Cloud Energy Software
Software Framework that Embraces Robust Energy Management Applications

Observing the international environmental problems, authorities around the world are initiating numerous carbon reduction regimes. Aiming to reduce carbon emissions, these regimes are designed to minimize energy usage and encourage investment in new technology. Observing the requirement of these carbon reduction managements, the U.S. has also implemented mandatory initiatives but at state and city level, which makes the energy market more complex. “It’s quite challenging to understand the effect of these regulations on businesses and deliver energy management applications accordingly,” expresses Stuart Whistance, CEO, Cloud Energy Software. Delivering solutions that enable clients to manage non compliance risks, and reduce their energy use and cost is Cloud Energy Software—a provider of robust, secure and scalable energy management solutions.

Big data and cloud computing form the basis of the company’s offerings for being able to react to the ever changing market needs. “The elements of big data, whether it’s the data in meter or logging device or non energy data, all depict a huge impact in the energy usage,” asserts Whistance. Further, as the energy management application has to integrate with other systems, the cloud computing elements helps the company to reduce cost of energy consumption and create an agile environment for a software supplier by reducing their startup timing. Cloud based software has positively impacted engagement; energy managers can gather stakeholders from organizations to share, realize and understand their true energy profile.

Cloud Energy’s software framework comprises of a series of applications, which forms the core of a web-based solution for energy users. These applications are developed on a common standard and database, organized to process large volumes of data that clients require. They capture data automatically and directly into the company’s database, whilst satisfying corporate security rules, enabling verification of the data accuracy and storing them in a single format. Being cloud based, these applications can be built into specific solutions for individual clients at a cost effective price. Moreover, the company offers Cloud Energy Application-as-a-Service (AaaS) for the U.S. market, which enables a software supplier to integrate energy management applications within their own solutions quickly.

To improve the accuracy of analytics data, Cloud Energy efficiently utilizes the capabilities of devices such as mobile phones and metering devices. “Our applications cover both supply and demand side for the energy market,” says Whistance.

The company involves immense planning process along with the staff to understand the plan and their role in delivering satisfactory solutions. Whistance has developed this practice from his personal life where he performs long distance cycling to raise money for charity. “Such events require planning,” says Whistance. For instance, one of the company’s clients, a major U.K. baker with 12 large production plants was struggling to get accurate data. Cloud Energy involved different data collection methods including electronic data interchange (EDI) utility feeds and accumulated relevant key performance indicators (KPI) on the shop floor on a regular basis. This helped the client’s production management to reduce energy consumption resulting in substantial energy savings.

We believe that Cloud Energy AaaS is innovative and will allow many software companies to add energy management offerings within their software application

With a vast market, the company observes good opportunity in the U.S. following the growing use of Energy Star and increase of sub metering activity. “We believe that Cloud Energy AaaS is innovative and will allow many software companies to add energy management offerings within their software application,” says Whistance. “Our future plans include launching a new level of energy modeling and verification by introducing a multidimensional modeling approach (MEMV),” concludes Whistance.