Browsing by Author "Torres Contreras, Santiago Patricio"

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AC dynamic transmission expansion planning using a hybrid optimization algorithm
(IEEE Computer Society, 2020) Morquecho, Edgar; Torres Contreras, Santiago Patricio; Matute, Nelson; Astudillo Salinas, Darwin Fabián; López Quizhpi, Julio César; Flores, Wilfredo
Dynamic Transmission Expansion Planning (DTEP) seeks to answer where, how many, and when new infrastructure should be added to the electrical system. The goal is to allow a correct and efficient operation along the planning horizon. In this research work, a load shedding formulation extended for the multistage alternating current (AC) model with the co-optimization of shunt compensation is proposed. A novel hybrid meta-heuristic is used as optimization technique to solve the DTEP problem. Solutions were obtained from IEEE 24-bus test system. For comparative purposes, the problem was also solved using static (STEP) and quasi-dynamic (QTEP) approaches.
AC transmission expansion planning considering uncertainty
(Institute of Electrical and Electronics Engineers Inc., 2019) Castro, Carlos Alberto
© 2019 IEEE. Taking into account uncertainty into the Transmission Expansion Planning (TEP) problem is an important and complex issue. So far, the literature has proposed only simplified models in order to solve this problem. In this research work, a formulation and solution method to solve the Transmission System Expansion Planning problem considering uncertainty and using the AC network model is proposed. A simheuristic technique that combines simulation with an Ant Colony Optimization algorithm is used. The Montecarlo Simulation (MS) technique to handle the stochastic behavior of demand and generation, and the Ant Colony Optimization algorithm for continuous domains (ACOR) to find the optimal solution of the problem were employed. The results were obtained for different test scenarios on the Garver 6-bus and the IEEE 24-bus test systems.
AC transmission network expansion planning considering losses
(Institute of Electrical and Electronics Engineers Inc., 2018) Morquecho Salto, Edgar Gonzalo; Torres Contreras, Santiago Patricio; Espinoza Abad, Juan Leonardo; Lopez Quizhpi, Julio César; Quizhpe Huiracocha, Klever Leonardo; Sempertegui Álvarez, Rodrigo Efraín; Solano Quinde, Lizandro Damián; Espinoza Abad, Juan Leonardo
This paper proposes to solve the transmission network expansion planning problem (TNEP) using the AC model formulated with full non-linear load flow equations, incorporating the cost of losses in the transmission network. Additionally, the decomposed formulation finds the location and amount of the reactive compensation needed in the system. A comparison between Evolutionary Programming (EP) and a variation of EP with a Cultural Algorithm (CEP) is presented to solve this very complex optimization problem. The results are obtained using Garver's 6-bus test system and IEEE 24-bus test system. Index Terms-AC model, Cultural Algorithm, Evolutionary Programming, Optimization, Transmission network expansion planning.
Algoritmo neuro-difuso para la detección y clasificación de fallas en líneas de transmisión eléctrica del sistema ecuatoriano usando simulaciones y datos de registradores de fallas
(2012) Alvarado Guichay, Efrén Vinicio; Torres Contreras, Santiago Patricio
An efficient hybrid metaheuristics optimization technique applied to the AC electric transmission network expansion planning
(2021) Morquecho Salto, Edgar Gonzalo; Torres Contreras, Santiago Patricio; Castro, Carlos A.
The transmission network expansion planning (TNEP) problem consists of determining the necessary infrastructure additions, within a planning horizon, to minimize an investment objective function while meeting some operational and physical constraints. Even using simplified models to represent the electric network, the TNEP becomes a very complex, combinatorial and non-convex optimization problem. In recent years, the full alternating current (AC) network model has been proposed to formulate the TNEP problem. Due to its complexity, more robust and efficient optimization techniques to solve the AC formulation are required. This paper proposes a new effcient hybrid metaheuristic technique to solve the TNEP problem. Additionally, it presents a comprehensive comparative study including different powerful conventional, emerging and hybrid optimization metaheuristics techniques applied to solve the static, long-term TNEP problem, using the AC model, considering both operating and reactive power compensation costs. Simulation results are shown for three test systems: Garver 6-bus system, IEEE 24-bus system and the IEEE 118-bus system.
