A method and system for rapid evaluation of economic efficiency and adequacy of an electric heat integrated energy system

Abstract

The application discloses a kind of electric heat comprehensive energy system economy and adequacy fast evaluation method and system, based on the time series load curve of the evaluated electric heat comprehensive energy system in a period of time, form electric heat load joint distribution function;According to the working principle of coupling equipment in electric heat comprehensive energy system and electric heat output feasible region, the capacity and forced outage rate information of independent energy supply element are used to convolute correction to electric heat load joint distribution function, consider the energy coupling mechanism of coupling equipment, to solve the difficulty that traditional electric heat coupling equipment modeling is difficult to analyze internal energy conversion mechanism.Economy and adequacy evaluation of electric heat coupling equipment provide theoretical basis.The method of the application carries out fast evaluation to the planning and design scheme of electric heat comprehensive energy system, overcome the shortcomings that existing comprehensive energy system time series simulation evaluation method is difficult to meet the efficient computing demand, can not carry out theoretical analysis to the transformation of energy flow.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of electric-thermal integrated energy system evaluation, and particularly relates to a method and system for rapidly evaluating the economy and adequacy of an electric-thermal integrated energy system. BACKGROUND

[0002] At present, the energy supply structure is unreasonable, and the overall energy utilization efficiency is low, so it is urgent to promote energy production and build a clean, low-carbon, safe and efficient energy system. The integrated energy system refers to an integrated energy production and sales system formed by organically coordinating and optimizing various energy production, distribution, conversion, consumption and storage links in the planning, design, construction and operation processes. The integrated energy system can break down the barriers between different forms of energy systems, utilize the interconnection between multiple energies, improve energy utilization efficiency, reduce social energy costs, and optimize energy structure.

[0003] In the integrated energy utilization system, the electric-thermal coupling system has significant advantages in improving energy utilization efficiency and reducing carbon emissions, and is very consistent with the current power structure dominated by thermal power.

[0004] The stochastic production simulation of the electric-thermal integrated energy system is a medium and long-term evaluation method, which refers to the simulation of energy production and conversion processes and the evaluation of economy and energy adequacy. The economy and adequacy evaluation of the electric-thermal integrated energy system can be directly used for source-side planning, electric-thermal conversion equipment planning, production scheme formulation, etc. of the electric-thermal integrated energy system, and is a basic theoretical tool supporting the planning and operation of the electric-thermal integrated energy system.

[0005] The existing medium and long-term economy evaluation method of the integrated energy system is mainly based on time sequence simulation. Dr. Li Yalou of China Electric Power Research Institute and others realized the simulation analysis of the integrated energy system based on the power system analysis comprehensive program (PSASP) using the Monte Carlo time sequence simulation method. However, the simulation efficiency of the time sequence simulation method is low, and it cannot adapt to the application scenarios with high efficiency requirements.

[0006] The integrated energy system in China is developing rapidly, and the construction of the electric-thermal integrated energy system will become a key promotion project in the future. The integrated energy supply and consumption system is gradually formed, and it is difficult to adapt to the current demand for rapid and efficient evaluation of multiple planning schemes in the planning stage by using the Monte Carlo time sequence simulation method to evaluate the economy and adequacy of the electric-thermal integrated energy system. Therefore, it is particularly important and urgent to study a stochastic production simulation method for the electric-thermal integrated energy system. SUMMARY

[0007] The present application aims to provide a method for quickly evaluating the economy and adequacy of an electric-thermal integrated energy system, so as to overcome the inherent problems of low efficiency and lack of accuracy in the evaluation of various schemes in the planning stage.

[0008] A method for quickly evaluating the economy and adequacy of an electric-thermal integrated energy system, comprising the following steps:

[0009] S1, based on the time-series load curve of the evaluated electric-thermal integrated energy system within a period of time, forming an electric-thermal load joint distribution function;

[0010] S2, according to the capacity and forced outage rate information of the independent energy supply elements of the evaluated electric-thermal integrated energy system, convoluting and correcting the electric-thermal load joint distribution function;

[0011] S3, based on the multi-energy critical transformation function, sequentially calculating the economic working capacity of the energy transformation elements according to the economy of the energy transformation elements, and further convoluting and correcting the corrected electric-thermal load joint distribution function in step S2 according to the economic working capacity and the forced outage rate;

[0012] S4, according to the corrected electric-thermal load joint distribution function, calculating the economy index and adequacy index of the evaluated electric-thermal integrated energy system.

