Method for evaluating energy conservation of wind heat storage system based on game theory

Abstract

The invention relates to the technical field of energy internet energy-saving evaluation, and discloses a wind heat storage system energy-saving evaluation method based on the game theory, and the method comprises the following steps: building an evaluation index system model which comprises an energy efficiency index, an energy structure index and a unit electric quantity pollutant emission index; establishing a GTCE-TOPSIS evaluation method model, determining a weight value of an evaluation index value by adopting a subjective weight method AHP and an objective weight method EWM, and carrying out integration on a weight result; the method comprises the following steps: constructing a weighting matrix, calculating a positive ideal solution and a negative ideal solution of each to-be-evaluated object in the weighting matrix, and the distance of the positive ideal solution and the distance of the negative ideal solution, then calculating the closeness values of the to-be-evaluated objects, and finally carrying out grade division on the closeness values to obtain a final grade. On the premise that a comfortable indoor environment is provided for a user, energy is saved, consumption of clean energy is promoted, and therefore the clean development target of an energy system is further achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy internet energy-saving assessment, and in particular to an energy-saving assessment method for a wind-heat storage system based on game theory. Background Art

[0002] With the continuous growth of energy demand and the diversification of energy structure, hybrid energy system (i.e. regional integrated energy system) has attracted extensive attention as an efficient and flexible energy supply method. Hybrid energy system integrates multiple energy types to achieve energy complementarity and optimal utilization, which is of great significance for improving energy utilization efficiency, reducing energy consumption and reducing environmental pollution.

[0003] Most of the existing studies evaluate the energy efficiency of hybrid energy systems based on the first law of thermodynamics or the second law of thermodynamics. However, these studies fail to fully consider the physical characteristics of multi-heterogeneous energy coupling and the unification of energy quantity, quality and efficiency scales during the evaluation. In addition, most of the existing energy efficiency evaluations focus on the system level, and lack research that decomposes energy efficiency evaluation to the subsystem level, equipment level, or even component level, which limits the accuracy of energy efficiency diagnosis and improvement. The existing comprehensive evaluation methods can be mainly divided into subjective evaluation methods and objective evaluation methods. The subjective evaluation method evaluates the object based on the opinions of experts on the object. This type of method can make full use of subjective experience when there is a lack of data. The participation of human factors makes the evaluation results subjective and inaccurate. The objective evaluation method evaluates based on objective data, and its evaluation results are relatively objective, but it only reflects the differences between the data, and sometimes results that are completely opposite to the facts appear; and the existing methods cannot meet the needs of energy-saving effect evaluation of multi-energy coupling and complementation systems, and do not consider the needs of users in terms of energy comfort. Summary of the invention

[0004] The purpose of the present invention is to provide an energy-saving evaluation method for a wind-heat storage system based on game theory in order to improve the mismatch between energy saving and user comfort.

[0005] The technical solution adopted by the present invention is as follows:

[0006] A method for energy-saving evaluation of a wind-heat storage system based on game theory comprises the following steps: establishing an evaluation index system model, including three types of indicators: energy efficiency index, energy structure index and unit electricity pollutant emission, wherein the energy structure index includes system comprehensive energy efficiency, energy storage capacity and thermal comfort; establishing a GTCE-TOPSIS evaluation method model, according to the comprehensive energy efficiency evaluation index value obtained by the evaluation index system model, using the subjective weight method AHP and the objective weight method EWM to determine the weight value of the evaluation index value, and centralizing the weight results; constructing a weighted matrix, calculating the positive ideal solution and the negative ideal solution of each object to be evaluated in the weighted matrix, as well as the distance between the positive ideal solution and the distance between the negative ideal solution, and then calculating the closeness value of the object to be evaluated, and finally classifying the closeness value to obtain the final grade.

[0007] It should be noted that the final grade is used to judge the match between user comfort and energy saving needs.

[0008] Furthermore, the energy efficiency index model includes the following:

[0009] S1: Thermal power plant power generation efficiency index model:

[0010]

[0011] Among them, P CON Represents the power generation of thermal power plants; ρ CON Indicates the calorific value parameter of the fuel in the thermal power plant; F CON It indicates the amount of coal consumed by the corresponding power generation of the thermal power plant;

[0012] S2: Thermal power plant power generation efficiency index model:

[0013]

[0014] Among them, P CHP represents the power generation of thermal power plant, ρ CHP represents the calorific value parameter of the fuel in the thermal power plant, λ represents the thermal power ratio of the thermal power plant, F CHP Indicates the amount of coal consumed corresponding to the power generation of thermal power plants;

[0015] S3: Thermal power plant heat production efficiency index model:

[0016]

[0017] Among them, Q CHP represents the heat output of the thermal power plant, ρ CHP Indicates the calorific value parameter of the fuel in the thermal power plant, F CHP It indicates the amount of coal consumed by the thermal power plant corresponding to the heat output;

