Capacity planning method and system for cogeneration compressed carbon dioxide energy storage power station

Abstract

The invention discloses a capacity planning method and system for a combined heat and power generation compressed carbon dioxide energy storage power station. The method comprises the steps that the corresponding relations between heat of a heat storage tank, the air pressure of a low-pressure air storage chamber and the air pressure of a high-pressure air storage chamber in the compressed carbon dioxide energy storage power station and electricity storage power, electricity generation power, heat storage power and heat supply power are obtained; based on the corresponding relationship, constructing a capacity planning model of the compressed carbon dioxide energy storage power station, and performing capacity planning by combining a cost minimization principle on the premise of meeting a preset constraint condition; and performing linearization processing on the carbon dioxide energy storage power station capacity planning model, and performing calculation solution on the carbon dioxide energy storage power station capacity planning model after the linearization processing through a linear optimization solver to obtain a capacity configuration result of the carbon dioxide energy storage power station. Through optimization planning, new energy output fluctuation and electric heating load changes can be effectively coped with, the utilization efficiency of electric energy and heat energy is improved, and the overall cost of the CHP system is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a capacity planning method and system for a combined heat and power compressed carbon dioxide energy storage power station. Background Art

[0002] Compressed Carbon Dioxide Energy Storage (CCES) technology recycles and reuses the compression heat generated in the compression stage through a heat storage device, achieving zero combustion and zero emissions throughout the entire process. It not only has the advantages of large capacity, long life, low cost, and safe and reliable operation, but the presence of the heat storage device also gives the CCES system the ability to operate in combined heat and power storage / cogeneration and coupled with external heat sources, further improving the flexibility and economy of the system's internal heat scheduling.

[0003] The combined heating and power system (CHP) integrates multiple energy forms such as electricity and heat to form an integrated system with coupled and complementary multi-energy flows, which effectively improves energy utilization. However, the access of high-penetration new energy sources also poses severe challenges to the safe and stable operation of the system. Therefore, equipment such as CCES is needed to provide important support for the multi-energy coordinated operation of CHP. At present, there are many implementation schemes for the optimization planning of CCES systems, but there is a lack of specific implementation methods for the design and optimization of each device in CCES power stations, which cannot meet the design requirements of CCES power stations, resulting in a long design cycle of CCES power stations and the need for repeated adjustments.

[0004] For example, in the case of high penetration of new energy, the interaction between various energy forms such as electricity and heat and various devices in CCES power stations has not been fully integrated, resulting in capacity planning being difficult to achieve optimal operation of the overall system; the dynamic changes in different energy demands have not been fully considered; and the differences in electricity and heat demand in different seasons and time periods have not been fully considered, resulting in capacity planning being likely to be in excess or insufficient in certain periods of time. Summary of the invention

[0005] The purpose of the embodiment of the present invention is to provide a capacity planning method and system for a cogeneration compressed carbon dioxide energy storage power station, which comprehensively considers the thermal capacity of the high and low pressure gas storage chambers and heat storage tanks of CCES, and fully utilizes the cogeneration characteristics of CCES. Through optimized planning, it can effectively respond to fluctuations in new energy output and changes in electric and thermal loads, improve the utilization efficiency of electric and thermal energy, reduce the overall cost of the CHP system, and show rapid cost recovery and good application prospects.

[0006] In order to solve the above technical problems, a first aspect of an embodiment of the present invention provides a capacity planning method for a cogeneration compressed carbon dioxide energy storage power station, comprising the following steps:

[0007] Obtain the corresponding relationships between the heat of the heat storage tank, the air pressure of the low-pressure gas storage chamber, the air pressure of the high-pressure gas storage chamber, and the storage power, power generation power, heat storage power, and heating power in the compressed carbon dioxide energy storage power station;

[0008] Based on the corresponding relationship, a capacity planning model of a compressed carbon dioxide energy storage power station is constructed, and capacity planning is performed in combination with the principle of cost minimization under the premise of satisfying preset constraints;

[0009] The carbon dioxide energy storage power station capacity planning model is linearized, and the linearized carbon dioxide energy storage power station capacity planning model is calculated and solved by a linear optimization solver to obtain a capacity configuration result of the carbon dioxide energy storage power station.

[0010] Furthermore, the corresponding relationship between the heat of the heat storage tank, the air pressure of the low-pressure air storage chamber, the air pressure of the high-pressure air storage chamber and the power storage power, the power generation power, the heat storage power and the heating power is:

[0011]

[0012] in, is the air pressure value of the low pressure air storage chamber, is the air pressure in the high pressure air storage chamber, is the calorific value of the heat storage tank, and are the relationship coefficients between the pressure change rate of the low-pressure gas storage tank and the gas mass flow rate flowing through the compressor and the expander, k mc,k,t and k mex,k,t are the relationship coefficients between the gas mass flow rate flowing through the compressor / expander and the compression power / generating power, and are the relationship coefficients between the pressure change rate of the high-pressure gas storage tank and the gas mass flow rate flowing through the compressor and the expander, and are the relationship coefficients between the heat change rate of the heat storage tank and the gas mass flow rate flowing through the compressor and the expander, k wh,k and k hl,k are the relationship coefficients between the heat change rate of the heat storage tank and the heat storage power and heating power, P c,k,t is the compression power of the k-node compressor at time t, P ex,k,t is the power generation power of the k-node expander at time t, P wh,k,t is the heat storage power of node k at time t, P hl,k,t is the heating power of node k at time t.

[0013] Furthermore, the air pressure value calculation formula of the low-pressure air storage chamber is:

[0014]

[0015] p l,k,min ≤p l,k,t ≤p l,k,max

[0016] Among them, p l,k,t and are the gas pressure value and pressure change rate of the low-pressure gas storage chamber at node k at time t, V l is the volume of the low pressure air storage chamber, R g is the gas constant, γ is the adiabatic index of carbon dioxide, m ex,k,t is the mass flow rate of carbon dioxide flowing into the expander at node k at time t, T ind is the temperature of the gas entering the low-pressure gas storage chamber after multi-stage heating and expansion, m c,k,t is the mass flow rate of carbon dioxide flowing into the compressor at node k at time t, T l is the gas temperature in the low-pressure gas storage chamber, p l,k,t-1 is the gas pressure value of the low-pressure gas storage chamber at node k at time t, Δt is the length of the time interval, and p l,k,min is the lower limit of the air pressure in the low pressure air storage chamber, p l,k,max It is the upper limit of the air pressure in the low-pressure air storage chamber;

[0017] The air pressure calculation formula of the high-pressure air storage chamber is:

[0018]

