A method and system for monitoring price risk in an electricity retail market

Abstract

A power retail market price risk monitoring method and system. The method comprises the following steps: acquiring provincial power retail market monthly operation data; constructing a retail market overall price monitoring index based on the power retail market monthly operation data; establishing a retail market price risk early warning model based on threshold dynamic correction to generate a list of retail electricity companies that need to be warned; and directing the disclosure of retail market overall price monitoring information to corresponding retail users. The present application realizes accurate quantitative evaluation of the overall price risk of the power retail market.

Description

Technical Field

[0001] This invention belongs to the field of electricity market monitoring, and specifically relates to a method and system for monitoring price risks in the electricity retail market. Background Technology

[0002] As a crucial component of the complete electricity market system, the electricity retail market primarily serves end-users and represents the final stage of electricity market reform. Currently, while the rules and regulations of the electricity retail market are gradually improving and the transaction volume is continuously expanding, the inherent information asymmetry in the electricity retail market makes it difficult to effectively transmit wholesale market price signals to retail users. Furthermore, the electricity retail market lacks effective methods for monitoring price risks.

[0003] Current methods for monitoring price risks in the electricity retail market suffer from the following shortcomings. Firstly, traditional monitoring methods use relatively fixed threshold values, failing to dynamically adapt to market changes and lacking in-depth analysis of contracted retail users of electricity sales companies. Secondly, indicators such as price volatility and price change rate are not included in the risk monitoring system, making it difficult to accurately assess the overall price risk in the retail market. Therefore, a method for monitoring price risks in the electricity retail market based on dynamically adjusted thresholds is urgently needed to address these issues. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method and system for monitoring price risks in the electricity retail market, thereby solving the technical problem of accurately quantifying and assessing the overall price risk in the electricity retail market.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution.

[0006] This invention first discloses a method for monitoring price risks in the electricity retail market, which includes the following steps: S1: Obtain monthly operational data of the provincial electricity retail market, including the average monthly settlement price of the retail market of electricity sales companies, the average monthly settlement volume of the retail market of electricity sales companies, and the average monthly settlement price of the retail users represented by the electricity sales companies; S2: Based on the monthly operating data of the electricity retail market, construct an overall price monitoring index for the retail market. The price monitoring index includes the monthly average settlement price of the retail market, the deviation of the monthly average settlement price of the electricity sales company in the retail market, the change rate of the monthly average settlement price of the retail market, and the monthly price volatility of the retail market. S3: Initialize the basic threshold of the overall price monitoring indicators of the retail market, establish a price risk early warning model for the retail market, and dynamically adjust the basic threshold according to the threshold trigger rate. S4: Based on the output of the retail market price risk early warning model, statistically analyze the distribution of settlement prices for retail users represented by electricity sales companies, form a list of retail users with high-priced contracts, and disclose the overall retail market price monitoring information to the corresponding retail users.

[0007] The present invention further includes the following preferred embodiments: Step S3 further includes: Set threshold ranges for monthly price volatility and monthly settlement average price change in the retail market, formulate a price risk early warning strategy for the retail market, and classify the risk warning levels into no warning required, yellow warning, and red warning; The system tracks and analyzes price risk warnings in the retail market for all 12 months of the year, and dynamically adjusts the base thresholds of monitoring indicators based on the number of times the thresholds are triggered.

[0008] Step S4 further includes: according to , , The distribution of settlement prices for retail users of electricity sales company i, based on three gradients, is statistically analyzed and output. The list of high-priced contracted retail users, and the deviation of the average monthly settlement price for retail users. ; Based on the list of high-priced contracted retail users, the average monthly settlement price in the retail market will be calculated. Average monthly settlement price of electricity sales company Distribution of settlement prices for electricity sales companies' agents and retail users.

[0009] In step S2, the retail market price monitoring indicators further include: (1) Average monthly settlement price in the retail market :

[0010] (2) Deviation of monthly average settlement price in the retail market of electricity sales company i :

[0011] (3) Monthly price volatility V in the retail market:

[0012] (4) Monthly settlement average price change rate R in the retail market

[0013] In the formula, This represents the average monthly settlement price in the retail market for the previous month.

