Energy configuration capacity determination method and system for heterogeneous energy system based on decoupling surface

Abstract

The present application relates to the technical field of power system, especially to a kind of energy configuration constant volume method and system for heterogeneous energy system based on decoupling surface, comprising: according to the preset boundary condition, set the energy storage capacity and cold storage capacity of heterogeneous energy supply equipment, and the cold storage cost and benefit in the preset operation cycle are calculated to obtain;Obtain the electricity-cold heat supply-heat supply in the preset operation cycle, and the energy supply cost and benefit are calculated to obtain;According to the cold storage cost and benefit, the energy supply cost and benefit, the operation benefit in the preset operation cycle is obtained;According to the energy conversion coefficient, the energy carbon emission is calculated, and according to the energy carbon emission and operation benefit, the optimal benefit evaluation index is obtained.The present application realizes the energy configuration constant volume method of comprehensive various factors by decoupling the connection of various energy systems under the limitation of current energy price and various costs, has the advantages of guaranteeing energy supply reliability, reducing carbon emission, saving cost and the like.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power systems, and particularly relates to an energy configuration capacity determination method and system for a heterogeneous energy system based on decoupling surfaces. BACKGROUND

[0002] At present, the energy supply mode is gradually changing from large-scale centralized energy production and supply to user-end distributed multi-energy collaborative complementary mode, so as to reduce energy loss in the process of energy generation, transmission and distribution, and improve the overall energy utilization efficiency of the whole society. At the same time, as a key technology for multi-energy collaborative control, energy storage technology is also a supporting technology for full utilization of renewable energy, distributed energy and micro-grid fields. Its development and application have important significance for the construction and configuration of efficient, safe and green energy systems.

[0003] The heterogeneous energy system fully considers the interaction of cold, heat and electricity, and analyzes the mutual relationship between various energy supplies. In the southern region, due to the higher refrigeration operation efficiency and the intuitive dominant benefit in the whole cycle, how to adopt the capacity determination technology of the heterogeneous energy system can effectively improve the system energy efficiency, improve the green proportion of energy supply, and at the same time make the cost benefit optimal, which has strong practical significance.

[0004] In the current field of park comprehensive energy system planning involving multiple energy types, there is no relatively optimal capacity determination method after decoupling of energy supply configuration. The traditional energy capacity determination method is based on the actual or simulated overall system operation data, and analyzes the multi-energy operation and load matching. The disadvantages of this energy system supply capacity determination method based on operation mode mainly include two aspects of logic and condition change:

[0005] Logical aspect: the actual large-scale heterogeneous energy system has many energy types and a large number of users with different behavior characteristics and great uncertainty. The capacity determination method based on system operation mode mainly compares the cost and technology of various energy configurations. Since the listed operation modes are limited, it is impossible to compare them by exhaustion, and the complexity of calculation and analysis is increased. At the same time, in the evaluation of indicators, it is also difficult to clearly compare various factors of multiple schemes. From the logic of various energy configurations, there is no clear capacity determination logic and principle of combing. Based on the comparison under a certain specific operation condition, the logical argument is not very sufficient, the adaptability of the scheme is not strong, and the credibility of the capacity determination result is decreased.

[0006] The condition change is mainly caused by the capacity and calculation capability limitation of the operation mode, and the corresponding conditions cannot be listed endlessly by the energy system, and due to the uncertainty of the field environment and demand, the results and conclusions also have corresponding uncertainty, and a clear conclusion cannot be obtained, and under different boundary conditions, what kind of configuration and capacity setting principles cannot be given clear guiding principles, and the actual research on configuration and capacity setting brings great difficulty. SUMMARY

[0007] The purpose of the present application is to provide an energy configuration and capacity setting method and system for heterogeneous energy systems based on decoupling, so as to decouple the connection of various energy systems and comprehensively consider various factors to realize energy supply equipment configuration and capacity setting.

[0008] To solve the above technical problems, the present application provides an energy configuration and capacity setting method and system for heterogeneous energy systems based on decoupling.

