Johnson Controls Tyco IP Holdings Llp

Johnson Controls Technology Company

Tyco Fire & Security Gmbh

Con Edison Battery Storage, LLC

Hitachi-johnson Controls Air Conditioning, Inc.

Taurus Des, LLC

Mohammad N ElBsat

Michael J Wenzel

Robert D Turney

Kirk H Drees

Matthew J Ellis

Anas W I Alanqar

John H Burroughs

Matthew J Asmus

Andrew J Przybylski

Juan Esteban Tapiero Bernal

Brennan H Fentzlaff

Fang Du

Graeme Willmott

Brett M Lenhardt

Serdar Suindykov

James P Kummer

Vineet Binodshanker Sinha

James Byron Burke

Timothy C Gamroth

Shawn D Schubert

Radu M Dorneanu

Liming Yang

Peter A Craig

Yasutaka Yoshida

Masayuki Nonaka

Thomas M Seneczko

David S Eidson

Jingduo Fan

Sudhi R Sinha

Alan S Schwegler

Jiaqi Li

Nicole Ann Madison

Carol T Tumey

Leyla Mousavi

Kerry M Bell

Tricia J Valentine

Collin W Eggert

Bridget E Kapler

Kierstyn R Robbins

Homero L Noboa

Koji Naito

Rajiv Ramanasankaran

Young M Lee

Jonathan D Douglas

Michael Risbeck

Abhishek Gupta

John Ismael Ruiz

Michael James Risbeck

Ryan A Baumgartner

Payal Pancholi

Hayato Mori

Zhigang Wu

Yoshiko Watanabe

Christos T Maravelias

Nishith R Patel

Mark L Ziolkowski

Clay G Nesler

Matthew J Deloge

Zhizhong Pang

Victor Zavala Tejeda

Apoorva Gupta

Joseph C Jones

Joseph F Mann

Ganesh Kalpundi

Renee Clair

Anza D'Antonio

Farhad Balali

Nicolaus P Meyer

Ranjeet Kumar

Mikihito Tokudi

Yaqing Wu

Mori Hayato

Parisa Khosravi

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

An energy optimization system includes an asset sizing system to determine an asset size and to cause a new asset to be purchased or installed. The energy optimization system uses a cost function dependent on a cost of operating a building system and on an initial purchase price of the new asset. The new asset may be a heat recover chiller, a solar energy system, a hydroelectric system, or an energy storage system. The optimization may be performed subject to a constraint related to the use of a resource supplied to the building system by one or more utilities. The optimization may include minimizing a simple pay back period or to maximizing a rate of return on the purchase of the new asset.

Asset sizing with utility use constraints

A method includes providing a net consumption trajectory comprising net consumption targets for one or more subperiods of a time period. Each net consumption target indicates a target difference from a beginning of a time period to an end of the subperiod between total consumption and total production or offset. The method also includes generating, for a subperiod of the plurality of subperiods, a set of curtailment actions predicted to achieve the net consumption target for the subperiod and implementing the set of curtailment actions.

Generating set of curtailment actions predicted to achieve net consumption target for a subperiod

A model predictive maintenance (MPM) system for building equipment includes one or more processing circuits having one or more processors and memory. The memory store instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including estimating a degradation state of the building equipment, using a degradation impact model to predict an amount of one or more input resources consumed by the building equipment to produce one or more output resources based on the degradation state of the building equipment, generating a maintenance schedule for the building equipment based on the amount of the one or more input resources predicted by the degradation impact model, and initiating a maintenance activity for the building equipment in accordance with the maintenance schedule.

Model predictive maintenance system with degradation impact model

A controller for performing automated system identification. The controller includes processors and non-transitory computer-readable media storing instructions that, when executed by the processors, cause the processors to perform operations including generating a predictive model to predict system dynamics of a space of a building based on environmental condition inputs and including performing an optimization of a cost function of operating building equipment over a time duration to determine a setpoint for the building equipment. The optimization is performed based on the predictive model. The operations include operating the building equipment based on the setpoint to affect a variable state or condition of the space and include monitoring prediction error metrics over time. The operations include, in response to detecting one of the prediction error metrics exceeds a threshold value, updating the predictive model.

