Very short term load prediction in an energy management system
First Claim
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1. A method of energy management and short term load prediction in a power system, comprising the steps of:
- dividing a time period into a plurality of sub-periods;
using a plurality of neural networks, each of the plurality of neural networks comprising a plurality of neurons to predict a short term load demand on the power system, the sub-periods being further divided into predicting intervals and assigning one of the plurality of neural networks to each of the plurality of sub-periods;
receiving historical load data and a short term load forecast (STLF) for a STLF interval which is greater than or equal to the largest prediction interval; and
using the output of each of the plurality of neural networks to predict the short term load demand in each predicting interval.
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Abstract
A method and system is provided for optimizing the performance of a power generation and distribution system by forecasting very short term load forecasts through the use of historical load data, demand patterns and short term load forecasts.
157 Citations
35 Claims
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1. A method of energy management and short term load prediction in a power system, comprising the steps of:
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dividing a time period into a plurality of sub-periods; using a plurality of neural networks, each of the plurality of neural networks comprising a plurality of neurons to predict a short term load demand on the power system, the sub-periods being further divided into predicting intervals and assigning one of the plurality of neural networks to each of the plurality of sub-periods; receiving historical load data and a short term load forecast (STLF) for a STLF interval which is greater than or equal to the largest prediction interval; and using the output of each of the plurality of neural networks to predict the short term load demand in each predicting interval. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17)
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18. A computer-readable medium having stored thereon instructions which when executed by a processor, cause the processor to perform the steps of:
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dividing a time period into a plurality of sub-periods; using a plurality of neural networks, each of the plurality of neural networks comprising a plurality of neurons to predict a short term load demand on the power system, the sub-periods being further divided into predicting intervals and assigning one of the plurality of neural networks to each of the plurality of sub-periods; receiving historical load data and a short term load forecast (STLF) for a STLF interval which is greater than or equal to the largest prediction interval; and using the output of each of the plurality of neural networks to predict the short term load demand in each predicting interval.
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19. A system for predicting short term loads within an energy management system of a power system, comprising:
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a processor for dividing a time period into a plurality of sub-periods and prediction intervals; and a plurality of neural networks, each of the plurality of neural networks comprising a plurality of neurons to predict a short term load demand on the power system, the sub-periods being further divided into predicting intervals and assigning one of the plurality of neural networks to each of the plurality of sub- periods; the processor, receiving and processing historical load data and a short term load forecast (STLF) for a STLF interval which is greater than or equal to the largest prediction interval; and using the output of each of the plurality of neural networks to predict the short term load demand in each predicting interval. - View Dependent Claims (20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35)
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Specification