Evaluation method and system for multi-energy complementary zero-carbon heat supply system

Abstract

The invention discloses an evaluation method and system for a multi-energy complementary zero-carbon heat supply system, and belongs to the technical field of renewable energy sources and building energy conservation. The method comprises the following steps: firstly, determining a multi-dimensional evaluation index set including a theoretical energy utilization rate, an actual energy comprehensive utilization rate, a system operation heat price, a system composite heat price, temperature rise response time and an operation carbon emission state; then acquiring system operation data and calculating each index value; establishing an evaluation model based on fuzzy comprehensive evaluation, and performing fuzzy synthesis operation to obtain an evaluation result vector by establishing an evaluation factor set, an evaluation grade set, a single-factor fuzzy evaluation matrix and weight vectors preset for different regions; and finally determining the comprehensive evaluation grade of the system. According to the evaluation method, the fuzziness problem of multi-index evaluation of the multi-energy complementary zero-carbon heat supply system is effectively solved, and a reliable basis can be provided for performance evaluation, optimization transformation and investment decision-making of the multi-energy complementary zero-carbon heat supply system.

Description

Technical Field

[0001] This invention relates to the field of renewable energy utilization and building energy conservation technology, and in particular to a comprehensive performance evaluation method and system for a multi-energy complementary zero-carbon heating system that combines solar energy, geothermal energy, and air energy. Background Technology

[0002] With the advancement of the "dual carbon" goal, multi-energy complementary heating systems composed of renewable energy sources such as solar, geothermal, and air source heat pumps are being used more and more widely in the building sector. These systems aim to achieve efficient, stable, and low-carbon energy supply through the synergistic cooperation of multiple energy sources.

[0003] However, multi-energy complementary systems are complex in structure, diverse in energy sources, and flexible in operation strategies, meaning their performance cannot be judged by a single indicator. Currently, the industry lacks a scientific, unified, and comprehensive evaluation method and system to comprehensively measure such systems. This leads to difficulties in system design, selection, operation optimization, and performance evaluation, hindering the full realization of the technological advantages of multi-energy complementary systems.

[0004] Therefore, there is an urgent need to establish a comprehensive evaluation system that can cover the entire life cycle of the system and take into account both technical performance and economic and environmental benefits, so as to provide a reliable basis for the design optimization, performance benchmarking and investment decisions of multi-energy complementary systems. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a scientific, comprehensive, and operable evaluation method and system for multi-energy complementary zero-carbon heating systems. This system achieves an objective and accurate assessment of the system's overall performance by constructing a set of multi-level, multi-dimensional quantitative indicators and combining them with fuzzy comprehensive evaluation theory.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: This invention provides an evaluation method for a multi-energy complementary zero-carbon heating system, comprising the following steps: S1. Determine the system performance evaluation indicators, which include theoretical energy utilization rate η1, actual comprehensive energy utilization rate η2, system operating heat price Uy, system composite heat price Ur, temperature rise response time T, and operating carbon emission status; S2. Obtain the operating data and design parameters of the system to be evaluated, and calculate the specific values ​​of each indicator in the evaluation index; S3. Establish an evaluation model based on fuzzy comprehensive evaluation, including establishing the evaluation factor set U, the evaluation level set V, the single-factor fuzzy evaluation matrix R, and the weight vector A; S4. Perform a fuzzy synthesis operation on the weight vector A and the single-factor fuzzy evaluation matrix R to obtain the fuzzy evaluation result vector B. S5. Process the fuzzy evaluation result vector B to determine the final comprehensive evaluation level of the system to be evaluated.