[0009] In a first aspect, the present application provides an energy configuration and capacity setting method for heterogeneous energy systems based on decoupling, which comprises the following steps:

[0010] Obtain the energy conversion coefficient of the heterogeneous energy supply equipment and the energy use cost of each electricity price period within a preset operation period;

[0011] Set the energy storage capacity and cold storage capacity of the heterogeneous energy supply equipment according to the preset boundary conditions, and calculate the cold storage cost and benefit within the preset operation period according to the energy time-of-use price;

[0012] Obtain the electricity-cold-heat amount of power supply-cold supply-heat supply within the preset operation period, and calculate the energy supply cost and benefit according to the energy conversion coefficient and the energy use cost;

[0013] Obtain the operation benefit within the preset operation period according to the cold storage cost and benefit, the energy supply cost and benefit;

[0014] Calculate the energy carbon emission according to the energy conversion coefficient, and obtain the optimal benefit evaluation index according to the energy carbon emission and the operation benefit;

[0015] The energy storage capacity of the heterogeneous energy supply equipment corresponding to the optimal benefit evaluation index is taken as the optimal energy capacity setting result.

[0016] In a further embodiment, the step of obtaining the energy use cost of each electricity price period within the preset operation period comprises:

[0017] Obtain the energy time-of-use price curve and energy demand curve of the heterogeneous energy within the preset operation period;

[0018] According to the energy time-sharing price curve and the energy demand curve, an energy use cost of each electricity price period in a preset operation period is obtained;

[0019] The each electricity price period includes a peak electricity price period, a flat electricity price period, and a valley electricity price period.

[0020] In a further implementation, the step of obtaining the optimal benefit evaluation index according to the energy carbon emission and the operation benefit includes:

[0021] The operation benefit is quantified by using the energy carbon emission to obtain a total operation benefit value in the preset operation period;

[0022] The benefit evaluation index is calculated according to the total operation benefit value;

[0023] The benefit evaluation index is decoupled by using a decoupling algorithm, and the decoupled benefit evaluation index is screened by using a particle swarm algorithm to obtain the optimal benefit evaluation index.

[0024] In a further implementation, the benefit evaluation index includes an internal rate of return evaluation index, a net present value evaluation index, and an investment payback period evaluation index in the preset operation period.

[0025] In a further implementation, the step of screening the decoupled benefit evaluation index by using the particle swarm algorithm to obtain the optimal benefit evaluation index includes:

[0026] The benefit evaluation index is classified according to an energy supply type and an energy storage capacity of the heterogeneous energy supply equipment, and is divided into each population;

[0027] A particle swarm algorithm parameter and a constraint condition are set, and a particle swarm is initialized;

[0028] A fitness value of each particle is determined, the fitness value of each particle is compared with a population optimal fitness value, if the fitness value of the particle is less than the population optimal fitness value, different scene parameters are adjusted, if the population optimal fitness value is reached, a speed and a position thereof are updated;

[0029] A global optimal value particle position is found, and different population iterations are continuously calculated until the optimal benefit evaluation index is output when a particle swarm iteration number is satisfied.

[0030] In a further implementation, the constraint condition includes an investment amount constraint, a construction space constraint, and an energy demand and supply constraint.

[0031] In a further implementation, the preset boundary condition includes a maximum energy storage flow and a power of the heterogeneous energy supply equipment.

[0032] In a second aspect, the present application provides an energy configuration capacity-determination system for a heterogeneous energy system based on a decoupling surface, the system comprising:

[0033] An energy data collection module configured to obtain an energy conversion coefficient of the heterogeneous energy supply device and an energy use cost of each electricity price period within a preset operation period;

[0034] An energy cost calculation module configured to set an energy storage capacity and a cold storage capacity of the heterogeneous energy supply device according to a preset boundary condition, and to obtain a cold storage cost and a benefit within the preset operation period according to the energy time-of-use price; the energy cost calculation module is further configured to obtain an electricity-cold-heat amount of electricity supply-cold supply-heat supply within the preset operation period, and to obtain an energy supply cost and a benefit according to the energy conversion coefficient and the energy use cost;

[0035] An operation benefit determination module configured to obtain an operation benefit within the preset operation period according to the cold storage cost and the benefit, and the energy supply cost and the benefit;

[0036] An optimal capacity-determination determination module configured to obtain an energy carbon emission amount according to the energy conversion coefficient, and to obtain an optimal benefit evaluation index according to the energy carbon emission amount and the operation benefit; the optimal capacity-determination determination module is further configured to take an energy storage capacity of the heterogeneous energy supply device corresponding to the optimal benefit evaluation index as an optimal energy capacity-determination result.

[0037] In a third aspect, the present application further provides a computer device, comprising a processor and a memory, wherein the processor is connected to the memory, the memory is configured to store a computer program, and the processor is configured to execute the computer program stored in the memory, so that the computer device executes the steps of the above method.

