Phase 2- Advanced Optimization Algorithms for Hydropower Dispatch

Project ID: 3906
Principal Investigator: David Harpman
Research Topic: Improved Power Generation
Priority Area Assignments: 2012 (Climate Adaptation)
Funded Fiscal Years: 2012 and 2013
Keywords: hydropower, optimal unit dispatch, optimization, heuristic algorithms

Research Question

Every hour the Bureau of Reclamation's (Reclamation) powerplant operators solve the unit dispatch problem. They must make a decision on which generator units to operate and set their output levels. Substantial gains can be realized from even small improvements in dispatch efficiency. Increasing the efficiency at Glen Canyon Dam by 2 percent would increase the economic value of the water released annually by $4,574,000 (2010 $).

Within the last 30 years, a variety of new optimization heuristics have been described in the power engineering literature. These heuristic approaches rely on innovative search techniques drawn from biological and physical processes. Although computationally intensive, these methods can solve difficult constrained optimization problems, like the unit dispatch problem, quickly and reliably.

We will develop computer code for several of the most promising of these new optimization approaches, apply these algorithms to example unit dispatch problems, and systematically assess their performance. The goal of this effort is to identify algorithms that can help guide the hydropower unit dispatch decision and improve efficiency. Improved dispatching efficiency will result in the generation of more electric power using less water, benefitting all water and power users.

Need and Benefit

The supervisory control and data acquisition (SCADA) systems installed at the preponderance of Reclamation hydropower plants (53 out of 57 plants) do not have an optimization package to assist with dispatch decisions. Powerplant operators use professional experience, acquired skill, and judgment to achieve powerplant efficiency, often relying on the equal loading rule of thumb. Savvy operators also try to minimize start/stop cycles and adjust generation rates while avoiding operation within each unit's rough zone(s).

The SCADA systems at a few of Reclamation's larger and more modern hydropower plants have been retrofitted with optimization software. Reclamation is in the process of installing the U.S. Army Corps of Engineers'
T-2 optimization system at Grand Coulee. Hungry Horse is remotely operated from Grand Coulee. An optimization routine developed by Steven Stitt, a retired Reclamation employee, has been used at Hoover Dam for several years and will be installed at Yellowtail by the end of 2011. Glen Canyon Dam is the focus of an optimization effort by Argonne National Laboratory, although the timing and details remain somewhat vague. Experience has shown these programs result in increased power revenues and potentially reduced maintenance and mechanical equipment repairs since operation within rough zones and start and stop cycles are minimized.

The benefits of this proposed research can be extended to powerplants in all Reclamation regions. The goal of this research project is to identify newly emergent algorithms suitable for the real-time solution of the hydropower economic dispatch problem. These algorithms can be embedded in a powerplant's SCADA system and help guide the dispatch decision process. Improved dispatching efficiency will result in the generation of more electric power using less water, benefitting water and power users as well as the American taxpayer.

Contributing Partners

Argonne National Laboratory, Department of Energy

Research Products

Bureau of Reclamation Review

The following documents were reviewed by experts in fields relating to this project's study and findings. The results were determined to be achieved using valid means.

Phase 2-- Advanced Algorithms for Hydropower Dispatch (final, PDF, 2.0MB)
By David Harpman
Report completed on December 12, 2013

Four promising evolutionary algorithms (EA's); the real coded genetic algorithm (RCGA), differential evolution (DE), particle swarm optimization (PSO) and the artificial bee colony optimization (ABCO) algorithm were applied to the unit dispatch problem. Experimental evidence indicates these algorithms can provide near real-time solutions and guidance for everyday operational decisions at Reclamation's hydropower plants.
Keywords: hydropower dispatch, heuristic algorithms, optimization

Last Updated: June 29, 2015