[0018] S4: Coal consumption per unit of electricity in thermal power plants:

[0019]

[0020] Among them, F CON Indicates the amount of coal consumed by the corresponding power generation of the thermal power plant, P CON It represents the power generation of thermal power plants;

[0021] S5: Coal consumption per unit of electricity in thermal power plants:

[0022]

[0023] Where, λ represents the thermal power ratio of the thermal power plant, F CHP Indicates the amount of coal consumed by the thermal power plant for power generation, P CHP It represents the power generation of thermal power plant;

[0024] S6: Coal consumption per unit heat index model for thermal power plants:

[0025]

[0026] Where, λ represents the thermal power ratio of the thermal power plant, F CHP Indicates the amount of coal consumed by the thermal power plant for power generation, Q CHP Represents the heat output of thermal power plants.

[0027] Furthermore, the energy structure indicator model includes the following:

[0028] T1: Comprehensive energy efficiency index model:

[0029]

[0030] Among them, P load , Q load Respectively represent the electrical and thermal loads of the system; H in , H out They represent the charging and discharging power of the heat storage tank, γ represents the thermal power ratio of the thermal power plant, ρ represents the total heat generated by the combustion of a unit of traditional energy, F represents the amount of coal consumed by the system, and P W Indicates wind power supply, P EB It indicates the amount of electricity used by the electric boiler. A indicates the sign of the abundance of wind power. When the minimum power output of the thermal power plant unit and the cogeneration power plant unit and the wind farm output are less than or equal to the power load, A is 0, otherwise A is 1. η indicates the electric-heat conversion efficiency of the electric boiler.

[0031] T2: Energy storage capacity index model:

[0032] D8=E S

[0033] Among them, E S is the energy storage capacity;

[0034] T3: Thermal comfort index model is:

[0035]

[0036] Among them, I TC The index reflects the ratio of the difference between the expected heat exchange and the actual heat exchange to the standard heat exchange, that is, the relative degree of deviation of the actual heat exchange from the expected heat exchange, T sub Indicates the psychological expected temperature, that is, the set temperature, T s Indicates standard temperature, T b Indicates the human body surface temperature, T id Indicates the actual room temperature.

[0037] Furthermore, the unit electricity pollutant emission index model includes the following:

[0038] P1: System unit electricity CO2 emission model:

[0039]

[0040] Among them, η represents the CO2 emission coefficient corresponding to standard coal, P CON , P CHP Represent the power generation of thermal power plants and thermal power plants respectively, F CON Indicates the amount of coal consumed by the corresponding power generation of the thermal power plant, F CHP Indicates the amount of coal consumed corresponding to the power generation of thermal power plants;

[0041] P2: System unit power NO X Emission model:

[0042]

[0043] Among them, τ represents the NO corresponding to standard coal X Emission factor, F CON Indicates the amount of coal consumed by the corresponding power generation of the thermal power plant, F CHP Indicates the amount of coal consumed by the thermal power plant for power generation, P CON , P CHP Represent the power generation of thermal power plants and thermal power plants respectively;

[0044] P3: System unit electricity SO2 emission model:

[0045]

[0046] In the formula, ψ represents the SO2 emission coefficient corresponding to standard coal, F CON Indicates the amount of coal consumed by the corresponding power generation of the thermal power plant, F CHP Indicates the amount of coal consumed by the thermal power plant for power generation, PCON , P CHP Represent the power generation of thermal power plants and thermal power plants respectively.

[0047] Furthermore, the GTCE-TOPSIS evaluation method also includes using the game theory comprehensive subjective weight method AHP to determine the weight value of each indicator based on the importance of each indicator by experts, and using the objective weight method EWM to determine the weight value of each indicator using the objective data of the indicator. The weight values ​​obtained by using different weighting methods are regarded as the two sides of the game, and they are combined into a strategy set, and the GTCE-TOPSIS evaluation method model is used to solve the weight value.

[0048] Furthermore, the steps of using game theory to combine subjective and objective weighting methods to determine the weights of energy-saving evaluation indicators of wind-heat storage system considering thermal comfort include the following:

[0049] Determine the weights of the two parties in the game, I, as AHP and EWM, that is, I = {W S ,W O},W S is the weight matrix of AHP, W O is the weight value matrix of EWM;

[0050] Determine the strategy space: The strategy space is the weight set W obtained by the two weighting methods.

[0051] W=W S ×W O

[0052] in, represents the weight vector obtained by AHP, n is the total number of indicators, represents the weight vector using EWM;

[0053] W z Represents the weight vector formed by linear combination of the weights of n feature indicators:

[0054]

[0055] in,

[0056] Determine the profit function: Determine all possible weight vectors W z After that, the optimal weight vector is obtained;

[0057]

[0058] The export is as follows:

[0059]

[0060] The linear equation corresponding to this formula is shown as follows:

[0061]

[0062] Calculate (a1, a2, ..., a n ), and normalize it as follows:

[0063]

[0064] Then the comprehensive weight of game theory is:

[0065]

[0066] in, is the transposed matrix of the policy space of the weight sets of the two weighting methods.

