Unbalanced fund allocation and return calculation method and system based on contract market and spot market coupling settlement

Abstract

The invention discloses an unbalanced fund sharing and returning calculation method and system based on contract market and spot market coupling settlement. The method comprises the following steps: establishing a generator set and user electric energy charge settlement method based on a market mode and a non-market mode; establishing an unbalanced fund allocation and return processing method based on cost classification; and establishing an expense settlement management mechanism based on data management and market risk identification. According to the scheme of the invention, electric energy and electricity charge settlement and unbalanced fund processing in a double-track system bilateral electricity market are realized.

Description

Technical Field

[0001] The present invention belongs to the field of power market settlement, and in particular relates to a method and system for calculating imbalance fund allocation and return based on settlement of coupled contract market and spot market. Background Art

[0002] With the advancement of power system reform, the power market presents a situation where a dual-track system of planning and market coexist. Against this background, the operation and development of bilateral power markets face a series of severe challenges. In the power trading process, the guidance of power and electricity charges has encountered many obstacles. Its complex cost structure and the diverse price formation mechanism are difficult to effectively connect, resulting in poor circulation of electricity charges. In terms of market balance, the allocation of imbalance costs is even more of a thorny problem, involving the interest game of many market players and complex calculation logic.

[0003] The existing electricity market settlement mechanism has achieved certain results in some local areas or specific scenarios. However, a comprehensive and systematic integration plan has not been formed for the settlement mechanism of the bilateral electricity market under the dual-track system. In particular, there are obvious shortcomings in the in-depth analysis of the mechanism of the generation of unbalanced funds and how to properly handle unbalanced funds. For example, the existing technology does not involve the inherent logic and reasonable allocation and return principles of ancillary service fees and deviation assessment fees. This lack directly leads to the possibility that power grid companies may be forced to bear excessive risks and cost pressures during market operations, seriously undermining the fair competition environment that the electricity market should have, and thus weakening the stability of the entire electricity market. In summary, designing a scientific and reasonable settlement method for coupling the contract market and the spot market, which can accurately and effectively handle unbalanced funds, has become a key issue that needs to be urgently addressed in the current power market. Summary of the invention

[0004] In order to address the deficiencies in the prior art, the present invention provides a method and system for calculating the allocation and return of imbalance funds based on the coupled settlement of the contract market and the spot market, so as to solve the difficult problems of electric energy and electricity fee settlement and imbalance fund processing in the bilateral power market under the dual-track system, improve the fairness, rationality and stability of power market settlement, and promote market players to actively participate in power market transactions.

[0005] In order to solve the above technical problems, the present invention adopts the following technical solutions.

[0006] The present invention first discloses a method for calculating the unbalanced fund allocation and return based on the coupled settlement of the contract market and the spot market, the method comprising the following steps:

[0007] Step 1: Establish the electricity bill settlement model between the generator set and the user under the market mode and the non-market mode respectively;

[0008] Step 2: For power generators and users, build a market-based auxiliary service fee allocation and refund processing model and a deviation assessment fee allocation and refund processing model to achieve imbalance fund allocation and refund processing based on fee classification;

[0009] Step 3: Build a data management platform, obtain data from generators and users, store them in categories, integrate them with relevant systems of the electricity bill settlement system, identify the risks of electricity bill settlement between generators and users under market and non-market modes, and automatically verify the electricity bill settlement results.

[0010] The present invention further includes the following preferred embodiments:

[0011] The electric energy and electricity fee settlement models for the generator set and the user under the market mode and the non-market mode are respectively established, further comprising:

[0012] Step 1.1: Market-based generator settlement:

[0013] (1) Determine the market-oriented power generation unit set Ω market :

[0014] Ω market ={thermal,gas,nuclear,hydro,wind,solar}

[0015] Among them, thermal, gas, nuclear, hydro, wind, and solar are the coordinated coal, gas, nuclear, hydro, wind, and solar units respectively;

[0016] (2) For each market-based generating unit i∈Ω market , the electricity fee settlement is carried out according to the principles of day-ahead basis, real-time difference and contract price difference;

[0017] (3) Calculate the day-ahead market electricity price

[0018]

[0019] in is the day-ahead market node electricity price of unit i in period t, is the day-ahead market electricity of unit i in period t;

[0020] (4) Calculate the real-time market differential electricity charges

[0021]

[0022] is the real-time market node electricity price of unit i in period t, The daily measured on-grid electricity of unit i in time period t;

[0023] (5) Calculate the difference in electricity charges in the contract market

[0024]

[0025] in are the government authorized contract electricity price, power generation right transaction price and ordinary direct transaction price of unit i in period t, are the corresponding contract electricity quantities;

[0026] Step 1.2: Settlement of non-market generating units:

[0027] (1) Determine the set of non-market generating units Ω non-market :

[0028] Ω non-market ={external,self-supply}

[0029] Among them, external refers to purchased electricity, and self-supply refers to self-provided power plants;

[0030] (2) For each non-market generating unit i∈Ω non-market , and its electricity fee settlement model is:

[0031]

[0032] in, is the catalog price of non-market generating unit i, is the metered power generation of non-market unit i in the time period;

[0033] Step 1.3: Market-based user settlement:

