A method and system for predicting the average power generation of a regional integrated energy system

Abstract

The present invention relates to a method and system for predicting the average power generation of a regional integrated energy system, including: determining the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system according to the load demand at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system; predicting the average power generation within the control period corresponding to the preset load transfer rate of the regional integrated energy system according to the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system. The technical solution provided by the present invention comprehensively considers the influence of the change in the load demand of the demand-side users on the average power generation of the integrated energy system, improves the accuracy of predicting the average power generation of the integrated energy system, provides a judgment index for the park planners to select production equipment, and provides a theoretical guarantee for the construction, operation and maintenance of the park integrated energy system.

Description

Technical Field

[0001] The present invention relates to the field of regional integrated energy system planning and design, and particularly relates to a method and system for predicting the average power generation of a regional integrated energy system. Background Art

[0002] Today, with the shortage of fossil energy, serious environmental pollution, and the increasing global warming, the integrated energy system with a region as the carrier can improve the penetration ratio of renewable energy, realize the cascaded and efficient utilization of low-grade heat sources and fossil energy, reduce the overall energy consumption and energy consumption per unit output value within the region, integrate various energy resources within the region, and reduce the emissions of carbon dioxide and polluting gases.

[0003] Therefore, the research on regional integrated energy systems has increasingly become the focus of research and exploration by scholars at home and abroad.

[0004] Existing research has carried out detailed research on the operation forms (centralized, decentralized, and integrated) of regional integrated energy systems, the optimization and evaluation in the planning, design, operation, and maintenance stages of regional integrated energy systems, and the market form of integrated energy systems.

[0005] However, with the development of regional integrated energy systems, the interaction between the demand side and the supply side is becoming increasingly strong. It is becoming increasingly important to comprehensively consider the impact of the demand side on the energy system of the supply side in the planning and design stage;

[0006] In current research, for the energy network planning and design of regional integrated energy systems, only the load demand of the demand side is used as a reference to predict the average power generation of the regional integrated energy system, and then the regional integrated energy system is planned and designed based on the average power generation of the regional integrated energy system; the impact of the interaction between the supply side and the demand side (or the change in the load demand of the demand side in response to the requirements of the supply side) on the prediction of the average power generation of the regional integrated energy system by the demand side is not considered. The accuracy of the predicted average power generation of the regional integrated energy system is not high, and the adaptability of the regional integrated energy system planned based on this is not strong. Summary of the Invention

[0007] Aiming at the deficiencies of the prior art, the purpose of the present invention is to provide a method for predicting the average power generation of a regional integrated energy system. This method gives a method for predicting the average power generation of a regional integrated energy system in the planning and design stage, comprehensively considers the impact of the demand-side user energy demand leveling on the average power generation of the integrated energy system, improves the accuracy of predicting the average power generation of the integrated energy system, provides a judgment index for regional planners to select production equipment, and provides a theoretical guarantee for the construction, operation, and maintenance of the regional integrated energy system.

[0008] The purpose of the present invention is achieved by adopting the following technical solutions:

[0009] The present invention provides a method for predicting the average power generation of a regional integrated energy system. The improvement lies in that the method includes:

[0010] Determine the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system according to the load demand at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system;

[0011] Predict the average power generation within the control period corresponding to the preset load transfer rate of the regional integrated energy system according to the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system.

[0012] Preferably, before determining the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system according to the load demand at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system, it further includes:

[0013] Determine the load transfer rate ω of the regional integrated energy system according to the following formula k The load demand at the i-th moment within the corresponding control period

[0014]

[0015] In the formula, P iy Is the predicted load demand of the regional integrated energy system at the i-th moment within the control period, Is the preset value of the demarcation point between the peak load demand period and the low load demand period of the load demand within the time period to which the i-th moment within the control period belongs. When The i-th moment within the control period is in the peak load demand period of its belonging time period; otherwise, the i-th moment within the control period is in the low load demand period of its belonging time period. Is the total number of moments in the peak load demand period within the time period to which the i-th moment within the control period belongs, Is the total number of moments in the low load demand period within the time period to which the i-th moment within the control period belongs, Is the time set of the time period to which the i-th moment within the control period belongs, i ∈ (1~ψ), ψ is the total number of moments within the control period, k ∈ (1~ζ), ζ is the total number of load transfer rates.

[0016] Preferably, determining the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system according to the load demand at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system includes:

[0017] Step A: Initialize i = 1, s = 1;

[0018] Step B: During the s-th iteration, the load transfer rate of the regional integrated energy system is ω k The load demand at the i-th moment within the corresponding control period and the pre-stored load transfer rate ω of the regional integrated energy system k Substitute the production capacity reference quantity sequences at each moment within the corresponding control period into the pre-constructed optimal scheduling model, solve the optimal scheduling model, and obtain the load transfer rate ω of the regional integrated energy system k The optimized production capacity reference quantity sequence, objective function value, and power generation reference quantity at the i-th moment within the corresponding control period; the production capacity reference quantity sequence includes the power generation reference quantity of each power generation device, the heat production reference quantity of each heat production device, and the cooling production reference quantity of each cooling production device in the regional integrated energy system; the load transfer rate of the regional integrated energy system is ω k The optimized power generation reference quantity at the i-th moment within the corresponding control period is the sum of the power generation reference quantities of each power generation device in the optimized production capacity reference quantity sequence at this moment;

[0019] Step C: According to the load transfer rate ω of the regional integrated energy system k The optimized production capacity reference quantity sequence at the i-th moment within the corresponding control period is used to update the pre-stored load transfer rate ω of the regional integrated energy system k The production capacity reference quantity sequence at the i-th moment within the corresponding control period;

[0020] Step D: When i = ψ, if during the s-th iteration, the load transfer rate of the regional integrated energy system is ω k The sum of the objective function values at each moment within the corresponding control period satisfies the preset termination condition, then output the load transfer rate ω of the regional integrated energy system obtained during the s-th iteration k The power generation reference quantities at each moment within the corresponding control period; otherwise, let s = s + 1, and return to Step B; when i ≠ ψ, let i = i + 1, and return to Step B;

[0021] where ψ is the total number of moments in the control period, k ∈ (1~ζ), and ζ is the total number of load transfer rates;

[0022] The preset termination condition is is the sum of the objective function values at each moment within the corresponding control period when the load transfer rate of the regional integrated energy system is ω during the s-th iteration k The load transfer rate is ω k The sum of the objective function values at each moment within the control period of the regional integrated energy system when is the load transfer rate of the regional integrated energy system during the (s - 1)-th iteration kThe sum of the objective function values at each moment within the corresponding control period, σ0 is the iteration termination threshold, k ∈ (1 to ζ), and ζ is the total number of load transfer rates.

[0023] Furthermore, the objective function of the pre-constructed optimal scheduling model is determined by the following formula:

[0024] F i = min(f i,e + f i,c + f i,h )

[0025] In the formula, F i is the objective function value of the regional integrated energy system at the i-th moment of the control period, f i,e is the equivalent standard coal consumption for power generation of the regional integrated energy system at the i-th moment of the control period, f i,c is the equivalent standard coal consumption for cooling production of the regional integrated energy system at the t-th moment of the control period, f i,h is the equivalent standard coal consumption for heat production of the regional integrated energy system at the i-th moment of the control period;

[0026] Among them, the equivalent standard coal consumption f i,e for power generation of the regional integrated energy system at the i-th moment of the control period is determined by the following formula:

[0027]

[0028] In the formula, p r,b is the equivalent standard coal consumption of primary energy consumed by the b-th power generation device in the regional integrated energy system for producing a unit of electric energy, is the power generation reference quantity of the b-th power generation device in the regional integrated energy system at the i-th moment of the control period, is the power generation efficiency of the b-th power generation device in the regional integrated energy system, is the equivalent annual coefficient of the b-th power generation device in the regional integrated energy system, IV b is the fixed technical level of the b-th power generation device in the regional integrated energy system, is the power generation reference quantity of the b-th power generation device in the regional integrated energy system stored in advance in the dataset at the Σ-th moment within the control period, M t,b is the maintenance loss of the b-th power generation device in the regional integrated energy system, b ∈ (1 to S b ), S b is the total number of power generation devices in the regional integrated energy system, i, Σ ∈ (1 to ψ), and ψ is the total number of moments in the control period;

[0029] The equivalent standard coal consumption f i,c for cooling production of the regional integrated energy system at the i-th moment of the control period is determined by the following formula:

[0030]

[0031] In the formula, p r,q is the equivalent standard coal consumption of primary energy consumed by the q-th refrigeration device in the regional integrated energy system to produce unit energy, is the reciprocal of the equivalent standard coal consumption corresponding to the electricity generation reference quantity at the i-th moment in the control period of the regional integrated energy system, is the cooling production reference quantity of the q-th refrigeration device in the regional integrated energy system at the i-th moment in the control period, is the cooling production reference quantity of the q-th refrigeration device by gas refrigeration at the i-th moment in the control period in the regional integrated energy system, is the gas refrigeration efficiency of the q-th refrigeration device in the regional integrated energy system, is the cooling production reference quantity of the q-th refrigeration device by electric refrigeration at the i-th moment in the control period in the regional integrated energy system, is the electric refrigeration efficiency of the q-th refrigeration device in the regional integrated energy system, is the equivalent annual coefficient IV of the q-th refrigeration device in the regional integrated energy system, q is the fixed technical level M of the q-th refrigeration device in the regional integrated energy system, i,q is the maintenance loss of the q-th refrigeration device in the regional integrated energy system, is the cooling production reference quantity of the q-th refrigeration device in the regional integrated energy system pre-stored in the dataset at the Σ-th moment in the control period, q ∈ (1~S q ), S q is the total number of refrigeration devices in the regional integrated energy system, is the electricity generation reference quantity of the regional integrated energy system at the i-th moment in the control period;

