Carbon management system and method

Abstract

A carbon management system and a carbon optimization system are provided, the system including a processing circuit operably coupled to a carbon site control module, the carbon site control module operably engaging one or more of a carbon resource module, a carbon capture control module, and / or a building management system.

Description

[Technical Field]

[0001] [CROSS-REFERENCE TO RELATED APPLICATIONS] This application is a continuation-in-part of U.S. Patent Application No. 17 / 963,592, entitled "Carbon Management System and Methods," filed October 11, 2022, which claims priority to and benefit of U.S. Provisional Patent Application No. 63 / 254,432, entitled "Carbon Management System and Methods," filed October 11, 2021, each of which is incorporated herein by reference in its entirety. This application is related to U.S. Provisional Patent Application No. 62 / 840,206, entitled "Building Carbon Dioxide Sequestration Systems and Methods," filed April 29, 2020, which was published on October 29, 2020 as U.S. Patent Application Publication No. 2020 / 0340665, and which claims priority to and benefit of U.S. Provisional Patent Application No. 62 / 977,050, entitled "Building Emission Processing and / or Sequestration Systems and Methods," filed February 14, 2020, the entire contents of each of which are incorporated herein by reference.

[0002] The present disclosure relates to managing carbon use and / or production in buildings. [Background technology]

[0003] Carbon dioxide generation in buildings contributes significantly to carbon dioxide generation overall. Carbon dioxide is currently listed as a global warming compound that is being sought to be reduced worldwide. Carbon dioxide generation is a necessary part of breathing, a necessary part of life, but limiting carbon dioxide generation is important to address climate change. Furthermore, buildings consume carbon in the form of energy. The present disclosure provides carbon management systems and methods that can address carbon dioxide generation and storage and / or carbon consumption. Summary of the Invention

[0004] A carbon management system and a carbon optimization system are provided, the system including a processing circuit operably coupled to a carbon site control module, the carbon site control module operably engaging one or more of a carbon resource module, a carbon capture control module, and / or a building management system.

[0005] A building carbon capture system is provided, the system including an inlet compressor configured to receive flue gas from a combustion source within the building, the inlet compressor operably coupled to a VPSA assembly, the VPSA assembly operably coupled to a liquefaction assembly, a plurality of flow / sensor assemblies operably engaged between the inlet compressor and the VPSA and between the VPSA and the liquefaction assembly, and a processing circuit configured to receive rate data from the plurality of flow / sensor assemblies and process the data to determine one or more system performance parameters.

[0006] A building environmental management system is also provided, which may include a building environmental optimization module configured to optimize building environmental conditions by modifying environmental parameters, and a building carbon conservation measures module configured to determine building environmental conditions when the building optimization module is static.

[0007] A method for determining building environmental performance is provided. The method can include optimizing building environmental conditions, determining environmental conditions while the optimization of the building environmental conditions is static, and resuming the optimization of the environmental conditions. The method can also include setting one or more building environmental set points in a building management system and using a carbon optimization system to optimize the one or more environmental conditions using the one or more building environmental set points of the building management system.

[0008] A method for engaging / disengaging a carbon optimization system from a building management system is also provided, the method including determining one or more building management system performance thresholds while the carbon optimization system is engaged / disengaged from the building management system, and engaging / disengaging the carbon optimization system from the building management system according to the one or more system performance thresholds. [Brief explanation of the drawings]

[0009] Embodiments of the present disclosure will now be described with reference to the accompanying drawings, in which: [Figure 1] FIG. 1 illustrates a processing circuit system according to one embodiment of the present disclosure. [Figure 2] FIG. 1 illustrates a processing circuit system integrated into a building and CO2 sequestration and deposition, according to one embodiment of the present disclosure. [Figure 3] FIG. 1 illustrates a processing circuit system including carbon optimization operably coupled with different building and energy resources, according to one embodiment of the present disclosure. [Figure 4A] FIG. 1 illustrates a processing circuit integrated with an architectural component according to one embodiment of the present disclosure. [Figure 4B] FIG. 1 illustrates a processing circuit integrated with an architectural component according to one embodiment of the present disclosure. [Figure 5] FIG. 10 is a diagram of machine learning performed within a processing circuit coupled to building operations, according to one embodiment of the disclosure. [Figure 6]FIG. 1 illustrates the relationship of a processing circuit system with respect to a building operation system, according to one embodiment of the present disclosure. [Figure 7] FIG. 1 illustrates a relationship of a building site processing system and processing circuitry systems with respect to building components, according to an embodiment of the present disclosure. [Figure 8] FIG. 1 is a diagram of an on-site and cloud system according to one embodiment of the present disclosure. [Figure 9] FIG. 1 is a diagram of a processing circuit system associated with flue gas processing according to one embodiment of the present disclosure. [Figure 10] FIG. 1 is a diagram of a processing circuit system associated with flue gas processing according to one embodiment of the present disclosure. [Figure 11A] FIG. 1 is a diagram of a processing circuit system associated with flue gas processing according to one embodiment of the present disclosure. [Figure 11B] FIG. 1 is a diagram of a processing circuit system associated with flue gas processing according to one embodiment of the present disclosure. [Figure 12] FIG. 2 is a diagram of a flue gas processing component according to one embodiment of the present disclosure. [Figure 13A] 1 is a diagram of a flue gas treatment system according to one embodiment of the present disclosure. [Figure 13B] 1 is a diagram of a flue gas treatment system according to one embodiment of the present disclosure. [Figure 13C] 1 is a diagram of a flue gas treatment system according to one embodiment of the present disclosure. [Figure 14] 1 is a diagram of a flue gas treatment system according to one embodiment of the present disclosure. [Figure 15] 1 is a diagram of a flue gas treatment system according to one embodiment of the present disclosure. [Figure 16] 1 is an overall view of a flue gas treatment system according to one embodiment of the present disclosure; [Figure 17] 1 is a diagram of a flue gas treatment system according to one embodiment of the present disclosure. [Figure 18] FIG. 1 is a diagram of an interface view according to one embodiment of the present disclosure. [Figure 19] FIG. 1 is a diagram of an interface view according to one embodiment of the present disclosure. [Figure 20] FIG. 1 is a diagram of an interface view according to one embodiment of the present disclosure. [Figure 21] FIG. 1 is a diagram of an interface view according to one embodiment of the present disclosure. [Figure 22] FIG. 1 is a diagram of an interface view according to one embodiment of the present disclosure. [Figure 23] FIG. 1 is a diagram of an interface view according to one embodiment of the present disclosure. [Figure 24] FIG. 1 illustrates a machine learning operation configuration according to an embodiment of the present disclosure. [Figure 25] 1 is an operational flowchart of packaging actions (CCM) recommended by machine learning according to an embodiment of the present disclosure. [Figure 26] FIG. 1 illustrates the operational relationship between the COS machine learning subsystem and the building control system, according to one embodiment of the present disclosure. [Figure 27] FIG. 2 illustrates a processing circuit according to one embodiment of the present disclosure. [Figure 28] FIG. 1 illustrates data that can be obtained using the system of the present disclosure. [Figure 29] FIG. 1 illustrates data that can be obtained using the system of the present disclosure. [Figure 30] FIG. 1 illustrates an exemplary machine learning optimization system according to one embodiment of the present disclosure. [Figure 31] FIG. 1 illustrates a machine learning optimization system according to one embodiment of the present disclosure. [Figure 32] FIG. 1 illustrates an exemplary CO2 separation stream according to one embodiment of the present disclosure. [Figure 33] FIG. 1 illustrates an exemplary general CO separation stream according to one embodiment of the present disclosure. [Figure 34] FIG. 10 illustrates an exemplary user interface screen according to one embodiment of the present disclosure. [Figure 35] FIG. 10 illustrates another exemplary user interface screen according to an embodiment of the present disclosure. [Figure 36]FIG. 2 illustrates an exemplary arrangement of processing circuit modules according to one embodiment of the present disclosure. [Figure 37] FIG. 10 shows exemplary data obtained with and without carbon optimization treatment. [Figure 38] FIG. 10 illustrates an exemplary baselining sampling table according to one embodiment of the present disclosure. [Figure 39] 1A-1C illustrate exemplary baselined and optimized data obtained using the systems and / or methods of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0010] The present disclosure will be described with reference to Figures 1 through 39. Referring to Figure 1, a system is provided that includes a Carbon Management System (CMS) operably coupled to a Carbon Optimization System (COS). These systems can be configured to work in conjunction with one another to provide carbon site control in a building management system. The building management system can also include carbon capture controls and be linked to carbon resources. These systems are designed for use in any style of building, including residential, industrial, commercial, and / or residential buildings, that leave a significant carbon footprint when using carbon resources, such as natural gas and / or other carbon sources, up to and including electricity that can be generated from carbon sources.

