CN116757307A - Set-based quota reference value measurement and optimization method for carbon market power industry - Google Patents
Set-based quota reference value measurement and optimization method for carbon market power industry Download PDFInfo
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Abstract
The invention discloses a unit-based quota reference value measuring and optimizing method for the carbon market power industry, which comprises the following steps: establishing a basic database of the unit; checking unit basic data of a unit basic database, and identifying and deleting error data to obtain a data sample; obtaining a quota allocation reference value feasible solution set and an optimal solution based on an improved enumeration method through reference value measurement and calculation; pre-evaluating the implementation effect of the quota allocation benchmark value optimal solution according to the evaluation key indexes; and dynamically adjusting according to the pre-evaluation and various constraint conditions to obtain an optimized quota allocation reference value optimal solution. The invention establishes a complete power industry quota allocation reference value calculation optimization flow, and defines each key step of reference value calculation; the method solves the problem of solving the optimal solution of the reference value under various complex constraint conditions, and the problem of quickly, accurately and dynamically adjusting and optimizing the reference value when the constraint conditions change. Providing a reference for further optimization of the quota allocation baseline approach.
Description
Technical Field
The invention belongs to the field of carbon emission right trading market system construction, and particularly relates to a unit-based quota reference value measuring and optimizing method for the carbon market power industry.
Background
The carbon market is a policy tool that utilizes market mechanisms to control and reduce greenhouse gas emissions. The carbon market is applied to more and more countries and regions worldwide due to the advantages of strong policy compatibility, strong regional/industry expansibility, strong financial derivatization, acceleration of carbon financial construction, release of price signals, autonomous emission reduction of a counter-forcing enterprise, promotion of green low-carbon technical innovation and the like. The carbon market is complex to operate and needs a series of matched systems, methods and systems for supporting, including a monitoring report checking (MRV) system, a data quality control system, a quota allocation system, a performance clearing system, a data reporting system, a registration and registration system, a market trading system, a violation punishment mechanism, a law enforcement inspection system and the like. The core product of the carbon market transaction is carbon emission quota, the amount of the quota obtained by enterprises is directly hooked with the economic benefits of the enterprises, and the amount of the quota provided directly influences the quota price, the transaction activity and the emission reduction effect. Therefore, the quota allocation system is at the heart of the carbon market, and a fair, scientific, reasonable and operable quota allocation method is the basis for smooth and healthy operation of the carbon market.
For the key emission units incorporated into the carbon market management, both the carbon emission and quota amounts within the statistical period depend on the statistical accounting of the data. Different carbon markets have differences in methods adopted for quota allocation of different industries, but basically summarized as a historical emission method, a historical emission intensity method and a baseline method. Various methods have advantages and disadvantages, and iteration is perfect in practice. The standard line method multiplies the carbon dioxide emission amount (namely a standard value) of the product yield of an enterprise and the unit product yield by the calculated quota amount, establishes a clear industrial emission intensity standard rod, establishes a clear enterprise emission reduction target, is direct and easy to operate, can exert the effects of reducing emission and eliminating low-energy-efficiency and high-energy-consumption equipment of an enterprise in the carbon market to the maximum extent, is suitable for verifying the quota for the industrial enterprise with relatively sound data quality and relatively single product, and is a relatively better quota allocation method. The power generation enterprises in the power industry have large energy consumption and high greenhouse gas emission, and the products are relatively single, so that the standard line method distribution quota is suitable for being adopted. The test point carbon market adopts a datum line to distribute quota to power generation enterprises in the power industry, the first performance period of the national carbon market is incorporated into quota management and is the power generation enterprises, and the datum line is also used for distributing quota. Although the baseline method has various advantages, the baseline method has obvious defects in the aspects of baseline measuring and calculating flow, baseline measuring and calculating method, baseline dynamic optimization and the like in practical application, and the method specifically comprises the following steps:
First, there is a lack of explicit reference value measurement procedures. The reference value is the core of reference line method application, and the reference value is related to factors such as total carbon market quota, overall surplus ratio design, unit class division and the like. Scientific and reasonable benchmark measurement requires a large amount of accurate actual emission sample data as a support, and establishes a benchmark design framework covering the whole flow of data processing, measurement, judgment, optimization, output and the like. At present, a set of clear reference value design flow is not established, and all key steps are not clear. The problems of different carbon market reference value measuring and calculating methods, optimization standards, adjustment methods, evaluation methods and the like are different in treatment modes, so that the comparability of different carbon market reference values is reduced.
Secondly, a definite constraint condition value measuring and calculating method for the reference value is lacked. When a reference line is applied to allocate quota to enterprises, the reference value often plays a certain policy guiding and encouraging role, such as encouraging a large capacity energy-efficient unit, encouraging a heat supply unit and the like, on the basis of meeting the overall surplus ratio control of the quota. At present, in the reference value design process, a constraint condition of how to quantitatively convert the requirements of policy guidance, encouragement directions and the like into reference value measurement and calculation is not clear. The boundary constraint is lacking in reference value calculation, so that the final reference value calculation result may be inappropriately valued, the encouraging direction and the policy guidance are not consistent, and the implementation effect does not reach the design expectation.
Thirdly, it is difficult to scientifically solve the reference value optimal solution under various complex conditions. As described above, the measurement and calculation of the reference value is often limited by various complex constraints, and is not simply solving the average, median, quartile, etc. of the emission intensities of a certain group of units. The value of the current reference value is usually obtained by adopting a trial calculation method, namely, the theoretical value range of the reference value is determined according to constraint conditions, and the reference value is obtained through repeated trial calculation and replacement. The method is complex and easy to make mistakes, can not fully satisfy all feasible solutions of the reference values under all constraint conditions, can not judge whether the final reference value of the result is the optimal solution, and reduces the scientificity of reference value design.
