Comprehensive energy system planning research method based on buried pipe cross-seasonal heat storage

Abstract

The invention relates to an integrated energy system planning research method based on buried pipe cross-seasonal heat storage. The method comprises the following steps: establishing a buried pipe model; based on the buried pipe model, establishing a wind-solar heat storage coordinated operation model; the method comprises the following steps: based on a wind-solar heat storage system operation model, considering equipment construction investment cost and production simulation cost of a target age limit at the same time, performing planning design for minimizing the total cost of the whole life cycle of the system, and establishing a comprehensive energy system planning model; decomposing the established integrated energy system planning model into a main problem and a sub-problem by adopting a Benders decomposition method, and solving the main problem and the sub-problem to obtain a plurality of candidate wind and light heat storage capacity ratios; the optimal wind-light heat storage capacity ratio meeting the load requirement and the green power direct supply ratio requirement is determined from the multiple candidate wind-light heat storage capacity ratios, so that the optimal capacity planning of the comprehensive energy system with long-time scale heat storage can be realized, and the utilization efficiency of new energy can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of distributed energy planning, and in particular to a research method for comprehensive energy system planning based on inter-seasonal heat storage in underground pipes. Background Art

[0002] Solar energy and wind energy have the characteristics of periodicity and time-varying. In order to ensure the stability of the power supply in the park, they also need to be equipped with energy storage systems. Reasonable optimization of the ratio of wind, solar and storage capacity is the basis for realizing the efficient utilization of new energy in the park power grid, in order to optimize the ratio of wind, solar and storage capacity and further reduce the power abandonment rate. According to the characteristics of wind and solar resources in various places, the installed capacity ratio of wind power and photovoltaic power generation is reasonably planned, and energy storage devices are configured to reduce the amount of wind and solar power abandoned, which has important practical significance in the development and utilization of new energy. At the same time, equipped with cross-season buried pipe heat storage, the excess electric energy can be stored in the buried pipe system in the form of heat energy through heat pumps. This active heat storage technology can break the rigid constraints of real-time balance between heat supply and heat load, improve the regulation capacity of the electric and thermal integrated energy system, and promote the consumption of renewable energy.

[0003] At present, photovoltaic and wind turbines are widely used in every region, and the output data of photovoltaic and wind turbines are not difficult to obtain. In order to consume new energy on a large scale, it is necessary to optimize the ratio of wind, solar and heat storage. The traditional integrated energy system planning method generally only considers short-term heat storage and focuses on the ratio of wind, solar and heat storage. The integrated energy system planning based on inter-seasonal underground pipe heat storage takes into account multiple parameters, which can reduce capital investment for the construction of distributed energy systems, reduce the rate of wind and solar power abandonment, realize large-scale consumption of green electricity, and meet the efficient use of new energy.

[0004] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In view of the above-mentioned shortcomings and deficiencies of the prior art, the present invention provides a comprehensive energy system planning research method based on inter-seasonal heat storage in underground pipes, which solves the technical problem of wind and solar heat storage capacity ratio in zero-carbon parks equipped with inter-seasonal energy storage and other similar long-term heat storage.

[0007] (II) Technical solution

[0008] In order to achieve the above object, the main technical solutions adopted by the present invention include:

[0009] In a first aspect, an embodiment of the present invention provides a research method for planning an integrated energy system based on inter-seasonal heat storage in underground pipes, including: establishing an underground pipe model; establishing a wind-solar-heat storage coordinated operation model based on the underground pipe model; based on the wind-solar-heat storage system operation model, considering both the equipment construction investment cost and the production simulation cost of the target years, planning and designing for minimizing the total cost of the entire life cycle of the system, and establishing an integrated energy system planning model; wherein the objective function of the integrated energy system planning model is to minimize the annual equivalent cost over the entire life cycle; using the Benders decomposition method to decompose the integrated energy system planning model into a main problem and sub-problems and solve them to obtain multiple candidate wind-solar-heat storage capacity ratios; determining the optimal wind-solar-heat storage capacity ratio that meets the load demand and the green electricity direct supply ratio requirements from the multiple candidate wind-solar-heat storage capacity ratios.

[0010] In a possible embodiment, the buried pipe model is used to obtain the soil temperature of the buried pipe; the expression of the soil temperature is:

[0011]

[0012] In the formula, r represents the radius of the buried pipe; τ represents time; T(r, τ) represents the soil temperature at radius r at time τ; T0 represents the initial soil temperature; q l Represents the energy input to the buried pipe; s represents the thermal physical parameters of the first buried pipe; α s Represents the thermal physical parameters of the second buried pipe.