[0038] In a fourth aspect, the present application further provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the above method.

[0039] This invention provides a decoupled approach to energy configuration and capacity determination for heterogeneous energy systems. Based on a pre-set energy storage capacity of the energy supply equipment and taking into account the energy demand in various time periods, the method calculates the energy cost required to supply the necessary cooling capacity within a preset operating cycle, taking into account real-time energy prices. Simultaneously, emissions are calculated and compared using a decoupled algorithm and a particle swarm optimization algorithm to obtain the optimal benefit evaluation index. This method integrates various factors to determine the energy equipment configuration and capacity. Compared with existing technologies, this method clearly and comprehensively reflects the balance between various energy supplies in terms of economics and carbon reduction under the latest policies, measures the comprehensive benefits of energy storage configuration schemes, achieves rational allocation of energy storage capacity in energy systems, improves the accuracy, reliability, and adaptability of energy storage capacity configuration in heterogeneous energy systems, and enhances the economics of energy storage in energy systems. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the energy configuration and capacity determination method for heterogeneous energy systems based on decoupling, provided in an embodiment of the present invention.

[0041] Figure 2 This is a schematic diagram of an energy configuration and capacity control system based on decoupling for heterogeneous energy systems provided in an embodiment of the present invention;

[0042] Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0043] The embodiments of the present invention are described in detail below with reference to the accompanying drawings. The embodiments are given for illustrative purposes only and should not be construed as limiting the present invention. The accompanying drawings are for reference and illustration only and do not constitute a limitation on the scope of patent protection of the present invention, because many changes can be made to the present invention without departing from the spirit and scope of the present invention.

[0044] refer to Figure 1 This invention provides a method for energy configuration and capacity determination of heterogeneous energy systems based on decoupling, such as... Figure 1 As shown, the method includes the following steps:

[0045] S1. Obtain the energy conversion coefficient of heterogeneous energy supply equipment and the energy usage cost for each electricity price period within the preset operating cycle.

[0046] Specifically, the embodiment collects the energy conversion coefficient of the heterogeneous energy supply device, the historical energy usage of the user and the latest energy time-of-use price curve in a preset operation period, obtains an energy demand curve according to the historical energy usage of the user, multiplies the energy demand in each electricity price period position by the energy time-of-use price based on the energy demand curve and the energy time-of-use price curve, integrates and sums the results of multiplication in each electricity price period position, and obtains the energy usage cost in each electricity price period in the preset operation period, wherein the electricity price periods include peak, flat and valley periods; and the preset operation period includes the whole life cycle of the device, that is, the time length experienced by the whole set of devices from being put into operation to being recycled.

[0047] It should be noted that the traditional energy consumption structure is gradually being replaced by a hybrid energy dominated by renewable energy, and the heterogeneous energy system is a comprehensive intelligent energy system that uniformly plans and dispatches various types of energy such as electricity, gas, heat and cold. Energy supply and users are gradually showing individualization and decentralization trends.

[0048] S2. Set the energy storage capacity and cold storage capacity of the heterogeneous energy supply device according to the preset boundary conditions, and calculate the cold storage cost and benefit in the preset operation period according to the energy time-of-use price.

[0049] The embodiment fully considers the role of energy storage and cold storage, sets the energy storage capacity and cold storage capacity of the heterogeneous energy supply device according to the preset boundary conditions, and calculates the cold storage cost and benefit by adjusting the energy time-of-use price; wherein the preset boundary conditions include the maximum energy storage flow and power of the heterogeneous energy supply device.

[0050] S3. Obtain the electricity, cold and heat of electricity supply-cold supply-heat supply in the preset operation period, and calculate the energy supply cost and benefit according to the energy conversion coefficient and the energy usage cost.

[0051] The embodiment calculates the electricity, cold and heat of electricity supply-cold supply-heat supply from the perspectives of electricity, cold and heat in the preset operation period, and calculates the energy supply cost and benefit by using the energy conversion coefficient and the energy usage cost, wherein the energy conversion coefficient is the energy input-output conversion value.

[0052] S4. Obtain the operation benefit in the preset operation period according to the cold storage cost and benefit and the energy supply cost and benefit.