[0034] (1) Determine the market-oriented user set Ψ market

[0035] Ψ market ={Wholesale,TradingLtd,Agent}

[0036] Wholesale, Trading Ltd, and Agent are market users, including wholesale market users, power sales companies, and industrial and commercial users who purchase electricity through power grid agents;

[0037] (2) For each market-oriented user j∈Ψ market The electricity fee includes three parts: day-ahead market fee, real-time market fee and contract market fee. The settlement model is:

[0038]

[0039] is the day-ahead market electricity price of market-based user j during period t:

[0040]

[0041] is the day-ahead market electricity price of market-based user j during period t:

[0042]

[0043] is the day-ahead market electricity price of market-based user j during period t:

[0044]

[0045] in, They are the day-ahead market electricity consumption, real-time metered electricity consumption and contract market electricity consumption of market-based user j in period t;

[0046] Step 1.4: Non-market user settlement:

[0047] (1) Determine the non-market user set Ψ non-market

[0048] Ψ non-market ={Resident,Agricultural}

[0049] Among them, Resident and Agricultural are residents and agricultural users who are not market users;

[0050] (2) For each non-marketized user j∈Ψ non-market , and its electricity fee settlement model is:

[0051]

[0052] in is the catalogue electricity price of non-market user j in period t, is the actual metered electricity consumption of user j in period t.

[0053] The construction of the market-based auxiliary service fee allocation and refund processing model further includes:

[0054] Step 2.11: According to the single-day provincial frequency regulation demand released by the dispatch center, take the unit as the reporting unit to participate in the frequency regulation quotation; calculate the j-th frequency regulation performance index of unit i and the single frequency regulation performance index

[0055]

[0056] in, is the jth frequency modulation rate of unit i, is the standard frequency regulation rate of the unit, is the j-th frequency regulation accuracy of unit i, It is the standard adjustment accuracy;

[0057] Step 2.12: Computer group comprehensive frequency modulation index

[0058]

[0059] in is the j-th forward frequency modulation mileage of unit i;

[0060] Step 2.13: Compensation income from frequency modulation of computer group

[0061]

[0062] in, are respectively the positive and negative frequency regulation mileage of the unit, K d is the negative FM penalty factor, Clearing prices for the FM market;

[0063] Step 2.14: Calculate backup ancillary service revenue

[0064]

[0065] in, is the compensation standard for standby ancillary services (yuan / MW), C i The adjustable capacity of the unit on that day;

[0066] Step 2.15: Calculate the total market-based ancillary service costs of the group

[0067]

[0068] Step 2.16: The ancillary service fee is shared by market users based on the actual metered electricity consumption. The sharing model is:

[0069]

[0070] in, The ancillary service costs allocated to market user j; is the actual metered electricity consumption of user j in settlement period t.

[0071] The construction of the allocation and refund processing model for deviation assessment expenses further includes:

[0072] Step 2.21: Calculate the deviation assessment cost on the power generation side

[0073] For market-based power generation entity i, when hour,

[0074]

[0075] when hour,

[0076]

[0077] when hour,

[0078]

[0079] in, is the market contract decomposition quantity of power generation entity i in this cycle, ΔQ i is the deviation between the actual power generation and the contracted power generation, ρ -DA The unit electricity deviation electricity fee base value;

[0080] Step 2.22: Establish a model for allocating and returning the cost of power generation deviation assessment; the power generation deviation assessment cost will be returned to market users in proportion to the actual metered electricity consumption:

[0081]

[0082] in, Return fees for the power generation deviation assessment of market-based user j;

[0083] Step 2.23: Calculate user-side deviation assessment fees

[0084] For user j, when hour,

[0085]

[0086] when hour,

[0087]

[0088] when hour,

[0089]

[0090] when hour,

[0091]

[0092] in is the contractual power consumption of user j in the settlement period, ΔQ j The deviation between the actual power consumption and the contracted power consumption of user j during the settlement period;

[0093] Step 2.24: Establish a user-side deviation assessment cost allocation and refund model. The user-side deviation assessment cost is allocated to the power generation enterprise according to the proportion of authorized contract electricity. The allocation model is:

[0094]

[0095] in, Return the cost of user deviation assessment for generator set i.

[0096] The data management platform is constructed to obtain data from the generator set and the user end and store the data in a classified manner, further comprising:

[0097] Build a centralized data management platform to store and manage various types of relevant data of generator sets and users. Obtain data from power generation companies, power grid companies, and user-side data sources in real time or regularly through data acquisition interfaces, including unit operation data, user electricity consumption data, market transaction data, and cost accounting data; clean, organize, and verify the collected data; classify and store data, and archive them according to generator set type, user type, and time series dimensions.

[0098] The integration with the related systems of the electric energy and electricity fee settlement system further includes:

[0099] Integrate the electric energy and electricity fee settlement system with the power market trading platform, power grid dispatching system, and financial management system, develop standard data interfaces, and realize data interaction and sharing among systems; conduct system joint debugging tests, simulate data interaction and settlement business processes in different scenarios, and verify system integration.

[0100] The identification of the settlement risk of electricity energy and electricity charges between the generator set and the user under the market mode and the non-market mode further includes:

[0101] Conduct quantitative analysis on market risks, policy risks, data risks and operational risks, analyze the probability distribution of price fluctuations in the electricity market and the financial impact of price fluctuations on generators and users through historical data and market forecasting models; establish a data risk assessment model to assess the degree of deviation of settlement results caused by data errors.

