Cornell University

Cornell Research Foundation Inc.

Christine A Shoemaker

David H Albonesi

Paula Petrica

Brandon Hencey

Adam M Izraelevitz

Howard Chong

Gregory J Whiffen

Methods, systems, and devices are disclosed for managing building power, in one aspect, a method for managing building power includes determining values for power usage of a heating, ventilation, or air conditioning (HVAC) system in one or more zones of a building, the values including a cost of power value, a comfort value, a weighting function between the cost of power value and the comfort value, or a thermal storage value, in which the determining the values is based on a plurality of parameters including a price of power, a time of use, a total power allocation, or random variables including weather and building occupancy factors, and determining a power level for a plurality of states based on the determined values, the plurality of states corresponding to different levels of power to operate the HVAC system in the one or more zones.

Building power management systems

The present disclosure provides methods and systems for managing power in a processor having multiple cores. In one implementation, a microarchitecture of a core within a general-purpose processor may include configurable lanes (horizontal slices through the pipeline) which can be powered on and off independently from each other within the core. An online optimization algorithm may determine within a reasonably small fraction of a time slice a combination of lanes within different cores of the processor to be powered on that optimizes performance under a power constraint budget for the workload running on the general-purpose processor. The online optimization algorithm may use an objective function based on response surface models constructed to fit to a set of sampled data obtained by running the workload on the general-purpose processor with multiple cores, without running the full workload. In other implementations, the power supply to lanes can be gated.

Multi-core computer processor based on a dynamic core-level power management for enhanced overall power efficiency

The present invention features a differential dynamic programming (DDP) method for computing optimal, time-varying pumping policies utilized in groundwater remediation. The strategy for treating the groundwater can use a feedback law generated by a constrained differential dynamic programming algorithm with penalty functions. The method has been tested in cases where there is uncertainty in the hydraulic conductivity. Confined transient aquifer flow and transport were modeled, using a two-dimensional Galerkin finite element scheme with implicit time differencing. Optimal policies were calculated using a given or 'measured' set of hydraulic conductivities and initial conditions. The optimal policies were applied using the same finite element model with a second, or 'true' set of conductivities The 'true' sets of conductivities were generated randomly from an autocorrelated lognormal distribution by the spectral method. The approach used had an advantage over other uncertainty approaches, because it was not necessary to specify precisely the probability distribution of each uncertain parameter. The method did not require any single probability distribution for each uncertain parameter. The relative weight assigned each penalty function was adjusted, which resulted in obtaining robust feedback laws that performed equally well under different, assumed error distributions. The water remediation method of this invention resulted in a cost savings within the approximate range of between 4% and 51% less than the cost of applying the calculated optimal policies without using a feedback law.

Feedback control of groundwater remediation

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Ithaca, NY, United States of America

Christine A Shoemaker