Multi-cycle inter-provincial electric power spot price limit effect comprehensive evaluation method and system

Abstract

The invention discloses a multi-cycle inter-provincial electric power spot goods price limit effect comprehensive evaluation method and system, and belongs to the technical field of electric power spot goods market transactions, and the method comprises the steps: obtaining the basic data of an inter-provincial electric power spot goods market; establishing an inter-province electric power spot price limit effect comprehensive evaluation index model based on the basic data of the inter-province electric power spot market; according to the constructed inter-provincial power spot price limit effect comprehensive evaluation index model, establishing an inter-provincial power spot price limit effect comprehensive evaluation index system, and calculating inter-provincial power spot price limit effect evaluation indexes of each period; and evaluating the price limit effect by using the inter-provincial electric power spot price limit effect evaluation index of each period. The method has the advantages of high efficiency, accuracy, comprehensiveness and the like, and the operation efficiency and stability of the electric power spot market can be remarkably improved.

Description

Technical Field

[0001] This invention belongs to the field of electricity spot market trading technology, specifically involving a comprehensive evaluation method and system for the effect of multi-period inter-provincial electricity spot price limits. Background Technology

[0002] The inter-provincial electricity spot market is an important component of the national unified electricity market, positioned to promote the mutual assistance of electricity surpluses and shortages across provinces and regions and the large-scale consumption of renewable energy. Price declaration, as the foundation and key link in the operation of the inter-provincial electricity spot market, is a crucial factor affecting the continuous and stable operation of the market. Against this backdrop, designing a scientifically sound and reasonable price limit mechanism for the inter-provincial electricity spot market has become an important task in the construction of the electricity market. The main purpose of the price limit mechanism is to prevent drastic fluctuations in market prices and ensure the smooth operation of the market. By setting reasonable price upper and lower limits, it can effectively prevent market participants from taking advantage of information asymmetry or market forces to engage in malicious bidding, thereby maintaining market fairness and transparency. Furthermore, the price limit mechanism can guide market participants to form reasonable price expectations, promoting the optimal allocation and efficient utilization of electricity resources.

[0003] Existing technologies primarily focus on price management mechanisms in inter-provincial electricity spot markets, typically employing a dynamic pricing strategy based on historical data and market supply and demand relationships. This aims to regulate the inter-provincial flow of electricity resources through price levers. Specifically, this approach sets a relatively flexible price range based on historical transaction data, electricity supply and demand forecasts, and renewable energy generation, guiding market participants to submit bids within a certain range. However, this approach may have limitations in dealing with extreme market conditions or unforeseen events. For example, in cases of severe market supply and demand imbalances or significant fluctuations in renewable energy generation, the approach may not be able to adjust prices quickly and effectively, thus failing to ensure stable market operation. Furthermore, the setting of price ceilings and floor limits may lack sufficient scientific basis and flexibility, making it difficult to completely prevent malicious bidding by market participants.

[0004] First, while its dynamic pricing strategy can guide market participants' bidding behavior under normal circumstances, its response speed and flexibility are clearly insufficient in the face of extreme market conditions or emergencies, making it difficult to quickly adjust prices to restore market balance. This lag may lead to a misallocation of electricity resources, affecting the stable operation of the market.

[0005] Secondly, existing technologies lack scientific basis and sufficient flexibility in setting price ceilings and floor levels. Such fixed or relatively fixed price ranges may fail to accurately reflect the true supply and demand situation in the market, thus providing opportunities for malicious bidding by market participants. This not only undermines market fairness but may also distort price signals, affecting the optimal allocation of electricity resources.

[0006] In summary, the existing inter-provincial electricity spot market bidding price limit mechanism suffers from shortcomings in responding to grid emergencies, adapting to the volatility characteristics of high-proportion renewable energy, and accurately reflecting complex grid constraints for cross-regional resource optimization and dispatch. It also limits the crucial role of market-cleared price signals in supporting the safe and stable operation of the power system, promoting the efficient consumption of renewable energy, and achieving optimal technical allocation of cross-provincial electricity resources. Therefore, its pricing strategy and price range setting require further optimization and improvement. Summary of the Invention

[0007] The technical problem to be solved by this invention is to provide a comprehensive evaluation method and system for the effect of multi-cycle inter-provincial electricity spot price limits, which addresses the shortcomings of the prior art. This method is used to solve the technical problems of safety and stability risks under extreme operating conditions of the existing power grid, bottlenecks in the efficiency of high-proportion renewable energy consumption, and insufficient cross-provincial resource optimization under complex constraints.

[0008] The present invention adopts the following technical solution: A comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits includes the following steps: Obtain basic data on the inter-provincial electricity spot market; A comprehensive evaluation index model for the effectiveness of inter-provincial electricity spot price limits is established based on basic data from the inter-provincial electricity spot market. Based on the constructed comprehensive evaluation index model of the inter-provincial electricity spot price limit effect, a comprehensive evaluation index system for the inter-provincial electricity spot price limit effect is established, and the evaluation index of the inter-provincial electricity spot price limit effect for each period is calculated. The effectiveness of the price limit was evaluated using evaluation indicators for the inter-provincial electricity spot price limit in each cycle.

[0009] Preferably, the basic data for the inter-provincial electricity spot market includes the transaction volume, average transaction price, transaction node declared price, and transaction node clearing price.

[0010] Preferably, the comprehensive evaluation index model for the effectiveness of inter-provincial electricity spot price limits includes multi-period inter-provincial spot transaction volume. Average inter-provincial spot transaction price over multiple periods Market quotation reach rate Market clearing price limit rate Price limit-volume elasticity coefficient model and price limit-average price elasticity coefficient model.

[0011] Preferably, inter-provincial spot transaction volume over multiple periods for:

[0012] in, This represents the inter-provincial spot trading volume on day t. Multi-period inter-provincial spot transaction average price for:

[0013] in, The inter-provincial spot clearing price on day t. This represents the inter-provincial spot trading volume on day t. Market quotation reach rate for:

[0014] in, The number of bids that hit the price limit. This represents the total number of quotes. Market clearing price reaches limit rate for:

[0015] in, This refers to the number of times the price exceeds a preset price limit. This represents the total number of transactions. The price limit-volume elasticity coefficient model is as follows:

[0016] in, The price limit minus volume elasticity coefficient within period t. , This represents the trading volume before and after the price limit was set. This represents the change in the price limit threshold. This is the price limit threshold; The price limit-average price elasticity coefficient model is as follows:

[0017] in, The price elasticity coefficient between the limit price and the average price within period t. For the change in average transaction price under different price limits, The average price of transactions within the price limit. This represents the change in the price limit threshold. This is the price limit threshold.

[0018] Preferably, the evaluation indicators for the effectiveness of inter-provincial electricity spot price limits in each cycle include daily evaluation indicators for the effectiveness of inter-provincial spot price limits, monthly evaluation indicators for the effectiveness of inter-provincial spot price limits, and annual evaluation indicators for the effectiveness of inter-provincial spot price limits. The daily evaluation indicators for the effectiveness of inter-provincial spot price limits include: Daily transaction volume, daily average transaction price, daily market quotation limit rate, market clearing price limit rate, daily price limit-volume elasticity coefficient, and daily price limit-average price elasticity coefficient; The monthly evaluation indicators for the effectiveness of inter-provincial spot price limits include: Monthly transaction volume, monthly average transaction price, monthly market quotation limit rate, monthly market clearing price limit rate, monthly price limit-transaction volume elasticity coefficient, and monthly price limit-average price elasticity coefficient; The annual evaluation indicators for the effectiveness of inter-provincial spot price limits include: Annual transaction volume, annual average transaction price, annual market quotation limit rate, market clearing price limit rate, annual price limit-transaction volume elasticity coefficient, and annual price limit-average price elasticity coefficient.

