A comprehensive energy system optimization design method, device, equipment and medium

Abstract

The present invention belongs to the technical field of integrated energy system optimization, and specifically relates to an integrated energy system optimization design method, device, equipment and medium. This scheme includes power-type energy storage equipment, energy-type energy storage equipment and compressed air energy storage system. By combining multiple energy storage equipment, the advantages of multiple energy storage devices are complementary. On the intraday time scale, supercapacitors as power-type energy storage equipment bear high-frequency fluctuation components, and lithium batteries as energy-type energy storage equipment bear low-frequency fluctuations. The power fluctuations are decomposed by variational mode decomposition to determine the power borne by the power-type energy storage equipment and the energy-type energy storage equipment respectively. The annual operating cost is minimized as the optimization goal, and the rated power and rated capacity of the supercapacitor and lithium battery are determined. The integrated energy system obtained by this method can effectively smooth the volatility of renewable energy and user power load in actual operation, and ensure the stability, flexibility and economy of the system.

Description

Technical Field

[0001] The present invention belongs to the technical field of integrated energy system optimization, and specifically relates to an integrated energy system optimization design method, device, equipment and medium. Background Art

[0002] As the world's fossil energy shortage and ecological environment deteriorate, accelerating the transformation of the energy structure dominated by fossil energy to renewable energy is the key to solving the current energy and environmental problems. The integrated energy system (IES) can achieve multi-energy complementarity and energy cascade utilization. It is an energy system with diversified structure, flexible operation and strong controllability. Adding renewable energy to the integrated energy system can reduce the use of natural gas and pollution emissions, and further promote energy conservation, emission reduction and consumption reduction.

[0003] However, the intermittent, random and volatile nature of renewable energy, as well as the uncertainty of user loads, pose challenges to the safe and stable operation of the integrated energy system. As a core component of the integrated energy system, energy storage equipment can play an important role in absorbing renewable energy and shifting peak loads. However, a single energy storage technology cannot simultaneously meet the stability and flexibility of the integrated energy system. Summary of the invention

[0004] The purpose of the present invention is to provide a method, device, equipment and medium for optimizing the design of an integrated energy system, so as to solve the problem in the prior art that a single energy storage technology cannot simultaneously meet the stability and flexibility of the integrated energy system.

[0005] In order to achieve the above object, the present invention adopts the following technical solution:

[0006] In a first aspect, the present invention provides a method for optimizing the design of an integrated energy system, comprising the following steps:

[0007] Obtaining a mathematical model of a pre-constructed integrated energy system; wherein the integrated energy system includes new energy power generation equipment, energy supply equipment, power-type energy storage equipment, energy-type energy storage equipment and a compressed air energy storage system;

[0008] Obtain the pre-defined day-ahead operation strategy of the integrated energy system, as well as typical day hourly load data and typical day wind and solar output data;

[0009] Based on the mathematical model of the integrated energy system, the day-ahead operation strategy of the integrated energy system, the hourly load data of the typical day, and the wind and solar output data of the typical day, a day-ahead optimization model is constructed with the goal of optimal economic efficiency, and the day-ahead optimization model is solved to obtain the output plan of the energy supply equipment and the compressed air energy storage system;

[0010] Determine the wind and solar power output data and the user's daily power load during the day, and determine the energy deviation between the power supply of the integrated energy system and the user's daily power load based on the output plan of the energy supply equipment and the compressed air energy storage system, the wind and solar power output data and the user's daily power load during the day; use the energy deviation as a power instruction, perform variational mode decomposition on the power instruction, and obtain K Intrinsic mode functions;

[0011] According to the preset frequency standard K The intrinsic mode functions are divided to obtain high-frequency components and low-frequency components; the high-frequency components and low-frequency components are reconstructed to obtain high-frequency power and low-frequency power; wherein the high-frequency power is borne by the power-type energy storage device, and the low-frequency power is borne by the energy-type energy storage device;

[0012] Based on the high-frequency power and low-frequency power, an energy storage optimization model is constructed with the goal of optimizing the overall economic efficiency of power-type energy storage equipment and energy-type energy storage equipment; the energy storage optimization model is solved to obtain the rated power and rated capacity of the power-type energy storage equipment, and the rated power and rated capacity of the energy-type energy storage equipment, respectively.