[0102] The present invention also discloses a system for calculating unbalanced funds allocation and return based on the coupled settlement of the contract market and the spot market, which utilizes the above-mentioned method for calculating unbalanced funds allocation and return based on the coupled settlement of the contract market and the spot market, comprising:

[0103] The electric energy and electricity fee settlement module is used to establish the electric energy and electricity fee settlement models between the generator set and the user in the market mode and the non-market mode respectively;

[0104] The fund allocation and return processing module is used to build a market-based auxiliary service fee allocation and return processing model and a deviation assessment fee allocation and return processing model for power generation units and users, and realize the imbalance fund allocation and return processing based on fee classification;

[0105] The data management and risk identification module is used to build a data management platform, obtain data from generators and users and store them in categories, integrate with relevant systems of the electric energy and electricity fee settlement system, identify the risks of electric energy and electricity fee settlement between generators and users under market and non-market modes, and automatically verify the electricity fee settlement results.

[0106] Accordingly, the present application also discloses a terminal, including a processor and a storage medium;

[0107] The storage medium is used to store instructions;

[0108] The processor is used to operate according to the instructions to execute the steps of the imbalance fund allocation and return calculation method based on the aforementioned settlement of the coupled contract market and the spot market.

[0109] Correspondingly, the present application also discloses a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the aforementioned method for calculating the imbalance fund allocation and return based on the coupled settlement of the contract market and the spot market are implemented.

[0110] Compared with the prior art, the present invention provides a method and system for calculating the unbalanced fund allocation and return based on the coupled settlement of the contract market and the spot market, and the beneficial effects are:

[0111] (1) Accurate and comprehensive electricity bill settlement has been achieved. In terms of electricity bill settlement between generators and users based on market and non-market models, a refined settlement system has been built for different types of generators (such as various energy units) and users (different market models, different industry types), laying a solid foundation for the stable operation of the entire power market, ensuring that the interests of all parties are reasonably reflected in the settlement process, and promoting the orderly conduct of power market transactions;

[0112] (2) The handling of unbalanced funds is more scientific and reasonable. A highly scientific and reasonable model based on cost classification has been constructed. For market-based ancillary service costs, full consideration is given to the actual demand for ancillary services, market roles and influencing factors of different users. By deeply analyzing the relationship between different users' electricity consumption behaviors and ancillary service needs, a more targeted allocation model has been established to ensure that the allocation of ancillary service costs is more fair and just. For the deviation assessment costs on the generation / consumption side, the principle of "whoever generates it, is responsible for it" is clarified in detail, and the standards and procedures for fee refunds are refined. The calculation and refund of deviation assessment costs are more accurate and reasonable, which effectively avoids the damage to the interests of market entities caused by unreasonable allocation and refund, ensures the fairness and stability of the power market, and encourages market entities to actively optimize their own behavior to reduce deviations.

[0113] (3) Efficient and stable fee settlement management. In terms of fee settlement management mechanism design, by establishing a system based on data management and market risk identification, the efficiency and stability of settlement management have been effectively improved. In terms of data management, a comprehensive and efficient data management platform has been built to collect, clean, organize and store various data of generators and users (including electricity consumption, electricity prices, transaction records, etc.) in real time to ensure the accuracy and completeness of the data. Through precise data management, a reliable basis is provided for electricity bill settlement, reducing settlement disputes caused by data errors. At the same time, a comprehensive and in-depth identification of market risks is carried out, including the risk of price fluctuations in the electricity market, policy adjustment risks, data security risks, and operational risks. Detailed response strategies have been formulated for various risks, a price risk early warning mechanism has been established, and settlement strategies have been adjusted in a timely manner when price fluctuations exceed a certain threshold; policy trends have been closely tracked, and response plans for policy adjustments have been prepared in advance; data security protection measures have been strengthened to prevent data leakage and tampering; and operating procedures have been standardized. This efficient and stable fee settlement management mechanism has effectively ensured the smooth settlement of electricity market fees, improved the market's ability to cope with risks, enhanced the confidence of market players in the settlement system, and promoted the healthy and sustainable development of the electricity market. It has important application value and practical significance in the power industry, and provides strong support for the modern management of the electricity market. BRIEF DESCRIPTION OF THE DRAWINGS

[0114] Figure 1 It is a flow chart of the method for calculating the imbalance fund allocation and return based on the coupled settlement of the contract market and the spot market in the present invention. DETAILED DESCRIPTION

[0115] In order to make the purpose, technical solution and advantages of the present invention more clear, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0116] The embodiments described in this application are only some embodiments of the present invention, not all embodiments. Based on the spirit of the present invention, other embodiments obtained by ordinary technicians in this field without creative work are all within the protection scope of the present invention.

[0117] In view of the shortcomings of the prior art, the present invention proposes a method and system for calculating the unbalanced fund allocation and return based on the coupled settlement of the contract market and the spot market, see Figure 1 As shown, the method for calculating the unbalanced fund allocation and return based on the coupled settlement of the contract market and the spot market disclosed in the present invention comprises the following steps:

[0118] Step 1: Establish the electricity bill settlement model between generators and users in market mode and non-market mode respectively.