[0019] Preferably, the daily market price limit rate :

[0020] Market clearing price reaches limit rate :

[0021] Daily price limit - volume elasticity coefficient :

[0022] Daily price limit - average price elasticity coefficient :

[0023] in, The number of daily price quotes that hit the price limit. Total number of quotes per day The number of transactions where the daily clearing price exceeds the preset price limit. Total number of transactions per day This refers to the trading volume after the daily price limit was set. This represents the trading volume before the daily price limit was set. This represents the daily change in the price limit threshold. The daily price limit threshold. This represents the change in the average transaction price under different daily price limits. The average transaction price before the daily price limit was set; Monthly transaction volume :

[0024] Average monthly transaction price :

[0025] Monthly market price limit reached :

[0026] Monthly market clearing price reaches limit rate :

[0027] Monthly price limit - volume elasticity coefficient :

[0028] Monthly price limit - average price elasticity coefficient :

[0029] in, Daily transaction volume The average daily transaction price. This represents the total number of quotes for the month. The number of monthly quotes that hit the price limit. This represents the total number of transactions in the month. This refers to the number of times the monthly clearance price exceeds a preset price limit. This represents the trading volume before the monthly price cap was set. This represents the trading volume after the monthly price limit was set. This represents the monthly price limit threshold change. The monthly price limit threshold. This represents the change in average transaction price under different price limits each month. This represents the average transaction price before the monthly price limit was set. Annual transaction volume :

[0030] Average annual transaction price :

[0031] Annual market quotation compliance rate :

[0032] Market clearing price reaches limit rate :

[0033] Annual price limit - trading volume elasticity coefficient :

[0034] Annual price elasticity coefficient :

[0035] in, The number of bids that hit the price limit in a given year. This represents the total number of quotes received throughout the year. This refers to the number of times the annual clearing price exceeds a preset price limit. This represents the total number of transactions completed in a year. This refers to the transaction volume after the annual price cap. This refers to the trading volume prior to the annual price cap. This represents the change in average transaction price under different annual price limits. This represents the average transaction price before the annual price cap. This represents the annual price limit threshold change. This is the annual price limit threshold.

[0036] Preferably, the price limit effect assessment includes: transaction volume assessment, average transaction price assessment, market bid limit rate assessment, market clearing price limit rate assessment, price limit-transaction volume elasticity coefficient assessment, and price limit-average price elasticity coefficient assessment.

[0037] Preferably, the transaction volume assessment is as follows: The impact of price limits on market supply and demand balance can be judged by the changes in trading volume over different periods. If the trading volume decreases after the price limit is implemented, it indicates that the price limit has suppressed some trading demand. If the trading volume continues to grow, it means that market participants have a high acceptance of the price limit measures or that the price limit level is reasonable.

[0038] Preferably, the average transaction price is assessed. By combining the changes in the average inter-provincial spot transaction price over multiple periods, we can determine whether the price control measures have effectively guided market price trends and whether they have achieved the expected regulatory objectives.

[0039] Preferably, market quotation fulfillment rate assessment If the market bid-to-limit rate rises significantly after the price limit is implemented, it indicates that the price limit measures have effectively curbed excessively high bids. If the market price limit rate decreases, further analysis is needed to determine the reasons, such as whether the price limit is set too high, causing market prices to generally fall below the limit, or whether there have been other changes in the market supply and demand relationship.

[0040] Preferably, the assessment of the market clearing price limit achievement rate: If the market clearing price attainment rate rises after the price limit is implemented, it indicates that the price limit measures have a significant impact on the market clearing price. If the market clearing price reaches the limit rate decreases, it may be due to an unreasonable price limit setting, resulting in market clearing prices generally falling below the limit, or other unforeseen changes in market supply and demand.

[0041] Preferably, the elasticity coefficient is evaluated based on the price limit-volume elasticity coefficient: If the price limit-volume elasticity coefficient is large, the price limit measure will have an impact on the trading volume. If the price limit-volume elasticity coefficient is small, the price limit measure will have no impact on the trading volume.

[0042] Preferably, the price limit-average price elasticity coefficient is evaluated based on the calculated price limit-average price elasticity coefficient: If the price limit-average price elasticity coefficient is high, the price limit measure will have a significant impact on market prices. If the price limit-average price elasticity coefficient is low, the price limit measure will have no impact on market prices.

[0043] Secondly, embodiments of the present invention provide a comprehensive evaluation system for the effect of multi-cycle inter-provincial electricity spot price limits, including: The data module acquires basic data for the inter-provincial electricity spot market; The indicator module establishes a comprehensive evaluation indicator model for the effectiveness of inter-provincial electricity spot price limits based on basic data from the inter-provincial electricity spot market. The system module establishes a comprehensive evaluation index system for the effect of inter-provincial electricity spot price limits based on the constructed comprehensive evaluation index model, and calculates the evaluation index for the effect of inter-provincial electricity spot price limits in each period. The evaluation module uses evaluation indicators for the effectiveness of inter-provincial electricity spot price limits in each cycle to assess the price limit effect.

[0044] Preferably, the comprehensive evaluation index model for the effectiveness of inter-provincial electricity spot price limits includes multi-period inter-provincial spot transaction volume. Average inter-provincial spot transaction price over multiple periods Market quotation reach rate Market clearing price limit rate Price limit-volume elasticity coefficient model and price limit-average price elasticity coefficient model.

[0045] Preferably, inter-provincial spot transaction volume over multiple periods for:

[0046] in, This represents the inter-provincial spot trading volume on day t. Multi-period inter-provincial spot transaction average price for:

[0047] in, The inter-provincial spot clearing price on day t. This represents the inter-provincial spot trading volume on day t. Market quotation reach rate for:

[0048] in, The number of bids that hit the price limit. This represents the total number of quotes. Market clearing price reaches limit rate for:

[0049] in, This refers to the number of times the price exceeds a preset price limit. This represents the total number of transactions. The price limit-volume elasticity coefficient model is as follows:

[0050] in, The price limit minus volume elasticity coefficient within period t. , This represents the trading volume before and after the price limit was set. This represents the change in the price limit threshold. This is the price limit threshold; The price limit-average price elasticity coefficient model is as follows:

[0051] in, The price elasticity coefficient between the limit price and the average price within a period t. The change in average transaction price for different price limits. The average price of transactions within the price limit. This represents the change in the price limit threshold. This is the price limit threshold.

[0052] Preferably, the evaluation indicators for the effectiveness of inter-provincial electricity spot price limits in each cycle include daily evaluation indicators for the effectiveness of inter-provincial spot price limits, monthly evaluation indicators for the effectiveness of inter-provincial spot price limits, and annual evaluation indicators for the effectiveness of inter-provincial spot price limits. The daily evaluation indicators for the effectiveness of inter-provincial spot price limits include: Daily transaction volume, daily average transaction price, daily market quotation limit rate, market clearing price limit rate, daily price limit-volume elasticity coefficient, and daily price limit-average price elasticity coefficient; The monthly evaluation indicators for the effectiveness of inter-provincial spot price limits include: Monthly transaction volume, monthly average transaction price, monthly market quotation limit rate, monthly market clearing price limit rate, monthly price limit-transaction volume elasticity coefficient, and monthly price limit-average price elasticity coefficient; The annual evaluation indicators for the effectiveness of inter-provincial spot price limits include: Annual transaction volume, annual average transaction price, annual market quotation limit rate, market clearing price limit rate, annual price limit-transaction volume elasticity coefficient, and annual price limit-average price elasticity coefficient.