[0007] Furthermore, the theoretical energy utilization rate Where Qy is the heat consumption on the user side, in MJ; Ql is the sum of the theoretical maximum heat supply of all energy sources in the system under their rated power. Qli represents the theoretical heat output of the i-th energy configuration in the system under its rated power, in MJ; The actual energy comprehensive utilization rate Where Qy represents the heat consumption on the user side, in MJ; Qr represents the actual total heat supply from all heat sources in the system, in MJ; Qri represents the actual heat output of the i-th heat source in the system, in MJ; The system operating heat price The unit is MJ; where Dri represents the electricity consumed in the operation of the i-th energy source, kWh; Yj represents the electricity price per unit of electricity in the j-th operating segment within a unit period, yuan / kWh; The system has a composite heat value The unit is MJ; where Ci is the construction investment of the i-th energy equipment in the system, in yuan; and Ti is the usage cycle of the i-th energy equipment, in hours. The temperature rise response time , h; where, This indicates the specific heat capacity of the air in the room requiring heating, in kJ / kg℃. This indicates the air density in a heated room, expressed in kg / m³. The volume of the room requiring heating is in m3; The design temperature of the heated room is ℃; The indoor temperature of the heated room at a certain moment, in °C; Specific heat capacity of the heating medium in the system, kJ / kg℃; The density of the heating medium in the system, in kg / m³; The circulating flow rate of the medium within the system is expressed in m³ / h. The system's heating medium is designed with a circulating temperature difference of ℃; The carbon emission status of the system is determined by comparing the total electricity consumed (Dr) during the system's operating cycle with the solar photovoltaic power generation (Ar) within the system. When Dr = Ar, the system is a zero-carbon system; when Dr < Ar, the system is a negative-carbon system; and when Dr > Ar, the system is a carbon-emitting system.

[0008] Furthermore, the evaluation factor set U={U1,U2,U3,U4,U5,U6}, where U1 is the theoretical energy utilization rate η1, used to evaluate the rationality of system configuration; U2 is the actual comprehensive energy utilization rate η2, used to evaluate the energy efficiency of system operation; U3 is the system operating heat price Uy, used to evaluate short-term operating economy; U4 is the system composite heat price Ur, used to evaluate the economic efficiency throughout the entire life cycle; U5 is the temperature rise response time T, used to evaluate the system response and control performance; and U6 is the operating carbon emission status, used to evaluate the degree of achievement of the zero-carbon core target.

[0009] Furthermore, the evaluation level set V = {V1, V2, V3, V4} = {Excellent, Good, Average, Poor}.

[0010] Furthermore, the single-factor fuzzy evaluation matrix R is obtained by inputting the calculated value of each evaluation factor Ui into a preset membership function. The membership function defines the degree of membership of each index value to each level in the evaluation level Vj, R=[rij] (6×4), where rij represents the i-th factor to the j-th evaluation level.

[0011] Furthermore, the weight vector A is determined based on the climate characteristics, resource conditions, and core evaluation objectives of the region where the system to be evaluated is located. The elements in the weight vector A correspond to the weights of each factor in the evaluation factor set U, A=(a1,a2,a3,a4,a5,a6), which represents the importance of each indicator in the final evaluation and satisfies Σai=1.

[0012] Furthermore, the fuzzy synthesis operation selects a weighted average operator M as the fuzzy synthesis operator, B=AR=(b1,b2,b3,b4,b5), and each element bj in vector B represents the comprehensive membership degree of the tested system to the evaluation Vj.

[0013] Furthermore, the final comprehensive evaluation level is determined using the maximum membership principle or the weighted average method.

[0014] The present invention also provides an evaluation system for a multi-energy complementary zero-carbon heating system, using the evaluation method described above.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This invention constructs a multi-dimensional evaluation factor set, covering system configuration rationality, operational energy efficiency, short-term operational economy, full life-cycle economy, response and control performance, and the achievement of zero-carbon core objectives, comprehensively reflecting the overall performance of multi-energy complementary systems. By introducing fuzzy comprehensive evaluation theory, it effectively handles the fuzziness and uncertainty among evaluation indicators, combining quantitative calculation with qualitative evaluation to make the evaluation results more consistent with objective reality. By pre-setting differentiated indicator weights for different regions and application scenarios, the evaluation system can flexibly adapt to diverse needs, making the evaluation conclusions more targeted and instructive. It not only provides a final rating for the system but also clarifies the system's strengths and weaknesses by analyzing the scores of each indicator, providing a clear direction for system optimization and transformation. All parameters required for the evaluation can be obtained through on-site testing, operational records, and design data; the method is clear, the process is well-defined, and it is easy to promote and apply in practical engineering projects. Detailed Implementation