[0013] Furthermore, the new energy power generation equipment includes wind power generation equipment and photovoltaic power generation equipment; the energy supply equipment includes internal combustion engines, organic Rankine cycle units, trough solar collectors, heat storage systems, jacket water heat exchangers, tail heat exchangers, absorption heat pumps, electric refrigerators and gas boilers; the power-type energy storage equipment is a supercapacitor; and the energy-type energy storage equipment is a lithium battery.

[0014] Furthermore, a pre-formulated day-ahead operation strategy of the integrated energy system is obtained, wherein the day-ahead operation strategy of the integrated energy system is specifically as follows:

[0015] Priority is given to using electricity generated by new energy power generation equipment to meet the user's power load. If there is a surplus of electricity, the compressed air energy storage system is used to store redundant power generation; if there is a power gap, the partial load rate of the internal combustion engine is determined at this time; when the partial load rate of the internal combustion engine is greater than or equal to the preset value, the internal combustion engine and the organic Rankine cycle unit are turned on to generate electricity. If the power generation of the internal combustion engine and the organic Rankine cycle unit still cannot meet the power gap, the compressed air energy storage system is used to generate electricity. If the power generation of the compressed air energy storage system still cannot meet the power gap, electricity is purchased from the power grid to meet the power gap; when the partial load rate of the internal combustion engine is less than When the preset value is reached, the compressed air energy storage system is directly used to generate electricity. If the compressed air energy storage system still cannot meet the electricity gap, electricity is purchased from the power grid to meet the electricity gap. The absorption heat pump and the electric refrigeration machine work together to meet the user's cooling load. If there is a cooling gap, the gas boiler will provide heat to the absorption heat pump to make up for the cooling gap. The trough solar collector and the tail heat exchanger will jointly meet the user's heat load. If there is excess heat, the heat storage system will store the excess heat. If there is a heat gap, the heat storage system will provide heat. If the heat storage system still cannot meet the heat gap, the gas boiler will be turned on to make up for the heat gap.

[0016] Furthermore, based on the mathematical model of the integrated energy system, the day-ahead operation strategy of the integrated energy system, the hourly load data of the typical day, and the wind and solar output data of the typical day, a day-ahead optimization model is constructed with the goal of optimal economic efficiency; wherein the day-ahead optimization model is as follows:

[0017] Construct the objective function with the goal of economic optimization:

[0018]

[0019]

[0020]

[0021]

[0022]

[0023] Where: OMC It represents the economic target operation and maintenance cost of the integrated energy system; C ope , C grid , C gas They are operation and maintenance cost, power purchase cost from the power grid, and natural gas purchase cost; c ope,i Indicates the device i Unit capacity cost; E i,t For equipment i existt Always contribute; m i For equipment i quantity; c gas is the price of natural gas; N gas,t for t Total natural gas consumption of the system at any given moment, including t Gas consumption of internal combustion engine at any time N ICE,t and gas consumption of gas boilers N GB,t ; c grid,t for t The electricity purchase price at any given moment; E grid,t for t Purchase electricity at any time;

[0024] Determine the constraints of the day-ahead optimization model as follows:

[0025]

[0026]

[0027]

[0028] Where: E ICE,t is the power generation of the internal combustion engine at time t; E ORC,t is the power generation of the organic Rankine cycle unit at time t; E PV,t is the power generation of the photovoltaic power generation equipment at time t; E WT,t is the power generation of the wind power generation equipment at time t; E grid,t is the amount of electricity purchased from the power grid at time t; E EC,t is the power consumption of the refrigerator at time t; H GB,t The heat provided by the gas boiler at time t; H tank,t is the heat stored in the hot water tank at time t; H AHP,t is the heat consumed by the absorption heat pump at time t; E CAE,out,t , E CAE,in ,t They are the discharge capacity and storage capacity of the compressed air energy storage system at time t respectively; H ex,t is the heat generated by the heat exchanger at time t; Eload,t , H load,t and C load,t are the electricity, heating and cooling loads of the user at time t respectively; C AHP,t is the cooling capacity of the absorption heat pump at time t; C EC,t is the cooling capacity of the electric refrigerator at time t; C waste,t is the cooling capacity abandoned at time t.

