Person:
Torres Contreras, Santiago Patricio

Birth Date

1973-09-29

ORCID

0000-0002-8803-6811

Scopus Author ID

57192268040

Afiliación

Universidad de Cuenca, Cuenca, Ecuador
Universidad de Cuenca, Departamento de Ingeniería Eléctrica, Electrónica y Telecomunicaciones(DEET), Cuenca, Ecuador
Universidad de Cuenca, Facultad de Ingeniería, Cuenca, Ecuador

País

Ecuador

Organizational Units

Organizational Unit

Facultad de Ingeniería

La Facultad de Ingeniería, a inicios de los años 60, mediante resolución del Honorable Consejo Universitario, se formalizó la Facultad de Ingeniería de la Universidad de Cuenca, conformada por las escuelas de Ingeniería Civil y Topografía. Esta nueva estructura permitió una mayor especialización y fortalecimiento en áreas clave para el desarrollo regional. Cuenta con programas académicos reconocidos internacionalmente, que promueven y lideran actividades de investigación. Aplica un modelo educativo centrado en el estudiante y con procesos de mejora continua. Establece como prioridad una educación integra, la formación humanística es parte del programa de estudios que complementa a la sólida preparación científico-técnica. Las actividades culturales pertenecen a un programa permanente y activo al interior de nuestras dependencias, a la par de proyectos que desde el alumnado y bajo la supervisión de docentes cumplen con servicios de apoyo a nivel local y regional; promoviendo así una vinculación estrecha con la comunidad.

Job Title

Profesor (T)

Last Name

Torres Contreras

First Name

Santiago Patricio

Full item page

Search Results

Now showing 1 - 10 of 10

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.
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
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.
Service restoration in distribution systems considering priority customers and microgrids
(2024) Ochoa Correa, Danny Vinicio; Campoverde Encalada, Eduardo Luis; Torres Contreras, Santiago Patricio
Service restoration (SR) consists of automatically generating and executing a plan to restore the service in healthy zones using the least number of maneuvers after detecting and isolating a permanent fault in the distribution system zone. This component is essential to self-healing functionality in smart grids and allows customers to reconnect quickly to the distribution grid after a power outage. Distributed generation (DG) supports the distribution network when there is insufficient capacity to restore all zones out of service or supply the loads locally through microgrids. The power supply must be restored to the highest priority customers in case of partial restoration. Also, most research works use simplified or linearized models to propose restoration algorithms. This paper proposes a complete AC formulation for the service restoration problem in distribution systems considering network reconfiguration (NR), the integration of distributed generation (DG), and priority customers (PCs) into the solution. The optimization problem is solved by a centralized algorithm based on combining the Differential Evolution (DE) and Continuous Population-Based Incremental Learning (PBILc) metaheuristics techniques. Simulation results are presented for three case studies in which the IEEE 33-bus distribution system is tested for different fault scenarios. The numerical results show the robustness and efficiency of the proposed algorithm.
Unified AC transmission expansion planning formulation incorporating VSC-MTDC, FACTS devices, and reactive power compensation
(2023) De Araújo, Anderson Ricardo Justo; Torres Contreras, Santiago Patricio; Pissolato Filho, José; Castro, Carlos; Van Hertem, Dirk
The main aim of the static Transmission Network Expansion Planning (TNEP) is to determine which and where new transmission equipment must be installed. The complexity added by the non-linearities leads to simplifications, which include the DC model. However, most non-linearities are solvable nowadays. Thus, the new scenario of large non-dispatchable power sources penetration and the several developments in technologies, e.g, Flexible AC Transmission Systems (FACTS) devices and High Voltage Direct Current (HVDC) interconnections, motivate the use of the AC model with its non-linearities. Some research works address the use of some of those technologies for TNEP in an independent fashion, which can lead to sub-optimal solutions. In this work, Voltage Source Controlled-Multiterminal HVDC (VSC-MTDC) systems, FACTS devices, and Reactive Power Planning (RPP) are integrated into the same planning optimization process, so that a unified AC TNEP formulation is proposed. A non-linear mathematical programming technique and a differential evolution based metaheuristics are chosen to achieve an optimal transmission configuration. To evaluate the benefits of the proposed approach, two IEEE modified test systems (9 and 118 buses) are used. Results suggest that more economical solutions can be obtained if different types of reinforcement strategies are taken into account in a unified approach.
Improving the AC transmission expansion planning by using initial solutions algorithms
(IEEE Computer Society, 2020) Matute, Nelson; Flores, Wilfredo; López Quizhpi, Julio César; Astudillo Salinas, Darwin Fabián; Morquecho, Edgar; Torres Contreras, Santiago Patricio
Initial Solutions (IS) are decisive in meta-heuristics based optimization problems since they impact the performance of the optimization process. This research work proposes and compares some random and deterministic algorithms to create initial solutions based on existing expansion planning criteria to solve the AC Transmission Expansion Planning (TEP) problem. The TEP is formulated as a full non-convex optimization problem using the AC network representation. A local version of the Particle Swarm Optimization (LPSO) technique is employed to solve the TEP problem. The Garver 6-bus and IEEE 24-bus test systems are used to evaluate the IS algorithms performance. It is shown that these algorithms have great potential to improve the robustness and computational effort of meta-heuristics.
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.
Transmission expansion planning considering the impact of distributed generation
(Institute of Electrical and Electronics Engineers Inc., 2019) Matute Alvarado, Nelson Esteban; Torres Contreras, Santiago Patricio; Castro, Carlos Alberto
Distributed Generation (DG) is a very important alternative to the traditional approach of centralized generation and plays a major role not only in electric distribution systems but also in transmission systems. The incidence of DG in the electrical system (sub-transmission and/or distribution) could defer the addition of new transmission circuits and reduce transmission network losses, representing potential economical savings. This paper studies the economic impact of DG on the Transmission Expansion Planning (TEP) problem including also the cost of transmission network losses. A long-term deterministic static transmission expansion planning using the mathematical AC model is presented. DG is modeled as the summation of each type of small-scale generation technology concentrated in the load node. The proposed TEP approach provides information on the optimal combination of transmission circuits and DG in load nodes. The problem, formulated using the AC model, corresponds to a full non convex, non-linear mixed-integer programming (MINLP) problem. Performance comparisons between Particle Swarm Optimization (PSO) and Artificial Fish Swarm Algorithm (AFSA), to solve the problem, are shown. Garver 6 - bus and IEEE 24 - bus test systems are used to evaluate this TEP approach.
Integrated AC/DC transmission expansion planning model considering VSC-MTDC systems
(IEEE Computer Society help@computer.org, 2018) Torres Contreras, Santiago Patricio
Significant technological advances in the electric sector have led to complexity increase and created new challenges to transmission expansion planners. On the one hand, the increasing penetration of renewable energy sources impacts the entire network. On the other hand, DC systems have become a favorable and viable option to link some of these sources of energy to the consumer centers. Thus, new models of the network equipment must be incorporated to the Transmission Expansion Planning (TEP) model to take such changes into account in a more accurate way. This research work aims to include AC and multi-terminal DC transmission lines as candidates in the expansion planning process. The AC network model is used and shunt compensation is also taken into account to allow more flexibility to the expansion options. The TEP problem is solved using a combination of nonlinear programming and differential evolution (DE). The results obtained using a 9-bus test network and a modified IEEE-118 bus show the feasibility of this approach.
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.