[0119] The traditional settlement model lacks unified and precise standards when dealing with units and users under different market models, resulting in the settlement results may not accurately reflect the actual costs and benefits of all parties. Under the market model, the electricity pricing mechanism for generators may not fully consider factors such as their power generation costs, operating efficiency, and contribution to the stability of the power system, making it impossible to reasonably guarantee the benefits of some units, affecting their enthusiasm for market participation. For users, the differences in electricity consumption characteristics and demands of different types of users (such as industrial users, commercial users, residential users, etc.) are not effectively reflected in the electricity bill settlement, which may cause some users to bear unreasonable electricity expenses. Under the non-market model, there is a lack of scientific and reasonable electricity bill accounting methods, making it difficult to balance the relationship between power supply costs and user affordability.

[0120] To this end, for the settlement of electricity charges between the generator set and the user based on the market mode and the non-market mode, the present invention adopts the following steps:

[0121] Step 1.1: Settlement of market-based power generation units.

[0122] (1) Determine the market-oriented power generation unit set Ω market :

[0123] Ω market ={thermal,gas,nuclear,hydro,wind,solar}

[0124] Among them, thermal, gas, nuclear, hydro, wind, and solar are respectively the coordinated coal, gas, nuclear, hydro, wind, and solar units.

[0125] (2) For each market-based generating unit i∈Ω market The electricity fee settlement is carried out according to the principles of day-ahead benchmark, real-time difference and contract price difference.

[0126] (3) Calculate the day-ahead market electricity price

[0127]

[0128] in is the day-ahead market node electricity price of unit i in period t, is the day-ahead market electricity consumption of unit i in period t. T is the day-ahead market trading period. Usually 15 minutes is selected as a trading period (divided into 96 periods per day).

[0129] (4) Calculate the real-time market differential electricity charges

[0130]

[0131] is the real-time market node electricity price of unit i in period t, The daily measured grid-connected electricity of unit i in time period t.

[0132] (5) Calculate the difference in electricity charges in the contract market

[0133]

[0134] in are the government authorized contract electricity price, power generation right transaction price and ordinary direct transaction price of unit i in period t, are the corresponding contract electricity quantities respectively.

[0135] Step 1.2: Settlement of non-market generating units.

[0136] (1) Determine the set of non-market generating units Ω non-market :

[0137] Ω non-market ={external,self-supply}

[0138] Among them, external refers to purchased electricity, and self-supply refers to self-provided power plant.

[0139] (2) For each non-market generating unit i∈Ω non-market , and its electricity fee settlement model is:

[0140]

[0141] in, is the catalog price of non-market generating unit i, is the metered power generation of non-market unit i in the period.

[0142] Step 1.3: Market-based user settlement.

[0143] (1) Determine the market-oriented user set Ψ market

[0144] Ψ market ={Wholesale,TradingLtd,Agent}

[0145] Wholesale, Trading Ltd, and Agent are market-oriented users including wholesale market users, power sales companies, and some industrial and commercial users who do not participate in the market independently and purchase electricity from the power grid as an agent.

[0146] (2) For each market-oriented user j∈Ψ market The electricity fee includes three parts: day-ahead market fee, real-time market fee and contract market fee. The settlement model is:

[0147]

[0148] is the day-ahead market electricity price of market-based user j during period t:

[0149]

[0150] is the day-ahead market electricity price of market-based user j during period t:

[0151]

[0152] is the day-ahead market electricity price of market-based user j during period t:

[0153]

[0154] in, They are the day-ahead market electricity consumption, real-time metered electricity consumption and contract market electricity consumption of market-based user j in period t.

[0155] Step 1.4: Non-market user settlement.

[0156] (1) Determine the non-market user set Ψ non-market

[0157] Ψ non-market ={Resident,Agricultural}

[0158] Among them, Resident and Agricultural are residents who are non-market users and agricultural users respectively.

[0159] (2) For each non-marketized user j∈Ψ non-market , and its electricity fee settlement model is:

[0160]

[0161] in is the catalogue electricity price of non-market user j in period t, is the actual metered electricity consumption of user j in period t.

[0162] Step 2: For power generators and users, build a market-based ancillary service fee allocation and refund processing model and a deviation assessment fee allocation and refund processing model to achieve imbalance fund allocation and refund processing based on fee classification.

[0163] The existence of a dual-track system in the electricity market and the complexity of electricity trading have made the problem of unbalanced funds more prominent. At present, the allocation method of market-based ancillary service costs is relatively simple, and is simply allocated according to electricity consumption, which fails to fully consider the actual demand for ancillary services by different users and their different roles and influences in the electricity market. For the deviation assessment costs on the generation / use side, there is a lack of clear and detailed standards and processes in the specific implementation process, which easily leads to inaccurate and unfair cost allocation and refund. On the power generation side, the differences in the capabilities and costs of different types of units in providing ancillary services and responding to deviation assessments have not been fully reflected, which may cause some units to bear excessive burdens and affect their enthusiasm for power generation and market competitiveness. On the user side, users in different industries have different electricity consumption characteristics and different impacts on deviations. The unified allocation method cannot accurately reflect the responsibilities they should bear, which may cause unreasonable fluctuations in electricity bills for some users and reduce their satisfaction with the power market.