[0011] The building may be a multi-use building and may include typical spaces within a building. These spaces may be offices, residences, shared spaces such as hallways and entryways, and semi-shared spaces such as meeting and workout spaces. The systems and / or methods of the present disclosure may be configured to operate or control the environments of these spaces based on the type of space. For example, the optimizations described herein may vary depending on the space's tolerance to environmental changes. Additionally, the spaces may include one or more sensors operably coupled to the systems and / or methods of the present disclosure. These sensors may include, but are not limited to, sensors for temperature, humidity, light, and molecular-level amounts of oxygen, nitrogen, carbon dioxide, and / or carbon monoxide. Data from one or more of these sensors may be processed in conjunction with different zones and / or stages of internal system processing. For example, carbon dioxide within a space may be processed in conjunction with the operation of the HVAC system and / or carbon capture system of the present disclosure.

[0012] Referring to FIG. 2 , the disclosed system can include a carbon management system that can be linked to residential buildings, factories, and / or office buildings via processing circuitry, as shown. These buildings can be configured to capture CO2 as they generate combustion products. As shown, this CO2 can be captured and transported to a CO2 storage facility, all of which can be linked via the carbon management system. According to an exemplary implementation, the carbon management system can be configured to dictate when CO2 is removed from a residential building, how much CO2 is removed, and where the CO2 is deposited. According to an exemplary implementation, for example, the carbon management system can receive data indicating that a particular building is generating more or less CO2 than other buildings, that a particular storage facility is full, or that CO2 is in need of storage. For example, the CO2 emanating from a factory can be food-grade CO2, and the carbon management system can dictate which CO2 carriers go to which storage facilities, so a fluid carbonation plant may need additional CO2. While the system in FIG. 2 is an example, it is contemplated that buildings could include systems relying on fuel cell technology. Also, for example, fuel cells can generate emissions that are not combustion products but include CO2. Exemplary fuel cells can produce emissions that are primarily water and CO. The systems and / or methods of the present disclosure can also be used in these CO emissions systems.

[0013] Referring to Figure 3, the carbon optimization system can also be linked to residential buildings, commercial industrial plants, and office buildings, which themselves can be configured to receive, for example, electric, natural gas, oil, or steam carbon sources. As shown below, these sources can be linked to a carbon optimization system and a carbon management system, which can link, for example, to portfolio carbon aggregation and market carbon sources. This data can be used to direct which buildings consume which sources and at what times to most efficiently meet the building's needs, while maintaining the amount of carbon sources utilized, produced, and stored at different facilities.

[0014] Referring to Figure 4A, the carbon management system can be operated from an interface as shown and can be operatively coupled to a carbon site control and building management system. The carbon optimization system can likewise be coupled to a carbon site control and building management system within the building. As shown, the building itself can be configured to receive natural gas, electricity, oil, and / or steam, and the building can be configured to utilize a carbon capture system. Operatively, the building can have resource areas for fuel and air handling systems, and these flue gas handling systems and air handling systems can be operatively coupled to the carbon management system and / or carbon optimization system.

[0015] Referring now to FIG. 4B, a more detailed description of the functionality of a building's interior combined with a carbon optimization and carbon management system is shown. In this implementation, the carbon management system can be coupled to third-party applications, such as a carbon trading platform, weather services, and / or carbon market services, but the carbon management system can also have an interface browser, as shown, available in iOS, Windows, or Android applications. Thus, the carbon optimization system and carbon management system can be coupled to a site controller, which is also coupled to a building management system and a building carbon metering system, and the carbon capture control system and electric carbon optimization system can be coupled to the building management system. In an exemplary implementation, the carbon capture system can include the use of hot water and chillers and boilers, as described in the referenced applications and disclosed herein, to produce approximately 12% carbon dioxide and approximately 65% ​​nitrogen. Condensation cooling, drying, and final storage and transport occur. These storage and transport functions can be used for sustainable CO2 offtake management, such as green concrete and / or wastewater treatment, agriculture, or aquaculture technologies.

[0016] As described, the systems and / or methods of the present disclosure may utilize or be part of a processing circuit. The processing circuit may include a processor, which may be part of a personal computing system including a computer processing unit, which may include one or more microprocessors, one or more support circuits, circuits including power supplies, clocks, input / output interfaces, circuits, etc. Generally, all computer processing units described herein may be of the same general type. The computing system may include memory, which may include random access memory, read-only memory, removable disk memory, flash memory, and various combinations of these types of memory. The memory may be referred to as main memory and may be part of cache memory or buffer memory. The memory may store various software packages and components, such as an operating system.

[0017] The computing system may also include a web server, which may be any type of computing device adapted to distribute data and process data requests. The web server may be configured to run system application software, such as reminder scheduling software, databases, email, etc. The web server's memory may include a system application interface for interacting with users and one or more third-party applications. The computer system of the present disclosure may be standalone or may operate in combination with other servers and other computer systems that may be utilized in a larger enterprise system, such as, for example, a utility provider and / or software support provider. The system is not limited to a particular operating system and may be adapted to run on multiple operating systems, such as, for example, Linux and / or Microsoft Windows. The computing system may be coupled to a server, which may be located, for example, at the same site as the computer system or at a remote location.

[0018] According to an exemplary implementation, these processes may be utilized in conjunction with the described processing circuitry. The processes may use the following combinations or types of software and / or hardware: For example, with respect to server-side languages, the circuitry may use, for example, Java, Python, PHP, .NET, Ruby, Javascript, or Dart. Some other types of servers the system may use include Apache / PHP, .NET, Ruby, NodeJS, Java, and / or Python. Databases that may be utilized include Oracle, MySQL®, SQL, NoSQL, or SQLLite (for mobile). Client-side languages ​​that may be used are user-side languages, such as ASM, C, C++, C#, Java, Objective-C, Swift, Actionscript / Adobe AIR, or Javascript / HTML5. Communication between the server and client may be utilized using, for example, a TCP / UDP socket-based connection, since third-party data network services that may be used include GSM, LTE, HSPA, UMTS, CDMA, WiMax, WiFi, Cable, and DSL. Hardware platforms that may be utilized within the processing circuitry include embedded systems such as (Raspberry PI / Arduino), (Android, iOS, Windows Mobile) phones and / or tablets, or any embedded system that uses these operating systems, i.e. cars, watches, glasses, headphones, augmented reality wear, etc., or desktop / laptop / hybrid (Mac, Windows, Linux). Architectures that may be utilized for the software and hardware interfaces include x86 (including x86-64), or ARM.

