Electric energy storage electricity market transaction risk assessment method in self-scheduling mode

Abstract

The invention discloses an electric energy storage electricity market transaction risk assessment method in a self-scheduling mode, and the method comprises the steps: obtaining basic data, and carrying out the assessment and dividing a transaction risk source; performing internal risk transaction risk assessment and external risk transaction risk assessment; and performing comprehensive risk assessment. The method is characterized in that a charge and discharge plan transaction risk assessment method in a self-scheduling mode based on transaction risk division is constructed, and risk sources are divided into external risks and internal risks according to differences of influence mechanisms of factors such as self faults and market prices. An internal risk assessment model and an external risk assessment model are respectively constructed, and internal and external risk indexes are measured and calculated, so that a comprehensive risk is obtained through measurement and calculation.

Description

Technical Field

[0001] The present invention relates to the field of electric energy storage and power technology, and in particular to a method for assessing electric energy storage and power market transaction risks in a self-dispatching mode. Background Art

[0002] With the rapid development of new energy sources such as wind power and photovoltaic power, the operation of the power system faces increasingly prominent operational challenges, which are reflected in insufficient peak-shaving capacity and insufficient rotational inertia. In this context, electric energy storage has become an important way to promote the consumption of new energy. As an important flexible power source, electric energy storage can promote the consumption of new energy in the off-peak period by discharging during peak hours and charging during off-peak hours, thus alleviating the tight power supply situation during peak hours.

[0003] At present, electric energy storage mainly adopts the self-dispatching mode to participate in the electricity spot market and obtain trading income. The main implementation features of this model include:

[0004] (1) Electric energy storage declares a charging and discharging plan, that is, based on the information disclosed by the power grid operation, the electric energy storage organization conducts an assessment of power market transactions, formulates a charging and discharging plan, including the charging and discharging time periods and exchange power, and submits it to the market operation agency;

[0005] (2) Clearing of electricity spot market transactions, that is, the market operator organizes the clearing of electricity spot market transactions based on the electricity supply and demand, the power generation capacity reported by market members and the quotations, and calculates the time-of-use node electricity price. It should be noted that this step does not take into account the participation of electric energy storage;

[0006] (3) Clearing of the declared plan of energy storage, that is, based on the declared charging and discharging plan of energy storage and the demand for new energy consumption, assess whether the clearing of the charging and discharging plan of energy storage is conducive to the consumption of new energy. If it is conducive, it will be cleared according to its declared charging and discharging plan as the charging and discharging scheduling plan of energy storage, otherwise it will not pass the clearing. For energy storage that meets the clearing conditions, it will be settled according to the time-of-use node electricity price obtained by clearing the electricity spot market in step 2. Summary of the invention

[0007] In view of the above existing problems, the present invention is proposed.

[0008] Therefore, the present invention provides a method for assessing the transaction risk of energy storage in the power market under the self-dispatching mode, which can solve the problem that the traditional method of energy storage in the power spot market has insufficient research on the expected returns of energy storage, while the existing transaction risks are not fully studied. While pursuing high transaction returns, energy storage will bear higher transaction risks.

[0009] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for assessing the risk of electric energy storage power market transactions under a self-dispatching mode, comprising:

[0010] Obtain basic data, evaluate and classify transaction risk sources; internal risk transaction risk assessment, external risk transaction risk assessment; comprehensive risk assessment.

[0011] As a preferred solution of the method for assessing the risk of electric energy storage market transactions in the self-dispatching mode described in the present invention, the basic data obtained includes historical power grid operation data, historical power market data, and forecast data of power grid operation on the day to be assessed.

[0012] As a preferred solution of the method for assessing the transaction risks of energy storage in the power market under the self-dispatching mode described in the present invention, wherein: the assessment and classification of transaction risk sources include: the expected return of energy storage in the self-dispatching mode is the product of the charging and discharging plan and the electricity price at the clearing node in the spot market; the charging and discharging plan of energy storage in the self-dispatching mode is declared by itself and cleared first.

[0013] The transaction risks of expected revenue from energy storage are divided into internal risks and external risks, as follows:

[0014] The risk of executing the charging and discharging plan is caused by the fact that the energy storage company itself cannot execute the charging and discharging plan as reported, which leads to the deviation of benefits. The transaction risk is determined by the equipment operation and management of the energy storage company itself and is defined as internal risk.

