This work proposes a real-time electricity bill for quantifying the energy used in domestic facilities in Mexico. This bill is a low-cost tool that takes advantage of the IoT technology for generating an easy reading real-time bill allowing the customers to constantly review and administrate their energy consumption. Using low-cost sensors and the electronic board Particle^® Photon, an energy meter is proposed. The presented prototype is extremely compact and satisfies safety measures to be used by anyone in a domestic installation. The measurement data is displayed and processed in real-time, and an appropriate algorithm determines the accumulated kWh. The energy consumed is displayed using an Html interface of easy interpretation for the customers, given recommendations about their consumption habits and some alarms in case of abnormal or high consumption. As a reinforcement measure for avoiding large consumption bills, the system is programmed to send messages to the user, remembering if the estimated consumption is large.

Las turbinas de gas son utilizadas como impulsores primarios en la generación de energía eléctrica. El desempeño de una unidad de turbo gas es dependiente de la unidad de control que tenga, ya que en ella radica gran parte de la optimización en la ejecución del sistema. En este trabajo se presentan los resultados de la evaluación de la estabilidad del controlador en el desempeño de un modelo de un controlador neurodifuso para una unidad turbogás, lo anterior como un primer paso para su aplicación en un proceso real. El diseño del controlador neurodifuso se basa en un controlador PI digital del tipo velocidad. El análisis y evaluación del controlador se hacen mediante simulaciones en tiempo discreto con un sistema de primer orden con retardo. Las pruebas incluyen variaciones de los parámetros del proceso: ganancia, retardo y constante de tiempo. Se evalúa el efecto de perturbaciones determinísticas y estocásticas en la señal de control, la variable manipulada y la variable controlada. Los resultados obtenidos demuestran la factibilidad de utilizar un controlador neurodifuso, integrado en equipos digitales, para aplicaciones reales.

This book chapter presents a flexible approach to incorporate mathematical models of FACTS devices into the Power Flow (PF) and the Optimal Power Flow (OPF) analysis tools, as well as into the standard OPF Market-Clearing (OPF-MC) procedure. The proposed approach uses the Matlab Optimization Toolbox because it allows to easily: (a) implement a given optimization model, (b) include different objective functions using distinct equality and inequality constraints and (c) modify and reuse an optimization model that has been previously implemented. The conventional OPF model is the main core of the proposed approach, which is easily implemented and adapted to include the mathematical models of FACTS devices. The resulting implementation of the OPF model featuring FACTS devices can be easily modified and adjusted to obtain the implementation of both the PF and the OPF-MC models which includes such devices. It should be mentioned that with the flexible approach proposed here, the complexity as well as the implementation time of optimized models featuring embedded FACTS devices is significantly reduced, since it is not necessary to define the expressions associated with the hessian matrix and the gradient vector. The flexibility and reliability of the proposed approach are demonstrated by means of several study cases using test as well as real power systems.