[0019] Referring now to FIG. 5, the carbon site controller can include a gateway above the building management system. Within the carbon optimization system, multiple routines can occur, including a carbon optimization algorithm that optimizes carbon control based on described outcomes and reward calculations, taking into account any external markers or portfolio conditions. The carbon optimization system also includes an interpreter, a reinforced machine learning (RL) or RML, which is an algorithm that calculates rewards based on behavioral outcomes. Reinforcement learning (RL), as a branch of machine learning (ML), can utilize rewards such as a point system. For example, the closer the optimization is to a setting (e.g., comfort), the more points are "rewarded." Alternatively, the further the optimization is from a setting (e.g., comfort), the fewer points are "rewarded." While given in the context of a setting, rewards can also be provided in relation to energy usage. For example, more points for less energy use, fewer points for more energy use.

[0020] As shown, the carbon site controller can be coupled to boilers, chillers, cooling water towers, rooftop VAC units, hot water systems, pumps, heaters, etc. Natural gas, electricity, steam, and oil can be coupled to these systems and monitored by the carbon site controller. A layer between the carbon site controller and these devices within the building can be a building management system, typically integrated into the building itself.

[0021] Referring to Figure 6, some of the rewards mentioned in Figure 5 are shown, including the carbon intensity of the resource, carbon tax credits such as New York City carbon tax credits, and carbon removal credits. These are credits given to buildings for efficient carbon utilization. The customer building management system can also include a New York City Fire Department monitor and CO2 removal, and the site itself can also include the amount of CO2 sequestered and a carbon site controller. Below that can be a layer of carbon capture controller, which can include a human-machine interface (HMI) or user interface, which can be part of the automation server. A firewall can exist between the site and the cloud and carbon site controller. The carbon capture controller can include network switches that allow the system to monitor and operate equipment in the system, such as the boiler, flue diverter, pressure swing adsorption, nitrogen management, liquid CO2, and storage. This can include, for example, the boiler controller, cooling tower components, diverter, pressure temperature sensor, front-end ELGI compressor, pressure swing adsorption, CO2 alarm, air turbine, VFD, liquid CO2 tank, load cell, CO2 alarm, chiller, and two-stage compressor.

[0022] Referring now to FIG. 7 , another detailed view of a system according to one embodiment of the present disclosure includes a cloud carbon optimization system (COS). The COS can include ML algorithms, and the CMS can include, for example, a communications infrastructure, a data store, and / or a UI server. The carbon management system has the CMS coupled to the cloud optimization system as part of the carbon management system, which in turn is coupled to a browser or interface that can include the carbon management system's portfolio, for example, all Glenwood buildings, all decarbonized resources, etc. Both the COS and CMS can be coupled to carbon site control, which can be coupled to the building management system via a BACnet interface. The building management system can also have site control firewalled from the COS and CMS, which can control carbon capture, boilers, cooling towers, AC units, etc. Carbon site control can also be carbon capture control, as well as electric and natural gas meter data.

[0023] Referring now to Figure 8, the platform core operations and the human interfaces associated with the system operator and installer are shown. The on-site can be distinguished from the cloud and grid, weather, and other external data. The on-site can be electricity metering, carbon capture, building management systems, and gas and CO2 metering monitoring. All of these can be monitored by a carbon site controller, which can be visually inspected by the installer, including both electricity metering, carbon capture devices, and Modbus TCP from BACnet relationships. The on-site system can link the on-site to cloud resources, including the platform core and carbon management and carbon optimization systems, which are trained to optimize carbon use and removal. The on-site resources connect to the cloud platform through the carbon site controller or directly via Message Queuing Telemetry Transport (MQTT). MQTT is a standard messaging protocol for IoT devices to connect directly to remote or cloud processing circuits. In some cases, sensor devices can connect through our gateway or directly to the CMS cloud using MQTT (or other standard protocols). This can have an interface that is monitored by the platform core operating via a browser as well as by the system operator via a browser.

[0024] Another implementation of the system according to an exemplary implementation including a carbon management system on top of carbon site control and capture control is described herein with reference to FIG. 9. This carbon capture control can include a series of data points B, D, P, S1, L, S2, and T. These data points can refer to combustion, separation, liquefaction, storage, and transfer. The data points can have ranges over which the system operates and can also indicate ranges over which it operates relative to other ranges. For example, if combustion is relatively slow and CO2 generation is relatively low, separation can be inhibited or manipulated accordingly, thereby directing changes to liquefaction, storage, and transfer.

[0025] 10, another exemplary implementation includes cloud resource, site resource, and process resource levels, as well as a field resource level. This depiction is referenced in the applications referenced and incorporated herein by reference. Thus, the cloud can include market and portfolio data, as well as a carbon management system and a carbon optimization system operably connected to a firewall carbon site controller.

[0026] Referring to FIG. 10, the plant, process, and field-level components of the control system are shown. According to an exemplary implementation, an exemplary overall control system is provided showing combustion emissions and control, a MASTER PLC controller, diverters, compression, dryers, separation, cooling and compression, refrigeration / storage, and food-grade CO2 delivery. These systems are also connected to electric, natural gas, and water utility systems. These control systems illustrate a basic network architecture diagram. The MASTER PLC controls the entire plant using an Ethernet loop connection and Internet IP protocol communication to local packaged controllers, as well as through direct connection and control to the digital and analog I / O field instrumentation level. An HMI server collects data from the MASTER PLC, manages real-time views of the plant, runs logging and data management applications, and communicates with external users through a secure firewall. Also included is an engineering development workstation that maintains all operational software and updates, which are periodically downloaded to the MASTER PLC.

[0027] 11A and 11B, exemplary implementations of the systems and / or methods are disclosed, detailing the sequence of the different components and processes described herein, as well as additional thermal management components associated with a building. As can be seen throughout the figures and accompanying description, there are multiple locations for transferring heat from the different components of the disclosed system to the existing building system. For example, as shown, chillers may be located within the building and within an existing cooling tower. These active cooling components can be operatively coupled to heat removed from the process components via individual cooling loops. In accordance with exemplary implementations, heat, sometimes referred to as waste heat, can be transferred to the building system, where the excess heat can be used to operate more efficiently. Therefore, with regard to waste heat from the disclosed system, the design preference is to transfer the waste heat first to the building steam and hot water make-up system, second to the building cooling tower, and finally to an appropriate chiller with heat exchange with air.

[0028] 10-17, numerous examples of building systems are provided that can be monitored, operated, and / or controlled to operate a building with optimal carbon consumption and / or production. These examples are provided in the context of a building carbon capture system. However, a building may not include this system; rather, a building may include a previously conventional heating / cooling system that can be monitored, operated, and / or controlled using the management systems and / or methods of the present disclosure.