[0019] p h,k,min ≤p h,k,t ≤p h,k,max

[0020] Among them, p h,k,t and are the gas pressure value and pressure change rate of the high-pressure gas storage chamber at node k at time t, V h is the volume of the high pressure gas storage chamber, R g is the gas constant; γ is the adiabatic index of carbon dioxide, m ex,k,t is the mass flow rate of carbon dioxide flowing through the expander at node k at time t, T ing is the temperature of the gas entering the high-pressure gas storage chamber after multi-stage compression and cooling, m c,k,t is the mass flow rate of carbon dioxide flowing out of the compressor at node k at time t, T h is the gas temperature in the high pressure gas storage chamber, p h,k,min is the lower limit of the pressure in the high pressure storage chamber, p h,k,max It is the upper limit of the gas pressure in the high-pressure gas storage chamber;

[0021] The heat calculation formula of the heat storage tank absorbed during the compression process is:

[0022]

[0023] Among them, ε c is the heat transfer coefficient between the heat carrier medium and carbon dioxide gas, T C is the temperature of the heat medium in the heat storage tank, m c,k,t is the mass flow rate of carbon dioxide flowing out of the compressor at node k at time t, c p is the specific heat capacity of carbon dioxide at constant pressure, N c is the total number of compressor stages, T cin (i) is the inlet temperature of the i-th stage compressor, β c (i) is the compression ratio of the i-th compressor, γ is the adiabatic index of carbon dioxide;

[0024] The heat released by the heat storage tank during the expansion process is calculated as follows:

[0025]

[0026] Among them, ε c is the heat transfer coefficient between the heat carrier medium and carbon dioxide gas, m ex,k,t is the mass flow rate of carbon dioxide flowing through the expander at node k during period t, N ex is the total number of expander stages, T exin (j) is the inlet temperature of the j-th stage expander, β ex (j) is the expansion ratio of the j-th stage expander, η ex (j) is the isentropic efficiency of the j-th expander, γ is the adiabatic index of carbon dioxide;

[0027] The heat calculation formula in the heat storage tank is:

[0028] Q H,k,t =Q H,k,t-1 +(P Qc,k,t -P Qex,k,t )Δt+(P cwh,k,t -P chl,k,t )Δt;

[0029] Q H,k,min ≤Q H,k,t ≤Q H,k,max ;

[0030] Among them, Q h,k,t is the energy stored in the heat storage tank of the compressed carbon dioxide energy storage power station at node k at time t, P cwh,k,t is the heat storage power of CCES absorbing heat from the outside at node k at time t, P chl,k,t is the heating power of CCES at node k at time t; Q h,k,minand Q h,k,max are the lower and upper limits of the energy stored in the thermal storage tank respectively.

[0031] Furthermore, the calculation formula of the compressor compression power is:

[0032]

[0033] Among them, P c,k,t is the total compression power of node k in period t, m c,k,t is the mass flow rate of carbon dioxide entering the compressor at node k during period t, c p is the specific heat capacity of carbon dioxide at constant pressure, N c is the total number of compressor stages, T cin (i) is the inlet temperature of the i-th stage compressor, β c (i) is the compression ratio of the i-th compressor, γ is the adiabatic index of carbon dioxide, η c (i) is the isentropic efficiency of the i-th stage compressor;

[0034] The calculation formula of the expander power generation is:

[0035]

[0036] Among them, P ex,k,t is the total power of the k-node expander in period t, m ex,k,t is the mass flow rate of carbon dioxide flowing through the expander at node k during period t, N ex is the total number of expander stages, T exin (j) is the inlet temperature of the j-th stage expander, β ex (j) is the expansion ratio of the j-th expander, η ex (j) is the isentropic efficiency of the j-th expander, and γ is the adiabatic index of carbon dioxide.

[0037] Furthermore, the preset constraints include: CCES operation constraints;

[0038] The calculation formula of the operation constraint condition is:

[0039] s c,t +s ex,t ≤1s c,t ,s ex,t ∈{0,1};

[0040] s c,t P cmin ≤P c,t ≤s c,t P cmax ;

[0041] s ex,t P exmin ≤Pex,t ≤s ex,t P cmax ;

[0042] Among them, s c,t 、s ex,t are 0-1 variables of the charge and discharge states of the compressed carbon dioxide energy storage power station at time t; P cmin , P cmax are the minimum and maximum compression power of the compressed carbon dioxide energy storage power station respectively; P exmin , P cmax are respectively the minimum and maximum power generation power of the compressed carbon dioxide energy storage power station.

[0043] Furthermore, the preset constraints also include: electrical balance constraints and thermal balance constraints;

[0044] The electrical balance constraint condition is:

[0045] P rein,t +P grid,t +P ex,t =P c,t +P eload,t ;

[0046] Among them, P rein,t is the actual grid active power of renewable energy generation at time t, P grid,t is the power purchased from the main grid at time t, P ex,t is the CCES power generation at time t, P c,t is the electric power absorbed at time t, P eload,t is the power absorbed by the electrical load at time t;

[0047] The thermal balance constraints are:

[0048] P hsou,t +P mh,t +P chl,t =P cwh,t +P hload,t ;

[0049] Among them, P hsou,t is the heating power of the local heat source at time t, P mh,t is the heating power of the main heating network at time t, P chl,t is the heating power provided by CCES to the regional heat load at time t, P cwh,t is the heat storage power P representing the heat absorbed by CCES from the heat source at time t hload,t is the power absorbed by the heat load at time t.

[0050] Furthermore, the cost minimization principle of the carbon dioxide energy storage power station capacity planning model is:

[0051] min C total =C inv +C run ;

[0052] C inv =[c 1 P c +c 2 P ex +c 3 P wh +c 4 P hl +c 5 (V h +V l )+c 6 Q H ];

[0053]

[0054] Among them, C total is the total cost of the compressed carbon dioxide energy storage power station, C inv is the total investment cost, C run is the total operating cost, c 1 、c 2 are the unit compression power and the investment cost of compression power, respectively, 3 、c 4 Decibel is the investment cost per unit heat storage power and heating power; c 5 is the investment cost of the gas storage room per unit capacity, c 6 is the unit capacity investment cost of the heat storage tank, π c , π ex are the annual operation and maintenance costs per unit compression power and expansion power of the compressed carbon dioxide energy storage power station, c ele,t is the price of electricity purchased from the main grid at time t, P grid,t is the power purchased from the main grid at time t, c re,t is the cost of renewable energy power abandonment at time t, P re,t , P rein,t They are the renewable energy power generation active power and the actual grid active power at time t respectively.

[0055] Furthermore, the linearization processing of the carbon dioxide energy storage power station capacity planning model includes:

[0056] The carbon dioxide energy storage power station capacity planning model is linearized based on the big M method.