[0015] The risk of electricity price forecast at the clearing node of the spot market is the transaction risk caused by the deviation between the price forecast value and the actual clearing value at the clearing node of the spot market. It is determined by the uncontrollable factors of electricity load, new energy power generation output and energy storage itself, so it is defined as an external risk.

[0016] As a preferred solution of the method for evaluating the transaction risk of electric energy storage power market in the self-dispatching mode described in the present invention, wherein: the evaluating and dividing the transaction risk sources includes evaluating the probability of occurrence of deviation in the execution of the electric energy storage charging and discharging plan;

[0017] Under the self-reliability statistics method, the data of the energy storage charging and discharging plan and execution are counted, and the execution deviation rate of the charging and discharging plan on each operating day is calculated, that is, the ratio of the actual average charging power to the planned average charging power, which can be expressed as:

[0018]

[0019] In the formula, λ s,d represents the execution deviation rate of the charge and discharge plan of the energy storage system on operation day d, They are the actual average charging power and the planned average charging power of the energy storage system on operation day d, respectively, and the value range is 0-100%. When the plan execution deviation rate is 0, it means that the energy storage system has not experienced any deviation in the execution of the charging and discharging plan due to its own fault. When the plan execution deviation rate is 100%, it means that the energy storage system has not been charged or discharged externally due to its own fault. When the value is between 0-100%, it means that the actual charging power is lower than the planned level due to fault factors.

[0020] As a preferred solution of the method for assessing the transaction risk of electric energy storage power market under the self-dispatching mode described in the present invention, wherein: the assessment and classification of transaction risk sources include: taking the probability of the plan execution deviation rate taking a value of 0 within the historical data statistical period as the assessment value of execution according to the plan; taking the probability of the plan execution deviation rate taking a value of 100% within the historical data statistical period as the valuation of the failure to perform the plan due to a fault; using a linear fitting method to assess the probability of plan deviation, and assessing the distribution function of the execution deviation rate of the electric energy storage charging and discharging plan, which is expressed as follows:

[0021]

[0022] In the formula, represents the probability of occurrence of deviation in the execution of the energy storage s charging and discharging plan, λ s Represents the execution deviation rate of the energy storage s charging and discharging plan, N s (λ s,d =0), N s (λ s,d =100%) are the number and total number of occurrences in the historical data where the execution deviation rate of the energy storage s charging and discharging plan is 0% and 100%, respectively. To obtain the next term coefficient and constant term coefficient when the deviation rate of the execution of the charging and discharging plan is between 0 and 100% by using the linear fitting method according to the historical data;

[0023] The expected transaction benefits under the deviation of charging and discharging plan execution can be expressed as the sum of the expected charging and discharging benefits and the plan deviation penalty, which is expressed as:

[0024]

[0025] In the formula, The execution deviation rate of the charging and discharging plan of the energy storage s is λ s The expected trading return under NT and ΔT are the number of divided periods and the time interval respectively. is the discharge power of the energy storage system at time period t on the operating day d; if the time period is in the charging state, the corresponding discharge power is the negative of the charging power, is the node clearing price at the node where the energy storage s is located during the operation period t on the day d, is the planned deviation power of the energy storage on operation day s, p D Penalize electricity prices for deviation in electricity consumption;

[0026] Evaluate the expected transaction risk under the deviation of charging and discharging plan. The expected transaction risk is defined as the sum of the difference between the expected transaction income and the target transaction income and the product of its occurrence probability, expressed as:

[0027]

[0028] In the formula, IA represents internal risk, that is, the transaction risk caused by deviation in charging and discharging plan due to its own fault. Declare the planned charging and discharging power for the energy storage system at time t on day s, then It represents the transaction income when there is no deviation in the charging and discharging plan, that is, the target transaction income. Min is the minimum value function, which is used to filter out the scenarios where the transaction income is lower than the target transaction income.

