Johnson Controls Technology Company

Johnson Controls Tyco IP Holdings Llp

Tyco Fire + Security Gmbh

Hitachi-johnson Controls Air Conditioning, Inc.

Matthew J Asmus

Graeme Willmott

Michael J Wenzel

Robert D Turney

Mohammad N ElBsat

Kirk H Drees

Ryan C Beaty

Shawn A Schlagenhaft

James P Kummer

Jared W Fread

Ryan A Baumgartner

Homero L Noboa

Peter A Craig

Nicole Ann Madison

Carol T Tumey

Bradley J Ridder

Saman Beyhaghi

Steven R Vitullo

John H Burroughs

Tricia J Valentine

Collin W Eggert

Peter A Kinsella

J Carlin Walser

Matthew J Ellis

Andrew J Przybylski

Justin Patrick Kauffman

Anas W I Alanqar

Liming Yang

Lisa E Strand

Justin J Seifi

Dennis J Flood

Joseph P Carmody

Maxwell J Neuman

Steven C Snyder

A system includes processors configured to perform operations including obtaining a base design resource production of a building asset and a base resource production data set comprising a base resource production of the building asset at a plurality of operating points, calculating a scaled resource production data set comprising a scaled resource production of the building asset at the plurality of operating points by scaling the base resource production data set based on a new design resource production of the building asset relative to the base design resource production of the building asset, generating a resource consumption data set comprising a resource consumption of the building asset at the plurality of operating points based on the scaled resource production data set, and initiating an automated action based on the scaled resource production data set and the resource consumption data set.

Central plant optimization system with scalable asset models

A method includes providing a control algorithm that may include a constraint constraining production of the equipment below maximum values for a plurality of time steps, and dynamically adjusting the constraint by updating the maximum values as a function of predicted values of a dynamic variable for the plurality of time step. The dynamic variable affects an actual maximum production of the equipment. The method includes determining control decisions for the plurality of time steps by executing the control algorithm and controlling the equipment in accordance with the control decisions.

Control system for building equipment with dynamic capacity constraints

A controller for equipment that operate to provide heating or cooling to a building or campus includes a processing circuit configured to obtain utility rate data indicating a price of resources consumed by the equipment to serve energy loads of the building or campus, obtain an objective function that expresses a total monetary cost of operating the equipment over an optimization period as a function of the utility rate data and an amount of the resources consumed by the equipment, determine a relationship between resource consumption and load production of the equipment, optimize the objective function over the optimization subject to a constraint based on the relationship between the resource consumption and the load production of the equipment to determine a distribution of the load production across the equipment, and operate the equipment to achieve the distribution.

High level central plant optimization

Disclosed herein are a system, method, and non-transitory computer readable medium for operating an energy plant. In one aspect, a system determines a ratio of flow rates between devices of the energy plant connected in parallel with each other in a branch. The system generates a candidate set of operating parameters of the devices according to the ratio of flow rates. The system predicts thermodynamic states of the devices operating according to the candidate set of operating parameters. The system determines whether the predicted thermodynamic states satisfy constraints of the devices. The system determines whether the predicted thermodynamic states satisfy a target thermal energy load of the branch based on the ratio of the flow rates. The system operates the energy plant according to the candidate set of operating parameters, in response to determining that the predicted thermodynamic states satisfy the constraints and the target thermal energy load.

Central plant control system with setpoints modification based on physical constraints

A controller for a plurality of interconnected devices in a system is shown. The controller includes a processing circuit configured to detect that a first device of the plurality of interconnected devices is unavailable and identify a second device of the plurality of interconnected devices schematically dependent upon the first device by conducting a graph theory analysis on schematic relationships indicating connections among the plurality of interconnected devices. The processing circuit is further configured to, in response to identifying the second device schematically dependent upon the first device, generate a reduced subset of the plurality of interconnected devices that excludes the second device. The processing circuit is further configured to operate the reduced subset to transfer one or more resources among the reduced subset via the connections.

Systems and methods to automatically link availability of series devices in a plant

A system for controlling building equipment determines a degradation factor for a first asset of the building equipment by comparing a design curve for the first asset and operational data for the first asset. The design curve includes a plurality of data points that define an operation of the first asset. The system generates an operational curve for the first asset by derating the design curve based on the degradation factor and operates the building equipment based on the operational curve.

Control system for building equipment with equipment model adaptation

An energy optimization system for a building includes a processing circuit configured to generate a user interface including an indication of one or more economic load demand response (energy) operation parameters, one or more first participation hours, and a first load reduction amount for each of the one or more first participation hours. The processing circuit is configured to receive one or more overrides of the one or more first participation hours from the user interface, generate one or more second participation hours, a second load reduction amount for each of the one or more second participation hours, and one or more second equipment loads for the one or more pieces of building equipment based on the received one or more overrides, and operate the one or more pieces of building equipment to affect an environmental condition of the building based on the one or more second equipment loads.

