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Pretest system for market price of electric power

A power market and price forecasting technology, applied in information technology support systems, commerce, instruments, etc., can solve problems such as difficult to predict power transaction prices, difficult to predict strategic bidding, etc., and achieve the effect of simple power transaction prices

Inactive Publication Date: 2007-05-09
HITACHI LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

This invention allows for accurate prediction over an electrical charge purchase based on its cost-effectiveness rather than just how much it costs or makes them worse by doing things that affect their performance.

Problems solved by technology

The technical problem addressed by this patented technology relates to accurately estimating electrical energy consumption during peak hours without overloading communication networks that are currently used to transmit excessive amounts of generated heat from generators into the grid. This issue becomes even more challenged because customers have increasingly demanded higher levels of flexibility than ever before.

Method used

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  • Pretest system for market price of electric power
  • Pretest system for market price of electric power
  • Pretest system for market price of electric power

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0033] FIG. 1 shows a functional block diagram of Embodiment 1 of the present invention. The functional blocks of Embodiment 1 of the present invention are composed of a demand forecasting device 101 , a transmission line data storage device 102 , a system congestion judging device 103 , and a power market price forecasting device 104 .

[0034] The demand forecasting device executes the demand curve of the delivery target day in each bidding area according to the time zone of the traded commodity in the exchange. It needs to be expected to be implemented according to the mode of JP-A-5-38051.

[0035] In addition, as another method of forecasting demand, the maximum demand is first calculated according to Ishii's "Development of Large Demand Forecasting Support System (1) and (2)" at the Electric Power and Energy Section Meeting of the Electric Society in 2018.

[0036] Next, the estimated demand curves of days with similar weather conditions on the most recent day are searc...

Embodiment 2

[0052] Modifications of this embodiment will be described below. Fig. 5 shows a functional block diagram of Embodiment 2 of the present invention. The functional blocks of Embodiment 2 of the present invention are composed of a demand forecasting device 101 , a transmission line data storage device 102 , a power transaction data storage device 201 , a system congestion determination device 103 , and a power market price prediction device 104 .

[0053] The agreed price of each traded product in each power bidding area in the past is stored in the power trade storage device. In addition, the agreed amount of each traded product in each electric power bidding area cut off due to past congestion is also stored.

[0054] In addition, as a system congestion judging device, after one consolidation as shown in Figure 2, after generating the data matrix of Table 1 in Figure 4, by adding the intensive power bidding area adjacent to the intensive transmission line 1 in the data matrix ...

Embodiment 3

[0060] Embodiment 3 of the present invention will be described below. Fig. 7 shows a functional block diagram of Embodiment 3 of the present invention. The functional blocks of the present invention are composed of a weather forecast data storage device 301 , a calendar data storage device 302 , a transmission line data storage device 102 , a system congestion determination device 103 , and a power market price prediction device 104 .

[0061] The weather forecast data storage device stores the delivery object date, past forecast weather, forecast minimum and maximum temperature, and forecast precipitation probability of representative locations in each power bidding area.

[0062] Date type (weekdays, Saturdays, Sundays, special days) data of year, month and day are stored in the calendar data storage device.

[0063] In the system congestion judging device, as shown in FIG. 2, after the first consolidation, the empty capacity of the transmission lines for each intensive tra...

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Abstract

PROBLEM TO BE SOLVED: To provide highly precise market price prediction data under the consideration of the congestion of a transmission line by using a statistical method from the past data concerning a support system for performing the transaction of power trade. ŽSOLUTION: This power market price prediction system predicts the congestion of a transmission line from the data of a demand prediction data storage device predicting the power demand of each bid area and the data of a transmission line data storage device connecting each of bid areas, and predicts a power market price by switching a model according to the result. Ž

Description

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Claims

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Application Information

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Owner HITACHI LTD
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