Electric water heater cluster power short-term interval prediction method considering climbing characteristics and prediction interval optimization
An electric water heater and interval optimization technology, which is applied in forecasting, instrumentation, data processing applications, etc., can solve the problems of weak RVM robustness and low prediction accuracy, achieve effective load volatility, high prediction accuracy, and improve interval prediction performance Effect
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[0079] The embodiments are described in detail below in conjunction with the accompanying drawings, and the embodiments do not limit the present invention.
[0080] 1. Analysis of ramp-like characteristics of EWHs cluster power
[0081] Such as figure 1 As shown, the load demand of EWHs is directly affected by the hot water usage of users, and has obvious time characteristics. During the peak and valley periods of hot water usage, the load fluctuates greatly and has obvious mutation characteristics. Taking 15min as the time scale, the analysis is carried out with the determination criterion of the climbing event defined by the formula (1). When P(τ+Δτ)-P(τ)>0, the climbing event will occur; P(τ+Δτ) When -P(τ)<0, a downhill climb event will occur.
[0082] The determination criterion of the climbing event defined by formula (2) is used to identify the long-term scale power of EWHs clusters for a long time. Grab the EWHs cluster power data of an intelligent community from Ju...
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