A MULTIPLE-BUILDING OPTIMIZATION SCHEME BASED ON STATISTICAL BUILDING-LOAD MODELS
Leslie K. Norford, Hai-Yun Xing
This paper presents an optimization process for multiple-building load aggregation based on statistical models of building dynamics. The aggregation process is modeled as a central optimizer and participating buildings as unit simulators. By learning from whole- building simulation results, unit simulators describe individual buildings’ base-load profiles and responses to control parameter changes. The optimizer makes supervisory control decisions based on a centralized objective function which takes inputs from individual simulators. A non-linear mathematical optimization problem is formulated and solved using an interior- point-method commercial solver. Results are compared to simple cases for which optimal or near-optimal results are relatively easy to find. The expansion of the analytical framework is discussed.
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