[0057] Accordingly, a second aspect of an embodiment of the present invention provides a capacity planning system for a combined heat and power compressed carbon dioxide energy storage power station, comprising:

[0058] A corresponding relationship acquisition module, which is used to obtain the corresponding relationship between the heat of the heat storage tank, the air pressure of the low-pressure gas storage chamber, the air pressure of the high-pressure gas storage chamber in the compressed carbon dioxide energy storage power station and the storage power, power generation power, heat storage power and heating power respectively;

[0059] A model building module, which is used to build a capacity planning model for a compressed carbon dioxide energy storage power station based on the corresponding relationship, and to perform capacity planning in combination with a cost minimization principle under the premise of satisfying preset constraints;

[0060] The planning calculation module is used to linearize the capacity planning model of the carbon dioxide energy storage power station, calculate and solve the linearized capacity planning model of the carbon dioxide energy storage power station through a linear optimization solver, and obtain the capacity configuration result of the carbon dioxide energy storage power station.

[0061] Accordingly, a third aspect of an embodiment of the present invention provides an electronic device, comprising: at least one processor; and a memory connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor executes the above-mentioned cogeneration compressed carbon dioxide energy storage power station capacity planning method.

[0062] Accordingly, a fourth aspect of an embodiment of the present invention provides a computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the above-mentioned cogeneration compressed carbon dioxide energy storage power station capacity planning method.

[0063] The above technical solution of the embodiment of the present invention has the following beneficial technical effects:

[0064] The thermal capacity of CCES's high and low pressure gas storage chambers and heat storage tanks is fully considered, and the cogeneration characteristics of CCES are fully utilized. Through optimized planning, it can effectively respond to fluctuations in new energy output and changes in electric and thermal loads, improve the utilization efficiency of electric and thermal energy, reduce the overall cost of the CHP system, and provide an effective way for the scientific planning of cogeneration compressed carbon dioxide energy storage power stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 It is a flow chart of a capacity planning method for a cogeneration compressed carbon dioxide energy storage power station provided by an embodiment of the present invention;

[0066] Figure 2 It is a module block diagram of a capacity planning system for a cogeneration compressed carbon dioxide energy storage power station provided by an embodiment of the present invention.

[0067] Reference numerals:

[0068] 1. Correspondence acquisition module, 2. Model building module, 3. Planning calculation module, DETAILED DESCRIPTION

[0069] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are only exemplary and are not intended to limit the scope of the present invention. In addition, in the following description, the description of well-known structures and technologies is omitted to avoid unnecessary confusion of the concept of the present invention.

[0070] The CCES-based cogeneration system architecture means that in traditional cogeneration systems, gas turbines are usually used for the power generation part, and waste heat boilers are used to recover the high-temperature flue gas emitted by the gas turbine, or internal combustion engine heat energy is used; not only does it have higher carbon emissions, but it also requires adjusting the unit parameters to achieve optimal allocation of the two energy sources, lacks flexibility, and also requires additional energy storage to absorb wind and solar power.

[0071] In the CCES-based cogeneration system of the present invention, the distribution network and the regional thermal network are coordinated and integrated; the distribution network includes two renewable energy sources, wind power and photovoltaics, and electric loads; the regional thermal network includes local heat sources and thermal loads; the CCES power station is used as the energy hub of the CHP system to realize the storage, conversion and distribution of electrical energy and thermal energy: its power storage stage can absorb abandoned wind and solar power and grid off-peak electricity, the power generation stage can supply electrical loads during peak power consumption, the heat storage stage can absorb valley waste heat, and the heat release stage can supply thermal loads; the unified scheduling of the two energy sources is realized to reduce the system operating costs.

[0072] CCES is mainly composed of a compressor, an expander, an intercooler, a heat exchanger, a heat storage tank, a cold storage tank, a high-pressure gas storage chamber and a low-pressure gas storage chamber. Its working mechanism is as follows:

[0073] In the energy storage stage, carbon dioxide (Carbon Dioxide, CO 2 ) is compressed to a high temperature and high pressure state by the compressor, and then cooled by heat exchange with the heat exchange medium through the intercooler, and the compression heat is transferred to the heat storage tank for storage; after multi-stage compression and inter-stage heat exchange, the high-pressure carbon dioxide is stored in the high-pressure gas storage chamber, and the electric energy is finally converted into CO 2 The internal energy of the gas and the thermal energy of the heat exchange medium are stored.

[0074] During the electrical energy release stage, the CO in the high-pressure gas storage chamber 2 It is sent to the reheater to heat up, absorbs heat from the heat storage tank, and finally enters the turbine to expand and do work, generating electrical energy output. 2 It is stored in the low-pressure gas storage chamber, and the heat exchange medium releases heat and is stored in the cold storage tank for the next cycle.2 The internal energy of the gas and the thermal energy of the heat carrier medium are released in the form of electrical energy.

[0075] At the same time, the heat storage tank can not only store compression heat, but also absorb heat from external heat sources. In addition to being used to heat carbon dioxide, the stored heat can also be directly supplied to the heat load of the regional heating network, reducing dependence on external heat sources.

[0076] Please refer to Figure 1 A first aspect of an embodiment of the present invention provides a capacity planning method for a combined heat and power compressed carbon dioxide energy storage power station, comprising the following steps:

[0077] Step S100, obtaining the corresponding relationships between the heat of the heat storage tank, the air pressure of the low-pressure gas storage chamber, the air pressure of the high-pressure gas storage chamber, and the storage power, the power generation power, the heat storage power, and the heating power in the compressed carbon dioxide energy storage power station.

[0078] By obtaining the corresponding relationships between the heat of the heat storage tank, the air pressure of the low-pressure gas storage chamber, and the air pressure of the high-pressure gas storage chamber in the compressed carbon dioxide energy storage power station and the storage power, power generation power, heat storage power, and heating power, the interaction between the key devices in the energy storage power station is fully considered, so that the capacity planning can better adapt to the multi-energy flow coupling characteristics of the cogeneration system, and provide an accurate basis for the reasonable capacity configuration of each device.

[0079] For example, the correspondence between the heat of the heat storage tank and the heating power helps to determine the appropriate capacity of the heat storage tank to meet the energy supply under different heating needs; the relationship between air pressure and power can guide the capacity planning of the gas storage room to ensure the stable storage and release of gas during energy storage and power generation.

[0080] Optionally, the heat of the heat storage tank in the compressed carbon dioxide energy storage power station in step S100, the air pressure of the low-pressure gas storage chamber, and the air pressure of the high-pressure gas storage chamber correspond to the power storage power, power generation power, heat storage power, and heating power, respectively. It is also possible to consider establishing an operating characteristic model of a compressed carbon dioxide energy storage power station, modeling key equipment such as compressors and expanders, and then establishing the above correspondence. In addition, the gas storage chamber and the heat storage tank are the core components of the CCES system energy storage. The size of the two jointly determines the amount of power storage, and the size of the heat storage tank determines the heat storage of the system, which is the main content of CCES capacity planning.

[0081] Specifically, mathematical models of the two key devices, compressor and expander, are established; multi-stage compression is usually used in the compression process, and the compression power is usually expressed as:

[0082]

[0083] Where P c,k,t is the total compression power of node k in period t; mc,k,t is the mass flow rate of carbon dioxide entering the compressor at node k during period t; c p is the specific heat capacity of carbon dioxide at constant pressure. N c is the total number of compressor stages; T cin (i) is the inlet temperature of the i-th stage compressor; β c (i) is the compression ratio of the i-th compressor; γ is the adiabatic index of carbon dioxide; η c (i) is the isentropic efficiency of the i-th stage compressor.

