A power consumption prediction apparatus, method, and non-transitory computer readable storage medium thereof are provided. The power consumption prediction apparatus receives a plurality of power consumption data of an appliance, wherein the power consumption data have a temporal sequence. Each power consumption datum includes a recorded status and a recorded time length, wherein each recorded status is one of a plurality operation statuses of the appliance. The power consumption prediction apparatus calculates an average operation time length of each operation status according to the recorded statuses and the recorded time lengths and calculates at least one transferring probability of each operation status according to the temporal sequence and the power consumption data. Each transferring probability is the probability of entering into a target status from a source status, wherein the source status is one of the operation statuses and the target status is one of the operation statuses.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A power consumption prediction apparatus, comprising: an interface, being configured to receive a plurality of first power consumption data of an appliance, wherein the appliance has a plurality of operation statuses, the first power consumption data have a first temporal sequence, each of the first power consumption data includes a first recorded status and a first recorded time length corresponding to the first recorded status, and each of the first recorded statuses is one of the operation statuses; and a processing unit, being electrically connected to the interface and configured to calculate an average operation time length of each of the operation statuses according to the first recorded statuses and the first recorded time lengths and calculate at least one transferring probability of each of the operation statuses according to the first temporal sequence and the first power consumption data, wherein each of the transferring probabilities is the probability of entering into a target status from a source status, the source status is one of the operation statuses, the target status is one of the operation statuses, and the source status is different from the target status. 2. The power consumption prediction apparatus as claimed in claim 1, wherein the processing unit calculates the average operation time length of each of the operation statuses by performing the following operations on each of the operation statuses: selecting at least one from the first power consumption data as at least one selected power consumption datum, wherein the first recorded status of each of the at least one selected power consumption datum is the operation status, averaging arithmetically the at least one first recorded time length corresponding to the at least one selected power consumption datum as the average operation time length of the operation status. 3. The power consumption prediction apparatus as claimed in claim 1, wherein the processing unit calculates the at least one transferring probability of each of the operation statuses by performing the following operations on each of the operation statuses: counting a first number of times of entering into the operation status according to the temporal sequence and the first recorded statuses, determining at least one transferring status that the appliance entered into after exiting the operation status according to the temporal sequence and the first recorded statuses, wherein each of the at least one transferring status is one of the operation statuses, counting at least one second number of times of entering into each of the at least one transferring status from the operation status according to the temporal sequence and the first recorded statuses, and dividing each of the at least one second number by the first number to obtain the at least one transferring probability of the operation status. 4. The power consumption prediction apparatus as claimed in claim 1, wherein the processing unit further determines a current status of the appliance at a current time point and a passed dwell time length under the current status according to a power feature datum of the appliance, the current status is one of the operation statuses, the processing unit further calculates a remaining dwell time according to an energy consumption prediction interval, the passed dwell time length, and the average operation time length corresponding to the current status, the processing unit further determines that the remaining dwell time is not less than zero, and the processing unit further calculates a predicted power consumption of the appliance from the current time point to a target time point according to a power of the current status, the remaining dwell time, the current time point, and the target time point. 5. The power consumption prediction apparatus as claimed in claim 1, wherein the processing unit further determines a current status of the appliance at a current time point and a passed dwell time length under the current status according to a power feature datum of the appliance, the current status is one of the operation statuses, the processing unit further calculates a remaining dwell time according to an energy consumption prediction interval, the passed dwell time length, and the average operation time length corresponding to the current status, the processing unit further determines that the remaining dwell time is less than zero, the processing unit further selects the at least one transferring probability of the current status as at least one selected transferring probability, and the processing unit further calculates a predicted power consumption of the appliance from the current time point to a target time point according to each of the at least one selected transferring probability, the average operation time length of the target status of each of the at least one selected transferring probability, at least one switching power of entering into the target status of each of the at least one selected transferring probability from the current status, the current time point, and the target time point. 6. The power consumption prediction apparatus as claimed in claim 1, wherein the processing unit further determines a current status of the appliance at a current time point and a passed dwell time length under the current status according to a power feature datum of the appliance, the current status is one of the operation statuses, the processing unit further calculates a remaining dwell time according to the passed dwell time length and the average operation time length corresponding to the current status, the processing unit further determines that the remaining dwell time is less than zero, the processing unit further calculates at least one selected transferring probability according to the at least one transferring probability of the current status, and the processing unit further calculates a predicted power consumption of the appliance from the current time point to a target time point according to each of the at least one selected transferring probability, the average operation time length of the target status of each of the at least one selected transferring probability, at least one switching power of entering into the target status of each of the at least one selected transferring probability from the current status, the current time point and the target time point. 7. The power consumption prediction apparatus as claimed in claim 1, wherein the interface further receives a plurality of second power consumption data of the appliance, the second power consumption data have a second temporal sequence, each of the second power consumption data includes a second recorded status and a second recorded time length corresponding to the second recorded status, and each of the second recorded statuses is one of the operation statuses, the processing unit further updates the average operation time length of each of the operation statuses according to the second recorded statuses and the second recorded time lengths, and updates the at least one transferring probability of each of the operation statuses according to the second temporal sequence and the second power consumption data. 8. A computer-implemented power consumption prediction method, comprising: (a) receiving a plurality of first power consumption data of an appliance, wherein the appliance has a plurality of operation statuses, the first power consumption data have a first temporal sequence, each of the first power consumption data includes a first recorded status and a first recorded time length corresponding to the first recorded status, and each of the first recorded statuses is one of the operation statuses; (b) calculating an average operation time length of each of the operation statuses according to the first recorded statuses and the first recorded time lengths; and (c) calculating at least one transferring probability of each of the operation statuses according to the first temporal sequence and the first power consumption data; wherein each of the transferring probabilities is the probability of entering into a target status from a source status, the source status is one of the operation statuses, the target status is one of the operation statuses, and the source status is different from the target status. 