[0164] To this end, the present invention adopts the following steps:

[0165] Step 2.1: Construct a model for the allocation and refund of market-based ancillary service costs. Specifically include:

[0166] Step 2.11: Units with frequency regulation function participate in the frequency regulation quotation according to the single-day provincial frequency regulation demand issued by the dispatch center. Calculate the frequency regulation performance index of unit i jth frequency regulation performance index of single frequency regulation

[0167]

[0168] in, is the jth frequency modulation rate of unit i, is the standard frequency regulation rate of the unit, is the j-th frequency regulation accuracy of unit i, This is the standard adjustment accuracy.

[0169] Step 2.12: Computer group comprehensive frequency modulation index

[0170]

[0171] in is the j-th forward frequency modulation mileage of unit i.

[0172] Step 2.13: Compensation income from frequency modulation of computer group

[0173]

[0174] in, are respectively the positive and negative frequency regulation mileage of the unit, K d is the negative FM penalty factor, Clearing price for the FM market.

[0175] Step 2.14: Calculate backup ancillary service revenue

[0176]

[0177] in, is the compensation standard for standby ancillary services (yuan / MW), C i It is the adjustable capacity of the unit on that day.

[0178] Step 2.15: Calculate the total market-based ancillary service costs of the group

[0179]

[0180] Step 2.16: The ancillary service fee is shared by market users based on the actual metered electricity consumption. The sharing model is:

[0181]

[0182] in, The ancillary service costs allocated to market user j; is the actual metered electricity consumption of user j in settlement period t.

[0183] Step 2.2: Construct a model for allocating and refunding deviation assessment costs.

[0184] On the power generation side, peak unit consumption is encouraged, positive deviation electricity is not included in the assessment scope, and negative deviations above 3% will be charged for assessment fees; on the electricity consumption side, wholesale market users and power sales companies will have their positive and negative deviations exceeding 3% included in the deviation assessment.

[0185] Step 2.21: Calculate the deviation assessment cost on the power generation side

[0186] For market-based power generation entity i, when hour,

[0187]

[0188] when hour,

[0189]

[0190] when hour,

[0191]

[0192] in, is the market contract decomposition quantity of power generation entity i in this cycle, ΔQ i is the deviation between the actual power generation and the contracted power generation, ρ -DA It is the base value of unit electricity deviation electricity charge (20% of the weighted average transaction price on the power generation side of the annual dual-agreement transaction).

[0193] Step 2.22: Establish a model for allocating and returning the cost of deviation assessment on the power generation side. The deviation assessment cost on the power generation side is returned to market users in proportion to the actual metered electricity consumption:

[0194]

[0195] in, The fee is refunded for the power generation deviation assessment of market user j.

[0196] Step 2.23: Calculate user-side deviation assessment fees

[0197] For user j, when hour,

[0198]

[0199] when hour,

[0200]

[0201] when hour,

[0202]

[0203] when hour,

[0204]

[0205] in is the contractual power consumption of user j in the settlement period, ΔQ j is the deviation between the actual electricity consumption and the contracted electricity consumption of user j during the settlement period.

[0206] Step 2.24: Establish a user-side deviation assessment fee allocation and refund model. The user-side deviation assessment fee is allocated to the power generation enterprise according to the proportion of authorized contract electricity. The allocation model is:

[0207]

[0208] in, Return the cost of user deviation assessment for generator set i.

[0209] Step 3: Build a data management platform, obtain data from generators and users, store them in categories, integrate them with relevant systems of the electricity bill settlement system, identify the risks of electricity bill settlement between generators and users under market and non-market modes, and automatically verify the electricity bill settlement results.

[0210] The step 3 further comprises:

[0211] Step 3.1: Build a centralized data management platform to store and manage various types of relevant data of generators and users. The platform has a data acquisition interface for real-time or regular acquisition of data from data sources such as power generation companies, power grid companies, and user terminals, including unit operation data, user electricity consumption data, market transaction data, cost accounting data, etc. Clean, organize and verify the collected data to ensure the accuracy and completeness of the data. For example, for abnormal power generation or power consumption data, identify and correct them through data verification algorithms to avoid deviations in electricity bill settlement due to data errors. Classify and store data, and archive them according to dimensions such as generator type, user type, and time series to facilitate subsequent query, analysis, and settlement processing.

[0212] Step 3.2: Integrate the electric energy and electricity bill settlement system with relevant systems such as the power market trading platform, power grid dispatching system, and financial management system. Develop standard data interfaces to achieve data interaction and sharing between systems. For example, interface with the power grid dispatching system to obtain real-time load data and power grid operation status information so that the impact of factors such as grid congestion on electricity prices can be considered in the electricity bill settlement; interface with the financial management system to achieve automatic accounting of electricity bill settlement results and capital flow processing.

[0213] Encryption technology, identity authentication and other means are used to protect the security of data transmission and storage, and prevent data leakage and malicious tampering.

[0214] Conduct system integration testing to simulate data interaction and settlement business processes in different scenarios, verify the effectiveness and accuracy of system integration, and promptly discover and resolve issues such as interface compatibility and data transmission delays.

