Abstract

Abstract

The term Microgrid refers to a power system in a small scale, made of active elements operating between them, namely renewable and traditional generation, energy storage and controllable charges. Previous studies have evaluated and modelled the operation cost of many elements that make up the Microgrid, in order to identify the correct point of operation. In this study, the researchers evaluated a model of Microgrid with diesel as traditional generator, a park of photovoltaic generation, two wind generators, one battery bank and two aggregators that manage electric vehicles. The objective of this research is to propose an equation capable of describing the operation cost of a Microgrid as a set, taking into account the modelling of the operation cost of photovoltaic energy, wind energy, and energy storage in battery banks and electric vehicles. This equation also seeks to obtain the best possible cost efficiency, i.e., decreasing the operation cost of the Microgrid. For this purpose, the Metauristic method DEEPSO (Differential Evolutionary Particle Swarm Optimization) was used, recognized for its performance for applications in power systems. Through this method, and determinate the conditions of operation of the different elements in the Microgrid. Taking into account all the parameters, the behavior of each one of the elements of the Microgrid in a 24-hour lapse was found and visualized. 

Abstract

Faced with the problem of wind speed in generation and the difficulty that this entails in the economic future of electric power, mathematical formulations (functions), called uncertainty costs, have been developed. The term is used in a model composed of two parts, an implication of penalization costs for overestimation and the other due to the underestimation of a programmed power. Through analytical mathematics and Monte Carlo simulations, we have found the expected value of the costs of uncertainty, the stability of primary resources through the distribution of probability. However, the results can not be evaluated accurately from an analytical point of view, without taking into account the variability around the average value. In this article we calculate the analytical function of the variance, we understand as a measure of dispersion of the expected values of uncertainty costs for the specific case of wind operators; Likewise, this formulation has been validated through Monte Carlo simulations. The function found is used to observe the dispersion of the data around its expected average value, by applying the standard deviation.

Abstract

The new engineering FASTLognoter software is presented. This code is essentially the result of the integration of two tools, along with some additional features. Thefirst basis tool is FAST (developed by NREL), a comprehensive aeroelastic simulator code for wind turbines. The second basis tool is Lognoter (developed by CompassIS), a general-purpose commercial software for managing and creating engineering forms. The integration of FAST and Lognoter gives a useful, comprehensive and versatile toolkit, which is verified in this work by means of bibliographic documented cases. An important advantage of the tool presented is the parametric design capability, allowing the user of FAST/AeroDyn/HydroDyn codes to analyze a massive group of cases; therefore, optimal design can be carried out.

Abstract

Abstract

Energy harvesting has currently taken a central role due to its application to feed low power devices, such as wireless sensors, radio-frequency transceivers, charging devices and cameras. Among other alternatives, wind energy harvesting based on aeroelastic phenomena plays a pivotal role in providing sufficient power for extended operation of such devices with little or no battery replacement. In this article, a concept that explores the possibility of harvesting wind energy using an array of harvesting devices is presented. Each device is built as a long span multifunctional wing that exhibits oscillatory motions under the action of the wind. The efficiency of these systems depends on inherently non-linear phenomena, as well as on the aerodynamic synergy between the harvesters, and between them and their wakes. In addition, a preliminary study of the feasibility of the concept is conducted through co-simulation techniques that allow one to investigate the fluid-structure interaction. The results of this effort are encouraging since they highlight the potential not only of the proposed concept but also of the combination of these new technologies with aeroelastic analysis and design methods to create a new generation of power harvesters.