Microsoft unveils smart grid software secrets

It is hoped through smart grid technology some of the pressure currently on power plants in the Middle East and globally can be lifted.
[More Images]

Establishing New
Business Models
Utility industry executives are increasingly concerned about the possible costs involved in changing their business models to enable the development of the smart energy ecosystem.

 

For example, utility company CIOs who have responsibility for data collection and warehousing for millions of customers, as well as all related business and generating operations, are looking for solutions that help in-house staff to support and fully respond to the challenges of smart grid scale and interoperability.

The transition of the power and utilities business to the new smart energy ecosystem may well be the most significant change to shape the industry since its inception.

Advertisement

FEATURED COMMENT Please click here to comment on this article

New processes such as end use loads dynamically participating in the ecosystem in a meaningful way, and new data requirements such as the 2,880 fold increase moving from one customer billing sample per month to 15 minute samples for a 30-day month, will significantly change the landscape.

Smart metering, automotive electric propulsion, renewable generation, new communications, new business models and a host of new industry players will all shape the future. The outlook can be a daunting challenge for anyone in the power and utilities computing arena.

To succeed, utilities will need a holistic view of how the smart grid fits into a smart energy ecosystem, as well as a strong foundation for migrating to the new infrastructure and services necessary to interact with, monitor, control and report on the assets of this new power system. This is especially true as utilities and the energy value chain reconfigure their business processes to establish new business models and capture new opportunities as they arise.

Architecting a Smart Energy Ecosystem
A technology architecture is needed to support the transition of the power and utilities business to the new smart energy ecosystem. The technology architecture of the smart energy ecosystem, however, won’t be confined to the need to revise business practices for workforce, consumer and regulatory changes. It will also need to be an enabler of new technologies, some we know about, and some that are yet to come.

For example, a new generation of field and home devices that have the ability to make local decisions using two-way communication capabilities will allow customers to better monitor, control and schedule energy consumption, as well as respond to demand response events and pricing signals.

Utilities or independent service providers could use these devices to extend their operational capabilities by facilitating registration of the devices in energy programmes that permit the power provider to adjust schedules to provide more efficient and balanced operation of distribution networks.

The smart energy ecosystem also will require new computing paradigm approaches. Real-time energy management systems, whether at the transmission or distribution levels, will continue to have rigorous performance and reliability constraints.

A smart energy reference architecture recognises that close coupling of all the new participants to the operation of the real-time systems will prove to be fragile and unreliable over the long term.

The scale of connected smart energy systems will grow to new levels with the addition of the active participation of loads (end-use customers) and a multitude of tiny new devices. Systems will need to be designed to be flexible and adaptive to autonomous behavior.

The true measure of success will be building a working system out of autonomous independent unreliable devices and participants.

The smart energy reference architecture as a result must enable interoperability in order for the ecosystem to develop in a cost effective manner. New solutions must work with previous utility technology systems in order to protect those investments.

Pragmatic integration approaches will need to be considered and the reference architecture should be flexible to allow deploying new components without custom integration. Otherwise, the vision for the ecosystem will not be pragmatic and will go unfulfilled.

---