[0067] Furthermore, the positive ideal solution and the negative ideal solution of each object to be evaluated in the weighted matrix are calculated:

[0068]

[0069] Among them, a + is a positive ideal solution, a - is a negative ideal solution;

[0070] Calculate the distance D+ and the distance D- from the positive ideal solution to the object to be evaluated: The distance D+ and the distance D- from the positive ideal solution and the negative ideal solution are calculated according to the following formula:

[0071]

[0072] Calculate the closeness value C of the object to be evaluated:

[0073]

[0074] Grade classification: The object to be evaluated is graded according to its closeness value C.

[0075] Furthermore, in the thermal comfort index model, by comparing the user's psychological expected temperature, that is, the set temperature T sub and the actual indoor temperature T id The size of the heat exchange rate, as well as the ratio of the difference between the expected heat exchange rate and the actual heat exchange rate to the standard heat exchange rate I TC , you can determine user needs;

[0076] The judgment method is:

[0077] When T sub -T id >0, I TC>0, that is, the set temperature is higher than the actual indoor temperature, indicating that the user expects the heating temperature to increase;

[0078] When T sub -T id <0, I TC <0, that is, the set temperature is lower than the actual indoor temperature, indicating that the user expects the heating temperature to be lowered;

[0079] When T sub -T id =0,I TC =0, that is, the set temperature is equal to the actual indoor temperature, indicating that the temperature set by the user is the same as the indoor temperature, the temperature meets the user's expectations, and the user's physiological comfort, psychological comfort, and thermal comfort feel optimal.

[0080] Furthermore, the calculation of each evaluation index value includes the following steps:

[0081] AHP indicator weight calculation: determine the judgment matrix, calculate the consistency ratio CR, judge the size of CR and 0.1, when CR>0.1, consult experts to adjust the judgment matrix; when CR≤0.1, calculate the AHP weight;

[0082] EWM indicator weight calculation: perform standardization operations, determine the standardization of positive and negative indicators, and determine the numerical matrix X;

[0083]

[0084] Among them, x ij is the value of the jth indicator of the i-th sample, (i=1,2,…,m; j=1,2,…,n);

[0085] Calculate the weight of the jth indicator of the i-th sample:

[0086]

[0087] Calculate the information entropy of the indicator:

[0088]

[0089] Calculate the information redundancy of the indicator:

[0090] d j =1-e j

[0091] Calculate the evaluation index weight vector:

[0092]

[0093] in,

[0094] Furthermore, the levels are divided into high level, relatively high level, medium level, relatively low level and low level, and the specific division values ​​are:

[0095] High level: C ≥ 0.8;

[0096] Higher level: 0.6≤C<0.8;

[0097] Medium level: 0.4≤C<0.6;

[0098] Lower level: 0.2≤C<0.4;

[0099] Low level: C<0.2.

[0100] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0101] The present invention determines weights by combining the subjective weight method AHP and the objective weight method EWM through game theory, coordinates the matching problem of system energy saving and user comfort needs, and determines the weight value of the evaluation model index system by combining experts' experience in comfort and energy saving and objective data, thereby comprehensively considering the needs between energy saving and user comfort, saving energy and promoting the consumption of clean energy on the premise of providing users with a comfortable indoor environment, thereby further achieving the clean development goal of the energy system. BRIEF DESCRIPTION OF THE DRAWINGS

[0102] Figure 1 It is a schematic diagram of the evaluation model structure of the present invention;

[0103] Figure 2 The weight value diagram of each index of AHP adopted by the present invention;

[0104] Figure 3 This is a graph of weight values ​​of various indicators of EWM used in the present invention;

[0105] Figure 4 This is a graph of weight values ​​of various indicators using GTCE-TOPSIS in the present invention;

[0106] Figure 5 It is a schematic diagram of the GTCE-TOPSIS evaluation calculation results of the present invention. DETAILED DESCRIPTION

[0107] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0108] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0109] An energy-saving evaluation index model for the wind-heat storage system is established from the three aspects of the system's energy efficiency, energy structure, and pollutant emissions per unit of electricity, as well as the user's thermal comfort index. Secondly, in order to address the mismatch between the system's energy-saving requirements and the needs to meet the user's thermal comfort in the energy-saving evaluation of the wind-heat storage system considering thermal comfort, a GTCE-TOPSIS comprehensive evaluation model is constructed based on game theory, and the weight values ​​of the AHP subjective and EWM objective indicators are aggregated to coordinate the needs between system energy saving and meeting the user's thermal comfort requirements. Finally, the evaluation results of the comprehensive energy-saving effects of the three schemes are compared to verify the effectiveness of the evaluation model.

