Abstract
Sustainability is strongly related to the appropriate use of available resources, being an important cornerstone in any company’s administration due to the direct influence on its efficiency and ability to compete in the global market. Therefore, the intelligent and proper management of these resources is a pressing matter in terms of cost savings. Among the possible alternatives for optimisation, the one regarding electricity consumption stands out due to its strong influence on the expenses account. In general, this type of optimisation can be carried out from two different perspectives: one that concerns the efficient use of energy itself and the other related to the proper adjustment of the electricity contract so that it meets the infrastructure needs while avoiding extra costs derived from poorly sized bills. This paper describes the application of an artificial intelligence based methodology for the optimisation of the parameters contracted in the electricity tariff in the Spanish market. This technique is able to adjust the power term needed so that the global economic cost derived from energy consumption is significantly reduced. The papers discusses the impact that this proposal may have on a demand response scenario associated to load shifting practices within university buildings. Furthermore, the role of human beings, specifically university employees, and their actions towards reducing the overuse of power consumption at the same time is also addressed.
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We acknowledge the support of the Spanish government for SentientThings project under Grant No.: TIN2017-90042-R.
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Kamara-Esteban, O., Borges, C.E., Casado-Mansilla, D. (2019). Can I Shift My Load? Optimizing the Selection of the Best Electrical Tariff for Tertiary Buildings. In: Tzovaras, D., Giakoumis, D., Vincze, M., Argyros, A. (eds) Computer Vision Systems. ICVS 2019. Lecture Notes in Computer Science(), vol 11754. Springer, Cham. https://doi.org/10.1007/978-3-030-34995-0_60
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