[0013] In a possible embodiment, the buried pipe model is further used to determine the temperature relationship between the inlet and outlet of the fluid; the expression of the temperature relationship is:

[0014]

[0015] Where, T f,out (τ) represents the outlet temperature of the fluid at time τ; T f,in (τ) represents the inlet temperature of the fluid at time τ; T b (τ) represents the wall temperature of the buried pipe at time τ; λ represents the heat transfer coefficient between the buried pipe and the soil; H is the drilling depth; c f represents the specific heat capacity of the heat transfer fluid; m f Represents the heat transfer fluid mass flow rate.

[0016] In one possible embodiment, the wind, solar, and heat storage coordinated operation model includes the power and operation constraints of the heat pump;

[0017] The expression of the electric heating / cooling conversion constraint of the heat pump system is:

[0018]

[0019] In the formula, Indicates the real-time heating capacity of the heat pump system; COPh indicates the heating coefficient of the heat pump system; represents the heating power of the heat pump system at time τ; It indicates the real-time cooling capacity of the heat pump system; COPc indicates the cooling coefficient of the heat pump system; represents the cooling power of the heat pump system at time τ;

[0020] And, the expression of the power constraint of the heat pump system is:

[0021]

[0022] Where P HP,min Indicates the minimum operating power of the heat pump system; Represents the power of the heat pump system at time τ; P HP,max Indicates the maximum operating power of the heat pump system.

[0023] In a possible embodiment, the wind-solar-thermal energy storage coordinated operation model further includes a constraint model of the buried pipe;

[0024] Among them, the constraint model of buried pipes includes:

[0025] The expression for maintaining balance between the extraction amount and heat injection amount of the buried pipe is:

[0026]

[0027] Where, IS represents the start time of heat injection; IE represents the end time of heat injection; represents the heat injection amount of the buried pipe at time τ; represents the amount of heat loss at time τ; represents the amount of heat supplement at time τ; ES represents the start time of heat extraction; EE represents the end time of heat extraction; represents the heat extraction of the buried pipe at time τ;

[0028] And, the expressions of heat injection and heat extraction of buried pipes are:

[0029]

[0030] And, the expressions for the constraints of heat injection and heat extraction of the buried pipe are:

[0031]

[0032] In the formula, n represents the total number of underground pipes; m f,irepresents the mass flow rate of the ith underground pipe; c f represents the specific heat capacity of the heat transfer fluid; T f,i,in (τ) represents the inlet temperature of the fluid in the i-th underground pipe at time τ; T f,i,out (τ) represents the outlet temperature of the fluid in the i-th buried pipe at time τ.

[0033] In a possible embodiment, the objective function is expressed as:

[0034] minF=C inv +C opt +C ST +C EA ;

[0035] In the formula, F represents the objective function value; C inv Represents the annual equivalent investment cost of equipment; C opt represents the annual equivalent operation and maintenance cost; C ST represents the penalty for hot and cold production deviation; C EA It means the punishment for abandoning wind and light;

[0036] And, C inv The expression is:

[0037]

[0038] In the formula, c inv,j represents the unit capacity investment cost of the jth equipment; E j represents the planned capacity of the jth type of equipment; r represents the radius of the buried pipe; m represents the planned life of the system in years; WT represents wind power; PV represents photovoltaic power; BS represents energy storage power station; HP represents heat pump; BT represents buried pipe;

[0039] And, C opt , C ST and C EA The expression is:

[0040]

[0041] In the formula, λ opt,j Represents the unit power operation and maintenance cost coefficient of the equipment; P j τ Indicates the real-time operating power of the device; PE represents the additional cost of purchasing electricity; represents the power purchased from the large power grid at time τ; λ EA Indicates the unit cost of wind and solar power abandonment; Indicates the wind and solar power absorbed by the system in real time; Represents the actual real-time wind and solar power generation power based on wind and solar resources; Hrepresents the unit penalty cost of the heating load deviating from the demand curve; ES represents the start time of heat extraction; EE represents the end time of heat extraction; Indicates the real-time heating capacity of the heat pump system; Q HP,h represents the planned heating capacity of the heat pump system; C represents the unit penalty cost of the cooling load deviating from the demand curve; IS represents the start time of heat injection; IE represents the end time of heat injection; Indicates the real-time cooling capacity of the heat pump system; Q HP,c Indicates the planned cooling capacity of the heat pump system.

[0042] In one possible embodiment, the constraints of the integrated energy system planning model include planning constraints;

[0043] The expression of planning constraints is:

[0044] E j ≥0;

[0045] In the formula, E j Represents the planned capacity of the j-th type of equipment.