[0014] The retail market price risk warning strategy in step S3 further includes: Set threshold ranges for monthly price volatility V and monthly settlement average price change rate R in the retail market, formulate a price risk early warning strategy for the retail market, and classify it into no warning required, yellow warning, and red warning. when When this occurs, it indicates that the electricity retail market price is highly stable and no early warning is needed; when or , When this occurs, it indicates that there are fluctuations in the electricity retail market price, requiring a yellow alert, and the data should be collected and output. List of electricity sales companies; when When this occurs, it indicates a significant anomaly in the electricity retail market price, requiring a red alert; and statistics and outputs are then compiled and released. List of electricity sales companies; The dynamic adjustment values ​​for the indicator thresholds further include: The system compiles statistics on retail market price risk warnings for all 12 months of the year and dynamically adjusts the base thresholds of monitoring indicators based on the number of times the thresholds are triggered. (1) When the number of warnings exceeds 9 times in 12 months of the year, the basic threshold of the overall retail market price monitoring indicator shall be raised:

[0015] (2) When the number of warnings is greater than 4 and less than 9 in 12 months of the year, there is no need to adjust the threshold of the overall price monitoring indicator for the retail market; (3) When the number of warnings is less than 4 in 12 months of the year, reduce the basic threshold of the overall retail market price monitoring indicator:

[0016] In step S4, calculating the deviation of the average monthly settlement price for retail users further includes: Calculate the deviation of the average monthly settlement price for retail users : .

[0017] In step S4, the overall retail market price monitoring information is disclosed to the corresponding retail users in a targeted manner, including: Based on the list of high-priced contracted retail users, the average monthly settlement price in the retail market will be calculated. Average monthly settlement price of electricity sales company Distribution of settlement prices for electricity sales companies' agents and retail users; deviation of average monthly settlement price for retail users. Information is disclosed to the relevant retail users in a targeted manner.

[0018] This invention also discloses an electricity retail market price risk monitoring system utilizing the aforementioned electricity retail market price risk monitoring method, comprising: The operation data acquisition module is used to acquire monthly operation data of the provincial electricity retail market, including the monthly average settlement price of the retail market of the electricity sales company, the monthly settlement volume of the retail market of the electricity sales company, and the monthly average settlement price of the retail users represented by the electricity sales company. The price monitoring indicator construction module is used to construct overall price monitoring indicators for the retail market based on the monthly operating data of the electricity retail market. The price monitoring indicators include the monthly average settlement price of the retail market, the deviation of the monthly average settlement price of the electricity sales company in the retail market, the change rate of the monthly average settlement price of the retail market, and the monthly price volatility of the retail market. The risk warning model construction module is used to initialize the basic threshold of the overall price monitoring indicators of the retail market, establish a retail market price risk warning model, and dynamically adjust the basic threshold according to the threshold trigger rate. The disclosure module is used to statistically analyze the distribution of settlement prices for retail users represented by electricity sales companies based on the output of the retail market price risk early warning model, form a list of retail users with high-priced contracts, and disclose the overall retail market price monitoring information to the corresponding retail users.

[0019] Accordingly, this application also discloses a terminal, including a processor and a storage medium; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the aforementioned electricity retail market price risk monitoring method.

[0020] Accordingly, this application also discloses a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the aforementioned electricity retail market price risk monitoring method.