Análisis de conductores de alto desempeño (HPC y HTLS) en la expansión de sistemas de transmisión de energía eléctrica
(Universidad de Cuenca, 2025-09-25) Barrionuevo Ortega, Daniel Enrique; Torres Contreras, Santiago Patricio
The sustained growth in electricity demand and the technical limitations of transmission networks have driven the need for innovative technologies that enhance system efficiency and reliability without requiring major infrastructure investments. In this context, high-performance conductors (HTLS) emerge as a viable alternative to conventional ones, as they allow operation at higher temperatures without compromising mechanical stability or operational safety. This thesis evaluates the incorporation of HTLS conductors in power system expansion through a comparative technical-economic approach using three representative test systems. To solve the expansion planning problem, a metaheuristic was implemented in combination with an AC optimal power flow model using MATPOWER. The selection of candidate lines was based on technical and economic criteria, and scenarios with different cost proportions for HTLS conductors were analyzed to assess the feasibility of their implementation and the potential advantages they could bring to the grid, such as reducing investment costs or increasing system loadability.
Análisis de factibilidad del uso de unidades de procesamiento gráfico en algoritmos de optimización meta-heurísticos
(Universidad de Cuenca, 2020-10-16) Guiracocha Yuquilima, Manuel Mesias; Astudillo Salinas, Darwin Fabián; Torres Contreras, Santiago Patricio
Currently, several real-world optimization problems have been mathematically modeled. The modeling process takes into account as much information as possible so that the model obtained is as close to reality. However, as information increases, complexity also increases. Consequently, larger computational capacity is needed to solve complex and scalable problems. Exact or mathematical optimization methods are considered exhaustive, which for multi-dimensional problems is not practical. As a result, meta-heuristic algorithms have been developed to solve complex optimization problems. These algorithms are commonly used for problems of two or more dimensions, involving vector and matrix operations. Therefore, to solve this type of problem, it is useful to carry out parallel processes that reduce the runtime. Currently, there are multi-core CPU that can easily solve small problems with parallel calculations. However, the GPU offers the potential to improve performance by incorporating a larger number of cores than the CPU, which is very useful for problems with multiple processes in parallel. A classic problem in the electrical power systems research community is the Transmission Expansion Planning (TEP). In the Department of Electrical, Electronics, and Telecommunications Engineering, in the project “Use of the AC model for multi-stage integrated planning of transmission / sub-transmission line expansion and reactive power sources in electric power systems”, It is tried to improve the performance of the TEP problem. The project seeks to reduce the calculation time by improving the meta-heuristic algorithms. In this final d egree p roject, a s a c omplement t o the aforementioned project, the feasibility of reducing the execution time was analyzed, implementing the meta-heuristic algorithms using a GPU. For which, prior to the implementation of the TEP problem, the use of the GPU in parallelizable problems and the implementation of a meta-heuristic algorithm in a two-dimensional problem were analyzed, in which favorable results have been obtained to motivate the use of the GPU
Análisis del impacto de la inserción de un sistema de generación distribuida en el alimentador 0427 ubicado en el Complejo Hidroeléctrico Machángara
(2019-04-26) Cuzco Tenempaguay, Mauro Xavier; Torres Contreras, Santiago Patricio; Sarmiento Vintimilla, Juan Carlos
Análisis estadístico de resultados de pruebas eléctricas y rediseño de protecciones para motores de sistemas auxiliares de la Central Molino según la norma IEEE Std C37.96-2012
(2019-04-25) Romero Mosquera, Valeria del Cisne; Torres Contreras, Santiago Patricio; Chalco Cando, Joffre Alexis
