The Use of Game Theory as a Decision Support Tool for the Electricity Sector Regarding Water Use—Case Study: Paraíba do Sul River Basin, Brazil
Currently 65% of Brazil’s electricity generation has been produced by hydropower plants. The reservoirs that are used for power generation are also used for other purposes, such as irrigation, public supply, flood control, tourism, navigation, and environmental protection. The demands and decisions of the multiple water users have an impact on the planning and management of the Brazilian electricity sector. In this study we analyze how users in the electricity sector can make more assertive decisions when faced with the actions of public supply companies. The study region is the Paraíba do Sul River Basin, located in the states of São Paulo, Rio de Janeiro, and Minas Gerais in Brazil. This region is currently responsible for approximately 6% of Brazil’s hydropower generation but located in the most populated area of the country, with conflicts between water users. The methodology consisted of analyzing the consumptive use (CU) flows adopted in scenarios that would be more and less beneficial for energy generation and scenarios that would be more beneficial for sanitation companies, always remembering that the higher the CU, the less energy is generated. Subsequently, the selected CU values were entered into the Gambit software, which indicated the Nash equilibrium considering water use as a game that calculates finite and non-cooperative games, thus finding the scenario that represents the Nash equilibrium and the most assertive CU flow rate to be adopted by the sector to assist in the decision-making process.
Authors
- Camila Brandão Nogueira Borges
- Renato C. Zambon (ORCID: https://orcid.org/0000-0003-4552-6236)
- Daniel L. Rodrigues
Institutions
- National Society of Professional Engineers (US)
- Universidade de São Paulo (BR)
Publication Details
- Published
- 2025-05-15
- DOI
- https://doi.org/10.1061/9780784486184.059
- Primary Topic
- Water resources management and optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00