[0021] The beneficial effects of this invention are as follows: Compared with the prior art, this invention provides a method and system for monitoring price risks in the electricity retail market. By collecting monthly operational data from the provincial electricity retail market, it establishes overall price monitoring indicators for the retail market, such as the deviation of the monthly average settlement price of electricity sales companies, the change rate of the monthly average settlement price of the retail market, and the monthly price volatility of the retail market. Furthermore, it dynamically adjusts the basic thresholds of these indicators based on the threshold trigger rate, achieving a precise quantitative assessment of the overall price risk in the electricity retail market. Compared to traditional static threshold monitoring methods, it can dynamically identify price risks under different scenarios, improving the sensitivity and accuracy of electricity retail market price monitoring. Simultaneously, this invention further analyzes the distribution of settlement prices for retail users represented by electricity sales companies based on the output results of the retail market price risk early warning model, forming a list of retail users with high-priced contracts. It then discloses the overall retail market price monitoring information to the corresponding retail users, which helps retail users understand market price levels, addresses information asymmetry, and creates an open, fair, and transparent competitive environment in the retail market. Attached Figure Description

[0022] Figure 1 This is a flowchart of the electricity retail market price risk monitoring method in this invention. Figure 2 This is a chart of monthly settlement data for the retail market in this invention. Figure 3 This is a distribution map of retail user settlement prices in this invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0024] The embodiments described in this application are merely some, not all, embodiments of the present invention. Based on the spirit of the present invention, other embodiments obtained by those skilled in the art without inventive effort are all within the protection scope of the present invention.

[0025] It should be noted that the use of terms such as "an embodiment," "an embodiment," "an exemplary embodiment," and "some embodiments" in the specification indicates that the described embodiment may include a specific feature, structure, or characteristic, but not every embodiment necessarily includes that specific feature, structure, or characteristic. Furthermore, when a specific feature, structure, or characteristic is described in connection with an embodiment, implementing such a feature, structure, or characteristic in conjunction with other embodiments (whether explicitly described or not) should be within the knowledge of those skilled in the art.

[0026] Generally, terms can be understood at least partly from their use in context. For example, depending at least partly on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in a singular sense, or a combination of features, structures, or characteristics in a plural sense. Additionally, the term "based on" can be understood not necessarily to convey an exclusive set of factors, but rather, alternatively, depending at least partly on the context, to allow for the presence of other factors that are not necessarily explicitly described.

[0027] To address the shortcomings of existing technologies, this invention proposes a method and system for monitoring price risks in the electricity retail market. (See [link to relevant documentation]). Figure 1 As shown, the electricity retail market price risk monitoring method disclosed in this invention includes the following steps: Step S1: Obtain monthly operational data for the provincial-level electricity retail market, including the average monthly settlement price of the electricity sales company's retail market. Monthly settlement electricity volume of electricity sales companies in the retail market The average monthly settlement price of electricity sales company i as an agent for retail user j .

[0028] in, , This indicates the number of electricity sales companies. This indicates the number of retail users.

[0029] S2: Based on the monthly operating data of the electricity retail market, construct an overall price monitoring index for the retail market, including the average monthly settlement price of the retail market. Deviation of monthly average settlement price in the retail market for electricity sales companies R represents the monthly average settlement price change rate in the retail market, and V represents the monthly price volatility rate in the retail market.

[0030] In a specific embodiment, the formula for calculating the retail market price monitoring indicator is as follows: (1) Average monthly settlement price in the retail market

[0031]

[0032] (2) Deviation of monthly average settlement price in the retail market of electricity sales company i

[0033]

[0034] (3) Monthly price volatility V in the retail market

[0035] (4) Monthly settlement average price change rate R in the retail market

[0036] In the formula, This represents the average monthly settlement price in the retail market for the previous month.

[0037] S3: Initialize the basic threshold of the overall price monitoring indicators in the retail market, establish a price risk early warning model for the retail market, and dynamically adjust the basic threshold according to the threshold trigger rate.

[0038] In a preferred embodiment, step 3 further includes: S3-1: Set the threshold ranges for the monthly price volatility V and the monthly settlement average price change rate R in the retail market, formulate a price risk early warning strategy for the retail market, and classify them into no warning required, yellow warning, and red warning.