[0013] Preferably, for the evaluation of the planning scheme, a time-series load curve is generated by a prediction method, and the electric-thermal load joint distribution function is formed according to the time-series load curve.

[0014] Preferably, according to the corrected electric-thermal load joint distribution function, the utilization rate index of the independent energy supply elements and the energy transformation elements in the system is calculated.

[0015] Preferably, the formation process of the electric-thermal load joint probability distribution model is represented by formula (1):

[0016]

[0017] In the formula, N represents the total number of measurement time points in the period, and respectively represent the electric load and the thermal load at time point n.

[0018] Preferably, the independent energy supply elements include independent power sources, independent heat sources, and micro gas turbine combined heat and power units.

[0019] Preferably, the convolution correction process of the independent power supply element i on the load probability distribution model is represented by the following formula:

[0020]

[0021]

[0022] where * is a mathematical operator, is a convolution operation of the sequence, and is equivalent to the summation of the corresponding values under the constraint is the load probability distribution model of the i-th independent energy supply element before convolution correction, is the load probability distribution model of the i-th independent energy supply element after convolution correction, Δx P is the selected discrete step size, n P is the discrete load level, is the output capacity of the i-th independent energy supply element, and is a constant.

[0023] Preferably, the energy conversion elements in the electro-thermal integrated energy system include electric-to-thermal elements and thermal-to-electric elements, and the working characteristics of the two energy conversion elements are represented by the following formula:

[0024]

[0025]

[0026] where P and H represent the electric power (MW) and thermal power (MW) of the energy conversion element, respectively, the superscripts P2H and H2P represent the electric-to-thermal element and the thermal-to-electric element, respectively, and c represents the conversion efficiency of the energy conversion element.

[0027] Preferably, the adequacy index of the system is calculated as:

[0028] The adequacy index of each energy subsystem of the electro-thermal integrated energy system can be described by LOLP and EENS, and the calculation method is as follows:

[0029]

[0030]

[0031]

[0032]

[0033] EENS CHPS = EENS P + EENS H (24)

[0034] where LOLP P , LOLP H represent the loss of load probability of the power subsystem and the heat subsystem, respectively, EENS P , EENS H , and EENS CHPS ​respectively represent the expected value of energy shortage of the power subsystem, the heating subsystem and the integrated electric-heating energy system.

[0035] Preferably, the economic indicators include system economic indicators and energy conversion element economic indicators, and the system economic indicators can be represented by energy supply cost:

[0036]

[0037]

[0038]

[0039]

[0040] wherein, respectively represent the energy supply cost of the power subsystem, the heating subsystem and the integrated electric-heating energy system in the research time, respectively represent the energy supply cost of the i-th independent power supply element and the energy supply cost of the j-th independent heating supply element; represents the energy supply cost saved by the k-th energy conversion element for the integrated electric-heating energy system in the research time, i.e., the benefit of the k-th energy conversion element in the research time, and respectively represent the energy supply cost of the system before and after the k-th energy conversion element is put into operation.

[0041] The application discloses an integrated electric-heating energy system economic and adequacy rapid evaluation system, which comprises a pretreatment module and an evaluation module.

[0042] The pretreatment module forms an electric-heating load joint distribution function according to the time sequence load curve of the integrated electric-heating energy system in a period of time, and performs convolution correction on the electric-heating load joint distribution function according to the capacity and forced outage rate information of the independent energy supply elements of the integrated electric-heating energy system; based on a multi-energy critical conversion function, the economic working capacity of the energy conversion element is calculated in turn according to the economic sequence of the energy conversion element, and the electric-heating load joint distribution function corrected in step S2 is further convoluted and corrected according to the economic working capacity and the forced outage rate.