[0029] Further, based on the output plan of the energy supply equipment and the compressed air energy storage system, the wind and solar power output data within the day, and the user's power load within the day, the energy deviation between the power supply of the integrated energy system and the user's power load within the day is determined, including:

[0030]

[0031]

[0032] Where: Subscript t 2 is the intraday time interval; subscripts rq and rn represent the day before and the day, respectively; P HESS The power instruction that the energy storage device needs to bear; P ICE is the power of the internal combustion engine; P ORC Generating power for an organic Rankine cycle unit; P WT The power generated by the wind turbine; P PV is the photovoltaic power generation power; P grid Purchase power for the grid; P load The power of the user's electrical load; P EC It is the cooling load power of the user; P CAE is the power of the compressed air energy storage system; P SC is the power of the supercapacitor; P BAT is the power of lithium battery.

[0033] Furthermore, the high-frequency component and the low-frequency component are reconstructed respectively to obtain the high-frequency power and the low-frequency power, including:

[0034]

[0035] Wherein, t represents the time; P H, P L are high frequency power and low frequency power respectively; is the eigenmode function; is the number of low-frequency components; K Represents the number of intrinsic mode functions.

[0036] Furthermore, an energy storage optimization model is constructed with the goal of optimizing the overall economic efficiency of power-type energy storage equipment and energy-type energy storage equipment; wherein the energy storage optimization model is as follows:

[0037]

[0038]

[0039]

[0040] Where: C all The total annual cost of lithium batteries and supercapacitors; C BAT , C SC They are the investment and operating costs of lithium batteries and supercapacitors; λ is the discount rate; Y BAT , Y SC They are the service life of lithium batteries and supercapacitors respectively; β BAT,1 , β BAT,2 , β BAT,3 They are the unit power cost, unit capacity cost, and operation and maintenance cost of lithium batteries; β SC,1 , β SC,2 , β SC,3 They are the unit power cost, unit capacity cost, and operation and maintenance cost of supercapacitors; P SC,N is the rated power of the supercapacitor; E SC,N is the rated capacity of the supercapacitor; P BAT,N is the rated power of the lithium battery; E BAT,N is the rated capacity of the lithium battery.

[0041] In a second aspect, the present invention provides a comprehensive energy system optimization design device, comprising:

[0042] A first data acquisition module is used to acquire a mathematical model of a pre-constructed integrated energy system; wherein the integrated energy system includes new energy power generation equipment, energy supply equipment, power type energy storage equipment, energy type energy storage equipment and a compressed air energy storage system;

[0043] The second data acquisition module is used to obtain the pre-defined day-ahead operation strategy of the integrated energy system, as well as the typical day hourly load data and the typical day wind and solar output data;

[0044] A day-ahead optimization module is used to construct a day-ahead optimization model based on the mathematical model of the integrated energy system, the day-ahead operation strategy of the integrated energy system, the hourly load data of the typical day, and the wind and solar output data of the typical day, with the goal of optimizing economic efficiency, solve the day-ahead optimization model, and obtain the output plan of the energy supply equipment and the compressed air energy storage system;

[0045] The deviation calculation module is used to determine the wind and solar power output data and the user's electric load during the day, and determine the energy deviation between the power supply of the integrated energy system and the user's electric load during the day based on the output plan of the energy supply equipment and the compressed air energy storage system, the wind and solar power output data during the day, and the user's electric load during the day; the energy deviation is used as the power instruction, and the power instruction is subjected to variational mode decomposition to obtain K Intrinsic mode functions;

[0046] The power decomposition module is used to divide the K The intrinsic mode functions are divided to obtain high-frequency components and low-frequency components; the high-frequency components and low-frequency components are reconstructed to obtain high-frequency power and low-frequency power; wherein the high-frequency power is borne by the power-type energy storage device, and the low-frequency power is borne by the energy-type energy storage device;

[0047] The energy storage optimization module is used to construct an energy storage optimization model based on the high-frequency power and the low-frequency power with the goal of optimizing the overall economic efficiency of the power-type energy storage device and the energy-type energy storage device; solve the energy storage optimization model to obtain the rated power and rated capacity of the power-type energy storage device, and the rated power and rated capacity of the energy-type energy storage device, respectively.

