System and method for optimization of power consumption and power storage

1. A method of managing power distribution in a portion of an electrical power grid, wherein the power grid comprises at least one power storage, the method comprising:

receiving at least one power consumption rule from at least one consumer of the power grid;

analyzing power consumption data from at least one power consumption meter connected to the power grid, wherein the received power consumption data corresponds to consumption of the at least one consumer;

receiving forecasted power consumption data;

applying the at least one power consumption rule on the analyzed power consumption data, wherein the application of the at least one power consumption rule is also based on forecasted data, wherein the forecasted data is selected from the group consisting of: forecasted power consumption, forecasted power production and forecasted energy prices; and

managing power consumption for the at least one consumer, based on the result of the at least one power consumption rule, and also based on a power capacity status of the at least one power storage, wherein the result of the at least one power consumption rule is calculated based on a machine learning algorithm configured to increase power distribution of the power grid towards a second predefined threshold.

2. The method of claim 1 , wherein the operation of power consumption management is selected from the group consisting of: allocating power resources to the at least one power storage, retrieving power from the power grid, consuming power from the at least one power storage instead of the power grid, and reallocating power resources to a different consumer of the power grid.

3. The method of claim 1 , wherein management of the power consumption comprises consuming power by an electrical appliance connected to the power grid.

4. The method of claim 1 , wherein the power grid further comprises at least one power production facility, and wherein the operation of power consumption management comprises at least one of: allocating power resources from the at least one power production facility to the at least one power storage, and allocating power resources from the at least one power production facility to the power grid.

5. The method of claim 1 , further comprising: analyzing influence of operations for managing power consumption for the at least one consumer on power distribution of the power grid; and

updating the at least one power consumption rule to maintain power distribution of the power grid below a first predefined threshold.

6. The method of claim 5 , wherein the first predefined threshold is based on power consumption data from consumers that are geographically adjacent to the at least one consumer.

7. The method of claim 1 , wherein the machine learning algorithm comprises a decision tree generated based on a consumer feedback loop.

8. The method of claim 1 , further comprising:

analyzing the forecasted data to calculate at least one possible scenario; determining at least one action plan for each calculated scenario; determining at least one action strategy for each determined action plan; and

determining a single optimal scenario based on the determined at least one action strategy.

9. The method of claim 8 , wherein the at least one action plan is deterministic.

10. The method of claim 8 , wherein the at least one action strategy is conditional.

11. The method of claim 8 , wherein the single optimal scenario is determined based on the at least one power consumption rule.

12. The method of claim 8 , wherein the single optimal scenario is determined based on at least one of hidden Markov model and a Monte-Carlo evaluator.

13. A system for managing power distribution in an electrical power grid, wherein the power grid comprises at least one power storage, the system comprising:

at least one power consumption meter connected to the power grid; and

a processor, coupled to the at least one power consumption meter, and configured to:

receive at least one power consumption rule from at least one consumer of the power grid;

analyze power consumption data from at least one power consumption meter, wherein the received power consumption data corresponds to consumption of the at least one consumer;

apply the at least one power consumption rule on the analyzed power consumption data, based on forecasted data wherein the forecasted data is selected from the group consisting of: forecasted power consumption—forecasted power production, and forecasted energy prices; and

manage power consumption for the at least one consumer, based on the result of the at least one power consumption rule, and also based on a power capacity status of the at least one power storage, wherein the result of the at least one power consumption rule is calculated based on a machine learning algorithm configured to increase power distribution of the power grid towards a second predefined threshold.

14. The system of claim 13 , wherein for the operation of power consumption management the processor is configured to carry out at least one of: allocate power resources to the at least one power storage, retrieve power from the power grid, consume power from the at least one power storage instead of the power grid, and reallocate power resources to a different consumer of the power grid.

15. The system of claim 13 wherein the power grid further comprises at least one power production facility, and wherein for the operation of power consumption management the processor is configured to carry out at least one of: allocate power resources from the at least one power production facility to the at least one power storage, and allocate power resources from the at least one power production facility to the power grid.

16. A method of managing power distribution of at least one electrical power production facility coupled to at least one power storage, the method comprising:

receiving at least one power consumption rule from at least one consumer of the at least one electrical power production facility;

analyzing power consumption data from at least one power consumption meter connected to the at least one electrical power production facility, wherein the received power consumption data corresponds to consumption of the at least one consumer;

applying the at least one power consumption rule on the analyzed power consumption data, based on forecasted data wherein the forecasted data is selected from the group consisting of: forecasted power consumption—forecasted power production, and forecasted energy prices; and

managing power consumption for the at least one consumer, based on the result of the at least one power consumption rule, and also based on a power capacity status of the at least one power storage, wherein the result of the at least one power consumption rule is calculated based on a machine learning algorithm configured to increase power distribution of the power grid towards a second predefined threshold.

17. The method of claim 16 , wherein the operation of power consumption management is selected from the group consisting of: allocating power resources from the at least one power production facility to the at least one power storage, consuming power from the at least one power storage, and reallocating power resources to a different consumer of the power grid.

18. The method of claim 16 , further comprising:

analyzing the forecasted data to calculate at least one possible scenario; determining at least one action plan for each calculated scenario; determining at least one action strategy for each determined action plan; and

determining a single optimal scenario based on the determined at least one action strategy.

19. The method of claim 18 , wherein the single optimal scenario is determined based on at least one of hidden Markov model and a Monte-Carlo evaluator.