[0043] The evaluation module calculates the economic indicators and the adequacy indicators of the integrated electric-heating energy system according to the corrected electric-heating load joint distribution function.

[0044] Compared with the prior art, the application has the following beneficial technical effects:

[0045] The application is a kind of method for rapid evaluation of economic efficiency and adequacy of electric-thermal integrated energy system, which is based on the time series load curve of the evaluated electric-thermal integrated energy system within a period of time to form an electric-thermal load joint distribution function; according to the working principle of the coupling equipment in the electric-thermal integrated energy system and the electric-thermal output feasible region, the capacity and forced outage rate information of the independent energy supply element are used to convolve and correct the electric-thermal load joint distribution function, and the energy coupling mechanism of the coupling equipment is considered, thereby solving the difficulty of traditional electric-thermal coupling equipment modeling in analyzing the internal energy conversion mechanism. It provides a theoretical basis for the economic efficiency and adequacy evaluation of electric-thermal coupling equipment.

[0046] The method of the application rapidly evaluates the planning and design scheme of the electric-thermal integrated energy system, overcomes the shortcomings of the existing time series simulation evaluation method of integrated energy system that cannot meet the efficient computing demand and cannot theoretically analyze the energy flow conversion, realizes more efficient and reasonable economic efficiency and adequacy evaluation, thereby rapidly evaluating multiple electric-thermal integrated energy system construction schemes proposed in the planning and design stage, providing a more effective basis for the planning and construction of integrated energy system and shortening the time cycle of the planning and design stage. BRIEF DESCRIPTION OF DRAWINGS

[0047] Figure 1 The method flowchart in the embodiment of the application is shown in the figure;

[0048] Figure 2 The load probability generation diagram in the embodiment of the application is shown in the figure, wherein (a) is a time series electric-thermal load curve, and (b) is an electric-thermal load probability model;

[0049] Figure 3 The correction of the independent power supply element to the electric load probability model in the embodiment of the application is shown in the figure;

[0050] Figure 4 The ideal operating point of the electric-thermal integrated energy system under the working characteristics of the i-th energy conversion element and the operating point under the actual capacity constraint in the embodiment of the application are shown in the figure;

[0051] Figure 5 The convolution correction of the energy conversion element to the load probability distribution model in the embodiment of the application is shown in the figure;

[0052] Figure 6 The convolution correction process of the energy conversion element to the electric-thermal load probability distribution function in the embodiment of the application is shown in the figure. DETAILED DESCRIPTION

[0053] In the following, the technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application, so that those skilled in the art can better understand the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work should fall within the scope of the present application.

[0054] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to the process, method, product or device.

[0055] As shown in Figure 1 A method for rapidly evaluating the economy and adequacy of an electric-thermal integrated energy system, comprising the following steps:

[0056] S1, based on the time-series load curve of the evaluated electric-thermal integrated energy system within a period of time (medium and long term), forming an electric-thermal load joint distribution function;

[0057] For the evaluation of the planning scheme, the time-series load curve is generated by the prediction method, and the electric-thermal load joint distribution function is formed according to the time-series load curve;

[0058] S2, according to the capacity and forced outage rate information of the independent energy supply elements of the evaluated electric-thermal integrated energy system, the electric-thermal load joint distribution function is convoluted and corrected;

[0059] S3, based on the multi-energy critical transformation function, according to the economic order of the energy transformation elements, the economic working capacity of the energy transformation elements is calculated in turn, and according to the economic working capacity and the forced outage rate, the electric-thermal load joint distribution function corrected in step S2 is further convoluted and corrected;

[0060] S4, according to the corrected electric-thermal load joint distribution function, the economic index, the adequacy index of the evaluated electric-thermal integrated energy system, and the utilization rate index of the independent energy supply elements and the energy transformation elements in the system are calculated.

[0061] Probability generation of medium and long term load data:

[0062] The present application carries out abnormal data elimination and repair in the time series data of electric load and thermal load (generally hourly load data) in the studied time period, selects discrete step Δx P , Δx H , obtains the probability distribution function g<x P , x H > of the electric load and thermal load in the time period, that is, the probability distribution model of the load in the electric-thermal integrated energy system. The time series electric load, thermal load and the corresponding electric load, thermal load joint distribution model are shown in (a) and (b) of Figure 2 . The formation process of the electric-thermal load joint probability distribution model can be represented by formula (1).