[0084] The power generation process is usually multi-stage expansion, and its power generation is usually expressed as:

[0085]

[0086] Where P ex,k,t is the total power of the turbine at node k during period t; m ex,k,t is the mass flow rate of carbon dioxide flowing through the turbine at node k during period t; N ex is the total number of turbine stages; T exin (j) is the inlet temperature of the j-th turbine; β ex (j) is the expansion ratio of the j-th turbine; η ex (j) is the isentropic efficiency of the j-th turbine stage.

[0087] Step S200: Based on the corresponding relationship, a capacity planning model for the compressed carbon dioxide energy storage power station is constructed, and capacity planning is performed in combination with the cost minimization principle under the premise of satisfying preset constraints.

[0088] The above capacity planning method ensures the safety and stability of the system operation and can minimize costs. For each device in the energy storage power station, by setting reasonable constraints, it can ensure that each device performs at its best within its safe operating range.

[0089] At the same time, the principle of cost minimization makes capacity planning more economical and efficient, avoiding overinvestment and waste of resources. For example, when determining the capacity of compression equipment, expansion equipment and other devices, their construction cost, operating cost and synergy with other devices will be comprehensively considered to achieve the optimal configuration of the overall system.

[0090] Step S300, linearizing the capacity planning model of the carbon dioxide energy storage power station, and calculating and solving the linearized capacity planning model of the carbon dioxide energy storage power station through a linear optimization solver to obtain a capacity configuration result of the carbon dioxide energy storage power station.

[0091] The capacity planning model of the carbon dioxide energy storage power station is linearized and solved by a linear optimization solver, which improves the accuracy and reliability of capacity planning. Linearization makes complex models easy to solve and can quickly obtain accurate capacity configuration results. For each device in the energy storage power station, this precise solution method can determine the most appropriate capacity size for it, avoiding errors caused by empirical or rough estimates. For example, when determining the capacity of devices such as heat exchangers and valves, the linear optimization solver can give the optimal size and parameters based on specific performance requirements and system constraints, ensuring that each device works together in the system and improving the operating efficiency and reliability of the entire energy storage power station.

[0092] Specifically, in a specific implementation of an embodiment of the present invention, the corresponding relationship between the heat of the heat storage tank, the air pressure of the low-pressure air storage chamber, the air pressure of the high-pressure air storage chamber, the storage power, the power generation power, the heat storage power and the heating power in step 100 is:

[0093]

[0094] in, is the air pressure value of the low pressure air storage chamber, is the air pressure in the high pressure air storage chamber, is the calorific value of the heat storage tank, and are the relationship coefficients between the pressure change rate of the low-pressure gas storage tank and the gas mass flow rate flowing through the compressor and the expander, k mc,k,t and k mex,k,t are the relationship coefficients between the gas mass flow rate flowing through the compressor / expander and the compression power / generating power, and are the relationship coefficients between the pressure change rate of the high-pressure gas storage tank and the gas mass flow rate flowing through the compressor and the expander, and are the relationship coefficients between the heat change rate of the heat storage tank and the gas mass flow rate flowing through the compressor and the expander, k wh,k and k hl,k are the relationship coefficients between the heat change rate of the heat storage tank and the heat storage power and heating power, P c,k,t is the compression power of the k-node compressor at time t, P ex,k,t is the power generation power of the k-node expander at time t, P wh,k,t is the heat storage power of node k at time t, P hl,k,t is the heating power of node k at time t.

[0095] The above correspondence accurately describes the dynamic relationship between the key parameters in the combined heat and power compressed carbon dioxide energy storage power station through clear mathematical expressions. Specifically, the air pressure value of the low-pressure gas storage chamber, the air pressure value of the high-pressure gas storage chamber, and the calorific value of the heat storage tank are respectively linked to the gas mass flow rate, compression power, power generation power, heat storage power, and heating power of the compressor and expander, so that when carrying out capacity planning, the dynamic changes of the system under different operating conditions can be fully considered, providing a solid theoretical basis for accurately determining the reasonable capacity of each device.

[0096] The various coefficients in the corresponding relationship relate different parameters to each other, making it possible to realize the coordinated planning of multiple devices in the energy storage power station. For example, the relationship coefficients and respectively reflect the relationship between the pressure change rate of the low-pressure gas storage tank and the gas mass flow rate flowing through the compressor and the expander, which means that when planning the capacity of the low-pressure gas storage chamber, the operation of the compressor and the expander and the change of the gas mass flow rate can be considered at the same time, thereby ensuring the coordinated work between the low-pressure gas storage chamber and other devices. In addition, through this corresponding relationship, the performance of the energy storage power station under different operating conditions can be more accurately evaluated. For example, according to the corresponding relationship, the parameters such as the compressor compression power, the expander power generation power, the heat storage power and the heating power at different time nodes can be calculated, and then the performance indicators such as the energy conversion efficiency and power output stability of the system can be analyzed.

[0097] Furthermore, the above coefficients can be derived and expressed as:

[0098]

[0099] k wh =ε c

[0100] Among them, the calculation formula for the air pressure value of the low-pressure air storage chamber is:

[0101]

[0102] p l,k,min ≤p l,k,t ≤p l,k,max

[0103] Among them, p l,k,t and are the gas pressure value and pressure change rate of the low-pressure gas storage chamber at node k at time t, V l is the volume of the low pressure air storage chamber, R g is the gas constant, γ is the adiabatic index of carbon dioxide, m ex,k,t is the mass flow rate of carbon dioxide flowing into the expander at node k at time t, T indis the temperature of the gas entering the low-pressure gas storage chamber after multi-stage heating and expansion, m c,k,t is the mass flow rate of carbon dioxide flowing into the compressor at node k at time t, T l is the gas temperature in the low-pressure gas storage chamber, p l,k,t-1 is the gas pressure value of the low-pressure gas storage chamber at node k at time t, Δt is the length of the time interval, and p l,k,min is the lower limit of the air pressure in the low pressure air storage chamber, p l,k,max It is the upper limit of the air pressure in the low-pressure air storage chamber.