[0032] The equivalent standard coal consumption f of heat production of the regional integrated energy system at the t-th moment in the control period is determined by the following formula t,h :

[0033]

[0034] In the formula, p r,j is the equivalent standard coal consumption of primary energy consumed by the j-th heating device in the regional integrated energy system to produce unit energy, is the heat production reference quantity of the j-th heating device in the regional integrated energy system at the i-th moment in the control period, is the heat production reference quantity of the j-th heating device by gas heating at the i-th moment in the control period in the regional integrated energy system, is the gas heating efficiency of the j-th heating device in the regional integrated energy system, is the reference heat production quantity by electric heating for the j-th heating device in the regional integrated energy system at the i-th moment of the control period. is the electric heating efficiency of the j-th heating device in the regional integrated energy system. is the equivalent annual coefficient of the j-th heating device in the regional integrated energy system, IV j is the fixed technical level of the j-th heating device in the regional integrated energy system, M i,j is the maintenance loss of the j-th heating device in the regional integrated energy system. is the reference heat production quantity of the j-th heating device in the regional integrated energy system at the Σ-th moment within the control period pre-stored in the dataset, j ∈ (1~S j ),S j is the total number of heating devices in the regional integrated energy system.

[0035] Furthermore, the constraint conditions of the objective function of the pre-constructed optimal scheduling model include: microgrid balance constraint condition, micro-cooling network balance constraint condition, micro-heating network balance constraint condition, CHP power generation equipment output constraint condition, refrigeration unit output constraint condition, and heating unit output constraint condition.

[0036] Preferably, the method for predicting the average power generation quantity of the regional integrated energy system corresponding to the preset load transfer rate according to the power generation reference quantities at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system includes:

[0037] According to the power generation reference quantities at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system, calculate the average value of the power generation reference quantities of the control periods corresponding to each load transfer rate of the regional integrated energy system;

[0038] Based on the average value of the power generation reference quantities of the control periods corresponding to each load transfer rate of the regional integrated energy system, establish a fitting relationship between each load transfer rate of the regional integrated energy system and the average value of the power generation reference quantities of its corresponding control period by using the regression analysis method;

[0039] Substitute the preset load transfer rate into the fitting relationship to predict the average power generation quantity of the control period corresponding to the preset load transfer rate of the regional integrated energy system.

[0040] The present invention provides a system for predicting the average power generation quantity of a regional integrated energy system, and the improvement lies in that the system includes:

[0041] The first determination module is used to determine the power generation reference quantities at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system according to the load demands at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system;

[0042] A prediction module, configured to predict the average power generation amount in a control period corresponding to a preset load transfer rate of the regional integrated energy system according to the power generation reference amounts at each moment in the control period corresponding to each load transfer rate of the regional integrated energy system.

[0043] Preferably, the system further includes an initial determination module, configured to

[0044] determine the load transfer rate ω of the regional integrated energy system according to the following formula k the load demand at the i-th moment in the corresponding control period

[0045]

[0046] wherein, P iy is the predicted load demand of the regional integrated energy system at the i-th moment in the control period, is the preset value of the demarcation point between the peak load demand period and the low load demand period of the time period to which the i-th moment in the control period belongs. When , the i-th moment in the control period is in the peak load demand period of its belonging time period, otherwise, the i-th moment in the control period is in the low load demand period of its belonging time period, is the total number of moments in the peak load demand period within the time period to which the i-th moment in the control period belongs, is the total number of moments in the low load demand period within the time period to which the i-th moment in the control period belongs, is the set of moments of the time period to which the i-th moment in the control period belongs, i ∈ (1~ψ), ψ is the total number of moments in the control period, k ∈ (1~ζ), ζ is the total number of load transfer rates.

[0047] Preferably, the first determination module includes:

[0048] An initialization unit, configured to initialize i = 1, s = 1;

[0049] An acquisition unit, configured to, during the s-th iteration, substitute the load demand at the i-th moment in the control period corresponding to the load transfer rate ω of the regional integrated energy system and the sequence of production capacity reference amounts at each moment in the control period corresponding to the load transfer rate ω of the regional integrated energy system stored in advance into the pre-constructed optimal scheduling model, solve the optimal scheduling model, and obtain the load transfer rate ω of the regional integrated energy system k corresponding to the load demand at the i-th moment in the corresponding control period and the load transfer rate ω of the regional integrated energy system k corresponding to the production capacity reference amount sequence at each moment in the corresponding control period into the pre-constructed optimal scheduling model, solve the optimal scheduling model, and obtain the load transfer rate ω of the regional integrated energy system kThe optimized production capacity reference quantity sequence, objective function value, and power generation reference quantity at the i-th moment within the corresponding control period; the production capacity reference quantity sequence includes the power generation reference quantity of each power generation device, the heat production reference quantity of each heat production device, and the cooling production reference quantity of each cooling production device in the regional integrated energy system; the load transfer rate of the regional integrated energy system is ω k The optimized power generation reference quantity at the i-th moment within the corresponding control period is the sum of the power generation reference quantities of each power generation device in the optimized production capacity reference quantity sequence at this moment;

[0050] An update unit, configured to update the pre-stored load transfer rate ω of the regional integrated energy system according to the optimized production capacity reference quantity sequence at the i-th moment within the corresponding control period k The optimized production capacity reference quantity sequence at the i-th moment within the corresponding control period, and update the pre-stored load transfer rate ω of the regional integrated energy system k The production capacity reference quantity sequence at the i-th moment within the corresponding control period;

[0051] An output unit, configured to, when i = ψ, if the sum of the objective function values at each moment within the corresponding control period during the s-th iteration satisfies a preset termination condition, output the load transfer rate ω of the regional integrated energy system obtained during the s-th iteration k The sum of the objective function values at each moment within the corresponding control period, and output the power generation reference quantity at each moment within the corresponding control period; otherwise, set s = s + 1, and return to step B; when i ≠ ψ, set i = i + 1, and return to step B; k where ψ is the total number of moments in the control period, k ∈ (1 ~ ζ), and ζ is the total number of load transfer rates;

[0052] The preset termination condition is

[0053] is the sum of the objective function values at each moment within the corresponding control period when the load transfer rate of the regional integrated energy system during the s-th iteration is ω is the sum of the objective function values at each moment within the corresponding control period when the load transfer rate of the regional integrated energy system during the s-th iteration is ω k is the sum of the objective function values at each moment within the corresponding control period of the regional integrated energy system k when the load transfer rate is ω, is the sum of the objective function values at each moment within the corresponding control period when the load transfer rate of the regional integrated energy system during the (s - 1)-th iteration is ω k is the sum of the objective function values at each moment within the corresponding control period, σ0 is the iteration termination threshold, k ∈ (1 ~ ζ), and ζ is the total number of load transfer rates.

[0054] Furthermore, the objective function of the pre-constructed optimal scheduling model is determined by the following formula:

[0055] F i = min(f i,e + f i,c + fi,h )

[0056] In the formula, F i is the objective function value of the regional integrated energy system at the i-th moment of the control period, and f i,e is the equivalent standard coal consumption for power generation of the regional integrated energy system at the i-th moment of the control period, and f i,c is the equivalent standard coal consumption for cooling production of the regional integrated energy system at the t-th moment of the control period, and f i,h is the equivalent standard coal consumption for heat production of the regional integrated energy system at the i-th moment of the control period;

[0057] Among them, the equivalent standard coal consumption f for power generation of the regional integrated energy system at the i-th moment of the control period is determined by the following formula i,e :

[0058]

[0059] In the formula, p r,b is the equivalent standard coal consumption of primary energy consumed by the b-th power generation device in the regional integrated energy system for producing a unit of electric energy, is the power generation reference quantity of the b-th power generation device in the regional integrated energy system at the i-th moment of the control period, is the power generation efficiency of the b-th power generation device in the regional integrated energy system, is the equivalent annual coefficient of the b-th power generation device in the regional integrated energy system, IV b is the fixed technical level of the b-th power generation device in the regional integrated energy system, is the power generation reference quantity of the b-th power generation device in the regional integrated energy system at the Σ-th moment during the control period pre-stored in the dataset, M t,b is the maintenance loss of the b-th power generation device in the regional integrated energy system, b ∈ (1 to S b ), S b is the total number of power generation devices in the regional integrated energy system, i, Σ ∈ (1 to ψ), and ψ is the total number of moments in the control period;

[0060] The equivalent standard coal consumption f for cooling production of the regional integrated energy system at the i-th moment of the control period is determined by the following formula ic :