[0039] (1) When When this occurs, it indicates that the electricity retail market price is highly stable and no early warning is needed; (2) When or , When this occurs, it indicates that there is some fluctuation in the electricity retail market price, requiring a yellow alert, and statistics and output should be compiled and released. List of electricity sales companies; (3) When When this occurs, it indicates a significant anomaly in the electricity retail market price, requiring a red alert; and statistics and outputs are then compiled and released. List of electricity sales companies; S3-2: Statistics on retail market price risk warnings for 12 months of the year, and dynamic adjustment of the basic threshold of the monitoring indicators based on the number of times the indicator threshold is triggered.

[0040] (1) When the number of warnings exceeds 9 times in 12 months of the year, the threshold value can be further increased based on the basic threshold of the overall price monitoring index of the retail market.

[0041]

[0042] (2) When the number of warnings in the 12 months of the year is greater than 4 and less than 9, there is no need to adjust the threshold of the overall price monitoring indicator for the retail market.

[0043]

[0044] (3) When the number of warnings is less than 4 times in 12 months of the year, the threshold value can be further reduced based on the basic threshold of the overall price monitoring index of the retail market.

[0045]

[0046] S4: Based on the output of the retail market price risk early warning model, statistically analyze the settlement price distribution of electricity sales company i-agent retail users, form a list of retail users with high-priced contracts, and disclose the overall retail market price monitoring information to the corresponding retail users.

[0047] Specifically, step S4 also includes: S4-1: According to " , , "The distribution of settlement prices for retail users of electricity sales company i, based on three gradients, is statistically analyzed and output." The list of high-priced contracted retail users, and the deviation of the average monthly settlement price for retail users. .

[0048]

[0049] S4-2: Based on the list of high-priced contracted retail users, calculate the average monthly settlement price in the retail market. Average monthly settlement price of electricity sales company Distribution of settlement prices for electricity sales companies' agents and retail users; deviation of average monthly settlement price for retail users. Information such as this will be disclosed to the corresponding retail users.

[0050] The following analysis uses the electricity retail market operation in a typical province in February 2025 as an example. In this province's electricity retail market, 10 electricity sales companies represent over 500 retail users participating in transactions. Monthly settlement data for the retail market is as follows: Figure 2 As shown.

[0051] Calculate the monthly average settlement price of the retail market according to step S2 above. Deviation of monthly average settlement price in the retail market for electricity sales companies The monthly average settlement price change rate R in the retail market and the monthly price volatility V in the retail market are shown in the table below.

[0052]

[0053] Based on the threshold range in step S3-1, when or , When this occurs, it indicates that there is some fluctuation in the electricity retail market price, requiring a yellow alert, and statistics and output should be compiled and released. Therefore, the list of electricity sales companies is provided, and electricity sales companies A and F are output, indicating that these two electricity sales companies need to be closely monitored.

[0054] Taking electricity sales company A as an example, according to step S4-1, the statistics are as follows: , , "The distribution of settlement prices for retail users of electricity sales company A under the three tiers is as follows:" Figure 3 As shown.

[0055] Output The list of high-priced contracted retail users includes: User 1, User 3, User 4, User 10, User 11, User 13, User 14, User 15, User 17, User 19, User 21, and User 26, totaling 23 retail users. The monthly average settlement price in the retail market will be used for this purpose. Average monthly settlement price of electricity sales company Distribution of settlement prices for electricity sales companies' agents and retail users; deviation of average monthly settlement price for retail users. Information such as this was disclosed to the aforementioned 23 retail users.

[0056] The beneficial effects of this invention are as follows: Compared with the prior art, this invention provides a method and system for monitoring price risks in the electricity retail market. By collecting monthly operational data from the provincial electricity retail market, it establishes overall price monitoring indicators for the retail market, such as the deviation of the monthly average settlement price of electricity sales companies, the change rate of the monthly average settlement price of the retail market, and the monthly price volatility of the retail market. Furthermore, it dynamically adjusts the basic thresholds of these indicators based on the threshold trigger rate, achieving a precise quantitative assessment of the overall price risk in the electricity retail market. Compared to traditional static threshold monitoring methods, it can dynamically identify price risks under different scenarios, improving the sensitivity and accuracy of electricity retail market price monitoring. Simultaneously, this invention further analyzes the distribution of settlement prices for retail users represented by electricity sales companies based on the output results of the retail market price risk early warning model, forming a list of retail users with high-priced contracts. It then discloses the overall retail market price monitoring information to the corresponding retail users, which helps retail users understand market price levels, addresses information asymmetry, and creates an open, fair, and transparent competitive environment in the retail market.