Building energy optimization system with economic load demand response (ELDR) optimization and ELDR user interfaces

Disclosed herein are related to a system, a method, and a non-transitory computer readable storing instructions for operating an energy plant comprised of heating, ventilation and air conditioning (HVAC) devices. In one aspect, the system generates gradient data indicating a gradient of operating performance of the energy plant with respect to values of a plurality of control variables of HVAC devices. The system determines, from the plurality of control variables, a reduced group of control variables of the HVAC devices based on the gradient data. The system determines a set of values of the reduced group of control variables. The system operates the energy plant according to the determined set of values of the reduced group of control variables.

Central plant control system with computation reduction based on sensitivity analysis

A system for controlling a subplant comprising one or more assets includes one or more memory devices having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to perform operations including generating a design curve for a first asset included in the subplant based on an asset model, the design curve comprising a plurality of data points that define an operation of the first asset, obtaining operational data for the first asset, determining a degradation factor for the first asset by comparing the design curve and the operational data, generating an operational curve for the first asset by derating the design curve based on the degradation factor, and operating the subplant based on the operational curve.

Central plant optimization system with equipment model adaptation

Disclosed herein are related to a system, a method, and a non-transitory computer readable medium for operating an energy plant. In one aspect, the system generates a regression model of a produced thermal energy load produced by a supply device of the plurality of devices. The system predicts the produced thermal energy load produced by the supply device for a first time period based on the regression model. The system determines a heat capacity of gas or liquid in the loop based on the predicted produced thermal energy load. The system generates a model of mass storage based on the heat capacity. The system predicts an induced thermal energy load during a second time period at a consuming device of the plurality of devices based on the model of the mass storage. The system operates the energy plant according to the predicted induced thermal energy load.

Central plant control system based on load prediction through mass storage model

Disclosed herein are related to a method, a system, and a non-transitory computer readable medium storing instructions for operating a group of central plant equipment to serve thermal energy loads of a building or building system. In one approach, a base capacity of one or more devices of the group of central plant equipment is identified. A change in requested load allocated to the one or more devices crossing the base capacity at a crossover time may be detected. In one approach, an adjusted capacity of the one or more devices is set such that the adjusted capacity is offset from the base capacity before the crossover time and decays toward the base capacity during a decay period after the crossover time. The requested load allocated may be compared with the adjusted capacity after the crossover time. The group of central plant equipment may be operated according to the comparison.

Central plant control system with decaying capacity adjustment

A control system for a central energy facility with distributed energy storage includes a high level coordinator, a low level airside controller, a central plant controller, and a battery controller. The high level coordinator is configured to perform a high level optimization to generate an airside load profile for an airside system, a subplant load profile for a central plant, and a battery power profile for a battery. The low level airside controller is configured to use the airside load profile to operate airside HVAC equipment of the airside subsystem. The central plant controller is configured to use the subplant load profile to operate central plant equipment of the central plant. The battery controller is configured to use the battery power profile to control an amount of electric energy stored in the battery or discharged from the battery at each of a plurality of time steps in an optimization period.

Control system for central energy facility with distributed energy storage

A system for monitoring and controlling a central plant includes a high level optimizer, a subplant monitor, a user interface, and a dispatch graphical user interface (GUI) generator. The central plant includes a plurality of subplants configured to serve a thermal energy load. The high level optimizer is configured to determine recommended subplant loads for each of the plurality of subplants. The subplant monitor is configured to monitor the central plant and identify actual subplant loads for each of the plurality of subplants. The user interface is configured to receive manual subplant loads specified by a user. The dispatch GUI generator is configured to generate a dispatch GUI and present the dispatch GUI via the user interface. The dispatch GUI includes the recommended subplant loads, the actual subplant loads, and the manual subplant loads.

Systems and methods for monitoring and controlling a central plant

A controller for an energy plant includes a processing circuit having a processor and memory which stores instructions executed by the processor. The processing circuit is configured to identify, from a plurality of thermodynamic states affected by a plurality of heat, ventilation, and air conditioning (HVAC) devices, a reduced subset of the plurality of thermodynamic states to be predicted based on connections between the plurality of HVAC devices. The processing circuit is configured to predict values of the reduced subset of the plurality of thermodynamic states and operate the plurality of HVAC devices based on the predicted values of the reduced subset of the plurality of thermodynamic states.

Growing community of inventors

Watertown, WI, United States of America

Matthew J Asmus