[0063]

[0064] In the formula, N represents the total number of measurement time points in the time period, and represent the electric load and thermal load at time point n, respectively.

[0065] Convolution correction of independent energy supply elements:

[0066] The independent energy supply elements include independent power supply, independent heat source and micro gas turbine combined heat and power unit. The independent power supply and independent heat source can directly adopt the modeling method of generator in the traditional production simulation method, and only the economy, upper and lower limits of output and failure rate are described.

[0067] The convolution correction of the independent energy supply elements to the load probability distribution model is the same as the traditional power system production simulation method, and the present application uses the following formula to represent the convolution correction process of the independent power supply element i to the load probability distribution model:

[0068]

[0069]

[0070] In the formula, * is a mathematical operator defined in the present application, which is a convolution operation of a sequence, and is equivalent to the corresponding numerical summation under the constraint condition . is the load probability distribution model before the convolution correction of the i-th independent energy supply element, is the load probability distribution model after the convolution correction of the i-th independent energy supply element, Δx P is the selected discrete step, n P is the discrete load level, is the output capacity of the i-th independent energy supply element, and is a constant.

[0071] Formula (2) and formula (3) are the convolution correction processes of the independent power supply element to the electrical load probability distribution model. The convolution correction process of the independent energy supply element to the thermal load probability distribution model is similar to the convolution correction process of the independent power supply element to the electrical load probability distribution model. One embodiment of the convolution correction process of the independent energy supply element to the load probability distribution model is shown in formula (4). Figure 3

[0072] In addition, the element failure can be equivalent to the working capacity of the element being zero. Therefore, the correction of the element failure to the load probability distribution model can be calculated by combining the two-state model of the element. Formula (4) is the convolution correction process of the independent power supply element to the load probability distribution model considering the failure rate.

[0073]

[0074] Since the convolution correction process of the thermal load probability distribution model is similar to the above formula, it is not described in detail.

[0075] Convolution correction of energy conversion equipment

[0076] (1) Energy conversion element working state determination

[0077] The energy conversion elements in the electric-thermal integrated energy system include electric-thermal conversion elements and thermal-electric conversion elements. The working characteristics of the two types of energy conversion elements can be represented by the following formula:

[0078]

[0079]

[0080] In the formula, P and H represent the electric power (megawatt) and the thermal power (megawatt) of the energy conversion element, respectively, the superscripts P2H and H2P represent the electric-thermal conversion element and the thermal-electric conversion element, respectively, and c represents the conversion efficiency of the energy conversion element.

[0081] The energy conversion element is a place that connects the energy flow of the electric power subsystem and the thermal power subsystem in the electric-thermal integrated energy system, and completes the conversion of one energy flow to another energy flow. In the integrated energy system, the conversion of energy flow is based on the principle of economic optimization, i.e., the objective function is to minimize the total energy supply cost under the current scenario, which can be represented by the following formula:

[0082]

[0083]

[0084]

[0085]

[0086] ​

[0087] wherein, and denote the energy supply cost (yuan / megawatt) of the ith independent power supply and the jth independent heat source, respectively, P i and H j denote the energy supply power (megawatt) of the ith independent power supply and the jth independent heat source, respectively, P load and H load denote the electric and heat load of the current scenario, respectively, and denote the upper limit of the conversion capacity of the kth electric-to-heat element and the lth heat-to-electric element, respectively. In formula (7), J is: the objective function of the energy conversion element operation model, i.e., to achieve the lowest overall energy supply cost of the integrated energy system; the power supply and load balance and the heat supply and load balance constraints of the electric-heat integrated energy system; the energy flow conversion capacity upper limit constraints of the electric-to-heat element and the heat-to-electric element.

[0088] The optimal solution of this optimization model is the working condition of each energy conversion element at a certain time, from which it can be seen that the conversion capacity of the energy conversion element is determined by the economy of the system at this time, i.e., the energy conversion element is put into operation only when it can reduce the total energy supply cost of the system. However, the optimization model based on time sequence simulation has low solving efficiency, so the optimization model can be converted into a power output probability model solving problem for a single energy conversion element.

