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：US20210207839A1

公开(公告)日：2021-07-08

申请号：US17181847

申请日：2021-02-22

Applicant: Johnson Controls Technology Company

Inventor： KIRK H. DREES ,  TIMOTHY C. GAMROTH ,  CRAIG E. TRIVELPIECE ,  JOSEPH PICCOLO, III

IPC: F24F11/63 ,  G05B19/042

Abstract: A system for controlling air quality of a building space includes HVAC equipment configured to serve the building space, sensors configured to measure a plurality of parameters relating to the building space, and a control system. The control system is configured to receive data from the sensors, determine a feedforward air quality contribution, determine a feedback air quality contribution based on a measured air quality and an air quality setpoint for the building space, combine the feedforward air quality contribution and the feedback air quality contribution to determine a target amount of ventilation or filtration to be provided to the building space by the HVAC equipment, and control the HVAC equipment to provide the target amount of ventilation or filtration.

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：US20160379319A1

公开(公告)日：2016-12-29

申请号：US15199622

申请日：2016-06-30

Applicant: JOHNSON CONTROLS TECHNOLOGY COMPANY

Inventor： KIRK H. DREES ,  JAMES P. KUMMER ,  MICHAEL J. WENZEL

IPC: G06Q50/06 ,  G01R21/133

CPC classification number: G06Q50/06 ,  G01R21/00 ,  G01R21/1333 ,  G06Q10/06

Abstract: A system for measuring and verifying energy savings resulting from energy conservation measures in a building includes one or more energy meters and a controller. The energy meters are configured to measure an actual amount of building energy usage The controller is configured to determine an actual amount of energy savings resulting from the energy conservation measures during the measurement and verification period and to calculate a least amount of energy savings resulting from the energy conservation measures. The least amount of energy savings is a lower confidence bound on the actual amount of energy savings. The controller is configured to cause a building management system for the building to stop performing a measurement and verification process before a normal end of the measurement and verification period in response to the least amount being greater than a target amount of energy savings to be achieved by the energy conservation measures.

Abstract translation: 用于测量和验证由建筑物中的节能措施产生的节能的系统包括一个或多个能量计和控制器。 能量计被配置为测量建筑物能量使用的实际量。控制器被配置为确定在测量和验证期间由节能措施产生的实际节能量，并且计算由 节能措施。 节能量最少的是对实际节能量的信心下降。 控制器被配置为使得建筑物的建筑物管理系统在测量和验证周期的正常结束之前停止执行测量和验证过程，以响应于最小量大于要达到的目标能量节省量 节能措施。

公开(公告)号：US20180254632A1

公开(公告)日：2018-09-06

申请号：US15474511

申请日：2017-03-30

Applicant: Johnson Controls Technology Company

Inventor： MOHAMMAD N. ELBSAT ,  MICHAEL J. WENZEL ,  KIRK H. DREES

IPC: H02J3/00 ,  H02J5/00 ,  G05B19/042

Abstract: An energy storage system for a building includes a battery asset configured to store electricity and discharge the stored electricity for use in satisfying a building electric load. The system includes a planning tool configured to identify one or more selected functionalities of the energy storage system and generate a cost function defining a cost of operating the energy storage system over an optimization period. The cost function includes a term for each of the selected functionalities. The planning tool is configured to generate optimization constraints based on the selected functionalities, attributes of the battery asset, and the electric energy load to be satisfied. The planning tool is configured to optimize the cost function to determine optimal power setpoints for the battery asset at each of a plurality of time steps of the optimization period.