9. The power consumption prediction method as claimed in claim 8, wherein the average operation time length of each of the operation statuses is calculated by executing the following steps on each of the operation statuses in the step (c): selecting at least one from the first power consumption data as at least one selected power consumption datum, wherein the first recorded status of each of the at least one selected power consumption datum is the operation status; and averaging arithmetically the at least one first recorded time length corresponding to the at least one selected power consumption datum as the average operation time length of the operation status. 10. The power consumption prediction method as claimed in claim 8, wherein the at least one transferring probability of each of the operation statuses is calculated by executing the following steps on each of the operation statuses in the step (c): counting a first number of times of entering into the operation status according to the temporal sequence and the first recorded statuses; determining at least one transferring status that the appliance entered into after exiting the operation status according to the temporal sequence and the first recorded statuses, wherein each of the at least one transferring status is one of the operation statuses; counting at least one second number of times of entering into each of the at least one transferring status from the operation status according to the temporal sequence and the first recorded statuses; and dividing each of the at least one second number by the first number to obtain the at least one transferring probability of the operation status. 11. The power consumption prediction method as claimed in claim 8, further comprising: determining a current status of the appliance at a current time point and a passed dwell time length under the current status according to a power feature datum of the appliance, wherein the current status is one of the operation statuses; calculating a remaining dwell time according to an energy consumption prediction interval, the passed dwell time length and the average operation time length corresponding to the current status; determining that the remaining dwell time is not less than zero; and calculating a predicted power consumption of the appliance from the current time point to a target time point according to a power of the current status, the remaining dwell time, the current time point and the target time point. 12. The power consumption prediction method as claimed in claim 8, further comprising: determining a current status of the appliance at a current time point and a passed dwell time length under the current status according to a power feature datum of the appliance, wherein the current status is one of the operation statuses; calculating a remaining dwell time according to the passed dwell time length and the average operation time length corresponding to the current status; determining that the remaining dwell time is less than zero; selecting the at least one transferring probability of the current status as at least one selected transferring probability; and calculating a predicted power consumption of the appliance from the current time point to a target time point according to each of the at least one selected transferring probability, the average operation time length of the target status of each of the at least one selected transferring probability, at least one switching power of entering into the target status of each of the at least one selected transferring probability from the current status, the current time point and the target time point. 13. The power consumption prediction method as claimed in claim 8, further comprising: determining a current status of the appliance at a current time point and a passed dwell time length under the current status according to a power feature datum of the appliance, wherein the current status is one of the operation statuses; calculating a remaining dwell time according to an energy consumption prediction interval, the passed dwell time length and the average operation time length corresponding to the current status; determining that the remaining dwell time is less than zero; calculating at least one selected transferring probability according to the at least one transferring probability of the current status; and calculating a predicted power consumption of the appliance from the current time point to a target time point according to each of the at least one selected transferring probability, the average operation time length of the target status of each of the at least one selected transferring probability, at least one switching power of entering into the target status of each of the at least one selected transferring probability from the current status, the current time point and the target time point. 14. The power consumption prediction method as claimed in claim 8, further comprising: receiving a plurality of second power consumption data of the appliance, the second power consumption data have a second temporal sequence, each of the second power consumption data includes a second recorded status and a second recorded time length corresponding to the second recorded status, and each of the second recorded statuses is one of the operation statuses; updating the average operation time length of each of the operation statuses according to the second recorded statuses and the second recorded time lengths; and updating the at least one transferring probability of each of the operation statuses according to the second temporal sequence and the second power consumption data. 15. A non-transitory computer readable storage medium having a computer program stored therein, the computer program executes a power consumption prediction method after being loaded into an electronic apparatus, and the power consumption prediction method comprising: receiving, by the electronic apparatus, a plurality of power consumption data of an appliance, wherein the appliance has a plurality of operation statuses, the power consumption data have a temporal sequence, each of the power consumption data includes a recorded status and a recorded time length corresponding to the recorded status, and each of the recorded statuses is one of the operation statuses; calculating, by the electronic apparatus, an average operation time length of each of the operation statuses according to the recorded statuses and the recorded time lengths; and calculating, by the electronic apparatus, at least one transferring probability of each of the operation statuses according to the temporal sequence and the power consumption data; wherein each of the transferring probabilities is the probability of entering into a target status from a source status, the source status is one of the operation statuses, the target status is one of the operation statuses, and the source status is different from the target status. 16. The non-transitory computer readable storage medium as claimed in claim 15, wherein the power consumption prediction method further comprises: determining, by the electronic apparatus, a current status of the appliance at a current time point and a passed dwell time length under the current status according to a power feature datum of the appliance, wherein the current status is one of the operation statuses; calculating, by the electronic apparatus, a remaining dwell time according to the passed dwell time length and the average operation time length corresponding to the current status; determining, by the electronic apparatus, that the remaining dwell time is not less than zero; and calculating, by the electronic apparatus, a predicted power consumption of the appliance from the current time point to a target time point according to a power of the current status, the remaining dwell time, the current time point and the target time point.