[0053] For the assumed same energy supply device, the embodiment obtains the cold storage saving cost by subtracting the cold storage benchmark cost from the cold storage cost, obtains the energy supply saving cost by subtracting the energy supply benchmark cost from the energy supply cost, and obtains the operation benefit of the heterogeneous energy supply device with the preset energy storage capacity in the preset operation period according to the cold storage saving cost, the energy supply saving cost, the benefit and the operation benefit. In the embodiment, the benchmark cost refers to the basic price of non-time-sharing energy.

[0054] S5. Calculate the energy carbon emission according to the energy conversion coefficient, and obtain the optimal benefit evaluation index according to the energy carbon emission and the operation benefit.

[0055] In one embodiment, the step of obtaining the optimal benefit evaluation index according to the energy carbon emission and the operation benefit comprises:

[0056] Quantify the operation benefit by using the energy carbon emission to obtain the total operation benefit value in the preset operation period;

[0057] Calculate the benefit evaluation index according to the total operation benefit value;

[0058] Decouple the benefit evaluation index by using the decoupling algorithm, and select the decoupled benefit evaluation index by using the particle swarm algorithm to obtain the optimal benefit evaluation index.

[0059] In one embodiment, the step of selecting the decoupled benefit evaluation index by using the particle swarm algorithm to obtain the optimal benefit evaluation index comprises:

[0060] Classify the benefit evaluation index according to the energy supply type and the energy storage capacity of the heterogeneous energy supply device, and divide it into various populations;

[0061] Set the particle swarm algorithm parameters and the limit conditions, and initialize the particle swarm; in the embodiment, the particle swarm algorithm parameters include population size, speed, position, iteration number, local optimal index and global optimal index; the limit conditions include investment amount limit, construction space limit, energy demand and supply limit, which can be converted into three values representing the upper limit of the device capacity;

[0062] Determine the fitness value of each particle, compare the fitness value of each particle with the optimal fitness value of the population, if the fitness value of the particle is less than the optimal fitness value of the population, ensure the population diversity, then adjust the different scene parameters; if the optimal fitness value of the population is reached, update the speed and position;

[0063] Select a pair of comprehensive benefits represented by all particles, respectively perform the full-cycle comprehensive benefit index calculation step to calculate, and calculate the corresponding comprehensive index value at the same time;

[0064] Find the global optimal value particle position, and constantly iterate the calculation between different populations until the particle swarm iteration times are met, and output the optimal benefit evaluation index;

[0065] Output the total value of the running benefit corresponding to the optimal benefit evaluation index, and take it as the optimal running benefit total value under the set energy storage capacity of the heterogeneous energy supply device.

[0066] Specifically, according to the energy conversion coefficient, the carbon emission of primary energy is calculated by once and twice energy comprehensive analysis substitution, then the running benefit is quantified by using the energy carbon emission, and the cumulative sum is obtained, and the total value of the running benefit in the preset running period is obtained; the benefit evaluation index is calculated by a general financial evaluation calculation method, in this embodiment, the benefit evaluation index includes the internal rate of return evaluation index, the net present value evaluation index and the investment recovery period evaluation index in the preset running period.

[0067] For different energy supply and utilization device capacities, the corresponding benefit evaluation index is obtained through the above process, and the decoupling algorithm and the particle swarm algorithm are used to find the optimal energy storage capacity corresponding to the optimal benefit evaluation index as the optimal output result of this embodiment:

[0068] This embodiment considers the partially decoupled algorithm, and decomposes the related decoupling factors, such as the relationship between part of the cold storage scale and power, and the poor coupling of energy supply, such as part of the power transmission and distributed energy processing. In addition, in a large number of energy options, the particle swarm algorithm is used for calculation, and the optimal benefit evaluation index is output. The core idea of the particle swarm algorithm is to use the mutual influence of particles in the population to evolve iteratively. Since the effects of different particles are different, the evolution paths of the affected particles are also different, thereby deriving the optimal value.

[0069] The embodiment of the present application comprehensively considers the decoupled unit cost comparison of each energy in the calculation and configuration process, and the output result is intuitive and has strong operability in various comparison calculations, and serves as a basis for related capacity and preliminary work.

[0070] S6. Take the energy storage capacity of the heterogeneous energy supply device corresponding to the optimal benefit evaluation index as the optimal energy capacity result.

[0071] When calculating the economic benefit index, this embodiment starts from the whole life cycle operation, compares the benchmark scheme with the whole external input, considers the fuel input cost, initial investment cost, operation cost and maintenance cost, considers the energy storage (including cold storage) and the benefit of local energy supply energy conversion, and takes them as the main basis for scheme comparison.