[0029] As a preferred solution of the method for assessing the risk of electric energy storage power market transactions in the self-dispatching mode described in the present invention, wherein: the external risk transaction risk assessment includes constructing an external risk source library and assessing the volatility characteristics of the external risk source;

[0030] Select an external risk factor from the external risk library in order. The fluctuation range and distribution law of the selected external risk factor in the historical data are the fluctuation characteristics of the external risk source. Divide the fluctuation range into N equal parts. The frequency corresponding to the number of occurrences in the historical data is used to evaluate the probability of occurrence of the fluctuation range, which is expressed as:

[0031]

[0032] In the formula, represents the volatility probability function of external risk factor a, N a,1 、N a,2 , ... N a,10 is the number of occurrences of different fluctuation ranges, is the total number of historical data, V a is the value of the external risk factor a, These are the dividing values ​​for the 10 intervals;

[0033] To evaluate the expected clearing price under the fluctuation of external risk factors, the market clearing prices within different ranges of external risk factors are counted from historical data, and the mode of the clearing prices is taken as the expected clearing price, which can be expressed as:

[0034]

[0035] In the formula, is the expected clearing price function under the fluctuation of external risk factor a, represents the actual market clearing price under the fluctuation of external risk factor a, It represents the mode function, which is used to calculate the market-clearing price with the most clearing times from the market-clearing prices under the fluctuation of external risk factor a.

[0036] As a preferred solution of the method for assessing the risk of electric energy storage market transactions in the self-dispatching mode described in the present invention, the external risk transaction risk assessment includes:

[0037] Evaluate the expected trading revenue changes under the fluctuation of external risk sources, that is, the expected trading revenue of electric energy storage corresponding to the change of market clearing price under the fluctuation of external risk factors, expressed as:

[0038]

[0039] In the formula, Represents the expected trading income of electric energy storage s under the fluctuation of external risk factor a;

[0040] Assess the transaction risk of external risk sources, which is defined as the sum of the difference between the expected transaction return and the target transaction return and the product of its probability of occurrence, expressed as:

[0041]

[0042] In the formula, represents the transaction risk of external risk factor a, and min is the minimum value function, which is used to screen out scenarios where the transaction income is lower than the target transaction income. Used to count all external risk factor fluctuation scenarios;

[0043] The transaction risks of all external risk factors are evaluated in sequence until all external risk factors are covered. The external risk under the combined influence of all external factors is defined as the weighted sum of the transaction risks of all external risk factors, expressed as:

[0044]

[0045] In the formula, OA represents external risk, NA is the number of external risk factors, α a is the weight coefficient of external risk factor a, which is determined by the electric energy storage operator.

[0046] As a preferred solution of the method for assessing the risk of electric energy storage market transactions in the self-dispatching mode described in the present invention, the comprehensive risk assessment includes: the comprehensive risk is defined as the sum of internal and external risks, expressed as:

[0047] CA=OA+IA (10)

[0048] In the formula, CA represents the comprehensive risk;

[0049] Electric energy storage operators assess the transaction risks of their charging and discharging plans based on comprehensive risks. If the comprehensive risk value exceeds the given limit, it indicates that the risk is high and prevention and control measures need to be taken; if the comprehensive risk value does not exceed the given limit, it indicates that the risk is controllable.

[0050] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, the steps of a method for risk assessment of electric energy storage power market transactions in a self-dispatching mode are implemented.

[0051] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of a method for risk assessment of electric energy storage power market transactions in a self-dispatching mode are implemented.

[0052] Beneficial effects of the present invention: The method of the present invention is based on a probability assessment model for transaction risk division, and constructs a transaction risk assessment model for charge and discharge plans under the self-dispatching mode. The model shows that the risk sources can be divided into external risks and internal risks according to the differences in the influencing mechanisms of factors such as self-failures and market prices, and internal and external risk assessment models are constructed respectively to calculate internal and external risk indicators, and then the comprehensive risk is calculated. This solves the problem that the traditional method has not studied the transaction risks of the expected returns of energy storage in the electricity spot market sufficiently, and that energy storage will bear higher transaction risks while pursuing high transaction returns. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0054] Figure 1 A schematic flow chart of a method for assessing the risk of electric energy storage market transactions in a self-dispatching mode provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0055] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0056] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0057] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0058] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0059] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0060] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0061] Example 1, reference Figure 1 , which is the first embodiment of the present invention, and provides a method for assessing the risk of electric energy storage market transactions in a self-dispatching mode, including:

[0062] Step 1: Obtain basic data

[0063] The purpose of implementing this step is to clarify the basic data required for the implementation of the present invention and determine its data source.

[0064] Preferably, the basic data and their sources required for the implementation of the present invention include:

[0065] (1) Historical data of power grid operation, including power load, renewable energy power generation output, conventional power supply capacity, etc., are derived from the energy management system;

[0066] (2) Historical electricity market data, including electricity spot market clearing prices, etc., which are derived from the electricity market trading system;

[0067] (3) The grid operation forecast data for the day to be evaluated is derived from forecast data such as power load, renewable energy power generation output, and conventional power supply capacity, which are derived from the energy management system.

