Instituto Tecnológico de Morelia

About: Instituto Tecnológico de Morelia is a education organization based out in Morelia, Mexico. It is known for research contribution in the topics: Electric power system & AC power. The organization has 498 authors who have published 572 publications receiving 4600 citations.

Multi-objective expansion planning approach: distant wind farms and limited energy resources integration

Abstract: This study presents a multi-objective framework to evaluate the integration of distant wind farms with associated transmission network upgrades on optimal power system planning. The presented approach also extends the technique to include the consideration of energy limitations associated with the installed hydro generation facilities. This study attempts to emphasise on the reliability implications rather than the production cost evaluation aspects. The decision making is based on hierarchal level II (HL-II) Expected Energy Not Served as an entire power system reliability assurance, and capital cost plus annual operational cost as an economical index. Non-dominated Sorting Genetic Algorithm is adopted to achieve the Pareto front of the aforementioned multi-objective problem. A fuzzy satisfying method, designated as the distance metric, is used to represents a trade-off between different objectives. To numerically evaluate the efficiency of the proposed method, simulation results on three case studies are provided. In spite of huge computation burden at HL-II reliability assessment, the results indicate high efficiency of the proposed method.

A survey on modeling, biofuels, control and supervision systems applied in internal combustion engines

Abstract: In this work, we present a survey on different topics related to Internal Combustion (IC) engines. The purpose of this work is to show the evolution on modeling, use of biofuels, simulation and/or implementation of different types of control laws applied to the IC engines. In the modeling section, we present a classification of the IC engines models according to their type; in this classification linear, nonlinear, and based on Neural Networks (NN) models are included. In the biofuels section, we included different works classified according to the used biofuel. In this classification, we consider pure biofuels (ethanol, methanol, hydrogen), gasoline-alcohol blends and gasoline-alcohol blend plus hydrogen as additive. In the control section, we include a classification according to the type of control, these are model-based control, observer-based control and intelligent control. Furthermore, in this section we include a review about Fault Diagnosis strategies applied to IC engines. Moreover, we present an overview of the failures provoked by corrosion effects when biofuels are used.