[0046] In a possible embodiment, the constraints of the integrated energy system planning model further include operation constraints, and the operation constraints include respectively establishing a system power balance equation and a heat balance equation, and determining actual grid-connected power constraints of wind power and photovoltaic power generation units, and interactive power constraints with the large power grid without considering the grid connection of surplus power;

[0047] Among them, the expressions of the system power balance equation and heat balance equation are:

[0048]

[0049] In the formula, represents the power generation of the photovoltaic unit at time τ; represents the power generated by the wind turbine at time τ; represents the energy release power of the energy storage power station at time τ; represents the power purchased from the large power grid at time τ; represents the energy storage power of the energy storage power station at time τ; represents the heat pump system power at time τ; represents the power consumption of the underground pipe heat storage system at time τ; represents the airport power load at time τ; represents the heating power of the heat pump system at time τ; represents the heat extraction of the buried pipe at time τ; represents the heat load of the airport at time τ; represents the cooling power of the heat pump system at time τ; represents the heat injection amount of the buried pipe at time τ; represents the cooling load of the airport at time τ.

[0050] In a possible embodiment, the constraints of the integrated energy system planning model further include planning-operation coupling constraints;

[0051] Among them, the expression of planning and operation coupling constraint is:

[0052]

[0053] In the formula, μ ES.min Indicates the minimum depth of charge and discharge of the energy storage device; E ES Represents the installed capacity of the energy storage power station; S OC,min Indicates the lower limit of the state of charge of the energy storage device; μ ES.max Indicates the maximum depth of charge and discharge of the energy storage device; S OC,max Indicates the upper limit of the charge state of the energy storage device.

[0054] In a second aspect, an embodiment of the present application provides a storage medium having a computer program stored thereon, and the computer program is executed by a processor to execute the method described in the first aspect or any optional implementation of the first aspect.

[0055] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the method described in the first aspect or any optional implementation method of the first aspect is performed.

[0056] In a fourth aspect, the present application provides a computer program product, which, when running on a computer, enables the computer to execute the method in the first aspect or any possible implementation of the first aspect.

[0057] (III) Beneficial effects

[0058] The beneficial effects of the present invention are:

[0059] The present application provides a research method for planning an integrated energy system based on inter-seasonal heat storage in underground pipes. An underground pipe model is established, and based on the underground pipe model, a wind-solar heat storage coordinated operation model is established, and based on the wind-solar heat storage system operation model, the equipment construction investment cost and the production simulation cost of the target years are considered at the same time, and planning and design are carried out for minimizing the total cost of the entire life cycle of the system, and an integrated energy system planning model is established, wherein the objective function of the integrated energy system planning model is to minimize the annual equivalent cost of the entire life cycle, and the Benders decomposition method is used to decompose the establishment of the integrated energy system planning model into a main problem and a sub-problem and solve them, and multiple candidate wind-solar heat storage capacity ratios are obtained, and the optimal wind-solar heat storage capacity ratio that meets the load demand and the green electricity direct supply ratio requirements is determined from the multiple candidate wind-solar heat storage capacity ratios, so as to establish an inter-seasonal underground pipe model that fits the power system, and combine the historical wind power generation and photovoltaic power generation data of typical days in the application site, The capacity ratio of the wind-solar heat storage system on the power generation side is calculated, which is used to determine the supply plan of zero-carbon energy in the zero-carbon park.

[0060] In addition, this method takes into account the cross-seasonal heat storage system and establishes an underground pipe model that conforms to the power system planning. The planning and solving requires little computational effort, and can achieve the optimal capacity planning of an integrated energy system equipped with long-term heat storage, and can effectively improve the utilization efficiency of new energy.

[0061] In order to make the above-mentioned objectives, features and advantages to be achieved by the embodiments of the present application more obvious and understandable, the following specifically cites preferred embodiments and describes them in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0063] Figure 1 A flow chart of a method for studying integrated energy system planning based on inter-seasonal heat storage in underground pipes provided in an embodiment of the present application is shown;

[0064] Figure 2 A specific flow chart of step S140 in a method for studying planning of an integrated energy system based on inter-seasonal heat storage in underground pipes provided in an embodiment of the present application is shown;

[0065] Figure 3A specific flow chart of step S150 in a method for studying integrated energy system planning based on inter-seasonal heat storage in underground pipes provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0066] In order to better explain the present invention and facilitate understanding, the present invention is described in detail below through specific implementation modes in conjunction with the accompanying drawings.

[0067] In order to solve the problem of wind-solar heat storage capacity ratio in zero-carbon parks equipped with cross-seasonal energy storage and other similar long-term heat storage existing in the prior art, the present application provides a comprehensive energy system planning research method based on underground pipe cross-seasonal heat storage, by establishing an underground pipe model, and based on the buried pipe model, establishing a wind-solar heat storage coordinated operation model, and based on the wind-solar heat storage system operation model, while considering the equipment construction investment cost and the production simulation cost of the target years, planning and design are carried out with the minimum total cost of the system throughout its life cycle, and a comprehensive energy system planning model is established, wherein the goal of the comprehensive energy system planning model is The function minimizes the annual equivalent cost over the entire life cycle, and uses the Benders decomposition method to decompose the establishment of the comprehensive energy system planning model into a main problem and sub-problems and solve them, thereby obtaining multiple candidate wind-solar-heat storage capacity ratios, and determining the optimal wind-solar-heat storage capacity ratio that meets the load demand and the green electricity direct supply ratio requirements from the multiple candidate wind-solar-heat storage capacity ratios. By establishing a cross-seasonal buried pipe model that fits the power system, combined with the historical wind power generation and photovoltaic power generation data of typical days in the application area, the capacity ratio of the wind-solar-heat storage system on the power generation side is calculated, which is used to determine the supply plan of zero-carbon energy in the zero-carbon park.

