Managed Services — The Future in Building Automation
Managed Services ensures that a building’s operations is overseen 24/7 by a highly trained and skilled operations team, responsible for ensuring the HVAC system delivers on guaranteed comfort and savings.
BuildingIQ’s Meter Processing Flow
Predictive Energy Optimization™ (PEO) platform is a paradigm-shifting technology used to reduce energy consumption in commercial, academic, and government buildings. This paper focuses on the important process of collecting meter data and feeding it into the PEO model.
Managing Maximum Demand Through Optimization
The status quo for today’s HVAC technology includes temperature control that is static and fragmented; that is, building temperatures directed by a fixed setpoint, and HVAC scheduling that is independent for each zone/room. Flexibility to move temperatures around leads to enormous opportunities to optimize energy efficiency and cost.
Energy Efficiency Ratings— Benchmarks that Drive Excellence in Building Design and Operations
Rating systems for the design and performance of energy efficient buildings have evolved rapidly over the last twenty-five years. They have become broader, deeper, and more precise as advances in technology-based, building intelligence have converged with the societal imperatives of saving energy, reducing environmental impact, and improving the quality of life.
Managing the Three Cs of Advanced Building Operations
The cutting edge of advanced building operations requires managing three challenges simultaneously—growing complexity, continuous change and conflicts arising from the pursuit of multiple objectives. Pre-programming HVAC controls is no longer a fine enough instrument for advanced building management. Adaptive learning and rapid, multifunctional response is needed to keep up with changing conditions and opportunities. The key lies in the marriage of automated awareness and multipleobjective, intelligent decision-making processes, both of which are integral to BuildingIQ’s Predictive Energy Optimization™ platform.
Measurement and Verification Functionality of the BuildingIQ System
Reducing building energy use through the implementation of energy efficiency projects is a proven strategy. However, claims of energy efficiency savings must be supported by measurement. Clients, investors, program administrators, and other stakeholders now require quantifiable evidence that the contract or programmatic goals have been met. For every project—whether lighting retrofits or HVAC optimization—providing evidence of energy savings is a critical element to ensure limited dollars are spent in the most cost-effective manner. M&V is the process of quantifying savings delivered from an energy conservation measure.
The security of customer BMS and IT systems is of the utmost importance to BuildingIQ, and our products and policies reflect that. BuildingIQ stays abreast of and uses the best practices as they emerge from the IT security community whose sole focus is on quickly dealing with current threats and anticipating future ones.
Moving from Connected Buildings to Smart Buildings
Since the early twentieth century when the father of modern air conditioning Willis Carrier invented air washers to cool air and control humidity in printing press warehouses, building engineers have struggled to keep occupants comfortable. Facility managers have relied on building control systems to optimize this conditioned environment. Over time these systems have progressed from analog to pneumatic to direct digital control giving managers better and better control. There have also been other advancements supporting building managers: open protocols, relational databases, larger hard drives, faster computers and better staff training. The result is that today’s modern office building is analogous to a living and breathing organism with connected systems monitoring its environment. But can the modern building learn from its environment?
Next Generation Building Energy Management Systems and Implications for Electricity Markets – By Argonne National Labs
The U.S. national electric grid is facing significant changes due to aggressive federal and state targets to decrease emissions while improving grid efficiency and reliability. Additional challenges include supply/demand imbalances, transmission constraints, and aging infrastructure. A significant number of technologies are emerging under this environment including renewable generation, distributed storage, and energy management systems. In this paper, we claim that predictive energy management systems can play a significant role in achieving federal and state targets.
New Approaches in Automating and Optimizing Demand Response to Solve Peak Load Management Problems
Grid power demand peaks and increasing supply/demand in- balances create management challenges for utilities. These challenges are increasingly being resolved using non- “supply side” solutions. While the use of curtailable load in Demand Response (DR) applications is a powerful solution in managing the problem of grid load peaks, it is not without its challenges. Delivering DR from commercial, industrial and institutional (C/I/I) buildings can be difficult, costly and risky for building owners. DR participation from these electricity customers can be unreliable and unpredictable unless the right tools, processes, economic incentives, systems and training are in place.