The objective of this thesis work is to analyze the behavior of the insulation resistance of the induction motors of the auxiliary systems of the Molino Hydroelectric Power Station, to determine the state of the insulation according to the IEEE Std 43-2013 standard and to carry out the study of the redesign of protections according to the IEEE Std C37.96-2012 standard. In this context, the HIDROPAUTE Business Unit, part of the Electric Corporation of Ecuador CELEC EP, in charge of the operation and maintenance of the Mill Plant, has been considered as a population or object of study the 10 generation units that it has, originating as sample two units one for each construction phase, being called U05 for phase AB and U06 for phase C. By means of a descriptive statistical analysis of the current state of the isolation and its tendency in time, it is intended to establish if it is feasible that the engines can continue operating or it is necessary to replace them, in order to guarantee the operational reliability of the plant's systems. On the other hand, the redesign of the protections for the induction motors of the auxiliary systems was carried out according to the IEEE Std C37.96-2012 standard, however the recommendations of the IEEE Std 242-2001 standard were also taken, with the purpose to realize a system of protections according to the needs of the plant, and thus avoid unavailability in it due to a generated failure.
Aplicación de aprendizaje por refuerzo en la planificación de la expansión de los sistemas de transmisión
(Universidad de Cuenca, 2025-09-18) Llivisaca Mejia, Mateo David; Astudillo Salinas, Darwin Fabian; Torres Contreras, Santiago Patricio
Transmission Expansion Planning (TEP) is, from a mathematical point of view, a complex optimization problem and, in practice, a key tool for planning the efficient growth of the Electric Power System (EPS). With the constant increase in demand and generation capacity, if the transmission bottleneck is not solved, a proper operation of the system cannot be guaranteed. In this research, Reinforcement Learning (RL) is applied to solve the TEP through three approaches: the use of Q-learning, a learning-guided metaheuristic and deep reinforcement learning. In this framework, both Q-learning and RL-based metaheuristics learn online and use that knowledge locally. On the other hand, deep reinforcement learning methods, such as Deep Q-Network (DQN) and REINFORCE, allow reusable general policies to be learned, although they require a better representation of the state. This is achieved by modeling the power grid as a complex network and evaluating nodes using centrality-based metrics. The results show that the use of RL in the metaheuristic improves the exploration of the solution space. As for the deep learning approach, this first approach offers promising results: although in some cases optimal topologies are not reached, feasible plans are obtained that can serve as initial solutions in classical optimization schemes.
Comparación de algoritmos basados en bio-geografía aplicados al planeamiento de la expansión de los sistemas eléctricos de transmisión usando el modelo AC
(2016) Chillogalli Astudillo, José Eduardo; Torres Contreras, Santiago Patricio
The Transmission Expansion Planning (TEP) consists in determining the future adequacies of the transmission network in order to meet the requirements of increasingdemand and new generation projects, satisfying quality, safety, reliability and economycriteria. In this research work, a solution method for the TEP problem using the alternating current model (AC) of transmission network has been implemented. Applying this model to the TEP problemmakes it a non-linear programming, mixed-integer (PNLIM) quite complex problem to be solved by classical optimization techniques. Therefore, four variations of the optimization algorithm based on Bio-Geography (BBO)have been implementedin order to make possible the use of AC model in the TEP problem. The performance of the algorithms based on Bio-Geography was validated in different test scenarios on the Garver 6-nodes system and the IEEE 24-nodes system.