[0104] Among them, the calculation formula of the air pressure value of the high-pressure air storage chamber is:

[0105]

[0106] p h,k,min ≤p h,k,t ≤p h,k,max

[0107] Among them, p h,k,t and are the gas pressure value and pressure change rate of the high-pressure gas storage chamber at node k at time t, V h is the volume of the high pressure gas storage chamber, R g is the gas constant; γ is the adiabatic index of carbon dioxide, m ex,k,t is the mass flow rate of carbon dioxide flowing through the expander at node k at time t, T ing is the temperature of the gas entering the high-pressure gas storage chamber after multi-stage compression and cooling, m c,k,t is the mass flow rate of carbon dioxide flowing out of the compressor at node k at time t, T h is the gas temperature in the high pressure gas storage chamber, p h,k,min is the lower limit of the pressure in the high pressure storage chamber, p h,k,max It is the upper limit of the gas pressure in the high-pressure gas storage chamber;

[0108] Among them, the calculation formula for the heat absorbed by the heat storage tank during the compression process is:

[0109]

[0110] Among them, ε c is the heat transfer coefficient between the heat carrier medium and carbon dioxide gas, T C is the temperature of the heat medium in the heat storage tank, m c,k,t is the mass flow rate of carbon dioxide flowing out of the compressor at node k at time t, c p is the specific heat capacity of carbon dioxide at constant pressure, N c is the total number of compressor stages, T cin (i) is the inlet temperature of the i-th stage compressor, β c (i) is the compression ratio of the i-th compressor, and γ is the adiabatic index of carbon dioxide.

[0111] Among them, the calculation formula for the heat released by the heat storage tank during the expansion process is:

[0112]

[0113] Among them, ε c is the heat transfer coefficient between the heat carrier medium and carbon dioxide gas, m ex,k,t is the mass flow rate of carbon dioxide flowing through the expander at node k during period t, N ex is the total number of expander stages, T exin (j) is the inlet temperature of the j-th stage expander, β ex (j) is the expansion ratio of the j-th stage expander, η ex (j) is the isentropic efficiency of the j-th expander, and γ is the adiabatic index of carbon dioxide.

[0114] Furthermore, the heat calculation formula in the heat storage tank is:

[0115] Q H,k,t =Q H,k,t-1 +(P Qc,k,t -P Qex,k,t )Δt+(P cwh,k,t -P chl,k,t )Δt;

[0116] Q H,k,min ≤Q H,k,t ≤Q H,k,max ;

[0117] Among them, Q h,k,t is the energy stored in the heat storage tank of the compressed carbon dioxide energy storage power station at node k at time t, P cwh,k,t is the heat storage power of CCES absorbing heat from the outside at node k at time t, P chl,k,t is the heating power of CCES at node k at time t; Q h,k,min and Q h,k,max are the lower and upper limits of the energy stored in the thermal storage tank respectively.

[0118] Accordingly, in the capacity planning model of the compressed carbon dioxide energy storage power station, the calculation formula for the compressor compression power is:

[0119]

[0120] Among them, P c,k,t is the total compression power of node k in period t, m c,k,t is the mass flow rate of carbon dioxide entering the compressor at node k during period t, c p is the specific heat capacity of carbon dioxide at constant pressure, N c is the total number of compressor stages, T cin (i) is the inlet temperature of the i-th stage compressor, β c(i) is the compression ratio of the i-th compressor, γ is the adiabatic index of carbon dioxide, η c (i) is the isentropic efficiency of the i-th stage compressor.

[0121] By associating the compressor compression power with multiple key parameters through a clear formula, the compression power of the compressor under different operating conditions can be accurately calculated; it helps to accurately determine the capacity requirements of the compressor in capacity planning and avoid over-configuration or under-configuration. Specifically, the formula takes into account multiple factors such as carbon dioxide mass flow rate, constant pressure specific heat capacity, number of compressor stages, inlet temperature of each stage, pressure ratio and isentropic efficiency. These factors comprehensively reflect the working state and performance of the compressor, making the calculation results more in line with the actual situation. For example, mass flow rate and pressure ratio directly affect the size of compression work, while isentropic efficiency reflects the energy conversion efficiency of the compressor. In addition, by analyzing the various parameters in the formula, the key factors affecting the compression power can be determined, thereby providing direction for the optimal design of the compressor. For example, the compression power demand can be reduced and the overall performance of the system can be improved by improving the isentropic efficiency, optimizing the pressure ratio or adjusting the inlet temperature.

[0122] Similarly, in the capacity planning model of the compressed carbon dioxide energy storage power station, the calculation formula for the expander power generation is:

[0123]

[0124] Among them, P ex,k,t is the total power of the k-node expander in period t, m ex,k,t is the mass flow rate of carbon dioxide flowing through the expander at node k during period t, N ex is the total number of expander stages, T exin (j) is the inlet temperature of the j-th stage expander, β ex (j) is the expansion ratio of the j-th stage expander, η ex (j) is the isentropic efficiency of the j-th expander, and γ is the adiabatic index of carbon dioxide.

[0125] The power generation formula of the expander can accurately calculate the power generation of the expander under different operating conditions based on multiple key parameters, providing a reliable basis for determining the capacity of the expander in capacity planning. By considering factors such as carbon dioxide mass flow rate, expander stage number, inlet temperature of each stage, expansion ratio and isentropic efficiency, the working state and performance of the expander are reflected, so that the calculation results can better reflect the actual power generation situation. For example, the mass flow rate and expansion ratio determine the size of the expansion work, while the isentropic efficiency affects the power generation efficiency. In addition, by analyzing the parameters in the formula, the key factors affecting the power generation of the expander can be determined, thereby providing guidance for optimizing the operation of the expander. For example, the power generation can be increased by adjusting the expansion ratio, improving the isentropic efficiency or optimizing the inlet temperature, thereby increasing the energy output of the system.

[0126] In the embodiment of the present invention, in order to improve the capacity planning effect of the compressed carbon dioxide energy storage power station, preset constraint conditions for the constraint model are also set, which include: CCES operation constraint conditions.

[0127] The calculation formula for the operation constraint condition is as follows:

[0128] s c,t +s ex,t ≤1s c,t ,s ex,t ∈{0,1};

[0129] s c,t P cmin ≤P c,t ≤s c,t P cmax ;

[0130] s ex,t P exmin ≤P ex,t ≤s ex,t P cmax ;

[0131] Among them, s c,t 、s ex,t are 0-1 variables of the charge and discharge state of the compressed carbon dioxide energy storage power station at time t; P cmin , P cmax are the minimum and maximum compression power of the compressed carbon dioxide energy storage power station; P exmin , P cmax They are the minimum and maximum power generation capacity of the compressed carbon dioxide energy storage power station.

[0132] By setting the minimum and maximum constraints of compression power and power generation, the operating boundaries of the compressed carbon dioxide energy storage power station under the charging and discharging states at different times are clarified to ensure that the system operates within a safe and stable range and avoid failures or damage caused by power exceeding the equipment's capacity. Operational constraints can also prompt the system to reasonably allocate compression power and power generation while meeting demand. For example, when more energy storage is needed, the compression power can be appropriately increased; and when discharge is required, the power generation power can be controlled within a reasonable range to meet load demand. In addition, operational constraints can also be used to reduce system uncertainty and risk and improve system reliability. By limiting the range of power fluctuations, the stress and wear of the equipment can be reduced and the service life of the equipment can be extended.

[0133] In addition, the preset constraints also include: electrical balance constraints and thermal balance constraints.