[0068] It should be understood that the name of the present application can also be referred to as a research method for capacity ratio planning of wind-solar heat storage systems in integrated energy systems based on underground pipe inter-seasonal heat storage systems.

[0069] In order to better understand the above technical solution, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to enable a clearer and more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0070] See also Figure 1 , Figure 1The flowchart of a method for studying the planning of an integrated energy system based on inter-seasonal heat storage in underground pipes provided in an embodiment of the present application is shown. It should be understood that the method for studying the planning of an integrated energy system can be executed by an electronic device, and the specific device of the electronic device can be set according to actual needs, and the embodiment of the present application is not limited thereto. Specifically, the electronic device can be a computer or a server. Specifically, the method for studying the planning of an integrated energy system includes:

[0071] Step S110, establishing a buried pipe model;

[0072] Step S120, establishing a wind-solar-heat storage coordinated operation model based on the buried pipe model;

[0073] Step S130, based on the wind-solar-heat storage system operation model, taking into account the equipment construction investment cost and the production simulation cost of the target years, planning and designing for minimizing the total cost of the system throughout its life cycle, and establishing a comprehensive energy system planning model; wherein the objective function of the comprehensive energy system planning model is to minimize the annual equivalent cost of the entire life cycle;

[0074] Step S140, using the Benders decomposition method to decompose the integrated energy system planning model into a main problem and sub-problems and solve them to obtain multiple candidate wind-solar-heat storage capacity ratios;

[0075] Step S150, determining the optimal wind-solar-heat storage capacity ratio that meets the load demand and the green electricity direct supply ratio requirements from multiple candidate wind-solar-heat storage capacity ratios.

[0076] Optionally, the buried pipe model in step S110 is established as follows:

[0077] As a planning prediction model, soil temperature prediction can be calculated and solved by simplifying the buried pipe model as a one-dimensional non-steady-state process. The soil temperature can be obtained by the Fourier heat conduction equation and the initial and boundary conditions:

[0078]

[0079] In the formula, r represents the radius of the buried pipe; τ represents time; T(r, τ) represents the soil temperature at radius r at time τ; T0 represents the initial soil temperature; q l Represents the energy input to the buried pipe; s represents the thermal physical parameters of the first buried pipe; α s Represents the thermal physical parameters of the second buried pipe.

[0080] In addition, this application focuses on the overall optimization planning of distributed multi-energy systems. The buried pipe can be equivalent to an equivalent pipe, and the thermal short circuit problem of the pipe pin is considered. The buried pipe wall temperature T bIt is considered as the condition of constant wall temperature. According to the law of energy conservation, the temperature relationship between the inlet and outlet of the fluid can be obtained as:

[0081]

[0082] Where, T f,out (τ) represents the outlet temperature of the fluid at time τ; T f,in (τ) represents the inlet temperature of the fluid at time τ; T b (τ) represents the wall temperature of the buried pipe at time τ; λ represents the heat transfer coefficient between the buried pipe and the soil, which is related to the size of the buried pipe, the properties of the fluid, the properties of the backfill material, etc.; H is the drilling depth; c f represents the specific heat capacity of the heat transfer fluid; m f Represents the heat transfer fluid mass flow rate.

[0083] Optionally, the wind-solar-heat storage coordinated operation model in step S120 mainly includes the power and operation constraints of the heat pump and the underground pipe. The specific constraints are as follows:

[0084] The following are the electric heating / cooling conversion constraints for the heat pump system:

[0085]

[0086] In the formula, Indicates the real-time heating capacity of the heat pump system; COPh indicates the heating coefficient of the heat pump system; represents the heating power of the heat pump system at time τ; It indicates the real-time cooling capacity of the heat pump system; COPc indicates the cooling coefficient of the heat pump system; represents the cooling power of the heat pump system at time τ;

[0087] And, the power constraint of the heat pump system is as follows:

[0088]

[0089] Where P HP,min Indicates the minimum operating power of the heat pump system; Represents the power of the heat pump system at time τ; P HP,max Indicates the maximum operating power of the heat pump system.