[0057] This invention can be a system, method, and / or computer program product. This invention also discloses an electricity retail market price risk monitoring system based on the aforementioned electricity retail market price risk monitoring method, comprising: The operation data acquisition module is used to acquire monthly operation data of the provincial electricity retail market, including the monthly average settlement price of the retail market of the electricity sales company, the monthly settlement volume of the retail market of the electricity sales company, and the monthly average settlement price of the retail users represented by the electricity sales company. The price monitoring indicator construction module is used to construct overall price monitoring indicators for the retail market based on the monthly operating data of the electricity retail market. The price monitoring indicators include the monthly average settlement price of the retail market, the deviation of the monthly average settlement price of the electricity sales company in the retail market, the change rate of the monthly average settlement price of the retail market, and the monthly price volatility of the retail market. The risk warning model construction module is used to initialize the basic threshold of the overall price monitoring indicators of the retail market, establish a retail market price risk warning model, and dynamically adjust the basic threshold according to the threshold trigger rate. The disclosure module is used to statistically analyze the distribution of settlement prices for retail users represented by electricity sales companies based on the output of the retail market price risk early warning model, form a list of retail users with high-priced contracts, and disclose the overall retail market price monitoring information to the corresponding retail users.

[0058] Based on the spirit of this invention, those skilled in the art will readily conceive of a computer program product that can be obtained based on the aforementioned method for monitoring price risks in the electricity retail market. The computer program product may include a computer-readable storage medium on which computer-readable program instructions are loaded to cause a processor to implement various aspects of this disclosure. That is, this application also includes a terminal comprising a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to perform the steps according to the aforementioned method for monitoring price risks in the electricity retail market.

[0059] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example, but not limited to, electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0060] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0061] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0062] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for monitoring price risks in the electricity retail market, characterized in that, Includes the following steps: S1: Obtain monthly operational data of the provincial electricity retail market, including the average monthly settlement price of the retail market of electricity sales companies, the average monthly settlement volume of the retail market of electricity sales companies, and the average monthly settlement price of the retail users represented by the electricity sales companies; S2: Based on the monthly operating data of the electricity retail market, construct an overall price monitoring index for the retail market. The price monitoring index includes the monthly average settlement price of the retail market, the deviation of the monthly average settlement price of the electricity sales company in the retail market, the change rate of the monthly average settlement price of the retail market, and the monthly price volatility of the retail market. S3: Initialize the basic threshold of the overall price monitoring indicators of the retail market, establish a price risk early warning model for the retail market, and dynamically adjust the basic threshold according to the threshold trigger rate. S4: Based on the output of the retail market price risk early warning model, statistically analyze the distribution of settlement prices for retail users represented by electricity sales companies, form a list of retail users with high-priced contracts, and disclose the overall retail market price monitoring information to the corresponding retail users.

2. The method for monitoring price risks in the electricity retail market according to claim 1, characterized in that, Step S3 further includes: Set threshold ranges for monthly price volatility and monthly settlement average price change in the retail market, formulate a price risk early warning strategy for the retail market, and classify the risk warning levels into no warning required, yellow warning, and red warning; The system tracks and analyzes price risk warnings in the retail market for all 12 months of the year, and dynamically adjusts the base thresholds of monitoring indicators based on the number of times the thresholds are triggered.

3. The method for monitoring price risks in the electricity retail market according to claim 2, characterized in that, Step S4 further includes: according to , , The distribution of settlement prices for retail users of electricity sales company i, based on three gradients, is statistically analyzed and output. The list of high-priced contracted retail users, and the deviation of the average monthly settlement price for retail users. ; Based on the list of high-priced contracted retail users, the average monthly settlement price in the retail market will be calculated. Average monthly settlement price of electricity sales company Distribution of settlement prices for electricity sales companies' agents and retail users.

