- Predictive Energy Optimization
- Optimized Demand Response & DRIQ
- System Architecture
- Security
- Safeguards and Monitoring
Predictive Energy Optimization is a unique capability of the BuildingIQ system that incorporates real time energy grid and weather information into a multi-objective optimization model. It overcomes the shortcomings of existing HVAC control systems by continuously predicting conditions and adapting settings to optimize energy efficiency without sacrificing comfort.
Controlling HVAC systems typically involves adjusting various setpoints, valves and dampers to deliver air flow which meets the needs of the occupied space. This is not always easy to achieve in practice due to inherent limitations of both legacy and new HVAC installations and the complex interaction among the various HVAC components. The situation is further complicated by the dependence of HVAC performance on building load, building thermal mass as well as the performance of fans, chillers, and other subsystems including the facade – all of which can change continuously over time. What should be a simple setpoint adjustment process turns out to be not only complex but also very inefficient from an energy usage perspective.
BuildingIQ‘s technology addresses the fundamental shortcomings of HVAC systems and the complexity of the control problem by using a multi-objective optimization framework. The framework is combined with an intelligent HVAC supervisory control system that utilizes multi-agent systems science and machine learning techniques to automatically evaluate different control scenarios to determine optimal control set-points and operating schedules. It also takes into account dynamic HVAC and building parameters, building occupant comfort feedback, as well as real-time energy grid and climate information. The supervisory control system pro-actively controls the existing Building Management System (BMS) to ensure that set-point outcomes are achieved. The technology is applicable to a wide range of BMS systems and types/ages of HVAC infrastructure. The figure below illustrates the architecture.
Optimized Demand Response is a unique approach to commercial building Demand Response (DR) management that achieves DR event objectives while maintaining occupant comfort. It provides building owners with information about the costs and benefits of meeting DR energy reduction targets, while also ensuring that tenant comfort commitments are met. This unique ability to meet both objectives makes Optimized Demand Response the only viable DR option for commercial building owners and managers.
To meet the dual objectives of DR targets and comfort, Optimized Demand Response models DR events in addition to building thermal behavior and occupant comfort. This higher level of sophistication in the optimization framework is added to the fundamental optimization provided by the core BuildingIQ system.
The world’s first product offering Optimized Demand Response is DRIQ, an add-on product available to BuildingIQ customers.
In the above, all the communication between the BuildingIQ appliance and the BMS is IP-based, with actual building data exchange achieved using one of several industry-standard protocols, including OPC, BACnet or oBIX. Both OPC and BACnet allow direct connection to a BMS system. oBIX allows connection via a Tridium gateway device, which facilitates connectivity to a very broad range of legacy BMS systems that may not support OPC and BACnet.
The BuildingIQ system is also connected to the Internet. The Internet connection provides access to external information, such as weather forecasts, pricing tariffs, and Demand-Response request notifications. It also provides a conduit for storing data in a central database for reporting and analytics purposes. The information stored in the database covers a wide spectrum of data acquired from the BMS as well as written to the BMS.