[0090] And, the buried pipe can be divided into two processes, heat extraction and heat injection. In order to maintain the energy balance of the underground space, the heat extraction amount and the heat injection amount should be balanced, so the expression is as follows:

[0091]

[0092] Where IS represents the start time of heat injection (summer cooling time); IE represents the end time of heat injection (summer cooling time); represents the heat injection amount of the buried pipe at time τ; represents the amount of heat loss at time τ; represents the amount of heat added at time τ; ES represents the start time of heat extraction (winter heating time); EE represents the end time of heat extraction (winter heating time); represents the heat extraction of the buried pipe at time τ.

[0093] And, the expressions of heat injection and heat extraction of buried pipes are:

[0094]

[0095] It should be understood that the heat extraction amount can also be referred to as the heat extraction amount, etc.

[0096] Furthermore, the heat storage and heat extraction of the buried pipe at time τ can be constrained by the fluid temperature and soil temperature as follows:

[0097]

[0098] In the formula, n represents the total number of underground pipes; m f,i represents the mass flow rate of the ith underground pipe; c f represents the specific heat capacity of the heat transfer fluid; T f,i,in (τ) represents the inlet temperature of the fluid in the i-th underground pipe at time τ; T f,i,out (τ) represents the outlet temperature of the fluid in the i-th buried pipe at time τ.

[0099] Optionally, the integrated energy system planning model in step S130 is a model constructed based on the objective function solution problem of minimum investment and operating cost, and the objective function is determined as follows:

[0100] Based on the buried pipe model, a wind-solar-heat storage system operation planning model is established, which takes into account both the equipment construction investment cost and the production simulation cost of the target years, and plans and designs the system to minimize the total cost of the entire life cycle. In addition, the objective function of the comprehensive energy system planning model is to minimize the annual equivalent cost of the entire life cycle, including the annual equivalent investment cost of the equipment C inv , annual equal operation and maintenance cost C opt , Penalty for abandoning wind and solar power C EA And the penalty C for hot and cold production deviation ST , as shown below:

[0101] minF=C inv +C opt +C ST +CEA ;

[0102] Equipment annual equivalent investment cost C inv Taking into account the equipment discount rate, it can be calculated by the following formula:

[0103]

[0104] In the formula, c inv,j represents the unit capacity investment cost of the j-th equipment, and the j-th equipment can be one of wind power, photovoltaic, energy storage power station, heat pump and buried pipe; E j represents the planned capacity of the jth type of equipment; r represents the radius of the buried pipe; m represents the planned life of the system in years; WT represents wind power; PV represents photovoltaic power; BS represents energy storage power station; HP represents heat pump; and BT represents buried pipe.

[0105] And, annual equivalent operation and maintenance cost C opt , Penalty for abandoning wind and solar power C EA And the penalty C for hot and cold production deviation ST , it can be obtained by the following formula:

[0106]

[0107] In the formula, λ opt,j Represents the unit power operation and maintenance cost coefficient of the equipment; P j τ Indicates the real-time operating power of the device; PE represents the additional cost of purchasing electricity; represents the power purchased from the large power grid at time τ; λ EA Indicates the unit cost of wind and solar power abandonment; Indicates the wind and solar power absorbed by the system in real time; Represents the actual real-time wind and solar power generation power based on wind and solar resources; H represents the unit penalty cost of the heating load deviating from the demand curve; ES represents the start time of heat extraction; EE represents the end time of heat extraction; Indicates the real-time heating capacity of the heat pump system; Q HP,h represents the planned heating capacity of the heat pump system; C represents the unit penalty cost of the cooling load deviating from the demand curve; IS represents the start time of heat injection; IE represents the end time of heat injection; Indicates the real-time cooling capacity of the heat pump system; Q HP,c Indicates the planned cooling capacity of the heat pump system.

[0108] It should be noted here that the 8760 mentioned above represents 8760 hours in a year.

[0109] Furthermore, the objective function of the integrated energy system planning model in step S130 mainly includes planning constraints, operation constraints and planning-operation coupling constraints.

[0110] Among them, planning constraints are used to represent the planning capacity constraints of various types of equipment in the system, as shown in the following formula:

[0111] E j ≥0;

[0112] In the formula, E j Represents the planned capacity of the j-th equipment.

[0113] And, the operation constraints are oriented to the system production simulation. First, the system power balance equation and heat balance equation are established respectively as shown in the following equations:

[0114]

[0115] In the formula, represents the power generation of the photovoltaic unit at time τ; represents the power generated by the wind turbine at time τ; represents the energy release power of the energy storage power station at time τ; represents the power purchased from the large power grid at time τ; represents the energy storage power of the energy storage power station at time τ; represents the heat pump system power at time τ; represents the power consumption of the underground pipe heat storage system at time τ; represents the airport power load at time τ; represents the heating power of the heat pump system at time τ; represents the heat extraction of the buried pipe at time τ; represents the heat load of the airport at time τ; represents the cooling power of the heat pump system at time τ; represents the heat injection amount of the buried pipe at time τ; represents the cooling load of the airport at time τ.