Fourth, there is no adjustment optimization method of the reference value. In the actual application process, the reference value is not fixed, and is often adjusted and optimized according to quota total amount control, notch design, policy guidance and the like, and the reference value is often adjusted by taking the performance year as a period. At present, a scientific reference value adjustment optimization method is lacked, and the reference value is difficult to adjust accurately in time according to the change of constraint conditions.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a quota reference value measuring and optimizing method for the carbon market power industry based on a unit.
In order to achieve the above purpose, the invention provides a unit-based quota reference value measurement and optimization method for the carbon market power industry, which comprises the following steps:
step 1) establishing a basic database of a unit;
step 2) auditing the unit basic data of the unit basic database, and identifying and deleting error data to obtain a data sample;
step 3) carrying out benchmark value measurement and calculation on the data sample, and obtaining a quota allocation benchmark value feasible solution set and an optimal solution based on an improved enumeration method;
step 4) pre-evaluating the implementation effect of the quota allocation benchmark value optimal solution according to the evaluation key indexes;
and 5) dynamically adjusting according to the pre-evaluation and various constraint conditions to obtain an optimized quota allocation reference value optimal solution.
As an improvement of the above method, the basic data of the basic database of the step 1) includes: sequential numbering, province, city, county, key emission unit name, unified social credit code, national economy industry code, unit number, main fuel type, installed capacity, unit type, product type, annual energy production, annual energy supply, annual heat supply, heat supply ratio, number of operating hours, load factor, cooling mode, whether combined loading exists, whether combined loading is across unit type, whether a biomass unit is co-fired, whether a secondary energy unit is co-fired, various fuel consumption, various low-level heat productivity of fuel and annual checked emission.
As an improvement of the above method, the step 2) includes:
step 2-1), judging whether the basic data of each unit is filled completely, if any parameter is missing, judging that the basic data is error data, and deleting the unit from a sample;
step 2-2) judging the accuracy of the product type of each unit, if the annual power supply is filled to 0, or the product type is a pure condensing generator set, the annual heat supply data is not equal to 0, or the product type is a cogeneration unit, and the annual heat supply filling data is equal to 0; determining that the data is error data, and deleting the unit from the sample;
step 2-3) judging the product yield accuracy of each unit:
annual energy production F of unit with unit number j j If any one of the following formulas is met, judging that the generated energy data is wrong, and deleting the unit in a sample;
F j >V j ×T j ×L j
S j >F j
wherein F is j Annual energy production for unit number j in megawatt hours; v (V) j The unit capacity of the unit is j, and the unit is megawatt; t (T) j The number of operating hours of the unit with the unit number j is L j The unit is the unit load coefficient of the unit number j; s is S j Annual power supply quantity of a unit with the unit number j is megawatt-hour; h j Annual heat supply for a unit with unit number j is achieved, and the unit is gigajoule; c (C) i，j The fuel consumption of the ith fossil fuel type of the unit with the unit number j is ton for solid or liquid fuel and ten thousand standard cubic meters for gas fuel; NCV (NCV) i,j The unit number j is the low-level heating value of the ith fossil fuel type of the unit, for solid or liquid fuel, the unit is giga-joule/ton, and for gas fuel, the unit is giga-joule/ten thousand standard cubic meters; i is a fossil fuel type; j is the number of the unit; n is the total number of fossil fuel types;
and 2-4) if the unit of the heat supply ratio of each unit is that the value range does not belong to [0,1] or the value range of the load coefficient does not belong to [0,1], judging that the unit is wrong data, and deleting the unit from the sample.
As an improvement of the above method, the step 3) includes:
step 3-1) dividing according to unit types, respectively calculating the power supply quota amount and the heat supply quota amount of each unit to obtain quota amounts of each unit, and calculating according to quota amounts of each unit to obtain quota surplus ratio of each unit; each unit comprises: a conventional coal-fired unit with a MW level above 300MW level, a conventional coal-fired unit with a MW level below 300MW level, an unconventional coal-fired unit and a gas unit;
Step 3-2) determining the encouraging direction and policy direction of quota allocation, and quantifying the policy direction into constraint conditions for quota reference value measurement;
step 3-3) calculating quota allocation balance values of various units according to a quota approval method, wherein the quota allocation balance values comprise: the power supply balance value and the heat supply balance value of the conventional coal-fired unit above 300MW grade, the power supply balance value and the heat supply balance value of the conventional coal-fired unit below 300MW grade, the power supply balance value and the heat supply balance value of the unconventional coal-fired unit and the power supply balance value and the heat supply balance value of the gas-fired unit;
step 3-4) determining the fluctuation range and the calculation step length of the reference value compared with the balance value;
step 3-5) obtaining value sets of power supply reference values and heat supply reference values of various units in a fluctuation range and a value step range, wherein u reference values of each set are obtained;
step 3-6) further screening each set of the step 3-5) according to the constraint condition of the step 3-2), deleting the reference value which does not meet the constraint condition, and deleting the reference value from the set; if the reference value meeting all the constraint conditions exists, the step 3-7 is carried out; otherwise, turning to the step 3-4) to expand the fluctuation range and reduce the calculation step length, and circularly calculating until the reference value meeting all constraint conditions is obtained, and turning to the step 3-7);
Step 3-7) outputting a reference value feasible solution set comprising v reference value feasible solutions;
and 3-8) comprehensively judging according to the reference value feasible solution set and a weight analysis method to obtain a reference value optimal solution for actual quota allocation in the performance period.