[0048] According to a third aspect of the present invention, there is provided an electronic device, comprising a processor and a memory, wherein the processor is used to execute a computer program stored in the memory to implement the above-mentioned integrated energy system optimization design method.

[0049] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, the integrated energy system optimization design method as described above is implemented.

[0050] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0051] The integrated energy system optimization design method provided by the present invention designs an integrated energy system including power-type energy storage equipment, energy-type energy storage equipment and compressed air energy storage system. By combining multiple energy storage equipment, the advantages of multiple energy storage devices are complementary, which is more advantageous in smoothing the fluctuations of renewable energy and improving the economy of the system.

[0052] The integrated energy system optimization design method provided by the present invention selects a compressed air energy storage system as an energy storage device on a long time scale before the day, which plays the role of peak shaving and valley filling. A mathematical model of each device in the integrated energy system is established, and the operation strategy of energy utilization is determined. Then, the economy is taken as the optimization goal, and the key parameters of the equipment operation are taken as the optimization variables. The optimal operation strategy of the integrated energy system before the day under the economic goal is optimized, which effectively improves the economy of the system. On the intraday time scale, the present invention takes into account the volatility of renewable energy and the instability of user electric load in the integrated energy system, selects supercapacitors as power-type energy storage devices to bear high-frequency fluctuation components, selects lithium batteries as energy-type energy storage devices to bear low-frequency fluctuations, and constructs a hybrid energy storage system together with the compressed air energy storage system. Further, the power fluctuation is decomposed by variational mode decomposition, and the power borne by the power-type energy storage device and the energy-type energy storage device is determined. The annual operating cost is minimized as the optimization goal, and the rated power and rated capacity of the supercapacitor and the lithium battery are determined. The integrated energy system in this scheme can effectively smooth the volatility of renewable energy and user electric load, and ensure the stability, flexibility and economy of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A schematic diagram of a flow chart of a comprehensive energy system optimization design method according to an embodiment of the present invention;

[0054] Figure 2 A structural diagram of a comprehensive energy system in an embodiment of the present invention;

[0055] Figure 3 This is a structural block diagram of a device for optimizing and designing a comprehensive energy system according to an embodiment of the present invention;

[0056] Figure 4 The present invention is a structural block diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0057] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0058] Example 1

[0059] like Figure 1 As shown, a comprehensive energy system optimization design method includes the following steps:

[0060] S10. Obtain a pre-built mathematical model of the integrated energy system.

[0061] like Figure 2 As shown, the comprehensive energy system involved in this scheme includes new energy power generation equipment, energy supply equipment, power type energy storage equipment, energy type energy storage equipment and compressed air energy storage system; among them, power type energy storage equipment, energy type energy storage equipment and compressed air energy storage system constitute a hybrid energy storage system. Specifically: New energy power generation equipment includes wind power generation equipment and photovoltaic power generation equipment; wind power generation equipment mainly generates electricity through wind turbines, and photovoltaic power generation equipment mainly generates electricity through photovoltaic panels; energy supply equipment includes internal combustion engines, cylinder jacket water heat exchangers, organic Rankine cycle units (ORC units, Organic RankineCycle), heat storage system, trough solar collector, tail heat exchanger, absorption heat pump, electric refrigerator and gas boiler, etc.; power type energy storage device is supercapacitor; energy type energy storage device is lithium battery; compressed air energy storage system includes first heat exchanger, second heat exchanger, third heat exchanger, fourth heat exchanger, first compressor, second compressor, air storage chamber, first expander, second expander, motor and generator; among them, user return water is heated by the waste heat of internal combustion engine in the cylinder jacket water heat exchanger to become low temperature water, low temperature water enters the first heat exchanger and the second heat exchanger in turn to be heated again to obtain medium temperature water, medium temperature water enters the tail heat exchanger to obtain high temperature water The electric motor drives the first compressor to compress air. The air compressed for the first time is cooled in the first heat exchanger and then enters the second compressor for compression again. The air compressed for the second time is cooled in the second heat exchanger and then stored in the air storage chamber. When the compressed air energy storage system generates electricity, the compressed air in the air storage chamber is heated up for the first time in the third heat exchanger and then enters the first expander to perform work, driving the generator to generate electricity. Then, the compressed air enters the fourth heat exchanger to be heated up again and then enters the second expander to perform work, driving the generator to generate electricity. Or, the compressed air in the air storage chamber directly enters the third heat exchanger and the fourth heat exchanger in turn to be heated up twice, and then enters the second expander to perform work, driving the generator to generate electricity.