[0029] 10 and 11A-11B, according to at least one implementation of carbon management, a thermal management system (e.g., see MASTER PLC, controller, etc.) can conserve fuel use, such as natural gas, in a boiler by optimizing combustion with a combustion controller, control water removal from flue gas with a front-end controller, perform additional separation with a dryer and PSA with a separation controller, liquefy and store CO2 with a liquefaction / storage controller, and direct offtake to pickup and / or delivery trucks with an offtake controller. These and additional controllers can function to control boiler feedwater, potable and / or industrial water, chiller water, and / or cooling tower water, as well as nitrogen expansion cooling, to reduce and / or eliminate heat loads in the system. This can cool flue gas for water knockout and can cool heat-generating electrical components, such as compressors, blowers, pumps, and fans.

[0030] According to exemplary embodiments, the systems and / or methods of the present disclosure can include an energy storage system that can be configured to include power conversion components and / or battery or battery bank components. As an example, energy can be generated via turbine expansion of nitrogen, which can then be converted and stored within the building. The energy can be converted and provided directly to system components, such as a compressor, and / or stored and then provided to system components, thereby reducing the energy demands of the building. Additionally, the energy can be provided to a power grid associated with the building itself.

[0031] According to an exemplary implementation, using a MASTER PLC, energy generated by the system can be utilized during "peak demand" times (e.g., when electricity rates are higher) and / or when the building is utilizing "peak" amounts of power. During these times, the MASTER PLC monitors building demand and then modifies system parameters to efficiently use energy storage and / or alter carbon dioxide separation, liquefaction, storage, and / or transportation to reduce energy consumption during "peak demand" and thus save on energy costs.

[0032] Exemplary embodiments of the disclosed systems and / or methods can provide not only a carbon capture system, but also improvements to overall building energy efficiency (both thermal and electrical) while reducing CO2 emissions. Exemplary implementations can include reducing carbon fuel consumption by optimizing boiler firing, providing warmer boiler feedwater and therefore requiring less energy to heat it, warming potable or process water and therefore requiring less energy to heat it, generating electrical energy and using it for power system components, and / or using a building's cooling tower to reduce the building's heat load, etc. Individually and / or collectively, these can be part of a system that dramatically improves a building's efficiency.

[0033] 12, a boiler configured with the systems and / or methods of the present disclosure is shown. Accordingly, air 60 and fuel 62 may be supplied to a combustion burner, with the mixing of the air 60 and fuel 62, and therefore the combustion of the air 60 and fuel 62, being controlled by a combustion controller 66 operatively connected to the free oxygen sensor 43. Accordingly, boiler feedwater 52 is received by the combustion boiler and heated to hot water or steam 50 that is used to heat a building and / or building systems, such as a water heater system 58. The water heater system 58 may be configured to receive potable water for heating and / or industrial process water for heating.

[0034] According to an exemplary implementation, the control 66 may utilize the sensor 43 to monitor the amount of free oxygen in the combustion burner and maintain the amount of free oxygen at approximately 3%. Approximately 3% free oxygen may include 3 to 7% free oxygen. According to an exemplary embodiment, the combustion may produce a flue gas 44. The composition of the flue gas 44 may be controlled to include at least approximately 10% carbon dioxide. Approximately 10% carbon dioxide may include 9 to 12% carbon dioxide of flue gas from the combustion of natural gas.

[0035] The systems and / or methods of the present disclosure may include separating the carbon dioxide from the flue gas, liquefying the carbon dioxide after separating the carbon dioxide from the flue gas, liquefying the separated carbon dioxide after separating the carbon dioxide from the flue gas, storing the carbon dioxide after liquefying the carbon dioxide, and / or transporting the carbon dioxide after storing the carbon dioxide.

[0036] Referring to FIG. 12 , a system and / or method is provided for operating a combustion boiler in a building that may include combusting air and fuel in a burner to produce flue gas 44 having an oxygen concentration, and restricting air from the flue gas by substantially excluding tramp air in a conduit operatively aligned to convey the flue gas from the burner.

[0037] According to at least one aspect of the present disclosure, real-time control of a combustion source or boiler can achieve greater efficiency, for example, by increasing the concentration of carbon dioxide in flue gas while reducing natural gas or fuel consumption. This may seem counterintuitive to increasing the concentration of carbon dioxide in flue gas when the disclosed systems and / or methods are utilized to reduce carbon emissions from a building. However, increasing the carbon dioxide concentration can provide the benefit of reducing fuel consumption by reducing heat loss through exhaust. Adjusting combustion to control free oxygen to 3% can result in more efficient combustion. According to an exemplary implementation, combustion control desirably achieves a carbon dioxide concentration of at least about 10% in the flue gas, approaching a 12% CO concentration value when burning natural gas. This is at least one feature of the disclosed building emissions treatment systems and / or methods and can be utilized as one of the initial steps in carbon capture.

[0038] Within a building, boiler operation can be directed by responding to the need for hot water or steam by controlling combustion burners to various predetermined firing rates: 1) off, 2) low fire rate, and / or 3) high fire rate. These rates may have been established in older boilers, for example, via calibrated mechanical linkages. Recognizing that cyclical boiler operation varies significantly from hour to hour, day to day, and season to season, it is desirable to establish automatic control of flame rate continuously across the entire boiler load range while also controlling free oxygen as described above. The disclosed systems and / or methods can be configured to reduce on / off cycling by extending boiler runtime with reduced flame rate, extending boiler life, and providing a more continuous flow of flue gas to the disclosed separation, liquefaction, storage, and / or transportation systems and / or methods.

[0039] Thus, the boiler and system controls (eg, FIG. 10) can achieve higher building thermal efficiency while creating optimal conditions for flue gas supply to the systems and methods of the present disclosure.

[0040] Referring now to Figures 13A-13C, portions of a system and method for separating water from flue gas and cooling the flue gas are shown. Referring initially to Figures 13A-13C, three different configurations of a system and / or method for cooling flue gas from a combustion boiler in a building are shown. Referring initially to Figure 13A, flue gas 44 can proceed to a combination of non-condensing and condensing economizers 60a. The flue gas 44 first proceeds to a non-condensing configuration in which boiler feedwater 52 is provided through a conduit, set of conduits, and / or coil, the flue gas is cooled, and the boiler feedwater is heated. Thus, a method for cooling flue gas from a combustion boiler in a building is provided. Once the boiler feedwater is heated, it can be provided to the boiler, thereby reducing the energy required to heat the feedwater to hot water and / or steam.

[0041] Additionally, the economizer may be configured for condensation. Thus, the conduit, set of conduits, or coil 54 may be configured to carry, for example, potable water or industrial process water received from a utility. This water may have a temperature close to that of groundwater, since it is typically transported through underground pipes. Thus, the water, even after being partially cooled in the non-condensing economizer, has a temperature substantially different from that of the flue gas. By providing flue gas to these conduits, water can be removed from the flue gas, thus producing a water-condensed effluent 53. This water traveling through the conduits is heated and provided to a water heating system 58 ( FIG. 12 ) as the water heating system's intake 54, where it is heated and received through an outlet 56. Thus, the amount of energy required to heat the water in the water heating system 58 is less, at least because the water received for heating does not need to be heated from a lower temperature associated with typical tap water, but rather has been preheated. According to an alternative configuration, referring to FIG. 13B, one set of coils 52 can be associated with one economizer 60b, and another set of coils 54 can be associated with another economizer 65a. In this configuration, economizer 60b can be a non-condensing economizer, and economizer 65a can be configured as a condensing economizer. According to another embodiment of the present disclosure, a diverter 64 can be operably coupled to the economizer, as shown in FIGS. 13A through 13C. According to an exemplary implementation, cooled flue gas can be provided from the diverter 64 using a blower. A system and / or method can control the amount of flue gas processed using the diverter. According to an exemplary implementation, a current system according to FIG. 13C would receive 450 standard cubic feet per minute (SCFM) to 500 SCFM of wet flue gas 44. The diverter can be controlled by an overall master system (FIG. 10), which can control a motor-operated butterfly valve within the diverter. The master system also collects gas temperature and flow data and can operate the blower as shown in FIG.

