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Technical efficiency of thermal power units through a stochastic frontier
(Universidad Nacional de Colombia, Facultad de Minas, 2015)
Marmolejo Saucedo, José Antonio
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Cedillo-Campos, Miguel Gastón
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Salazar-Martínez, María Soledad
This work presents a model to obtain a stochastic frontier production function of a Mexican power generation company. The stochastic frontier allows us to evaluate the technical efficiency of an energy producer according of the level of inputs. Electricity generation based on thermal generation is highly expensive due to operational inefficiency of thermal power plants. At the moment, in Mexico, technical efficiency of thermal power units has not been studied for the national electricity system. Therefore, in order to know the productivity levels of thermal generation, an empirical application of the stochastic frontier model is obtained using a panel data of thermoelectric units from the Mexican electricity system for the 2009-2013. © The author; licensee Universidad Nacional de Colombia
Scopus© Citations 1 9
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Short-term generation planning by primal and dual decomposition techniques
(Universidad Nacional de Colombia, Facultad de Minas, 2015)
Marmolejo Saucedo, José Antonio
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This paper addresses the short-term generation planning (STGP) through thermoelectric units. The mathematical model is presented as a Mixed Integer Non Linear Problem (MINLP). Several works on the state of art of the problem have revealed that the computational effort of this problem grows exponentially with the number of time periods and number of thermoelectric units. Therefore, we present two alternatives to solve a STGP based on Benders’ partitioning algorithm and Lagrangian relaxation in order to reduce the computational effort. The proposal is to apply primal and dual decomposition techniques, which exploit the structure of the problem to reduce solution time by decomposing the STGP into a master problem and a subproblem. For Benders’ algorithm, the master problem is a Mixed Integer Problem (MIP) and for the subproblem, it is a Non Linear Problem (NLP). For Lagrangian relaxation, the master problem and the subproblem are MINLP. The computational experiments show the performance of both decomposition techniques applied to the STGP. These techniques allow us to save computation time when compared to some high performance commercial solvers. ©Universidad Nacional de Colombia: Facultad de Minas, Los autores.
Scopus© Citations 2 7
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Fat Tail Model for Simulating Test Systems in Multiperiod Unit Commitment
(2015)
Marmolejo Saucedo, José Antonio
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This paper describes the use of Chambers-Mallows-Stuck method for simulating stable random variables in the generation of test systems for economic analysis in power systems. A study that focused on generating test electrical systems through fat tail model for unit commitment problem in electrical power systems is presented. Usually, the instances of test systems in Unit Commitment are generated using normal distribution, but in this work, simulations data are based on a new method. For simulating, we used three original systems to obtain the demand behavior and thermal production costs. The estimation of stable parameters for the simulation of stable random variables was based on three generally accepted methods: (a) regression, (b) quantiles, and (c) maximum likelihood, choosing one that has the best fit of the tails of the distribution. Numerical results illustrate the applicability of the proposed method by solving several unit commitment problems.
Scopus© Citations 9 20
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Design of a Distribution Network Using Primal-Dual Decomposition
(2016)
Marmolejo Saucedo, José Antonio
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Cruz-Mejía, Oliverio
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Saucedo-Martínez, Jania Astrid
A method to solve the design of a distribution network for bottled drinks company is introduced. The distribution network proposed includes three stages: manufacturing centers, consolidation centers using cross-docking, and distribution centers. The problem is formulated using a mixed-integer programming model in the deterministic and single period contexts. Because the problem considers several elements in each stage, a direct solution is very complicated. For medium-to-large instances the problem falls into large scale. Based on that, a primal-dual decomposition known as cross decomposition is proposed in this paper. This approach allows exploring simultaneously the primal and dual subproblems of the original problem. A comparison of the direct solution with a mixed-integer lineal programming solver versus the cross decomposition is shown for several randomly generated instances. Results show the good performance of the method proposed.
Scopus© Citations 8 10
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A proposed method for design of test cases for economic analysis in power systems
(Universidad Nacional Autónoma de México, Instituto de Ciencias Aplicadas y Tecnología, 2015)
Marmolejo Saucedo, José Antonio
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Nowadays, in power systems, we still lack the existence of standardized test systems that can be used to benchmark the performance and solution quality of proposed optimization techniques. Several authors report that the electric load pattern is very complex. It is therefore necessary to develop new methods for design of test cases for economic analysis in power systems. Therefore, we compared two methods to generate test systems: time series model and a method simulating stable random variables based on the use of Chambers-Mallows-Stuck. This paper describes a method for simulating stable random variables in the generation of test systems for economic analysis in power systems. A study focused on generating test electrical systems through stable distribution to model for unit commitment problem in electrical power systems. Usually, the instances of test systems in unit commitment are generated using normal distribution, but the behavior of electrical demand does not follow a normal distribution; in this work, simulation data are based on a new method. For empirical analysis, we used three original systems to obtain the demand behavior and thermal production costs. Numerical results illustrate the applicability of the proposed method by solving several unit commitment problems directly and through the Lagrangian relaxation of the original problem. All Rights Reserved © 2015 Universidad Nacional Autónoma de México, Centro de Ciencias Aplicadas y Desarrollo Tecnológico. This is an open access item distributed under the Creative Commons CC License BY-NC-ND 4.0.
