Dynamic and proactive matheuristic for AC/DC hybrid smart home energy operation considering load, energy resources and price uncertainties

Rodrigo Motta de Azevedo ◽  
Luciane Neves Canha ◽  
Vinícius Jacques Garcia ◽  
Camilo Alberto Sepúlveda Rangel ◽  
Tiago Augusto Silva Santana ◽  
2019 ◽  
Vol 242 ◽  
pp. 351-363 ◽  
Ivo Gonçalves ◽  
Álvaro Gomes ◽  
Carlos Henggeler Antunes

2019 ◽  
Vol 8 (4) ◽  
pp. 5312-5315 ◽  

In an era of SMART BUILDING, SMART HOUSES, this project came up with an idea of building a smart device which works smartly on some level. The system always tried to use the resources in a way that it should be conserved and should also not disturb current need and fulfil it. In order to come up with a solution which will not only conserve the energy resources but will also be an assistant with its control over the device. The system using Arduino paired with sensors and bunch of algorithms which will help in controlling the device and the device which is to be controlled with this controller will be an Air Conditioner. Using the data analysis of different aspects of weather conditions and timings and will train controller to control the device with solving the W’s of the situation i.e. How, When, Why and Where. The device will automatically control the air conditioner like when to power on and off, like on what temperature the AC should be and more.

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3201 ◽  
Muhammad Rafique ◽  
Zunaib Haider ◽  
Khawaja Mehmood ◽  
Muhammad Saeed Uz Zaman ◽  
Muhammad Irfan ◽  

The present environmental and economic conditions call for the increased use of hybrid energy resources and, concurrently, recent developments in combined heat and power (CHP) systems enable their use at a domestic level. In this work, the optimal scheduling of electric and gas energy resources is achieved for a smart home (SH) which is equipped with a fuel cell-based micro-CHP system. The SH energy system has thermal and electrical loops that contain an auxiliary boiler, a battery energy storage system, and an electrical vehicle besides other typical loads. The optimal operational cost of the SH is achieved using the real coded genetic algorithm (RCGA) under various scenarios of utility tariff and availability of hybrid energy resources. The results compare different scenarios and point-out the conditions for economic operation of micro-CHP and hybrid energy systems for an SH.

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