[0134] Among them, the electrical balance constraint condition is:

[0135] P rein,t +P grid,t +P ex,t =P c,t +P eload,t ;

[0136] Among them, P rein,t is the actual grid active power of renewable energy generation at time t, P grid,t is the power purchased from the main grid at time t, P ex,t is the CCES power generation at time t, P c,t is the electric power absorbed at time t, P eload,t is the power absorbed by the electrical load at time t.

[0137] The electric balance constraint conditions clarify the relationship between the inflow and outflow of electricity in each part of the system. Through the constraints of the equation, it is ensured that the supply and demand of electricity can be balanced at any time. This helps to avoid the occurrence of excess or insufficient electricity, improve the stability and reliability of the system; it also prompts the system to reasonably allocate power resources when planning capacity. For example, when the electric load demand is large, the discharge power of the energy storage power station can be adjusted or the output of other power sources can be increased to meet the load demand. At the same time, the power supply structure can also be optimized according to the power generation cost and efficiency of different power sources. Through the electric balance constraint, the system can be prompted to improve the energy conversion efficiency as much as possible while meeting the load demand. For example, the charging and discharging timing of the energy storage power station can be reasonably arranged to reduce energy loss and waste and improve the overall efficiency of the system.

[0138] The heat balance constraint is:

[0139] P hsou,t +P mh,t +P chl,t =P cwh,t +P hload,t ;

[0140] Among them, P hsou,t is the heating power of the local heat source at time t, P mh,t is the heating power of the main heating network at time t, P chl,t is the heating power provided by CCES to the regional heat load at time t, P cwh,t is the heat storage power P representing the heat absorbed by CCES from the heat source at time t hload,t is the power absorbed by the heat load at time t.

[0141] The heat balance constraint clarifies the relationship between the generation and consumption of heat in each part of the system, ensuring that the balance of heat supply and demand can be achieved at any time. This helps to avoid the occurrence of excess or insufficient heat, improve the stability and reliability of the system; it also encourages the system to make rational use of heat resources when planning capacity. For example, when the heat load demand is large, the heating power of the local heat source can be adjusted or the heating power of the energy storage power station can be increased to meet the load demand. At the same time, the heat supply structure can also be optimized according to the cost and efficiency of different heat resources. Through the heat balance constraint, the system can be prompted to improve the comprehensive utilization efficiency of energy as much as possible while meeting the heat load demand. For example, the heat storage and heating timing of the energy storage power station can be reasonably arranged to reduce heat loss and waste and improve the overall energy efficiency of the system.

[0142] Furthermore, the cost minimization principle of the CO2 energy storage power station capacity planning model is:

[0143] minC total =C inv +C run ;

[0144] C inv =[c 1 P c +c 2 P ex +c 3 P wh +c 4 P hl +c 5 (V h +V l )+c 6 Q H ];

[0145]

[0146] Among them, C total is the total cost of the compressed carbon dioxide energy storage power station, C inv is the total investment cost, C run is the total operating cost, c 1 、c 2 are the unit compression power and the investment cost of compression power, respectively, 3 、c 4 Decibel is the investment cost per unit heat storage power and heating power; c 5 is the investment cost of the gas storage room per unit capacity, c 6 is the unit capacity investment cost of the heat storage tank, π c , π ex are the annual operation and maintenance costs per unit compression power and expansion power of the compressed carbon dioxide energy storage power station, c ele,tis the price of electricity purchased from the main grid at time t, P grid,t is the power purchased from the main grid at time t, c re,t is the cost of renewable energy power abandonment at time t, P re,t , P rein,t They are the renewable energy power generation active power and the actual grid active power at time t respectively.

[0147] The total cost of a compressed carbon dioxide energy storage power station is divided into total investment cost and total operating cost, which clearly shows the various components of the cost. This makes it possible to accurately evaluate the impact of different decisions on costs when conducting capacity planning, thereby making more economical and efficient planning. By considering the investment costs of unit compression power, heat storage power, heating power, gas storage chambers and heat storage tanks, as well as the annual operation and maintenance costs of compression and expansion power, this principle comprehensively considers various cost factors in the construction and operation of energy storage power stations. This helps to weigh the cost-effectiveness of different equipment and technologies during the planning process and select the optimal capacity configuration plan.

[0148] Specifically, the linearization process of the carbon dioxide energy storage power station capacity planning model in step S300 is as follows:

[0149] The capacity planning model of carbon dioxide energy storage power station is linearized based on the big M method.

[0150] Since the capacity planning model of the compressed carbon dioxide energy storage power station is a nonlinear planning optimization problem, there are binary variables and continuous variables multiplied in the operation constraints of the CCES power station, so the Big M method is introduced to linearize it. Among them, the Big M method is also called Big M Method, which is a mathematical optimization method used to solve linear programming problems.

[0151] For example, for the compression power upper and lower limit constraints, it can be converted to:

[0152] P cmin +(s c,t -1)M≤P c,t

[0153] P c,t ≤P cmax +(1-s c,t )M;

[0154] -s c,t M≤P c,t ≤s c,t M

[0155] Where M is a sufficiently large constant.

[0156] When c,tWhen s is 0, it means that CCES does not work in the compression state. At this time, according to the third inequality, the compression power is also constrained to zero. c,t When it is 1, it means that CCES works in compression state. At this time, it can be seen from the first two inequalities that the compression power is constrained to be between the maximum and minimum values. The same is true for other nonlinear constraints.

[0157] After the model is linearized, the problem can be solved by a linear optimization solver, and finally the capacity configuration result of CCES can be obtained.

[0158] The Big M method is used to linearize the model, converting the originally complex nonlinear model into a linear model, so that it can be solved using a mature linear optimization solver. This greatly simplifies the calculation process and improves the efficiency and accuracy of the solution. The linearized model is easier to understand and apply, and can be easily combined and integrated with other linear models. At the same time, it also enables different optimization algorithms and tools to be better applied to the model, broadening the scope of application of the model. Linearization can reduce uncertainty and errors in the model and improve the reliability and stability of the model. By converting nonlinear relationships into linear relationships, the accuracy and error range of the model can be better controlled, resulting in more reliable results.

[0159] In addition, it is also possible to consider linearizing the model based on piecewise linearization, Taylor series expansion, and variable substitution, which can also meet the above purpose.

[0160] This paper proposes a grid-friendly combined heat and power compressed carbon dioxide energy storage power station capacity planning method, which comprehensively considers the heat capacity of the high and low pressure gas storage chambers and heat storage tanks of CCES, and fully utilizes the combined heat and power characteristics of CCES. Through optimized planning, it can effectively cope with the fluctuation of new energy output and the change of electric and thermal loads, improve the utilization efficiency of electric and thermal energy, reduce the overall cost of CHP system, and show rapid cost recovery and good application prospects.

