This article proposes a control of lighting and electrical loads, suitable for smart homes, using embedded systems with low-cost wireless communication modules. The system is based on a distributed intelligent home automation architecture, to work autonomously or interconnect wirelessly to a larger system. It has a set of sensors that allow you to ration the use of electricity through automatic switching off the lights or electrical devices, allowing the lighting to be regulated. It has several modules that communicate to a central node wirelessly, and an interface based on a mobile application. UML and Petri Nets were used for the projection, modelling and validation of the system, its implementation was developed in C/C ++ language for 32-bit microcontrollers. Tests of the prototype showed stable behavior, fast communications and sufficient coverage for a single-family house, whose performance is higher to other similar works found in the scientific community.

Intelligent distributed module for local control of lighting and electrical outlets in a home

A single effect LiBr–H2O absorption refrigeration system coupled with a solar collector and a storage tank was studied to develop an assessment tool using the built-in App Designer in MATLAB®. The model is developed using balances of mass, energy, and species conservation in the components of the absorption cooling system, taking into account the effect of external streams through temperature and pressure drop. The whole system, coupled with the solar energy harvesting arrangement, is modeled for 24 h of operation with changes on an hourly basis based on ambient temperature, cooling system load demand, and hourly solar irradiation, which is measured and recorded by national weather institutes sources. Test through simulations and validation procedures are carried out with acknowledged scientific articles. These show 2.65% of maximum relative error on the energy analysis with respect to cited authors. The environmental conditions used in the study were evaluated in Barranquilla, Colombia, with datasets of the Institute of Hydrology, Meteorology and Environmental Studies (IDEAM), considering multiannual average hourly basis solar irradiation. This allowed the authors to obtain the behavior of the surface temperature of the water in the tank, COP, and exergy efficiency of the system. The simulations also stated the generator as the biggest source of irreversibility with around 45.53% of total exergy destruction in the inner cycle without considering the solar array, in which case the solar array would present the most exergy destruction.

A New Computational Tool for the Development of Advanced Exergy Analysis and LCA on Single Effect LiBr–H2O Solar Absorption Refrigeration System

Due to the randomness of wind speed and direction, the output power of wind turbine also has randomness. After large-scale wind power integration, it will bring a lot of adverse effects on the power quality of the power system, and also bring difficulties to the formulation of power system dispatching plan. In order to improve the prediction accuracy, an optimized method of wind speed prediction with support vector machine and genetic algorithm is put forward. Compared with other optimization methods, the simulation results show that the optimized genetic algorithm not only has good convergence speed, but also can find more suitable parameters for data samples. When the data is updated according to time series, the optimization range of vaccine and parameters is adaptively adjusted and updated. Therefore, as a new optimization method, the optimization method has certain theoretical significance and practical application value, and can be applied to other time series prediction models.

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An Optimized Method of Wind Speed Prediction with Support Vector Machine and Genetic Algorithm

The SunAnalyzer, developed in Citect SCADA, was implemented to monitor, and control the exploitation of two solar parks in the provinces of Guantanamo and Cienfuegos (Cuba). The SunAnalyzer permits real-time visualization of operating parameters, perform operating diagnostics, and display information in detailed graphs. The system was developed as a user friendly to facilitate its use by operators, and the technical and administrative staffs. Additionally, the implementation of a database allows comparing operating data over time, which helps to support the decision-making process. As a result of the SunAnalyzer, the operating costs are significantly reduced in both solar plants.

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Modernización del sistema de control de los parques solares ‘Santa Teresa II’ (Guantánamo) y ‘Bagacera de Cruces’ (Cienfuegos).

Analysis of the Economic and Environmental Feasibility of a Home Automation System

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Fabiola Reyes

Papers

Wind speed prediction based on univariate ARIMA and OLS on the Colombian Caribbean Coast