[0061]

[0062] In the formula, p r,q is the equivalent standard coal consumption of primary energy consumed by the q-th refrigeration device in the regional integrated energy system for producing a unit of energy, is the reciprocal of the equivalent standard coal consumption corresponding to the power generation reference quantity of the regional integrated energy system at the i-th moment of the control period, $Q_{c,q,i}^{ref}$ is the reference cooling output of the $q$-th refrigeration device in the regional integrated energy system at the $i$-th moment within the control period. $Q_{c,g,q,i}^{ref}$ is the reference cooling output of the $q$-th refrigeration device in the regional integrated energy system by gas refrigeration at the $i$-th moment within the control period. $\eta_{g,q}$ is the gas refrigeration efficiency of the $q$-th refrigeration device in the regional integrated energy system. $Q_{c,e,q,i}^{ref}$ is the reference cooling output of the $q$-th refrigeration device in the regional integrated energy system by electric refrigeration at the $i$-th moment within the control period. $\eta_{e,q}$ is the electric refrigeration efficiency of the $q$-th refrigeration device in the regional integrated energy system. $IV_q$ is the equivalent annual coefficient of the $q$-th refrigeration device in the regional integrated energy system. q $M_q$ is the fixed technical level of the $q$-th refrigeration device in the regional integrated energy system. i,q $L_q$ is the maintenance loss of the $q$-th refrigeration device in the regional integrated energy system. $Q_{c,q,\sum}^{ref}$ is the reference cooling output of the $q$-th refrigeration device in the regional integrated energy system pre-stored in the dataset at the $\sum$-th moment within the control period, $q\in(1\sim S$ q ) and $S$ q $S$ is the total number of refrigeration devices in the regional integrated energy system. $Q_{e,i}^{ref}$ is the reference power generation output of the regional integrated energy system at the $i$-th moment within the control period;

[0063] The equivalent standard coal consumption $f$ of heat production at the $t$-th moment in the control period of the regional integrated energy system is determined by the following formula t,h :

[0064]

[0065] In the formula, $p$ r,j is the equivalent standard coal consumption of primary energy consumed by the $j$-th heating device in the regional integrated energy system to produce unit energy, $Q_{h,j,i}^{ref}$ is the reference heat production output of the $j$-th heating device in the regional integrated energy system at the $i$-th moment within the control period, $Q_{h,g,j,i}^{ref}$ is the reference heat production output of the $j$-th heating device in the regional integrated energy system by gas heating at the $i$-th moment within the control period, $\eta_{g,j}$ is the gas heating efficiency of the $j$-th heating device in the regional integrated energy system. $Q_{h,e,j,i}^{ref}$ is the reference heat production output of the $j$-th heating device in the regional integrated energy system by electric heating at the $i$-th moment within the control period, $\eta_{e,j}$ is the electric heating efficiency of the $j$-th heating device in the regional integrated energy system. $IV_j$ is the equivalent annual coefficient of the $j$-th heating device in the regional integrated energy system. j $M_j$ is the fixed technical level of the $j$-th heating device in the regional integrated energy system. i,jis the maintenance loss of the j-th heating device in the regional integrated energy system. is the heat production reference quantity of the j-th heating device in the regional integrated energy system pre-stored in the dataset at the Σ-th moment within the control period, where j ∈ (1 to S j ), and S j is the total number of heating devices in the regional integrated energy system.

[0066] Furthermore, the constraint conditions of the objective function of the pre-constructed optimal scheduling model include: microgrid balance constraint conditions, micro-cooling network balance constraint conditions, micro-heating network balance constraint conditions, CHP power generation equipment output constraint conditions, refrigeration unit output constraint conditions, and heating unit output constraint conditions.

[0067] Preferably, the prediction module includes:

[0068] A calculation unit that calculates the average value of the electricity production reference quantity of the control period corresponding to each load transfer rate of the regional integrated energy system according to the electricity production reference quantity of each moment within the control period corresponding to each load transfer rate of the regional integrated energy system.

[0069] A fitting unit that, based on the average value of the electricity production reference quantity of the control period corresponding to each load transfer rate of the regional integrated energy system, uses the regression analysis method to establish a fitting relationship between each load transfer rate of the regional integrated energy system and the average value of the electricity production reference quantity of its corresponding control period.

[0070] A prediction unit that substitutes the preset load transfer rate into the fitting relationship to predict the average electricity production of the control period corresponding to the preset load transfer rate of the regional integrated energy system.

[0071] Compared with the closest prior art, the beneficial effects of the present invention are:

[0072] The technical solution provided by the present invention determines the electricity production reference quantity of each moment within the control period corresponding to each load transfer rate of the regional integrated energy system according to the load demand of each moment within the control period corresponding to each load transfer rate of the regional integrated energy system; determines the predicted average electricity production of the control period corresponding to the preset load transfer rate of the regional integrated energy system according to the electricity production reference quantity of each moment within the control period corresponding to each load transfer rate of the regional integrated energy system; this solution comprehensively considers the influence of the change in the load demand of the demand-side users on the average electricity production of the integrated energy system, improves the accuracy of the prediction of the average electricity production of the integrated energy system, provides a judgment index for the park planners to select production equipment, and provides a theoretical guarantee for the construction, operation, and maintenance of the park's integrated energy system. Description of the Drawings

[0073] Figure 1 is a flowchart of a method for predicting the average electricity production of a regional integrated energy system;

[0074] Figure 2 It is the energy network structure diagram of the regional integrated energy system in the embodiment of the present invention;

[0075] Figure 3 It is the initial cooling, heating, and power load curve diagram of a typical day of a certain regional integrated energy system in the embodiment of the present invention;

[0076] Figure 4 It is the power generation, heat and cold reference quantity curve diagram corresponding to a typical day of a certain regional integrated energy system in the embodiment of the present invention when the load transfer rate is 0;

[0077] Figure 5 It is the iteration curve diagram in the embodiment of the present invention;

[0078] Figure 6 It is the average power generation amount, configuration ratio, and fitting curve of a certain regional integrated energy system in the embodiment of the present invention under different load transfer rates;

[0079] Figure 7 It is the average cooling output and average heating output of a certain regional integrated energy system in the embodiment of the present invention under different load transfer rates;

[0080] Figure 8 It is the system structure diagram of a method for predicting the average power generation amount of a regional integrated energy system. Specific embodiments

[0081] The following further elaborates on the specific embodiments of the present invention in conjunction with the accompanying drawings.

[0082] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0083] The present invention provides a method for predicting the average power generation amount of a regional integrated energy system, as Figure 1 shown, the method includes:

[0084] Step 101. Determine the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system according to the load demand at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system;

[0085] Step 102. Predict the average power generation of the control period corresponding to the preset load transfer rate of the regional integrated energy system according to the power generation reference quantity at each moment in the control period corresponding to each load transfer rate of the regional integrated energy system.

[0086] Specifically, before step 101, the method further includes:

[0087] The load transfer rate of the regional integrated energy system is determined as follows: k The load demand at the i-th moment in the corresponding control cycle

[0088]

[0089] Where P iy is the predicted load demand of the regional integrated energy system at the i-th moment in the control period, It is the preset value of the demarcation point between the peak load demand period and the trough load demand period of the regional integrated energy system in the period of the i-th moment of the control cycle. When , the i-th moment of the control cycle is in the peak period of the load demand in the period to which it belongs, otherwise, the i-th moment of the control cycle is in the trough period of the load demand in the period to which it belongs. is the total number of peak load demand moments in the time period of the i-th moment in the control cycle, is the total number of moments in the low load demand period within the time period of the i-th moment in the control cycle, is the time set of the time period to which the i-th moment of the control cycle belongs, i∈(1~ψ), ψ is the total number of moments in the control cycle, k∈(1~ζ), ζ is the total number of load transfer rates.

[0090] In the best embodiment of the present invention, the energy demand within a time period is divided into a valley period and a peak period according to the load characteristics of the energy-intensive area. The percentage of the load transferred from the peak period to the valley period in the total load demand within the time period is the load transfer rate. By setting the load transfer rate, the load in the peak period within the time period is transferred to the peak and valley period within the time period, so as to achieve the leveling of the energy demand of the demand side and achieve the effect of peak shaving and valley filling. Table 1 shows the maximum load changes in the region corresponding to different load transfer rates. The table shows that when the load transfer rate increases, the maximum load demand of the regional comprehensive energy system first decreases and then increases. This shows that the load transfer rate is not the larger the better. When it exceeds a certain limit, a new peak load will be generated, which will have the opposite effect on the energy configuration on the supply side.