[0215] Step 3.3: Identify the potential risks faced by power generators and users in the process of electricity bill settlement based on market and non-market models. Quantitatively analyze market risks, policy risks, data risks and operational risks, and assess their probability of occurrence and possible impact. For example, analyze the probability distribution of power market price fluctuations and the financial impact of price fluctuations on power generators and users through historical data and market forecasting models; establish a data risk assessment model to assess the degree of deviation of data errors on settlement results.

[0216] In response to market risks, power generators use hedging and other financial instruments to lock in some of the electricity price risks, and users stabilize electricity costs by signing long-term contracts or participating in power demand management projects. At the same time, a market risk early warning mechanism is established to monitor market prices and supply and demand changes in real time and adjust settlement strategies in advance.

[0217] In view of policy risks, we closely monitor government policy trends and establish a policy tracking and interpretation mechanism. When policies are adjusted, we promptly assess the impact on settlement and communicate and coordinate with government departments to strive for reasonable transition policies and adjustment time.

[0218] In response to data risks, we strengthen data management and backup measures, adopt multiple data storage and recovery technologies, and conduct regular data audits and verifications. At the same time, we establish a data security protection system to prevent external attacks and data leaks.

[0219] In view of operational risks, we will strengthen the operation and maintenance management of the settlement system, regularly upgrade and test the system, and improve the stability and reliability of the system. We will also train and assess operators, standardize operating procedures, and reduce human errors.

[0220] Step 3.4: Set up an internal verification module in the settlement system to automatically verify the electricity bill settlement results in real time or regularly. The verification content includes the correctness of the calculation logic, the accuracy of the data reference, the compliance of the settlement formula, etc. For example, by comparing the settlement results obtained by different calculation methods, check whether there are any differences; verify whether the electricity bill calculations of various types of generators and users comply with the established pricing model and settlement rules.

[0221] Generate settlement result verification reports regularly, record in detail the problems and abnormal situations found during the verification process, and notify relevant departments in a timely manner to make rectifications and adjustments.

[0222] Compared with the prior art, the present invention provides a method and system for calculating the unbalanced fund allocation and return based on the coupled settlement of the contract market and the spot market, and the beneficial effects are:

[0223] (1) Accurate and comprehensive electricity bill settlement has been achieved. In terms of electricity bill settlement between generators and users based on market and non-market models, a refined settlement system has been built for different types of generators (such as various energy units) and users (different market models, different industry types), laying a solid foundation for the stable operation of the entire power market, ensuring that the interests of all parties are reasonably reflected in the settlement process, and promoting the orderly conduct of power market transactions;

[0224] (2) The handling of unbalanced funds is more scientific and reasonable. A highly scientific and reasonable model based on cost classification has been constructed. For market-based ancillary service costs, full consideration is given to the actual demand for ancillary services, market roles and influencing factors of different users. By deeply analyzing the relationship between different users' electricity consumption behaviors and ancillary service needs, a more targeted allocation model has been established to ensure that the allocation of ancillary service costs is more fair and just. For the deviation assessment costs on the generation / consumption side, the principle of "whoever generates it, is responsible for it" is clarified in detail, and the standards and procedures for fee refunds are refined. The calculation and refund of deviation assessment costs are more accurate and reasonable, which effectively avoids the damage to the interests of market entities caused by unreasonable allocation and refund, ensures the fairness and stability of the power market, and encourages market entities to actively optimize their own behavior to reduce deviations.

[0225] (3) Efficient and stable fee settlement management. In terms of fee settlement management mechanism design, by establishing a system based on data management and market risk identification, the efficiency and stability of settlement management have been effectively improved. In terms of data management, a comprehensive and efficient data management platform has been built to collect, clean, organize and store various data of generators and users (including electricity consumption, electricity prices, transaction records, etc.) in real time to ensure the accuracy and completeness of the data. Through precise data management, a reliable basis is provided for electricity bill settlement, reducing settlement disputes caused by data errors. At the same time, a comprehensive and in-depth identification of market risks is carried out, including the risk of price fluctuations in the electricity market, policy adjustment risks, data security risks, and operational risks. Detailed response strategies have been formulated for various risks, a price risk early warning mechanism has been established, and settlement strategies have been adjusted in a timely manner when price fluctuations exceed a certain threshold; policy trends have been closely tracked, and response plans for policy adjustments have been prepared in advance; data security protection measures have been strengthened to prevent data leakage and tampering; and operating procedures have been standardized. This efficient and stable fee settlement management mechanism has effectively ensured the smooth settlement of electricity market fees, improved the market's ability to cope with risks, enhanced the confidence of market players in the settlement system, and promoted the healthy and sustainable development of the electricity market. It has important application value and practical significance in the power industry, and provides strong support for the modern management of the electricity market.

[0226] The present invention may be a system, a method and / or a computer program product. The present invention also discloses a calculation system for unbalanced fund allocation and return based on the above-mentioned unbalanced fund allocation and return calculation method based on the coupled settlement of the contract market and the spot market, comprising:

[0227] The electric energy and electricity fee settlement module is used to establish the electric energy and electricity fee settlement models between the generator set and the user in the market mode and the non-market mode respectively;

[0228] The fund allocation and return processing module is used to build a market-based auxiliary service fee allocation and return processing model and a deviation assessment fee allocation and return processing model for power generation units and users, and realize the imbalance fund allocation and return processing based on fee classification;

[0229] The data management and risk identification module is used to build a data management platform, obtain data from generators and users and store them in categories, integrate with relevant systems of the electric energy and electricity fee settlement system, identify the risks of electric energy and electricity fee settlement between generators and users under market and non-market modes, and automatically verify the electricity fee settlement results.