[0116] Furthermore, the capacity and power constraints of wind power and photovoltaic units are expressed as shown in the following formula, which means that the expected power generation of wind power and photovoltaic units is subject to the annual wind and solar resource constraints in the production simulation, as follows:

[0117]

[0118] In the formula, represents the power generation of the wind turbine at time τ; It represents the maximum power generation of unit capacity wind power in 8760h during the production simulation; represents the installed capacity of wind power; represents the power generation power of the photovoltaic unit at time τ; It represents the maximum power generation of the photovoltaic unit during 8760 hours of production simulation; Indicates the installed capacity of the photovoltaic system.

[0119] And the actual grid-connected power constraints of wind power and photovoltaic generators:

[0120]

[0121] In the formula, represents the expected power generation of photovoltaic at time τ; Represents the expected power generation of the wind turbine at time τ.

[0122] And, without considering the surplus power grid connection, the interaction power constraint with the large power grid is:

[0123]

[0124] Where P PE，min Indicates the lower limit of the interactive electric power between the system and the large power grid; P PE，max Indicates the upper limit of the interactive electric power between the system and the large power grid.

[0125] In addition, the coupling constraints between planning and operation are mainly the charge and discharge depth constraints of the equipment capacity of the energy storage equipment and the system charge state during operation, as shown in the following formula:

[0126]

[0127] In the formula, μ ES.min Indicates the minimum depth of charge and discharge of the energy storage device; E ES Represents the installed capacity of the energy storage power station; S OC,min Indicates the lower limit of the state of charge of the energy storage device; μ ES.max Indicates the maximum depth of charge and discharge of the energy storage device; S OC,max Indicates the upper limit of the state of charge of the energy storage device.

[0128] Optionally, for step S140, Figure 2 As shown, the decision variables include equipment capacity variables, represented by x, including wind power and photovoltaic unit capacity, battery energy storage system capacity, heat pump system capacity, and buried pipe system capacity. Another type of variable is the equipment operation status variable, represented by y, including the real-time operating power variables of the above equipment, the real-time output upper limit of wind and solar units, and the real-time SOC status of energy storage equipment. Constraints can be divided into three categories, including only x or y, or both x and y. The compact mode of the planning operation model proposed by the upper bound can be expressed as shown below:

[0129]

[0130] Where b T The coefficient vector representing the equipment capacity in the planning problem; c T represents the coefficient vector of the equipment operating status in the planning problem; A represents the constraint matrix of equipment capacity; a represents the constraint conditions of equipment capacity; B represents the equipment capacity matrix containing both capacity and operating status constraints; C represents the equipment operating status matrix containing both capacity and operating status constraints; M represents the constraint conditions containing both capacity and operating status; D represents the constraint matrix of equipment operating status; d represents the constraint conditions of equipment operating status.

[0131] It should be noted that the full name of "st" in the above formula is subject to, which represents the commonly used symbol in solving the optimization problem, or it can be understood as representing the constraint condition. Correspondingly, the "st" appearing elsewhere in this application is similar and will not be explained one by one. For details, please refer to the relevant description of this paragraph.

[0132] In order to solve the problem of difficulty in solving the planning problem caused by the solution ideas and the number of variables, this application adopts the solution ideas of Benders decomposition method, using the main problem to represent the equipment capacity solution problem, and the sub-problem to represent the production simulation operation optimization problem under known capacity conditions. In view of the large number of sub-problem variables at the operation level, a model decomposition method is adopted to decompose the operation sub-problems month by month by setting common variables to balance the number of sub-problems and the difficulty of solving a single sub-problem. Finally, the original planning problem is modeled as a two-level planning model containing a main problem and multiple sub-problems for solution.

[0133] In this example, there are timing operation constraints between the multiple sub-problems decomposed for 8760h, including the climbing constraints of each device between adjacent moments and the SOC constraints of the energy storage device. Each operation sub-problem cannot be directly calculated independently. Therefore, a small number of operation variables y1 are introduced into the main problem model to represent the operation variables at the first operation moment in each sub-problem, and relevant constraints are supplemented to realize the introduction of timing constraints for each sub-task, so that the two-layer model can reflect the original model.

[0134]

[0135] In the formula, Represents the coefficient vector of the equipment introducing the operating state in the planning problem; η represents the state constraint; C1 represents the equipment operating state matrix that contains both capacity and the introduced operating state constraints; M1 represents the supplementary constraint conditions that contain both capacity and the introduced operating state; D1 represents the supplementary constraint matrix of the equipment introducing the operating state; d1 represents the supplementary constraint conditions of the equipment introducing the operating state.