[0062] Specifically, the mathematical model of the integrated energy system includes the following:

[0063] 1) Internal combustion engine

[0064] As the main equipment of the integrated energy system, the internal combustion engine has a partial load rate of PLR ICE The calculation formula is as follows:

[0065] (1)

[0066] Where: W ICE and G ICE They are the actual power generation and rated capacity of the internal combustion engine, kW.

[0067] 2) Organic Rankine cycle unit

[0068] Using R113 as the organic working fluid of the organic Rankine cycle unit, the calculation formula for power generation of the organic Rankine cycle unit is as follows:

[0069] (2)

[0070] Where: is the power generation of the organic Rankine cycle unit; q m,R113 is the mass flow rate of organic working fluid, kg / s; h 1 and h 2 are the specific enthalpies of the organic working fluid R113 flowing into and out of the turbine respectively.

[0071] 3) Compressed air energy storage system

[0072] In this scheme, the compressed air energy storage system includes a first heat exchanger, a second heat exchanger, a third heat exchanger, a fourth heat exchanger, a first compressor, a second compressor, an air storage chamber, a first expander, a second expander, a motor and a generator. It should be noted that when the compressed air energy storage system in this scheme is in operation, the air is regarded as an ideal gas with a constant specific heat capacity; the heat capacity of the air is equal to the heat capacity of the heat storage medium; the momentum change and gravitational potential energy change of the fluid in the process are not considered; the working process of the compressor and the expander is adiabatic.

[0073] (1) Energy storage stage

[0074] When storing energy, the air compression process is regarded as an irreversible adiabatic variable process; the compressor outlet air temperature T co,out The calculation formula is as follows:

[0075] (3)

[0076] Where: T co,in is the compressor inlet temperature, K; κ is the adiabatic polytropic index; β c is the pressure ratio of the compressor; η c is the isentropic efficiency of the compressor.

[0077] compression m Compression work of kg air ( W co, J) is obtained by the following formula:

[0078] (4)

[0079] Where: is the constant-pressure specific heat capacity of air, J / (kg·K).

[0080] In addition, the efficiency of the heat exchanger in the compressed air energy storage system As shown in formula (5):

[0081] (5)

[0082] Where: c is the constant pressure specific heat capacity of the corresponding fluid, J / (kg·K); q is the mass flow rate of the fluid in the heat exchanger, kg / s; T in , T out Respectively represent the inlet and outlet fluid temperatures of the heat exchanger, K; subscripts c and h represent the hot and cold fluids, respectively; ( cq ) min Meaning: Take the minimum value of the constant-pressure specific heat capacity in the fluid on the hot and cold sides of the heat exchanger, and the minimum value of the mass flow rate in the fluid on the hot and cold sides of the heat exchanger, and multiply the two minimum values.

[0083] Pressure loss coefficient of heat exchanger See formula (6):

[0084] (6)

[0085] Heat exchanger outlet fluid temperature The calculation formula is as follows:

[0086] (7)

[0087] Where: T 1,in and T 2,in are the temperatures of the different fluids on both sides of the heat exchanger.