[0230] Based on the spirit of the present invention, those skilled in the art can easily think that a computer program product can be obtained based on the aforementioned method for calculating the allocation and return of unbalanced funds based on the coupling settlement of the contract market and the spot market. The computer program product may include a computer-readable storage medium, which carries computer-readable program instructions for enabling a processor to implement various aspects of the present disclosure. That is, the present application also includes a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the aforementioned method for calculating the allocation and return of unbalanced funds based on the coupling settlement of the contract market and the spot market.

[0231] Computer readable storage medium can be a tangible device that can keep and store the instructions used by the instruction execution device. Computer readable storage medium can be, for example, - but not limited to - electrical storage device, magnetic storage device, optical storage device, electromagnetic storage device, semiconductor storage device or any suitable combination of the above. More specific examples (non-exhaustive list) of computer readable storage medium include: portable computer disk, hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital versatile disk (DVD), memory stick, floppy disk, mechanical encoding device, for example, punch card or groove protrusion structure with instructions stored thereon and any suitable combination of the above. Computer readable storage medium used here is not interpreted as instantaneous signal itself, such as radio wave or other free propagating electromagnetic wave, electromagnetic wave propagated by waveguide or other transmission medium (for example, light pulse by optical fiber cable) or electrical signal transmitted by wire.

[0232] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0233] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages-such as Smalltalk, C++, etc., and conventional procedural programming languages-such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network-including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA) may be personalized by utilizing the state information of a computer-readable program instruction, and the electronic circuit may execute a computer-readable program instruction, thereby realizing various aspects of the present disclosure.

[0234] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for calculating the unbalanced fund allocation and return based on the coupled settlement of the contract market and the spot market, characterized in that: The following steps are involved: Step 1: Establish the electricity bill settlement model between the generator set and the user under the market mode and the non-market mode respectively; Step 2: For power generators and users, build a market-based auxiliary service fee allocation and refund processing model and a deviation assessment fee allocation and refund processing model to achieve imbalance fund allocation and refund processing based on fee classification; Step 3: Build a data management platform, obtain data from generators and users, store them in categories, integrate them with relevant systems of the electricity fee settlement system, identify the risks of electricity fee settlement between generators and users under market and non-market modes, and automatically verify the electricity fee settlement results.

2. The method for calculating the unbalanced fund allocation and return based on the coupled settlement of the contract market and the spot market according to claim 1, characterized in that: The electric energy and electricity fee settlement models for the generator set and the user under the market mode and the non-market mode are respectively established, further comprising: Step 1.1: Market-based generator settlement: (1) Determine the market-oriented power generation unit set Ω market : Ω market ={thermal,gas,nuclear,hydro,wind,solar} Among them, thermal, gas, nuclear, hydro, wind, and solar are the coordinated coal, gas, nuclear, hydro, wind, and solar units respectively; (2) For each market-based generating unit i∈Ω market , the electricity fee settlement is carried out according to the principles of day-ahead basis, real-time difference and contract price difference; (3) Calculate the day-ahead market electricity price in is the day-ahead market node electricity price of unit i in period t, is the day-ahead market electricity of unit i in period t; (4) Calculate the real-time market differential electricity charges is the real-time market node electricity price of unit i in period t, The daily measured on-grid electricity of unit i in time period t; (5) Calculate the difference in electricity charges in the contract market in are the government authorized contract electricity price, power generation right transaction price and ordinary direct transaction price of unit i in period t, are the corresponding contract electricity quantities; Step 1.2: Settlement of non-market generating units: (1) Determine the set of non-market generating units Ω non-market : Ω non-market ={external,self-supply} Among them, external refers to purchased electricity, and self-supply refers to self-provided power plants; (2) For each non-market generating unit i∈Ω non-market , and its electricity fee settlement model is: in, is the catalogue price of non-market generating unit i, is the metered power generation of non-market unit i in the time period; Step 1.3: Market-based user settlement: (1) Determine the market-oriented user set Ψ market P market ={Wholesale,TradingLtd,Agent} Wholesale, Trading Ltd, and Agent are market users, including wholesale market users, power sales companies, and industrial and commercial users who purchase electricity through power grid agents; (2) For each market-oriented user j∈Ψ market The electricity fee includes three parts: day-ahead market fee, real-time market fee and contract market fee. The settlement model is: is the day-ahead market electricity price of market-based user j during period t: is the day-ahead market electricity price of market-based user j during period t: is the day-ahead market electricity price of market-based user j during period t: in, They are the day-ahead market electricity consumption, real-time metered electricity consumption and contract market electricity consumption of market-based user j in period t; Step 1.4: Non-market user settlement: (1) Determine the non-market user set Ψ non-market Ψ non-market ={Resident,Agricultural} Among them, Resident and Agricultural are residents and agricultural users who are not market users; (2) For each non-marketized user j∈Ψ non-market , and its electricity fee settlement model is: in is the catalogue electricity price of non-market user j in period t, is the actual metered electricity consumption of user j in period t.