Systems and methods for automated system identification

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 system includes a first subsystem configured to produce a resource by consuming electricity, a second subsystem configured to produce the resource by consuming a fuel, and a controller. The controller is configured to determine an allocation of a predicted demand for the resource over a future time period between the first subsystem and the second subsystem based on a first carbon emissions rate associated with off-site production of the electricity and a second carbon emissions rate associated with on-site consumption of the fuel. The controller is also configured to control the first subsystem and the second subsystem to produce the resource in accordance with the allocation during the future time period.

Control system with multi-factor carbon emissions optimization

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 model predictive maintenance (MPM) system for building equipment includes one or more processing circuits including 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. The operations include obtaining one or more performance indicators for the building equipment and determining whether a trigger condition has been satisfied based on the one or more performance indicators. The operations include triggering a model predictive maintenance process to generate a maintenance schedule for the building equipment in response to determining that the trigger condition has been satisfied. The operations include initiating a maintenance activity for the building equipment in accordance with the maintenance schedule.

Model predictive maintenance system with event or condition based performance

A thermostat for a building zone includes at least one of a model predictive controller and an equipment controller. The model predictive controller is configured to obtain a cost function that accounts for a cost of operating HVAC equipment during each of a plurality of time steps, use a predictive model to predict a temperature of the building zone during each of the plurality of time steps, and generate temperature setpoints for the building zone for each of the plurality of time steps by optimizing the cost function subject to a constraint on the predicted temperature. The equipment controller is configured to receive the temperature setpoints generated by the model predictive controller and drive the temperature of the building zone toward the temperature setpoints during each of the plurality of time steps by operating the HVAC equipment to provide heating or cooling to the building zone.

Smart thermostat with model predictive control

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.

Building energy storage system with planning tool

A controller for operating building equipment of a building including processors and non-transitory computer-readable media storing instructions that, when executed by the processors, cause the processors to perform operations including obtaining a first setpoint trajectory from a cloud computation system. The first setpoint trajectory includes setpoints for the building equipment or for a space of the building. The setpoints correspond to time steps of an optimization period. The operations include determining whether a connection between the controller and the cloud computation system is active or inactive at a time step of the optimization period and determining an active setpoint for the time step of the optimization period using either the first or second setpoint trajectory based on whether the connection between the controller and the cloud computation system is active or inactive at the time step. The operations include operating the building equipment based on the active setpoint.

Building control system with features for operating under intermittent connectivity to a cloud computation system

A building system operates to receive building data from one or more building data sources associated with the building, wherein at least a portion of the building data is associated with control of the one or more environmental conditions of the building and generate, based on the building data, one or more data quality indicators for the building data received from the one or more building data sources, the one or more data quality indicators indicating quality levels of the building data. The building system operates to generate user interface data configured to cause a user device to display a user interface providing indications of the one or more data quality indicators.

Building system for building equipment with data health operations

One implementation of the present disclosure is a controller for a variable refrigerant flow system. The controller includes processors and memory storing instructions that, when executed by the processors, cause the processors to perform operations including identifying zones within a structure, generating zone groupings defining zone groups and specifying which of the zones are grouped together to form each of the zone groups, generating metric of success values corresponding to the zone groupings and indicating a control feasibility of a corresponding zone grouping, selecting a zone grouping based on the metric of success values, and using the selected zone grouping to operate equipment of the variable refrigerant flow system to provide heating or cooling to the zones.

Variable refrigerant flow system with zone grouping control feasibility estimation

A controller for equipment that operate to store, discharge, generate, or consume one or more resources is configured to provide an objective function indicating a total value of obtaining a resource from a utility provider over a plurality of time steps subject to a load-following-block rate structure. The objective function includes a first term representing a load-following-block of the resource as being sourced from the utility provider at a fixed rate and a second term representing a remainder of the resource as being sourced from the utility provider at a variable rate. The controller is configured to use the objective function to generate values for decision variables and control the equipment to store, discharge, generate, or consume amounts of the resources indicated by the values of the decision variables at the plurality of time steps.

Building energy system with load-following-block resource allocation

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Milwaukee, WI, United States of America

Mohammad N ElBsat