[0110] like Figure 1-5 As shown in the figure, a wind-heat storage system energy-saving evaluation method based on game theory is constructed according to the characteristics of the wind-heat storage system, including energy efficiency indicators:

[0111] Evaluation index system: including energy efficiency index, energy structure index and pollutant emission per unit of electricity. Among them, energy efficiency index includes power generation efficiency of thermal power plant, power generation efficiency of thermal power plant, heat production efficiency of thermal power plant, coal consumption per unit of electricity of thermal power plant, coal consumption per unit of electricity of thermal power plant and coal consumption per unit of heat of thermal power plant; energy structure index mainly includes system comprehensive energy efficiency, energy storage capacity and thermal comfort; pollutant emission per unit of electricity includes system unit of electricity CO2, NO X and SO2 emissions; reflects the comprehensive utilization of multiple energy sources in the system;

[0112] A GTCE-TOPSIS evaluation method model is established. According to the comprehensive energy efficiency evaluation index value obtained from the evaluation index system model, the subjective weight method AHP and the objective weight method EWM are used to determine the weight value of the evaluation index value, and the weight results are centralized; a weighted matrix is ​​constructed, and the positive ideal solution and negative ideal solution of each object to be evaluated in the weighted matrix, as well as the distance between the positive ideal solution and the distance between the negative ideal solution, are calculated, and then the closeness value of the object to be evaluated is calculated. Finally, the closeness value is graded to obtain the final grade.

[0113] The final level is divided into a range. The higher the level, the better the matching problem between energy-saving goals and user comfort can be improved, and the energy-saving goal can be achieved while satisfying user comfort.

[0114] The energy-saving evaluation method of wind-heat storage system based on game theory effectively improves the mismatch between energy-saving goals and meeting the comfort of thermal users by constructing an evaluation index system and a GTCE-TOPSIS evaluation method model. This method not only improves the accuracy and reliability of the evaluation, but also provides strong support for the optimized operation of the wind-heat storage system.

[0115] The energy efficiency index model includes the following:

[0116] S1: Thermal power plant power generation efficiency index model:

[0117]

[0118] Among them, P CON Represents the power generation of thermal power plants; ρ CON Indicates the calorific value parameter of the fuel in the thermal power plant; F CON It indicates the amount of coal consumed by the corresponding power generation of the thermal power plant;

[0119] S2: Thermal power plant power generation efficiency index model:

[0120]

[0121] Among them, P CHP represents the power generation of thermal power plant, ρ CHP represents the calorific value parameter of the fuel in the thermal power plant, λ represents the thermal power ratio of the thermal power plant, F CHP Indicates the amount of coal consumed corresponding to the power generation of thermal power plants;

[0122] S3: Thermal power plant heat production efficiency index model:

[0123]

[0124] Among them, Q CHP represents the heat output of the thermal power plant, ρ CHP Indicates the calorific value parameter of the fuel in the thermal power plant, F CHP It indicates the amount of coal consumed by the thermal power plant corresponding to the heat output;

[0125] S4: Coal consumption per unit of electricity in thermal power plants:

[0126]

[0127] Among them, F CON Indicates the amount of coal consumed by the corresponding power generation of the thermal power plant, P CON It represents the power generation of thermal power plants;

[0128] S5: Coal consumption per unit of electricity in thermal power plants:

[0129]

[0130] Where, λ represents the thermal power ratio of the thermal power plant, F CHP Indicates the amount of coal consumed by the thermal power plant for power generation, P CHP It represents the power generation of thermal power plant;

[0131] S6: Coal consumption per unit heat index model for thermal power plants:

[0132]

[0133] Where, λ represents the thermal power ratio of the thermal power plant, F CHP Indicates the amount of coal consumed by the thermal power plant for power generation, Q CHP Represents the heat output of thermal power plants.

[0134] By setting weights for the indicators of the three models of energy efficiency index, energy structure index and pollutant emission per unit of electricity, the energy structure indicators of thermal power plants and thermal power plants are determined, which facilitates the subsequent determination of their weights.

[0135] The energy structure indicator model includes the following:

[0136] T1: Comprehensive energy efficiency index model:

[0137]

[0138] Among them, P load , Q load Respectively represent the electrical and thermal loads of the system; H in , H out They represent the charging and discharging power of the heat storage tank, γ represents the thermal power ratio of the thermal power plant, ρ represents the total heat generated by the combustion of a unit of traditional energy, F represents the amount of coal consumed by the system, and P W Indicates wind power supply, P EB Indicates the amount of electricity used by the electric boiler, A indicates, η

[0139] T2: Energy storage capacity index model:

[0140] D8=E S

[0141] Among them, E S is the energy storage capacity;

[0142] T3: Thermal comfort index model is:

[0143]

[0144] Among them, I TC The index reflects the ratio of the difference between the expected heat exchange and the actual heat exchange to the standard heat exchange, that is, the relative degree of deviation of the actual heat exchange from the expected heat exchange, T sub Indicates the psychological expected temperature, that is, the set temperature, T s Indicates standard temperature, T b Indicates the human body surface temperature, T id Indicates the actual room temperature.

