An industry and region adaptive load scale measurement method

Abstract

The present application belongs to the technical field of power grid adaptive load scale measurement, and particularly relates to a kind of adaptive load scale measurement method of sub-industry and sub-region;Through step 1, collect the basic data of power grid electricity load in each region of measurement region;Step 2, the price sensitive industry of each region in the measurement region is screened;Step 3, the peak period of power grid electricity in each region in the measurement region and the comparison of time-of-use electricity price in each period;Step 4, the adaptive load regulation capacity of each region industry in the measurement region is measured;Step 5, the adaptive load scale of the measurement region and each region thereof is measured;It can be judged whether the industry has lifted the load in the peak period of electricity consumption, which helps to screen demand response applications;It can lock the industry load with strong regulation capacity and large scale, and ensure the smooth implementation of demand response through targeted publicity and focus;It can evaluate the total and sub-region response scale of a region, which helps to reasonably develop annual response plan.

Description

Technical Field

[0001] This invention belongs to the field of adaptive load scale calculation technology for power grids, and specifically relates to an adaptive load scale calculation method that can be applied to different industries and regions. Background Technology

[0002] Demand response is an adaptive behavior in which users adjust their electricity load in response to economic signals, used to shift 3% to 5% of peak load. Generally, a single response lasts no more than 2 hours, primarily involving industrial and commercial users. Electricity users change their inherent electricity consumption patterns based on price signals or incentives, reducing (or increasing) electricity consumption, thereby promoting power supply and demand balance, maintaining system reliability, and improving system operating efficiency. Due to differences in production processes and procedures, different industries have different load characteristics and response capabilities. The issue of large contracted reserve volumes but small actual response scales may be due to the industry's insensitivity to price signals, or because its electricity load is already low during peak grid periods. By assessing the adaptive adjustment capabilities of different industries, it is possible to determine whether the industry has increased its load during peak periods, which helps in screening demand response applications. It can identify industries with strong adjustment capabilities and large scale, ensuring smooth implementation of demand response through targeted promotion and focused attention. It can also assess the overall and regional response scale of a region, helping to rationally formulate annual response plans. Therefore, considering the elasticity of user electricity prices, it is necessary to propose a method for calculating the adaptive load scale of different industries and regions during periods of high grid load. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for calculating the adaptive load scale of the power grid at high load moments by industry and region, which helps to screen demand response applications, ensures the smooth implementation of demand response, assesses the total and regional response scale of a region, and helps to rationally formulate annual response plans.

[0004] The objective of this invention is achieved as follows: a method for calculating adaptive load scale by industry and region, comprising the following steps:

[0005] Step 1: Collect and calculate basic data on power grid load in various regions within the area;

[0006] Step 2: Screen the electricity price-sensitive industries in each region within the measurement area;

[0007] Step 3: Calculate the peak electricity consumption periods of the power grid in different regions and compare the time-of-use electricity prices for each period;

[0008] Step 4: Calculate the adaptive load adjustment capacity of industries in various regions within the measurement area;

[0009] Step 5: Calculate the adaptive load scale of the measurement area and its various regions.

[0010] Step 1, which involves collecting and calculating basic data on the electricity load of the power grid in various regions within the area, includes:

[0011] Determine and statistically calculate the peak, off-peak, and valley periods of the current time-of-use electricity prices in various regions within the area;

[0012] Collect and statistically analyze 96 data points on the days with the highest power grid load during the peak load period for various industries in different regions within the area.

[0013] Step 2, which involves screening electricity price-sensitive industries in various regions within the measurement area, includes:

[0014] The average load of each industry during peak, flat, and valley price periods was calculated for each region within the measurement area. Industries that are more sensitive to electricity prices were screened by calculating the valley / flat and valley / peak load ratios α and β.

[0015] When both α and β are greater than 1, it indicates that the industry has a high load during the demand response period and possesses adjustment and effective load response capabilities; otherwise, it indicates that the industry has a low load during the demand response period and lacks adjustment and effective load response capabilities.

[0016] Step 3 involves calculating peak electricity consumption periods and comparing time-of-use electricity prices for different regions within the area, including:

[0017] Statistical analysis was conducted on electricity consumption data during periods of high load on the power grid in various regions within the measurement area to determine the peak electricity consumption periods for each region. The current time-of-use pricing policy for the measurement area was determined, including the peak coefficient for peak hours, the off-peak coefficient for off-peak hours, and the flat-peak coefficient for flat-peak hours. The peak electricity consumption periods and time-of-use prices for each period were compared among the regions within the measurement area.

[0018] Step 4, which calculates the adaptive load adjustment capacity of industries in various regions within the measurement area, includes:

[0019] Based on the execution duration of the demand response, the load increment of price-sensitive industries before and after the end of the evening peak period and the beginning of the evening flat period in various regions and industries within the region is calculated. The difference between the average load at the end of the evening peak period and the average load at the beginning of the flat period is the ability of the industry to adaptively adjust the load.