As an improvement of the above method, the constraint condition for measuring and calculating the quota reference value in the step 3-2) includes the following constraint conditions that are satisfied simultaneously:
constraint 1: quota overall surplus Rate R t Less than 0; wherein R is t Calculated according to the following formula:
wherein Q is t Is the total quota amount, in tons; p (P) t The unit is ton for the total amount of quota to be paid; e (E) t The unit is ton for the total annual checked discharge;
constraint 2: quota overall surplus Rate R t Greater than-0.5%;
constraint 3: quota surplus of conventional coal-fired unit with 300MW grade or aboveResidual ratio R m 300MW grade and below conventional coal-fired unit quota surplus rate R n And quota surplus rate R of unconventional coal-fired unit o Satisfies the following formula:
R o ≤R n <R m
wherein m is a conventional coal-fired unit with the grade of more than 300 MW; n is a conventional coal-fired unit with the MW level of 300MW and below; o is an unconventional coal-fired unit; p is a gas unit;
constraint 4: for each type of unit, the heat supply quota surplus ratio is larger than 0, and the heat supply quota surplus ratio of each type of unit is larger than the power supply quota surplus ratio of the type of unit;
Constraint 5: the quota surplus rate of the gas unit is larger than 0.
As an improvement of the above method, the evaluation key indicators of the step 4) include: the quota overall evaluation index, the unit quota evaluation index and the key parameter evaluation index specifically comprise:
the quota overall evaluation index comprises total quota, quota surplus and quota surplus rate of all nations and all provinces;
the unit quota evaluation index: the system comprises quota total amount, quota surplus and quota surplus rate of units of different fuel types, different unit types and different product types;
the key parameter evaluation indexes comprise quota total quantity, quota surplus and quota surplus of units in different heating ratio value ranges, different cooling modes and different load coefficient ranges.
As an improvement of the above method, the various constraint conditions of the step 5) include: quota approval methods, benchmark constraints, and performance offers.
As an improvement of the above method, the step 5) specifically includes:
canceling the heat supply correction coefficient and recalculating the power supply quota; adding various unit quota total constraints and each unit quota total constraint, calculating an optimized and adjusted reference value feasible solution set by adopting an enumeration method based on the quota allocation reference value optimal solution obtained in the step 3), and obtaining an optimized and adjusted reference value optimal solution by adopting a weight analysis method.
On the other hand, the invention provides a unit-based quota reference value measuring and optimizing system for the carbon market power industry, which comprises the following components:
the data storage module is used for establishing a basic database of the unit;
the data auditing module is used for auditing the basic data of the basic database of the unit, and identifying and deleting the error data to obtain a data sample;
the reference value measuring and calculating module is used for measuring and calculating the reference value of the data sample, and obtaining a quota allocation reference value feasible solution set and an optimal solution based on an improved enumeration method;
the quota pre-evaluation module is used for pre-evaluating the implementation effect of the quota allocation benchmark value optimal solution according to the evaluation key indexes; and
and the benchmark value optimization module is used for dynamically adjusting according to the pre-evaluation and various constraint conditions to obtain an optimized quota allocation benchmark value optimal solution.
Compared with the prior art, the invention has the advantages that:
1. the invention establishes a complete power industry quota allocation reference value calculation optimization flow, and defines each key step of reference value calculation, and the method is used for quota allocation of any carbon market power industry and promotes the application and perfection of quota allocation reference line method;
2. The invention solves the problem of how to quantize the expected reference values such as policy guidance, encouragement direction and the like into the constraint condition of reference value measurement and calculation;
3. the invention solves the problem of solving the reference value under various constraint conditions, exhaustively solves all the possible solutions of the reference value under all constraint conditions, and can obtain the optimal solution of the reference value;
4. according to the invention, a carbon market quota optimization management model (CMAM) is established, so that complexity of quota reference value measurement is greatly reduced, and accuracy and efficiency of reference value measurement are improved;
5. the invention solves the problem of rapid, accurate and dynamic adjustment and optimization of the reference value when the constraint condition changes.
Drawings
FIG. 1 is a flow of a unit-based optimization method for measuring and calculating quota reference values in the electric power industry of the carbon market.
Detailed Description
In order to solve the defects in the prior art, a quota reference value measuring and optimizing method for the carbon market power industry based on a unit is provided. In order to achieve the purpose, the invention establishes a unit-based carbon market electricity industry quota reference value measurement and calculation optimization model, namely a carbon market quota optimization management model (Carbon Market Allowance Optimization Management Model, CMAM). The method can solve the following technical problems:
Firstly, a complete power industry quota allocation reference value measurement and optimization flow is established, and the problems of the reference value measurement and calculation flow and the steps are solved;
secondly, establishing a benchmark value measuring and calculating constraint condition, and solving the quantization problem of conversion from policy guidance and design expectation to constraint condition;
thirdly, solving the problem of solving the reference value under various complex constraint conditions, and exhausting all the feasible solutions of the reference value which meet all the constraint conditions to obtain a feasible solution set of the reference value and an optimal solution of the reference value;
fifthly, the problem of rapid and accurate adjustment and optimization of the reference value when the constraint condition changes is solved;
the invention discloses a quota reference value measuring and optimizing method for a carbon market power industry based on a unit. The method comprises the following steps: establishing a basic database of the unit involved in reference value measurement and calculation, and defining naming rules of standardization of various unit data; judging the accuracy of basic data of the unit, and identifying and deleting problem data; based on the data sample, calculating to obtain a quota allocation reference value optimal solution through eight specific steps of determining a unit type dividing mode, determining a quota verification method, determining a quota overall surplus ratio, calculating quota allocation balance values of each unit type, determining a quota clear-cut performance offer policy, solving a reference value feasible solution set and obtaining a reference value optimal solution; providing an evaluation key index, and pre-evaluating the implementation effect of the reference value optimal solution; and finally, dynamically adjusting the optimized quota reference value, and solving the optimized quota reference value. The invention has the advantages that a complete power industry quota allocation reference value calculation optimization flow is established, and each key step of reference value calculation is defined; solving the problem of solving the reference value optimal solution under various complex constraint conditions; the problem of quick, accurate dynamic adjustment optimization of the benchmark value when constraint conditions change is solved. Providing a reference for further optimization of the quota allocation baseline approach.
