Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Bidding strategy for electricity purchase

A technology of electricity price and strategy, applied in market forecasting, instruments, data processing applications, etc., can solve the problems of scientificity and accuracy that cannot satisfy users, affect the transaction situation of the electricity market, and affect the efficiency of the allocation of electricity resources in the electricity market, etc. Improve accuracy and scientific, high-accuracy effects

Inactive Publication Date: 2017-05-17
YUNNAN POWER GRID CO LTD ELECTRIC POWER RES INST
View PDF0 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] As co-participants in the power market, the bidding strategies of the power generation side and the user side will affect the transaction situation of the power market, thereby affecting the allocation efficiency of power resources in the power market
At present, there are few studies on user-side electricity price forecasting. Existing user-side bidding strategies are usually based on users' predictions of short-term electricity prices, and the scientificity and accuracy cannot meet the requirements of users to participate in grid bidding.

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
  • Bidding strategy for electricity purchase
  • Bidding strategy for electricity purchase
  • Bidding strategy for electricity purchase

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0040] Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with aspects of the invention as recited in the appended claims.

[0041] figure 1 is a flow chart of an electricity purchase bidding strategy according to an exemplary embodiment, as shown in figure 1 As shown, the electricity purchase bidding strategy provided by the embodiment of the present invention includes:

[0042] S110: Using the gray relational analysis method to select similar days of the electricity price day to be predicted.

[0043] Factors tha...

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 relates to a bidding strategy for electricity purchase. The strategy comprises that a day similar to an electricity-price-to-predict day is selected via a grey correlation analysis method; according to the electricity price of the similar day, the electricity price of the electricity-price-to-predict day is predicted via a multivariate linear regression method; according to historical electricity prices of the similar days, the predicted electricity price of the similar day is obtained via the multivariate linear regression method, and a relative error probability density distribution function of electricity price prediction is established according to the historical and predicted electricity price; and according to the relative error probability density distribution function and the electricity cost of the electricity-price-to-predict day, bidding for electricity purchase is carried out via particle swarm optimization. According to embodiments of the invention, bidding for electricity purchase is carried out by utilizing the electricity cost of the day similar to the electricity-price-to-predict day, and the accuracy is high; and the established relative error probability density distribution function is used, and the electricity price of the electricity-price-to-predict day is adjusted via particle swarm optimization, so that the electricity purchasing price of the electricity-price-to-predict day is obtained, and bidding for electricity purchase of users is more accurate and more scientific.

Description

technical field [0001] The invention relates to the technical field of power market transactions, in particular to a bidding strategy for power purchases. Background technique [0002] The market is the most effective way to allocate resources, and electric energy, as a kind of power resource, has a high allocation efficiency in the electricity market environment. In the electricity market, the price is the core of the whole market. The fluctuation of electricity price directly affects the flow and distribution of electricity resources in the market. The electricity transaction through bidding has become a new model of my country's electricity industry. [0003] The bidding in the electric power industry includes the bidding on the power generation side and the bidding on the power consumption side. At present, the bidding in the electric power industry is mainly the bidding on the generating side. Bidding on the power generation side refers to the bidding of power plants t...

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): G06Q30/02G06Q50/06
CPCG06Q30/0206G06Q50/06
Inventor 赵明李孟阳梁俊宇谢青阳李萍杨家全
Owner YUNNAN POWER GRID CO LTD ELECTRIC POWER RES INST
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
Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com