[0136] The relevant constraints are the same as those at the operation level. However, since only the first running moment is considered, the variable data is the number of subtasks multiplied by the number of running variables at a single moment. It does not significantly increase the complexity of the main problem and can be efficiently solved through existing mathematical programming methods.

[0137] Optionally, for step S150, if Figure 3 As shown, the solved capacity solution is used to perform corresponding calculations using 8760 hours of historical data to determine whether the solved capacity can meet the load demand and the required direct green electricity supply ratio.

[0138] Therefore, with the help of the above technical solution, this application takes into account multiple parameters and can achieve the minimum capital investment, the minimum payback period and the optimal energy utilization efficiency. In addition, through model calculation, it can reduce capital investment for the construction of distributed energy systems, reduce the wind and solar power abandonment rate, realize large-scale green electricity consumption, and meet the efficient utilization of new energy.

[0139] It should be understood that the above-mentioned comprehensive energy system planning research method based on inter-seasonal heat storage in buried pipes is only exemplary, and those skilled in the art can make various modifications based on the above-mentioned method, and the modified scheme also falls within the scope of protection of this application.

[0140] The present application provides a storage medium having a computer program stored thereon. The computer program is executed by a processor to execute the method described in the embodiment.

[0141] The present application also provides a computer program product, which, when executed on a computer, enables the computer to execute the method described in the method embodiment.

[0142] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take 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.

[0143] The present invention is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present invention. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions.

[0144] It should be noted that in the claims, any reference numerals placed between brackets shall not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention may be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In the claims enumerating several means, several of these means may be embodied by the same hardware. The use of the words first, second, third, etc., is for convenience of expression only and does not indicate any order. These words may be understood as part of the component name.

[0145] In addition, it should be noted that, in the description of this specification, the description of the terms "one embodiment", "some embodiments", "embodiment", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0146] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments after knowing the basic creative concept. Therefore, the claims should be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present invention.

[0147] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention should also include these modifications and variations.

Claims

1. A research method for planning an integrated energy system based on inter-seasonal heat storage in underground pipes, characterized in that: include: Establishing buried pipe model; Based on the buried pipe model, a wind-solar-heat storage coordinated operation model is established; Based on the wind-solar-heat storage system operation model, the equipment construction investment cost and the production simulation cost of the target years are considered at the same time, and the planning and design are carried out to minimize the total cost of the system throughout its life cycle, and a comprehensive energy system planning model is established; wherein the objective function of the comprehensive energy system planning model is to minimize the annual equivalent cost of the entire life cycle; The Benders decomposition method is used to decompose the establishment of the integrated energy system planning model into a main problem and sub-problems and solve them to obtain multiple candidate wind-solar-heat storage capacity ratios; The optimal wind-solar-heat storage capacity ratio that meets the load demand and the green electricity direct supply ratio requirements is determined from the multiple candidate wind-solar-heat storage capacity ratios.

2. The integrated energy system planning research method according to claim 1 is characterized in that: The buried pipe model is used to obtain the soil temperature of the buried pipe; the expression of the soil temperature is: Where r is the radius of the buried pipe; τ is the time; T(r, τ) is the soil temperature at radius r at time τ; T0 is the initial soil temperature; q l Represents the energy input to the buried pipe; s represents the thermal physical property parameters of the first buried pipe; α s Represents the thermal physical parameters of the second buried pipe.

3. The integrated energy system planning research method according to claim 2 is characterized in that: The buried pipe model is further used to determine the temperature relationship between the fluid inlet and outlet; the expression of the temperature relationship is: Where, T f,out (τ) represents the outlet temperature of the fluid at the time τ; T f,in (τ) represents the inlet temperature of the fluid at the time τ; T b (τ) represents the wall temperature of the buried pipe at the time τ; λ represents the heat transfer coefficient between the buried pipe and the soil; H is the drilling depth; c f represents the specific heat capacity of the heat transfer fluid; m f Represents the heat transfer fluid mass flow rate.

4. The integrated energy system planning research method according to claim 1 is characterized in that: The wind-solar-heat-storage coordinated operation model includes the power and operation constraints of the heat pump; The expression of the electric heating / cooling conversion constraint of the heat pump system is: In the formula, represents the real-time heating capacity of the heat pump system; COPh represents the heating coefficient of the heat pump system; represents the heating power of the heat pump system at the time τ; represents the real-time cooling capacity of the heat pump system; COPc represents the cooling coefficient of the heat pump system; represents the cooling power of the heat pump system at the time τ; And, the power constraint expression of the heat pump system is: Where P HP,min represents the minimum operating power of the heat pump system; represents the power of the heat pump system at the time τ; P HP,max Indicates the maximum operating power of the heat pump system.