The specific method flow and the CMAM model module comprise the following steps:
(1) The data storage module aims at establishing a basic database of the unit related to reference value measurement and calculation, realizing data storage and subsequent calling, judging, supplementing, deleting and updating, and establishing naming rules for standardization of various unit attributes. The system comprises 26 parameters including sequential numbering, province, city, county, key discharge unit name, unified social credit code, national economy industry code, unit number, main fuel type, installed capacity, unit type, product type, annual energy generation, annual energy supply, heat supply ratio, operation hours, load (output) coefficient, cooling mode, whether combined filling exists, whether combined filling is carried out across unit types, whether the combined filling is a unit for mixing and burning biomass (including garbage, sludge and the like), whether the combined and burned unit is a unit for mixing and burning self-produced secondary energy (including coke oven gas, blast furnace gas, refinery dry gas, dry distillation gas and the like), various fuel consumption, various fuel low-grade heating values and annual checked discharge; (2) The data auditing module is used for identifying and deleting the problem data according to the accuracy of the unit basic data in the judging module (1) such as the data logic relation, the value range and the like of the power enterprise, and providing accurate unit data samples for subsequent calculation. Including data integrity determination, product type accuracy determination, product yield accuracy determination, and other parameter accuracy determination. (3) The reference value measuring and calculating module aims at measuring and calculating a quota allocation reference value optimal solution based on the data sample of the module (2), and the module (3) is a core module of the CMAM model and comprises eight specific steps of determining a unit type dividing mode, determining a quota verifying method, determining a quota overall surplus ratio, calculating quota allocation balance values of each unit type, determining a quota clear and pay performance discount policy, solving a reference value feasible solution set and obtaining a reference value optimal solution; (4) quota pre-evaluation module: the method aims at providing an evaluation key index and pre-evaluating the implementation effect of the reference value optimal solution. The indexes comprise quota overall evaluation indexes, unit quota evaluation indexes and key parameter evaluation indexes. (5) The benchmark value optimization module aims at combining the latest policy guidance and the development direction of the carbon market, dynamically adjusting and optimizing the quota benchmark value when the quota approval method, the benchmark constraint condition, the performance preference policy and the like are changed, and solving the optimized quota benchmark value.
The technical scheme of the invention is described in detail below with reference to the accompanying drawings and examples.
Example 1
As shown in fig. 1, embodiment 1 of the present invention proposes a unit-based quota reference value calculation optimization method for the carbon market power industry. In order to achieve the above purpose, the invention establishes a unit-based quota reference value measuring and calculating optimization model for the carbon market power industry, and based on the basic parameters of the unit units of the key emission brought into the carbon market management, and by combining constraint conditions designed by a quota allocation scheme, the invention rapidly and accurately calculates all quota reference value feasible solution sets meeting the constraint conditions to obtain the optimal solution as the value actually applied in the quota allocation scheme; meanwhile, pre-evaluating and rationality evaluating the implementation effect of the reference value optimal solution; in addition, an adjustment and optimization method for the reference value under the condition of constraint condition change is provided, and the adjusted reference value is quickly solved. Various implementation steps and methods are described in detail in connection with a CMAM model, and a specific method flow is shown in FIG. 1, including:
(1) And a data storage module: the method aims at establishing a basic database of the unit involved in reference value measurement and calculation, realizing data storage and subsequent calling, judging, supplementing, deleting and updating, and establishing naming rules for standardization of various unit attributes. All basic data and naming rules of the unit comprise: the method comprises the steps of sequentially numbering, province, city, county, key discharge unit name, unified social credit code, national economy industry code, unit number, main fuel type, installed capacity, unit type, product type, annual energy generation, annual energy supply, heat supply ratio, operation hours, load (output) coefficient, cooling mode, whether combined filling exists, whether combined filling is carried out across unit types, whether the unit is a biomass (including garbage, sludge and the like) mixed burning unit, whether the unit is a self-produced secondary energy (including coke oven gas, blast furnace gas, refinery dry gas, dry distillation gas and the like) mixed burning unit, each fuel consumption, each fuel low-level heating value and annual checked discharge amount, and the total 26 parameters are calculated;
(2) A data auditing module: the method aims at identifying and deleting problem data according to the accuracy of unit basic data in the judging module (1) such as the logic relation, the value range and the like of the power enterprise data, and providing accurate unit data samples for subsequent calculation. The method comprises the following five steps:
step one: and judging the data integrity, judging whether the 26 basic data of each unit are filled completely, and screening the missing data. If any one of the 26 parameters is missing, determining that the data is error data, and deleting the unit in the sample;
step two: judging the accuracy of the product type judgment, 1) if the annual power supply quantity of the unit is filled with 0, judging the unit as error data, and deleting the unit in a sample; 2) If the unit ' product type ' is a ' pure condensing generator set ', and the annual heat supply quantity ' data is not equal to ' 0 ', determining that the unit is wrong data, and deleting the unit in a sample; 3) If the unit ' product type ' is ' cogeneration unit ', and the annual heat supply quantity ' filling data is equal to ' 0 ', determining that the unit is wrong data, and deleting the unit in a sample;
step three: judging the accuracy of the product yield, and according to the following formula, 1) if the annual energy production of a unit is larger than the product of the installed capacity, the number of operating hours and the load coefficient of the unit, judging that the data of the energy production is wrong, and deleting the unit in a sample; 2) If the power supply quantity of the unit is larger than the power generation quantity of the unit, determining that the data of the power supply quantity is wrong, and deleting the unit in a sample; 3) If the generated energy multiplied by 3.6 is greater than the total generated energy of the unit, judging that the data is wrong, and deleting the unit in the sample;
F j >V j ×T j ×L j (1)
S j >F j (2)