[0091] Table 1

[0092]

[0093] Specifically, the step 101 includes:

[0094] Step A: Initialize i = 1 and s = 1;

[0095] Step B: During the s-th iteration, set the load transfer rate of the regional integrated energy system as ω k The load demand at the i-th moment within the corresponding control period and the pre-stored load transfer rate ω of the regional integrated energy system k Substitute the production capacity reference quantity sequences at each moment within the corresponding control period into the pre-constructed optimal scheduling model, solve the optimal scheduling model, and obtain the load transfer rate ω of the regional integrated energy system k The optimized production capacity reference quantity sequence, objective function value, and power generation reference quantity at the i-th moment within the corresponding control period; the production capacity reference quantity sequence includes the power generation reference quantity of each power generation device, the heat production reference quantity of each heat production device, and the cooling production reference quantity of each cooling production device in the regional integrated energy system; the load transfer rate of the regional integrated energy system is ω k The optimized power generation reference quantity at the i-th moment within the corresponding control period is the sum of the power generation reference quantities of each power generation device in the optimized production capacity reference quantity sequence at this moment;

[0096] Step C: According to the load transfer rate ω of the regional integrated energy system k The optimized production capacity reference quantity sequence at the i-th moment within the corresponding control period, update the pre-stored load transfer rate ω of the regional integrated energy system k The production capacity reference quantity sequence at the i-th moment within the corresponding control period;

[0097] Step D: When i = ψ, if the sum of the objective function values at each moment within the corresponding control period during the s-th iteration when the load transfer rate of the regional integrated energy system is ω k meets the preset termination condition, then output the load transfer rate ω of the regional integrated energy system obtained during the s-th iteration k The power generation reference quantities at each moment within the corresponding control period; otherwise, set s = s + 1 and return to Step B; when i ≠ ψ, set i = i + 1 and return to Step B;

[0098] where ψ is the total number of moments in the control period, k ∈ (1~ζ), and ζ is the total number of load transfer rates;

[0099] The preset termination condition is is the sum of the objective function values at each moment within the corresponding control period during the s-th iteration when the load transfer rate of the regional integrated energy system is ω k The sum of the objective function values at each moment within the control period when the load transfer rate is ω k The sum of the objective function values at each moment within the control period of the regional integrated energy system when The load transfer rate of the regional integrated energy system during the (s - 1)-th iteration is ω k The sum of the objective function values at each moment within the corresponding control period, σ0 is the iteration termination threshold, k ∈ (1 to ζ), and ζ is the total number of load transfer rates.

[0100] In the best embodiment of the present invention, before the initial iteration starts, the pre-stored load transfer rate of the regional integrated energy system is ω k The electricity generation reference quantity of each electricity generation device, the heat production reference quantity of each heat production device, and the cooling production reference quantity of each cooling production device in the production capacity reference quantity sequence of the regional integrated energy system at each moment within the corresponding control period are all 0.

[0101] Furthermore, the objective function of the pre-constructed optimal scheduling model is determined according to the following formula:

[0102] F i = min(f i,e + f i,c + f i,h )

[0103] In the formula, F i is the objective function value of the regional integrated energy system at the i-th moment of the control period, f i,e is the equivalent standard coal consumption for electricity generation of the regional integrated energy system at the i-th moment of the control period, f i,c is the equivalent standard coal consumption for cooling production of the regional integrated energy system at the t-th moment of the control period, f i,h is the equivalent standard coal consumption for heat production of the regional integrated energy system at the i-th moment of the control period;

[0104] Among them, the equivalent standard coal consumption for electricity generation f i,e of the regional integrated energy system at the i-th moment of the control period is determined according to the following formula:

[0105]

[0106] In the formula, p r,b is the equivalent standard coal consumption of primary energy consumed by the b-th electricity generation device in the regional integrated energy system for producing a unit of electricity, is the electricity generation reference quantity of the b-th electricity generation device in the regional integrated energy system at the i-th moment of the control period, is the electricity generation efficiency of the b-th electricity generation device in the regional integrated energy system, is the equivalent annual coefficient of the b-th electricity generation device in the regional integrated energy system, IV b is the fixed technical level of the b-th electricity generation device in the regional integrated energy system, and its value is equal to the product of the annual maximum capacity of the b-th electricity generation device and the unit value of the b-th electricity generation device, $M_{b,\Sigma}$ is the reference power generation quantity of the $b$-th power generation device in the pre-stored regional integrated energy system in the dataset at the $\Sigma$-th moment within the control period. t,b $M_{b}$ is the maintenance loss of the $b$-th power generation device in the regional integrated energy system, where $b\in(1\sim S)$ b ) and $S$ b is the total number of power generation devices in the regional integrated energy system. $i,\Sigma\in(1\sim\psi)$, and $\psi$ is the total number of moments in the control period.

[0107] The equivalent standard coal consumption $f_{i}$ of cooling production in the regional integrated energy system at the $i$-th moment within the control period is determined by the following formula i,c :

[0108]

[0109] In the formula, $p_{q}$ r,q is the equivalent standard coal consumption of primary energy consumed by the $q$-th refrigeration device in the regional integrated energy system to produce a unit of energy. $\frac{1}{M_{i}}$ is the reciprocal of the equivalent standard coal consumption corresponding to the reference power generation quantity of the regional integrated energy system at the $i$-th moment within the control period. $Q_{q,i}$ is the reference cooling production quantity of the $q$-th refrigeration device in the regional integrated energy system at the $i$-th moment within the control period. $Q_{q,g,i}$ is the reference cooling production quantity of the $q$-th refrigeration device by gas refrigeration at the $i$-th moment within the control period in the regional integrated energy system. $\eta_{q,g}$ is the gas refrigeration efficiency of the $q$-th refrigeration device in the regional integrated energy system. $Q_{q,e,i}$ is the reference cooling production quantity of the $q$-th refrigeration device by electric refrigeration at the $i$-th moment within the control period in the regional integrated energy system. $\eta_{q,e}$ is the electric refrigeration efficiency of the $q$-th refrigeration device in the regional integrated energy system. $IV_{q}$ is the equivalent annual coefficient of the $q$-th refrigeration device in the regional integrated energy system. q $M_{q}$ is the fixed technical level of the $q$-th refrigeration device in the regional integrated energy system, and its value is equal to the product of the annual maximum capacity of the $q$-th refrigeration device and the unit value of the $q$-th refrigeration device. i,q $M_{q}$ is the maintenance loss of the $q$-th refrigeration device in the regional integrated energy system. $Q_{q,\Sigma}$ is the pre-stored reference cooling production quantity of the $q$-th refrigeration device in the regional integrated energy system in the dataset at the $\Sigma$-th moment within the control period, where $q\in(1\sim S)$ q ) and $S$ q is the total number of refrigeration devices in the regional integrated energy system. $M_{i}$ is the reference power generation quantity of the regional integrated energy system at the $i$-th moment within the control period.

[0110] The equivalent standard coal consumption $f_{t}$ of heat production in the regional integrated energy system at the $t$-th moment within the control period is determined by the following formulat,h :

[0111]

[0112] where p r，j is the equivalent standard coal consumption of primary energy consumed by the j-th heating device in the regional integrated energy system to produce unit energy, is the heat production reference quantity of the j-th heating device in the regional integrated energy system at the i-th moment of the control period, is the heat production reference quantity of the j-th heating device by gas heating at the i-th moment of the control period in the regional integrated energy system, is the gas heating efficiency of the j-th heating device in the regional integrated energy system, is the heat production reference quantity of the j-th heating device by electric heating at the i-th moment of the control period in the regional integrated energy system, is the electric heating efficiency of the j-th heating device in the regional integrated energy system, is the equivalent annual coefficient of the j-th heating device in the regional integrated energy system, IV j is the fixed technical level of the j-th heating device in the regional integrated energy system, and its value is equal to the product of the annual maximum capacity of the j-th heating device and the unit value of the j-th heating device, M i,j is the maintenance loss of the j-th heating device in the regional integrated energy system, is the heat production reference quantity of the j-th heating device in the regional integrated energy system at the Σ-th moment within the control period pre-stored in the dataset, j ∈ (1~S j ), S j is the total number of heating devices in the regional integrated energy system. Among them, the equivalent annual coefficient of the b-th power generation device in the regional integrated energy system is determined by the following formula

[0113]

[0114] The equivalent annual coefficient of the q-th refrigeration device in the regional integrated energy system is determined by the following formula

[0115]

[0116] The equivalent annual coefficient of the j-th heating device in the regional integrated energy system is determined by the following formula

[0117]

[0118] The maintenance loss M of the b-th power generation device in the regional integrated energy system is determined by the following formula i,b :

[0119]

[0120] Determine the maintenance loss \(M\) of the \(q\)-th refrigeration device in the regional integrated energy system according to the following formula i,q :

[0121]

[0122] Determine the maintenance loss \(M\) of the \(j\)-th heating device in the regional integrated energy system according to the following formula i,j :

[0123]

[0124] In the formula, \(r\) is the discount rate, is the life cycle of the \(b\)-th power generation device in the regional integrated energy system, is the life cycle of the \(q\)-th refrigeration device in the regional integrated energy system, is the life cycle of the \(j\)-th heating device in the regional integrated energy system, \(\alpha\) b is the fixed maintenance coefficient of the \(b\)-th power generation device in the regional integrated energy system, \(\beta\) b is the variable maintenance coefficient of the \(b\)-th power generation device in the regional integrated energy system, \(\alpha\) q is the fixed maintenance coefficient of the \(q\)-th refrigeration device in the regional integrated energy system, \(\beta\) q is the variable maintenance coefficient of the \(q\)-th refrigeration device in the regional integrated energy system, \(\alpha\) j is the fixed maintenance coefficient of the \(j\)-th heating device in the regional integrated energy system, \(\beta\) j is the variable maintenance coefficient of the \(j\)-th heating device in the regional integrated energy system.