[0145] The energy structure index is used to reflect the comprehensive utilization of various energy sources. By setting the user's psychological expected temperature value and comparing it with the actual indoor temperature, the thermal comfort index is obtained, thereby quantifying the user's comfort demand.

[0146] The unit electricity pollutant emission index model includes the following:

[0147] P1: System unit electricity CO2 emission model:

[0148]

[0149] Among them, η represents the CO2 emission coefficient corresponding to standard coal, P CON , P CHP Represent the power generation of thermal power plants and thermal power plants respectively, F CON Indicates the amount of coal consumed by the corresponding power generation of the thermal power plant, F CHP Indicates the amount of coal consumed corresponding to the power generation of thermal power plants;

[0150] P2: System unit power NO X Emission model:

[0151]

[0152] Among them, τ represents the NO corresponding to standard coal X Emission factor, F CON Indicates the amount of coal consumed by the corresponding power generation of the thermal power plant, F CHP Indicates the amount of coal consumed by the thermal power plant for power generation, P CON , P CHP Represent the power generation of thermal power plants and thermal power plants respectively;

[0153] P3: System unit electricity SO2 emission model:

[0154]

[0155] In the formula, ψ represents the SO2 emission coefficient corresponding to standard coal, F CON Indicates the amount of coal consumed by the corresponding power generation of the thermal power plant, F CHP Indicates the amount of coal consumed by the thermal power plant for power generation, P CON , P CHP Represent the power generation of thermal power plants and thermal power plants respectively.

[0156] In order to more comprehensively consider the system performance and user comfort, a scientific and reliable evaluation model needs to be constructed. The GTCE-TOPSIS evaluation method also includes using the game theory comprehensive subjective weight method AHP to determine the weight value of each indicator by relying on the importance of each indicator by experts, and using the objective weight method EWM to determine the weight value of each indicator using the objective data of the indicator, treating the weight values ​​obtained by different weighting methods as the two sides of the game, and combining them into a strategy set, and using the GTCE-TOPSIS evaluation method model to solve the weight value.

[0157] By adopting the GTCE-TOPSIS evaluation method model, combined with game theory, and integrating the subjective weight method AHP and the objective weight method EWM, the weight value of each evaluation index is determined, and then the energy-saving evaluation of the wind-heat storage system is carried out.

[0158] like Figure 2-4 As shown in the figure, the steps of using game theory to combine subjective and objective weighting methods to determine the weights of energy-saving evaluation indicators of wind-heat storage system considering thermal comfort include the following:

[0159] Determine the weights of the two parties in the game, I, as AHP and EWM, that is, I = {W S ,W O},W S is the weight matrix of AHP, W O is the weight value matrix of EWM;

[0160] Determine the strategy space: The strategy space is the weight set W obtained by the two weighting methods.

[0161] W=W S ×W O

[0162] in, represents the weight vector obtained by AHP, n is the total number of indicators, represents the weight vector using EWM;

[0163] W z Represents the weight vector formed by linear combination of the weights of n feature indicators:

[0164]

[0165] in, is the transposed matrix of the policy space of the weight sets of the two weighting methods.

[0166] Determine the profit function: Determine all possible weight vectors W z After that, the optimal weight vector is obtained;

[0167]

[0168] The export is as follows:

[0169]

[0170] The linear equation corresponding to this formula is shown as follows:

[0171]

[0172] Calculate (a1, a 2, K,a n ), and normalize it as follows:

[0173]

[0174] Then the comprehensive weight of game theory is:

[0175]

[0176] The process of using AHP is to first determine the indicator system to build a hierarchical model, build a judgment matrix, calculate the weight vector, and test the consistency; the meaning of consistency test is to determine whether there are logical problems in the constructed judgment matrix.

[0177] Solve the CR value based on CI and RI, and compare CR with 0.1 to determine whether they are consistent;

[0178]

[0179] Among them, CI and RI are consistency indicators. When CI = 0, the matrix is ​​completely consistent. The larger the CI, the more serious the inconsistency of the judgment matrix.

[0180] When CR ≥ 0.1, experts were consulted to adjust the judgment matrix; when CR < 0.1, the consistency of the matrix was considered to be within the permissible range, and the AHP weight was calculated.

