With the complexity of the grid is growing, a cooperative effort from the Pacific Northwest National Laboratory (PNNL) and the Midcontinent Independent System Operator (MISO) has yielded a new computational tool dedicated to helping operators manage that intricacy.
Traditionally, regional independent system operators managing wholesale markets handle planning and scheduling of the electricity supply, which currently come from a mix of power plants as well as distributed and intermittent energy resources — including renewable energy sources — which can make it tricky to align supply with predicted demand. All this must be done in about two to three hours, as part of a process known as security constrained unit commitment (SCUC), which includes settling bids, making offers, undergoing feasibility tests, and weighing minimum costs against generators’ limits and conditions.
The effort requires significant mathematical prowess under tight deadlines. What PNNL and MISO have created — High-Performance Power-grid Optimization (HIPPO) — represents is a much quicker solver of these calculations. It hastens resource scheduling and power market settlement by using multiple algorithms concurrently, running on either multiple workstations or in high performance computing environments.
“I am proud that after three years, the team, through close collaboration and hard work, was able to transform the proposed ideas into a technology embraced by industry,” Feng Pan, PNNL principle investigator, said. “The increased computation speed will potentially lower electricity costs and increase operational reliability and flexibility while enabling system operators to consider complex market designs to support a more diversified energy resource portfolio.”
In a comparison test with the current generation production solver used by MISO, HIPPO allowed grid operators to perform calculations up to 35 times faster. In terms of turnaround, calculations could go from taking up to two hours, to less than 20 minutes, without sacrificing optimal cost figures.
To achieve this, PNNL and MISO also partnered with Gurobi Optimization, GE Grid Solutions, the University of Florida, and Cognitive Analytics, after receiving initial funding by the U.S. Department of Energy’s Advanced Research Projects Agency-Energy.
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