Browsing by Author "Zambrano Asanza, Sergio Patricio"

Now showing 1 - 11 of 11

Análisis del impacto en transitorios y niveles de tensión relacionados con la conexión de micro-redes eléctricas al sistema de distribución
(Universidad de Cuenca, 2017) Zambrano Asanza, Sergio Patricio; Espinoza Abad, Juan Leonardo
This article presents an analysis of the impact on the distribution system produced by the so-called micro-grids (micro-electric networks), supplied by small generation sources. Studies are developed in both steady state and dynamic state to obtain results that do not affect the network or consumers. The analysis is performed for photovoltaic, wind, diesel generator, gas generator, and mini-hydropower systems, which are part of the University of Cuenca’s micro-grid. The software used for this work was DIgSILENT PowerFactory, enabling the conduct of power flows and electromagnetic transients (EMT) studies. Technical impacts caused by the micro-grid on losses, voltage profiles, overhead lines when it is installed to the closer distribution network are detailed. Also, a sensitivity study is carried out to know if the distribution network is suitable for the interconnection of a micro-grid under the concept of Distributed Generation - GD.
Análisis del modelo común de datos eléctrico para la integración de sistema de manejo de la distribución mediante estándares internacionales
(2011) Zambrano Asanza, Sergio Patricio; Andrade Rodas, Juan Manuel
Coordinación gráfica de protecciones de sobrecorriente en sistemas radiales
(2001) Zambrano Asanza, Sergio Patricio; Montalvo Blacio, José Mauricio; Carrillo Torres, Hernán
Determinación del índice de electrificación mediante el procesamiento de imágenes satelitales para la zona rural del área de concesión de la Empresa Eléctrica Regional Centro Sur. C.A.
(Universidad de Cuenca, 2022-03-09) Paredes Cajamarca, Héctor Bayron; Tamayo Saquicela, Anghela Nicole; Sanango Fernández, Juan Bautista; Zambrano Asanza, Sergio Patricio
The importance of addressing the use of technological tools to solve problems facing society is becoming more and more evident. Among these problems is the determination of the electrification index, an indicator that allows measuring the level of access to electricity. In Ecuador, finding this metric is limited to census applications that are expensive and require a large number of staff. Thus, in the present work, Deep Learning was applied for the analysis of satellite images in the ArcGIS Pro software. The objective is to extract the traces of the houses in 18 parishes of the Cuenca canton as a representative sample of the rural concession area of the “Empresa Eléctrica Regional Centro Sur” (Centrosur). For this, it is proposed to work with Convolutional Neural Networks, using the Mask-RCNN model, obtaining results with an average precision of approximately 94% and an F1 Score of 84%. Finally, the metric corresponding to the electrification index is calculated and a comparison is made with the statistics provided by the “Instituto Nacional de Estadística y Censos” (INEC).
Estimación de la capacidad de alojamiento de generación solar fotovoltaica a través de una penetración masiva a nivel de consumidores en redes de distribución mediante simulación de flujos de carga con series de tiempo
(Universidad de Cuenca, 2023-07-27) Patiño Chitacapa, César Andrés; Zambrano Asanza, Sergio Patricio
The growing integration of distributed generation based on photovoltaic solar technology, connected in synchronism to the distribution network, constitutes a challenge for utility operations and planning. High penetration can have a negative impact on system performance, making it necessary to estimate hosting capacity. For this, the proposed methodology performs an analysis of adoption scenarios for generation by consumers, on which short circuits and power flows are simulated using time series that consider operational and regulatory restrictions, the current state of the system, and its equipment. Real and highresolution load profile information in the source node, voltage level of quality sensors, the existing control scheme, and characteristic data of loads per customer class are also considered. The generator's capacity is sized for each user based on their self-consumption, in accordance with current national regulations. Finally, the hosting capacity of a feeder integrating the medium and low voltage networks is defined based on impact criteria established in technical standards and regulatory frameworks to ensure that it does not pose a risk to the operation and does not compromise the quality and reliability of the network.
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.
Graph partitioning-based clustering for the planning of distribution network topology using spatial- temporal load forecasting
(Institute of Electrical and Electronics Engineers (IEEE), 2021) Cando Naula, Diego Jonnathan
Planning the expansion and the new topology of distribution networks requires knowing the location and characterization of the load as well as its future growth. Spatial load forecasting is a key tool in this task, providing high spatial resolution and adequate temporal granularity. Nowadays, with the penetration of distributed energy resources, multiple microgrid connection strategies, and implementation of self-healing and protection schemes, it is necessary to identify load blocks to plan the new active network architecture. Based on spatial load forecasting information, this paper proposes a graph partitioning technique to create load clusters in the distribution feeders. A weighted graph is constructed by means of a minimum spanning tree that allows to consider adjacency relations. The results of the simulation, carried out in a real distribution network, have demonstrated the effectiveness of the proposed method.