[0161] Accordingly, please refer to Figure 2 A second aspect of an embodiment of the present invention provides a capacity planning system for a combined heat and power compressed carbon dioxide energy storage power station, comprising:

[0162] Correspondence acquisition module 1, which is used to obtain the correspondence between the heat of the heat storage tank, the air pressure of the low-pressure gas storage chamber, the air pressure of the high-pressure gas storage chamber in the compressed carbon dioxide energy storage power station and the storage power, power generation power, heat storage power and heating power respectively;

[0163] Model building module 2, which is used to build a capacity planning model for a compressed carbon dioxide energy storage power station based on the corresponding relationship, and perform capacity planning in combination with the cost minimization principle under the premise of satisfying preset constraints;

[0164] The planning calculation module 3 is used to linearize the capacity planning model of the carbon dioxide energy storage power station, and calculate and solve the linearized carbon dioxide energy storage power station capacity planning model through a linear optimization solver to obtain the capacity configuration result of the carbon dioxide energy storage power station.

[0165] Accordingly, a third aspect of an embodiment of the present invention provides an electronic device, comprising: at least one processor; and a memory connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor executes the above-mentioned cogeneration compressed carbon dioxide energy storage power station capacity planning method.

[0166] Accordingly, a fourth aspect of an embodiment of the present invention provides a computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the above-mentioned cogeneration compressed carbon dioxide energy storage power station capacity planning method.

[0167] The embodiment of the present invention aims to protect a capacity planning method and system for a cogeneration compressed carbon dioxide energy storage power station, wherein the method includes the following steps: obtaining the correspondence between the heat of the heat storage tank, the air pressure of the low-pressure gas storage chamber, and the air pressure of the high-pressure gas storage chamber in the compressed carbon dioxide energy storage power station and the storage power, power generation power, heat storage power, and heating power, respectively; based on the correspondence, constructing a capacity planning model for the compressed carbon dioxide energy storage power station, and performing capacity planning in combination with the principle of cost minimization under the premise of satisfying preset constraints; linearizing the capacity planning model of the carbon dioxide energy storage power station, and calculating and solving the linearized carbon dioxide energy storage power station capacity planning model through a linear optimization solver to obtain the capacity configuration result of the carbon dioxide energy storage power station. The above technical scheme has the following effects:

[0168] The thermal capacity of CCES's high and low pressure gas storage chambers and heat storage tanks is fully considered, and the cogeneration characteristics of CCES are fully utilized. Through optimized planning, it can effectively respond to fluctuations in new energy output and changes in electric and thermal loads, improve the utilization efficiency of electric and thermal energy, reduce the overall cost of the CHP system, and provide an effective way for the scientific planning of cogeneration compressed carbon dioxide energy storage power stations.

[0169] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0170] The present application 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 application. 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. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0171] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0172] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0173] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A capacity planning method for a combined heat and power compressed carbon dioxide energy storage power station, characterized in that: The steps include: Obtain the corresponding relationships between the heat of the heat storage tank, the air pressure of the low-pressure gas storage chamber, the air pressure of the high-pressure gas storage chamber, and the storage power, power generation power, heat storage power, and heating power in the compressed carbon dioxide energy storage power station; Based on the corresponding relationship, a capacity planning model of a compressed carbon dioxide energy storage power station is constructed, and capacity planning is performed in combination with the principle of cost minimization under the premise of satisfying preset constraints; The carbon dioxide energy storage power station capacity planning model is linearized, and the linearized carbon dioxide energy storage power station capacity planning model is calculated and solved by a linear optimization solver to obtain a capacity configuration result of the carbon dioxide energy storage power station.

2. The capacity planning method for a combined heat and power compressed carbon dioxide energy storage power station according to claim 1 is characterized in that: The corresponding relationship between the heat of the heat storage tank, the air pressure of the low-pressure air storage chamber, the air pressure of the high-pressure air storage chamber and the power storage power, power generation power, heat storage power and heating power is: in, is the air pressure value of the low pressure air storage chamber, is the air pressure in the high pressure air storage chamber, is the calorific value of the heat storage tank, and are the relationship coefficients between the pressure change rate of the low-pressure gas storage tank and the gas mass flow rate flowing through the compressor and the expander, k mc,k,t and k mex,k,t are the relationship coefficients between the gas mass flow rate flowing through the compressor / expander and the compression power / generating power, and are the relationship coefficients between the pressure change rate of the high-pressure gas storage tank and the gas mass flow rate flowing through the compressor and the expander, and are the relationship coefficients between the heat change rate of the heat storage tank and the gas mass flow rate flowing through the compressor and the expander, k wh,k and k hl,k are the relationship coefficients between the heat change rate of the heat storage tank and the heat storage power and heating power, P c,k,t is the compression power of the k-node compressor at time t, P ex,k,t is the power generation power of the k-node expander at time t, P wh,k,t is the heat storage power of node k at time t, P hl,k,t is the heating power of node k at time t.

3. The capacity planning method for a combined heat and power compressed carbon dioxide energy storage power station according to claim 2 is characterized in that: The air pressure calculation formula of the low-pressure air storage chamber is: p l,k,min ≤p l,k,t ≤p l,k,max Among them, p l,k,t and are the gas pressure value and pressure change rate of the low-pressure gas storage chamber at node k at time t, V l is the volume of the low pressure air storage chamber, R g is the gas constant, γ is the adiabatic index of carbon dioxide, m ex,k,t is the mass flow rate of carbon dioxide flowing into the expander at node k at time t, T ind is the temperature of the gas entering the low-pressure gas storage chamber after multi-stage heating and expansion, m c,k,t is the mass flow rate of carbon dioxide flowing into the compressor at node k at time t, T l is the gas temperature in the low-pressure gas storage chamber, p l,k,t-1 is the gas pressure value of the low-pressure gas storage chamber at node k at time t, Δt is the length of the time interval, and p l,k,min is the lower limit of the air pressure in the low pressure air storage chamber, p l,k,max It is the upper limit of the air pressure in the low-pressure air storage chamber; The air pressure calculation formula of the high-pressure air storage chamber is: p h,k,min ≤p h,k,t ≤p h,k,max Among them, p h,k,t and are the gas pressure value and pressure change rate of the high-pressure gas storage chamber at node k at time t, V h is the volume of the high pressure gas storage chamber, R g is the gas constant; γ is the adiabatic index of carbon dioxide, m ex,k,t is the mass flow rate of carbon dioxide flowing through the expander at node k at time t, T ing is the temperature of the gas entering the high-pressure gas storage chamber after multi-stage compression and cooling, m c,k,t is the mass flow rate of carbon dioxide flowing out of the compressor at node k at time t, T h is the gas temperature in the high pressure gas storage chamber, p h,k,min is the lower limit of the pressure in the high pressure storage chamber, p h,k,max It is the upper limit of the gas pressure in the high-pressure gas storage chamber; The heat calculation formula of the heat storage tank absorbed during the compression process is: Among them, ε c is the heat transfer coefficient between the heat carrier medium and carbon dioxide gas, T C is the temperature of the heat medium in the heat storage tank, m c,k,t is the mass flow rate of carbon dioxide flowing out of the compressor at node k at time t, c p is the specific heat capacity of carbon dioxide at constant pressure, N c is the total number of compressor stages, T cin (i) is the inlet temperature of the i-th stage compressor, β c (i) is the compression ratio of the i-th compressor, γ is the adiabatic index of carbon dioxide; The heat released by the heat storage tank during the expansion process is calculated as follows: Among them, ε c is the heat transfer coefficient between the heat carrier medium and carbon dioxide gas, m ex,k,t is the mass flow rate of carbon dioxide flowing through the expander at node k during period t, N ex is the total number of expander stages, T exin (j) is the inlet temperature of the j-th stage expander, β ex (j) is the expansion ratio of the j-th expander, η ex (j) is the isentropic efficiency of the j-th expander, γ is the adiabatic index of carbon dioxide; The heat calculation formula in the heat storage tank is: Q H,k,t =Q H,k,t-1 +(P Qc,k,t -P Qex,k,t )Δt+(P cwh,k,t -P chl,k,t )Δt; Q H,k,min ≤Q H,k,t ≤Q H,k,max ; Among them, Q h,k,t is the energy stored in the heat storage tank of the compressed carbon dioxide energy storage power station at node k at time t, P cwh,k,t is the heat storage power of CCES absorbing heat from the heat source at node k at time t, P chl,k,t is the heating power of CCES at node k at time t; Q h,k,min and Q h,k,max are the lower and upper limits of the energy stored in the thermal storage tank respectively.