[0016] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0017] The multi-energy complementary zero-carbon heating system described in this invention is a comprehensive system that uses solar energy, geothermal energy, and air energy as heat sources, with the rooms within a building requiring heating as the user side. Geothermal energy is at least one of medium-deep rock geothermal and shallow soil geothermal, while solar energy is divided into solar thermal and photovoltaic components. During operation, the multi-energy complementary system utilizes solar energy, geothermal energy, and air energy in a complementary manner to heat the building's rooms. The main energy consumption is the electricity used to drive the heat pump and circulation pump equipment, which primarily comes from the solar photovoltaic portion of the system. Therefore, the entire heating system has zero energy input and zero external carbon emissions, achieving zero-carbon heating.

[0018] This invention provides an evaluation method for a multi-energy complementary zero-carbon heating system, comprising the following steps: S1. Determine the system performance evaluation indicators, which include theoretical energy utilization rate η1, actual comprehensive energy utilization rate η2, system operating heat price Uy, system composite heat price Ur, temperature rise response time T, and operating carbon emission status; S2. Obtain the operating data and design parameters of the system to be evaluated, and calculate the specific values ​​of each indicator in the evaluation index; S3. Establish an evaluation model based on fuzzy comprehensive evaluation, including establishing the evaluation factor set U, the evaluation level set V, the single-factor fuzzy evaluation matrix R, and the weight vector A; S4. Perform a fuzzy synthesis operation on the weight vector A and the single-factor fuzzy evaluation matrix R to obtain the fuzzy evaluation result vector B. S5. Process the fuzzy evaluation result vector B to determine the final comprehensive evaluation level of the system to be evaluated.

[0019] Specifically, to facilitate the evaluation of the rationality of the heat source equipment configuration in a multi-energy complementary system and the energy efficiency levels of different types of heat source equipment, the theoretical comprehensive energy utilization efficiency is adopted. The theoretical energy utilization rate... Where Qy is the heat consumption on the user side, measured in MJ, and can be directly measured by a heat meter installed on the user side; Ql is the sum of the theoretical maximum heat supply of all energy sources in the system at their rated power. Qli represents the theoretical heat output of the i-th energy configuration in the system under the rated power, in MJ. Qli can be calculated by the rated power of the system configuration of different types of renewable energy based on the average operating time of the multi-energy complementary system. The theoretical energy utilization rate is an evaluation index of the rationality of the system configuration. The larger the value of this index, the more reasonable the configuration.

[0020] Specifically, to facilitate the evaluation of energy utilization during the operation of a multi-energy complementary system, including energy conversion, transmission, distribution, and utilization, the actual energy utilization rate is used for evaluation. The actual comprehensive energy utilization rate... Where Qy represents the heat consumption on the user side, in MJ, which is directly measured by a heat meter installed on the user side; Qr represents the actual total heat supply from all heat sources in the system, in MJ. Qri represents the actual heat supply of the i-th heat source in the system, in MJ, and is directly measured by heat meters installed at the heat outlets of different types of heat sources. The actual comprehensive energy utilization rate during operation represents the energy conversion and utilization efficiency during actual system operation; a higher value indicates higher energy utilization efficiency.

