Extending Edge Computing and Cloud Paradigms to EMSs

Energy management systems (EMSs) have been used for decades by commercial and industrial facilities to help reduce costs and improve their energy usage. Early generations of these software platforms were installed on hosted servers within the facility. However, in recent years, driven by the imperative to take costs out of the business, the development and adoption of cloud-based EMSs using the software as a service (SaaS) model has grown in popularity. While some prospective customers are hesitant, operational benefits realized across a growing base of cloud-based deployments are facilitating a more decentralized future for EMSs.

EMS Architectures Center on Two Primary Application Areas

EMS functionality can be split into two logical areas. One logical area within EMS applications ingests data generated from sensors and then suggests quick corrective actions such as powering equipment on and off. These functions must be done in real time and with high reliability to prevent waste or damage. The other logical area within EMS applications tends to be less time-critical and relies on facilities staff to architect rules and commands to enable the most desirable settings. 

The Architecture of a Traditional EMS Application

(Source: Guidehouse Insights)

EMS Application Areas Have Differentiated, Evolving Requirements 

Traditional EMS offerings have primarily consisted of single software packages. However, these two logical areas have very different computer processing needs. The first logical area relies on advanced improvement algorithms and must provide exceptional reliability for real-time use cases and be located on premises. The other logical area is more focused on user accessibility and ease-of-use and can be located either on premises or remotely. 

The processing demands associated with this second area have grown increasingly sophisticated over time. This includes coordinating when and how facilities’ staff want things to operate over different time scales (i.e., day, month, or season), interfacing with other building systems, analyzing conditions on the power grid, and working with data visualization packages such as ABB Ability. The U.S. Department of Energy discusses some of the many possibilities in its report Artificial Intelligence Applications for Energy Management.

EMS Modularization Enables Higher Levels of Cloud Adoption

To address these increasing divergent needs, EMS vendors have been rearchitecting their solutions to enable these two functional areas to operate on their own hardware platforms under a SaaS model. The on-premises part of the EMS application runs on industrial gateways specially built to provide uptime while the more administrative functions of the EMS application operate on conventional IT hardware. If the connection between the two sides fails, the onsite equipment will continue to follow whatever it was last instructed to do.

The value of the cloud operations resides on the other side, where the software waits until an event occurs, at which point it needs a significant amount of processing power. This can operate on-premises using equipment that mostly sits idle, but these kinds of demands are better suited for highly scalable cloud computing architectures. With the SaaS model, the costs are lower and can often be expensed rather than capitalized. 

The Terminology of the Cloud

The concept of edge computing has taken the industry by storm over the past decade. This shift in EMS offerings and software architectures is just one example of this edge computing paradigm, with the bulk of processing occurring in the cloud. EMS is an ideal example of SaaS where you get the best of local and cloud computing. In addition to being able to quickly scale up and down the processing needs, it enables the connection of useful and unconventional data sources while supporting leading cybersecurity practices. The Guidehouse Insights November 3, 2021 webinar, The Growing Impact of EMS Solutions: The Power of SaaS for EMS, presents the value of this platform configuration.