Design of an Energy Management System for Secure Integration of Renewable Energy Sources into Microgrids

This chapter presents the design and development of an energy management system (EMS), which guarantees a secure operation of an islanded microgrid under possible imbalances between generation capacity and loads demand. The EMS performs an optimal calculation of low priority loads to be shed, as well as charging and discharging cycles of batteries within the microgrid. A nonlinear model‐predictive control (NMPC) algorithm is selected for implementing the EMS, which processes a data set composed of loads measurements, generation capacity, batteries state of charge (SOC), and a set of operation constraints. The EMS is designed under the assumption of having an advanced metering infrastructure (AMI) installed in the microgrid. The EMS is tested in a simulation platform that integrates models of the microgrid components, as well as their distributed controllers (DCs). Simulation results show the effectiveness of the proposed approach, since critical variables as the microgrid’s frequency and voltage magnitude operate within a secured interval even under the presence of faults in one of the DCs

Predictive Control of a Closed Grinding Circuit System in Cement Industry

This paper presents the development of a non-linear model predictive controller (NMPC) applied to a closed grinding circuit system in the cement industry. A Markov chain model is used to characterize the cement grinding circuit by modeling the ball mill and the centrifugal dust separator. The probability matrices of the Markovian model are obtained through a combination of comminution principles and experimental data obtained from the particle size distribution (PSD) of cement samples at specific stages of the system. The NMPC is designed as a supervisory controller in order to manage distributed controllers (DCs) installed in the process. Both the model and the controller are validated online through the implementation of the proposed approach in the supervisory control and data acquisition (SCADA) system of an industrial plant. The results show a significant improvement in the performance of the grinding circuit in comparison to the operation of the system without the proposed controller

Mechatronic Design of a Lower Limb Exoskeleton

This chapter presents a lower limb exoskeleton mechatronic design. The design aims to be used as a walking support device focused on patients who suffer of partial lower body paralysis due to spine injuries or caused by a stroke. First, the mechanical design is presented and the results are validated through dynamical simulations performed in Autodesk Inventor and MATLAB. Second, a communication network design is proposed in order to establish a secure and fast data link between sensors, actuators, and microprocessors. Finally, patient‐exoskeleton system interaction is presented and detailed. Movement generation is performed by means of digital signal processing techniques applied to electromyography (EMG) and electrocardiography (EEG) signals. Such interaction system design is tested and evaluated in MATLAB whose results are presented and explained. A proposal of real‐time supervisory control is also presented as a part of the integration of every component of the exoskeleton

Mitigation of Short-Term Wind Power Ramps through Forecast-Based Curtailment

As the penetration of renewable energy generation in electric grids becomes more substantial, its contribution to the variability of the net load becomes more noticeable. Particularly in small or weak grids, the rate at which the output power of a wind farm decreases may become a concern to grid operators. In the present work, a novel approach, called forecast-based curtailment (FBC), is shown to be able to self-mitigate downward ramps on short time scales at a very small energy penalty, compared to conventional mitigation schemes, such as flat curtailment or up-ramp limitations. FBC allows to achieve compliance with ramp limits imposed by system operators at a very small energy cost and modest additional upfront investments

Aplicación de tecnologías inalámbricas al monitoreo climatológico en la cuenca del Río Paute

The program for the management of the water and soil (PROMAS) is a research department of the University of Cuenca. It focuses on the monitoring and conservation of the water sources and natural resources. Among others, such program mainly requires the monitoring of several variables by means of a set of hydro-meteorological stations. From its beginning, the program has deployed around 130 stations in an extensive geographic area of interest, ranging from the Cajas sector in the province of Azuay to the province of Cañar. Currently, the meteorological stations stores the variables of interest in their internal memory. Then, the analysis of the collected data requires the physical displacement of the Promas staff to the different sites. Due to the fact that most of the remote sites are of difficult access, the personal obtain the information with a periodicity of around 30 and 45 days. In this context, this paper describes the work on progress whose main objective is to provide to the meteorological stations with the wireless transmission capacity of the data collected by the sensors to the Promas data center in real time.El Programa para el Manejo del Agua y Suelo (PROMAS) de la Universidad de Cuenca, realiza investigación y consultoría en el campo de monitoreo y conservación de recursos hídricos. Dicho programa requiere principalmente el monitoreo de varias variables mediante la utilización de estaciones meteorológicas. Desde sus inicios, el programa ha desplegado alrededor de 130 estaciones en un área de interés geográfica extensa, que comprende desde el sector del Cajas en la provincia del Azuay hasta la provincia del Cañar. Las estaciones meteorológicas guardan las variables de interés en su memoria interna y por tanto, la obtención de los datos recopilados por los distintos sensores para su análisis requiere el desplazamiento del personal hacia los sitios, que en su mayoría son de difícil acceso y por tanto se hacen con una periodicidad de entre 30 y 45 días. En este contexto, el presente artículo describe los avances de un proyecto en curso que tiene como principal objetivo el de dotar a las estaciones meteorológicas con la capacidad de transmisión inalámbrica de los datos recopilados por los sensores en tiempo real hacia el centro de datos del Promas ubicado en el campus de la Universidad de Cuenca

