Decision Making And Artificial Intelligence In Public Electricity Management

Decision Making and Artificial Intelligence in Public Electricity Management by Fabricio Quadros Borges  

DECISION MAKING AND  

ARTIFICIAL INTELLIGENCE IN  

PUBLIC ELECTRICITY  

MANAGEMENT  

1ª edition  

Fabricio Quadros Borges  

_______________________________________________  

São Paulo - SP  

2024  

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Decision Making and Artificial Intelligence in Public Electricity Management by Fabricio Quadros Borges  

BORGES, Fabricio Quadros  

Decision Making and Artificial Intelligence in Public  

Electricity Management / Fabricio Quadros Borges.  

São Paulo, SP: AlphaGraphics. Brazil, 2024.  

41p.; 29cm.  

ISBN

:

978-65-00-98918-2  

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Decision Making and Artificial Intelligence in Public Electricity Management by Fabricio Quadros Borges  

SUMÁRIO  

Presentation

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3  

Introduction

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4

Mission of Public Energy Management

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8  

Historical Evolution Of The Development Process

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11  

Public Electricity Management

.............................................................................................................

19  

Machine Learning

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22  

Structure of the Decision-Making Model

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24  

Analysis of the Decision-Making Model

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28  

Advances in the Proposed Decision-Making Model

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36  

Bibliographic References

..................................................................................................................................

38  

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Decision Making and Artificial Intelligence in Public Electricity Management by Fabricio Quadros Borges  

PRESENTATION  

The analyzes carried out by artificial intelligence must start from a complete and  

integrated data structure, which is classified and grouped with the intention of synergistically  

producing mental and predictive captures. In this perspective, the objective of this study is  

to analyze the possibility of contribution of artificial intelligence in guiding decision-making  

in the public planning of sustainable electrical matrices. The methodological procedures of  

this investigation, built a structure of analysis of electricity sources, based on the economic,  

social, environmental and technological dimensions; as well as a sectoral analysis structure  

of energy sustainability indicators, supported by linear correlations of an economic, social,  

environmental and political nature.  

The planning of electrical matrices, according to the inferences of this investigation,  

can use artificial intelligence as a strategic guide for decisions, as long as they are based  

on analysis structures focused on the strategic use of electricity sources and the use of  

sectoral and multidimensional indicators. This investigation constitutes an original  

contribution insofar as it discusses the possibilities of connections between artificial  

intelligence and the construction of electrical matrices, from the perspective of improving the  

decision-making process in Brazilian public planning.  

The discussion about these connections helps to raise subsidies for machine learning  

to process and develop methodologies, based on algorithms, that automate the construction  

of decision analysis models in the planning and sustainable construction of the use of  

electricity.  

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Decision Making and Artificial Intelligence in Public Electricity Management by Fabricio Quadros Borges  

INTRODUCTION  

Studies on A.I. emerged in the 1950s, through scientists Herbert Simon and Allen  

Newell, who created the first artificial intelligence laboratory at Carnegie Mellon University  

(Santos, 2021). The advances in Artificial Intelligence (A.I.) bring important reflections on  

how this field of knowledge will affect human routine. The Web Summit 2018, one of the  

largest technology and innovation conferences in the world, points to a solid and irreversible  

path towards this technology. The AI branch seeks, through computational symbols, to  

elaborate mechanisms that simulate the human capacity to be intelligent, which already  

demonstrates effects in several areas of knowledge; the advances of these studies  

represent improvements in the application of available resources to the extent that they can  

strategically guide the decision-making process in organizations (Colson, 2019; Santos,  

2021).  

In view of this panorama, there is a hope that A.I. it could also help public planning in  

the electricity sector, insofar as it could support public managers to design more sustainable  

electrical systems through the optimization of resources, help motivate individual or  

organizational