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.
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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, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35)
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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.
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Specification