[0042] 14, drying of the flue gas may continue with a blower 68 to increase the pressure of the flue gas from the diverter. This blower 68 may support flow through a heat exchanger / condenser 70, which may include a water outlet 71 operably coupled to an acid quench assembly 74. The heat exchanger 70 may be configured to cool the gas below its dew point to condense most of the water, leaving less than about 3% water, or as low as about 0.2% water.

[0043] Heat exchanger 70 may be of tube and shell configuration and may be cooled, for example, by an external water / glycol loop provided by a chiller and / or water from a building's cooling tower. As shown, it is expected that the water removed from the system at heat exchanger 70 may be slightly acidic, allowing the water to be neutralized before proceeding to a public treatment plant (POTW) or through a sewer network. Additionally, some water remains in the process stream as small droplets, mist, or acidic aerosols that are minimized or removed by special heat exchanger designs, impingement devices, or possibly precipitators.

[0044] After most of the water has been removed and the acid aerosols mitigated, the cooled flue gas 72 continues to a compressor, which can increase the pressure of the flue gas to an optimum level of approximately 100 psig or less, as dictated by the PSA system specifications.

[0045] Referring now to FIG. 15, a compressor 74 may receive the flue gas 72. The compressor 74 may be an "oil-free" compressor to remove downstream product contamination, and the compressor may be configured with a variable frequency drive (VFD) to respond to variable gas flows. Because compression may increase the temperature of the flue gas, a second heat exchanger 76 may be utilized to reduce the temperature of the flue gas to below 40°C. At this stage, the gas may have less than about 3% water present as steam, and the gas may be at a temperature below 40°C and a pressure of about 100 psig.

[0046] Referring to FIG. 15 , a system and / or method for separating carbon dioxide from flue gas generated from a combustion boiler in a building may include providing flue gas 72 having less than approximately 3% water, compressing the flue gas, cooling a compressor 74 with a heat transfer fluid 90, and providing the heat transfer fluid to / from a chiller and / or cooling tower. The heat transfer fluid may be, for example, water, and the chiller water may be cooled in the building's cooling tower before returning the spent heat transfer fluid to the chiller. Thus, the disclosed system and / or method may include additional separation, liquefaction, storage, and / or transportation. This is just one example of a heat-generating component of the system that may be cooled with the chiller and / or cooling tower heat transfer fluid. More than 70% of the cooling requirements of the disclosed system and / or method may come from heat generated in the compressor and / or pump and the heat exchanger of the liquefaction skid. Each of these components may include a water cooling circuit supplied from a local chiller or directly from a central chiller. Local chillers can be water-cooled by a water loop coming from a central chiller or from the building's cooling tower. The central chiller can be designed to prioritize heat transfer in the following order: a) domestic hot water make-up, b) cooling tower, c) exchange with, for example, outside air.

[0047] Referring again to FIG. 15 , after compression, the flue gas can be provided to a dryer 78, such as a desiccant dryer. The dryer 78 can be operatively engaged with a nitrogen feed, such as a sweep feed, configured to regenerate the spent desiccant. Typically, the dryer is a two-chamber cycle device, where one chamber is dried and the other chamber is regenerated for drying, and the cycle continues. Nitrogen can be provided to the spent desiccant in one chamber, while the other chamber dries the flue gas. Thus, a system and / or method for separating carbon dioxide from flue gas generated from a combustion boiler in a building is provided, which can include drying the flue gas using nitrogen recovered during separation of the carbon dioxide recovered from the flue gas. This recovered nitrogen can be conveyed from the pressure swing adsorption assembly 80 to the dryer 78 via conduit 92 and then discharged through stack 86. According to an exemplary implementation, the dried flue gas can be provided for further separation, liquefaction, storage, and / or transportation.

[0048] From the dryer, flue gas 79, containing less than 10 ppm water, can proceed to a pressure swing adsorption (PSA) assembly 80. This pressure swing adsorption assembly can provide greater than 85% CO2 recovery at greater than 95% purity, 1 psig, and 100°C. The maximum CO2 output flow at this point can be approximately 40 SCFM. The remaining portion of the flue gas, which is primarily nitrogen, can continue under pressure and / or can be split so that a portion returns to the dryer 78. Another portion of the nitrogen can proceed to a turbine expander 82 / generator 93, which can provide electrical energy 94 and a low-temperature output gas at near ambient pressure. Additionally, a control valve 84 with a silencer can be operably aligned in parallel with the expander 82 / generator 93.

[0049] Thus, a method for separating carbon dioxide from flue gas produced from a combustion boiler in a building is provided, the method can include removing at least a portion of the nitrogen from the flue gas using a pressure swing adsorption assembly 80 to produce greater than about 95% carbon dioxide. The nitrogen removed from the flue gas can be used, for example, to remove water from the flue gas before providing the flue gas to the pressure swing adsorption assembly in a dryer 78. Alternatively or additionally, at least a portion of the nitrogen removed from the flue gas can be provided to a gas expander / generator. Alternatively or additionally, a portion of the nitrogen from the PSA can be provided to a control valve with a silencer, and another portion can be provided to the expander / generator. According to an exemplary implementation, the disclosed system and / or method can include separating the nitrogen into portions and providing one portion to the dryer and another portion to the expander / generator. In one exemplary implementation, the one portion is about one-third of the nitrogen from the pressure swing adsorption assembly.

[0050] Also provided is a system and / or method for using the nitrogen output of a PSA to cool carbon dioxide separated from flue gas produced from a combustion boiler in a building. The system and / or method can include separating the nitrogen from the flue gas using a pressure swing adsorption assembly 80, expanding the nitrogen through a turbine in the presence of a heat exchanger 92 to cool a fluid in the heat exchanger 92, and transferring the cooled fluid to another heat exchanger 100 operatively aligned with the carbon dioxide product of the pressure swing adsorption assembly to cool the carbon dioxide product. The turbine can be part of a generator 93, for example, or can be provided to cool the exchanger 92.

[0051] Typically, nitrogen gas exiting the PSA may be at least 85 psig at a flow rate greater than 65% of the rated system flow rate. According to an exemplary embodiment, the nitrogen may be processed and stored as a marketable product. For power generation, grid-compatible power conversion is required. The turbogenerator has a 500 Hz output that does not fit into the 60 Hz grid. Therefore, it is assumed that appropriate power conversion will be specified. This may be a DC-to-AC polyphase inverter with rectification followed by appropriate safety features in case of a building power outage. After use in the turbogenerator and CO2 heat exchanger, the nitrogen exhaust gas may be returned to the exhaust stack or plenum.

[0052] Referring now to FIG. 16 , in another series of components of the present disclosure, greater than 95% pure CO2 can be cooled and compressed in sequential steps, as shown by heat exchanger 104, compressors 106 and 108, and heat exchanger 110, with the compressor operatively engaged with the cooled transport fluid 90 to approach a phase change state for liquefaction. According to an exemplary embodiment, greater than 95% pure CO2 can have a temperature exiting the PSA as high as 100°C. As mentioned above, heat exchangers can be provided to reduce the temperature of the gas to a sufficient temperature and then compress the gas to a higher pressure. They can also be provided to increase the temperature of the nitrogen gas exiting the PSA before expansion through the turbine. This can improve turbine efficiency by allowing full use of the nitrogen stream before exceeding the COLD temperature output limit. This is just one of several examples of utilizing heat from system components in other parts of the system to obtain a more efficient overall system.