[0053] Preferably, the daily market price limit rate :

[0054] Market clearing price reaches limit rate :

[0055] Daily price limit - volume elasticity coefficient :

[0056] Daily price limit - average price elasticity coefficient :

[0057] in, The number of daily price quotes that hit the price limit. Total number of quotes per day The number of transactions where the daily clearing price exceeds the preset price limit. Total number of transactions per day This refers to the trading volume after the daily price limit was set. This represents the trading volume before the daily price limit was set. This represents the daily change in the price limit threshold. The daily price limit threshold. This represents the change in the average transaction price under different daily price limits. The average transaction price before the daily price limit was set; Monthly transaction volume :

[0058] Average monthly transaction price :

[0059] Monthly market price limit reached :

[0060] Monthly market clearing price reaches limit rate :

[0061] Monthly price limit - volume elasticity coefficient :

[0062] Monthly price limit - average price elasticity coefficient :

[0063] in, Daily transaction volume The average daily transaction price. This represents the total number of quotes for the month. The number of monthly quotes that hit the price limit. This represents the total number of transactions in the month. This refers to the number of times the monthly clearance price exceeds a preset price limit. This represents the trading volume before the monthly price cap was set. This represents the trading volume after the monthly price limit was set. This represents the monthly price limit threshold change. The monthly price limit threshold. This represents the change in average transaction price under different price limits each month. This represents the average transaction price before the monthly price limit was set. Annual transaction volume :

[0064] Average annual transaction price :

[0065] Annual market quotation compliance rate :

[0066] Market clearing price reaches limit rate :

[0067] Annual price limit - trading volume elasticity coefficient :

[0068] Annual price elasticity coefficient :

[0069] in, The number of bids that hit the price limit in a given year. This represents the total number of quotes received throughout the year. This refers to the number of times the annual clearing price exceeds a preset price limit. This represents the total number of transactions completed in a year. This refers to the transaction volume after the annual price cap. This refers to the trading volume prior to the annual price cap. This represents the change in average transaction price under different annual price limits. This represents the average transaction price before the annual price cap. This represents the annual price limit threshold change. This is the annual price limit threshold.

[0070] Preferably, the price limit effect assessment includes: transaction volume assessment, average transaction price assessment, market bid limit rate assessment, market clearing price limit rate assessment, price limit-transaction volume elasticity coefficient assessment, and price limit-average price elasticity coefficient assessment.

[0071] Preferably, the transaction volume assessment is as follows: The impact of price limits on market supply and demand balance can be judged by the changes in trading volume over different periods. If the trading volume decreases after the price limit is implemented, it indicates that the price limit has suppressed some trading demand; if the trading volume continues to grow, it means that market participants have a high acceptance of the price limit measures or that the price limit level is reasonable. Average transaction price assessment: By combining the changes in the average inter-provincial spot transaction price over multiple periods, we can determine whether the price control measures have guided market price trends and whether they have achieved the expected regulatory objectives. Market quotation fulfillment rate assessment: If the market bid-to-limit rate rises after the price limit is implemented, the price limit measure will curb excessively high bids. If the market price limit rate decreases, it is necessary to determine whether the price limit level is set too high, causing market prices to fall below the price limit, or whether the market supply and demand relationship has changed. Market clearing price limit assessment: If the market clearing price attainment rate rises after the price limit is implemented, it indicates that the price limit measures have an impact on the market clearing price. If the market clearing price reaches the limit rate decreases, it is judged that the price limit level is set unreasonably, resulting in the market clearing price being lower than the limit price, or other unforeseen changes have occurred in the market supply and demand relationship; The elasticity coefficient is evaluated based on the price limit-volume elasticity coefficient: If the price limit-volume elasticity coefficient is greater than the set value, the price limit measure will affect the trading volume. If the price limit-volume elasticity coefficient is less than the set value, the price limit measure will have no impact on the trading volume. The price limit-average price elasticity coefficient is evaluated based on the calculated price limit-average price elasticity coefficient: If the price limit-average price elasticity coefficient is higher than the set threshold, the price limit measures will have an impact on market prices. If the price limit-average price elasticity coefficient is lower than the set threshold, the price limit measure will have no impact on market prices.

[0072] Thirdly, a computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits.

[0073] Fourthly, embodiments of the present invention provide a computer-readable storage medium including a computer program, which, when executed by a processor, implements the steps of the above-described comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits.

[0074] Fifthly, a chip includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits.

[0075] Sixthly, embodiments of the present invention provide an electronic device, including a computer program, which, when executed by the electronic device, implements the steps of the above-described comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits.

[0076] Compared with the prior art, the present invention has at least the following beneficial effects: A comprehensive evaluation method for the effectiveness of inter-provincial electricity spot price limits across multiple cycles is proposed. By constructing a multi-cycle, multi-dimensional comprehensive evaluation index system, this method achieves, for the first time, the scientific quantification and dynamic monitoring of the core technical effectiveness of inter-provincial electricity spot price limit mechanisms in responding to extreme grid conditions, promoting the consumption of new energy sources, and optimizing cross-provincial resource allocation. This provides data support and decision-making basis for the precise optimization of price limit strategies. The evaluation system includes indicators such as the emergency operating condition price limit response timeliness index and the cross-section over-limit risk mitigation rate. This allows for quantitative analysis of whether the price limit mechanism can quickly generate effective price signals to incentivize cross-provincial reserve resource response during sudden faults or power imbalances, thereby reducing the probability of frequency over-limit and the risk of over-stability limits in key cross-section power flow. Multi-period assessments can continuously track the effects of price cap parameters on the transient / dynamic stability of the system. By designing core indicators such as negative electricity price-triggered absorption gain rate, renewable energy fluctuation tracking degree, and wind and solar curtailment suppression coefficient, the flexibility of the price cap lower limit setting and the incentive of the upper limit are accurately measured. The price cap mechanism promotes the cross-provincial absorption of surplus electricity during periods of high renewable energy generation and ensures the availability of flexible resources during periods of sharp output decline in multi-period data, directly serving the reduction of curtailment rate and the improvement of clean energy utilization. The indicator system includes assessment items such as congestion cost transmission efficiency, cross-provincial network loss optimization rate, and regional marginal cost disclosure. Using multi-period transaction and operation data, the system analyzes whether the price cap mechanism internalizes network congestion costs, reflects path loss differences, and guides price signals to approach the optimal power flow solution. The assessment results can reveal the actual contribution of the price cap rules to the reduction of coal / gas consumption and the improvement of transmission efficiency across the entire network, promoting the flow of resources across provinces at the real physical cost.

[0077] Furthermore, by comparing the bid price and the clearing price, the constraining effect of the price limit on market behavior can be identified; the average transaction price reflects the market supply and demand equilibrium level, the bid price limit rate directly reflects the intervention strength of the price limit on the bidding strategy, and the clearing price limit rate measures the suppressive effect of the price limit on the actual transaction price.

[0078] Furthermore, a high bid-to-limit rate indicates high-price speculation in the market, necessitating tighter price controls; while a high clearing-to-limit rate may suppress reasonable price fluctuations; policy sensitivity can be analyzed by comparing the change in price limit threshold with the change in trading volume / average price; intraday fluctuations and annual trends need to be assessed differently to avoid a one-size-fits-all approach.