[0068] Step 2: Evaluate and classify transaction risk sources

[0069] The purpose of implementing this step is to evaluate the transaction risk sources that affect its transaction income based on the business characteristics of the electric energy storage self-dispatch model, and divide them into different types.

[0070] Preferably, the expected revenue of energy storage under the self-dispatching mode is the product of the charging and discharging plan and the electricity price at the clearing node in the spot market. Under the self-dispatching mode, the charging and discharging plan of energy storage is declared by itself and cleared first. Therefore, the transaction risk of expected revenue of energy storage can be divided into internal risk and external risk, as follows:

[0071] (1) Internal risk, i.e. the risk of executing the charging and discharging plan, is caused by the fact that the energy storage company itself cannot execute the charging and discharging plan as reported, which leads to the deviation of the execution and the resulting benefit deviation, and the resulting transaction risk. This factor is mainly determined by the operation and management of the energy storage company's own equipment, so it is defined as internal risk;

[0072] (2) External risk, i.e. the risk of electricity price forecast at the clearing node of the spot market, is the transaction risk caused by the deviation between the price forecast value at the clearing node of the spot market and the actual clearing value. This factor is mainly determined by the uncontrollable factors of the energy storage itself, such as electricity load and new energy power generation output, so it is defined as external risk.

[0073] Step 3: Internal Risk Transaction Risk Assessment

[0074] The purpose of implementing this step is to evaluate the execution deviation of the energy storage charging and discharging plan and the possible loss of trading revenue based on the reliability of the energy storage equipment.

[0075] Preferably, the probability of occurrence of deviation in the execution of the energy storage charge and discharge plan is evaluated. Various methods such as the similar reliability reference method and the self-reliability statistical method can be used to evaluate the deviation in the execution of the energy storage charge and discharge plan. Among them, the similar reliability reference method refers to evaluating the deviation in the execution of the energy storage charge and discharge plan based on the operation data of the same type of energy storage, as a reference for the deviation in the execution of the energy storage charge and discharge plan to be evaluated. The self-reliability statistical method refers to analyzing the deviation in the execution of the energy storage charge and discharge plan to be evaluated, and calculating its expected charge and discharge execution deviation. Without loss of generality, the present invention recommends the use of the self-reliability statistical method because the operating reliability differences between energy storages are large, and the use of the similar reliability reference method cannot ensure a relatively accurate evaluation result.

[0076] Under the self-reliability statistics method, the data of the energy storage charging and discharging plan and execution are counted, and the execution deviation rate of the charging and discharging plan on each operating day is calculated, that is, the ratio of the actual average charging power to the planned average charging power, which can be expressed as:

[0077]

[0078] In the formula, λ s,d represents the execution deviation rate of the charge and discharge plan of the energy storage system on operation day d, They are the actual average charging power and the planned average charging power of the energy storage system on operation day d, respectively, with a value range of 0-100%. When the planned execution deviation rate is 0, it means that the energy storage system has not experienced any deviation in the execution of the charging and discharging plan due to its own faults and other factors; when the planned execution deviation rate is 100%, it means that the energy storage system has not been charged or discharged due to its own faults; when the value is between 0-100%, it means that the actual charging power is lower than the planned level due to fault factors.

[0079] The probability of the plan execution deviation rate being 0 within the historical data statistical period is used as the evaluation value of the plan execution; the probability of the plan execution deviation rate being 100% within the historical data statistical period is used as the valuation of the failure to perform the plan due to a fault; the linear fitting method is used to evaluate the probability of plan deviation. Based on the above principles, the distribution function of the execution deviation rate of the energy storage charging and discharging plan can be evaluated and expressed as follows:

[0080]

[0081] In the formula, represents the probability of execution deviation of the energy storage s charging and discharging plan, λ s Represents the execution deviation rate of the energy storage s charging and discharging plan, N s (λ s,d =0), N s (λ s,d =100%) are the number and total number of occurrences in the historical data where the execution deviation rate of the energy storage s charging and discharging plan is 0% and 100%, respectively. The linear fitting method is used to fit the historical data to obtain the next term coefficient and constant term coefficient when the charge and discharge plan execution deviation rate is between 0 and 100%.