Scopus© Citations 2 15
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Foreword : Nature-Inspired Intelligent Techniques for Solving Biomedical Engineering Problems
(IGI Global, 2018)
Marmolejo Saucedo, José Antonio
Nature-Inspired Intelligent Techniques for Solving Biomedical Engineering Problems is a pivotal reference source for emerging scholarly research on trends and techniques in the utilization of nature-inspired approaches in biomedical engineering. Featuring extensive coverage on relevant areas such as artificial intelligence, clinical decision support systems, and swarm intelligence, this publication is an ideal resource for medical practitioners, professionals, students, engineers, and researchers interested in the latest developments in biomedical technologies.©2018.
12 2
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Data analysis and optimization for engineering and computing problems : Preface
(Springer Science and Business Media Deutschland GmbH, 2019)
Marmolejo Saucedo, José Antonio
This book presents the proceedings of The EAI International Conference on Computer Science: Applications in Engineering and Health Services (COMPSE 2019). The conference highlighted the latest research innovations and applications of algorithms designed for optimization applications within the fields of Science, Computer Science, Engineering, Information Technology, Management, Finance and Economics and Health Systems. Focusing on a variety of methods and systems as well as practical examples, this conference is a significant resource for post graduate-level students, decision makers, and researchers in both public and private sectors who are seeking research-based methods for modelling uncertain and unpredictable real-world problems. ©2020, Springer Science and Business Media Deutschland GmbH.
10 2
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Importance of organizational structure for TQM success and customer satisfaction
(2019)
García-Alcaraz, Jorge Luis
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Flor Montalvo, Francisco Javier
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Sánchez-Ramírez, Cuauhtémoc
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Avelar-Sosa, Liliana
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Marmolejo Saucedo, José Antonio
This paper reports a structural equation model to relate three critical success factors for total quality management (TQM) (i.e. managerial commitment, role of quality department, and quality policies) with customer satisfaction benefits through six hypotheses, which are statistically tested with information from 398 responses to a survey applied to Mexican manufacturing industry and using partial least squares technique integrated in WarpPLS v.6 software. The paper also reports a sensitivity analysis based on conditional probabilities for analyze low and high scenarios. Findings indicate that managerial commitment is the most important variable to ensure TQM, yet it depends on the role of the quality department for deploy quality policies and guarantee customer satisfaction. Similarly, sensibility analysis demonstrate that high levels of managerial commitment always guarantee a high performance in quality departments and good quality policies, thereby contributing to customer satisfaction. From this perspective, there are statistical evidence to declare that managers and operators are the main facilitators of TQM success.
Scopus© Citations 21 40 2
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A Genetic Algorithm to Solve Power System Expansion Planning with Renewable Energy
(2018)
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Marmolejo Saucedo, José Antonio
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Ramírez, Juan Manuel
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Hernández, Agustina
In this paper, a deterministic dynamic mixed-integer programming model for solving the generation and transmission expansion-planning problem is addressed. The proposed model integrates conventional generation with renewable energy sources and it is based on a centralized planned transmission expansion. Due a growing demand over time, it is necessary to generate expansion plans that can meet the future requirements of energy systems. Nowadays, in most systems a public entity develops both the short and long of electricity-grid expansion planning and mainly deterministic methods are employed. In this study, an heuristic optimization approach based on genetic algorithms is presented. Numerical results show the performance of the proposed algorithm. © 2018, Springer Nature Switzerland AG.
Scopus© Citations 1 34 1
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Analysis of Constraint-Handling in Metaheuristic Approaches for the Generation and Transmission Expansion Planning Problem with Renewable Energy
(2018)
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Ramírez, Juan Manuel
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Marmolejo Saucedo, José Antonio
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Hernández, Agustina
A multiperiod generation and transmission expansion planning (G&TEP) problem is considered. This model integrates conventional generation with renewable energy sources, assuming a stochastic approach. The proposed approach is based on a centralized planned transmission expansion. Due to the worldwide recent energy guidelines, it is necessary to generate expansion plans adequate to the forecast demand over the next years. Nowadays, in most energy systems, a public entity develops both the short and long of electricity-grid expansion planning. Due to the complexity of the problem, there are different strategies to find expansion plans that satisfy the uncertainty conditions addressed. We proposed to address the G&TEP problem with a pure genetic algorithm approach. Different constraint-handling techniques were applied to deal with two complex case studies presented. Numerical results are shown to compare the strategies used in the test systems, and key factors such as a prior initialization of population and the estimated minimum number of generations are discussed. ©2018, Wiley/Hindawi.
Scopus© Citations 6 12 1

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