4. The capacity planning method for a combined heat and power compressed carbon dioxide energy storage power station according to claim 2, characterized in that: The calculation formula of the compressor compression power is: Among them, P c,k,t is the total compression power of node k in period t, m c,k,t is the mass flow rate of carbon dioxide entering the compressor at node k during period t, c p is the specific heat capacity of carbon dioxide at constant pressure, N c is the total number of compressor stages, T cin (i) is the inlet temperature of the i-th stage compressor, β c (i) is the compression ratio of the i-th compressor, γ is the adiabatic index of carbon dioxide, η c (i) is the isentropic efficiency of the i-th stage compressor; The calculation formula of the expander power generation power is: Among them, P ex,k,t is the total power of the k-node expander in period t, m ex,k,t is the mass flow rate of carbon dioxide flowing through the expander at node k during period t, N ex is the total number of expander stages, T exin (j) is the inlet temperature of the j-th stage expander, β ex (j) is the expansion ratio of the j-th expander, η ex (j) is the isentropic efficiency of the j-th stage expander, and γ is the adiabatic index of carbon dioxide.

5. The capacity planning method for a combined heat and power compressed carbon dioxide energy storage power station according to claim 1, characterized in that: The preset constraints include: CCES operation constraints; The calculation formula of the operation constraint condition is: s c,t +s ex,t ≤1s c,t ,s ex,t ∈{0,1}; s c,t P cmin ≤P c,t ≤s c,t P cmax ; s ex,t P exmin ≤P ex,t ≤s ex,t P cmax ; Among them, s c,t 、s ex,t are 0-1 variables of the charge and discharge states of the compressed carbon dioxide energy storage power station at time t; P cmin , P cmax are the minimum and maximum compression power of the compressed carbon dioxide energy storage power station respectively; P exmin , P cmax are respectively the minimum and maximum power generation power of the compressed carbon dioxide energy storage power station.

6. The capacity planning method for a combined heat and power compressed carbon dioxide energy storage power station according to claim 5, characterized in that: The preset constraints also include: electrical balance constraints and thermal balance constraints; The electrical balance constraint condition is: P rein,t +P grid,t +P ex,t =P c,t +P eload,t ; Among them, P rein,t is the actual grid active power of renewable energy generation at time t, P grid,t is the power purchased from the main grid at time t, P ex,t is the CCES power generation at time t, P c,t is the electric power absorbed at time t, P eload,t is the power absorbed by the electrical load at time t; The thermal balance constraints are: P hsou,t +P mh,t +P chl,t =P cwh,t +P hload,t ; Among them, P hsou,t is the heating power of the local heat source at time t, P mh,t is the heating power of the main heating network at time t, P chl,t is the heating power provided by CCES to the regional heat load at time t, P cwh,t is the heat storage power P representing the heat absorbed by CCES from the heat source at time t hload,t is the power absorbed by the heat load at time t.

7. The capacity planning method for a combined heat and power compressed carbon dioxide energy storage power station according to any one of claims 1 to 6, characterized in that: The cost minimization principle of the carbon dioxide energy storage power station capacity planning model is: minC total =C inv +C run ; C inv =[c1P c +c2P ex +c3P wh +c4P hl +c5(V h +V l )+c6Q H ]; Among them, C total is the total cost of the compressed carbon dioxide energy storage power station, C inv is the total investment cost, C run is the total operating cost, c1 and c2 are the unit compression power and investment cost of compression power respectively, c3 and c4 are the unit heat storage power and investment cost of heating power respectively; c5 is the unit capacity investment cost of gas storage room, c6 is the unit capacity investment cost of heat storage tank, π c , π ex are the annual operation and maintenance costs per unit compression power and expansion power of the compressed carbon dioxide energy storage power station, c ele,t is the price of electricity purchased from the main grid at time t, P grid,t is the power purchased from the main grid at time t, c re,t is the cost of renewable energy abandonment at time t, P re,t , P rein,t They are the renewable energy power generation active power and the actual grid active power at time t respectively.

8. The capacity planning method for a combined heat and power compressed carbon dioxide energy storage power station according to any one of claims 1 to 6, characterized in that: The linearizing process of the carbon dioxide energy storage power station capacity planning model includes: The carbon dioxide energy storage power station capacity planning model is linearized based on the big M method.

9. A capacity planning system for a combined heat and power compressed carbon dioxide energy storage power station, characterized in that: include: A corresponding relationship acquisition module, which is used to obtain the corresponding relationship between the heat of the heat storage tank, the air pressure of the low-pressure gas storage chamber, the air pressure of the high-pressure gas storage chamber and the storage power, the power generation power, the heat storage power and the heating power in the compressed carbon dioxide energy storage power station; A model building module, which is used to build a capacity planning model for a compressed carbon dioxide energy storage power station based on the corresponding relationship, and to perform capacity planning in combination with a cost minimization principle under the premise of satisfying preset constraints; The planning calculation module is used to linearize the capacity planning model of the carbon dioxide energy storage power station, calculate and solve the linearized capacity planning model of the carbon dioxide energy storage power station through a linear optimization solver, and obtain the capacity configuration result of the carbon dioxide energy storage power station.

10. An electronic device, characterized in that: include: at least one processor; And a memory connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor executes the capacity planning method for a cogeneration compressed carbon dioxide energy storage power station as described in any one of claims 1-8.

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