Self-Optimizing Control System to Maximize Power Extraction and Minimize Loads on the Blades of a Wind Turbine

This research proposes a methodology for designing and testing a self-optimizing control (SOC) algorithm applied to a wind energy conversion system (WECS). The SOC maximizes WECS power output and reduces the mechanical stress of the wind turbine (WT) blades by optimizing a multiobjective cost function. The cost function computation uses a combined blade element momentum (BEM) and thin-wall beam (TWB) model for calculating wind the turbine power output and blades’ stress. The SOC deployment implies a low computational cost due to an optimization space reduction via a matrix projection applied to a measurement vector, based on a prior offline calculation of a projection matrix, H. Furthermore, the SOC optimizes the operation of the WECS in the presence of uncertainty associated with the wind speed variation by controlling a linear combination of measured variables to a set point. A MATLAB simulation of a wind turbine model allows us to compare the WECS operating with the SOC, a baseline classic control system (BCS), and a nonlinear model predictive controller (NMPC). The SOC algorithm is evaluated in terms of power output, blades’ stress, and computational cost against the BCS and NMPC. The power output and blades’ stress performance of the SOC algorithm are compared with that of the BCS and NMPC, showing a significant improvement in both cases. The simulation results demonstrate that the proposed SOC can effectively optimize a WECS operation in real time with minimal computational costs

Dynamic Modeling and Control of a Parallel Mechanism Used in the Propulsion System of a Biomimetic Underwater Vehicle

Incorporation of parallel mechanisms inside propulsion systems in biomimetic autonomous underwater vehicles (BAUVs) is a novel approach for motion generation. The vehicle to which the studied propulsion system is implemented presents thunniform locomotion, and its thrust depends mainly on the oscillation from its caudal fin. This paper describes the kinematic and dynamic modeling of a 3-DOF spherical 3UCU-1S parallel robotic system to which the caudal fin of a BAUV is attached. Lagrange formalism was employed for inverse dynamic modeling, and its derivation is detailed throughout this paper. Additionally, the implementation of control strategies to compute forces required to actuate limbs to change platform’s flapping frequencies was developed. Four controllers: classic PD, a feedforward plus feedback PD, an adaptive Fuzzy-PD, and a feedforward plus Fuzzy-PD were compared in different simulations. Results showed that augmenting oscillating frequencies (from 0.5 to 5 Hz) increased the complexity of the path tracking task, where the classic control strategy (i.e., PD) was not sufficient, reaching percentage errors above 9%. Control strategies using feedforward terms combined with adaptive feedback techniques reduced tracking error below 2% even during the presence of external disturbances

Modeling, Trajectory Analysis and Waypoint Guidance System of a Biomimetic Underwater Vehicle Based on the Flapping Performance of Its Propulsion System

The performance of biomimetic underwater vehicles directly depends on the correct design of their propulsion system and its control. These vehicles can attain highly efficient motion, hovering and thrust by properly moving part(s) of their bodies. In this article, a mathematical modeling and waypoint guidance system for a biomimetic autonomous underwater vehicle (BAUV) is proposed. The BAUV achieves sideways and dorsoventral thunniform motion by flapping its caudal fin through a parallel mechanism. Also, an analysis of the vehicle’s design is presented. A thrust analysis was performed based on the novel propulsion system. Furthermore, the vehicle’s kinematics and dynamic models were derived, where hydrodynamic equations were obtained as well. Computed models were validated using simulations where thrust and moment analysis was employed to visualize the vehicle’s performance while swimming. For the path tracking scheme, a waypoint guidance system was designed to correct the vehicle’s direction toward several positions in space. To accurately obtain waypoints, correction over the propeller’s flapping frequency and bias was employed to achieve proper thrust and orientation of the vehicle. The results from numerical simulations showed how by incorporating this novel propulsion strategy, the BAUV improved its performance when diving and maneuvering based on the dorsoventral and/or sideways configuration of its swimming mode. Furthermore, by designing proper strategies to regulate the flapping performance of its caudal fin, the BAUV followed the desired trajectories. The efficiency for the designed strategy was obtained by comparing the vehicle’s traveled distance and ideal scenarios of straight-line trajectories between targets. During simulations, the designed guidance system presented an efficiency of above 80% for navigation tasks