design involves complex processes, including selection of the geometric parameters and operating parameters. The traditional approach to design shell and tube heat exchangers is evaluating a number of different geometries of the exchanger to identify those that meet a requirement of heat and a set of geometric and operational constraints. However, this approach is slow, inaccurate and does not guarantee an optimal solution. In this paper is analyzed a procedure for designing heat exchangers and develops the economic optimization of the data by the method of simulated annealing. It was considered as the objective function the minimization of the total annual cost. For design optimization were considered as independent variables the inner diameter of the shell, the outer diameter of the tube and the spacing between the baffles. Also were considered to optimize two provisions or arrangements of tubes: in a triangle and a square. In this paper it is also presented an example of optimization of a heat exchanger. The results of the optimization using simulated annealing technique are compared with those obtained using particle swarm and genetic algorithms. [ABSTRACT FROM AUTHOR]

As the classical water-supply looped-network optimization problem is mathematically nonconvex and multimodal, the resulting solution of most approaches is uncertain in the sense of how close it is to the "best" solution. In many cases, this "best"' or "global" solution is invoked and pursued without a clear understanding of its meaning. This paper discusses what is involved in "global" solutions and the role that pipe flow distribution can play to deal with nonconvexity and multimodality in a new context. The author has introduced this new context recently after formulating a new objective function capable of finding that a looped network can be economically more attractive than its related branched one. Therefore, the convenience of an approach dealing with flows and heads, as relevant decision variables, is encouraged in this paper and its advantages enumerated under the new concepts. The entropy approach is studied critically and an example is provided for comparison with the proposed approach. [ABSTRACT FROM AUTHOR]

The objective of this paper is to show a methodology that allows finding the optimal behavior of a system, given a measure of effectiveness and a set of controllable variables. In the paper simulation techniques are combined with experimental design to produce a response surface, and after an optimization method is applied. A case study in the Cuban sugar industry is described. [ABSTRACT FROM AUTHOR]

This paper analyzes the effect of different configurations of initial conditions for the optimization algorithm based on particle swarms with vorticity behavior. The proposed algorithm combines the gradient-based search and particle swarm behavior, thus, this algorithm can be affected by the initial conditions for the particles. Finally, a 2D test function is used to observe the characteristics of the algorithm. [ABSTRACT FROM AUTHOR]

This paper presents a methodology to solve the problem of service restoration in electric distribution systems, which is proposed as a model of mixed integer non-linear optimization where the objective function is to maximize the load that is outside of service, subject to a set of technical and operational constraints. The problem is solved using heuristic techniques, through sensitivity indicators that guide the restoration process. The methodology is validated in distribution systems, finding good-quality results. [ABSTRACT FROM AUTHOR]

Hydrogen is an attractive energy source due to its high energy content and friendly combustion. Among the various mechanisms for hydrogen production, dark fermentation is one of the most interesting, because it uses the wastes as feedstock. The research on hydrogen production is to date in study, but the results are not yet conclusive. In this sense, this paper aims to do a critical review between 1993 and 2011 to show the most studied factors, the configurations most employed and the main results on this topic. Our findings showed the need, not only to optimize the factors that influence the production, but also to do more studies on real scale and in continuous flow. [ABSTRACT FROM AUTHOR]

This paper presents a methodological approach for tuning fuzzy classifiers intended to recognize the Australian sign-language considering two particular contexts. We describe the fuzzy classification architecture and the tuning process based on differential evolution. The validation results show that it is possible to find a fuzzy classifier whose classification error is around 13.0% over a group of words taken from several experts for each interaction context. This characteristic is relevant as previous works only considered recognizing words provided only by one interpreter. [ABSTRACT FROM AUTHOR]

The economic advantages of a looped network have not been considered in any of the optimization models found in the literature. This paper introduces a new formulation and methodology in an attempt to give a practical solution to this problem. The new formulation consists of a non-linear optimization model solved by classical differential calculus and the Newton-Raphson technique. An example shows how the looped network can be less costly than a branched one. Previous research usually optimizes the network for a given design demand. Also the value that should be specified as the desired network reliability has not been reported so far. This work introduces a methodology to obtain not only an adequate value for the reliability of a looped network but also the appropriate design demand as well based on a thorough cost analysis. A second example illustrates the detailed performance of this methodology. [ABSTRACT FROM AUTHOR]