[0088] (2) Energy release stage

[0089] Expander outlet air temperature The calculation formula is as follows:

[0090] (8)

[0091] Where: T e,in is the expander inlet air temperature, K; β eis the expansion ratio of the expander; is the isentropic efficiency of the expander.

[0092] m kg of air does work in the expander Calculated by formula (9):

[0093] (9)

[0094] (3) Gas storage chamber

[0095] ①Energy storage process

[0096] During the energy storage process, there is no material and energy exchange between the gas storage chamber and the outside world, and the pressure inside the gas storage chamber is β The temperature changes with time:

[0097] (10)

[0098] (11)

[0099] Where: T in is the inlet air temperature of the air storage chamber, K; h c is the convection heat transfer coefficient between gas and the wall of the gas storage chamber, W / (m 2 K); A c is the internal surface area of ​​the gas storage chamber, m 2 ; T w is the inner wall temperature of the gas storage chamber, K; T is the air temperature in the air storage room, K; t is time, s; q m,b is the air mass flow rate at the air storage chamber inlet, kg / s; p 0 is atmospheric pressure, Pa; c v is the specific heat capacity of air at constant volume, J / (kg·K); R g is the gas constant, J / (kg·K); V is the volume of the air storage chamber, m 3 .

[0100] ②Energy release process

[0101] The relationship between the pressure ratio and temperature of the gas storage chamber during energy release is as follows:

[0102] (12)

[0103] (13)

[0104] Where: q m,e is the air mass flow rate at the outlet of the air storage chamber, kg / s.

[0105] ③The interval process between energy storage and energy release

[0106] During the interval between energy storage and energy release, the relationship between the pressure ratio and temperature in the gas storage chamber over time is:

[0107] (14)

[0108] (15)

[0109] (4) Throttle valve

[0110] (16)

[0111] Where: h val,in and h val,out They represent the specific enthalpy of gas at the inlet and outlet of the throttle valve, J / kg respectively.

[0112] 4) Trough solar collector

[0113] The amount of heat collected by trough solar collectors ( H PTC , kW) and the effective solar radiation intensity ( R eff , kW / m 2 ) as shown in equations (17) and (18):

[0114] (17)

[0115] (18)

[0116] (19)

[0117] Where: A PTC is the collecting area of ​​the trough solar collector, m 2 ; R b,n is the direct solar radiation intensity, kW / m 2 ; is the incident angle, °; is the declination angle, °; is the solar hour angle, °.

[0118] Declination and solar hour angle The calculation formula is:

[0119] (20)

[0120] (twenty one)

[0121] (twenty two)

[0122] (twenty three)

[0123] (twenty four)

[0124] Where: N The number of days from January 1st of each year to the calculation time; AST is solar time, min; LST is the local standard time, min; SL The longitude of the local standard time zone is selected as the longitude of Beijing time, which is 120° east longitude; LL is the local longitude, °; ET It is the time difference caused by the movement and rotation speed change of the earth when it revolves around the sun, min.

[0125] Effective heat collection of trough solar collectors H PTC,eff As shown in the formula:

[0126] (25)

[0127] Where: c p,oil is the specific heat capacity of PTC thermal oil at constant pressure, kJ / (kg·K); m oil is the mass flow rate of heat transfer oil, kg / s; T oil,out and T oil,in are the inlet and outlet temperatures of the heat transfer oil in the PTC, K; η PTC is the PTC heat collection efficiency, and its calculation formula is H PTC,eff as follows:

[0128] (26)

[0129] Where: a is the intercept efficiency of the trough solar collector, which is selected as 0.762; b and c are the heat loss coefficients, which are selected as 0.2125 and 0.001672 respectively; is the ambient temperature.

[0130] 5) Thermal storage system

[0131] In this scheme, the thermal storage system is a hot water storage tank, and the operation model is as follows:

[0132] (27)

[0133] (28)

[0134] (29)

[0135] Where: H tank ( t ) is a hot water tank t The amount of heat stored in a moment, kW; φ in , φ out are heat storage and heat release power coefficients respectively; H tank,in , H tank,out is the heat storage and output of the hot water storage tank, kW; H in,max , H out,max They are the maximum and minimum heat release power of the hot water tank, kW respectively.