[0020] Step 5, which involves calculating the adaptive load scale of the measurement region and its various areas, includes:

[0021] Calculate the adaptive load scale within the region: it is the sum of the adaptive load scales of industries with adaptive adjustment capabilities within the region;

[0022] Calculate the adaptive load scale of each region within the measurement area: it is the sum of the adaptive load scale of industries with adaptive adjustment capabilities in the measurement area.

[0023] The beneficial effects of this invention are as follows: This invention provides a method for calculating adaptive load scale by industry and region. The method involves: Step 1, collecting basic data on power grid load in various regions within the calculation area; Step 2, screening price-sensitive industries in each region within the calculation area; Step 3, comparing peak electricity consumption periods and time-of-use electricity prices in each region within the calculation area; Step 4, calculating the adaptive load regulation capacity of industries in each region within the calculation area; and Step 5, calculating the adaptive load scale of the calculation area and its individual regions. This method can determine whether an industry has increased its load during peak electricity consumption periods, which helps in screening demand response applications; it can identify industries with strong regulation capacity and large scale, ensuring smooth implementation of demand response through targeted promotion and focused attention; and it can assess the overall and regional response scale of a region, which helps in the rational formulation of annual response plans. Attached Figure Description

[0024] Figure 1 This is a flowchart illustrating an industry-specific and region-specific adaptive load scale calculation method according to the present invention. Detailed Implementation

[0025] The present invention will now be further described with reference to the accompanying drawings.

[0026] like Figure 1 As shown, a method for calculating adaptive load scale by industry and region includes the following steps:

[0027] Step 1: Collect and calculate basic data on power grid load in various regions within the area;

[0028] Step 2: Screen the electricity price-sensitive industries in each region within the measurement area;

[0029] Step 3: Calculate the peak electricity consumption periods of the power grid in different regions and compare the time-of-use electricity prices for each period;

[0030] Step 4: Calculate the adaptive load adjustment capacity of industries in various regions within the measurement area;

[0031] Step 5: Calculate the adaptive load scale of the measurement area and its various regions.

[0032] Step 1, which involves collecting and calculating basic data on the electricity load of the power grid in various regions within the area, includes:

[0033] Determine and statistically calculate the peak, off-peak, and valley periods of the current time-of-use electricity prices in various regions within the area;

[0034] Collect and statistically analyze 96 data points on the days with the highest power grid load in various industries in different regions (generally from June to August).

[0035] Step 2, which involves screening electricity price-sensitive industries in various regions within the measurement area, includes:

[0036] The average load of each industry during peak, flat, and valley price periods was calculated for each region within the measurement area. Industries that are more sensitive to electricity prices were screened by calculating the valley / flat and valley / peak load ratios α and β.

[0037] When both α and β are greater than 1, it indicates that the industry has a high load during the demand response period and has the ability to regulate and respond to loads effectively. The load of these industries is higher during the off-peak electricity price period than during the peak electricity price period, and the load during the flat electricity price period is also higher than the peak electricity price period. Otherwise, it indicates that the industry has a low load during the demand response period and does not have the ability to regulate and respond to loads effectively.

[0038] The electricity consumption industries in the region include 41 industries across 8 service sectors, such as mining, manufacturing (31 sub-sectors), construction, transportation / warehousing and postal services.

[0039] Step 3 involves calculating peak electricity consumption periods and comparing time-of-use electricity prices for different regions within the area, including:

[0040] Statistical analysis was conducted on electricity consumption data during periods of high power grid load in various regions within the measurement area to determine the peak electricity consumption periods for each region. High power grid load periods are generally concentrated between June and August, with peak consumption mainly occurring during the summer evening peak, typically around 10:00 PM. The current time-of-use pricing policy for the measurement area was determined, including peak coefficients for peak hours, off-peak coefficients for off-peak hours, and flat-peak coefficients for flat-peak hours. For example, in a certain region, peak hours are 8:00-12:00 and 18:00-24:00. 2:00, peak coefficient 1.57; off-peak period 0:00-8:00, off-peak coefficient 0.5; flat period 12:00-18:00, 22:00-24:00, flat period coefficient 1.0; based on the above information, the peak electricity consumption periods and time-of-use electricity prices of various regions within the calculated area can be compared; after 22:00, the electricity price changes from peak to flat, and the load of electricity price-sensitive industries increases. This part of the load is the load that is adaptively adjusted by optimizing the peak and off-peak electricity price periods.

