Basically all of the computing resources that cities use rely on energy in some way, shape or form, so it makes sense for cities to constantly monitor for efficiencies and economies as they use, deploy and procure computing resources. As discussed in detail in the Universal chapter:
Consider a cloud computing framework to enable scalability of systems, reduce costs and improve reliability.
Have access to a central geographic information system (GIS) to improve decision-making capabilities, enable efficiency gains through more intelligent scheduling and routing, provide improved accuracy of essential records and boost resiliency of key assets.
Have access to a comprehensive device management system to improve infrastructure security and resiliency, deliver cost savings and enforce compliance with city data management, security and privacy policies. This target, as we noted, takes on special importance in the energy discussion due to the numerous smart devices and other computing resources deployed throughout smart cities.
As we’ve said previously, analytics are absolutely critical to smart city success and perhaps nowhere is that more evident than in a smart energy network that powers so much of what a city is and does. We’ll quickly review three of the analytics targets already discussed in the Universal chapter and then introduce two more that speak volumes about energy’s importance in a smart city.
Achieve full situational awareness. This refers to giving operators a complete picture of their energy system at any given moment to increase its reliability and resiliency and quickly respond to trouble. A complete operating picture is incredibly important to city energy systems. One example: It helps operators detect energy theft and thereby conserve resources.
Achieve operational optimization. Building the very best smart energy network possible is what cities want to achieve from the instrumentation and connectivity investments they make in their energy infrastructure.