[0181] Using the AHP hierarchical analysis method, phenomena or problems are decomposed into relevant factors according to their nature, and classified according to the relationship between them to form a multi-level structural model. Then, through experience or experts, the relative importance of low-level factors to high-level factors is judged and measured, and the weight ranking is obtained according to the degree of importance, and then quantitative analysis and comparison can be performed. The core of the hierarchical analysis method is to hierarchize and digitize the influencing factors. It decomposes an abstract phenomenon or problem from difficult to easy, making it easy to intuitively judge complex problems and make decisions. The hierarchical analysis method has the advantages of simplifying complex problems and simple calculations. It is widely used, such as in many fields and aspects such as personnel quality assessment, multi-scheme comparison, scientific and technological achievement evaluation, and work performance evaluation.

[0182] The GTCE-TOPSIS evaluation method includes the following:

[0183] Calculate the positive ideal solution and negative ideal solution of each object to be evaluated in the weighted matrix:

[0184]

[0185] Among them, a + is a positive ideal solution, a - is a negative ideal solution;

[0186] Calculate the distance D+ between the object to be evaluated and the positive ideal solution, and the distance D- between the object to be evaluated and the negative ideal solution:

[0187]

[0188] Calculate the closeness value C of the object to be evaluated:

[0189]

[0190] Grade classification: The object to be evaluated is graded according to its closeness value C.

[0191] Based on the normalized original data matrix, the cosine method is used to find the best and worst solutions among the finite solutions, and then the distance between each evaluation object and the best and worst solutions is calculated respectively to obtain the relative closeness between each evaluation object and the best solution, which is used as the basis for evaluation. This method has no strict restrictions on data distribution and sample content, and data calculation is simple and easy.

[0192] Depend on Figure 5 It can be seen that scheme one uses the AHP hierarchical analysis method to calculate the subjective weight, scheme two uses the entropy weight method EWM to calculate the objective weight, and scheme three uses the GTCE-TOPSIS evaluation method; from the experimental results, it can be seen that the C value of scheme three is the largest, so energy saving is more in line with user comfort requirements.

[0193] In the thermal comfort index model, by comparing the user's psychological expectation temperature, that is, the set temperature T sub and the actual indoor temperature T id The size of the heat exchange rate, as well as the ratio of the difference between the expected heat exchange rate and the actual heat exchange rate to the standard heat exchange rate I TC , you can determine user needs;

[0194] The judgment method is:

[0195] When T sub -T id >0, I TC >0, that is, the set temperature is higher than the actual indoor temperature, indicating that the user expects the heating temperature to increase;

[0196] When T sub -T id <0, I TC <0, that is, the set temperature is lower than the actual indoor temperature, indicating that the user expects the heating temperature to be lowered;

[0197] When T sub -T id =0,I TC =0, that is, the set temperature is equal to the actual indoor temperature, indicating that the temperature expected by the user is the same as the indoor temperature at this time, and the temperature meets the user's expectations, which represents the user's physiological and psychological comfort state, and the thermal comfort feels optimal. At this time, the user's comfort needs are met, and the index system is further improved.

[0198] The analytic hierarchy process (AHP) and entropy weight method (EWM) are used to calculate the subjective weight and objective weight of the indicators respectively, aiming to provide a more comprehensive and accurate weight distribution for system evaluation. The calculation of each evaluation indicator value includes the following steps:

[0199] AHP indicator weight calculation: determine the judgment matrix. According to the hierarchical structure of the evaluation system, invite experts to compare the indicators at the same level in pairs to form a judgment matrix. The elements of the judgment matrix are usually expressed using a 1-9 scale, where 1 means that the two indicators are equally important, 9 means that one indicator is more important than the other, and the middle numbers represent different degrees of comparison results. Calculate the consistency ratio CR and judge the size of CR and 0.1. When CR>0.1, consult experts to adjust the judgment matrix; when CR≤0.1, calculate the AHP weight;

[0200] EWM indicator weight calculation: perform standardization operations, collect actual data of each indicator, and construct the original data matrix. Since the dimensions and value ranges of each indicator may be different, it is necessary to standardize the original data to obtain the standardized numerical matrix X, determine the numerical matrix X; for each element in the numerical matrix X, calculate the weight in its column (i.e. the same indicator), obtain the weight matrix, and calculate the weight Z of the jth indicator of the i-th sample ij , calculate the information entropy ej of the indicator. The smaller the information entropy, the greater the amount of information of the indicator and the higher its contribution in the evaluation. Calculate the information redundancy dj of the indicator. Information redundancy is the complement of information entropy. The greater the information redundancy, the higher the contribution of the indicator in the evaluation. Calculate the evaluation indicator weight vector W according to the information redundancy of each indicator.

[0201] The weight values ​​of the evaluation model index system are determined by integrating experts' experience in comfort and energy saving and objective data.

[0202] The levels are divided into high level, relatively high level, medium level, relatively low level and low level, and the specific division values ​​are:

[0203] High level: C ≥ 0.8;

[0204] Higher level: 0.6≤C<0.8;

[0205] Medium level: 0.4≤C<0.6;

[0206] Lower level: 0.2≤C<0.4;

[0207] Low level: C<0.2.