[0136] 6) Jacket water heat exchanger

[0137] The jacket water heat exchanger provides the heat source required for the user's return water. The calculation formula is as follows:

[0138] (30)

[0139] Where: H j,out , H j,in are the heat entering and leaving the jacket water heat exchanger, kW; η j is the heat transfer efficiency of the jacket water heat exchanger, 0.8.

[0140] 7) Wind power generation equipment

[0141] Wind power generation equipment mainly includes wind turbines. The output power of wind turbines ( P WT , kW) and wind speed ( v ,m / s) are as follows:

[0142] (31)

[0143] In the formula,v in , v N , v out They are the cut-in wind speed, rated wind speed, and cut-out wind speed of the fan, m / s; P WT N is the rated power of the fan, in kWh.

[0144] 8) Photovoltaic power generation equipment

[0145] Photovoltaic power generation equipment mainly generates electricity through photovoltaic panels. The power generated by photovoltaic panels ( P PV ( t ), kW) subject to working current ( I ( t ), A), working voltage( V ( t ), V) and actual operating temperature ( t pv,real , ℃). Its actual power generation is determined by formula (32), the actual working current is determined by formula (34), the actual working voltage is determined by formula (35), and the actual working temperature is determined by formula (39).

[0146] (32)

[0147] (33)

[0148] (34)

[0149] (35)

[0150] (36)

[0151] (37)

[0152] Where: P 0 is the theoretical power generation of the photovoltaic panel (kW); f real is the temperature correction coefficient of the photovoltaic panel; f s is the dust accumulation factor, which is taken as 0.98; R eff is the solar radiation intensity, the unit here is W / m 2 ; R eff,0 is the solar radiation of the PV panel under standard conditions, W / m 2 ; I sc,0The area is S m 2 The short-circuit current of the PV panel; I pm0 The area is S m 2 The peak current of the PV panel; V pm0 The area is S m 2 The peak voltage of the PV panel. is the actual operating temperature of the photovoltaic panel, is the ambient temperature.

[0153] 9) Tail heat exchanger

[0154] The tail heat exchanger provides heat ( H ex,out , kW) is shown below:

[0155] (38)

[0156] Where: H ex,in The waste heat released by flue gas to the tail heat exchanger, kW; η ex is the heat transfer efficiency of the rear heat exchanger, 0.8.

[0157] 10) Absorption heat pump

[0158] Cooling capacity of absorption heat pump ( C AHP , kW) is calculated as follows:

[0159] (39)

[0160] Where: H AHP is the heat consumed by the absorption heat pump, kW; COP AHP is the coefficient of performance of the absorption heat pump, and its value is 0.7.

[0161] 11) Electric Refrigerator

[0162] Cooling capacity of electric refrigerator ( C EC , kW) is calculated as follows:

[0163] (40)

[0164] Where: E EC is the power consumption of the electric refrigerator, kW; COP ECis the coefficient of performance of the electric refrigerator, and its value is 4.

[0165] 12) Gas boiler

[0166] The additional load required by the user is provided by the gas boiler, which releases heat. H GB The calculation formula is as follows:

[0167] (41)

[0168] Where: N GB is the natural gas consumption of gas boiler, kW; η GB It is the heat exchange efficiency of gas boiler.

[0169] The gas boiler provides heat to supplement the heat load and cooling load required by the user, so the following formula must also be met:

[0170] (42)

[0171] Where: H GB,h , H GB,c They are the heat and cooling capacity provided by the gas boiler to the user, kW.

[0172] 13) Supercapacitor

[0173] The operation model of supercapacitor is as follows:

[0174] (43)

[0175] (44)

[0176] (45)

[0177] (46)

[0178] (47)

[0179] Where: E SC is the capacity of the supercapacitor, kWh; φ sc is the supercapacitor charge and discharge coefficient; P SC,in , P SC,out are the input and output power of the supercapacitor, kW; P SC,N is the rated power of the supercapacitor, kW; SOCSC is the charge state of the supercapacitor; E SC,N is the rated capacity of the supercapacitor, kWh; t Indicates time.