[0072] The heterogeneous energy system involves a plurality of energy types, covers applications such as electricity, cold and heat, and has relatively many schemes. For a hypothetical capacity value, the conventional idea of time-by-time simulation, judgment and calculation needs exponential growth of the number of operations, and the embodiment of the present application effectively reduces the number of calculation cycles and greatly improves the calculation speed and algorithm running efficiency by using local decoupling. The embodiment is related to a plurality of schemes caused by the heterogeneous configuration of a plurality of devices and a plurality of energy structures. From the weighted comparison of comparison parameters, the number of comparison schemes and the amount of calculation are greatly reduced by using decoupling decomposition and particle swarm calculation, and an effective calculation and analysis method is provided for the capacity determination of the heterogeneous energy configuration. The cold, heat and electricity cooperative operation in the embodiment involves the related capacities of various cold storage, refrigeration and power system devices.

[0073] The embodiment provides an energy configuration capacity determination method for a heterogeneous energy system based on decoupling. The method realizes an energy device configuration capacity determination method that comprehensively considers various factors by decoupling the connection of various energy systems under the limitation of current energy prices and various costs. For a hypothetical energy supply and utilization device capacity, the energy configuration capacity determination method calculates the energy cost expenditure required for supplying the required cold storage amount in the preset operation period when the current hypothetical energy storage capacity device is configured, and simultaneously calculates the carbon emission amount and comprehensively compares them to obtain the optimal economic benefit brought by the energy device with the hypothetical capacity.

[0074] It should be noted that the size of the serial number of the above processes does not mean the execution order, and the execution order of the processes should be determined according to its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0075] In one embodiment, as shown in FIG. 1, Figure 2 The embodiment of the present application provides an energy configuration capacity determination system for a heterogeneous energy system based on decoupling, and the system comprises:

[0076] The energy data acquisition module 101 is configured to acquire the energy conversion coefficient of the heterogeneous energy supply device and the energy use cost of each electricity price period in the preset operation period.

[0077] The energy cost calculation module 102 is configured to set the energy storage capacity and the cold storage amount of the heterogeneous energy supply device according to the preset boundary condition, and calculate the cold storage cost and the benefit in the preset operation period according to the energy time-of-use price. The energy cost calculation module 102 is also configured to acquire the electricity-cold-heat amount of the power supply-cold supply-heat supply in the preset operation period, and calculate the energy supply cost and the benefit according to the energy conversion coefficient and the energy use cost.

[0078] The operation benefit determination module 103 is configured to obtain operation benefits in a preset operation period according to the cold storage cost and benefit and the energy supply cost and benefit.

[0079] The optimal capacity determination module 104 is configured to obtain energy carbon emissions according to the energy conversion coefficient, and obtain an optimal benefit evaluation index according to the energy carbon emissions and the operation benefits. The optimal capacity determination module 104 is further configured to take the energy storage capacity of the heterogeneous energy supply equipment corresponding to the optimal benefit evaluation index as an optimal energy capacity result.

[0080] The specific limitation of the energy configuration and capacity determination system for the heterogeneous energy system based on the decoupling surface can refer to the limitation of the energy configuration and capacity determination method for the heterogeneous energy system based on the decoupling surface, which will not be repeated here. Those skilled in the art can realize that the various modules and steps described in combination with the embodiments disclosed in the present application can be realized in hardware, software or both. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0081] The embodiment of the present application provides an energy configuration and capacity determination system for a heterogeneous energy system based on a decoupling surface. The system collects energy data through an energy data collection module. The energy cost calculation module and the operation benefit determination module take satisfying the energy demand of each time period as a premise, combine the energy time-sharing price, calculate the energy cost expenditure required for supplying the required cold storage capacity in the preset operation period when configuring the current assumed energy storage capacity, calculate the carbon emissions and perform comprehensive comparison to obtain the optimal economic benefit brought by the energy equipment with the assumed capacity. Compared with the prior art, the capacity determination system provided in the embodiment has the advantages of guaranteeing energy supply reliability, reducing carbon emissions, saving expenditure and improving economic efficiency.

[0082] Figure 3 The computer device provided in the embodiment of the present application includes a memory, a processor and a transceiver which are connected through a bus. The memory is used to store a set of computer program instructions and data, and can transmit the stored data to the processor. The processor can execute the program instructions stored in the memory to execute the steps of the above method.

