Daniel Bienstock is a professor at the Industrial Engineering and Operations Research, and Applied Math and Applied Physics departments at Columbia University, where he has been since 1989. His research focuses on high-performance methodologies and computing implementations of algorithms for optimization problems, with special focus on large nonconvex and integer programming models. A second focus is on applications of optimization to problems arising in electrical power transmission. Please visit http://www.columbia.edu/~dano/ for more information on Daniel Bienstock.
When incorporating renewable sources, especially wind, this setup does not work so well because real-time wind fluctuations can be quite large (in either direction) and the frequency response framework can cause line flows to become very large, a phenomenon already observed in regions with high renewable penetration (e.g. Germany). In this talk we describe a modification to the OPF computation that takes into account the intermittent nature of wind by formulating a chance-constrained (stochastic) optimization problem that can be solved very quickly. We will describe some of the underlying mathematics, the computational tricks needed to make it run fast, and provide some examples of the methodology in action.
Light dinner will be provided. Attendance at the lecture will be for NJ and NY Metro INFORMS members. 2014 chapter dues of $10 for INFORMS National Member, $11 for Non-member or $3.00 for student or retiree.
Further information can be obtained by contacting Keh-Wei Lih at email@example.com. Visit NJ INFORMS Chapter home page at http://rutcor.rutgers.edu/~lih/informs/njchap.html