Fuzzy Second Order Change in Home Energy Economy: Photovoltaic cells for sustainability in Mexico

According to the Comisión Federal de Electricidad (CFE) in Mexico, despite high investment costs and the lack of confidence in photovoltaics (PV) technology, the number of PV users has increased in recent years. In many cases, expected savings are not achieved, which can be put down to shortcomings in maintenance, an insufficient number of PVs, or obsolete equipment, among others. We consider three sets of factors that affect energy saving and sustainability: collateral factors, cognitive factors, and strategic change. The learning process approach is divided into two stages: first and second-order learning. We use fuzzy logic, fuzzy hamming distance and neural networks to emulate training - learning by analyzing the homeostatic sensitivity of the alpha coefficient in the transformation from first order to second order change through mean squared error and application of the backpropagation algorithm. Energy consumption records indicate that the oldest installations do not achieve energy saving due to bad practices in energy consumption and poor equipment maintenance. We found there was a positive disposition towards technological changes, while influencing others to decrease electricity consumption is weak. Evolution of training can be measured by a decrease in mean squared error, and the homeostatic process can be measured by applying α coefficient.