An Enhanced Simulated Annealing Scheduling Approach for Smart Meter Technology


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Abstract


For residential electricity consumers, there are power loads which need to be switched on for a time between two predefined time instants. The electricity price could be different between peak and off-peak time. Customers can minimize their own energy expense if the smart grid could calculate and schedule the electrical equipments’ operation times which are determined by their power consumptions and operation time constraints.
We call these services Demand Response (DR) services. In the Smart Grid environments, the Advanced Metering Infrastructure (AMI) could automatically schedule the operation time of each equipment to minimize the residential overall power consumption while satisfying the equipment’s operation time constraint i.e. the equipment needs to be started at a time between two predefined time instants, and the system power load constraint i.e. the power system is not overloaded at any time instant. The paper formulates the situation as an optimization problem and proposes an enhanced Simulated Annealing (SA) based algorithm to find the optimum schedule arrangement for all the tasks. The simulation results show that the SA based scheduling algorithm can efficiently and optimally minimize customers’ electricity cost


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Keywords


Smart Grid; Advanced Metering Infrastructure; Demand Response; Simulated Annealing

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