4. The method for monitoring price risks in the electricity retail market according to claim 3, characterized in that, In step S2, the retail market price monitoring indicators further include: (1) Average monthly settlement price in the retail market : (2) Deviation of monthly average settlement price in the retail market of electricity sales company i : (3) Monthly price volatility V in the retail market: (4) Monthly settlement average price change rate R in the retail market In the formula, This represents the average monthly settlement price in the retail market for the previous month.

5. The method for monitoring price risks in the electricity retail market according to claim 4, characterized in that, The retail market price risk warning strategy in step S3 further includes: Set threshold ranges for monthly price volatility V and monthly settlement average price change rate R in the retail market, formulate a price risk early warning strategy for the retail market, and classify it into no warning required, yellow warning, and red warning. when When this occurs, it indicates that the electricity retail market price is highly stable and no early warning is needed; when or , When this occurs, it indicates that there are fluctuations in the electricity retail market price, requiring a yellow alert, and the data should be collected and output. List of electricity sales companies; when When this occurs, it indicates a significant anomaly in the electricity retail market price, requiring a red alert; and statistics and outputs are then compiled and released. List of electricity sales companies.

6. The method for monitoring price risks in the electricity retail market according to claim 5, characterized in that, In step S3, the dynamic correction value of the indicator threshold further includes: The system compiles statistics on retail market price risk warnings for all 12 months of the year and dynamically adjusts the base thresholds of monitoring indicators based on the number of times the thresholds are triggered. (1) When the number of warnings exceeds 9 times in 12 months of the year, the basic threshold of the overall retail market price monitoring indicator shall be raised: (2) When the number of warnings is greater than 4 and less than 9 in 12 months of the year, there is no need to adjust the threshold of the overall price monitoring indicator for the retail market; (3) When the number of warnings is less than 4 in 12 months of the year, reduce the basic threshold of the overall retail market price monitoring indicator: 。 7. The method for monitoring price risks in the electricity retail market according to claim 6, characterized in that, In step S4, calculating the deviation of the average monthly settlement price for retail users further includes: Calculate the deviation of the average monthly settlement price for retail users : 。 8. The method for monitoring price risks in the electricity retail market according to claim 7, characterized in that, In step S4, the overall retail market price monitoring information is disclosed to the corresponding retail users in a targeted manner, including: Based on the list of high-priced contracted retail users, the average monthly settlement price in the retail market will be calculated. Average monthly settlement price of electricity sales company Distribution of settlement prices for electricity sales companies' agents and retail users; deviation of average monthly settlement price for retail users. Information is disclosed to the relevant retail users in a targeted manner.

9. A price risk monitoring system for the electricity retail market, characterized in that, include: The operation data acquisition module is used to acquire monthly operation data of the provincial electricity retail market, including the monthly average settlement price of the retail market of the electricity sales company, the monthly settlement volume of the retail market of the electricity sales company, and the monthly average settlement price of the retail users represented by the electricity sales company. The price monitoring indicator construction module is used to construct overall price monitoring indicators for the retail market based on the monthly operating data of the electricity retail market. The price monitoring indicators include the monthly average settlement price of the retail market, the deviation of the monthly average settlement price of the electricity sales company in the retail market, the change rate of the monthly average settlement price of the retail market, and the monthly price volatility of the retail market. The risk warning model construction module is used to initialize the basic threshold of the overall price monitoring indicators of the retail market, establish a retail market price risk warning model, and dynamically adjust the basic threshold according to the threshold trigger rate. The disclosure module is used to statistically analyze the distribution of settlement prices for retail users represented by electricity sales companies based on the output of the retail market price risk early warning model, form a list of retail users with high-priced contracts, and disclose the overall retail market price monitoring information to the corresponding retail users.

10. A terminal, comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the electricity retail market price risk monitoring method according to any one of claims 1-8.

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