Finding the peak of an optimization problem or model is just part of the solution process. This paper analyzes dual prices, objective function coefficients, the reduced cost of each variable, sensitivity ranges, and the width of the values in the right side of restrictions by means of a computer program, and a profit maximization lineal programming model applied to an agricultural business. The post optimal analysis reveals vital information to farmers who operate in a dynamic context for the best decisions to be made in regards to variation options of determined parameters in a model of a future project to upgrade the optimum value of the objective function. The agricultural producer gets to know how the optimal production plan may remain the same while increasing profits that are subject to variations in the boundaries of the problem or the business itself. He gets to assess the real needs of available resources and might find out what would be the best choices and decisions to improve the optimal value when simultaneously considering the marginal profit that the dual price represents and the allowed increase in the value on the right side of each restriction. [ABSTRACT FROM AUTHOR]

Evolution Strategies is a bio-inspired, robust, and efficient technique for solving optimization problems where the solution space is unrestricted. However, this assumption is unreal in many cases because the solution space is limited by complex boundaries in the form of linear and non-linear restrictions. In this paper, a modification of the original algorithm of Evolution Strategies for optimizing problems where the solution space is bounded using complex restrictions is proposed. The proposed method is based on the use of a penalization function which is zero inside of the feasible region and equal to the maximum value inside of the feasible region when an unfeasible point is considered. The proposed approach is proved using six benchmark problems. In all cases, our approach found an optimal point equal or lower than the values reported in the literature. [ABSTRACT FROM AUTHOR]

This paper presents a multiobjective analysis including variables of the environment of the energy system which is conditioned by the use of solid fuels, for this reason the analysis includes the external characteristics of the resource (fuel) of residue (ash) and the product (electricity/steam). The energy system used is Termocesar, a Colombian process for generating electricity from carbon. Three functions named thermoeconomic objective function, technology objective function and environmental objective function, are analyzed to establish the best location of the energy The genetic algorithm method is used for the optimization of the system. The results were analyzed for nine combinations of weights and show that for most of the cases the optimum includes coals from the Department of Cesar in Colombia. [ABSTRACT FROM AUTHOR]

This paper describes an optimization process implemented using Genetic Algorithms. The initial population of the GA is composed of 128 chromosomes with 11 genes per chromosome. The chromosomes of the GA are composed by the length and separations of the elements of the Yagi-Uda antenna; the ranks of this genes where chosen by design standards for such antennas. All genes undergo a process of analysis to assess every one of the antennas of each generation of the GA to assign the fitness of the individuals. In order to verify the obtained results, various tests were made, and among them excel the construction of the optimized Yagi-Uda antenna to measure and verify it electromagnetic characteristics. [ABSTRACT FROM AUTHOR]

To improve the quality of service in cell systems, techniques of Dynamic Assignment Channels are used to reduce the probability of blocking calls. In this paper an algorithm of assignment channels is required to reduce the probability of blocking, extending the system capacity to add new calls. This is obtained by using an interchange of channels of current calls and reducing the restrictions of electromagnetic compatibility. According to this, the algorithm has to provide solutions of commitments between two different objectives; on the one hand reduce the amount of assignments, and on the other to do the same with the level of interference due to the flexible restrictions of electromagnetic compatibility. A heuristic focus based on the evolution paradigm is presented to solve the multi-objective optimization problem. Two evolutionary multi-objective algorithms (SPEAII y NSGA II) are compared by the use of two different metrics. The results show that the proposed methodology can be applied to different generations of mobile communication systems. [ABSTRACT FROM AUTHOR]

In this paper, the design of a genetic algorithm that modifies and recalculates the values those describe the membership functions for a fuzzy controller, has showed. The controller is applied in a bio-film fermentative process to obtain an improvement in the dichromate's production (DCM). The membership functions act over the concentration of substrate in the aeration tank so that produces the homogenous double saturation kinetic of the DCM, and this is increased, obtaining an improvement in their production. This is shown by development of the numerical algorithm. [ABSTRACT FROM AUTHOR]

This paper presents a multi-objective optimization method which is an alternative solution for multicast networks load balancing, using a software implementation of the Simulated Annealing heuristic. The method minimize four basic parameters necessaries for guarantee the quality of service (QoS) in multicast transmissions, these are: end-to-end delay, maximum link utilization, bandwidth consumption and hop count. The results obtained by the heuristic will be compared with the results hurtled by the mathematical pattern proposed in previous investigations. [ABSTRACT FROM AUTHOR]

A study of the optimal pipe diameter selection, when in the system the pumped fluid is non newtonian, is made in this paper. For this case, the most used correlations are given. The application of this correlation is showed through two illustrative examples. [ABSTRACT FROM AUTHOR]