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User power consumption prediction method

A forecasting method and technology of electricity consumption, applied in forecasting, data processing applications, instruments, etc., can solve the problems of not considering users and cannot reflect the actual change trend of electricity well, and achieve the effect of avoiding waste of resources

Pending Publication Date: 2019-09-27
SHANGHAI MUNICIPAL ELECTRIC POWER CO +1
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Problems solved by technology

However, the existing research on electricity demand of residents does not directly deconstruct and analyze power big data, and does not consider the influence of factors such as user attributes and external conditions on electricity demand, that is, how the probability of different electricity demand of users varies with the above variables. Therefore, the obtained power demand probability results cannot reflect the actual change trend of electricity well.

Method used

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Embodiment Construction

[0031] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. Apparently, the described embodiments are some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0032] The finite mixture model assumes that the observed sample is a mixture of multiple distributions. Specifically, the system F is composed of K distributions, where K is determined by data-driven judgment. The Gaussian mixture distribution is a mixture distribution form composed of K Gaussian distributions, and its expression is as follows:

[0033]

[0034] Among them, F(K,λ,μ,σ) is the observed mixed distribution, f(μ i ,σ i ) is the component Gaussian distribution function, λ i is the probability of occurrence of each ...

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Abstract

The invention relates to a user power consumption prediction method, which comprises the following steps of 1) establishing a limited hybrid model with adjoint variables by combining the influence of the factors, such as user attributes, external conditions, etc., on the power consumption requirements; 2) according to the finite mixing model established in the step 1), deconstructing power utilization data of users in a certain region; 3) performing deconstruction on the total power consumption of the users in a certain region, obtaining an expected power consumption value, and completing the prediction of the power consumption of the users; and 4) detecting the correctness and the stability of the deconstruction of the total power consumption in the step 3) by using the relative error. Compared with the prior art, the method has the advantages that the power consumption demand probabilities of different users can be calculated through the adjoint variables, the prediction of the power consumption demand of the user in the auxiliary area is facilitated, and the actual change trend of the power consumption can be effectively reflected.

Description

technical field [0001] The invention relates to the technical field of power market demand forecasting and analysis, in particular to a method for forecasting user electricity consumption. Background technique [0002] Electric energy is widely used in industry, agriculture, enterprises and institutions, and people's daily life, and is an indispensable energy source for the national economy and people's lives. However, while we are enjoying the convenience and light that electricity brings us, we are also wasting electricity all the time. For the research and analysis of users' electricity demand, in the prior art, the per capita disposable income, the user's electricity price and the previous period's per capita electricity consumption are selected as factors, and an error correction prediction model for the residents' living electricity demand in the current period is established; Based on the panel data model, using the self-calculated comprehensive electrical appliance ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06K9/62
CPCG06Q10/04G06Q50/06G06F18/2415
Inventor 苏运吴力波周阳马戎施政昱陈伟郭乃网田英杰瞿海妮张琪祁时志雄宋岩庞天宇沈泉江
Owner SHANGHAI MUNICIPAL ELECTRIC POWER CO
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