5. The integrated energy system planning research method according to claim 4 is characterized in that: The wind-solar-heat-storage coordinated operation model further includes a constraint model for underground pipes; Wherein, the constraint model of the buried pipe includes: The expression for maintaining balance between the extraction amount and heat injection amount of the buried pipe is: Where, IS represents the start time of heat injection; IE represents the end time of heat injection; represents the heat injection amount of the buried pipe at the time τ; represents the amount of heat loss at the time τ; represents the amount of heat supplement at the time τ; ES represents the start time of heat extraction; EE represents the end time of heat extraction; represents the heat extraction amount of the underground pipe at the time τ; And, the expressions of the heat injection amount of the buried pipe and the heat extraction amount of the buried pipe are: And, the constraint expressions of the heat injection amount of the underground pipe and the heat extraction amount of the underground pipe are: Wherein, n represents the total number of holes of the buried pipe; m f,i represents the mass flow rate of the ith underground pipe; c f represents the specific heat capacity of the heat transfer fluid; T f,i,in (τ) represents the inlet temperature of the fluid in the i-th underground pipe at the time τ; T f,i,out (τ) represents the outlet temperature of the fluid in the i-th buried pipe at the time τ.

6. The integrated energy system planning research method according to claim 1 is characterized in that: The expression of the objective function is: minF=C inv +C opt +C ST +C EA ; In the formula, F represents the objective function value; C inv Represents the annual equivalent investment cost of equipment; C opt represents the annual equivalent operation and maintenance cost; C ST represents the penalty for hot and cold production deviation; C EA It means the punishment for abandoning wind and light; And, the C inv The expression is: In the formula, c inv,j represents the unit capacity investment cost of the jth equipment; E j represents the planned capacity of the jth type of equipment; r represents the radius of the buried pipe; m represents the planned life of the system in years; WT represents wind power; PV represents photovoltaic power; BS represents energy storage power station; HP represents heat pump; BT represents buried pipe; And, the C opt , said C ST and the C EA The expression is: In the formula, λ opt,j Represents the unit power operation and maintenance cost coefficient of the equipment; P j τ Indicates the real-time operating power of the device; PE represents the additional cost of purchasing electricity; represents the power purchased from the large power grid at time τ; λ EA Indicates the unit cost of wind and solar power abandonment; Indicates the wind and solar power absorbed by the system in real time; Represents the actual real-time wind and solar power generation power based on wind and solar resources; H represents the unit penalty cost of the heating load deviating from the demand curve; ES represents the start time of heat extraction; EE represents the end time of heat extraction; Indicates the real-time heating capacity of the heat pump system; Q HP,h represents the planned heating capacity of the heat pump system; C represents the unit penalty cost of the cooling load deviating from the demand curve; IS represents the start time of heat injection; IE represents the end time of heat injection; represents the real-time cooling capacity of the heat pump system; Q HP,c It represents the planned cooling capacity of the heat pump system.

7. The integrated energy system planning research method according to claim 1 is characterized in that: The constraints of the integrated energy system planning model include planning constraints; The expression of planning constraints is: E j ≥0； In the formula, E j Represents the planned capacity of the j-th type of equipment.

8. The integrated energy system planning research method according to claim 7 is characterized in that: The constraint conditions of the integrated energy system planning model further include operation constraints, and the operation constraints include establishing a system power balance equation and a heat balance equation respectively, and determining the actual grid-connected power constraints of wind power and photovoltaic power generation units, and the interactive power constraints with the large power grid without considering the surplus power being connected to the grid; The expressions of the power balance equation and the heat balance equation of the system are as follows: In the formula, represents the power generation of the photovoltaic unit at time τ; represents the power generation of the wind turbine at the time τ; represents the energy release power of the energy storage power station at the time τ; represents the power purchased from the large power grid at the time τ; represents the energy storage power of the energy storage power station at the time τ; represents the power of the heat pump system at the time τ; represents the power consumption of the underground pipe heat storage system at the time τ; represents the airport electricity load at the time τ; represents the heating power of the heat pump system at the time τ; represents the heat extraction amount of the underground pipe at the time τ; represents the heat load of the airport at said time τ; represents the cooling power of the heat pump system at the time τ; represents the heat injection amount of the buried pipe at the time τ; represents the cooling load of the airport at said time τ.

9. The integrated energy system planning research method according to claim 8, characterized in that: The constraints of the integrated energy system planning model further include planning-operation coupling constraints; The expression of the planning operation coupling constraint is: In the formula, μ ES.min Indicates the minimum depth of charge and discharge of the energy storage device; E ES Represents the installed capacity of the energy storage power station; S OC,min Indicates the lower limit of the state of charge of the energy storage device; μ ES.max Indicates the maximum depth of charge and discharge of the energy storage device; S OC,max Indicates the upper limit of the state of charge of the energy storage device.

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