[0125] Furthermore, the constraint conditions of the objective function of the pre-constructed optimal scheduling model include: microgrid balance constraint conditions, micro-cooling network balance constraint conditions, micro-heating network balance constraint conditions, CHP power generation equipment output constraint conditions, refrigeration unit output constraint conditions, and heating unit output constraint conditions.

[0126] Among them, determine the microgrid balance constraint conditions according to the following formula

[0127]

[0128] In the formula, is the power consumption of other devices at the \(i\)-th moment in the control period of the regional integrated energy system, is the power consumption of the \(q\)-th refrigeration device at the \(i\)-th moment in the control period of the regional integrated energy system, is the power consumption of the \(j\)-th heating device at the \(i\)-th moment in the control period of the regional integrated energy system;

[0129] Determine the balance constraint conditions of the micro-cooling network according to the following formula:

[0130]

[0131] In the formula, LC i is the cooling load of the regional integrated energy system at the i-th moment of the control period;

[0132] Determine the balance constraint conditions of the micro-heating network according to the following formula:

[0133]

[0134] In the formula, LH i is the heating load of the regional integrated energy system at the i-th moment of the control period;

[0135] Determine the output constraint conditions of the CHP power generation equipment according to the following formula:

[0136]

[0137]

[0138] In the formula, is the reference power generation quantity of the CHP power generation equipment t in the regional integrated energy system at the i-th moment of the control period, G i,chp(t) is the gas consumption of the CHP power generation equipment t in the regional integrated energy system at the i-th moment of the control period, is the power generation efficiency of the CHP power generation equipment t in the regional integrated energy system, q rq is the calorific value of the gas, is the minimum limit value of the power generation quantity of the CHP power generation equipment t in the regional integrated energy system, is the start-stop state of the CHP power generation equipment t in the regional integrated energy system at the i-th moment of the control period, is the maximum limit value of the power generation quantity of the CHP power generation equipment t in the regional integrated energy system. When the CHP power generation equipment t in the regional integrated energy system is turned on at the i-th moment of the control period. When the CHP power generation equipment t in the regional integrated energy system is turned off at the i-th moment of the control period, t ∈ (1~S t ), S t is the total number of CHP power generation equipment in the regional integrated energy system;

[0139] Determine the output constraint conditions of the electric refrigeration unit according to the following formula:

[0140]

[0141]

[0142] In the formula, is the reference cooling output of the electric refrigeration equipment κ in the regional integrated energy system at the i-th moment of the control period, is the power consumption of the electric refrigeration equipment κ in the regional integrated energy system at the i-th moment of the control period, is the refrigeration efficiency of the electric refrigeration equipment κ in the regional integrated energy system, is the minimum limit of the cooling output of the electric refrigeration equipment κ in the regional integrated energy system, is the maximum limit of the cooling output of the electric refrigeration equipment κ in the regional integrated energy system, is the start-stop state of the electric refrigeration equipment κ in the regional integrated energy system at the i-th moment of the control period. When , the electric refrigeration equipment κ in the regional integrated energy system is turned on at the i-th moment of the control period. When , the electric refrigeration equipment κ in the regional integrated energy system is turned off at the i-th moment of the control period, where κ ∈ (1~S κ ), and S κ is the total number of electric refrigeration equipment in the regional integrated energy system;

[0143] The output constraint condition of the electric heating unit is determined according to the following formula:

[0144]

[0145]

[0146] In the formula, is the reference heat output of the electric heating equipment ξ in the regional integrated energy system at the i-th moment of the control period, is the power consumption of the electric heating equipment ξ in the regional integrated energy system at the i-th moment of the control period, is the heating efficiency of the electric heating equipment ξ in the regional integrated energy system at the i-th moment of the control period, is the minimum limit of the heat output of the electric heating equipment in the regional integrated energy system, is the start-stop state of the electric heating equipment ξ in the regional integrated energy system at the i-th moment of the control period, is the maximum limit of the heat output of the electric heating equipment in the regional integrated energy system. When , the electric refrigeration equipment ξ in the regional integrated energy system is turned on at the i-th moment of the control period. When , the electric refrigeration equipment ξ in the regional integrated energy system is turned off at the i-th moment of the control period, where ξ ∈ (1~S ξ ), and S ξ is the total number of electric heating equipment in the regional integrated energy system.

[0147] Specifically, step 102 includes:

[0148] Calculate the average value of the power generation reference quantity for each control period corresponding to each load transfer rate of the regional integrated energy system based on the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system;

[0149] Based on the average value of the power generation reference quantity for each control period corresponding to each load transfer rate of the regional integrated energy system, use the regression analysis method to establish a fitting relationship between each load transfer rate of the regional integrated energy system and the average value of the power generation reference quantity for its corresponding control period;

[0150] Substitute the preset load transfer rate into the fitting relationship to predict the average power generation amount for the control period corresponding to the preset load transfer rate of the regional integrated energy system.

[0151] In the best embodiment of the present invention, the average value of the power generation reference quantity for each control period corresponding to each load transfer rate of the regional integrated energy system is equal to the ratio of the sum of the power generation reference quantities at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system to the number of moments in the control period.

[0152] In a specific embodiment of the present invention, Figure 2 The energy network structure diagram of a certain regional integrated energy system is given. Based on the 12 different load transfer rates listed in Table 1 and Figure 3 the initial cooling, heating, and power load curve diagrams of a certain typical day of a certain regional integrated energy system shown, using the pre-constructed optimal scheduling model, solve to obtain the power generation / cooling / heating reference values at each moment of this region corresponding to a load transfer rate of 0 on this typical day, Figure 4 It can be seen from [reference] that the typical day can be divided into section G and section E according to the power generation reference values at each moment of the typical day.

[0153] Figure 5 [Reference] shows the iterative process when determining the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system. It can be seen that the larger the number of iterative steps, the smoother the iterative curve. After the number of iterative steps reaches a certain value, the iterative curve basically does not change;

[0154] Figure 6 [Reference] gives the average power generation amount (which can also be called the power generation technical level or power generation capacity), configuration ratio, and fitting curve diagrams under 12 different load transfer rate scenarios; the configuration ratio is the ratio of the maximum installed capacity at a specific load transfer rate to the maximum installed capacity at a load transfer rate of 0, and the expression of its fitting curve is:

[0155]

[0156] Among them, is the average power generation of a regional integrated energy system on a typical day, TR is the load transfer rate, and R 2 is the fitting accuracy.

[0157] Due to the delay and attenuation effects of heat and cold transmission, it is difficult to quantify the heat and cold responses of the demand side. Therefore, the heat and cold responses of the demand side are not considered in this method.

[0158] By processing the regional integrated energy system under 12 different load transfer rates, it is obtained that: 1) From the perspective of the initial energy configuration, as the load transfer rate increases, the configuration ratio decreases from point B to point A and then rises to point C. At point A, the regional integrated energy system has the minimum installed capacity. The installed capacity at point C is higher than the installed capacity before load transfer, which means that excessive load transfer will generate new peak power demands. 2) Among Figure 6 them, the load transfer situation above the black dotted line (original configuration line) will not have a positive impact on the reduction of initial investment. 3) From the perspective of operation, on the one hand, as the installed capacity of the regional integrated energy system decreases, when the load is low, the energy conversion efficiency will increase. Therefore, the power generation technology level will rise at this time. On the other hand, load transfer is to transfer electricity from the peak period of the large power grid to the valley period. This means that the power consumption in the valley period increases with the increase of the load transfer rate, which leads to the increase of the daily power generation technology level in the regional integrated energy system. In the figure

[0159] The technology levels of typical daily heat and cold production under different load transfer rates are as shown in Figure 7 (TR refers to the load transfer rate). As TR increases, the change in the technology level of refrigeration is very small, but the technology level of heating gradually decreases. The gradual decrease in the heating technology level is caused by the following progressive relationship: 1) Load transfer leads to an increase in power consumption in the valley period; 2) Therefore, the installed capacity and operation time of the CHP decrease; 3) This results in a reduction in the free heating provided by the CHP; 4) Finally, the heating technology level gradually decreases. Since the proportion of free cooling provided by the CHP in the total cooling is small, the change in the cooling technology level is small.

[0160] The present invention provides a system for predicting the average power generation of a regional integrated energy system, as shown in Figure 8 , the system includes:

[0161] A first determination module, configured to determine the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system according to the load demand at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system;

[0162] A prediction module, configured to predict the average power generation within the control period corresponding to the preset load transfer rate of the regional integrated energy system according to the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system.

[0163] Specifically, the system further includes an initial determination module for

[0164] determining the load transfer rate ω of the regional integrated energy system according to the following formula k the load demand at the i-th moment in the corresponding control period

[0165]

[0166] where P iy is the predicted load demand of the regional integrated energy system at the i-th moment in the control period, is the preset value of the demarcation point between the peak load demand period and the low load demand period of the load demand in the period to which the i-th moment in the control period belongs. When the i-th moment in the control period is in the peak load demand period of its belonging period, otherwise, the i-th moment in the control period is in the low load demand period of its belonging period, is the total number of moments in the peak load demand period within the period to which the i-th moment in the control period belongs, is the total number of moments in the low load demand period within the period to which the i-th moment in the control period belongs, is the moment set of the period to which the i-th moment in the control period belongs, i ∈ (1~ψ), ψ is the total number of moments in the control period, k ∈ (1~ζ), ζ is the total number of load transfer rates.