3. The method for calculating the unbalanced fund allocation and return based on the coupled settlement of the contract market and the spot market according to claim 2, characterized in that: The construction of the market-based auxiliary service fee allocation and refund processing model further includes: Step 2.11: According to the single-day provincial frequency regulation demand released by the dispatch center, take the unit as the reporting unit to participate in the frequency regulation quotation; calculate the j-th frequency regulation performance index of unit i and the single frequency regulation performance index in, is the jth frequency modulation rate of unit i, is the standard frequency regulation rate of the unit, is the j-th frequency regulation accuracy of unit i, It is the standard adjustment accuracy; Step 2.12: Computer group comprehensive frequency modulation index in is the j-th forward frequency modulation mileage of unit i; Step 2.13: Compensation income from frequency modulation of computer group in, are respectively the positive and negative frequency regulation mileage of the unit, K d is the negative FM penalty factor, Clearing prices for the FM market; Step 2.14: Calculate backup ancillary service revenue in, is the compensation standard for standby ancillary services (yuan / MW), C i The adjustable capacity of the unit on that day; Step 2.15: Calculate the total market-based ancillary service costs of the group Step 2.16: The ancillary service fee is shared by market users based on the actual metered electricity consumption. The sharing model is: in, The ancillary service costs allocated to market user j; is the actual metered electricity consumption of user j in settlement period t.

4. The method for calculating the unbalanced fund allocation and return based on the coupled settlement of the contract market and the spot market according to claim 3 is characterized in that: The construction of the allocation and refund processing model for deviation assessment expenses further includes: Step 2.21: Calculate the deviation assessment cost on the power generation side For market-based power generation entity i, when hour, when hour, when hour, in, is the market contract decomposition quantity of power generation entity i in this cycle, ΔQ i is the deviation between the actual power generation and the contracted power generation, ρ -DA The unit electricity deviation electricity fee base value; Step 2.22: Establish a model for allocating and returning the cost of power generation deviation assessment; the power generation deviation assessment cost will be returned to market users in proportion to the actual metered electricity consumption: in, Return fees for the power generation deviation assessment of market-based user j; Step 2.23: Calculate user-side deviation assessment fees For user j, when hour, when hour, when hour, when hour, in is the contractual power consumption of user j in the settlement period, ΔQ j The deviation between the actual power consumption and the contracted power consumption of user j during the settlement period; Step 2.24: Establish a user-side deviation assessment cost allocation and refund model. The user-side deviation assessment cost is allocated to the power generation enterprise according to the proportion of authorized contract electricity. The allocation model is: in, Return the cost of user deviation assessment for generator set i.

5. The method for calculating the unbalanced fund allocation and return based on the coupled settlement of the contract market and the spot market according to claim 4 is characterized in that: The data management platform is constructed to obtain data from the generator set and the user end and store the data in a classified manner, further comprising: Build a centralized data management platform to store and manage various types of relevant data of generator sets and users. Obtain data from power generation companies, power grid companies, and user-side data sources in real time or regularly through data acquisition interfaces, including unit operation data, user electricity consumption data, market transaction data, and cost accounting data; clean, organize, and verify the collected data; classify and store data, and archive them according to generator set type, user type, and time series dimensions.

6. The method for calculating the unbalanced fund allocation and return based on the coupled settlement of the contract market and the spot market according to claim 5, characterized in that: The integration with the related systems of the electric energy and electricity fee settlement system further includes: Integrate the electric energy and electricity fee settlement system with the power market trading platform, power grid dispatching system, and financial management system, develop standard data interfaces, and realize data interaction and sharing among systems; conduct system joint debugging tests, simulate data interaction and settlement business processes in different scenarios, and verify system integration.

7. The method for calculating the unbalanced fund allocation and return based on the coupled settlement of the contract market and the spot market according to claim 6, characterized in that: The identification of the settlement risk of electricity energy and electricity charges between the generator set and the user under the market mode and the non-market mode further includes: Conduct quantitative analysis on market risks, policy risks, data risks and operational risks, analyze the probability distribution of price fluctuations in the electricity market and the financial impact of price fluctuations on generators and users through historical data and market forecasting models; establish a data risk assessment model to assess the degree of deviation of settlement results caused by data errors.

8. A calculation system for imbalance fund allocation and return based on the coupled settlement of contract market and spot market, characterized in that: include: The electric energy and electricity fee settlement module is used to establish the electric energy and electricity fee settlement models between the generator set and the user in the market mode and the non-market mode respectively; The fund allocation and return processing module is used to build a market-based auxiliary service fee allocation and return processing model and a deviation assessment fee allocation and return processing model for power generation units and users, and realize the imbalance fund allocation and return processing based on fee classification; The data management and risk identification module is used to build a data management platform, obtain data from generators and users and store them in categories, integrate with relevant systems of the electric energy and electricity fee settlement system, identify the risks of electric energy and electricity fee settlement between generators and users under market and non-market modes, and automatically verify the electricity fee settlement results.

9. A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is used to operate according to the instructions to execute the steps of the imbalance fund allocation and return calculation method based on the coupled settlement of the contract market and the spot market according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method for calculating the imbalance fund allocation and return based on the coupled settlement of the contract market and the spot market as described in any one of claims 1 to 7 are implemented.

Images