[0089] According to the loading sequence of the independent power supply and the independent heat source in the traditional production simulation theory, the marginal cost MC P and MC H of each energy subsystem at different load levels can be obtained. For the ith energy conversion element, the multi-energy conversion critical function is defined as follows:

[0090]

[0091] wherein, ψ i denotes the multi-energy conversion critical function of the ith energy conversion element, MC P (x P ), MC H (x H ) denote the marginal cost of the power subsystem at the electric load level x P and the marginal cost of the heat subsystem at the heat load level x H , respectively, c i denotes the conversion efficiency of the ith energy conversion element, and κ and ζ denote the set of electric-to-heat elements and the set of heat-to-electric elements. The multi-energy conversion critical function ψ i (x P , x H) depicts the energy conversion direction of the i-th energy conversion element. The negative value of the multi-energy conversion critical function indicates that the marginal cost of heat supply of the i-th energy conversion element is lower than that of the existing heat subsystem. Therefore, the negative value of this function indicates the tendency of the electric-thermal integrated energy system to convert electric energy into heat energy. Similarly, the positive value of the multi-energy conversion critical function indicates that the marginal cost of power supply of the i-th energy conversion element is lower than that of the existing power subsystem, i.e., indicates the tendency of the electric-thermal integrated energy system to convert heat energy into electric energy. If the multi-energy conversion critical function takes the value of zero, it indicates that the economic efficiency of the electric-thermal integrated energy system has reached the optimal, and the i-th energy conversion element does not need to work. If the type of the i-th energy conversion element is the same as the energy conversion tendency indicated by the multi-energy conversion critical function, this energy conversion element should be put into operation under this condition, and vice versa.

[0092] Energy conversion element working state determination:

[0093] In addition, the operating capacity of the i-th energy conversion element under different load levels can also be obtained by the multi-energy conversion critical function. The ideal operating point of the electric-thermal integrated energy system under the working characteristics of the i-th energy conversion element is shown in (a). Figure 4

[0094] According to the properties of the ideal operating point, the expected working capacity of the i-th energy conversion element can be obtained as follows:

[0095]

[0096] wherein, P i ex , are the expected working capacity of the i-th energy conversion element, are the initial electric load level and the initial heat load level of the electric-thermal integrated energy system, respectively.

[0097] Considering the working capacity constraint of the energy conversion element, the actual working capacity of the i-th energy conversion element is shown in (b) and can be expressed as follows: Figure 4

[0098]

[0099]

[0100] wherein, P i * , are the electric and heat working capacity (megawatts) of the i-th energy conversion element, respectively, are the upper limits of the electric and heat working capacity (megawatts) of the i-th energy conversion element, respectively.

[0101] ​​Convolution of energy conversion element to load probability distribution model:

[0102] As the energy conversion element working model, the essential difference between the energy conversion element and the independent energy supply element is that the working capacity of the energy conversion element changes with the load level. The convolution of the energy conversion element to the load probability distribution model is as follows:

[0103]

[0104]

[0105] In the formula, * is a mathematical operator defined in the present invention, which is a convolution operation of a sequence, equivalent to the corresponding numerical summation under the constraint condition . is the load probability distribution model before convolution correction of the i th energy conversion element, is the load probability distribution model after convolution correction of the i th energy conversion element, Δx P is the selected discrete step, n P is the discrete load level, P i * (n P ) is the discrete sequence of the electric power of the i th energy conversion element with respect to the electric load level. The schematic diagram of the convolution correction of the energy conversion element to the load probability distribution model is as Figure 5 .

[0106] Convolution of energy conversion element failure state to load probability distribution model:

[0107] Element failure can be equivalent to the working capacity of this element being zero. Therefore, the two-state model of this element can be combined to calculate the correction of the load probability distribution model due to the failure of this element. Equation (14) is the convolution correction process of the energy conversion element to the electric load probability distribution model considering the failure rate.