[0167] Specifically, the first determination module includes:

[0168] an initialization unit for initializing i = 1, s = 1;

[0169] an acquisition unit for, during the s-th iteration, taking the load demand at the i-th moment in the corresponding control period of the regional integrated energy system with the load transfer rate ω k and the production capacity reference quantity sequence at each moment in the corresponding control period of the regional integrated energy system with the load transfer rate ω k pre-stored in the dataset and substituting them into the pre-constructed optimal scheduling model to solve the optimal scheduling model and obtain the objective function value, production capacity reference quantity sequence and power generation reference quantity at the i-th moment in the corresponding control period of the regional integrated energy system with the load transfer rate ω k ;

[0170] a replacement unit for replacing the production capacity reference quantity sequence at the i-th moment in the corresponding control period of the regional integrated energy system with the load transfer rate ω k pre-stored in the dataset with the obtained production capacity reference quantity sequence at the i-th moment in the corresponding control period of the regional integrated energy system with the load transfer rate ω kThe production capacity reference quantity sequence at the \(i\)-th moment within the corresponding control period;

[0171] An output unit, which is used to, when \(i = \psi\), if the load transfer rate of the regional integrated energy system during the \(s\)-th iteration is \(\omega\) k and the sum value of the objective function values at each moment within the corresponding control period meets a preset termination condition, then output the load transfer rate \(\omega\) of the regional integrated energy system obtained during the \(s\)-th iteration k The electricity generation reference quantity at each moment within the corresponding control period; otherwise, let \(s = s + 1\), and return to step B; when \(i\neq\psi\), let \(i = i + 1\), and return to step B;

[0172] wherein, the production capacity reference quantity sequence is composed of the electricity generation reference quantity of each power generation device, the heat production reference quantity of each heat production device, and the cooling production reference quantity of each cooling production device in the regional integrated energy system, \(\psi\) is the total number of moments in the control period, \(k\in(1\sim\zeta)\), \(\zeta\) is the total number of load transfer rates, and the preset termination condition is the sum value of the objective function values at each moment within the corresponding control period for the load transfer rate \(\omega\) of the regional integrated energy system during the \(s\)-th iteration k the sum value of the objective function values at each moment within the corresponding control period, with the load transfer rate being \(\omega\) k when the load transfer rate is \(\omega\), the sum value of the objective function values at each moment within the control period of the regional integrated energy system the sum value of the objective function values at each moment within the corresponding control period for the load transfer rate \(\omega\) of the regional integrated energy system during the \((s - 1)\)-th iteration k \(\sigma_0\) is the iteration termination threshold, \(k\in(1\sim\zeta)\), and \(\zeta\) is the total number of load transfer rates.

[0173] Furthermore, determine the objective function of the pre-constructed optimal scheduling model according to the following formula:

[0174] F i \(=\min(f i,e +f i,c +f i,h )

[0175] In the formula, \(F i is the objective function value of the regional integrated energy system at the \(i\)-th moment in the control period, \(f i,e is the equivalent standard coal consumption for electricity generation of the regional integrated energy system at the \(i\)-th moment in the control period, \(f i,c is the equivalent standard coal consumption for cooling production of the regional integrated energy system at the \(t\)-th moment in the control period, \(f i,h is the equivalent standard coal consumption for heat production of the regional integrated energy system at the \(i\)-th moment in the control period;

[0176] wherein, determine the equivalent standard coal consumption \(f\) for electricity generation of the regional integrated energy system at the \(i\)-th moment in the control period according to the following formulai,e :

[0177]

[0178] In the formula, p r,b is the equivalent standard coal consumption of primary energy consumed for the production of unit electricity by the b-th power generation equipment in the regional integrated energy system, is the reference power generation quantity of the b-th power generation equipment in the regional integrated energy system at the i-th moment in the control period, is the power generation efficiency of the b-th power generation equipment in the regional integrated energy system, is the equivalent annual coefficient of the b-th power generation equipment in the regional integrated energy system, IV b is the fixed technical level of the b-th power generation equipment in the regional integrated energy system, is the reference power generation quantity of the b-th power generation equipment in the regional integrated energy system at the Σ-th moment in the control period pre-stored in the dataset, M t,b is the maintenance loss of the b-th power generation equipment in the regional integrated energy system, b ∈ (1 ~ S b ), S b is the total number of power generation equipment in the regional integrated energy system, i, Σ ∈ (1 ~ ψ), and ψ is the total number of moments in the control period;

[0179] The equivalent standard coal consumption for cooling f of the regional integrated energy system at the i-th moment in the control period is determined by the following formula i,c :

[0180]

[0181] In the formula, p r,q is the equivalent standard coal consumption of primary energy consumed for the production of unit energy by the q-th refrigeration equipment in the regional integrated energy system, is the reciprocal of the equivalent standard coal consumption corresponding to the reference power generation quantity at the i-th moment in the control period of the regional integrated energy system, is the reference cooling quantity of the q-th refrigeration equipment in the regional integrated energy system at the i-th moment in the control period, is the reference cooling quantity of the q-th refrigeration equipment by gas refrigeration at the i-th moment in the control period in the regional integrated energy system, is the gas refrigeration efficiency of the q-th refrigeration equipment in the regional integrated energy system, is the reference cooling quantity of the q-th refrigeration equipment by electric refrigeration at the i-th moment in the control period in the regional integrated energy system, is the electric refrigeration efficiency of the q-th refrigeration equipment in the regional integrated energy system, is the equivalent annual coefficient of the q-th refrigeration equipment in the regional integrated energy system, IV qis the fixed technical level of the q-th refrigeration device in the regional integrated energy system, M i,q is the maintenance loss of the q-th refrigeration device in the regional integrated energy system, is the pre-stored cooling production reference quantity of the q-th refrigeration device in the regional integrated energy system at the Σ-th moment within the control period, q ∈ (1~S q ), S q is the total number of refrigeration devices in the regional integrated energy system, Q i e is the power generation reference quantity of the regional integrated energy system at the i-th moment within the control period;

[0182] Determine the equivalent standard coal consumption f of heat production of the regional integrated energy system at the t-th moment within the control period according to the following formula t,h :

[0183]

[0184] In the formula, p r,j is the equivalent standard coal consumption of primary energy consumed by the j-th heating device in the regional integrated energy system to produce unit energy, is the heat production reference quantity of the j-th heating device in the regional integrated energy system at the i-th moment within the control period, is the heat production reference quantity of the j-th heating device in the regional integrated energy system by gas heating at the i-th moment within the control period, is the gas heating efficiency of the j-th heating device in the regional integrated energy system, is the heat production reference quantity of the j-th heating device in the regional integrated energy system by electric heating at the i-th moment within the control period, is the electric heating efficiency of the j-th heating device in the regional integrated energy system, is the equivalent annual coefficient of the j-th heating device in the regional integrated energy system, IV j is the fixed technical level of the j-th heating device in the regional integrated energy system, M i,j is the maintenance loss of the j-th heating device in the regional integrated energy system, is the pre-stored heat production reference quantity of the j-th heating device in the regional integrated energy system at the Σ-th moment within the control period, j ∈ (1~S j ), S j is the total number of heating devices in the regional integrated energy system.

[0185] Further, the constraint conditions of the objective function of the pre-constructed optimal scheduling model include: microgrid balance constraint conditions, micro-cooling network balance constraint conditions, micro-heating network balance constraint conditions, CHP generation equipment output constraint conditions, refrigeration unit output constraint conditions, and heating unit output constraint conditions.

[0186] Specifically, the prediction module includes:

[0187] A calculation unit, configured to calculate the average value of the power generation reference quantity of the control period corresponding to each load transfer rate of the regional integrated energy system according to the power generation reference quantity at each moment in the control period corresponding to each load transfer rate of the regional integrated energy system;

[0188] A fitting unit, configured to establish a fitting relationship between each load transfer rate of the regional integrated energy system and the average value of the power generation reference quantity of its corresponding control period by using the regression analysis method based on the average value of the power generation reference quantity of the control period corresponding to each load transfer rate of the regional integrated energy system;

[0189] A prediction unit, configured to substitute a preset load transfer rate into the fitting relationship to predict the average power generation amount of the control period corresponding to the preset load transfer rate of the regional integrated energy system.

[0190] The present invention further improves the planning and design of the regional integrated energy system. In particular, the game between the supply side and the demand side at the initial stage of energy allocation is introduced, making the planning result more valuable and significant in guiding, and making the design result more in line with engineering reality. In addition, the present invention improves the prediction accuracy of the average power generation prediction amount (power generation capacity) of the supply side in the control period, reduces the energy consumption of the demand side, and ensures the interconnection and unity of the park integrated energy system.

[0191] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0192] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or means for implementing the functions specified in one or more of the blocks.

