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Stochastic optimization with individualized hydropower plants for planning operation of Brazilian hydrothermal system

Grant number: 13/03432-9
Support type:Scholarships abroad - Research
Effective date (Start): July 01, 2013
Effective date (End): June 30, 2014
Field of knowledge:Engineering - Civil Engineering
Principal Investigator:Renato Carlos Zambon
Grantee:Renato Carlos Zambon
Host: William W-G. Yeh
Home Institution: Escola Politécnica (EP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Local de pesquisa : University of California, Los Angeles (UCLA), United States  
Associated research grant:08/58508-1 - HydroRisk: risk management technologies applied to water and electricity supply systems , AP.TEM

Abstract

The Brazilian electrical system is a large scale hydrothermal system, with strong predominance of hydroelectricity, with over 140 medium and large hydropower plants. In the last twelve years, on average, the hydropower plants produced 91% of the total electricity consumed in the country, the remainder supplemented by thermal power plants and other sources. In our previous studies, we developed the HIDROTERM model to optimize the management and operation of the hydrothermal system. It is a deterministic model, considers individual hydropower plants, thermal power plants and other sources, multiple water users, expansion of the system and is solved by nonlinear programming (NLP) using the General Algebraic Modeling System (GAMS) package. A typical optimization problem with 15 thousand decision variables is solved in few minutes. Preliminary results with a new stochastic version were obtained, but only 10 scenarios in a "fork" scheme of branching required many hours processing. Several improvements are needed to directly incorporate the stochasticity of the inflows and load levels to represent hourly load variation. The approach is based on a two-stage stochastic programming with recourse. The multi-stage inflow scenario tree is first built. The first stage is deterministic using inflow forecasts resulting one scenario independent decision. The second stage branches out into possible scenarios. The branching can be scaled up gradually until the end of the planning horizon. To reduce the size of the stochastic programming with recourse problem we need to continue investigating different scenario tree schemes and reduction methods as well as methods that can be used to reduce the simulation time of the underlying hydrothermal model. These include a complete reformulation of the model, the software interface, the database, the development of algorithms to generate better initial solutions for the NLP model, simplifications of the nonlinearities of the problem, shortening of the planning horizon, analyzing the use of three different load levels for demands and production, and using variable time periods in the planning horizon. (AU)

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
MENDES, LUDMILSON ABRITTA; LEME DE BARROS, MARIO THADEU; ZAMBON, RENATO CARLOS; YEH, WILLIAM W-G. Trade-Off Analysis among Multiple Water Uses in a Hydropower System: Case of Sao Francisco River Basin, Brazil. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT, v. 141, n. 10 OCT 2015. Web of Science Citations: 9.
XU, BIN; ZHONG, PING-AN; ZAMBON, RENATO C.; ZHAO, YUNFA; YEH, WILLIAM W. -G. Scenario tree reduction in stochastic programming with recourse for hydropower operations. WATER RESOURCES RESEARCH, v. 51, n. 8, p. 6359-6380, AUG 2015. Web of Science Citations: 15.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.