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A method for quantitatively evaluating time-varying capacity of decentralized electric heating load based on measured data and its modeling system

A technology of measured data and load modeling, which is applied in the field of electric heating, can solve the problems that the accuracy is difficult to meet the quantitative evaluation of electric heating load time-shift capability, it is difficult to accurately reflect the operating characteristics of electric heating load, and the model error is large.

Active Publication Date: 2019-03-26
NORTHEAST DIANLI UNIVERSITY +1
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Problems solved by technology

However, in practical engineering applications, the electric heating load model directly uses the first-order equivalent thermodynamic model of air-conditioning load, and the air-conditioning load is concentrated in the southern region to meet the cooling demand in summer. There is a huge difference between th

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  • A method for quantitatively evaluating time-varying capacity of decentralized electric heating load based on measured data and its modeling system
  • A method for quantitatively evaluating time-varying capacity of decentralized electric heating load based on measured data and its modeling system
  • A method for quantitatively evaluating time-varying capacity of decentralized electric heating load based on measured data and its modeling system

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Embodiment Construction

[0060] Below in conjunction with embodiment the present invention is further described.

[0061] see Figure 1-Figure 2 , Embodiment 1, this embodiment is a quantitative evaluation method for the time-shift capability of distributed electric heating load based on measured data, including obtaining time series data of the operating state of the electric heating system, constructing a simplified second-order model of electric heating load, and constructing a model error margin function, to solve its time-shifting ability, the details are as follows:

[0062] 1) Obtain the time series data of the operating status of the electric heating system;

[0063] ①Using ΔT as the sampling period, measure and store the indoor temperature T in the period of 1,2,...,s...,Sc in-m , outside temperature T out-m , power P m The time series data of each period, the total number of data groups (or total time steps) in each period is l 1 , l 2 ,...,l s ...,l Sc , where Sc is the current peri...

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Abstract

The invention relates to a method for quantitatively evaluating time-varying capacity of decentralized electric heating load based on measured data and its modeling system, It is characterized in thatthe electric heating load modeling system is constructed to obtain the time series data of the electric heating system in the past period of time, and the simplified second-order model of the electric heating load and the error margin function of the model are fitted by the cloud computing system based on the measured time series data, and the time-shifting ability of the electric heating systemis solved accordingly. The basic principle of time-shifting capacity quantitative evaluation of electric heating load using measured parameters is determined, and the corresponding detailed computer-realizable evaluation steps and system architecture are proposed. The invention can provide an accurate and practical electric heating load dispatching model, and improves the accuracy and practicability of the electric heating load time-shifting capacity.

Description

technical field [0001] The invention belongs to electric heating, and relates to a quantitative evaluation method and a modeling system for distributed electric heating load time shift capability based on measured data. Background technique [0002] With the continuous advancement of clean heating, the proportion of electric heating in the grid in northern regions has increased year by year. Taking Changchun City as an example, in 2017, the cumulative installed capacity of electric heating was 290MW, and the heating area was 3.17 million square meters, accounting for 3.08% of the city's total heating, and showing a rapid development trend. Among them, distributed electric heating occupies an important proportion in the electric heating load. The electric heating load has thermal inertia, and its regulation resources can be gathered without affecting the user's comfort, which is of great value in improving the safe and economical operation of a high-proportion renewable ener...

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/06F24D19/10
CPCG06Q10/0639G06Q10/067G06Q50/06F24D19/1096
Inventor 穆钢杨玉龙严干贵刘劲松韩月刘芮彤杨滢璇
Owner NORTHEAST DIANLI UNIVERSITY
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