Toru Namerikawa on Robust Optimization for Energy Management Systems with Renewables
The talk deals with photovoltaics (PV) power prediction problem and optimal management of energy storage.
You can meet Toru Namerikawa at ITS, Wednesday the 23rd of January.
At first, I describe a prediction interval (PI) method using a copula, which can express the relation between a multivariable joint distribution and each marginal distribution.
Then, the energy storage optimization problem in a building is developed. A scenario robust (SR) optimization theorem, which calculates the robustness of the optimal solution, is applied to the proposed PI method, and hence we obtain an optimal energy storage solution taking the robustness of the solution into account. Additionally, we propose a method which combines a model predictive control (MPC) technique and SR to reduce the total electricity costs. The simulation results finally illustrate the cost reduction and robustness properties of the proposed method.
Toru Namerikawa received the B.E., M.E and Ph.D of Engineering degrees in Electrical and Computer Engineering from Kanazawa University, Japan, in 1991, 1993 and 1997, respectively. He is currently a Professor at Department of System Design Engineering, Keio University, Yokohama, Japan. He held visiting positions at Swiss Federal Institute of Technology in Zurich in 1998, University of California, Santa Barbara in 2001, University of Stuttgart in 2008 and Lund University in 2010.
He received 2014 Pioneer Technology Award from SICE Control Division and 2017 Outstanding Paper Award from SICE.
His main research interests are robust control, distributed and cooperative control and their application to power network systems.