[0021] Specifically, to facilitate the evaluation of the operational economics of the multi-energy complementary system during operation, a system operating heat price is adopted. The system operating heat price... The unit is yuan / MJ; where Dri represents the electricity consumed in the operation of the i-th energy source, in kWh, obtained by testing the electricity consumption of different types of renewable energy in actual operation; Yj represents the electricity price per unit time in the j-th operating segment within a unit cycle, in yuan / kWh, which can be obtained by querying the electricity price for the corresponding time based on the operating statistics of the multi-energy complementary system. The system operating heat price is used to evaluate the energy consumption, economic unit price, and systemic performance of the multi-energy complementary system with different heat sources in actual operation. The lower this indicator, the better the system performance.

[0022] Specifically, to facilitate the evaluation of the relationship and economic efficiency between the construction investment, operating costs, and heat supply of a multi-energy complementary system, a composite heat price index is introduced. This index calculation first requires combining the construction investment of various energy sources with their life cycles, distributing the construction investment evenly across each operating period within the life cycle. The ratio of the sum of the distributed construction investment and operating costs to the heat supply on the user side is used as the calculated composite heat price. This allows for the evaluation of the overall economic efficiency of the multi-energy complementary system's construction investment and operation. The aforementioned composite heat price... The unit is yuan / MJ; where Ci is the construction investment of the i-th energy equipment in the system, in yuan; and Ti is the service life of the i-th energy equipment, in hours. The system composite heat price is used as a comprehensive indicator to evaluate the system's construction investment and operating price, characterizing the service life of the system equipment and its economic efficiency during operation. The lower this indicator, the better the economic performance of the system throughout its entire life cycle.

[0023] Specifically, to facilitate the evaluation of the degree to which a multi-energy complementary heating system meets heating demand, a temperature rise response time index is introduced. The testing and calculation of this index first requires testing the hourly indoor temperature and the supply and return water temperatures of the multi-energy complementary system. Other parameters are the thermophysical properties of the heating medium and air, all of which can be obtained from relevant literature. The temperature rise response time... The unit is h; where, This indicates the specific heat capacity of the air in the room requiring heating, expressed in kJ / kg℃. This indicates the air density in a heated room, expressed in kg / m³. The volume of the room requiring heating, in meters. 3 ; The design temperature of the heated room, in °C, is set according to the room's function or usage requirements. The indoor temperature of a heated room at a certain moment, expressed in °C, is obtained by measuring with a temperature testing instrument. Specific heat capacity of the heating medium within the system, expressed in kJ / kg℃; The density of the heating medium within the system, expressed in kg / m³. 3 ; The circulating flow rate of the medium within the system, expressed in m³. 3 / h, obtained through testing with instruments such as ultrasonic flow meters; The design circulating temperature difference for the system's heating medium is expressed in °C. The temperature rise response time is used to evaluate the rationality of the control strategy and methods for the multi-energy complementary system; a smaller value indicates more rational system operation and control, and greater energy efficiency.

[0024] Specifically, since the only energy consumed during the operation of the multi-energy complementary system is electricity, the total electricity consumed during the operating cycle is Dr (kWh), and the power generated by the solar photovoltaic system within the system during this period is Ar (kWh). Both can be tested by the electricity meter installed on the system during the operation phase. The carbon emission status during operation is determined by comparing the total electricity consumed Dr during the system's operating cycle with the solar photovoltaic power generated Ar within the system; when Dr = Ar, the system is a zero-carbon system; when Dr < Ar, the system is a negative-carbon system; when Dr > Ar, the system is a carbon-emitting system.

[0025] Specifically, the evaluation factor set U={U1,U2,U3,U4,U5,U6}, where U1 is the theoretical energy utilization rate η1, used to evaluate the rationality of system configuration; U2 is the actual comprehensive energy utilization rate η2, used to evaluate the energy efficiency of system operation; U3 is the system operating heat price Uy, used to evaluate short-term operating economics; U4 is the system composite heat price Ur, used to evaluate the economics throughout the entire life cycle; U5 is the temperature rise response time T, used to evaluate the system response and control performance; and U6 is the operating carbon emission status, used to evaluate the degree of achievement of the zero-carbon core target.

