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By Andres Carvallo and John Cooper
Utilities today have a fragmented view of operations. This derives from their siloed approach. And from their dependence on proprietary technologies that lack the ability to communicate with each other. Walking through an energy control center today would show multiple operational units monitoring and managing different parts of the grid – from DCS to EMS/SCADA to OMS to AMI to DR -- each with a distinctive view provided by a stand-alone, proprietary system. It is left to the human grid operators to integrate these disparate views and make management decisions with the information they have at hand.
Unlike telecom operators today, electric utility operators have no view of the entire operation on a single screen. Unlike the telecom operator who sees when a cell phone enters or leaves the network, an electric utility operator has no ability to see single devices. In fact, the operator is blind to grid events beyond the distribution substation.
A new alternative emerges
A new alternative has emerged to replace application silos – the smart grid optimization engine. Tremendous efficiencies become available with new interoperability standards and new processes that stress a holistic perspective (looking at the organization as an integrated ecosystem rather than a collection of partially connected silo organizations). Data can flow into a common database. That enables individual applications to draw on a comprehensive set of timely data rather than limited subsets that risk leaving blind spots.
A smart grid optimization engine needs to provide universal management functionality. First, it should be capable of running on any conceivable IP network. Second, the engine must provide complete security that is NIST, FIPS and NERC CIP compliant. Third, it should fully support Internet protocol and be capable of operating at near real-time speeds – at 100 ms or less. Fourth, it should provide superb interoperability. It should support all electric devices (e.g., transformers, feeders, switches, capacitor banks, meters, inverters) from any vendor.
Fifth, a smart grid optimization engine should be capable of growing to meet future needs, since massive scalability will be needed. When the distributed energy resources now under development become commercially viable, millions of new devices will come under utility purview. Finally, the engine has to be economically competitive on a total cost of ownership basis.
Next page: The benefits of an optimization engine >>
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