Stochastic Decision-Making Optimization Model for Large Electricity Self-Producers Using Natural Gas in Industrial Processes: An Approach Considering a Regret Cost Function

Laís Domingues Leonel (), Mateus Henrique Balan, Luiz Armando Steinle Camargo, Dorel Soares Ramos, Roberto Castro and Felipe Serachiani Clemente
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Laís Domingues Leonel: Department of Energy Engineering and Electrical Automation, Polytechnique School University of São Paulo, São Paulo 05508-010, SP, Brazil
Mateus Henrique Balan: Department of Energy Engineering and Electrical Automation, Polytechnique School University of São Paulo, São Paulo 05508-010, SP, Brazil
Luiz Armando Steinle Camargo: Department of Energy Engineering and Electrical Automation, Polytechnique School University of São Paulo, São Paulo 05508-010, SP, Brazil
Dorel Soares Ramos: Department of Energy Engineering and Electrical Automation, Polytechnique School University of São Paulo, São Paulo 05508-010, SP, Brazil
Roberto Castro: MRTS Consultoria, São Paulo 05503-001, SP, Brazil
Felipe Serachiani Clemente: Alcoa, São Paulo 04794-000, SP, Brazil

Energies, 2024, vol. 17, issue 21, 1-19

Abstract: In the context of high energy costs and energy transition, the optimal use of energy resources for industrial consumption is of fundamental importance. This paper presents a decision-making structure for large consumers with flexibility to manage electricity or natural gas consumption to satisfy the demands of industrial processes. The proposed modelling energy system structure relates monthly medium and hourly short-term decisions to which these agents are subjected, represented by two connected optimization models. In the medium term, the decision occurs under uncertain conditions of energy and natural gas market prices, as well as hydropower generation (self-production). The monthly decision is represented by a risk-constrained optimization model. In the short term, hourly optimization considers the operational flexibility of energy and/or natural gas consumption, subject to the strategy defined in the medium term and mathematically connected by a regret cost function. The model application of a real case of a Brazilian aluminum producer indicates a measured energy cost reduction of USD 3.98 millions over a six-month analysis period.

Keywords: energy procurement; load-supply flexibility; integrated stochastic optimization model; regret cost function (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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