The U.S. power grid is, in a sense, the industrial predecessor to the Internet of Things (IoT), having been in place since the early-mid 1900’s and being the largest interconnected machine on the planet with 9,200 electric generating units, over one million megawatts of generating capacity, and over 300,000 miles of transmission lines.
The Department of Energy states that the American power grid is 99.7% reliable – and yet – no one can deny that its old – very old.
The classic electric meter is the link to the current grid, installed at a customers’ location to measure electric energy delivered for billing purposes, usually stated in kilowatt hours. In some instances they can also: a) measure “time of day” demand, b) adjust rates, c) maximize use of power within specified intervals and d) demand response load shed.
Smart meter installations on the other hand, create smart energy grids, which, through the utilization of sensors, open a world of transparency and predictive opportunities to help us understand, analyze and determine the impacts of energy consumption and how to best achieve load and cost reductions.
When compared to todays’ classic centralized grid, tomorrow’s smart grid is user driven and iterative, relying upon sensor-driven bi-directional communication to constantly adapt and tune the delivery of energy.
Some smart grids utilize as many as 20 specific types of sensors at strategic points in the processes of power generation through distribution ending at your meter. These sensors continuously assess, in real-time: a) state of the grid, b) availability of power flowing into the grid and c) demand on the grid.
Sensors are superior data collectors and aggregators, and can, over time, determine what “behaviors” can be changed to optimize energy delivery. In other words – they can become “predictive tools” assisting users in understanding cause/effect more clearly such that behavior change is only one aspect of the value of the smart grid.
As an example of predictive planning rather than behavior change, data can be used to help architects/engineers and large corporate users understand the thermal efficiency of their portfolios, including buildings, facilities and retail, and within that, the kind of energy flexibility that is available. What energy requirements must be met? Which are candidates for deferral?
Imagine the day smart grids – fed by data from smart meters processed by smart sensors control and allocate energy according to your customized energy program and budget for your building or portfolio. Like a phone data plan, the smart grid could text you on a predictive basis and: a) alert you to potential overages, b) require your real-time authorization to go over budget or c) automatically make adjustments necessary to stay within budget.
Predictive and real-time, my imaginary technology will come about someday – and probably soon. It truly exemplifies power of the IoT working harmoniously in union with SustainAbility, a lovely marriage led by the ring-bearer – our beloved electric meter!!
Nadine Cino LEED AP is the CEO and co-inventor of Tyga-Box Systems, Inc., New York, N.Y.