Comparación de técnicas de creación de soluciones iniciales usando el modelo AC y el algoritmo meta-heurístico Firefly para resolver el problema de planeamiento óptimo de la expansión del sistema de transmisión
(2018) Espinoza Loja, Fausto Santiago; Torres Contreras, Santiago Patricio
The Planning of the Expansion of the Transmission System (PET) has the purpose of determining a future infrastructure for the transmission network, which is capable of meeting the requirements of the growth of the demand, fulfilling the criteria of quality, safety, reliability and economy. In this research work it is proposed to implement and compare different methods of initial solution creation techniques (random, pseudo-random, Sobol sequence, based on opposites) implemented in the Firefly optimization technique to solve the (PET) problem using the model AC. The algorithms were validated in the Garver and IEEE test systems of 6 and 24 nodes respectively. In addition, the performance of these techniques is also compared using the particle swarm optimization algorithm.
Comparison of an Improved Metaheuristic and Mathematical Optimization Based Methods to Solve the Static AC TNEP Problem
(2023) Morquecho Salto, Edgar Gonzalo; Torres Contreras, Santiago Patricio; Astudillo Salinas, Darwin Fabián
The complexity of current and future electricity networks demands the use of more accurate models to solve the Transmission Network Expansion Planning (TNEP) problem. To deal with this issue, formulations based on AC network equations have been proposed by the research community. Although the AC formulations exist, they do not work with problems with a large number of candidate transmission paths, different planning scenarios due to convergence issues or infeasible solutions. Also, it has been difficult for the power system community to be aware of the real advantages and disadvantages of the existing approaches due to the lack of rigorous and fair comparisons among them. In this research work, a full non-convex AC formulation to solve the TNEP problem is proposed. It considers in an integrated fashion reactive power expansion, the contingency criterion and operational costs. The formulation is solved by an improved non-convex optimization algorithm in a two-stage approach. Also, a fair and rigorous quantitative and qualitative comparison among the proposed approach and other state-of-art metaheuristics and mathematical programming methods has been performed. Simulation results show that the proposed formulation and solution method are superior to other approaches with respect to reliability and suitability for cases with large search spaces and different scenarios. Results are shown for four test systems, namely the Garver 6-bus system, the IEEE 24-bus system, the IEEE 118-bus system, and a modified version of the IEEE 300-bus system. IEEE
Detección de áreas débiles respecto a la estabilidad de tensión en tiempo real utilizando lógica difusa
(2013) Samaniego Rojas, Eduardo Mauricio; Torres Contreras, Santiago Patricio
Diagnóstico del estado de los transformadores de potencia de las Centrales Molino y Mazar basado en análisis de aceite
(2016) Rivera Gutiérrez, Luis Xavier; Sucozhañay Morocho, Abraham Santiago; Torres Contreras, Santiago Patricio; Marín Roman, Jonathan Francisco
This thesis aims to provide technical information to the CELEC EP – HIDROPAUTE Company. This information will let the company update the power transformers predictive maintenance plan of theMazar and Molino power stations. The emphasis of this work is put on the dielectric oil, which is a vital component for the correct operation of the transformer. First of all, a theoretical basis about the power transformer and the types of maintenance performed on this equipment was established; also,the physicochemical characteristics and the dissolved gases on the dielectric oil were studied. In addition, the types of faults that could appear in oil and their diagnostic methods were explained. After that, statistical analysis of physicochemical data and dissolved gaseswere performed in order to obtain an estimation of the performance curve and trend charts. The obtained information was entered into the TOA (Transformer Oil Analyst) computer application in order to get a diagnostic of the oil transformer condition. This task was performed based on IEEE and IEC international standards. Finally,a comparison between the laboratory results and those issued by the Perception online software of the transformer U04 was presented.Conclusions and recommendations were obtained based on the previous analyses.
Diseño y Construcción de un analizador de espectros de frecuencia de hasta 1 MHz
(1998) Segarra Espinoza, Raúl; Torres Contreras, Santiago Patricio; Doutreloigne, Jan
Distributed State Estimation Through Nodal Redundancy in EPS
(IEEE, 2024) Torres Contreras, Santiago Patricio; Moyano Bojorque, Henrry Fernando; Moyano Bojorque, Henrry Fernando
This research work proposes a robust methodology for partitioning electrical systems within the distributed estimation framework, using the principle of nodal redundancy. The approach employs measurements from the electrical system’s nodes. This method’s application involves a comparative analysis between centralized estimation and the proposed technique, using the IEEE 14-bus system as the benchmark. The findings underscore the efficacy of the quality of the estimation and the computational efficiency achieved through this novel methodology.