[0108]

[0109] System and device performance evaluation:

[0110] (1) Energy supply calculation of independent energy supply element:

[0111] According to the economy of each energy supply element, the energy supply of each energy supply element can be obtained in sequence according to its loading order. Taking the independent power supply element as an example, the calculation method is briefly described:

[0112]

[0113]

[0114]

[0115]

[0116] where, is the total energy supply of the ith independent energy supply element in the study time T, represents the load probability distribution function of all elements after convolution correction, represents the load cumulative probability distribution function of all elements after convolution correction. The heat supply of the independent heat supply element is calculated in a similar manner as described above, and is not described here.

[0117] Energy conversion element energy conversion amount calculation:

[0118] Energy conversion amount and capacity utilization rate are important indicators for measuring the utilization rate of each energy conversion element in the study period and the economic efficiency of the planning scheme of the electric-thermal integrated energy system, and the calculation method is as follows:

[0119]

[0120]

[0121]

[0122] where, are the electric energy conversion amount and the thermal energy conversion amount of the electric-thermal energy conversion element, respectively, and CSR i * represents the capacity utilization rate of the energy conversion element in the study time.

[0123] System adequacy index calculation:

[0124] The adequacy index of each energy subsystem of the electric-thermal integrated energy system can be described by LOLP and EENS, and the calculation method is as follows:

[0125]

[0126]

[0127]

[0128]

[0129] EENS CHPS = EENS P + EENS H (54)

[0130] where, LOLP P , LOLP H represent the loss of load probability of the power subsystem and the heat subsystem, respectively, and EENSP EENS H EENS CHPS respectively represent the energy shortage expectation value of the power subsystem, the heat subsystem and the electric-thermal integrated energy system.

[0131] Economic index calculation:

[0132] The economic index includes both the system economic index and the energy conversion element economic index. The system economic index can be represented by the energy supply cost, while the economic index of the energy conversion element is represented by the difference in system cost before and after its investment.

[0133]

[0134]

[0135]

[0136]

[0137] wherein, respectively represent the energy supply cost of the power subsystem, the heat subsystem and the electric-thermal integrated energy system in the study time, respectively represent the energy supply cost of the i-th independent power supply element and the heat supply cost of the j-th independent heat supply element. represents the energy supply cost saved by the k-th energy conversion element for the electric-thermal integrated energy system in the study time, i.e., the benefit of the k-th energy conversion element in the study time, and respectively represent the cost of system energy supply before and after the investment of the k-th energy conversion element.

[0138] Actual electric-thermal coupled integrated energy system economic and adequacy rapid assessment effect display:

[0139] The embodiments of the present application take the annual heating and power supply load of a certain urban area in 2020 as an example for display. Taking one hour as the measurement interval, there are a total of 8760 detection points. The peak value of the system power supply load is close to 500 MW, and the peak value of the heat supply load is about 350 MW. The time sequence load curve is shown in Figure 2 (a), and the electric-thermal load probability distribution function is shown in Figure 2 (b). The system contains a total of 7 types of independent power sources, a total of 12; contains a total of 7 types of independent heat sources, a total of 12. The cost, capacity, forced outage rate information is shown in the following table.

[0140] Table 1 Information of independent energy supply elements in the embodiments

[0141] Serial number Category Capacity / MW Cost / $MW -1 ]]> Forced outage rate Number 1 Independent power source 50 5.47 0.02 1 2 Independent power source 50 10.52 0.02 2 3 Independent power source 30 10.89 0.05 1 4 Independent power source 60 13.32 0.01 2 5 Independent power source 75 16.73 0.02 2 6 Independent power source 60 22.93 0.01 2 7 Independent power source 80 26.11 0.05 2 8 Independent heat source 20 7.91 0.01 1 9 Independent heat source 30 13.16 0.02 2 10 Independent heat source 40 15.52 0.05 2 11 Independent heat source 60 18.69 0.02 2 12 Independent heat source 50 20.33 0.03 2 13 Independent heat source 50 24.29 0.03 2 14 Independent heat source 70 28.93 0.05 1

[0142] Table 2. Energy conversion element information for example

[0143]

[0144]