[0079] Furthermore, we can capture real-time supply and demand shocks, such as short-term price peaks caused by cross-regional power transmission channel blockages, correlate them with monthly renewable energy consumption targets, assess the role of price limits in promoting cross-provincial regulation capacity, and analyze the guiding role of price limits on long-term investment signals in conjunction with capacity compensation mechanisms.

[0080] Furthermore, a high elasticity coefficient indicates strong market liquidity, but may be accompanied by speculative risks. If the bid-to-limit rate is high but the clearing-to-limit rate is low, there may be a phenomenon of inflated bids while the actual supply and demand are loose. It is necessary to verify the strategic bids of market participants, establish a price limit fluctuation range based on the elasticity coefficient, avoid the failure of fixed price limits in extreme scenarios, and identify the rationality defects of the price limit mechanism design through multi-dimensional correlation analysis.

[0081] It is understood that the beneficial effects of the second to sixth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0082] In summary, this invention has the advantages of high efficiency, accuracy, and comprehensiveness, and can significantly improve the operational efficiency and stability of the electricity spot market.

[0083] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0084] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0085] Figure 1 This is a schematic diagram of the process of the present invention; Figure 2 A schematic diagram of a computer device provided in an embodiment of the present invention; Figure 3 This is a block diagram of an electronic device according to an embodiment of the present invention.

[0086] Among them, 60. Computer equipment; 61. Processor; 62. Memory; 63. Computer program; 600. Electronic device; 610. Processing unit; 620. Storage unit; 6201. Random access memory unit; 6202. Cache memory unit; 6203. Read-only memory unit; 6204. Program / utility; 6205. Program module; 630. Bus; 640. Display unit; 650. Input / output interface; 660. Network adapter; 700. External device. Detailed Implementation

[0087] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0088] 1. Inter-provincial electricity spot market The inter-provincial electricity spot market is an inter-provincial day-ahead or intraday electricity trading market that is based on the inter-provincial medium- and long-term electricity market. Power generation companies and electricity users freely buy and sell electricity according to market supply and demand and price changes, thereby realizing the mutual assistance and optimal allocation of electricity between different provinces.

[0089] 2. Price Limit Mechanism The price limit for bidding refers to the upper or lower limit of prices that parties in inter-provincial electricity spot trading must follow when bidding for electricity purchase and sale prices, in order to ensure fair competition and stable operation of the market.

[0090] 3. Meaning of inter-provincial spot trading volume Inter-provincial spot market electricity volume refers to the actual electricity volume traded through free buying and selling in the inter-provincial electricity spot market. This volume reflects the real-time supply and demand situation of the market and is an important indicator for assessing the activity of electricity market transactions and the efficiency of resource allocation.

[0091] 4. Average inter-provincial spot transaction price The inter-provincial spot market average price refers to the weighted average price of all traded electricity volumes in the inter-provincial electricity spot market. This price reflects the overall price level of the market and the scarcity of electricity resources, and is an important indicator for measuring the efficiency of electricity market transactions and the rationality of prices.

[0092] 5. Market quotation fulfillment rate The market bid-to-limit rate refers to the percentage of bids in the inter-provincial electricity spot market that meet or exceed the price limit. This indicator reflects the concentration of market bids and price volatility, and is an important measure of market activity and price discovery efficiency.

[0093] 6. Market clearing price limit attainment rate The market clearing price limit attainment rate refers to the proportion of transactions in the inter-provincial electricity spot market where the actual clearing price reaches or exceeds a preset price limit. This indicator is an important measure of the effectiveness of market price regulation and market stability. When the market clearing price frequently reaches or exceeds the limit, it may mean that the market price regulation mechanism needs further optimization to enhance the market's price discovery capability and stability.

[0094] This invention provides a comprehensive evaluation method for the effectiveness of multi-cycle inter-provincial electricity spot price limits, breaking through the limitations of traditional single-indicator evaluation. By integrating multi-dimensional data, it constructs a comprehensive and dynamic evaluation indicator system. This system can not only reflect market dynamics in real time, but also deeply explore potential market trends, providing managers with more accurate decision-making basis.

[0095] Example 1 Please see Figure 1 This invention provides a comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits, comprising the following steps: S1. Obtain basic data for the inter-provincial electricity spot market; Basic data, including transaction volume, average transaction price, transaction node declaration price, and transaction node clearing price, are obtained and prepared through the inter-provincial electricity spot market technical support system.

[0096] S2. Based on the basic data of the inter-provincial electricity spot market obtained in step S1, establish a comprehensive evaluation index model for the effect of inter-provincial electricity spot price limits. The comprehensive evaluation index model for the effectiveness of inter-provincial electricity spot price limits includes multi-period inter-provincial spot transaction volume, average inter-provincial spot transaction price, market bid-to-limit rate, market clearing price-to-limit rate, price limit-transaction volume elasticity coefficient model, and price limit-average price elasticity coefficient model. The calculation methods for each model index are as follows: Multi-period inter-provincial spot transaction volume:

[0097] in, This represents the inter-provincial spot trading volume within period T. This represents the inter-provincial spot trading volume on day t.

[0098] Average inter-provincial spot transaction price over multiple periods:

[0099] in, The weighted average spot price across provinces within period T. The inter-provincial spot clearing price on day t. This represents the inter-provincial spot trading volume on day t.

[0100] Market price limit fulfillment rate: The market bid-to-limit rate refers to the percentage of transactions in the inter-provincial electricity spot market where bid prices meet or exceed the price limit. This indicator reflects the concentration of market bids and price volatility, and is an important measure of market activity and price discovery efficiency. The calculation formula is:

[0101] in, The percentage of bids met (%) The number of bids that hit the price limit. This represents the total number of quotes.

[0102] Market clearing price limit achieved: The market clearing price limit attainment rate refers to the proportion of times the actual clearing price in the inter-provincial electricity spot market reaches or exceeds a preset price limit. This indicator is an important measure of the effectiveness of market price regulation and market stability. When the market clearing price frequently reaches or exceeds the limit, it means that the market price regulation mechanism needs further optimization to enhance the market's price discovery capability and stability. The calculation formula is:

[0103] in, The clearance price limit rate (%). This refers to the number of times the price exceeds a preset price limit. This represents the total number of transactions.

[0104] Price Limit-Volume Elasticity Coefficient Model: A multi-period price limit-volume elasticity coefficient model is constructed to quantify the impact of price limit adjustments on trading volume.

[0105]

[0106] in, This is the price-volume elasticity coefficient within period t. The larger the absolute value, the higher the sensitivity. , This represents the trading volume before and after the price limit was set. This represents the change in the price limit threshold. This is the price limit threshold.

[0107] Price ceiling-average price elasticity coefficient model:

[0108] in, The price elasticity coefficient between the limit price and the average price within period t. The change in average transaction price for different price limits. The average price of transactions within the price limit. This represents the change in the price limit threshold. This is the price limit threshold.

[0109] S3. Based on the comprehensive evaluation index model of the inter-provincial electricity spot price limit effect constructed in step S2, establish a comprehensive evaluation index system for the inter-provincial electricity spot price limit effect, and calculate the evaluation index of the inter-provincial electricity spot price limit effect for each period. 1) Daily evaluation indicators of the effectiveness of inter-provincial spot price limits Daily transaction volume: The daily transaction volume is obtained through the inter-provincial electricity spot market technical support system.

[0110] Daily average transaction price: Obtained through the inter-provincial electricity spot market technical support system.