[0053] 17, a CO liquefaction and storage system and / or method is shown in which CO gas 112 is sparged inside a vessel 113, such as an insulated vessel. An exemplary insulated vessel may include, but is not limited to, a vacuum-jacketed liquid storage tank. Within the vessel, the gas 112 may be converted to a liquid 114. According to an exemplary implementation, the gas 112 may be provided to a sparging assembly 118 where it is provided as a sparging gas 120 that liquefies upon sparging into the liquid 114.

[0054] The vapor 116 at the top of the vessel 113 is managed by a refrigeration system 122 that cools the vapor 116, which condenses back into liquid 114 and returns to the vessel 113. According to an exemplary configuration, the system 122 can be configured as a loop in fluid communication with the vessel 113, where the vapor CO2 116 enters the system 122 and returns to the vessel 113 as liquid CO2 114. In at least one configuration, the system 122 is configured as a low-temperature condenser with an evaporator.

[0055] In the event of a building power loss, the excellent insulation of the vacuum jacketed tank can maintain liquid CO for at least 30 days, for example. According to an exemplary implementation, the building itself may be able to access the vessel 113 for a supply of CO to extinguish fires, for example, fires associated with electronic components requiring CO fire extinguishing methods.

[0056] 18-23 are exemplary depictions of interface readouts received by an operator of an optimization and / or management system according to exemplary implementations. According to at least some of these readouts, a carbon intensity can be determined and then processed to optimize carbon capture according to the systems and methods described herein. This intensity can be determined in real time.

[0057] Figures 19 and 20 show an example of CMS calculated performance for a carbon capture system. This data is collected in real time and can be aggregated on a daily, weekly, monthly, and yearly basis to show system performance. Gross tons of CO2 captured and net tons of CO2 reduced (after removing electrical equivalents in real time as calculated by CMS) are presented, tracked, and provided as required by the specific market in which the system operates. Additionally, as required by the market, the system tracks the final utilization of CO2 offtake and CO2 product, as well as the percentage of sequestered value represented by each purchasing application and market. Thus, this CMS functionality tracks and calculates the complete carbon life cycle and carbon life cycle analysis of the system in real time, aggregates the results on a daily, weekly, monthly, and yearly basis, and provides a user interface and reporting of the system's decarbonization performance.

[0058] FIG. 24 is a system diagram for a machine learning operational architecture including analysis, versioning, transformation, CO2 capture, model, CO2 reduction, predictive maintenance, CO2 forecasting, anomaly detection, prediction, deployment, evaluation, training, and data ingestion.

[0059] Figure 25 is a loop diagram of a carbon management system, including carbon capture management and associated with a building management system, and the optimization route performed using machine learning of Figure 24. The COS architecture interfaces to the CMS using software constructs entitled Carbon Conservation Measures (CCMs). Each CCM acts as a container for a specific machine learning algorithm that is configured, scheduled, and assigned to a specific carbon consuming device, equipment, or system. The CCM interfaces with the BMS via a standard protocol and data architecture that allows the software to work with any BMS system connected to the carbon consuming device. Multiple CCMs may be configured and applied to the BMS simultaneously as applicable to each building-specific implementation.

[0060] Figure 26 is another diagram of an enhanced machine learning (RML) system for building decarbonization optimization that includes field devices communicating their respective data sets to an interpreter and agents through a BMS. Examples include various state data, including current set points, various control variables (e.g., temperature, pressure, flow rate, metering, occupancy, and / or humidity). This data can be used by the interpreter algorithm to calculate rewards. The interpreter algorithm considers the building's "comfort" conditions and decarbonization results together to determine whether previous actions resulted in optimal conditions as defined by the algorithm.

[0061] The reward value changes based on how well the agent's previous iteration performed. The agent receives the reward and state data and then uses its machine learning algorithm to determine the optimal action to send to the building environment (building systems and devices) for control. The continuous loop of decarbonization optimal control utilizes an interpreter and reward system to continuously reinforce positive results, allowing the system to continuously learn optimal actions across an ever-changing set of environmental conditions. As seasons and building conditions constantly evolve, the RML system adapts, continuing to learn and provide optimal decarbonization results while taking into account the built environment and comfort. The algorithm can be adjusted to weight "comfort" and "decarbonization" differently for each building use, ensuring that the correct balance can be provided to the owner to suit their preferences. Furthermore, the algorithm can be configured with absolute control boundaries that attempt to avoid exceeding and manage the window of available optimal control conditions.

[0062] All of the above can be configured separately within the boundaries of that configuration, as described above, for specific configured carbon conservation measures (CCMs), specific algorithms, and specific devices. As an example, a package AC unit (PAC) in the lobby may be different from a PAC in the gym, or a rooftop HVAC unit controlling a specific zone may have a different CCM as another zone. This provides the flexibility to continuously optimize all systems / subsystems within a building separately and autonomously, providing the combined benefits of carbon optimization for the building. Note that RML is very computationally intensive and is generally not run on-site. A remote or cloud COS leverages multiple RML applications in the cloud COS for each building to optimally control devices. If cloud connectivity is lost, devices default to their configured point control.

[0063] FIG. 27 illustrates another system according to an embodiment of the present disclosure, including a CMS and COS in the cloud associated with a gateway site that includes a Delta Building Management System discovery configuration. The system itself includes, for example, PACs 1-4 and rooftop units 1-2, as well as a cooling tower system and a boiler system. This embodiment is an example that uses standard BMS protocols, allowing the carbon site gateway to communicate with any standards-based BMS. Furthermore, the embodiment provides examples of various devices that consume carbon resources within a building. Devices typically interface through the BMS, but may also interface directly via MQTT. Any device that provides lighting, heating, cooling, and / or support subsystems that can be controlled for operation may be included in an embodiment in which the COS framework can operate.

[0064] 28-29 demonstrate real-time data that can be obtained utilizing the systems and methods of the present disclosure. The CMS / COS system utilizes a method for baseline system performance and comparing these conditions to actual performance to determine carbon reduction results. These results are reported in real time and aggregated daily, weekly, monthly, and yearly to show the individual and aggregate decarbonization performance of the CCM. This data is combined with carbon capture system performance measurements to show overall building decarbonization results and compliance with regulatory measurements specified in each market.

[0065] 30, an exemplary system is provided that provides further details regarding the machine learning that occurs at the carbon optimization system level where rewards are calculated and new set points are calculated to optimize the rewards. This particular example is given in a summer cooling situation where the COS is coupled to a carbon site controller that is also coupled to a building management system, and the rooftop units and cooling towers are coupled to the building management system, showing the baseline and results as data shown at T=0 and T=N.

[0066] A more detailed example of water heating with carbon optimization is shown in Figure 31. As shown, the carbon optimization system is set up to control and optimize the unit at different temperature levels and utilize the boiler conditions required to optimize the unit at different temperature levels.

[0067] Referring now to Figure 32, an exemplary CO separation and / or sequestration flow is shown including sensors configured to determine the flow and quantity of CO at locations within the process. As shown, flow meters and flow assumptions exist. In Figure 33, a more general flow is shown including at least two CO flow meters between the exit compressor and the VPSA and between the VPSA and the liquid CO. Shown in dashed lines may be one or more additional flow steps, including, but not limited to, CO storage and / or a transportation vehicle.