[0082] Preferably, the expected transaction benefit under the deviation of the charging and discharging plan execution can be expressed as the sum of the expected charging and discharging benefit and the plan deviation penalty, which can be expressed as:

[0083]

[0084] In the formula, The execution deviation rate of the charging and discharging plan of the energy storage s is λ s The expected trading return under NT and ΔT are the number of divided periods and the time interval respectively. is the discharge power of the energy storage system s during period t on the operating day d (if the period is in the charging state, the corresponding discharge power is the negative of the charging power), is the node clearing price at the node where the energy storage s is located during the operation period t on the day d, is the planned deviation power of the energy storage on operation day s, p D The penalty electricity price for deviation in electricity consumption is determined by market operating rules.

[0085] Preferably, the expected transaction risk under the deviation of the charging and discharging plan is evaluated. The expected transaction risk is defined as the sum of the difference between the expected transaction income and the target transaction income and the product of its probability of occurrence, which can be expressed as:

[0086]

[0087] In the formula, IA represents internal risk, that is, the transaction risk caused by deviation in charging and discharging plan due to its own fault. Declare the planned charging and discharging power for the energy storage system at time t on day s, then It represents the transaction income when there is no deviation in the charging and discharging plan, that is, the target transaction income. Min is the minimum value function, which is used to filter out the scenarios where the transaction income is lower than the target transaction income.

[0088] Step 4: External Risk Transaction Risk Assessment

[0089] The purpose of implementing this step is to build an external risk assessment framework and implementation methods to quantify the external risks caused by changes in spot market clearing prices.

[0090] Preferably, an external risk source library is constructed. There are many factors that affect the clearing price of electricity spot market transactions, including maximum power load, minimum power load, etc. At the same time, the impact of the above factors has significant regional differences. For this reason, the present invention recommends the use of an expert screening method, in which dispatching and operation professionals in the area to be evaluated select external risk factors to be included in the analysis, and thus construct an external risk library.

[0091] Preferably, the volatility characteristics of external risk sources are evaluated. An external risk factor is selected from the external risk library in order. The volatility range and distribution law of the external risk factor in historical data are the volatility characteristics of the external risk source. The volatility range is divided into N equal parts, and the frequency corresponding to the number of occurrences in the historical data is used to evaluate the probability of occurrence of the range, which can be expressed as:

[0092]

[0093] In the formula, represents the volatility probability function of external risk factor a, N a,1 、N a,2 , ... N a,10 is the number of occurrences of different fluctuation ranges, is the total number of historical data, V a is the value of the external risk factor a, These are the dividing values ​​for the 10 intervals.

[0094] Preferably, the expected clearing price under the fluctuation of external risk factors is evaluated. The market clearing prices within different ranges of external risk factors are counted from historical data, and the mode of the clearing prices is used as the expected clearing price, which can be expressed as:

[0095]

[0096] In the formula, is the expected clearing price function under the fluctuation of external risk factor a, represents the actual market clearing price under the fluctuation of external risk factor a, It represents the mode function, which is used to calculate the market-clearing price with the most clearing times from the market-clearing prices under the fluctuation of external risk factor a.

[0097] Preferably, the expected transaction revenue changes under the fluctuation of external risk sources are evaluated, that is, the expected transaction revenue of electric energy storage corresponding to the changes in market clearing prices under the fluctuation of external risk factors can be expressed as:

[0098]

[0099] In the formula, Represents the expected trading income of electric energy storage s under the fluctuation of external risk factor a.

[0100] Preferably, the transaction risk of the external risk source is evaluated, which is defined as the sum of the difference between the expected transaction return and the target transaction return and the product of its probability of occurrence, which can be expressed as:

[0101]

[0102] In the formula, represents the transaction risk of external risk factor a, and min is the minimum value function, which is used to screen out scenarios where the transaction income is lower than the target transaction income. Used to compile statistics on all external risk factor fluctuation scenarios.

[0103] Preferably, external risks are evaluated. The transaction risks of all external risk factors are evaluated in order until all external risk factors are covered. Considering that external risk factors affect transaction risks by affecting the clearing price, the external risk under the combined influence of all external factors is defined as the weighted sum of the transaction risks of all external risk factors, which can be expressed as:

[0104]

[0105] In the formula, OA represents external risk, NA is the number of external risk factors, α a is the weight coefficient of external risk factor a, which is determined by the electric energy storage operator.