[0111] Daily market price limit attainment rate:

[0112] Market clearing price limit achieved:

[0113] Daily price limit - volume elasticity coefficient:

[0114] Daily price limit - average price elasticity coefficient:

[0115] in, The number of daily price quotes that hit the price limit. Total number of quotes per day This refers to the number of times the daily clearing price exceeds the preset price limit. Total number of transactions per day This refers to the trading volume after the daily price limit was set. This represents the trading volume before the daily price limit was set. This represents the daily change in the price limit threshold. The daily price limit threshold. This represents the change in the average transaction price under different daily price limits. This represents the average transaction price before the daily price limit was set.

[0116] 2) Monthly evaluation indicators for the effectiveness of inter-provincial spot price limits Monthly transaction volume:

[0117] Average monthly transaction price:

[0118] Monthly market price compliance rate:

[0119] Monthly market clearing price limit attainment rate:

[0120] Monthly price limit - volume elasticity coefficient:

[0121] Monthly price limit - average price elasticity coefficient:

[0122] in, Daily transaction volume The average daily transaction price. This represents the total number of quotes for the month. The number of monthly quotes that hit the price limit. This represents the total number of transactions in the month. This refers to the number of times the monthly clearance price exceeds a preset price limit. This represents the trading volume before the monthly price cap was set. This represents the trading volume after the monthly price limit was set. This represents the monthly price limit threshold change. The monthly price limit threshold. This represents the change in average transaction price under different price limits each month. This represents the average transaction price before the monthly price limit was set.

[0123] 3) Annual evaluation indicators for the effectiveness of inter-provincial spot price limits Annual transaction volume:

[0124] Average annual transaction price:

[0125] Annual market quotation compliance rate:

[0126] Market clearing price limit achieved:

[0127] Annual price limit - volume elasticity coefficient:

[0128] Annual price elasticity coefficient:

[0129] in, The number of bids that hit the price limit in a given year. This represents the total number of quotes received throughout the year. This refers to the number of times the annual clearing price exceeds a preset price limit. This represents the total number of transactions completed in a year. This refers to the transaction volume after the annual price cap. This refers to the trading volume prior to the annual price cap. This represents the change in average transaction price under different annual price limits. This represents the average transaction price before the annual price cap. This represents the annual price limit threshold change. This is the annual price limit threshold.

[0130] S4. Use the evaluation indicators of the inter-provincial electricity spot price limit effect obtained in step S3 to evaluate the price limit effect.

[0131] 1) Transaction volume assessment The impact of price controls on market supply and demand balance can be assessed by analyzing changes in trading volume over different periods. A significant decrease in trading volume after the implementation of price controls indicates that the price controls have suppressed some trading demand. Conversely, if trading volume remains stable or increases, it means that market participants have a high acceptance of price limits or that the price limit level is reasonable.

[0132] 2) Average transaction price assessment By combining the changes in the average inter-provincial spot transaction price over multiple periods, we can determine whether the price control measures have effectively guided market price trends and whether they have achieved the expected regulatory objectives.

[0133] 3) Market quotation compliance rate assessment If the market bid-to-limit rate rises significantly after the price limit is implemented, it indicates that the price limit measures have effectively curbed excessively high bids. Conversely, if the market price limit rate decreases, further analysis is needed to determine the reasons, such as whether the price limit is set too high, causing market prices to generally fall below the limit, or whether there have been other changes in the market supply and demand relationship.

[0134] 4) Market clearing price limit assessment If the market-clearing price attainment rate rises significantly after the price limit is implemented, it indicates that the price limit measures have had a significant impact on the market-clearing price and have effectively curbed excessively high prices.

[0135] Conversely, if the market clearing price limit rate declines, it is necessary to analyze the reasons in depth, such as whether the price limit level is set unreasonably, resulting in market clearing prices generally being lower than the limit price, or whether there have been other unforeseen changes in the market supply and demand relationship.

[0136] 5) Evaluation of the price limit-volume elasticity coefficient The elasticity coefficient is evaluated based on the price limit-volume elasticity coefficient calculated in step (3): A high price limit-volume elasticity coefficient indicates that price limits have a significant impact on trading volume, and adjustments to the price limit can cause substantial changes in trading volume. This suggests that market participants are highly sensitive to price limits, and that price limits play a crucial role in regulating market supply and demand.

[0137] Conversely, if the price limit-volume elasticity coefficient is small, it indicates that the price limit measure has a limited impact on trading volume, and the adjustment of the price limit has failed to cause a significant change in trading volume. This means that the market supply and demand relationship is relatively rigid, or that market participants are not sensitive enough to the price limit measure.

[0138] 6) Evaluation of the price limit-average price elasticity coefficient The average price elasticity coefficient is evaluated based on the price limit-average price elasticity coefficient calculated in step S3: A high price limit-to-average price elasticity coefficient indicates that price limits have a significant impact on market prices, and adjustments to price limits can cause substantial fluctuations in the average market price. This reflects the high sensitivity of market participants to price changes, and the important role that price limits play in regulating market prices.

[0139] Conversely, a low price limit-to-average price elasticity coefficient indicates that the price limit measure has a small impact on market prices, and adjustments to the price limit have failed to cause a significant change in the average market price. This implies that market prices are more influenced by other factors, or that market participants are not sensitive enough to the price limit measure.

[0140] This invention, through scientific methods and a comprehensive indicator system, can accurately assess the impact of price limit adjustments on the inter-provincial electricity spot market within different cycles.

[0141] First, the system can capture dynamic changes in the market in real time, reflect the true situation of the market in a timely manner, and avoid decision-making errors caused by information lag.

[0142] Secondly, through the built-in comprehensive indicator calculation module, the system can automatically calculate multiple key indicators, such as transaction volume, average transaction price, and market quotation limit rate, providing managers with comprehensive data support and enabling them to more accurately judge the market's operating status.

[0143] Furthermore, the system can evaluate the price limit-volume elasticity coefficient and the price limit-average price elasticity coefficient in real time, promptly detect abnormal market reactions, such as anomalous effects, and thus help managers take corresponding regulatory measures to ensure the stable operation of the market.

[0144] In addition, the system supports retrospective analysis of historical data, providing strong data support for formulating more scientific and reasonable price control policies.

[0145] Those skilled in the art will understand that various aspects of the present invention can be implemented as systems, methods, or program products. Therefore, various aspects of the present invention can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or a combination of hardware and software aspects, collectively referred to herein as a "circuit," "module," or "platform."

[0146] Example 2 This invention provides a comprehensive evaluation system for the effect of multi-cycle inter-provincial electricity spot price limits. This system can be used to implement the aforementioned comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits. Specifically, the comprehensive evaluation system for the effect of multi-cycle inter-provincial electricity spot price limits includes a data module, an indicator module, a system module, and an evaluation module.

[0147] The data module acquires basic data from the inter-provincial electricity spot market. The indicator module establishes a comprehensive evaluation indicator model for the effectiveness of inter-provincial electricity spot price limits based on basic data from the inter-provincial electricity spot market. The system module establishes a comprehensive evaluation index system for the effect of inter-provincial electricity spot price limits based on the constructed comprehensive evaluation index model, and calculates the evaluation index for the effect of inter-provincial electricity spot price limits in each period. The evaluation module uses evaluation indicators for the effectiveness of inter-provincial electricity spot price limits in each cycle to assess the price limit effect.

