Real-Time Dispatch for Multi-Unit Hydroelectric Plants With AC Optimal Power Flow: The Case of the Santo Antonio System

Abstract

The growing demand for green energy has driven the building of large-capacity hydroelectric plants away from the load centers. In this setting, one key aspect is constructing electrical networks for efficient power transmission to the primary grid, which is sometimes combined with high-voltage direct current systems. However, in-site applications based on real-time dispatch problems often do not model the AC power flow (ACPF) constraints, partly due to a lack of appealing methods to simultaneously include the dispatch and ACPF operating characteristics. Furthermore, a precise hydropower production function, a priority in this kind of problem, can introduce additional complexity, and practical applications commonly sacrifice the grid-connection modeling. This paper proposes a technique for incorporating ACPF constraints in real-time hydro dispatch, promoting widespread methods and optimization tools. The presented strategy is based on mixed-integer quadratic programming that yields convergent electrical variables compatible with exact ACPF to minimize a compromise between transmission losses and turbined outflow. The testbed is the Santo Antônio system, composite by 50 generating units, 13 power transformers, and 41 buses. Simulations based on real-life data demonstrate the impact of ACPF modeling, achieving losses reduction consistently above 5%, at the cost of a higher processing time.

Hydropower Operation Optimization Using Machine Learning: A Systematic Review

“…However, there are indeed plants with many generators units that would benefit from ML application. For example, the work [90] deals with the dispatch of the Santo Antonio plant, a hydropower plant in the Amazon basin in Brazil with 50 generator units. The explosive number of generating units combinations possible to dispatch the hydropower plant open the way for ML application.…”