Wherein F is annual energy production per megawatt hour (MW.h); v is the unit capacity of the machine, in Megawatts (MW); t is the number of operating hours, per hour (h); l is the load (output) coefficient in units; j is the number of the unit; s is annual power supply quantity, and the unit megawatt-hour (MW.h); h is annual heat supply, and is unit Gigajoule (GJ); c is the fuel consumption, for solid or liquid fuels, in tons (t), for gaseous fuels, in thousands of standard cubic meters (ten thousand meters) 3 ) The method comprises the steps of carrying out a first treatment on the surface of the NCV is the low-grade calorific value of fuel, for solid or liquid fuel, the unit is giga-joule/ton (GJ/t), for gaseous fuel, the unit is giga-joule/ten-thousand standard cubic meters (GJ/ten-thousand m) 3 ) The method comprises the steps of carrying out a first treatment on the surface of the i is a fossil fuel type;
step four: judging the accuracy of other parameters, wherein the accuracy is shown according to the following formula, 1) if the value range of the heat supply ratio of the unit does not belong to [0,1], judging that the heat supply ratio is wrong, and deleting the unit in a sample; 2) If the value range of the load (output) coefficient is not 0,1, judging that the data of the load (output) coefficient is wrong, and deleting the unit in the sample;
0≤a j ≤1 (4)
0＜L j ≤1 (5)
wherein a is the heat supply ratio in units;
(3) The reference value measuring and calculating module is used for: the method aims at calculating and obtaining an optimal solution of a quota allocation reference value based on sample data obtained by the module (2), wherein the module (3) is a core module of a CMAM model and comprises eight specific steps:
Step one: determining unit type dividing modes, wherein the heat supply and power supply reference values of different types of units are different, the unit type dividing modes determine the number of reference values (namely unknown numbers) to be solved, in the embodiment, the unit components are divided into four types, namely a conventional coal-fired unit with more than 300MW grade, a non-conventional coal-fired unit and a gas unit, the power supply and heat supply reference values of each type of unit are different, and the number of the reference values (unknown numbers) to be solved is 8;
step two: the quota checking method comprises a quota calculation formula, a correction coefficient and a quota total amount determining mode. In the case, the quota is approved by taking the unit as the minimum unit, and the total quota is obtained by summarizing from bottom to top. The enterprise quota amount is equal to the sum of all unit quota amounts of the enterprise, the regional quota amount is equal to the sum of all enterprise quota amounts in the region, and the national quota amount is equal to the sum of all regional quota amounts.
Wherein b is the enterprise number; r is the region number; t is the total amount;
the unit quota amount consists of a power supply quota and a heat supply quota which are calculated respectively. The heat supply quota of the unit is calculated according to the heat supply quantity of the unit and the heat supply reference value of the category to which the heat supply quota belongs; the power supply quota is calculated according to the unit power supply quantity, the power supply reference value of the category, the heat supply quantity correction coefficient, the cooling correction coefficient and the load (output) coefficient correction coefficient.
Q j ＝Q j，h +Q j，e (9)
Q j，h ＝H j ×B h，x (10)
Q j，e ＝S j ×B e，x ×F r，j ×F l，j ×F f，j (11)
Wherein Q is quota amount per ton (t); b (B) e For the power supply reference value of the category to which the unit belongs, the unit ton of carbon dioxide per megawatt hour (tCO 2 /MWh)；F r The heat supply quantity correction coefficient of the unit is provided; f (F) f Correcting the coefficient for the load (output) coefficient of the unit; f (F) l Correcting coefficients for the unit cooling mode; b (B) h For the heat supply reference value of the category of the unit, the unit ton of carbon dioxide per giga-coke (tCO) 2 GJ); x is the class of the unit; h represents heat supply; e represents power supply;
step three: a quota overall surplus rate is determined. The overall surplus rate of the quota in the present track period is determined, the calculation mode of the surplus rate is as follows, the calculation result is regular and represents the surplus of the quota, and the calculation result is negative and represents the quota shortage:
wherein Q is t The unit is ton, which is the total quota amount, namely the sum of quota amounts of all units; p (P) t The unit is ton, which is the total amount of the quota to be paid, namely the sum of the amounts of the quota to be paid of all units; e (E) t The unit is ton, which is the total annual checked discharge, namely the sum of annual checked discharge of all units;
step four: determining encouraging directions and policy directions of quota allocation, and quantifying the policy directions into constraint conditions for quota reference value measurement, in this case, designing 5 constraint conditions, as follows:
Constraint 1: plays roles of controlling and reducing carbon emission of enterprises in the carbon market, and improves market transaction activity. The quota total should have a gap, i.e., the quota total surplus is less than 0, as follows:
R t ＜0 (13)
constraint 2: on the basis of meeting constraint condition 1, the quota gap rate should not be too high. In this case, the quota overall gap rate is set to be greater than-0.5% and less than 0, as follows:
-0.5％＜R t ＜0 (14)
constraint 3: encourage advanced, high capacity, high energy efficiency level units, eliminate low energy efficiency lagging units. In the case, the quota surplus ratio of the conventional coal-fired unit above 300MW grade is set to be larger than the quota surplus ratio of the conventional coal-fired unit and the unconventional coal-fired unit below 300MW grade, and the absolute error of the quota surplus ratio of the conventional coal-fired unit and the unconventional coal-fired unit below 300MW grade is not more than 0.5%, and the formula is as follows:
R o ≤R n ＜R m (15)
wherein m is a conventional coal-fired unit with the grade of more than 300 MW; n is a conventional coal-fired unit with the MW level of 300MW and below; o is an unconventional coal-fired unit; p is gas unit
Constraint 4: considering the national direction of "heat protection", a suitable incentive is given to the unit heat supply. In the embodiment, the surplus rate of the heat supply quota for each type of unit is set to be larger than 0, and the surplus rate of the heat supply quota for each type of unit is set to be larger than the surplus rate of the power supply quota;
R hx >0 (17)
R hx >R ex (18)
The heat supply quota surplus ratio of the single unit is calculated according to the heat supply quota amount and the heat supply emission amount of the unit, and the power supply quota surplus ratio of the single unit is calculated according to the power supply quota amount and the power supply emission amount of the unit:
the surplus ratio of the heat supply quota of each type of unit is calculated according to the total heat supply quota amount and the heat supply emission amount of all units belonging to the category,
constraint 5: setting the overall surplus ratio of the gas unit quota to be larger than 0 for encouraging the development of the gas unit;
R p >0 (29)
step five: and calculating quota allocation balance values of each group of units according to the group classification mode and the quota approval method. The balance value characterizes the power supply and discharge amount of each type of unit to be equal to the power supply quota amount, and the power supply and heat supply quota reference value when the heat supply discharge amount is equal to the heat supply quota amount, namely when the balance value calculates the quota, the quota total amount of each type of unit is equal to the checked discharge amount, and the balance value reflects the actual discharge intensity of the unit.
