Industrial Energy Management Planning based on reliability forecasting in generation, in a context of the Sustainable Development Goals

Abstract

Introduction: Energy management in industrial environments is a strategic challenge, especially in sectors such as oil refining and crude oil production, where self-generation of energy allows for cost reduction and ensures operational continuity. However, generation reliability is not absolute, as the occurrence of failures necessitates supplementing demand with purchases from the National Interconnected System, generally at a higher cost. Uncertainty regarding the frequency and duration of these failures complicates energy procurement planning, which can lead to cost overruns or operational deficits.

Objective: This study proposes a predictive model based on System Dynamics to improve energy planning, optimizing generation reliability and cost management.

Method: Through the simulation of different scenarios, the need for energy purchases is anticipated, enabling more efficient decisions aligned with operational sustainability. This research aligns with Sustainable Development Goals 7 (Affordable and Clean Energy), 9 (Industry, Innovation and Infrastructure), and 12 (Responsible Consumption and Production), promoting more resilient and sustainable energy management strategies.

Results: System modeling identifies the challenges associated with the reliability of the electricity supply in a crude oil production complex, highlighting the need for strategies that guarantee energy efficiency and economic sustainability.

Conclusion: The results underscore the importance of a systemic approach to energy management in industrial environments, particularly in the crude oil production sector. Through System Dynamics modeling, the main variables affecting the energy performance of the analyzed complex are identified, allowing for the evaluation of the impact of different strategies on operational and financial efficiency.