[0106] Step 5: Comprehensive risk assessment

[0107] The purpose of implementing this step is to coordinate the internal and external risks under the electric energy storage self-dispatch mode and calculate its comprehensive risks.

[0108] Preferably, the comprehensive risk is defined as the sum of internal and external risks, which can be expressed as:

[0109] CA=OA+IA (10)

[0110] Where CA stands for comprehensive risk.

[0111] Electric energy storage operators assess the transaction risks of their charging and discharging plans based on comprehensive risks. If the comprehensive risk value exceeds the given limit, it indicates that the risk is high and prevention and control measures need to be taken; if the comprehensive risk value does not exceed the given limit, it indicates that the risk is controllable.

[0112] 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 preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0113] Example 2

[0114] The second embodiment of the present invention is different from the previous embodiment in that:

[0115] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0116] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0117] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0118] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0119] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0120] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for assessing the risk of electric energy storage market transactions under the self-dispatching mode, characterized by: include, Obtain basic data, evaluate and classify transaction risk sources; Internal risk transaction risk assessment, external risk transaction risk assessment; Comprehensive risk assessment.

2. The method for assessing the risk of electric energy storage market transactions in the self-dispatching mode according to claim 1, characterized in that: The basic data obtained include historical power grid operation data, historical power market data, and power grid operation forecast data for the day to be evaluated.

3. The method for assessing the risk of electric energy storage market transactions in the self-dispatching mode according to claim 2, characterized in that: The evaluation and classification of transaction risk sources include: the expected return of energy storage in the self-dispatching mode is the product of the charging and discharging plan and the electricity price at the clearing node of the spot market; in the self-dispatching mode, the charging and discharging plan of energy storage is declared by itself and cleared first; The transaction risks of expected revenue from energy storage are divided into internal risks and external risks, as follows: The risk of executing the charging and discharging plan is caused by the fact that the energy storage company itself cannot execute the charging and discharging plan as reported, which leads to the deviation of benefits. The transaction risk is determined by the equipment operation and management of the energy storage company itself and is defined as internal risk. The risk of electricity price forecast at the clearing node of the spot market is the transaction risk caused by the deviation between the price forecast value and the actual clearing value at the clearing node of the spot market. It is determined by the uncontrollable factors of electricity load, new energy power generation output and energy storage itself, so it is defined as an external risk.

4. The method for assessing the risk of electric energy storage market transactions in the self-dispatching mode according to claim 3, characterized in that: The said evaluating and classifying transaction risk sources includes evaluating the probability of occurrence of deviation in execution of electric energy storage charging and discharging plan; Under the self-reliability statistics method, the data of the energy storage charging and discharging plan and execution are counted, and the execution deviation rate of the charging and discharging plan on each operating day is calculated, that is, the ratio of the actual average charging power to the planned average charging power, which is expressed as: In the formula, λ s,d represents the execution deviation rate of the charge and discharge plan of the energy storage system on operation day d, are the actual average charging power and the planned average charging power of the electric energy storage system on operation day d, respectively, with a value range of 0-100%; When the plan execution deviation rate is 0, it means that the energy storage system has not experienced any deviation in the charge and discharge plan execution due to its own fault; when the plan execution deviation rate is 100%, it means that the energy storage system has not been charged or discharged to the outside due to its own fault; a value between 0-100% indicates that the actual charging power is lower than the planned level due to fault factors.