A e For the power supply balance value of the class of the unit, unit ton of the unit is oxidizedCarbon per megawatt hour (tCO) 2 /MWh)；A h For the heat supply balance value of the category of the unit, the unit ton of carbon dioxide is per giga-coke (tCO) 2 /GJ)；
Step six: and determining the performance preferential policy of the quota clearing stage. In order to reduce the performance burden of a part of enterprises with larger quota gaps, a performance preferential policy is set, namely, a certain amount of quota gaps are exempted from a part of enterprises, and the amount of the enterprise to be paid is lower than the emission amount through checking. In this case, two performance preference policies are: setting an upper limit of 20% of performance gap quantity of an enterprise, namely adding 20% of checked discharge quantity to the maximum quota clearing obligation of the enterprise when the enterprise quota gap quantity accounts for more than 20% of checked discharge quantity, and setting an incomplete performance policy of the gas unit, namely adding the quota clearing obligation of the gas unit to all the acquired free quota quantity when the checked discharge quantity of the gas unit is not lower than the checked free quota quantity.
P b,max ＝Q b +20％×E b (38)
P p ＝E p (when Q p >E p ) (39)
P p ＝Q p (when Q p ≤E p ) (40)
Wherein P is b,max The method comprises the steps of (1) setting a unit ton (t) for the maximum quota amount to be paid by an enterprise;
step seven: and solving a reference value feasible solution set. Based on the balance values of power supply and heat supply quota of various units, the quota overall surplus, various constraint conditions and performance preference policies are combined, and the reference value feasible solution set meeting the conditions is solved based on an improved enumeration method. Enumeration is also known as exhaustion, i.e. enumerating elements that are eligible from all possible solutions to a problem. On the basis of the quota balance value, setting an allowable fluctuation range of each solution, gradually reducing a solution set range meeting the conditions through each constraint condition, and finally solving a feasible solution set meeting all the constraint conditions. Simple exhaustion is low-efficiency and time-consuming, and the situation that repetition is preferably deleted and the situation that repetition is unlikely to occur is preferably deleted, the simple enumeration method is improved based on the thought of the branch-and-bound method in the model, for each reference value, a larger adjustment set (for example, the total fluctuation range is set to be 5%, 10%, 20%, the value step length is set to be 1%, 2%, 5%, and the like) is firstly obtained, and if a feasible solution meeting all constraint conditions cannot be obtained, the value of the fluctuation range is enlarged; if the accuracy of the calculation result is improved, the range of the calculation step length value is reduced, and the specific calculation method of the improved enumeration method is as follows:
1. Inputting the power supply and heat supply quota balance values of various units obtained by calculation in the step five;
2. determining the fluctuation range and the calculation step length of the reference value compared with the balance value;
3. acquiring all value sets of power supply and heat supply reference values of various units in a fluctuation range and a value step range, wherein the total value of the reference values is u, and the conventional coal-fired unit sets above 300MW level are as follows:
the 300MW grade and following conventional coal-fired units are assembled as follows:
the unconventional coal-fired unit set is as follows:
the gas unit set is as follows:
4. primary screening is limited according to the total amount in the third step, and the reference value which does not meet the condition is deleted from the set;
5. screening the constraint conditions one by one according to the fourth step, and deleting the reference values which do not meet the constraint conditions from the set;
6. after each constraint condition is screened one by one, if reference values meeting all constraint conditions exist, outputting a set, wherein v reference values are taken at the moment, and the conventional coal-fired unit set with the MW level of more than 300MW is as follows:
the 300MW grade and following conventional coal-fired units are assembled as follows:
the unconventional coal-fired unit set is as follows:
the gas unit set is as follows:
7. if the solutions meeting all the constraint conditions do not exist, returning to the step 2, expanding the fluctuation range, reducing the calculation step length, and circularly calculating until a feasible solution is obtained.
Step eight: and obtaining a reference value optimal solution. And comprehensively researching and judging according to the reference value feasible solution set and a weight analysis method to obtain a reference value optimal solution for actual quota allocation in the performance period.
(4) Quota pre-evaluation module: the method aims at providing an evaluation key index and pre-evaluating the implementation effect of the reference value optimal solution. The indexes comprise:
1. quota overall evaluation index: the method comprises the steps of national quota total, quota surplus and quota surplus rate of each province;
2. unit quota assessment index: the method comprises the steps of different fuel types, different unit types, quota total amount, quota surplus and quota surplus rate of units of different product types;
3. key parameter evaluation index: the system comprises quota total amount, quota surplus and quota surplus rate of units in different heating ratio value ranges, different cooling modes and different load (output) coefficient ranges.
