公开(公告)号：US20200218208A1

公开(公告)日：2020-07-09

申请号：US16240028

申请日：2019-01-04

Applicant: Johnson Controls Technology Company

Inventor： ANAS W. I. ALANQAR ,  MATTHEW J. ELLIS ,  MICHAEL J. WENZEL ,  JUAN ESTEBAN TAPIERO BERNAL

IPC: G05B15/02 ,  G05B23/02 ,  G06Q10/04

Abstract: A building management system includes building equipment operable generate training data relating to behavior of a building system and a controller configured to perform a system identification process that includes generating a prediction error function based on the training data and a system model, generating initial guesses of one or more parameters of the system model, running an optimization problem of the prediction error function for a first group of iterations, discarding, after the first group of iterations, a portion of the initial guesses based on one or more criteria and ranking a remaining portion of the initial guesses, running the optimization problem of the prediction error function for a top-ranked initial guess of the remaining portion to local optimality to identify a first set of values of the one or more parameters, and identifying the one or more parameters as having the first set of values.

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.

公开(公告)号：US20210173366A1

公开(公告)日：2021-06-10

申请号：US16703514

申请日：2019-12-04

Applicant: Johnson Controls Technology Company

Inventor： ROBERT D. TURNEY ,  MICHAEL J. WENZEL ,  MOHAMMAD N. ELBSAT ,  LIMING YANG ,  MATTHEW J. ELLIS ,  MASAYUKI NONAKA

IPC: G05B19/042

Abstract: An environmental control system of a building including a first building device operable to affect environmental conditions of a zone of the building by providing a first input to the zone. The system includes a second building device operable to independently affect a subset of the environmental conditions by providing a second input to the zone and further includes a controller including a processing circuit. The processing circuit is configured to perform an optimization to generate control decisions for the building devices. The optimization is performed subject to constraints for the environmental conditions and uses a predictive model that predicts an effect of the control decisions on the environmental conditions. The processing circuit is configured to operate the building devices in accordance with the control decisions.

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.