[0026] Specifically, the evaluation level set V = {V1, V2, V3, V4} = {Excellent, Good, Average, Poor}. This evaluation level set is used to describe the final overall assessment of the system.

[0027] Specifically, the single-factor fuzzy evaluation matrix R is obtained by inputting the calculated value of each evaluation factor Ui into a preset membership function. The membership function defines the degree of membership of each index value to each level in the evaluation level Vj. The membership function maps precise index values ​​to the [0,1] interval, and the evaluation equivalence of each index is as follows: U1 (Theoretical Energy Utilization Rate η1): Based on industry standards and expert experience, η1>0.85 is considered "excellent", 0.75<η1≤0.85 is considered "good", 0.65<η1≤0.75 is considered "average", and η1≤0.65 is considered "poor". U2 (Actual Energy Utilization Rate η2): Based on the analysis of monitoring data on system operating efficiency, η2>0.80 is considered "excellent", 0.70<η2≤0.80 is considered "good", 0.60<η2≤0.70 is considered "average", and η2≤0.60 is considered "poor". U3: System operating heat price (Uy): Due to the different current charging standards for heat prices in different regions, after comprehensive consideration of heat prices in different regions of my country, Uy≤45 yuan / GJ is excellent, 45<Uy≤55 yuan / GJ is good, 55<Uy≤65 yuan / GJ is average, and Uy>65 yuan / GJ is average. U4: System composite heat price (Ur). Based on a comprehensive evaluation of the construction investment and operating costs of solar energy systems, medium-deep geothermal systems, etc., combined with expert opinions and industry standards, Ur≤55 yuan / GJ is excellent, 55<Uy≤60 yuan / GJ is good, 60<Uy≤70 yuan / GJ is average, and Uy>70 yuan / GJ is average. U5: Temperature rise response time (T). Based on the analysis results of relevant operating data and expert opinions, T≤1 hour is excellent, 1<T≤1.5 hours is good, 1.5<Uy≤2 hours is average, and Uy>2 hours is average. U6: Operating carbon emissions (Dr). Currently, the carbon emissions of renewable energy heating systems are mainly calculated based on the electricity consumed and its corresponding carbon emission factor. Considering carbon emissions and the proportion of green electricity consumed, Dr < 0 and green electricity ratio ≥ 30% is considered excellent; Dr < 0 and 20% ≤ green electricity ratio < 30% is considered good; Dr < 0 and 10% ≤ green electricity ratio < 20% is considered average; Dr < 0 and green electricity ratio ≤ 10% and Dr ≥ 0 are considered average.

[0028] Based on the evaluation function set for each indicator above, for a tested system, we can finally obtain the evaluation level corresponding to each indicator, forming a fuzzy relation matrix R, then R = [rij] (6×4), where rij represents the evaluation level of the i-th factor to the j-th factor.

[0029] Specifically, the weight vector A is determined based on the climate characteristics, resource conditions, and core evaluation objectives (economic priority, low-carbon priority, and stability priority) of the region where the system to be evaluated is located. The elements in the weight vector A correspond to the weights of each factor in the evaluation factor set U, A=(a1,a2,a3,a4,a5,a6), which represents the importance of each indicator in the final evaluation and satisfies Σai=1.

[0030] In one specific implementation scenario of this invention, for the arid Northwest region (extremely rich in solar energy resources, with cold winters), the weight ratio is: A (Northwest) = (0.20, 0.20, 0.10, 0.15, 0.15, 0.20). The core consideration is to fully utilize the free and abundant solar energy, ensuring heating reliability under extreme weather conditions, and the initial investment can be appropriately relaxed. Weight allocation: U6 has the highest weight, with the core goal of zero carbon; and it has the conditions to achieve negative carbon; U1 and U2 have high weights to ensure that the system design can maximize the use of solar energy; U5 has a medium weight, which needs to ensure a certain level of heating comfort and prevent excessively low temperatures at night or on cloudy days; U3 and U4 can have relatively lower weights, focusing more on environmental protection and performance, with a slightly higher tolerance for cost.

