Smart home energy management system based on a hybrid wireless network architecture

Currently, in electrical energy sector, due to the population growth and the increasing energy consumption demand, the electrical grid is becoming more and more complex. This creates new challenges in term of electrical energy management. Our contribution in this area, presented in this paper, consists of the design, implementation and test of a wireless monitoring and control system for household electrical appliances. This system offers to the residential customers a helpful tool to monitor and control the energy consumption of their household appliances. The developed system is composed by a set of components connected to each other using wireless network technologies: the monitoring devices, the gateway and the client devices (with the respective user interface). For the development of this system, we opted to use a hybrid wireless network solution based on Wi-Fi and Bluetooth Low Energy (BLE). We describe the design and the implementation of the monitoring device hardware, as well as the calculation methodologies to obtain the electrical quantities and to reduce as much as possible the measurement errors. This paper describes also the development of the BLE/Wi-Fi gateway and the Graphical User Interface (GUI). The performance of the developed monitoring device was evaluated by means of experimental tests, where we achieved a voltage measurement error below 0.2% and a current measurement error below 0.5%.FCT - Fundació Catalana de Trasplantament (UID/EEA/04436/2019

Sensor fault reconstruction for wind turbine benchmark model using a modified sliding mode observer

This paper proposes a fault diagnosis scheme applied to a wind turbine system. The technique used is based on a modified sliding mode observer (SMO), which permits the reconstruction of actuator and sensor faults. A wind turbine benchmark with a real sequence of wind speed is exploited to validate the proposed fault detection and diagnosis scheme. Rotor speed, generator speed, blade pitch angle, and generator torque have different orders of magnitude. As a result, the dedicated sensors are susceptible to faults of quite varying magnitudes, and estimating simultaneous sensor faults with accuracy using a classical SMO is difficult. To address this issue, some modifications are made to the classic SMO. In order to test the efficiency of the modified SMO, several sensor fault scenarios have been simulated, first in the case of separate faults and then in the case of simultaneous faults. The simulation results show that the sensor faults are isolated, detected, and reconstructed accurately in the case of separate faults. In the case of simultaneous faults, with the proposed modification of SMO, the faults are precisely isolated, detected, and reconstructed, even though they have quite different amplitudes; thus, the relative gap does not exceed 0.08% for the generator speed sensor fault

Low-cost real-time internet of things-based monitoring system for power grid transformers

One of the most common causes of blackouts is unexpected failures at power system transformer levels. The purpose of this project is to create a low-cost Internet of things (IoT)-based monitoring system for power grid transformers in order to investigate their working status in real-time. Our monitoring system’s key functions are the gathering and display of many metrics measured at the transformer level (temperature, humidity, oil level, voltage, vibration, and pressure). The data will be collected using various sensors connected to a microcontroller with an embedded Wi-Fi module (DOIT Esp32 DevKit v1), and then supplied to a cloud environment interface with a full display of all the ongoing changes. This technology will provide the power grid maintenance center with a clear image of the transformers’ health, allowing them to intervene at the right time to prevent system breakdown. The method described above would considerably improve the efficiency of a power transformer in a smart grid system by detecting abnormalities before they become critical

A New Maximum Power Point Tracking Based on Neural Networks and Incremental Conductance for Wind Energy Conversion System

This work presents a new Maximum Power Point Tracking (MPPT) for the connection of the wind turbine system (WT) to the synchronous permanent magnet generator (PMSG). To search the maximum power of the wind turbine, we have proposed a new MPPT which combines two techniques: Artificial Neural Network (ANN) and incremental conductance (IncCond) method. The advantage of ANN-based WT model method is the fast MPP approximation base on the ability of ANN according the parameters of WT that used. The advantage of IncCond method is the ability to search the exactly MPP based on the feedback voltage. In our case the ANN is employed to predict the maximum voltage of the WT, under different values of wind speed, and the control of DC–DC boost converter operation is executed by applying incremental conductance (IncCond) technique. The proposed system includes a wind turbine associated to a permanent magnet synchronous generator (PMSG), a rectifier and a DC-DC converter with MPPT control. The proposed algorithm is tested under MATLAB SIMULINK

Remote calibration system of a smart electrical energy meter

The need to control the power grid in real time has opened a new field of research, today researchers are trying to design electrical meters that are completely remote controlled, to create an advanced metering infrastructure. One of the most important processes in the field of measurement is the calibration of measuring instruments. The calibration process of the electrical meters was performed at laboratories. However, the new directives, now, require a regular test of accuracy. Nevertheless, moving each time on site to check the accuracy of a meter can be annoying. To solve this problem our contribution is to propose a new structure of a smart meter that integrates a calibration card, so that, this process is carried out remotely. To be able to calibrate the meter or test its accuracy, we have included an AC-AC converter powered by the electrical grid and that provides a stable voltage independent of the electrical grid in term of frequency and amplitude. The output voltage of the converter is used as the reference signal during calibration or accuracy testing. In this paper, we will present the structure of the calibration card, the study and dimensioning of the converter, as well as the control technique used to eliminate variations of the input voltage. At the end, we will present the results of simulations and experiments

Asymmetric Fuzzy Logic Controlled DC-DC Converter for Solar Energy system

<p><strong>In this paper, a controlled voltage system for a solar energy source is presented, by a new command called fuzzy logic controller (FLC), via a DC-DC converter .The fuzzy logic control is selected due its performance and efficiency even for nonlinear systems such as the DC-DC converters.  </strong></p><p><strong>A simulation with MATLAB SIMULINK environment of the FL control system, compared with a classical PI controller, is presented at the end of the paper to illustrate the good behavior of the control.</strong></p

Fuzzy sliding mode control for maximum power point tracking of a photovoltaic pumping system

In this paper a new maximum power point tracking method based on fuzzy sliding mode control is proposed, and employed in a PV water pumping system based on a DC-DC boost converter, to produce maximum power from the solar panel hence more speed in the DC motor and more water quantity. This method combines two different tracking techniques sliding mode control and fuzzy logic; our controller is based on sliding mode control, then to give better stability and enhance the power production a fuzzy logic technique was added. System modeling, sliding method definition and the new control method presentation are represented in this paper. The results of the simulation that are compared to both sliding mode controller and perturbation and observation method demonstrate effectiveness and robustness of the proposed controller