5. The method for assessing the risk of electric energy storage market transactions in the self-dispatching mode according to claim 4, characterized in that: The evaluation and classification of transaction risk sources include: taking the probability of the plan execution deviation rate being 0 within the historical data statistical period as the evaluation value of the plan execution; taking the probability of the plan execution deviation rate being 100% within the historical data statistical period as the valuation of the failure to perform the plan due to a fault; using a linear fitting method to evaluate the probability of plan deviation, and evaluating the distribution function of the execution deviation rate of the energy storage charging and discharging plan, which is expressed as follows: In the formula, represents the probability of occurrence of deviation in the execution of the energy storage s charging and discharging plan, λ s Represents the execution deviation rate of the energy storage s charging and discharging plan, N s (λ s,d =0), N s (λ s,d =100%) are the number and total number of occurrences in the historical data where the execution deviation rate of the energy storage s charging and discharging plan is 0% and 100%, respectively. To obtain the next term coefficient and constant term coefficient when the deviation rate of the execution of the charging and discharging plan is between 0 and 100% by using the linear fitting method according to the historical data; The expected transaction benefits under the deviation of charging and discharging plan execution can be expressed as the sum of the expected charging and discharging benefits and the plan deviation penalty, which is expressed as: In the formula, The execution deviation rate of the charging and discharging plan of the energy storage s is λ s The expected trading return under NT and ΔT are the number of divided periods and the time interval respectively. is the discharge power of the energy storage system at time period t on the operating day d; if the time period is in the charging state, the corresponding discharge power is the negative of the charging power, is the node clearing price at the node where the energy storage s is located during the operation period t on the day d, is the planned deviation power of the energy storage on operation day s, p D Penalize electricity prices for deviation in electricity consumption; Evaluate the expected transaction risk under the deviation of charging and discharging plan. The expected transaction risk is defined as the sum of the difference between the expected transaction income and the target transaction income and the product of its occurrence probability, expressed as: In the formula, IA represents internal risk, that is, the transaction risk caused by deviation in charging and discharging plan due to its own fault. Declare the planned charging and discharging power for the energy storage system at time t on day s, then Represents the transaction profit without charge and discharge plan deviation, that is, the target transaction profit; min is a minimum value function, which is used to filter out scenarios where transaction returns are lower than the target transaction returns.

6. The method for assessing the risk of electric energy storage market transactions in the self-dispatching mode according to claim 5, characterized in that: The external risk transaction risk assessment includes building an external risk source library and assessing the volatility characteristics of external risk sources; Select an external risk factor from the external risk library in order. The fluctuation range and distribution law of the selected external risk factor in the historical data are the fluctuation characteristics of the external risk source. Divide the fluctuation range into N equal parts. The frequency corresponding to the number of occurrences in the historical data is used to evaluate the probability of occurrence of the fluctuation range, which is expressed as: In the formula, represents the volatility probability function of external risk factor a, N a,1 、N a,2 , ... N a,10 is the number of occurrences of different fluctuation ranges, is the total number of historical data, V a is the value of the external risk factor a, These are the dividing values ​​for the 10 intervals; To evaluate the expected clearing price under the fluctuation of external risk factors, the market clearing prices within different ranges of external risk factors are counted from historical data, and the mode of the clearing prices is taken as the expected clearing price, which can be expressed as: In the formula, is the expected clearing price function under the fluctuation of external risk factor a, represents the actual market clearing price under the fluctuation of external risk factor a, It represents the mode function, which is used to calculate the market-clearing price with the most clearing times from the market-clearing prices under the fluctuation of external risk factor a.

7. The method for assessing the risk of electric energy storage market transactions in the self-dispatching mode according to claim 6, characterized in that: The external risk transaction risk assessment includes assessing the expected transaction revenue changes under the fluctuation of external risk sources, that is, the expected transaction revenue of electric energy storage corresponding to the market clearing price changes under the fluctuation of external risk factors, which is expressed as: In the formula, Represents the expected trading income of electric energy storage s under the fluctuation of external risk factor a; Assess the transaction risk of external risk sources, which is defined as the sum of the difference between the expected transaction return and the target transaction return and the product of its probability of occurrence, expressed as: In the formula, represents the transaction risk of external risk factor a, and min is the minimum value function, which is used to screen out scenarios where the transaction income is lower than the target transaction income. Used to count all external risk factor fluctuation scenarios; The transaction risks of all external risk factors are evaluated in sequence until all external risk factors are covered. The external risk under the combined influence of all external factors is defined as the weighted sum of the transaction risks of all external risk factors, expressed as: In the formula, OA represents external risk, NA is the number of external risk factors, α a is the weight coefficient of external risk factor a, which is determined by the electric energy storage operator.

8. The method for assessing the risk of electric energy storage market transactions in the self-dispatching mode according to claim 7, characterized in that: The comprehensive risk assessment includes, The comprehensive risk is defined as the sum of internal and external risks, expressed as: CA=OA+IA (10) In the formula, CA represents the comprehensive risk; Electric energy storage operators assess the transaction risks of their charging and discharging plans based on comprehensive risks. If the comprehensive risk value exceeds the given limit, it indicates that the risk is high and prevention and control measures need to be taken; if the comprehensive risk value does not exceed the given limit, it indicates that the risk is controllable.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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