[0068] According to at least one example implementation, a building carbon capture system can include an inlet compressor configured to receive flue gas from a combustion source within the building, which can be a natural gas combustion source within a residential building.

[0069] The inlet compressor can be operably coupled to a VPSA assembly. The VPSA assembly can be operably coupled to a liquefaction assembly configured to provide, for example, liquid CO2. The system can include a plurality of flow / sensor assemblies operably engaged between the inlet compressor and the VPSA, and between the VPSA and the liquefaction assembly. The system can also include processing circuitry configured to receive rate data from the plurality of flow / sensor assemblies and process the data to determine one or more system performance parameters. The system performance parameters can include system recovery, and / or the processing circuitry can be configured to determine one or more system performance parameters using the CO2 rate data, for example, according to the following table utilized in the context of FIG. 32: [Table 1] [Table 2]

[0070] For example, the system may also include a user interface that displays a dashboard displaying one or more system performance parameters, such as those shown in FIGS.

[0071] According to another exemplary embodiment, and with reference to Figures 36-39, a building environmental management system and method for determining building environmental performance is provided. CCM, or "carbon conservation measures," is the application of the carbon domain to the existing concept of "energy conservation measures" (ECM). However, CCM relates carbon (typically in the form of CO2 and / or hydrocarbon fuels) to the energy domain. CCM can be dynamically optimized and / or determined in real time relative to static or retrospective observations. CCM can be continuous (e.g., 15 minutes) compared to every quarter. And / or CCM can be automated via software versus manual via an expert.

[0072] To determine the performance of a CCM, one or more "baselines" can be determined. In the context of energy efficiency and carbon efficiency, baselining is used to determine the performance of an energy or carbon conservation measure.

[0073] Baselining can compare "before" and "after" or "with" and "without." For example, with a traditional ECM, if all old incandescent light bulbs were replaced with new LEDs, electrical savings were determined by comparing the monthly power consumption of the old lights ("before") with the monthly power consumption of the new lights ("after"). If the "before" was 100 kWh and the "after" was 50 kWh, the ECM reduced power consumption by 50 kWh, or 50%. The 100 kWh "before" was the baseline. This hindsight perspective fails to provide truly usable data. For example, if the baseline month was in the darkness of winter and the comparison month was full of long, sunny days, the comparison is of little value. This is because traditional energy efficiency baselining, like ECM, tends to be static (one baseline), infrequent (quarterly best case, more often annually), and manual (by an expert). As an example, a simple baselining is shown in Figure 30.

[0074] According to one embodiment of the present disclosure, a building environmental management system is provided that provides dynamic baselining. For example, as shown in FIG. 36 , the system may include a building environmental optimization module (COS) configured to optimize building environmental conditions by modifying environmental parameters. The system may also include a building carbon conservation measures module (e.g., a baselining schedule) configured to determine building environmental conditions when the building optimization module is static or inactive. As described herein, the building environmental parameters may include one or more of temperature, humidity, and / or light, and / or the environmental conditions may be optimized for occupant comfort and / or carbon efficiency. The building environmental conditions may include zone environmental conditions, which may include HVAC devices.

[0075] The system may also include a comparison module configured to compare the building environmental conditions during optimization with the building environmental conditions without optimization (e.g., COS) and provide the same in the form of a performance report.

[0076] According to an exemplary embodiment, a method for determining building environmental performance is also provided. The method can include optimizing building environmental conditions (e.g., a COS in combination with a BMS). However, the building environmental conditions to be optimized are static or inactive while the building environmental conditions are determined. After the determination, optimization of the environmental conditions can be resumed.

[0077] According to an exemplary implementation, the building environmental conditions include one or more of temperature, humidity, light, and / or carbon efficiency. The environmental conditions are optimized for occupant comfort. The building environmental conditions can include zone environmental conditions. Each zone has an HVAC device (air conditioner, heater). The COS can measure zone-based energy, temperature, etc., and ultimately sub-devices (VFDs).

[0078] The building environmental conditions can be compared during optimization to the building environmental conditions while the optimization is static or inactive. The optimization can be static or inactive for one or more specific time periods. The time periods can be predetermined or randomly generated.

[0079] For example, referring to Figure 37, data for COS operation using all-day slot samples is shown. The first day (March 17) was a baselining day (see "Actual Heating Setpoint") and was stable and not controlled by the COS. On the second day (March 18), the COS was engaged and processed to lower the "Actual Heating Setpoint" in order to reduce carbon emissions while maintaining tenant comfort (zone temperatures).

[0080] According to an example implementation, "slot-based sampling" can be performed. For example, the 17th is an inactive slot for baselining, and the 18th is an active slot for optimization. Slots can be assigned as shown in Figure 38.

[0081] Emissions can be estimated by multiplying the emission rate during non-optimization (non-optimized emission rate) during a selected time interval by the duration of the entire selected time interval. This non-optimized emission rate can be measured in real time, at a flexible time, duration, and / or frequency. For example, a daily 3-hour rolling sample, or every other day, or similar forecast day. Baselining can be dynamic, real-time / flexible, zone-by-zone, and automatic. Thus, "eliminating sample bias" is similar to A / B testing, offering the significant advantage of determining performance in real time compared to waiting a year. For example, as shown in Figure 39, here the COS uses a dynamic baselining schedule to turn CCM on or off, which is used for COS performance reporting.

[0082] According to another embodiment of the present disclosure, a COS can be configured to operate in conjunction with a BMS having environmental set points determined by a building operator, such as a manager.

[0083] Thus, there is provided a method for optimizing building environmental performance, which may include setting one or more building environmental set points in a building management system. The set points may be room and / or zone temperatures, and zone or room tolerances for optimization.

[0084] The method can include using a carbon optimization system to optimize one or more environmental conditions using one or more building environmental setpoints in a building management system. According to an exemplary implementation, thermostat comfort setpoints and flexibility (seasonality) by zone via BMS comfort goals can be set by an administrator. Tolerances can also be set. For example, a zone or room may be more temperature sensitive than other zones or rooms in the building. High, medium, and low tolerances (°C) for temperature can be set from a dead band (no occupancy range, e.g., + / - 2°C). For example, a high tolerance can be set = service aisles, allowing the COS to optimize more (+ / - 3°C); a medium tolerance = aisles, lobbies, common areas (2°C); and a low tolerance can be set = gym, not allowing the COS to optimize more, keeping it tight (<1°C).

[0085] According to additional embodiments, a method for engaging / disengaging a carbon optimization system from a building management system is also provided. The method can include determining one or more building management system performance thresholds while the carbon optimization system is engaged / disengaged from the building management system. The thresholds can be measures of system change relative to a setpoint target. For example, if the BMS is attempting to reach a room or zone temperature but all systems are engaged, the temperature cannot be reached, the setpoint target is not reached, and the threshold is not reached. This can occur on a very hot or cold day.

[0086] The method may include engaging / disengaging the carbon optimization system from the building management system according to one or more system performance thresholds.

[0087] According to an exemplary implementation, the carbon optimization system engages to optimize the environmental set points of the building management system, and if the building management system does not meet the environmental set points, the carbon optimization system disengages from the building management system.

[0088] According to another exemplary implementation, the carbon optimization system is disengaged to optimize the environmental setpoint of the building management system, and when the building management system meets the environmental setpoint, the carbon optimization system is engaged with the building management system.

[0089] These methods and systems can provide automatic COS suspension.

