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Strategy and Modeling for Building DR Optimization



Richard Lau, Sami Ayyorgun, Siun Chuon Mau, Archan Misra, David Holmberg, Steven T. Bushby


While it is well recognized that renewable microgrid generation and intelligent storage can significantly reduce a building's need for grid power and its peak loading, there is currently no sound and generalized approach to combine these two technologies. Further, loads are becoming increasingly responsive, in terms of both sheddability and shiftability. In this paper, we formulate the building energy management problem based on a demand-response (DR) adaptation framework that extends the traditional "supply-demand matching" to a "supply-store-demand-time-shift-utility adaptation" paradigm. Stochastic modeling of distributed-energy resources (DER) and measurement-based stochastic models of loads are used to approximately optimize building DR actions. Compared to systems that have no DR, the proposed optimization achieves savings in the range of approximately 35 to 70 %, depending on the amount of energy storage, the flexibility of the loads, and the accuracy of the stochastic models.
Proceedings Title
Proceedings of the Second IEEE International Conference on Smart Grid Communications
Conference Dates
October 17-20, 2011
Conference Location
Brussels, BE


commercial buildings, demand response, energy storage, load modeling, local renewable, optimization policy


Lau, R. , Ayyorgun, S. , Mau, S. , Misra, A. , Holmberg, D. and Bushby, S. (2011), Strategy and Modeling for Building DR Optimization, Proceedings of the Second IEEE International Conference on Smart Grid Communications, Brussels, BE, [online], (Accessed February 26, 2024)
Created October 16, 2011, Updated October 12, 2021