Johnson Controls Technology Company

Johnson Controls Tyco IP Holdings LLP

Con Edison Battery Storage, LLC

Tyco Fire + Security Gmbh

Johnson Service Company

Johnson Controls Technology LLC

Tyco Fire & Security Gmbh

Taurus Des, LLC

Johnson Controls Gmbh

Kirk H Drees

Michael J Wenzel

Mohammad N ElBsat

James P Kummer

Jonathan D Douglas

Homero L Noboa

Robert D Turney

Brennan H Fentzlaff

Michael Risbeck

Clay G Nesler

Brett M Lenhardt

John Ismael Ruiz

Young Min Lee

Andrew J Boettcher

Paul Harrison Rode

Derek Supple

Marc D Andraca

Timothy I Salsbury

Matthew J Ellis

John E Seem

Matthew J Asmus

Carlos Felipe Alcala Perez

Timothy C Gamroth

Marcello Passoni

Gerald A Duenkel

Zhanhong Jiang

Herbert J Doll

Andrew J Przybylski

Shawn D Schubert

Camille M Aucoin

Thomas M Seneczko

John M House

Vineet Binodshanker Sinha

James Byron Burke

John H Burroughs

Bernard Clement

Vivek V Gupta

Sugumar Murugesan

Radu M Dorneanu

Abu Bakr Khan

Mark T Fischbach

Viswanath Ramamurti

Jack A Peterson

David S Eidson

Rachel A Glanzer

Nebil Ben-Aissa

Craig Evan Trivelpiece

Joseph Piccolo, Iii

Kevin A Weiss

Steven R Vitullo

Gaylon M Decious

Michael James Risbeck

Jonathan D West

Donald R Albinger

Duane S Freimuth

Ryan A Baumgartner

William R Kuckuk

Alex Bernaden, Iii

Ranjeet Kumar

Sudhi R Sinha

Vaidhyanathan Venkiteswaran

Miguel Galvez

Karl F Reichenberger

Curtis Christian Crane

Walter Andrew Martin

Gary A Romanowich

Kenneth J Sieth

Graeme Willmott

Ryan A Piaskowski

Donald A Gottschalk

Justin Patrick Kauffman

David E Rasmussen

Russell T Jenks

Thomas O Kautz

Christopher Merkl

John T Pierson

Dimitrios S Papadopoulos

Jason T Sawyer

Daniel M Curtis

Juan Esteban Tapiero Bernal

Rachel D M Ellerman

Dinesh Trikha

Jeffrey J Gloudeman

Kyle M Bero

Hunter R Hobgood

George J Janu

Juliet A Pagliaro Herman

Nicholas P Prato

Terrill R Laughton

Siddharth Goyal

Mohammad N EIBsat

Serdar Suindykov

Mark L Ziolkowski

Joseph C Jones

Matthew J Deloge

Victor Zavala Tejeda

Dominic B Ticali

Bin Chen

A cascaded control system for coordinating and controlling carbon emissions associated with operating building equipment distributed across a plurality of subsystems includes a first controller configured to generate carbon emissions targets for each of a plurality of subsystems using a predictive control process that accounts for an aggregate carbon emissions of the plurality of subsystems predicted to result from the carbon emissions targets. The cascaded control system also includes a plurality of second controllers, each corresponding to one of the plurality of subsystems and configured to generate control decisions for building equipment of the corresponding subsystem that are predicted to cause the building equipment to achieve the carbon emissions targets for the corresponding subsystem; and operate the building equipment of the corresponding subsystem using the control decisions.

Building control system with predictive control of carbon emissions using marginal operating emissions rate

An infection control tool for a building HVAC system includes processing circuitry configured to receive one or more inputs defining a HVAC system configuration for each of a baseline scenario and one or more other scenarios. The processing circuitry is also configured to estimate infection risk and at least one of energy consumption or operating cost for each of the one or more other scenarios relative to the baseline scenario. The processing circuitry is also configured to operate a display to provide the infection risk and at least one of the energy consumption or operating cost to a user.

Infection control tool for HVAC system

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.

Building energy system with stochastic model predictive control and demand charge incorporation

A feedforward-feedback controller for integrated temperature and pressure control of a building space includes one or more processing circuits. The one or more processing circuits are configured to generate a supply air flow rate setpoint using a combined feedforward-feedback control process that (i) proactively compensates for a feedforward air flow disturbance in the building space and (ii) reactively compensates for a feedback air pressure error in the building space, generate a supply air temperature setpoint using a predictive temperature model that predicts the supply air temperature setpoint required to achieve a zone temperature setpoint for the building space when supply air is provided to the building space at the supply air flow rate setpoint and the supply air temperature setpoint, and operate building equipment to provide the supply air to the building space at the supply air flow rate setpoint and the supply air temperature setpoint.

Critical environment feedforward-feedback control system with room pressure and temperature control

A pathogen detection system for a building includes multiple pathogen detectors positioned in the building at different locations. The pathogen detectors are configured to output detection data including a detected presence of a pathogen. The pathogen detection system includes processing circuitry configured to obtain the detection data from the pathogen detectors. The processing circuitry is also configured to determine a responsive action based on the detected presence of the pathogen, and the locations. The responsive action includes a magnitude of effect and a magnitude of locality. The processing circuitry is configured to perform the responsive action or initiate the responsive action.