[0083] The memory can include a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memory; the processor can be a central processing unit, a microprocessor, an application-specific integrated circuit, a programmable logic device, or a combination thereof. By way of example and not limitation, the programmable logic device can be a complex programmable logic device, a field programmable logic gate array, a general array logic, or any combination thereof.

[0084] In addition, the memory can be a physically independent unit, or can be integrated with the processor.

[0085] Those skilled in the art can understand that, Figure 3 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have the same component arrangement.

[0086] In one embodiment, the present embodiment provides a computer readable storage medium having a computer program stored thereon, and the computer program is executed by a processor to implement the steps of the above method.

[0087] The energy configuration and capacity determination method and system for a heterogeneous energy system based on a decoupling surface provided by the embodiment of the present application utilize a decoupling algorithm and a particle swarm algorithm to comprehensively compare benefit evaluation indexes, obtain optimal benefit evaluation indexes, and take the energy storage capacity of the heterogeneous energy supply equipment corresponding to the optimal benefit evaluation indexes as the optimal energy configuration and capacity determination result. The method clearly and comprehensively reflects the balance relationship between various energy supplies in terms of economy and carbon reduction under the latest policy, can be applied to the situation under the implementation of the latest electric power market policy, and can be derived and applied to other heterogeneous energy systems, electric cold and heat, and source network load storage and energy storage equipment capacity determination.

[0088] In the above embodiments, all or part of the methods can be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the methods can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transferred from one website, computer, server or data center to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line) or wireless (such as infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that includes one or more available media sets. The available media can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, an SSD), etc.

[0089] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing related hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments.

[0090] The above-mentioned embodiments only express several preferred embodiments of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the patent. It should be noted that for ordinary skilled in the art, without departing from the technical principles of the present application, a number of improvements and replacements can be made, which should be considered as the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the protection scope of the claims.

Claims

1. A method for energy configuration and capacity determination in heterogeneous energy systems based on decoupling, characterized in that, Includes the following steps: Obtain the energy conversion coefficient of heterogeneous energy supply equipment and the energy usage cost for each electricity price period within a preset operating cycle; the energy conversion coefficient is the energy input-output conversion value; The energy storage capacity and cold storage capacity of the heterogeneous energy supply equipment are set according to preset boundary conditions, and the cold storage cost and revenue within the preset operating cycle are calculated based on the preset boundary conditions and the time-of-use energy price. The preset boundary conditions include the maximum energy storage flow rate and power of the heterogeneous energy supply equipment. The system obtains the electrical, cooling, and heating quantities of the power supply, air conditioning supply, and heat supply within a preset operating cycle, and calculates the energy supply cost and revenue based on the energy conversion coefficient and energy usage cost. The operational efficiency within a preset operating cycle is obtained based on the aforementioned cold storage costs and benefits, and the aforementioned energy supply costs and benefits. Energy carbon emissions are calculated based on the energy conversion coefficient. Then, based on the energy carbon emissions and the operational benefits, a decoupling algorithm is used to separate the physical coupling relationship, generating a decoupled benefit evaluation index. Finally, under constraints of investment amount limitations, construction space limitations, and energy demand and supply limitations, a particle swarm optimization algorithm is used to iteratively solve for the globally optimal energy storage capacity, yielding the optimal benefit evaluation index. Separating the physical coupling relationship includes separating power transmission from distributed energy processing. The step of obtaining the optimal benefit evaluation index based on the energy carbon emissions and the operational efficiency includes: The operational benefits are quantified using the energy carbon emissions to obtain the total operational benefits over a preset operating period. Based on the total operational benefits, the benefit evaluation indicators are calculated. The benefit evaluation indicators are decoupled using a decoupling algorithm, and the optimal benefit evaluation indicators are obtained by screening the decoupled benefit evaluation indicators using a particle swarm optimization algorithm. The step of selecting the optimal benefit evaluation index by using the particle swarm optimization algorithm includes: The benefit evaluation indicators are classified into different groups based on the energy supply type and energy storage capacity of heterogeneous energy supply equipment. Set the particle swarm algorithm parameters and constraints, and initialize the particle swarm; Determine the fitness value of each particle, compare the fitness value of each particle with the optimal fitness value of the population, and if the fitness value of a particle is less than the optimal fitness value of the population, adjust the parameters of different scenarios; if the optimal fitness value of the population is reached, update its velocity and position. Find the position of the globally optimal particle, and continuously iterate the calculation among different populations until the number of particle swarm iterations is satisfied, then output the optimal benefit evaluation index. The energy storage capacity of the heterogeneous energy supply equipment corresponding to the optimal benefit evaluation index is taken as the optimal energy capacity result.