Evaluación del balance energético en el Sur del Ecuador mediante el modelo de optimización de los sistemas energéticos urbanos (URBS)
(Universdidad de Cuenca, 2023-06-05) Guamán Paguay, Juan Carlos; Torres Contreras, Santiago Patricio
As the share of renewables has grown to high penetration in some countries, flexibility options have become vital to ensure a reliable and sustainable power system. Energy modeling provides the qualitative and quantitative knowledge needed for future energy system planning and operation. Ecuador already has a large percentage of renewable energy due to its large hydroelectric potential, however, overdependence on this resource must be avoided through good energy planning, balancing resources and available technologies. This study performs an energy balance using the urbs modeling framework to evaluate the possibility of creating a diversified and clean energy mix that can supply the projected future demand in southern Ecuador, taking into account technical and economic criteria for each type of technology available. The results show that it is possible to achieve a decentralized energy mix based mostly on renewable energies with an energy contribution of 85.43% with hydroelectric power plants, 9.3% with renewable energy power plants (biomass, wind and solar), 4.71% with natural gas power plants and only 0. In addition, it is observed that investment in renewable energy generation can significantly reduce the use of technologies based on fossil fuels, which implies a reduction in fuel use of up to 70% and a 27% reduction in CO2 emissions.
Evaluación inversa de la confiabilidad del sistema de distribución de la Empresa Eléctrica Regional Centro Sur C.A.
(Universidad de Cuenca, 2021-10-29) Agudo Guiracocha, Milton Patricio; Tenesaca Caldas, Marcelo Sebastián; Torres Contreras, Santiago Patricio; Zambrano Asanza, Sergio Patricio
Generally, the reliability evaluation is approached by finding the reliability indices, from the reliability parameters of the components that make up the electrical system. This article addresses the problem in reverse, finding the unknown parameters from the system indexes, this is called the IRE (Inverse Reliability Evaluation) problem. The IRE problem model is formulated and solved using a system of non-linear equations. Granularity is added to the problem by dividing the feeders into reliability zones using an outage log. For this, an algorithm has been implemented in Python, with the help of the DIgSILENT PowerFactory software. In order to verify the effectiveness of the model and the solution method, these are implemented in 3 substations of the Empresa Eléctrica Regional Centro Sur C. A.
Impacto de la generación distribuida en el planeamiento de la expansión de los sistemas de transmisión
(2018) Matute Alvarado, Nelson Esteban; Torres Contreras, Santiago Patricio
The Transmission System Expansion Planning (TEP) consists of determining the optimal topology of the transmission network which goal is to satisfy the electrical demand projected in a certain time horizon. The optimal plan is obtained by minimizing the investment costs of transmission infrastructure and fulfilling all the technical requirements of the electrical system. Currently, technological developments have significantly reduced the investment costs of Distributed Generation (DG), which allows this new approach to be an alternative to the traditional approach of centralized generation. The incidence of GD in the electrical system could avoid the addition of new transmission circuits, which, in turn, could help to defer investments in the electrical system representing a possible saving. This work studies the economic impact of DG on TEP considering a long-term static planning (10 years) and using the mathematical AC model. The TEP, using the AC model, corresponds to a non-linear mixed-integer programming (MINLP) problem which is solved by the meta-heuristic that presents the best performance: Tabu Search (TS) and Artificial Fish Swarm Algorithm (AFSA). The results are obtained using Garver 6 - buses and IEEE 24 - buses test systems. DG is modeled as the summation of each type of small-scale generation technology concentrated in the distribution node.