[0031] In one specific implementation scenario of this invention, for the central region (hot summer and cold winter) (with peak energy demand and sensitive electricity prices), the weighting ratio is: A (Central Region) = (0.10, 0.20, 0.25, 0.25, 0.15, 0.05). The core consideration is the system's overall energy efficiency and economic benefits throughout the year, taking into account both summer cooling and winter heating. Weighting allocation: U4 and U3 have the highest weights, as users are highly sensitive to operating costs, and the total life cycle cost is key; U2 has a high weight, directly related to electricity expenses; U5 has a medium weight, with certain requirements for comfort; U1 and U6 have relatively low weights, prioritizing economic efficiency while meeting basic environmental and performance requirements.

[0032] In one specific implementation scenario of this invention, for high-latitude frigid regions (Northeast China, where heating demand is high and continuous, and stability is paramount), the weighting ratio is: A (Northeast) = (0.15, 0.20, 0.15, 0.20, 0.20, 0.10). The core considerations are the absolute reliability and stability of heating, and the low-temperature performance of geothermal and air energy sources. Weighting allocation: U5 and U2 have the highest weights, requiring rapid response to heating demands and efficient operation even at extremely low temperatures; U4 has a high weight, as its initial investment may be large, necessitating an examination of its long-term economic viability; U1 has a medium weight, with configuration prioritizing performance under extreme conditions; U6 has a relatively low weight, pursuing low carbon emissions while ensuring heating safety.

[0033] Specifically, the fuzzy synthesis operation selects a weighted average operator M as the fuzzy synthesis operator, B=AR=(b1,b2,b3,b4,b5), and each element bj in vector B represents the comprehensive membership degree of the tested system to the evaluation Vj.

[0034] Specifically, the final comprehensive evaluation level is determined using the maximum membership principle or the weighted average method. After obtaining the fuzzy evaluation result vector B, the maximum membership principle is usually used to determine the final level. For example, if B = (0.30, 0.45, 0.20, 0.05, 0.00), then the maximum value of 0.45 corresponds to the comment "Good," and the overall performance of the system can be judged as "Good." For greater precision, the comment set V can also be assigned values ​​(e.g., Excellent = 5, Good = 4, Average = 3, Poor = 2, Poor = 1), and the weighted average of B can be calculated to obtain a specific comprehensive score, facilitating comparison between different systems.

[0035] Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

Claims

1. An evaluation method for a multi-energy complementary zero-carbon heating system, characterized in that, Includes the following steps: S1. Determine the system performance evaluation indicators, which include theoretical energy utilization rate η1, actual comprehensive energy utilization rate η2, system operating heat price Uy, system composite heat price Ur, temperature rise response time T, and operating carbon emission status; S2. Obtain the operating data and design parameters of the system to be evaluated, and calculate the specific values ​​of each indicator in the evaluation index; S3. Establish an evaluation model based on fuzzy comprehensive evaluation, including establishing the evaluation factor set U, the evaluation level set V, the single-factor fuzzy evaluation matrix R, and the weight vector A; S4. Perform a fuzzy synthesis operation on the weight vector A and the single-factor fuzzy evaluation matrix R to obtain the fuzzy evaluation result vector B. S5. Process the fuzzy evaluation result vector B to determine the final comprehensive evaluation level of the system to be evaluated.