[0145] This example was evaluated according to the implementation of the evaluation method described above. The convolution correction of the electrical-thermal load probability distribution function by the eight energy conversion elements was shown in Figure 6 (a)-(i). The initial electrical-thermal load probability distribution was shown in the dark area of Figure 6 (a), the economic operating region of the first energy conversion element was shown in the shaded area of Figure 6 (a), and the result of the convolution correction of the electrical-thermal load probability distribution function by the first energy conversion element was shown in the dark area of Figure 6 (b). The results of the convolution correction of the electrical-thermal load probability distribution function by the second to eighth energy conversion elements were shown in the dark areas of Figure 6 (c)-(i), respectively. Figure 6 The final electrical-thermal load probability distribution used for evaluation was shown in the dark area of

[0146] The evaluation results of the energy conversion elements in the example were shown in Table 3.

[0147] Table 3. Evaluation results of energy conversion elements

[0148] Serial number Category Economic benefit / $ Average use capacity / MW Capacity utilization efficiency 1 Electric to heat element 54539.4 35804.767 0.5279 2 Electric to heat element 19804.11 14352.770 0.3174 3 Electric to heat element 23961.26 17937.159 0.1983 4 Electric to heat element 6679.714 6393.285 0.0943 5 Electric to heat element 1594.33 1847.810 0.0272 6 Heat to electric element 12387.48 170.934 0.0019 7 Heat to electric element 3915.57 35.278 0.0004 8 Heat to electric element 1712.13 3.482 0.0001

[0149] The economic and adequacy evaluation results of the electrical-thermal integrated energy system in the example for the Chicago city area were shown in Table 4.

[0150] System EENS / MWh LOLP Operating cost / $ Electric power subsystem 0.0051 1.26e-7 6457898 Thermal power subsystem 1.5204 2.92e-5 1242386 Electric-thermal integrated energy system 1.5255 / 7700284

[0151] The economic and adequacy evaluation results of the electrical-thermal integrated energy system in the example for the Chicago city area were shown in Table 4.

[0152] The application establishes an equivalent model composed of independent power supply, independent heat source and energy conversion equipment (including electric heat conversion equipment and heat electric conversion equipment) according to the working principle of coupling equipment in an electric heat comprehensive energy system and electric heat output feasible region. The model considers the energy coupling mechanism of the coupling equipment, thereby solving the difficulty that the internal energy conversion mechanism is difficult to analyze in the modeling of the traditional electric heat coupling equipment. The model provides a theoretical basis for the economy and adequacy evaluation of the electric heat coupling equipment. The method of the application can quickly evaluate the planning and design scheme of the electric heat comprehensive energy system, overcome the shortcomings that the existing time sequence simulation evaluation method of the comprehensive energy system cannot meet the efficient computing demand and cannot theoretically analyze the energy flow conversion, realize more efficient and reasonable economy and adequacy evaluation, thereby quickly evaluating multiple electric heat comprehensive energy system construction schemes proposed in the planning and design stage, provide a more effective basis for the planning and construction of the comprehensive energy system and shorten the time cycle of the planning and design stage.

Claims

1. A method for quickly evaluating the economic efficiency and adequacy of an electric and thermal integrated energy system, characterized in that: The following steps are involved: S1, based on the time series load curve of the evaluated electric and thermal integrated energy system over a period of time, forms a joint distribution function of electric and thermal loads; S2, based on the capacity and forced outage rate information of the independent energy supply components of the evaluated electric and thermal integrated energy system, the joint distribution function of electric and thermal loads is convoluted and corrected; The following formula is used to express the convolution correction process of the load probability distribution model by the independent power supply component i: In the formula, * is a mathematical operator, which is a convolution operation of the sequence, and is equivalent to the constraint condition Sum the corresponding values ​​under ; is the load probability distribution model of the i-th independent energy supply element before convolution correction, is the load probability distribution model after convolution correction of the i-th independent energy supply element, Δx P is the selected discrete step length, n P is the load level after discretization, is the output capacity of the i-th independent energy supply element, which is a constant; S3, based on the multi-energy critical conversion function, the economic working capacity of the energy conversion elements is calculated in sequence according to the economic efficiency ranking of the energy conversion elements, and the electric and heating load joint distribution function corrected in step S2 is further convoluted and corrected based on the economic working capacity and the forced outage rate; The energy conversion elements in the electric-thermal integrated energy system include electric-to-heat elements and heat-to-electric elements. The operating characteristics of the two energy conversion elements are expressed by the following formula: Where P and H represent the electrical power (megawatt) and thermal power (megawatt) of the energy conversion element, respectively; the superscripts P2H and H2P represent the electrical-to-heat element and the thermal-to-electrical element, respectively; and c represents the conversion efficiency of the energy conversion element. S4. Based on the modified electric and thermal load joint distribution function, the economic index and adequacy index of the evaluated electric and thermal integrated energy system are calculated.

