Frequency modulation capacity time-sharing optimization method based on conditional probability

A technology of frequency modulation capacity and optimization method, which is applied to electrical components, reduction/prevention of power oscillation, AC network circuits, etc. It can solve the problem that the calculation results cannot truly reflect the frequency modulation capacity demand of the power system, the calculation of the frequency modulation capacity demand is complicated, and the applicability is reduced. question

Active Publication Date: 2019-09-17
TSINGHUA UNIV +2
View PDF8 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In recent years, the rapid growth of renewable energy, the uncertainty and volatility of its output has increased the difficulty of power system active power balance, and also made the calculation of frequency regulation capacity requirements more complicated
[0004] At present, in the actual power system, the demand for frequency regulation capacity is mostly fixed at each time period according to experience. However, the applicability of

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Frequency modulation capacity time-sharing optimization method based on conditional probability
  • Frequency modulation capacity time-sharing optimization method based on conditional probability
  • Frequency modulation capacity time-sharing optimization method based on conditional probability

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0058] The present invention proposes a time-period optimization method for frequency modulation capacity based on conditional probability, which will be further described in detail below in conjunction with specific embodiments.

[0059] The present invention proposes a conditional probability-based frequency modulation capacity optimization method by time period, including the following steps:

[0060] 1) The historical data collection, processing and screening stage; the specific steps are as follows:

[0061] 1-1) Collect the historical data of the past N years (N≥1; this embodiment is 3 years) in the automatic generation control (AGC) control area, the historical data includes: the total load power L per minute, the total load power per minute Renewable energy power generation G r , A for each AGC assessment period (15min is a period) 2 Indicators, the average upward adjustment capacity R of each AGC assessment period up and the average downregulated capacity R dn . ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a frequency modulation capacity time-sharing optimization method based on conditional probability, and belongs to the field of power system automatic power generation control of. The method comprises the steps of firstly collecting the historical data of an AGC control area, and screening a sample composed of the historical data according to an AGC assessment period; constructing and training an extreme learning machine model predicted by a net load standard deviation section to obtain a trained extreme learning machine model; in an application phase, outputting, by the trained extreme learning machine model, the net load standard deviation section predicted values corresponding to the respective time periods on a certain day in the future, and according to the screened data of each AGC assessment period, calculating frequency modulation performance standard-reaching probabilities corresponding to the up-regulation capacity and the down-regulation capacity of the prediction time period, and obtaining the up-regulation reserve capacity optimization result and the down-regulation capacity reserve capacity optimization result of this time period. The method can correct the calculation result of a frequency modulation capacity demand according to a frequency modulation score, and the obtained result can truly reflect the frequency modulation capacity demand of a power system.

Description

technical field [0001] The invention belongs to the field of automatic power generation control of electric power systems, and in particular relates to a conditional probability-based method for optimizing frequency modulation capacity by time period. Background technique [0002] Automatic generation control (AGC) is of great significance to balance the active power deviation of the power system and maintain the stability of the system frequency. The normal operation of the AGC system needs sufficient frequency regulation reserve as support, but too much frequency regulation reserve will cause high operating costs of the power grid. Therefore, accurate calculation of power system frequency regulation capacity requirements is of great significance for maintaining grid frequency stability and reducing grid operating costs. [0003] With the rapid growth of renewable energy in recent years, the uncertainty and volatility of its output have increased the difficulty of power sy...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): H02J3/24H02J3/46
CPCH02J3/24H02J3/46H02J2203/20
Inventor 胡泽春刘礼恺宁剑江长明张哲
Owner TSINGHUA UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products