Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

New energy electricity price prediction method and system

A forecasting method and new energy technology, applied in forecasting, information technology support systems, electrical components, etc., can solve the company's problems such as reduced profits, losses, and low forecasting accuracy, and achieve the goals of saving workload, ensuring profits, and ensuring reliability. Effect

Pending Publication Date: 2021-05-28
NANJING HUADUN ELECTRIC POWER INFORMATION SAFETY EVALUATION CO LTD
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to solve the problem in the prior art that the company's benefit is reduced or even lost due to the low prediction accuracy of the electricity market price in the prior art, it provides a new energy electricity price prediction method and system. The method or system obtains the bidding space and divides the data time Points, match the historical bidding space according to the time point, and then obtain electricity price information to form a day-ahead market price curve forecast, and improve the control ability of new energy in the market

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
  • New energy electricity price prediction method and system
  • New energy electricity price prediction method and system
  • New energy electricity price prediction method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0062] The present invention is a new energy electricity price prediction method, comprising the following steps:

[0063] A new energy electricity price prediction method, comprising the following steps:

[0064] Step 1: Obtain the supply and demand data for the date to be predicted in the market where the new energy company is located. The supply and demand data include thermal power, hydropower, new energy and other power sources. Select the supply and demand data of different working days and holidays, use the data as the data source, set the minimum value of thermal power in the data source as A, the adjustable value of thermal power as B, the planned value of hydropower generation as C, and the planned value of new energy forecasting Set it as D, set the value of other power types as E, and set the load space of the entire market as M.

[0065] Divide a day into 96 time points, obtain the supply and demand data of 96 time points in a day to form a supply and demand matr...

Embodiment 2

[0109] A new energy electricity price prediction system in the present invention is used to implement the new energy electricity price prediction method in Embodiment 1, including

[0110] Supply and demand matrix acquisition module: acquire the supply and demand data of each power supply type, and obtain the supply and demand matrix L according to the supply and demand data;

[0111] Matrix correction module: perform weighted correction on the supply and demand matrix L to obtain a new supply and demand matrix N

[0112] Bidding space calculation module: calculate the bidding space according to the new supply and demand matrix N;

[0113] Electricity price prediction module: match the historical bidding space according to the bidding space, and obtain the forecasted electricity price

[0114] Classify the historical market electricity price data according to the time points. The classification rules are: according to the season and the time point of the day; first obtain the...

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 new energy electricity price prediction method and system. The method comprises the following steps: obtaining a supply and demand matrix L; performing weighted correction on the supply and demand matrix L to obtain a new supply and demand matrix N; obtaining a bidding space according to the new supply and demand matrix N; matching the bidding space with a historical bidding space to obtain a predicted electricity price; classifying the historical market electricity price data according to time points, wherein the classification rule is according to the time points of the seasons and the current day; the method comprises the steps of firstly obtaining the category of a to-be-matched bidding space, and then performing matching in a historical bidding space of the category; and matching the bidding spaces of other time points of one day in sequence to obtain predicted electricity price information of one day. According to the method or the system, the bidding space is obtained, the time points are divided for the data, the historical bidding space is matched according to the belonging time points, then the electricity price information is obtained to form day-ahead market price curve prediction, and the control capability of new energy in the market is improved.

Description

technical field [0001] The present invention relates to a prediction method and system, in particular to a new energy electricity price prediction method and system. Background technique [0002] In the electricity spot market, the biggest problem for new energy power generation companies represented by wind power is the uncontrollability of power generation performance. First of all, the volatility of its own power generation curve will increase the risks faced in the spot market. Taking Gansu Province as an example, Gansu Province has a relatively high proportion of clean energy, and its output volatility is one of the most important factors affecting market prices. , Judging from the current price situation in the spot market in Gansu Province, affected by the output of new energy, the market price presents a cliff-like curve. When the generation of new energy is booming, the output of thermal power units is reduced. When the output of new energy is tight, the output of ...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q30/02G06Q50/06G06F17/16H02J3/00
CPCG06F17/16G06Q10/04G06Q30/0283G06Q50/06H02J3/008Y04S10/50Y04S50/14
Inventor 余泽鑫雒雷雷吴昊武志军李鹏张耀李明哲
Owner NANJING HUADUN ELECTRIC POWER INFORMATION SAFETY EVALUATION CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap 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