公开(公告)号：US20190079473A1

公开(公告)日：2019-03-14

申请号：US16115290

申请日：2018-08-28

Applicant: Johnson Controls Technology Company

Inventor： RANJEET KUMAR ,  MICHAEL J. WENZEL ,  MATTHEW J. ELLIS ,  MOHAMMAD N. ELBSAT ,  KIRK H. DREES ,  VICTOR MANUEL ZAVALA TEJEDA

IPC: G05B13/04 ,  G06Q40/00 ,  G06Q50/06 ,  G06Q10/06 ,  H02J3/38

Abstract: A building energy system includes equipment configured to consume, store, or discharge one or more energy resources purchased from a utility supplier. At least one of the energy resources is subject to a demand charge. The system further includes a controller configured to determine an optimal allocation of the energy resources across the equipment over a demand charge period. The controller includes a stochastic optimizer configured to obtain representative loads and rates for the building or campus for each of a plurality of scenarios, generate a first objective function comprising a cost of purchasing the energy resources over a portion of the demand charge period, and perform a first optimization to determine a peak demand target for the optimal allocation of the energy resources. The peak demand target minimizes a risk attribute of the first objective function over the plurality of the scenarios. The controller is configured to control the equipment to achieve the optimal allocation of energy resources.

公开(公告)号：US20180314220A1

公开(公告)日：2018-11-01

申请号：US15963891

申请日：2018-04-26

Applicant: Johnson Controls Technology Company

Inventor： RANJEET KUMAR ,  MICHAEL J. WENZEL ,  MATTHEW J. ELLIS ,  MOHAMMAD N. ELBSAT ,  KIRK H. DREES ,  VICTOR MANUEL ZAVALA TEJEDA

IPC: G05B19/042 ,  G06Q30/02

CPC classification number: G05B19/042 ,  G05B15/02 ,  G05B2219/25387 ,  G05B2219/2639 ,  G05B2219/2642 ,  G06Q30/0283

Abstract: A building energy system includes equipment and an asset allocator configured to determine an optimal allocation of energy loads across the equipment over a prediction horizon. The asset allocator generates several potential scenarios and generates an individual cost function for each potential scenario. Each potential scenario includes a predicted load required by the building and predicted prices for input resources. Each individual cost function includes a cost of purchasing the input resources from utility suppliers. The asset allocator generates a resource balance constraint and solves an optimization problem to determine the optimal allocation of the energy loads across the equipment. Solving the optimization problem includes optimizing an overall cost function that includes a weighted sum of individual cost functions for each potential scenario subject to the resource balance constraint for each potential scenario. The asset allocator controls the equipment to achieve the optimal allocation of energy loads.