[0148] Example 3 This invention provides a terminal device comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, graphics processing units (GPUs), tensor processing units (TPUs), digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to achieve corresponding method flows or corresponding functions. The processor described in this embodiment can be used in the operation of a multi-cycle inter-provincial electricity spot price limit effect comprehensive evaluation method, including: Obtain basic data on the inter-provincial electricity spot market; establish a comprehensive evaluation index model for the effectiveness of inter-provincial electricity spot price limits based on the basic data of the inter-provincial electricity spot market; establish a comprehensive evaluation index system for the effectiveness of inter-provincial electricity spot price limits based on the constructed comprehensive evaluation index model, and calculate the evaluation index for the effectiveness of inter-provincial electricity spot price limits for each period; use the evaluation index for the effectiveness of inter-provincial electricity spot price limits for each period to evaluate the effectiveness of price limits.

[0149] Please see Figure 2 The terminal device is a computer device. In this embodiment, the computer device 60 includes a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When executed by the processor 61, the computer program 63 implements the comprehensive evaluation method for the multi-cycle inter-provincial electricity spot price limit effect in this embodiment. To avoid repetition, these details are not elaborated here. Alternatively, when executed by the processor 61, the computer program 63 implements the functions of each model / unit in the comprehensive evaluation system for the multi-cycle inter-provincial electricity spot price limit effect in this embodiment. To avoid repetition, these details are not elaborated here.

[0150] Computer device 60 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. Computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will understand that... Figure 2 This is merely an example of computer device 60 and does not constitute a limitation on computer device 60. It may include more or fewer components than shown, or combine certain components, or different components. For example, computer device may also include input / output devices, network access devices, buses, etc.

[0151] The processor 61 may be a Central Processing Unit (CPU), or other general-purpose processors, graphics processing units (GPUs), tensor processing units (TPUs), digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0152] The memory 62 can be an internal storage unit of the computer device 60, such as a hard disk or RAM of the computer device 60. The memory 62 can also be an external storage device of the computer device 60, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., provided on the computer device 60.

[0153] Furthermore, the memory 62 may include both internal storage units of the computer device 60 and external storage devices. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 can also be used to temporarily store data that has been output or will be output.

[0154] Please see Figure 3 The terminal device is an electronic device 600, which is manifested in the form of a general-purpose computing device. The components of the electronic device may include, but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including storage unit 620 and processing unit 610), a display unit 640, etc.

[0155] The storage unit stores program code, which can be executed by the processing unit 610 to perform the steps described in the method section of this specification according to various exemplary embodiments of the present invention. For example, the processing unit 610 can perform actions such as... Figure 1 The steps are shown in the figure.

[0156] Storage unit 620 may include a readable medium in the form of a volatile storage unit, such as random access memory (RAM) 6201 and / or cache memory 6202, and may further include a read-only memory (ROM) 6203.

[0157] Storage unit 620 may also include a program / utility 6204 having a set (at least one) program module 6205, such program module 6205 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0158] Bus 630 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the multiple bus structures.

[0159] Electronic device 600 can also communicate with one or more external devices 700 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 600, and / or with any device that enables electronic device 600 to communicate with one or more other computing devices (e.g., router, modem). This communication can be performed via input / output interface 650. Furthermore, electronic device 600 can also communicate with one or more networks (e.g., local area network, wide area network, and / or public network, such as the Internet) via network adapter 660. Network adapter 660 can communicate with other modules of electronic device 600 via bus 630. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0160] Example 4 This invention also provides a storage medium, specifically a computer-readable storage medium, which is a memory device in a terminal device for storing programs and data. It is understood that the computer-readable storage medium here can include both built-in storage media in the terminal device and extended storage media supported by the terminal device; it can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor, which can be one or more computer programs (including program code). More specific examples of the computer-readable storage medium include: an electrical connection with one or more wires, a portable disk, a hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical fiber, portable compact disk read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0161] Computer-readable storage media also include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable storage medium can also be any readable medium other than a readable storage medium that can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium can be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, radio frequency, etc., or any suitable combination thereof.

[0162] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0163] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the comprehensive evaluation method for the multi-cycle inter-provincial electricity spot price limit effect in the above embodiments; one or more instructions in the computer-readable storage medium are loaded and executed by the processor in the following steps: Obtain basic data on the inter-provincial electricity spot market; establish a comprehensive evaluation index model for the effectiveness of inter-provincial electricity spot price limits based on the basic data of the inter-provincial electricity spot market; establish a comprehensive evaluation index system for the effectiveness of inter-provincial electricity spot price limits based on the constructed comprehensive evaluation index model, and calculate the evaluation index for the effectiveness of inter-provincial electricity spot price limits for each period; use the evaluation index for the effectiveness of inter-provincial electricity spot price limits for each period to evaluate the effectiveness of price limits.

[0164] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0165] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0166] Simulation verification and experimental data analysis 1. Simulation Scene Construction Data source: Based on the operating data of spot markets in Shanxi, Shandong, and Inner Mongolia in 2024, the impact of adjusting the price limit threshold on the market is simulated. The scenario is set as follows: Price limit adjustment experiment: The upper limit of the price is lowered from 1.5 yuan / kWh to 1.2 yuan / kWh, and the lower limit is raised from 0.1 yuan / kWh to 0.15 yuan / kWh. Market behavior changes are observed from January 2024 to March 2025.

[0167] New energy fluctuation scenario: Simulate extreme conditions such as a sudden drop of 30% in wind and solar power output and a surge of 20% in load, and compare the response effect of the price limit mechanism.

[0168] 2. Experimental Data and Results Analysis Analysis of changes in trading volume

[0169] The reduction in the price ceiling led to a decrease in market trading volume recently (elasticity coefficient -0.45), but the real-time market saw a counter-trend increase in trading volume as market participants sought alternative trading channels (elasticity coefficient +0.35). This indicates that price ceiling adjustments need to be combined with cross-cycle coordination mechanisms to avoid a contraction in liquidity in a single market.

[0170] Analysis of average transaction price and compliance rate

[0171] After the price limit threshold was tightened, the average market price decreased by 8.2%, and the bid and clearing rates significantly decreased, verifying the effectiveness of the price limit mechanism in curbing malicious bidding.

[0172] In scenarios where wind and solar power output plummeted, the peak rate of bids reaching the limit dropped from 25% to 12%, indicating that the price limit mechanism still has the ability to stabilize prices under extreme conditions.

[0173] Elasticity coefficient sensitivity verification

[0174] The elasticity coefficient increases significantly with the increase of new energy penetration rate (from 0.62 to 1.15), indicating that the price limit is more sensitive to the average price regulation under the high proportion of new energy scenarios.

[0175] The negative volume elasticity coefficient (-0.92) indicates that when new energy is booming, excessively strict price limits may inhibit the cross-provincial consumption capacity, and the threshold needs to be dynamically adjusted.

[0176] This invention comprehensively considers the impact of price limit adjustments on the average price of inter-provincial electricity spot market within different cycles. It automatically calculates transaction volume, average transaction price, market bid-to-limit rate, market clearing price-to-limit rate, price limit-volume elasticity coefficient, and price limit-average price elasticity coefficient for each cycle based on historical data and market dynamics. Furthermore, it performs real-time evaluation of the price limit-volume elasticity coefficient and the price limit-average price elasticity coefficient according to preset grading standards. It can promptly detect abnormal market reactions, thereby helping managers take corresponding regulatory measures to ensure stable market operation. In addition, it supports retrospective analysis of historical data, providing strong data support for formulating more scientific and reasonable price limit policies.

[0177] In summary, this invention presents a comprehensive evaluation method and system for the effectiveness of multi-period inter-provincial electricity spot price limits. By constructing a multi-period price limit effectiveness evaluation model and combining dynamic elasticity coefficients with wide-area collaborative technology, it solves core problems of traditional mechanisms such as lag response in extreme scenarios (adjustment cycle shortened by 80%), cross-period arbitrage (price difference risk reduced by 40%), and renewable energy consumption (curtailment rate reduced by 6.3%). Simulation and case studies demonstrate that this method can improve market stability and resource allocation efficiency, providing key technical support for the construction of a unified national electricity market.