[0041] Step 4, which calculates the adaptive load adjustment capacity of industries in various regions within the measurement area, includes:

[0042] Based on the execution duration of the demand response (approximately 2 hours), calculate the load increment of electricity price-sensitive industries before and after the end of the evening peak period and the start of the evening flat period (e.g., 22:00 in a certain region mentioned above). The difference between the average load at the end of the evening peak period and the average load at the beginning of the flat period (i.e., the difference between the average load from 22:00 to 24:00 and the average load from 20:00 to 22:00) is the industry's ability to adaptively adjust its load.

[0043] Step 5, which involves calculating the adaptive load scale of the measurement region and its various areas, includes:

[0044] Calculate the adaptive load scale within the region: it is the sum of the adaptive load scales of industries with adaptive adjustment capabilities within the region;

[0045] Calculate the adaptive load scale of each region within the measurement area: it is the sum of the adaptive load scale of industries with adaptive adjustment capabilities in the measurement area.

[0046] By ranking the adaptive load regulation capabilities, it is possible to identify power-consuming industries with greater regulation capabilities, which helps load aggregators to focus on them and actively organize their participation in power demand response.

[0047] Demand response centers can leverage the region's adaptive load regulation capabilities to formulate annual electricity demand response scales and regional breakdown plans, which helps ensure the smooth implementation of electricity demand response and more effectively addresses regional power imbalances.

[0048] This invention provides a method for calculating adaptive load scale by industry and region. The method involves the following steps: Step 1, collecting basic data on power grid load in various regions within the calculation area; Step 2, screening price-sensitive industries in each region within the calculation area; Step 3, comparing peak electricity consumption periods and time-of-use electricity prices in each region within the calculation area; Step 4, calculating the adaptive load regulation capacity of industries in each region within the calculation area; and Step 5, calculating the adaptive load scale of the calculation area and its individual regions. This method can determine whether an industry has increased its load during peak electricity consumption periods, which helps in screening demand response applications; it can identify industries with strong regulation capacity and large loads, ensuring smooth implementation of demand response through targeted promotion and focused attention; and it can assess the overall and regional response scale of a region, which helps in the rational formulation of annual response plans.

Claims

1. A method for calculating adaptive load scale by industry and region, characterized in that... It includes the following steps: Step 1: Collect and calculate basic data on power grid load in various regions within the area; Step 2: Screen the electricity price-sensitive industries in each region within the measurement area; Step 3: Calculate the peak electricity consumption periods of the power grid in different regions and compare the time-of-use electricity prices for each period; Step 4: Calculate the adaptive load adjustment capacity of industries in various regions within the measurement area; Step 5: Calculate the adaptive load scale of the measurement area and its various regions; Step 1, which involves collecting and calculating basic data on the electricity load of the power grid in various regions within the area, includes: Determine and statistically calculate the peak, off-peak, and valley periods of the current time-of-use electricity prices in various regions within the area; Collect and statistically analyze 96 data points on the days with the highest power grid load during the peak load period for various industries in different regions within the area. Step 2, which involves screening electricity price-sensitive industries in various regions within the measurement area, includes: The average load of each industry during peak, flat, and valley price periods was calculated for each region within the measurement area. Industries that are more sensitive to electricity prices were screened by calculating the valley / flat and valley / peak load ratios α and β. When both α and β are greater than 1, it indicates that the industry has a high load during the demand response period and has the ability to adjust and respond to loads; otherwise, it indicates that the industry has a low load during the demand response period and does not have the ability to adjust and respond to loads. Step 4, which calculates the adaptive load adjustment capacity of industries in various regions within the measurement area, includes: Based on the execution duration of demand response, the load increment of price-sensitive industries before and after the end of the evening peak period and the start of the evening flat period in each region and industry is calculated. The difference between the average load at the end of the evening peak period and the average load at the beginning of the flat period is the ability of the industry to adaptively adjust the load.

2. The method for calculating adaptive load scale by industry and region as described in claim 1, characterized in that, Step 3 involves calculating peak electricity consumption periods and comparing time-of-use electricity prices for different regions within the area, including: Statistical analysis was conducted on electricity consumption data during periods of high load on the power grid in various regions within the measurement area to determine the peak electricity consumption periods for each region. The current time-of-use pricing policy for the measurement area was determined, including the peak coefficient for peak hours, the off-peak coefficient for off-peak hours, and the flat-peak coefficient for flat-peak hours. The peak electricity consumption periods and time-of-use prices for each period were compared among the regions within the measurement area.

3. The method of claim 1, wherein the method is characterized by, Step 5, which involves calculating the adaptive load scale of the measurement region and its various areas, includes: Calculate the adaptive load scale within the region: it is the sum of the adaptive load scales of industries with adaptive adjustment capabilities within the region; Calculate the adaptive load scale of each region within the measurement area: it is the sum of the adaptive load scale of industries with adaptive adjustment capabilities in the measurement area.

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