[0193] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or means for implementing the functions specified in one or more of the blocks.

[0194] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and / or blocks Figure 1 or means for implementing the functions specified in one or more of the blocks.

[0195] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications or equivalent substitutions can still be made to the specific embodiments of the present invention, and any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered by the protection scope of the claims of the present invention.

Claims

1. A method for predicting the average power generation of a regional integrated energy system, characterized in that, The method includes: Determining the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system according to the load demand at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system; Predicting the average power generation quantity within the control period corresponding to the preset load transfer rate of the regional integrated energy system according to the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system; The determining the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system according to the load demand at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system includes: Step A: Initialize i = 1, s = 1; Step B: During the s-th iteration, the load transfer rate of the regional integrated energy system is ω k The load demand at the i-th moment within the corresponding control period and the pre-stored load transfer rate of the regional integrated energy system is ω k Substitute the production capacity reference quantity sequences at each moment within the corresponding control period into the pre-constructed optimal scheduling model, solve the optimal scheduling model, and obtain the load transfer rate of the regional integrated energy system as ω k The optimized production capacity reference quantity sequence, objective function value, and power generation reference quantity at the i-th moment within the corresponding control period; the production capacity reference quantity sequence includes the power generation reference quantity of each power generation device, the heat production reference quantity of each heat production device, and the cooling production reference quantity of each cooling production device in the regional integrated energy system; the load transfer rate of the regional integrated energy system is ω k The optimized power generation reference quantity at the i-th moment within the corresponding control period is the sum of the power generation reference quantities of each power generation device in the optimized production capacity reference quantity sequence at this moment; Step C: According to the load transfer rate of the regional integrated energy system being ω k The optimized production capacity reference quantity sequence at the i-th moment within the corresponding control period is used to update the pre-stored load transfer rate of the regional integrated energy system to be ω k The production capacity reference quantity sequence at the i-th moment within the corresponding control period; Step D: When i = ψ, if the load transfer rate of the regional integrated energy system during the s-th iteration is ω k and the sum of the objective function values at each moment within the corresponding control period satisfies the preset termination condition, then output the load transfer rate ω of the regional integrated energy system obtained during the s-th iteration k and the electricity generation reference quantity at each moment within the corresponding control period; otherwise, let s = s + 1, and return to Step B; when i ≠ ψ, let i = i + 1, and return to Step B; where ψ is the total number of moments in the control period, k ∈ (1~ζ), and ζ is the total number of load transfer rates; The preset termination condition is that the load transfer rate of the regional integrated energy system during the s-th iteration is ω k the sum of the objective function values at each moment within the corresponding control period, and the load transfer rate is ω k the sum of the objective function values at each moment within the control period of the regional integrated energy system when the load transfer rate of the regional integrated energy system during the (s - 1)-th iteration is ω k the sum of the objective function values at each moment within the corresponding control period, σ0 is the iteration termination threshold, k ∈ (1~ζ), and ζ is the total number of load transfer rates; The predicting the average power generation quantity within the control period corresponding to the preset load transfer rate of the regional integrated energy system according to the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system includes: Calculating the average value of the power generation reference quantity within the control period corresponding to each load transfer rate of the regional integrated energy system according to the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system; Based on the average value of the power generation reference quantity within the control period corresponding to each load transfer rate of the regional integrated energy system, establishing a fitting relationship between each load transfer rate of the regional integrated energy system and the average value of the power generation reference quantity within its corresponding control period by using the regression analysis method; Substituting the preset load transfer rate into the fitting relationship to predict the average power generation quantity within the control period corresponding to the preset load transfer rate of the regional integrated energy system.

2. The method according to claim 1, wherein Before the determining the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system according to the load demand at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system, it further includes: The load transfer rate ω of the regional integrated energy system is determined by the following formula k The load demand at the i-th moment during the corresponding control period Wherein, P iy is the predicted load demand of the regional integrated energy system at the i-th moment of the control period, is the preset value of the demarcation point between the peak load demand period and the low load demand period of the time period to which the regional integrated energy system belongs at the i-th moment of the control period. When , the i-th moment of the control period is in the peak load demand period of its affiliated time period; otherwise, the i-th moment of the control period is in the low load demand period of its affiliated time period. is the total number of moments in the peak load demand period within the time period to which the i-th moment of the control period belongs, is the total number of moments in the low load demand period within the time period to which the i-th moment of the control period belongs, is the set of moments of the time period to which the i-th moment of the control period belongs, i ∈ (1~ψ), ψ is the total number of moments of the control period, k ∈ (1~ζ), and ζ is the total number of load transfer rates.

3. The method according to claim 1, characterized in that, Determining the objective function of the pre-constructed optimal scheduling model according to the following formula: F i = min(f i,e + f i,c + f i,h ) where, F i is the objective function value of the regional integrated energy system at the i-th moment of the control period, and f i,e is the equivalent standard coal consumption for power generation of the regional integrated energy system at the i-th moment of the control period, and f i,c is the equivalent standard coal consumption for cooling of the regional integrated energy system at the t-th moment of the control period, and f i,h is the equivalent standard coal consumption for heat production of the regional integrated energy system at the i-th moment of the control period; Among them, the equivalent standard coal consumption f of the regional integrated energy system at the i-th moment of the control period is determined by the following formula i,e :[[]]END]] Where p r,b is the equivalent standard coal consumption of primary energy consumed by the b-th power generation equipment per unit of electricity produced in the regional integrated energy system, is the reference power generation quantity of the b-th power generation equipment in the regional integrated energy system at the i-th moment of the control period, is the power generation efficiency of the b-th power generation equipment in the regional integrated energy system, is the equivalent annual coefficient of the b-th power generation equipment in the regional integrated energy system, IV b is the fixed technical level of the b-th power generation equipment in the regional integrated energy system, is the reference power generation quantity of the b-th power generation equipment in the regional integrated energy system at the Σ-th moment during the control period pre-stored in the dataset, M t,b is the maintenance loss of the b-th power generation equipment in the regional integrated energy system, b ∈ (1~S b ), S b is the total number of power generation equipment in the regional integrated energy system, i, Σ ∈ (1~ψ), and ψ is the total number of moments in the control period; Determine the equivalent standard coal consumption f of cold production of the regional integrated energy system at the i-th moment of the control period according to the following formula i,c : where p r,q is the equivalent standard coal consumption of primary energy consumed per unit energy produced by the q-th refrigeration device in the regional integrated energy system, is the reciprocal of the equivalent standard coal consumption corresponding to the reference power generation amount of the regional integrated energy system at the i-th moment in the control period, is the reference cooling output of the q-th refrigeration device in the regional integrated energy system at the i-th moment in the control period, is the reference cooling output of the q-th refrigeration device by gas refrigeration at the i-th moment in the control period in the regional integrated energy system, is the gas refrigeration efficiency of the q-th refrigeration device in the regional integrated energy system, is the reference cooling output of the q-th refrigeration device by electric refrigeration at the i-th moment in the control period in the regional integrated energy system, is the electric refrigeration efficiency of the q-th refrigeration device in the regional integrated energy system, is the equivalent annual coefficient of the q-th refrigeration device in the regional integrated energy system, IV q is the fixed technical level of the q-th refrigeration device in the regional integrated energy system, M i,q is the maintenance loss of the q-th refrigeration device in the regional integrated energy system, is the reference cooling output of the q-th refrigeration device in the regional integrated energy system pre-stored in the dataset at the Σ-th moment in the control period, q ∈ (1~S q ), S q is the total number of refrigeration devices in the regional integrated energy system, is the reference power generation amount of the regional integrated energy system at the i-th moment in the control period; Determine the equivalent standard coal consumption f of heat production of the regional integrated energy system at the t-th moment of the control period according to the following formula t,h : Where p r,j is the equivalent standard coal consumption of primary energy consumed per unit energy produced by the j-th heating device in the regional integrated energy system, is the heat production reference quantity of the j-th heating device in the regional integrated energy system at the i-th moment of the control period, is the heat production reference quantity of the j-th heating device by gas heating at the i-th moment of the control period in the regional integrated energy system, is the gas heating efficiency of the j-th heating device in the regional integrated energy system, is the heat production reference quantity of the j-th heating device by electric heating at the i-th moment of the control period in the regional integrated energy system, is the electric heating efficiency of the j-th heating device in the regional integrated energy system, is the equivalent annual coefficient of the j-th heating device in the regional integrated energy system, IV j is the fixed technical level of the j-th heating device in the regional integrated energy system, M i,j is the maintenance loss of the j-th heating device in the regional integrated energy system, is the heat production reference quantity of the j-th heating device in the regional integrated energy system at the Σ-th moment during the control period pre-stored in the dataset, j ∈ (1~S j ), S j is the total number of heating devices in the regional integrated energy system.

4. The method according to claim 3, wherein The constraint conditions of the objective function of the pre-constructed optimal scheduling model include: microgrid balance constraint conditions, micro-cooling network balance constraint conditions, micro-heating network balance constraint conditions, CHP generation equipment output constraint conditions, refrigeration unit output constraint conditions, and heating unit output constraint conditions.

