Climatization and Luminosity Optimization of Buildings using Genetic Algorithm, Random Forest and Regression Models - Genetic Algorithm

The case study for the Genetic Algorithm uses real sensor data, provided by a research unit that develops scientific research and innovation in areas such as Smart Grinds, Electricity Markets, Distributed Resources, Demand Response, Energy Efficiency, and Intelligent Buildings. The collected data represents a year, from the 1st of May 2019 to the 30th of April 2020, of sensor data from a room, and market prices, which are considered to be MIBEL prices. Also, all the data is provided in intervals of one hour. All the input data (e.g. sensor data, MIBEL prices, and available PV) had to been retracted, due to privacy reasons, thus these files only represent the output given by the Genetic Algorithm, for each scenario.

File Description:

Genetic_Algorithm_Dataset_Statistics - Dataset used for the genetic algorithm case study, with attached statistics regarding energy cost, temperature deviation, luminosity deviation, and VOC

Input_Genetic_Algorithm_JSON_Example - Example of JSON input data for the genetic algorithm