2. The evaluation method for a multi-energy complementary zero-carbon heating system as described in claim 1, characterized in that: The theoretical energy utilization rate Where Qy is the heat consumption on the user side, in MJ; Ql is the sum of the theoretical maximum heat supply of all energy sources in the system at their rated power. Qli represents the theoretical heat output of the i-th energy configuration in the system under its rated power, in MJ; The actual energy comprehensive utilization rate Where Qy represents the heat consumption on the user side, in MJ; Qr represents the actual total heat supply from all heat sources in the system, in MJ; Qri represents the actual heat supply of the i-th heat source in the system, in MJ; The system operating heat price The unit is RMB / MJ; where Dri represents the electricity consumed in the operation of the i-th energy source, kWh; Yj represents the electricity price per unit of electricity in the j-th operating segment within a unit period, RMB / kWh; The system has a composite heat value The unit is MJ; where Ci is the construction investment of the i-th energy equipment in the system, in yuan; and Ti is the usage cycle of the i-th energy equipment, in hours. The temperature rise response time , h; where, This indicates the specific heat capacity of the air in the room requiring heating, in kJ / kg℃. This indicates the air density of a heated room, expressed in kg / m³. 3 , For the volume of the room requiring heating, m 3 ; The design temperature of the heated room is ℃; The indoor temperature of the heated room at a certain moment, in °C; Specific heat capacity of the heating medium in the system, kJ / kg℃; The density of the heating medium within the system, kg / m³ 3 ; m is the circulating flow rate of the medium within the system. 3 / h; The system's heating medium is designed with a circulating temperature difference of ℃; The carbon emission status of the system is determined by comparing the total electricity consumed (Dr) during the system's operating cycle with the solar photovoltaic power generation (Ar) within the system. When Dr = Ar, the system is a zero-carbon system; when Dr < Ar, the system is a negative-carbon system; and when Dr > Ar, the system is a carbon-emitting system.

3. The evaluation method for a multi-energy complementary zero-carbon heating system as described in claim 1, characterized in that: The evaluation factor set U={U1,U2,U3,U4,U5,U6}, where U1 is the theoretical energy utilization rate η1, used to evaluate the rationality of system configuration; U2 is the actual comprehensive energy utilization rate η2, used to evaluate the energy efficiency of system operation; U3 is the system operating heat price Uy, used to evaluate short-term operating economy; U4 is the system composite heat price Ur, used to evaluate the economic efficiency throughout the entire life cycle; U5 is the temperature rise response time T, used to evaluate the system response and control performance; and U6 is the operating carbon emission status, used to evaluate the degree of achievement of the zero-carbon core target.

4. The evaluation method for a multi-energy complementary zero-carbon heating system as described in claim 1, characterized in that: The evaluation level set V = {V1, V2, V3, V4} = {Excellent, Good, Average, Poor}.

5. The evaluation method for a multi-energy complementary zero-carbon heating system as described in claim 1, characterized in that: The single-factor fuzzy evaluation matrix R is obtained by inputting the calculated value of each evaluation factor Ui into a preset membership function. The membership function defines the degree of membership of each index value to each level in the evaluation level Vj, R=[rij] (6×4), where rij represents the i-th factor to the j-th evaluation level.

6. The evaluation method for a multi-energy complementary zero-carbon heating system as described in claim 1, characterized in that: The weight vector A is determined based on the climate characteristics, resource conditions and core evaluation objectives of the region where the system to be evaluated is located. The elements in the weight vector A correspond to the weights of each factor in the evaluation factor set U, A=(a1,a2,a3,a4,a5,a6), which represents the importance of each indicator in the final evaluation and satisfies Σai=1.

7. The evaluation method for a multi-energy complementary zero-carbon heating system as described in claim 1, characterized in that: The fuzzy synthesis operation selects a weighted average operator M as the fuzzy synthesis operator, B=AR=(b1,b2,b3,b4,b5), and each element bj in vector B represents the comprehensive membership degree of the tested system to the evaluation Vj.

8. The evaluation method for a multi-energy complementary zero-carbon heating system as described in claim 1, characterized in that: The final comprehensive evaluation level is determined using the maximum membership principle or the weighted average method.

9. An evaluation system for a multi-energy complementary zero-carbon heating system, characterized in that, The evaluation method described in any one of claims 1 to 8 shall be adopted.

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