2. A method for rapid evaluation of the economy and adequacy of an electric and thermal integrated energy system according to claim 1, characterized in that: For the evaluation of planning schemes, a forecasting method is used to generate a time series load curve, and a joint distribution function of electric and thermal loads is formed based on the time series load curve.

3. A method for rapid evaluation of the economy and adequacy of an electric and thermal integrated energy system according to claim 1, characterized in that: Based on the corrected joint distribution function of electric and thermal loads, the utilization indexes of independent energy supply components and energy conversion components in the system are calculated.

4. A method for rapid evaluation of the economy and adequacy of an electric and thermal integrated energy system according to claim 1, characterized in that: The formation process of the electric-heat load joint probability distribution model is expressed by formula (5): Where N represents the total number of measurement moments in the time period, and They represent the electric charge and heat load at time n respectively.

5. A method for rapid evaluation of the economy and adequacy of an electric and thermal integrated energy system according to claim 1, characterized in that: The independent energy supply elements include an independent power source, an independent heat source and a micro gas turbine cogeneration unit.

6. A method for rapid evaluation of the economy and adequacy of an electric and thermal integrated energy system according to claim 1, characterized in that: System adequacy index calculation: The abundance index of each energy subsystem of the electric and thermal integrated energy system can be described by LOLP and EENS, and the calculation method is as follows: AT SOMETIME CHPS =AGREE P +AGREE H (10) Where, LOLP P ,LOLP H They represent the load loss probability of the power subsystem and the thermal subsystem, EENS P , EENS H , EENS CHPS They represent the expected energy deficit of the power subsystem, thermal subsystem and electric-thermal integrated energy system respectively.

7. A method for rapid evaluation of the economy and adequacy of an electric and thermal integrated energy system according to claim 1, characterized in that: Economic indicators include system economic indicators and energy conversion component economic indicators. System economic indicators can be expressed by energy supply costs: Where, Respectively represent the energy supply costs of the power subsystem, thermal subsystem and electric-thermal integrated energy system during the study period, denote the power supply cost of the i-th independent power supply element and the heating cost of the j-th independent heating element respectively; represents the energy cost saved by the k-th energy conversion element for the electric-thermal integrated energy system during the study period, that is, the benefit of the k-th energy conversion element during the study period, and They represent the cost of system energy supply before and after the kth energy conversion element is put into use.

8. A system for quickly evaluating the economy and adequacy of an electric-thermal integrated energy system based on the method for quickly evaluating the economy and adequacy of an electric-thermal integrated energy system according to claim 1, characterized in that: Includes preprocessing module and evaluation module; The preprocessing module forms a joint distribution function of electric and thermal loads based on the time-series load curve of the evaluated electric and thermal integrated energy system over a period of time; performs convolution correction on the joint distribution function of electric and thermal loads based on the capacity and forced outage rate information of the independent energy supply components of the evaluated electric and thermal integrated energy system; calculates the economic working capacity of the energy conversion components in sequence based on the economic efficiency ranking of the energy conversion components based on the multi-energy critical conversion function, and further performs convolution correction on the joint distribution function of electric and thermal loads corrected in step S2 based on the economic working capacity and forced outage rate; The evaluation module calculates the economic index and adequacy index of the evaluated electric and thermal integrated energy system based on the modified electric and thermal load joint distribution function.

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