Modeling and Prediction of Energy Consumption for Public Lighting in the State of São Paulo

• Grant number: 24/14892-5
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Effective date (Start): October 01, 2024
• Effective date (End): September 30, 2025
• Field of knowledge: Interdisciplinary Subjects
• Principal Investigator: Romis Ribeiro de Faissol Attux
• Grantee: Antônio José Trevisan
• Host Institution: Faculdade de Engenharia Elétrica e de Computação (FEEC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 21/11380-5 - CPTEn - São Paulo Center for the Study of Energy Transition, AP.CCD

Abstract

The state of São Paulo is served by 7 distribution concessionaries in the market for the supply of electrical energy, each with its own consumption and demand bill model, which results in the need for customized data extraction regarding the Groups A and B, and Blue and Green ranges. Moreover, the open energy market have certain peculiarities. As a reference, the Executive Branch of São Paulo owns more than 30.100 properties, of which 16.200 are directly related to the government (under various types). In a first analysis, 24 types were identified, like schools, police stations and penitentiaries, with 24x7 consumption, administrative buildings, which operate from 8:00 to 18:00, avoiding consumption at the peak, aside from several other kinds of service. In this project, the units of the State of São Paulo will be analized. Thus, with the creation of the database proposed by CPTEn (AI and data science branch), it will be possible to analyze the consumption profile according to the 24 identified building categories. This project aims at mapping the data regarding energy consumption in the context of public buildings and public lighting. The idea comes from the need for an efficient database that will be developed within the undergraduate research projects of CPTEn. Having these data, the need for energy forecast associated with each building is relevant, and this can be done using historical time series, together with future expectations not only of the demand, but also of environmental parameters that indirectly affects the consumption, e.g. temperature and humidity. Moreover, energy planning may be useful an financial and expansion planning, as well as, providing knowledge of the impact that the installation of an equipment will cause. Furthermore, the project has a significant replication potential, and may have projected results for the 30.100 properties, engendering a huge study database. Therefore, this energy mapping is of great importance, with the production and organization of these data to help the fulfilment of the CPTEn results, contributing to the energy management of public lighting and to the analysis of ways to reduce expenses, aside from contributing to data transparence. Finally, it is very important to point out that, with these formulations, one may support the government of the state of São Paulo and the energy generating companies in defining public policies.