5. A prediction system for the average power generation of a regional integrated energy system, characterized in that, The system includes: A first determination module, configured to determine the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system according to the load demand at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system; A prediction module, configured to predict the average power generation quantity within the control period corresponding to the preset load transfer rate of the regional integrated energy system according to the power generation reference quantity at each moment within the control period corresponding to each load transfer rate of the regional integrated energy system; The first determination module includes: An initialization unit, configured to initialize i = 1, s = 1; An acquisition unit, configured to, during the s-th iteration, set the load transfer rate of the regional integrated energy system to ω k the load demand at the i-th moment within the corresponding control period and the pre-stored load transfer rate of the regional integrated energy system being ω k substitute the production capacity reference quantity sequences at each moment within the corresponding control period into the pre-constructed optimal scheduling model, solve the optimal scheduling model, and obtain the load transfer rate of the regional integrated energy system being ω k the optimized production capacity reference quantity sequence, objective function value, and power generation reference quantity at the i-th moment within the corresponding control period; the production capacity reference quantity sequence includes the power generation reference quantity of each power generation device, the heat production reference quantity of each heat production device, and the cooling production reference quantity of each cooling production device in the regional integrated energy system; the load transfer rate of the regional integrated energy system is ω k the optimized power generation reference quantity at the i-th moment within the corresponding control period is the sum of the power generation reference quantities of each power generation device in the optimized production capacity reference quantity sequence at this moment; An update unit, configured to update the pre-stored load transfer rate ω of the regional integrated energy system according to the optimized production capacity reference quantity sequence at the i-th moment within the corresponding control period when the load transfer rate of the regional integrated energy system is ω k k The optimized production capacity reference quantity sequence at the i-th moment within the corresponding control period;Update the pre-stored load transfer rate ω of the regional integrated energy system according to the production capacity reference quantity sequence at the i-th moment within the corresponding control period when the load transfer rate of the regional integrated energy system is ω An output unit, configured to, when i = ψ, if the load transfer rate of the regional integrated energy system during the s-th iteration is ω k and the sum value of the objective function values at each moment within the corresponding control period satisfies a preset termination condition, output the load transfer rate ω of the regional integrated energy system obtained during the s-th iteration k and the electricity generation reference quantity at each moment within the corresponding control period; otherwise, set s = s + 1 and return to step B; when i ≠ ψ, set i = i + 1 and return to step B; where ψ is the total number of moments in the control period, k ∈ (1~ζ), and ζ is the total number of load transfer rates; The preset termination condition is The load transfer rate of the regional integrated energy system during the s-th iteration is ω k The sum of the objective function values at each moment within the corresponding control period, with the load transfer rate being ω k The sum of the objective function values at each moment within the control period of the regional integrated energy system when The load transfer rate of the regional integrated energy system during the (s - 1)-th iteration is ω k The sum of the objective function values at each moment within the corresponding control period, σ0 is the iteration termination threshold, k ∈ (1 ~ ζ), and ζ is the total number of load transfer rates; The prediction module includes: A calculation unit, configured to calculate an average value of power generation reference amounts for control periods corresponding to respective load transfer rates of a regional integrated energy system according to the power generation reference amounts at respective moments within the control periods corresponding to the respective load transfer rates of the regional integrated energy system; A fitting unit, configured to establish a fitting relationship between respective load transfer rates of a regional integrated energy system and average values of power generation reference amounts for control periods corresponding thereto by using a regression analysis method based on the average values of power generation reference amounts for control periods corresponding to the respective load transfer rates of the regional integrated energy system; A prediction unit, configured to substitute a preset load transfer rate into the fitting relationship to predict an average power generation amount for a control period corresponding to the preset load transfer rate of the regional integrated energy system.

6. The system according to claim 5, wherein The system further includes an initial determination module, configured to The load transfer rate ω of the regional integrated energy system is determined by the following formula k The load demand at the i-th moment within the corresponding control period Wherein, P iy is the predicted load demand of the regional integrated energy system at the i-th moment of the control period, is the preset value of the demarcation point between the peak load demand period and the low load demand period of the time period to which the regional integrated energy system belongs at the i-th moment of the control period. When , the i-th moment of the control period is in the peak load demand period of its affiliated time period; otherwise, the i-th moment of the control period is in the low load demand period of its affiliated time period. is the total number of moments in the peak load demand period within the time period to which the i-th moment of the control period belongs, is the total number of moments in the low load demand period within the time period to which the i-th moment of the control period belongs, is the set of moments of the time period to which the i-th moment of the control period belongs, i ∈ (1~ψ), ψ is the total number of moments of the control period, k ∈ (1~ζ), and ζ is the total number of load transfer rates.

7. The system according to claim 5, characterized in that, determine an objective function of a pre-constructed optimal scheduling model according to the following formula: F i = min(f i,e + f i,c + f i,h ) where, F i is the objective function value of the regional integrated energy system at the i-th moment of the control period, and f i,e is the equivalent standard coal consumption for power generation of the regional integrated energy system at the i-th moment of the control period, and f i,c is the equivalent standard coal consumption for cooling of the regional integrated energy system at the t-th moment of the control period, and f i,h is the equivalent standard coal consumption for heat production of the regional integrated energy system at the i-th moment of the control period; Among them, the equivalent standard coal consumption \(f\) of power generation of the regional integrated energy system at the \(i\)-th moment of the control period is determined by the following formula i,e : where p r,b is the equivalent standard coal consumption of primary energy consumed by the b-th power generation device per unit of electricity produced in the regional integrated energy system, is the reference power generation quantity of the b-th power generation device in the regional integrated energy system at the i-th moment of the control period, is the power generation efficiency of the b-th power generation device in the regional integrated energy system, is the equivalent annual coefficient of the b-th power generation device in the regional integrated energy system, IV b is the fixed technical level of the b-th power generation device in the regional integrated energy system, is the reference power generation quantity of the b-th power generation device in the regional integrated energy system at the Σ-th moment during the control period pre-stored in the dataset, M t,b is the maintenance loss of the b-th power generation device in the regional integrated energy system, b ∈ (1~S b ), S b is the total number of power generation devices in the regional integrated energy system, i, Σ ∈ (1~ψ), and ψ is the total number of moments in the control period; Determine the equivalent standard coal consumption \(f\) of cooling production of the regional integrated energy system at the \(i\)-th moment of the control period according to the following formula i,c : where p r,q is the equivalent standard coal consumption of primary energy consumed per unit energy produced by the q-th refrigeration equipment in the regional integrated energy system, is the reciprocal of the equivalent standard coal consumption corresponding to the reference power generation amount of the regional integrated energy system at the i-th moment in the control period, is the reference cooling capacity of the q-th refrigeration equipment in the regional integrated energy system at the i-th moment in the control period, is the reference cooling capacity of the q-th refrigeration equipment by gas refrigeration at the i-th moment in the control period in the regional integrated energy system, is the gas refrigeration efficiency of the q-th refrigeration equipment in the regional integrated energy system, is the reference cooling capacity of the q-th refrigeration equipment by electric refrigeration at the i-th moment in the control period in the regional integrated energy system, is the electric refrigeration efficiency of the q-th refrigeration equipment in the regional integrated energy system, is the equivalent annual coefficient of the q-th refrigeration equipment in the regional integrated energy system, IV q is the fixed technical level of the q-th refrigeration equipment in the regional integrated energy system, M i,q is the maintenance loss of the q-th refrigeration equipment in the regional integrated energy system, is the reference cooling capacity of the q-th refrigeration equipment in the regional integrated energy system at the Σ-th moment in the control period pre-stored in the dataset, q ∈ (1~S q ), S q is the total number of refrigeration equipment in the regional integrated energy system, is the reference power generation amount of the regional integrated energy system at the i-th moment in the control period; Determine the equivalent standard coal consumption f of heat production of the regional integrated energy system at the t-th moment of the control period according to the following formula t,h : where p r,j is the equivalent standard coal consumption of primary energy consumed by the j-th heating device in the regional integrated energy system for producing unit energy, is the heat production reference quantity of the j-th heating device in the regional integrated energy system at the i-th moment of the control period, is the heat production reference quantity of the j-th heating device in the regional integrated energy system at the i-th moment of the control period by gas heating, is the gas heating efficiency of the j-th heating device in the regional integrated energy system, is the heat production reference quantity of the j-th heating device in the regional integrated energy system at the i-th moment of the control period by electric heating, is the electric heating efficiency of the j-th heating device in the regional integrated energy system, is the equivalent annual coefficient of the j-th heating device in the regional integrated energy system, IV j is the fixed technical level of the j-th heating device in the regional integrated energy system, M i,j is the maintenance loss of the j-th heating device in the regional integrated energy system, is the heat production reference quantity of the j-th heating device in the regional integrated energy system at the Σ-th moment in the control period pre-stored in the dataset, j ∈ (1~S j ), S j is the total number of heating devices in the regional integrated energy system.

8. The system according to claim 7, wherein Constraint conditions of the objective function of the pre-constructed optimal scheduling model include: a microgrid balance constraint condition, a micro-cooling network balance constraint condition, a micro-heating network balance constraint condition, a CHP power generation equipment output constraint condition, a refrigeration unit output constraint condition, and a heating unit output constraint condition.

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