Systems and methods for on-site pathogen detection

A method for controlling building equipment includes providing a user interface comprising a graphical representation of a relationship between a carbon emissions control objective and a second control objective that competes with the carbon emissions control objective over a range of control strategies for the building equipment, and assigning a weight to the carbon emissions control objective or the second control objective in an objective function. The weight is associated with a control strategy that corresponds to a user selection based on the graphical representation. The method also includes generating control decisions for the building equipment using the objective function with the weight assigned to the carbon emissions control objective or the second control objective and operating the building equipment in accordance with the control decisions.

Building control system with multi-objective control of carbon emissions and occupant comfort

A building system operates to receive air quality measurements of a plurality of spaces of the building from a mobile air quality sensor, the mobile air quality sensor configured to collect the air quality measurements of the plurality of spaces while the mobile air quality sensor moves throughout the plurality of spaces of the building and provide the collected air quality measurements to the one or more processors. The air quality measurements include data identifying locations and times at which the air quality measurements were collected The building system operates to cause the one or more processors to store information, or a link to the information, in a database based on the collected air quality measurements, the database including a contextual representation of the plurality of spaces of the building and perform at least one operation using the information based on the air quality measurements.

Building data platform with air quality analysis based on mobile air quality sensors

A controller for heating, ventilation, or air conditioning (HVAC) equipment operable to affect an environmental condition of a building is configured to obtain predictive models that predict values of an energy control objective and an air quality control objective as a function of control decision variables for the HVAC equipment. The controller executes a multi-objective optimization process using the predictive models to produce multiple sets of optimization results corresponding to different values of the control decision variables, the energy control objective, and the air quality control objective. The controller selects one or more of the sets of optimization results based on the values of the energy control objective and the air quality control objective. The controller operates the HVAC equipment to affect the environmental condition of the building in accordance with the values of the control decision variables corresponding to a selected set of the optimization results.

Building HVAC system with multi-objective optimization control

A frequency response optimization system includes a battery, a power inverter, and a frequency response controller. The battery is configured to store and discharge electric power. The power inverter is configured to control an amount of the electric power stored or discharged from the battery. The frequency response controller includes a high level controller configured to determine values of clipping parameters and a low level controller configured to use the values of the clipping parameters to modify battery power setpoints. The power inverter is configured to use the modified battery power setpoints to control the amount of the electric power stored or discharged from the battery.

Frequency response control system with clipping parameter determination

A building manager includes a communications interface configured to receive time-of-use information from a smart energy grid and a processing circuit configured to process the time-of-use information received from the smart energy grid to generate load shedding decisions for building subsystems or devices including determining when to utilize energy from energy storage equipment. The processing circuit is configured to determine an amount of greenhouse gas emissions corresponding to the load shedding decisions and convert the amount of greenhouse gas emissions into tradable carbon credits. The processing circuit is configured to generate a graphical user interface including modules indicating the amount of greenhouse gas emissions, the tradable carbon credits, or energy savings resulting from the load shedding decisions. The processing circuit is configured to rearrange, resize, or reconfigure the modules or change the modules for different modules in response to a user input or selection provided via the graphical user interface.

Smart building manager

A building management system (BMS) operates a plurality of HVAC devices to affect a physical state or condition and detects a fault condition at a second HVAC device affected by the physical state or condition and having causal relationships with the plurality of HVAC devices such that faulty operation of one or more of the plurality of HVAC devices causes a detectable effect at the second HVAC device. The BMS identifies, based on the fault condition, a predetermined set of system parameters corresponding to the fault condition and comprising a plurality of system parameters of the plurality of HVAC devices that are potential causes of the fault condition. The BMS retrieves operating data for the predetermined set of system parameters and transmits a signal to display a user interface comprising the operating data on a display screen.

HVAC system with data driven user interface for equipment commissioning and operation

Systems and methods for reducing health risks with respect to an infectious disease in buildings. Health data for an infectious diseases is used to determine a health risk level for building spaces and individuals in the building. An air handling action or a disinfection action is performed based on the health risk level.

Air quality control and disinfection system

A building system that operates to receive a plurality of data samples from building equipment of the building and identity whether one or more data samples of the plurality of data samples are anomalous indicating that one or more pieces of the building equipment are possibly experiencing a fault. The building system operates to generate one or more data health scores for the building equipment based on whether the one or more data samples are anomalous, the one or more data health scores indicating quality levels of the plurality of data samples and generate user interface data configured to cause a user device to display a user interface providing indications of the one or more pieces of building equipment that are possibly experiencing the fault and the one or more data health scores.

Building system for building equipment with fault based data health operations

A heating, ventilation, or air conditioning system (HVAC) design and operational tool includes one or more processors and memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including obtaining a dynamic temperature model and a dynamic infectious quanta model for one or more building zones, determining an infection probability, and performing a plurality of simulations for a plurality of different equipment configurations using the dynamic temperature model, the dynamic infectious quanta model, and the infection probability to generate results. The operations include generating, using the results of the plurality of simulations, at least one of design including one or more recommended design parameters data or operational data including one or more recommended operational parameters for the HVAC system and initiating an automated action using at least one of the design data or the operational data.

HVAC system design and operational tool for building infection control

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

Growing community of inventors

Cedarburg, WI, United States of America

Kirk H Drees