Automatic system for controlling appliances

A method for managing house appliances supplied through a power grid, each house appliance being adapted to operate according to at least one corresponding operative mode, each operative mode comprising a sequence of operative phases, the method comprising:

• collecting power profile data comprising timing and electric power consumption data of each operative phase of each operative mode of the house appliances;
• generating a time schedule of house appliances operations by distributing in time execution of the operative phases thereof in such a way that a total power consumption of the house appliances is kept under a maximum power threshold of the power grid, wherein the distributing in time the execution of the operative phases comprises maintaining a first sequence of operative phases for a first appliance of the house appliances and shifting in time one or more operative phases of a second sequence of operative phases for a second appliance of the house appliances, wherein the generating the time schedule comprises:
• randomly generating a population of candidate time schedules within a search space comprising a plurality of candidate time schedules;
• for each candidate time schedule of the population, calculating a corresponding cost by using a cost function;
• moving the candidate time schedules in the search space based on the cost thereof with a Quantum Particle Swarm Optimization approach exploiting a Lévyprobability distribution;
• and
• generating the time schedule based on the candidate time schedules;
• and
• controlling the operation of the house appliances based on the time schedule,
• wherein the step of generating the time schedule includes exploiting a Particle Swarm Optimization approach based on a nature-inspired evolutionary flight.

A computer readable medium having a software program stored thereon that, when executed by a processor, causes the processor to perform operations comprising:

• collecting power profile data comprising timing and electric power consumption data of each operative phase of each operative mode of house appliances;
• generating a time schedule of operations of the house appliances by distributing in time execution of the operative phases thereof in such a way that a total power consumption of the house appliances is kept under a maximum power threshold of the power grid, wherein the distributing in time the execution of the operative phases comprises maintaining a first sequence of operative phases for a first appliance of the house appliances and shifting in time one or more operative phases of a second sequence of operative phases for a second appliance of the house appliances, wherein the generating the time schedule comprises:
• randomly generating a population of candidate time schedules within a search space comprising a plurality of candidate time schedules;
• for each candidate time schedule of the population, calculating a corresponding cost by using a cost function;
• moving the candidate time schedules in the search space based on the cost thereof with a Quantum Particle Swarm Optimization approach exploiting a Lévyprobability distribution;
• and
• generating the time schedule based on the candidate time schedules;
• and
• controlling the operation of the house appliances based on the time schedule,
• wherein the generating the time schedule includes exploiting a Particle Swarm Optimization approach based on a nature-inspired evolutionary flight.