Even though residential loads account for close to 40% of the total electrical load in the US, utilities often resort to large commercial or industrial users for demand relief. This application introduces a middleman - The Integrator who will control a cluster of loads such as a neighborhood or a large apartment complex and provide demand relief to the utilities during their time of need.
We assume certain appliances in these household are metered via smart meters. They will be able to send data regarding power consumption to the aggregator who will build a load model based on this. Customers can specify which of their appliances are critical and non-critical thereby ensuring that customers are as comfortable as they want to be, which is critical in garnering full support for this program.
Certainly, the complete details of consumption will not be obtained by the aggregator from the smart meters alone - it is infeasible to have smart meters for every appliance. This is where the Green Button data standard plays an important role. By constantly updating the integrators as to what the actual consumption is, the API provides them information to estimate the non-metered load constantly.
Within the constraints of time limits, aggregators can now move non-critical loads such as laundry machines, dishwashers and so on to whenever they feel the consumption would be the lowest.
The application builds this data for the aggregator. Using GreenButton data and sample load data, this application can demonstrate how moving the load to different parts of the day can have a direct impact on meeting the constraints set by the aggregator.
The application also uses temperature data to predict the heating or cooling requirement of the building(s).
Using this application, utilities can seek demand relief from customers via third party aggregators.
Possible Incentives for customers to sign up could include a lowering of electricity charge based upon participation or spot incentives based upon performance.
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