(5) And the reference value optimizing module: the method aims at combining the latest policy guidance with the development direction of the carbon market, dynamically adjusting a quota reference value when a quota approval method, a reference value constraint condition, a performance offer and the like are changed, and solving the optimized quota reference value, and comprises the following three specific steps:
step one: an optimization adjustment term is determined. The case changes the quota calculation method based on the original quota calculation method and the constraint conditions, and newly adds two constraint conditions:
1. The quota calculation method is changed, the heat supply correction coefficient is cancelled in the power supply quota calculation method, and the power supply quota calculation method is changed from the formula (11) to the formula (49).
Q j,e,new ＝S j ×B e,x ×F l,j ×F f,j (49)
Q j,new ＝Q j,e,new +Q j,h,new (50)
Wherein new represents the new quota measurement method.
2. Increasing the total quota constraint of each unit, namely that the recalculated total quota of each unit is close to the original total quota of each unit:
where α is the relative error, 1%, 3%, 5% ….
3. Adding quota total constraint of each unit, namely the quota total adjusted by each unit is close to the quota total calculated according to the original reference value optimal solution:
where β is the relative error, 1%, 3%, 5% ….
Step two: and solving a reference value feasible solution set. Based on the changed quota calculation formulas (49) and (50) and the newly added constraint conditions, an improved enumeration method which is the same as that in the step seven of the module (3) is adopted to calculate the optimized and adjusted reference value feasible solution set on the basis of the original reference value optimal solution. Meanwhile, considering the extreme cases of units, it is not practical that all units meet the above requirements, and the number of units capable of meeting all constraint conditions is recorded as Passnum, and the final model is as follows:
Wherein, passnum is the number of units which can meet all constraint conditions; k is
Step three: obtaining an optimized reference value optimal solution, and obtaining an optimized and adjusted reference value optimal solution by adopting a weight analysis method which is the same as that in the step eight of the module (3).
Example 2
The embodiment 2 of the invention provides a unit-based quota reference value measurement and optimization system for the carbon market power industry, which is realized based on the method of the embodiment 1, and comprises the following steps:
the data storage module is used for establishing a basic database of the unit;
the data auditing module is used for auditing the basic data of the basic database of the unit, and identifying and deleting the error data to obtain a data sample;
the reference value measuring and calculating module is used for measuring and calculating the reference value of the data sample, and obtaining a quota allocation reference value feasible solution set and an optimal solution based on an improved enumeration method;
the quota pre-evaluation module is used for pre-evaluating the implementation effect of the quota allocation benchmark value optimal solution according to the evaluation key indexes;
the benchmark value optimization module is used for dynamically adjusting according to the pre-evaluation and various constraint conditions to obtain an optimized quota allocation benchmark value optimal solution
Finally, it should be noted that the above embodiments are only for illustrating the technical solution of the present invention and are not limiting. Although the present invention has been described in detail with reference to the embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the present invention, which is intended to be covered by the appended claims.
Claims (9)
1. A method for optimizing quota benchmark value measurement in a carbon market power industry based on a unit, the method comprising:
step 1) establishing a basic database of a unit;
step 2) auditing the unit basic data of the unit basic database, and identifying and deleting error data to obtain a data sample;
step 3) carrying out benchmark value measurement and calculation on the data sample, and obtaining a quota allocation benchmark value feasible solution set and an optimal solution based on an improved enumeration method;
step 4) pre-evaluating the implementation effect of the quota allocation benchmark value optimal solution according to the evaluation key indexes;
and 5) dynamically adjusting according to the pre-evaluation and various constraint conditions to obtain an optimized quota allocation reference value optimal solution.
2. The unit-based carbon market power industry quota reference value measurement and optimization method according to claim 1, wherein the basic data of the basic database of step 1) includes: sequential numbering, province, city, county, key emission unit name, unified social credit code, national economy industry code, unit number, main fuel type, installed capacity, unit type, product type, annual energy production, annual energy supply, annual heat supply, heat supply ratio, number of operating hours, load factor, cooling mode, whether combined loading exists, whether combined loading is across unit type, whether a biomass unit is co-fired, whether a secondary energy unit is co-fired, various fuel consumption, various low-level heat productivity of fuel and annual checked emission.
3. The unit-based carbon market electricity industry quota reference value measurement and optimization method according to claim 2, wherein said step 2) includes:
step 2-1), judging whether the basic data of each unit is filled completely, if any parameter is missing, judging that the basic data is error data, and deleting the unit from a sample;
step 2-2) judging the accuracy of the product type of each unit, if the annual power supply is filled to 0, or the product type is a pure condensing generator set, the annual heat supply data is not equal to 0, or the product type is a cogeneration unit, and the annual heat supply filling data is equal to 0; determining that the data is error data, and deleting the unit from the sample;
step 2-3) judging the product yield accuracy of each unit:
annual energy production F of unit with unit number j j If any one of the following formulas is met, judging that the generated energy data is wrong, and deleting the unit in a sample;
F j >V j ×T j ×L j
S j >F j
wherein F is j Annual energy production for unit number j in megawatt hours; v (V) j The unit capacity of the unit is j, and the unit is megawatt; t (T) j The number of operating hours of the unit with the unit number j is L j The unit is the unit load coefficient of the unit number j; s is S j Annual power supply quantity of a unit with the unit number j is megawatt-hour; h j Annual heat supply for a unit with unit number j is achieved, and the unit is gigajoule; c (C) i,j The fuel consumption of the ith fossil fuel type of the unit with the unit number j is ton for solid or liquid fuel and ten thousand standard cubic meters for gas fuel; NCV (NCV) i,j The unit number j is the low-level heating value of the ith fossil fuel type of the unit, for solid or liquid fuel, the unit is giga-joule/ton, and for gas fuel, the unit is giga-joule/ten thousand standard cubic meters; i is a fossil fuel type; j is the number of the unit; n is the total number of fossil fuel types;
and 2-4) if the unit of the heat supply ratio of each unit is that the value range does not belong to [0,1] or the value range of the load coefficient does not belong to [0,1], judging that the unit is wrong data, and deleting the unit from the sample.