[0090] In accordance with the statute, embodiments of the invention have been described in language that is more or less specific with respect to structural and methodical features. However, since the disclosed embodiments include forms of practicing the invention, it is to be understood that the invention as a whole is not limited to the specific features and / or embodiments shown and / or described. The invention is therefore claimed in any of its forms or modifications within the proper scope of the appended claims, appropriately interpreted in accordance with the doctrine of equivalents.

Claims

1. 1. A carbon management system comprising: A carbon management system comprising: a processing circuit operably coupled to a carbon site control module, the carbon site control module operably engaging one or more of a carbon resource module, a carbon capture control module, and / or a building management system.

2. The carbon management system of claim 1 , wherein the managed carbon is substantially carbon dioxide.

3. The carbon management system of claim 1 , wherein the carbon site control module is operatively associated with one or more of a residential building, a factory, and / or an office building.

4. The carbon management system of claim 3 , wherein the carbon resource module is in operative engagement with one or more of a carbon transport vehicle and / or a carbon reservoir.

5. The carbon management system of claim 1 further comprising a carbon optimization system operatively engaged with said carbon site control module.

6. 6. The carbon management system of claim 5, wherein one or both of the carbon management system and / or the carbon optimization system are operatively engaged with one or more of an electric carbon source, a natural gas carbon source, and an oil carbon source, and / or a steam carbon source.

7. The carbon management system of claim 1 , wherein the carbon capture control module is in operative engagement with a carbon capture system.

8. The carbon management system of claim 7 , wherein the carbon capture system is in operative engagement with a combustion system.

9. The carbon management system of claim 8 , wherein the carbon capture system is configured to facilitate separation of carbon dioxide from combustion products of the combustion system.

10. The carbon management system of claim 1 , wherein the carbon site control module is in operative engagement with a building management system.

11. 1. A carbon optimization system, comprising: A carbon optimization system comprising: a processing circuit operably coupled to a carbon site control module, the carbon site control module operably engaging one or more of a carbon resource module, a carbon capture control module, and / or a building management system.

12. The carbon optimization system of claim 11 , wherein the processing circuitry includes a machine learning module.

13. The carbon optimization system of claim 12 , wherein the machine learning module is configured to receive carbon production and use data received from one or more carbon site control modules.

14. The carbon optimization system of claim 13 , wherein each of the carbon site control modules is in operative engagement with one or more building management systems.

15. The carbon optimization system of claim 11 , wherein the machine learning module comprises one or more of an analytics module, a versioning module, a predictive maintenance module, and / or anomaly detection module.

16. The carbon optimization system of claim 11 , wherein the carbon optimization system is a cloud-based processing circuit.

17. The carbon optimization system of claim 15 , wherein the cloud-based processing circuitry is operably coupled to receive external data.

18. The carbon optimization system of claim 16 , wherein the external data includes one or more of power grid usage and / or weather data.

19. The carbon optimization system of claim 11 , wherein the system further comprises processing circuitry configured to receive and analyze carbon market data.

20. The carbon optimization system of claim 18 , wherein the carbon market data includes one or more of electricity costs, fuel costs, steam costs, and / or carbon dioxide costs.

21. 1. A building carbon capture system comprising: an inlet compressor configured to receive flue gas from a combustion source within the building, the inlet compressor being operably coupled to a VPSA assembly, the VPSA assembly being operably coupled to a liquefaction assembly; a plurality of flow / sensor assemblies operably engaged between the inlet compressor and the VPSA, and between the VPSA and the liquefaction assembly; a processing circuit configured to receive rate data from the plurality of flow / sensor assemblies and process the data to determine one or more system performance parameters.

22. 22. The building carbon capture system of claim 21, wherein the combustion source within the building is a natural gas combustion source within a residential building.

23. 22. The building carbon capture system of claim 21, further comprising a user interface comprising a dashboard displaying one or more system performance parameters.

24. 24. The building carbon capture system of claim 23, wherein the system performance parameters include a system recovery rate.

25. 24. The building carbon capture system of claim 23, wherein the system performance parameters are obtained at one or more of a plurality of stages.

26. One or more of the flow / sensor assemblies ２ 22. The building carbon capture system of claim 21 configured to sense

27. The processing circuitry may include: a CO ２ 27. The building carbon capture system of claim 26 configured to use rate data.

28. A building environmental management system, comprising: a building environment optimization module configured to optimize building environment conditions by modifying environmental parameters; a building carbon conservation measures module configured to determine a building environmental condition when the building optimization module is static.

29. 30. The system of claim 28, wherein the building environment parameters include one or more of temperature, humidity, and / or light.

30. 30. The system of claim 28, wherein the environmental conditions are optimized for occupant comfort.

31. 30. The system of claim 28, wherein the environmental conditions include carbon efficiency.

32. 30. The system of claim 28, further comprising a comparison module configured to compare the building environmental conditions during optimization with the building environmental conditions without optimization.

33. 30. The system of claim 28, wherein the building environmental conditions include zone environmental conditions.

34. 34. The system of claim 33, wherein the zone environmental condition includes an HVAC device.

35. A method for determining the environmental performance of a building, comprising: optimizing building environmental conditions; determining environmental conditions while the optimization of the building environmental conditions is static; and resuming the optimization of the environmental conditions.

36. 36. The method of claim 35, wherein the building environmental conditions include one or more of temperature, humidity, light, and / or carbon efficiency.

37. 36. The method of claim 35, wherein the environmental conditions are optimized for occupant comfort.

38. 36. The method of claim 35, further comprising the step of comparing building environmental conditions during optimization with building environmental conditions while the optimization is static.

39. 36. The method of claim 35, wherein the building environmental conditions include zone environmental conditions.

40. 36. The method of claim 35, wherein the optimization is static for one or more specific periods of time.

41. 41. The method of claim 40, wherein the period of time is predetermined.

42. 41. The method of claim 40, wherein the period of time is random.

43. 1. A method for optimizing building environmental performance, comprising: setting one or more building environmental set points in a building management system; using a carbon optimization system to optimize one or more environmental conditions using the one or more building environmental set points of the building management system.

44. 44. The method of claim 43, wherein the building environmental set point is a temperature.

45. 44. The method of claim 43, wherein the building environmental set point is a zone tolerance.

46. 44. The method of claim 43, wherein the setting of the one or more building environmental set points is performed by a building manager.

47. 1. A method for engaging / disengaging a carbon optimization system from a building management system, comprising: determining one or more building management system performance thresholds while the carbon optimization system is engaged / disengaged from the building management system; engaging / disengaging the carbon optimization system from the building management system according to the one or more system performance thresholds.

48. 48. The method of claim 47, wherein the one or more building management performance thresholds include meeting an environmental set point.

49. 49. The method of claim 48, wherein the environmental set point is a temperature.

50. 50. The method of claim 49, wherein the temperature is room temperature.

51. 51. The method of claim 50, wherein the temperature is in a zone.

52. 48. The method of claim 47, wherein the carbon optimization system engages to optimize an environmental set point of the building management system, and wherein the carbon optimization system disengages from the building management system if the building management system does not meet the environmental set point.

53. 53. The method of claim 52, wherein the environmental set point is room temperature.

54. 48. The method of claim 47, wherein the carbon optimization system is disengaged to optimize an environmental set point of the building management system, and wherein the carbon optimization system is engaged with the building management system when the building management system satisfies the environmental set point.

55. 55. The method of claim 54, wherein the environmental set point is room temperature.

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