2. The energy configuration and capacity determination method for heterogeneous energy systems based on decoupling as described in claim 1, characterized in that, The steps for obtaining the energy usage cost for each electricity price period within the preset operating cycle include: Obtain the time-of-use price curve and energy demand curve of heterogeneous energy within a preset operating cycle; Based on the energy time-of-use price curve and the energy demand curve, obtain the energy usage cost for each electricity price period within the preset operating cycle; The electricity price periods mentioned above include peak, off-peak, and valley periods.

3. The energy configuration and capacity determination method for heterogeneous energy systems based on decoupling as described in claim 1, characterized in that: The benefit evaluation indicators include internal rate of return (IRR) evaluation indicators, net present value (NPV) evaluation indicators, and investment payback period evaluation indicators within a preset operating period.

4. The energy configuration and capacity determination method for heterogeneous energy systems based on decoupling as described in claim 1, characterized in that: The restrictions include limits on investment amount, construction space, and energy demand and supply.

5. A decoupling-based energy configuration and constant-capacity system for heterogeneous energy systems, characterized in that, The system includes: The energy data acquisition module is used to obtain the energy conversion coefficient of heterogeneous energy supply equipment and the energy usage cost of each electricity price period within a preset operating cycle; the energy conversion coefficient is the energy input-output conversion value; The energy cost calculation module is used to set the energy storage capacity and cold storage capacity of the heterogeneous energy supply equipment according to preset boundary conditions, and to calculate the cold storage cost and revenue within a preset operating cycle based on the preset boundary conditions and time-of-use energy prices; it is also used to obtain the electric, cold, and heat supply within the preset operating cycle, and to calculate the energy supply cost and revenue based on the energy conversion coefficient and energy usage cost; the preset boundary conditions include the maximum energy storage flow rate and power of the heterogeneous energy supply equipment; The operational efficiency determination module is used to obtain the operational efficiency within a preset operating cycle based on the cold storage cost and revenue, and the energy supply cost and revenue. The optimal capacity determination module is used to calculate the energy carbon emissions based on the energy conversion coefficient, and based on the energy carbon emissions and the operational benefits, to separate the physical coupling relationship using a decoupling algorithm, generating a decoupled benefit evaluation index. Then, using a particle swarm optimization algorithm under constraints of investment amount limits, construction space limits, and energy demand and supply limits, iteratively solves for the globally optimal energy storage capacity to obtain the optimal benefit evaluation index. Separating the physical coupling relationship includes separating power transmission from distributed energy processing. It is also used to take the energy storage capacity of the heterogeneous energy supply equipment corresponding to the optimal benefit evaluation index as the optimal energy capacity determination result. The step of obtaining the optimal benefit evaluation index based on the energy carbon emissions and the operational efficiency includes: The operational benefits are quantified using the energy carbon emissions to obtain the total operational benefits over a preset operating period. Based on the total operational benefits, the benefit evaluation indicators are calculated. The benefit evaluation indicators are decoupled using a decoupling algorithm, and the optimal benefit evaluation indicators are obtained by screening the decoupled benefit evaluation indicators using a particle swarm optimization algorithm. The step of selecting the optimal benefit evaluation index by using the particle swarm optimization algorithm includes: The benefit evaluation indicators are classified into different groups based on the energy supply type and energy storage capacity of heterogeneous energy supply equipment. Set the particle swarm algorithm parameters and constraints, and initialize the particle swarm; Determine the fitness value of each particle, compare the fitness value of each particle with the optimal fitness value of the population, and if the fitness value of a particle is less than the optimal fitness value of the population, adjust the parameters of different scenarios; if the optimal fitness value of the population is reached, update its velocity and position. Find the position of the globally optimal particle, and continuously iterate the calculation among different populations until the number of iterations of the particle swarm is satisfied, at which point the optimal benefit evaluation index is output.

6. A computer device, characterized in that: The device includes a processor and a memory, the processor being connected to the memory for storing computer programs, and the processor for executing the computer programs stored in the memory to cause the computer device to perform the method as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program that, when executed, implements the method as described in any one of claims 1 to 4.

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