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Predictive Analysis of Photovoltaic Generation and Liquidity Price in the Energy Market via Artificial Intelligence Techniques and Exploratory Data Analysis

Grant number: 21/08298-5
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): October 01, 2021
Effective date (End): September 30, 2022
Field of knowledge:Engineering - Electrical Engineering - Power Systems
Principal researcher:Wallace Correa de Oliveira Casaca
Grantee:Leonardo Fernando Fini
Home Institution: Universidade Estadual Paulista (UNESP). Campus de Rosana. Rosana , SP, Brazil

Abstract

In the speculative and competitive environment such as the energy market, predicting electricity generation as well as its corresponding price are very challenging tasks that can support decision-making for the market agents. In addition to wind and hydraulic generation, the photovoltaic energy has attracted a lot of contracts signed in this market. Therefore, this project aims to study the problem of forecasting the energy generated at Pirapora solar plant, the second largest solar complex in Brazil, as well as predicting its corresponding price in the national energy market. For this purpose, we will study Exploratory Data Analysis (AED) tools and Artificial Intelligence (AI) models, including Random Forest, Support Vector Machines and Gradient Boosting. The AI models will be prototyped and validated by combining different data collections, which gather several energy-related features such as solar energy generation, climate data, natural affluent energy and liquidity prices, thus enabling the development of new strategies and computational apparatus for agents in the Brazilian electricity market.

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