[0208] The calculated C value can be used to classify the levels according to the classification parameters, thereby evaluating the energy saving and comfort levels, and further adjusting the plan to make the level closer to the ideal level.

[0209] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for evaluating energy saving of a wind-heat storage system based on game theory, characterized in that: The method comprises the following steps: Establish an evaluation index system model, including three types of indicators: energy efficiency index, energy structure index and pollutant emission per unit of electricity. Among them, the energy structure index includes system comprehensive energy efficiency, energy storage capacity and thermal comfort; A GTCE-TOPSIS evaluation method model is established. According to the comprehensive energy efficiency evaluation index value obtained from the evaluation index system model, the subjective weight method AHP and the objective weight method EWM are used to determine the weight value of the evaluation index value, and the weight results are centralized; a weighted matrix is ​​constructed, and the positive ideal solution and negative ideal solution of each object to be evaluated in the weighted matrix, as well as the distance between the positive ideal solution and the distance between the negative ideal solution, are calculated, and then the closeness value of the object to be evaluated is calculated. Finally, the closeness value is graded to obtain the final grade.

2. According to claim 1, a game theory-based wind-heat storage system energy-saving evaluation method is characterized in that: The energy efficiency index model includes the following: S1: Thermal power plant power generation efficiency index model: Among them, P CON Represents the power generation of thermal power plants; ρ CON Indicates the calorific value parameter of the fuel in the thermal power plant; F CON It indicates the amount of coal consumed by the corresponding power generation of the thermal power plant; S2: Thermal power plant power generation efficiency index model: Among them, P CHP represents the power generation of thermal power plant, ρ CHP represents the calorific value parameter of the fuel in the thermal power plant, λ represents the thermal power ratio of the thermal power plant, F CHP Indicates the amount of coal consumed corresponding to the power generation of thermal power plants; S3: Thermal power plant heat production efficiency index model: Among them, Q CHP represents the heat output of the thermal power plant, ρ CHP Indicates the calorific value parameter of the fuel in the thermal power plant, F CHP It indicates the amount of coal consumed by the thermal power plant corresponding to the heat output; S4: Coal consumption per unit of electricity in thermal power plants: Among them, F CON Indicates the amount of coal consumed by the corresponding power generation of the thermal power plant, P CON It represents the power generation of thermal power plants; S5: Coal consumption per unit of electricity in thermal power plants: Where, λ represents the thermal power ratio of the thermal power plant, F CHP Indicates the amount of coal consumed by the thermal power plant for power generation, P CHP It represents the power generation of thermal power plant; S6: Coal consumption per unit heat index model for thermal power plants: Where, λ represents the thermal power ratio of the thermal power plant, F CHP Indicates the amount of coal consumed by the thermal power plant for power generation, Q CHP Represents the heat output of thermal power plants.

3. According to a game theory-based wind-heat storage system energy-saving evaluation method according to claim 1, it is characterized in that: The energy structure indicator model includes the following: T1: Comprehensive energy efficiency index model: Among them, P load , Q load Respectively represent the electrical and thermal loads of the system; H in , H out They represent the charging and discharging power of the heat storage tank, γ represents the thermal power ratio of the thermal power plant, ρ represents the total heat generated by the combustion of a unit of traditional energy, F represents the amount of coal consumed by the system, and P W Indicates wind power supply, P EB It indicates the amount of electricity used by the electric boiler. A indicates the sign of the abundance of wind power. When the minimum power output of the thermal power plant unit and the cogeneration power plant unit and the wind farm output are less than or equal to the power load, A is 0, otherwise A is 1. η indicates the electric-heat conversion efficiency of the electric boiler. T2: Energy storage capacity index model: D8=E S Among them, E S is the energy storage capacity; T3: Thermal comfort index model is: Among them, I TC The index reflects the ratio of the difference between the expected heat exchange and the actual heat exchange to the standard heat exchange, that is, the relative degree of deviation of the actual heat exchange from the expected heat exchange, T sub Indicates the psychological expected temperature, that is, the set temperature, T s Indicates standard temperature, T b Indicates the human body surface temperature, T id Indicates the actual room temperature.

4. The method for evaluating energy saving of a wind-heat storage system based on game theory according to claim 1 is characterized in that: The unit electricity pollutant emission index model includes the following: P1: System unit electricity CO2 emission model: Among them, η represents the CO2 emission coefficient corresponding to standard coal, P CON , P CHP Represent the power generation of thermal power plants and thermal power plants respectively, F CON Indicates the amount of coal consumed by the corresponding power generation of the thermal power plant, F CHP Indicates the amount of coal consumed corresponding to the power generation of thermal power plants; P2: System unit power NO X Emission model: Among them, τ represents the NO corresponding to standard coal X Emission factor, F CON Indicates the amount of coal consumed by the corresponding power generation of the thermal power plant, F CHP Indicates the amount of coal consumed by the thermal power plant for power generation, P CON , P CHP Represent the power generation of thermal power plants and thermal power plants respectively; P3: System unit electricity SO2 emission model: In the formula, ψ represents the SO2 emission coefficient corresponding to standard coal, F CON Indicates the amount of coal consumed by the corresponding power generation of the thermal power plant, F CHP Indicates the amount of coal consumed by the thermal power plant for power generation, P CON , P CHP Represent the power generation of thermal power plants and thermal power plants respectively.