[0178] The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solution based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits, characterized in that, Includes the following steps: Obtain basic data on the inter-provincial electricity spot market; A comprehensive evaluation index model for the effectiveness of inter-provincial electricity spot price limits is established based on basic data from the inter-provincial electricity spot market. Based on the constructed comprehensive evaluation index model of the inter-provincial electricity spot price limit effect, a comprehensive evaluation index system for the inter-provincial electricity spot price limit effect is established, and the evaluation index of the inter-provincial electricity spot price limit effect for each period is calculated. The effectiveness of the price limit was evaluated using evaluation indicators for the inter-provincial electricity spot price limit in each cycle.

2. The comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 1, characterized in that, The basic data for the inter-provincial electricity spot market includes the transaction volume, average transaction price, transaction node bid price, and transaction node clearing price.

3. The comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 1, characterized in that, The comprehensive evaluation index model for the effectiveness of inter-provincial electricity spot price limits includes multi-period inter-provincial spot transaction volume. Average inter-provincial spot transaction price over multiple periods Market price limit attainment rate Market clearing price limit rate Price limit-volume elasticity coefficient model and price limit-average price elasticity coefficient model.

4. The comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 3, characterized in that, Multi-period inter-provincial spot transaction volume for: in, This represents the inter-provincial spot trading volume on day t. Multi-period inter-provincial spot transaction average price for: in, The inter-provincial spot clearing price on day t. This represents the inter-provincial spot trading volume on day t. Market quotation reach rate for: in, The number of bids that triggered the price limit. This represents the total number of quotes. Market clearing price reaches limit rate for: in, This refers to the number of times the price exceeds a preset price limit. This represents the total number of transactions. The price limit-volume elasticity coefficient model is as follows: in, The price limit minus volume elasticity coefficient within period t. , This represents the trading volume before and after the price limit was set. This represents the change in the price limit threshold. This is the price limit threshold; The price limit-average price elasticity coefficient model is as follows: in, The price elasticity coefficient between the limit price and the average price within period t. The change in average transaction price for different price limits. The average price of transactions within the price limit. This represents the change in the price limit threshold. This is the price limit threshold.

5. The comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 1, characterized in that, The evaluation indicators for the effectiveness of inter-provincial electricity spot price limits for each cycle include daily evaluation indicators, monthly evaluation indicators, and annual evaluation indicators. The daily evaluation indicators for the effectiveness of inter-provincial spot price limits include: Daily transaction volume, daily average transaction price, daily market quotation limit rate, market clearing price limit rate, daily price limit-volume elasticity coefficient, and daily price limit-average price elasticity coefficient; The monthly evaluation indicators for the effectiveness of inter-provincial spot price limits include: Monthly transaction volume, monthly average transaction price, monthly market quotation limit rate, monthly market clearing price limit rate, monthly price limit-transaction volume elasticity coefficient, and monthly price limit-average price elasticity coefficient; The annual evaluation indicators for the effectiveness of inter-provincial spot price limits include: Annual transaction volume, annual average transaction price, annual market quotation limit rate, market clearing price limit rate, annual price limit-transaction volume elasticity coefficient, and annual price limit-average price elasticity coefficient.

6. The comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 5, characterized in that, Daily market price limit reached : Market clearing price reaches limit rate : Daily price limit - volume elasticity coefficient : Daily price limit - average price elasticity coefficient : in, The number of daily price quotes that hit the price limit. Total number of quotes per day The number of transactions where the daily clearing price exceeds the preset price limit. Total number of transactions per day This refers to the trading volume after the daily price limit was set. This represents the trading volume before the daily price limit was set. This represents the daily change in the price limit threshold. The daily price limit threshold. This represents the change in the average transaction price under different daily price limits. The average transaction price before the daily price limit was set; Monthly transaction volume : Average monthly transaction price : Monthly market price limit reached : Monthly market clearing price reaches limit rate : Monthly price limit - volume elasticity coefficient : Monthly price limit - average price elasticity coefficient : in, Daily transaction volume The average daily transaction price. This represents the total number of quotes for the month. The number of monthly quotes that hit the price limit. This represents the total number of transactions in the month. This refers to the number of times the monthly clearance price exceeds a preset price limit. This represents the trading volume prior to the monthly price cap. This represents the trading volume after the monthly price limit was set. This represents the monthly price limit threshold change. The monthly price limit threshold. This represents the change in average transaction price under different price limits each month. This represents the average transaction price before the monthly price limit was set. Annual transaction volume : Average annual transaction price : Annual market quotation compliance rate : Market clearing price reaches limit rate : Annual price limit - trading volume elasticity coefficient : Annual price elasticity coefficient : in, The number of bids that hit the price limit in a given year. This represents the total number of quotes received throughout the year. This refers to the number of times the annual clearing price exceeds a preset price limit. This represents the total number of transactions completed in a year. This refers to the transaction volume after the annual price cap. This refers to the trading volume before the annual price cap. This represents the change in average transaction price under different annual price limits. This represents the average transaction price before the annual price cap. This represents the annual price limit threshold change. This is the annual price limit threshold.

7. The comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 1, characterized in that, The evaluation of the effectiveness of price limits includes: transaction volume evaluation, average transaction price evaluation, market bid reaching the limit rate evaluation, market clearing price reaching the limit rate evaluation, price limit-transaction volume elasticity coefficient evaluation, and price limit-average price elasticity coefficient evaluation.

8. The comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 7, characterized in that, The specific assessment of transaction volume is as follows: The impact of price limits on market supply and demand balance can be judged by the changes in trading volume over different periods. If the trading volume decreases after the price limit is implemented, it indicates that the price limit has suppressed some trading demand. If the trading volume continues to grow, it means that market participants have a high acceptance of the price limit measures or that the price limit level is reasonable.

9. The comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 7, characterized in that, Average transaction price assessment By combining the changes in the average spot transaction price between provinces over multiple periods, we can determine whether the price control measures have guided market price trends and whether they have achieved the expected regulatory objectives.

10. The comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 7, characterized in that, Market quotation achievement rate assessment If the market bid-to-limit rate rises after the price limit is implemented, the price limit measure will curb excessively high bids. If the market price limit rate decreases, it is necessary to determine whether the price limit level is set too high, causing market prices to fall below the price limit, or whether the market supply and demand relationship has changed.

11. The comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 7, characterized in that, Market clearing price limit assessment: If the market clearing price attainment rate rises after the price limit is implemented, it indicates that the price limit measures have an impact on the market clearing price. If the market clearing price reaches the limit rate and declines, it is judged that the price limit level is set unreasonably, resulting in the market clearing price falling below the limit price, or that other unforeseen changes have occurred in the market supply and demand relationship.

12. The comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 7, characterized in that, The elasticity coefficient is evaluated based on the price limit-volume elasticity coefficient: If the price limit-volume elasticity coefficient is greater than the set value, the price limit measure will affect the trading volume. If the price limit-volume elasticity coefficient is less than the set value, the price limit measure will have no impact on the trading volume.

13. The comprehensive evaluation method for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 7, characterized in that, The price limit-average price elasticity coefficient is evaluated based on the calculated price limit-average price elasticity coefficient: If the price limit-average price elasticity coefficient is higher than the set threshold, the price limit measures will have an impact on market prices. If the price limit-average price elasticity coefficient is lower than the set threshold, the price limit measure will have no impact on market prices.

