Modeling of energy management with electric load curve using fuzzy logic system for office electricity consumers.

Currently, the need for electrical energy continues to increase. Therefore, a detailed pattern of electricity use is needed to change a consumer's use of electricity and reduce global energy consumption. In energy management, electricity loading is needed to regulate if there is an increase in load in the electricity sector. So that the electrical load curve can detect a peak load from excessive energy use. This research is a fuzzy logic artificial intelligence method to process a rule of input variables and produce an energy consumption that has been used. In the resulting energy consumption, the electric load curve is influenced by variable factors such as the period of use of the equipment and the number of users. The input data used for this fuzzy logic system is the actual data of the period of use of the equipment used every day and the number of users using the equipment. From the results of the study, it was found that the level of accuracy between the actual data and fuzzy logic data will be obtained from the mean absolute percentage error (MAPE). It is hoped that this research can be a modeling of an electrical energy detection system in a residence or office because it will facilitate the use of energy in an equipment. [ABSTRACT FROM AUTHOR]