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A Multiparametric Approach to Monetizing Demand Flexibility on Power Networks

Energy storage and demand flexibility are becoming increasingly important features of our power networks. While the effect of current installations tends to be small, large utility-scale storage will need to account for its effect on market prices and network congestion when optimizing its operation. In general, considering these effects yields non-convex bi-level problems for market participants, however we show that these problems can be solved exactly using techniques from multiparametric programming. We illustrate the results through the cost-minimization problem of a large utility possessing energy storage distributed across a network. We will also demonstrate further applications of this approach to the siting and sizing of energy storage, transmission planning, and strategic bidding.

Type of Seminar:
IfA Seminar
Jonathan Mather
Aug 11, 2016   1.00 pm

Contact Person:

Florian Dörfler
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Biographical Sketch:
Bio: Jonathan Mather is a 4th year PhD Candidate in Mechanical Engineering at UC Berkeley, supervised by Prof. Kameshwar Poolla. He received his MEng. degree in Engineering Science from the University of Oxford in 2013. His research interests are focused on the techno-economics of power systems and energy markets, with a particular focus on the integration and operation of flexible resources such as energy storage.