4. The unit-based carbon market electricity industry quota reference value measurement and optimization method according to claim 2, wherein said step 3) includes:
step 3-1) dividing according to unit types, respectively calculating the power supply quota amount and the heat supply quota amount of each unit to obtain quota amounts of each unit, and calculating according to quota amounts of each unit to obtain quota surplus ratio of each unit; each unit comprises: a conventional coal-fired unit with a MW level above 300MW level, a conventional coal-fired unit with a MW level below 300MW level, an unconventional coal-fired unit and a gas unit;
Step 3-2) determining the encouraging direction and policy direction of quota allocation, and quantifying the policy direction into constraint conditions for quota reference value measurement;
step 3-3) calculating quota allocation balance values of various units according to a quota approval method, wherein the quota allocation balance values comprise: the power supply balance value and the heat supply balance value of the conventional coal-fired unit above 300MW grade, the power supply balance value and the heat supply balance value of the conventional coal-fired unit below 300MW grade, the power supply balance value and the heat supply balance value of the unconventional coal-fired unit and the power supply balance value and the heat supply balance value of the gas-fired unit;
step 3-4) determining the fluctuation range and the calculation step length of the reference value compared with the balance value;
step 3-5) obtaining value sets of power supply reference values and heat supply reference values of various units in a fluctuation range and a value step range, wherein u reference values of each set are obtained;
step 3-6) further screening each set of the step 3-5) according to the constraint condition of the step 3-2), deleting the reference value which does not meet the constraint condition, and deleting the reference value from the set; if the reference value meeting all the constraint conditions exists, the step 3-7 is carried out; otherwise, turning to the step 3-4) to expand the fluctuation range and reduce the calculation step length, and circularly calculating until the reference value meeting all constraint conditions is obtained, and turning to the step 3-7);
Step 3-7) outputting a reference value feasible solution set comprising v reference value feasible solutions;
and 3-8) comprehensively judging according to the reference value feasible solution set and a weight analysis method to obtain a reference value optimal solution for actual quota allocation in the performance period.
5. The unit-based carbon market power industry quota reference value measurement optimization method according to claim 4, wherein the constraint conditions of the quota reference value measurement in step 3-2) include the following constraint conditions that are satisfied simultaneously:
constraint 1: quota overall surplus Rate R t Less than 0; wherein R is t Calculated according to the following formula:
wherein Q is t Is the total quota amount, in tons; p (P) t The unit is ton for the total amount of quota to be paid; e (E) t Is the general menstrual nucleusChecking the discharge amount, wherein the unit is ton;
constraint 2: quota overall surplus Rate R t Greater than-0.5%;
constraint 3: quota surplus ratio R of conventional coal-fired unit with 300MW grade or above m 300MW grade and below conventional coal-fired unit quota surplus rate R n And quota surplus rate R of unconventional coal-fired unit o Satisfies the following formula:
R o ≤R n <R m
wherein m is a conventional coal-fired unit with the grade of more than 300 MW; n is a conventional coal-fired unit with the MW level of 300MW and below; o is an unconventional coal-fired unit; p is a gas unit;
Constraint 4: for each type of unit, the heat supply quota surplus ratio is larger than 0, and the heat supply quota surplus ratio of each type of unit is larger than the power supply quota surplus ratio of the type of unit;
constraint 5: the quota surplus rate of the gas unit is larger than 0.
6. The unit-based carbon market power industry quota reference value measurement and optimization method according to claim 1, wherein the evaluation key index of step 4) comprises: the quota overall evaluation index, the unit quota evaluation index and the key parameter evaluation index specifically comprise:
the quota overall evaluation index comprises total quota, quota surplus and quota surplus rate of all nations and all provinces;
the unit quota evaluation index: the system comprises quota total amount, quota surplus and quota surplus rate of units of different fuel types, different unit types and different product types;
the key parameter evaluation indexes comprise quota total quantity, quota surplus and quota surplus of units in different heating ratio value ranges, different cooling modes and different load coefficient ranges.
7. The unit-based carbon market power industry quota reference value measurement and optimization method according to claim 1, wherein the various constraint conditions of step 5) include: quota approval methods, benchmark constraints, and performance offers.
8. The unit-based carbon market electricity industry quota reference value measurement and optimization method according to claim 7, wherein the step 5) specifically includes:
canceling the heat supply correction coefficient and recalculating the power supply quota; adding various unit quota total constraints and each unit quota total constraint, calculating an optimized and adjusted reference value feasible solution set by adopting an enumeration method based on the quota allocation reference value optimal solution obtained in the step 3), and obtaining an optimized and adjusted reference value optimal solution by adopting a weight analysis method.
9. A unit-based quota reference value measurement and optimization system for the carbon market power industry, the system comprising:
the data storage module is used for establishing a basic database of the unit;
the data auditing module is used for auditing the basic data of the basic database of the unit, and identifying and deleting the error data to obtain a data sample;
the reference value measuring and calculating module is used for measuring and calculating the reference value of the data sample, and obtaining a quota allocation reference value feasible solution set and an optimal solution based on an improved enumeration method;
the quota pre-evaluation module is used for pre-evaluating the implementation effect of the quota allocation benchmark value optimal solution according to the evaluation key indexes; and
And the benchmark value optimization module is used for dynamically adjusting according to the pre-evaluation and various constraint conditions to obtain an optimized quota allocation benchmark value optimal solution.
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