Welcome to PENSA at Princeton University

PENSA is the home of the SAP Initiative for Energy Systems Research at Princeton University. Our goal is to bring advanced analytical thinking to the development of new energy technologies, the rigorous study of energy policy, and the efficient management of energy resources.

The 2012 annual report for PENSA's activities is now available here.

Research associate Arta Jamshidi presents his latest work in Dirichlet clouds, a semi-parametric statistical method designed for recursive estimation with exceptionally fast updating. The method is being designed for stochastic search, which arises throughout applications in energy systems. We eventually hope to use it as a general purpose approximation strategy in approximate dynamic programming algorithms.

PENSA is undertaking a major project to develop SMART-ISO, and advanced stochastic simulator of the PJM grid. Special care is being used to model uncertainty. The first project will be the analysis of off-shore wind in a DOE-funded project with the University of Delaware. For more on SMART-ISO, see http://energysystems.princeton.edu/smartiso.htm.

We have begun two projects managing energy systems for buildings. The first is a model of energy flows for Princeton University, which involves optimizing the chilled water energy storage facility with energy from the grid (at spot prices), gas turbine, and a diesel generator. The university operates several boilers and eight chillers. These have to be optimized to meet campus loads while minimizing exposure to real-time spot prices. A separate project involves optimizing steam generation for building loads, given the complex peak-load pricing policy of Consolidated Edison of New York.

Warren Powell met with members of the NJ state legislature and the Bureau of Public Utilities to help Tom Nyquist and Ted Borer from Princeton University explain new rules that might stabilize solar renewable energy credit markets. A multiagent simulator developed by Will Harrel '13 helped to analyze the effect of the newrules.

Warren Scott designed a direct policy search algorithm using his adaptation of the knowledge gradient algorithm for continuous parameters, resulting in a battery storage policy that produced solutions within 5-10 percent of a benchmark optimal policy. Along the way, he demonstrated the equivalence of projected Bellman error minimization and Bellman error minimization using instrumental variables (but neither of these worked as well as direct policy search). Warren defended his dissertation in May.

Ricardo Collado kicks off the summer luncheon series for PENSA with a lecture on dynamic risk measures. 19 attended, including 6 summer interns, 5 graduate students, 5 post-docs and 3 faculty/staff. Risk plays an important role in the management of energy systems.