14. A comprehensive evaluation system for the effect of multi-period inter-provincial electricity spot price limits, characterized in that, include: The data module acquires basic data for the inter-provincial electricity spot market; The indicator module establishes a comprehensive evaluation indicator model for the effectiveness of inter-provincial electricity spot price limits based on basic data from the inter-provincial electricity spot market. The system module establishes a comprehensive evaluation index system for the effect of inter-provincial electricity spot price limits based on the constructed comprehensive evaluation index model, and calculates the evaluation index for the effect of inter-provincial electricity spot price limits in each period. The evaluation module uses evaluation indicators for the effectiveness of inter-provincial electricity spot price limits in each cycle to assess the price limit effect.

15. The comprehensive evaluation system for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 14, characterized in that, The comprehensive evaluation index model for the effectiveness of inter-provincial electricity spot price limits includes multi-period inter-provincial spot transaction volume. Average inter-provincial spot transaction price over multiple periods Market price limit attainment rate Market clearing price limit rate Price limit-volume elasticity coefficient model and price limit-average price elasticity coefficient model.

16. The comprehensive evaluation system for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 15, characterized in that, Multi-period inter-provincial spot transaction volume for: in, This represents the inter-provincial spot trading volume on day t. Multi-period inter-provincial spot transaction average price for: in, The inter-provincial spot clearing price on day t. This represents the inter-provincial spot trading volume on day t. Market quotation reach rate for: in, The number of bids that triggered the price limit. This represents the total number of quotes. Market clearing price reaches limit rate for: in, This refers to the number of times the price exceeds a preset price limit. This represents the total number of transactions. The price limit-volume elasticity coefficient model is as follows: in, The price limit minus volume elasticity coefficient within period t. , This represents the trading volume before and after the price limit was set. This represents the change in the price limit threshold. This is the price limit threshold; The price limit-average price elasticity coefficient model is as follows: in, The price elasticity coefficient between the limit price and the average price within period t. The change in average transaction price for different price limits. The average price of transactions within the price limit. This represents the change in the price limit threshold. This is the price limit threshold.

17. The comprehensive evaluation system for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 14, characterized in that, The evaluation indicators for the effectiveness of inter-provincial electricity spot price limits for each cycle include daily evaluation indicators, monthly evaluation indicators, and annual evaluation indicators. The daily evaluation indicators for the effectiveness of inter-provincial spot price limits include: Daily transaction volume, daily average transaction price, daily market quotation limit rate, market clearing price limit rate, daily price limit-volume elasticity coefficient, and daily price limit-average price elasticity coefficient; The monthly evaluation indicators for the effectiveness of inter-provincial spot price limits include: Monthly transaction volume, monthly average transaction price, monthly market quotation limit rate, monthly market clearing price limit rate, monthly price limit-transaction volume elasticity coefficient, and monthly price limit-average price elasticity coefficient; The annual evaluation indicators for the effectiveness of inter-provincial spot price limits include: Annual transaction volume, annual average transaction price, annual market quotation limit rate, market clearing price limit rate, annual price limit-transaction volume elasticity coefficient, and annual price limit-average price elasticity coefficient.

18. The comprehensive evaluation system for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 17, characterized in that, Daily market price limit reached : Market clearing price reaches limit rate : Daily price limit - volume elasticity coefficient : Daily price limit - average price elasticity coefficient : in, The number of daily price quotes that hit the price limit. Total number of quotes per day The number of transactions where the daily clearing price exceeds the preset price limit. Total number of transactions per day This refers to the trading volume after the daily price limit was set. This represents the trading volume before the daily price limit was set. This represents the daily change in the price limit threshold. The daily price limit threshold. This represents the change in the average transaction price under different daily price limits. The average transaction price before the daily price limit was set; Monthly transaction volume : Average monthly transaction price : Monthly market price limit reached : Monthly market clearing price reaches limit rate : Monthly price limit - volume elasticity coefficient : Monthly price limit - average price elasticity coefficient : in, Daily transaction volume The average daily transaction price. This represents the total number of quotes for the month. The number of monthly quotes that hit the price limit. This represents the total number of transactions in the month. This refers to the number of times the monthly clearance price exceeds a preset price limit. This represents the trading volume prior to the monthly price cap. This represents the trading volume after the monthly price limit was set. This represents the monthly price limit threshold change. The monthly price limit threshold. This represents the change in average transaction price under different price limits each month. This represents the average transaction price before the monthly price limit was set. Annual transaction volume : Average annual transaction price : Annual market quotation compliance rate : Market clearing price reaches limit rate : Annual price limit - trading volume elasticity coefficient : Annual price elasticity coefficient : in, The number of bids that hit the price limit in a given year. This represents the total number of quotes received throughout the year. This refers to the number of times the annual clearing price exceeds a preset price limit. This represents the total number of transactions completed in a year. This refers to the transaction volume after the annual price cap. This refers to the trading volume before the annual price cap. This represents the change in average transaction price under different annual price limits. This represents the average transaction price before the annual price cap. This represents the annual price limit threshold change. This is the annual price limit threshold.

19. The comprehensive evaluation system for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 14, characterized in that, The evaluation of the effectiveness of price limits includes: transaction volume evaluation, average transaction price evaluation, market bid reaching the limit rate evaluation, market clearing price reaching the limit rate evaluation, price limit-transaction volume elasticity coefficient evaluation, and price limit-average price elasticity coefficient evaluation.

20. The comprehensive evaluation system for the effect of multi-cycle inter-provincial electricity spot price limits according to claim 19, characterized in that, The specific assessment of transaction volume is as follows: The impact of price limits on market supply and demand balance can be judged by the changes in trading volume over different periods. If the trading volume decreases after the price limit is implemented, it indicates that the price limit has suppressed some trading demand; if the trading volume continues to grow, it means that market participants have a high acceptance of the price limit measures or that the price limit level is reasonable. Average transaction price assessment: By combining the changes in the average inter-provincial spot transaction price over multiple periods, we can determine whether the price control measures have guided market price trends and whether they have achieved the expected regulatory objectives. Market quotation fulfillment rate assessment: If the market bid-to-limit rate rises after the price limit is implemented, the price limit measure will curb excessively high bids. If the market price limit rate decreases, it is necessary to determine whether the price limit level is set too high, causing market prices to fall below the price limit, or whether the market supply and demand relationship has changed. Market clearing price limit assessment: If the market clearing price attainment rate rises after the price limit is implemented, it indicates that the price limit measures have an impact on the market clearing price. If the market clearing price reaches the limit rate decreases, it is judged that the price limit level is set unreasonably, resulting in the market clearing price being lower than the limit price, or other unforeseen changes have occurred in the market supply and demand relationship; The elasticity coefficient is evaluated based on the price limit-volume elasticity coefficient: If the price limit-volume elasticity coefficient is greater than the set value, the price limit measure will affect the trading volume. If the price limit-volume elasticity coefficient is less than the set value, the price limit measure will have no impact on the trading volume. The price limit-average price elasticity coefficient is evaluated based on the calculated price limit-average price elasticity coefficient: If the price limit-average price elasticity coefficient is higher than the set threshold, the price limit measures will have an impact on market prices. If the price limit-average price elasticity coefficient is lower than the set threshold, the price limit measure will have no impact on market prices.

21. A computer-readable storage medium for storing one or more programs, characterized in that, The one or more programs include instructions that, when executed by a computing device, cause the computing device to perform the method of any one of claims 1 to 13.

22. A computing device, characterized in that, include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including steps for performing the method of any one of claims 1 to 13.

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