5. The method for energy-saving evaluation of a wind-heat storage system based on game theory according to claim 1 is characterized in that: The GTCE-TOPSIS evaluation method also includes using a game theory-based comprehensive subjective weight method AHP to determine the weight value of each indicator based on the importance of each indicator by experts, and using an objective weight method EWM to determine the weight value of each indicator using the objective data of the indicator. The weight values ​​obtained by using different weighting methods are regarded as the two sides of the game, and are combined into a strategy set. The GTCE-TOPSIS evaluation method model is used to solve the weight value.

6. The method for evaluating energy saving of a wind-heat storage system based on game theory according to claim 5 is characterized in that: The steps of using game theory to combine subjective and objective weighting methods to determine the weights of energy-saving evaluation indicators of wind-heat storage system considering thermal comfort include the following: Determine the weights of the two parties in the game, I, as AHP and EWM, that is, I = {W S ,W O },W S is the weight matrix of AHP, W O is the weight value matrix of EWM; Determine the strategy space: The strategy space is the weight set W obtained by the two weighting methods. W=W S ×W O in, represents the weight vector obtained by AHP, n is the total number of indicators, represents the weight vector using EWM; W z Represents the weight vector formed by linear combination of the weights of n feature indicators: in, Determine the profit function: Determine all possible weight vectors W z After that, the optimal weight vector is obtained; The export is as follows: The linear equation corresponding to this formula is shown as follows: Calculate (a1, a2, ..., a n ), and normalize it as follows: Then the comprehensive weight of game theory is: in, is the transposed matrix of the policy space of the weight sets of the two weighting methods.

7. The method for evaluating energy saving of a wind-heat storage system based on game theory according to claim 5 is characterized in that: Calculate the positive ideal solution and negative ideal solution of each object to be evaluated in the weighted matrix: Among them, a + is a positive ideal solution, a - is a negative ideal solution; Calculate the distance D+ and the distance D- from the positive ideal solution to the object to be evaluated: The distance D+ and the distance D- from the positive ideal solution and the negative ideal solution are calculated according to the following formula: Calculate the closeness value C of the object to be evaluated: Grade classification: The object to be evaluated is graded according to its closeness value C.

8. The method for evaluating energy saving of a wind-heat storage system based on game theory according to claim 3 is characterized in that: In the thermal comfort index model, by comparing the user's psychological expectation temperature, that is, the set temperature T sub and the actual indoor temperature T id The size of the heat exchange rate, as well as the ratio of the difference between the expected heat exchange rate and the actual heat exchange rate to the standard heat exchange rate I TC , you can determine user needs; The judgment method is: When T sub -T id >0, I TC >0, that is, the set temperature is higher than the actual indoor temperature, indicating that the user expects the heating temperature to increase; When T sub -T id <0, I TC <0, that is, the set temperature is lower than the actual indoor temperature, indicating that the user expects the heating temperature to be lowered; When T sub -T id =0,I TC =0, that is, the set temperature is equal to the actual indoor temperature, indicating that the temperature set by the user is the same as the indoor temperature, the temperature meets the user's expectations, and the user's physiological comfort, psychological comfort, and thermal comfort feel optimal.

9. The method for evaluating energy saving of a wind-heat storage system based on game theory according to claim 7 is characterized in that: The calculation of each evaluation index value comprises the following steps: AHP indicator weight calculation: determine the judgment matrix, calculate the consistency ratio CR, judge the size of CR and 0.1, and when CR>0.1, consult experts to adjust the judgment matrix; When CR≤0.1, calculate the AHP weight; EWM indicator weight calculation: perform standardization operations to determine the standardization of positive and negative indicators, and then determine the numerical matrix X: Among them, x ij is the value of the jth indicator of the i-th sample, (i=1,2,…,m; j=1,2,…,n); Calculate the weight of the jth indicator of the i-th sample: Calculate the information entropy of the indicator: Calculate the information redundancy of the indicator: d j =1-e j Calculate the evaluation index weight vector: in, 10. The method for energy-saving assessment of a wind-heat storage system based on game theory according to claim 7, characterized in that: The levels are divided into high level, relatively high level, medium level, relatively low level and low level, and the specific division values ​​are: High level: C ≥ 0.8; Higher level: 0.6≤C<0.8; Medium level: 0.4≤C<0.6; Lower level: 0.2≤C<0.4; Low level: C<0.2.

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