Integrating artificial neural networks and cellular automata model for spatial-temporal load forecasting
(2023) Franco, John Fredy
The long-term distribution planning should include an understanding of consumer behavior and needs to develop strategic expansion alternatives that meet the future demand. The magnitude of growth along with the place where and when it will be developed are determined by the spatial load forecasting. Thus, this paper proposes a spatial-temporal load forecasting method to recognize and predict development patterns using historical dynamics and determine the development of consumers and electric load in small areas. An artificial neural network is integrated to a cellular automaton method to establish transition rules, based on land-use preferences, neighborhood states, spatial constraints, and a stochastic disturbance. The main feature is the incorporation of temporality, as well as taking advantage of geospatial-temporal data analytics to calibrate and validate a holistic and integral framework. Validation consists of measuring the spatial error pattern during the training and testing phase. The performance of the method is assessed in the service area of an Ecuadorian power utility. The knowledge extraction from large-scale data, evaluating the sensitivity of parameters and spatial resolution was carried out in reasonable times. It is concluded that adequate normalization and use of temporality in the spatial factors improve the error in the spatial-temporal load forecasting.
Modelación y simulación de las redes de baja tensión de la Empresa Eléctrica Regional Centro Sur C.A
(2017) Cárdenas Cobos, José Geovanny; Jaramillo León, Brian Daniel; López Quizhpi, Julio César; Zambrano Asanza, Sergio Patricio
The present project makes the modeling and simulation of the low voltage networks of the Electrical Utility Centro Sur C.A, to estimate the technical losses and to analyze the impact of the incorporation of induction cookers in residential clients. The process of creating and validating the equipment (transformers, conductors, cables and structures) necessary for the modeling of secondary distribution networks is initially shown. Once the low voltage network is modeled, load flows are run of a representative group of low voltage networks are simulated, with the objective of analyzing the voltage profile, loadability in the lines and equipment, and mainly determining the technical losses produced in them, to finally extrapolate them to the entire low voltage system. In addition, a methodology is applied to evaluate the incorporation of electromagnetic induction cookers in five secondary distribution networks, simulating power flows by adding the load profile of the induction cooker to the residential clients of the secondary networks. Finally the conclusions and recommendations of the project are established.
Optimal subtransmission switching using a reliability simulation-based multi-objective optimization model
(2022) Banegas Dutan, Stalin Fernando
The growth of subtransmission network aims at satisfying load growth, maintaining a contingency level, and providing a high quality and reliable electricity service. Utilities direct the investments to reinforce this system and thus a meshed network with multiple-point feeding to the transmission system arises. At this point, an efficient alternative to achieve these objectives is to carry out a diagnosis of the network architecture and, taking advantage of the switching capability, to plan the switching of the subtransmission lines. An optimal subtransmission switching approach is proposed based on constrained multi-objective optimization that deals with energy losses and reliability, in addition to using information on the characteristics of loads and generation. A simulation-based optimization framework is constructed using the non-dominated genetic classification algorithm NSGA-II in the optimization phase and reliability assessment during simulation phase. As a result, a set of non-dominated solutions approximating the Pareto front is obtained, which allows the planner to make decisions based on its priorities and needs. The performance of the proposal is assessed with a real subtransmission system of an Ecuadorian power utility. This approach to the operational planning of a meshed subtransmission network constitutes a powerful decision-making tool that could be adopted by distribution utilities.
Proyección espacial de la demanda en la Empresa Eléctrica Regional Centro Sur C.A. mediante el método de simulación espacio-temporal
(2017) Chumbi Quito, Wilson Enrique; Patiño Chitacapa, César Andrés; Salgado Rodríguez, Modesto Enrique; Zambrano Asanza, Sergio Patricio; Quituisaca Astudillo, Patricio
The present study presents the process of a spatial load forecasting model based in a regular grid base, applied in response to a medium and long range planning problem of the Electrical Distribution System of the Regional Electric Company Centro Sur CA. The proposed forecast model consists of three main modules that correspond to the global, temporal, and spatial module. The global module controls the global development that is the sum of all developments in the region for every time step. The spatial module is pattern recognition used to identify a match between customers’ preferences and parcels regarding the characteristics of the land they are finding. The spatial module is based on several local, proximity, and surround factors for each land use classes, thus computing a continuous map of potential for development based on its local attributes, i.e. estimating the suitability of every small area for customer growth. The result of the spatial module is a map of potential for development based in small areas, where each small area has a preference based on influence factors. The temporal module determines the load curves and consumption per-capita for each type of customer set. The growth obtained from the global module is spread into the small areas with the highest preference over the geographical region, and then converted into electrical load with the temporal module. The result represents the effective development of consumer growth, thus defining the magnitude of the load in a specific area along each time stage.