[0180] 14) Lithium battery

[0181] (48)

[0182] (49)

[0183] (50)

[0184] (51)

[0185] (52)

[0186] Where: E BAT is the capacity of the lithium battery, kWh; φ BAT is the charge and discharge coefficient of lithium battery; P BAT,in , P BAT,out are the input and output power of the lithium battery, kW; P BAT,N is the rated power of the lithium battery, kW; SOC BAT is the state of charge of the lithium battery; E BAT,N is the rated capacity of the lithium battery, kWh; t Indicates time.

[0187] S20. Obtain the pre-defined day-ahead operation strategy of the integrated energy system, as well as the hourly load data on a typical day and the wind and solar output data on a typical day.

[0188] Specifically, the day-ahead operation strategy of the integrated energy system is as follows:

[0189] Priority is given to using electricity generated by new energy power generation equipment to meet the user's power load. If there is a surplus of electricity, the compressed air energy storage system is used to store redundant power generation; if there is a power gap, the partial load rate of the internal combustion engine is determined at this time; when the partial load rate of the internal combustion engine is greater than or equal to the preset value, the internal combustion engine and the organic Rankine cycle unit are turned on to generate electricity. If the power generation of the internal combustion engine and the organic Rankine cycle unit still cannot meet the power gap, the compressed air energy storage system is used to generate electricity. If the power generation of the compressed air energy storage system still cannot meet the power gap, electricity is purchased from the power grid to meet the power gap; when the partial load rate of the internal combustion engine is less than When the preset value is reached, the compressed air energy storage system is directly used to generate electricity. If the compressed air energy storage system still cannot meet the electricity gap, electricity is purchased from the power grid to meet the electricity gap. The absorption heat pump and the electric refrigeration machine work together to meet the user's cooling load. If there is a cooling gap, the gas boiler will provide heat to the absorption heat pump to make up for the cooling gap. The trough solar collector and the tail heat exchanger will jointly meet the user's heat load. If there is excess heat, the heat storage system will store the excess heat. If there is a heat gap, the heat storage system will provide heat. If the heat storage system still cannot meet the heat gap, the gas boiler will be turned on to make up for the heat gap.

[0190] S30. Based on the mathematical model of the integrated energy system, the day-ahead operation strategy of the integrated energy system, the hourly load data of the typical day, and the wind and solar output data of the typical day, a day-ahead optimization model is constructed with the goal of optimal economic efficiency. The day-ahead optimization model is solved to obtain the output plan of the energy supply equipment and the compressed air energy storage system.

[0191] Specifically, the day-ahead optimization model constructed in this solution is as follows:

[0192] Construct the objective function with the goal of economic optimization:

[0193] (53)

[0194] (54)

[0195] (55)

[0196] (56)

[0197] (57)

[0198] Where: OMC (Operation Maintenance Cost) represents the economic target operation and maintenance cost of the integrated energy system; C ope , C grid , C gasThey are operation and maintenance cost, power purchase cost from the power grid, and natural gas purchase cost, RMB; c ope,i Indicates the device i Unit capacity cost; E i,t For equipment i exist t Output at any time, kWh; m i For equipment i quantity; c gas is the natural gas price, which is 0.22 yuan / kWh; N gas,t for t Total natural gas consumption of the system at any given moment, including t Gas consumption of internal combustion engine at any time N ICE,t and gas consumption of gas boilers N GB,t , kWh; c grid,t for t The electricity purchase price at any given moment; E grid,t for t Purchase electricity at any time;

[0199] Determine the constraints of the day-ahead optimization model, including the cooling, heating and electric power balance constraints, as follows:

[0200] (58)

[0201] (59)

[0202] (60)

[0203] Where: Subscript t Indicates the moment; E ICE,t is the power generation of the internal combustion engine at time t; E ORC,t is the power generation of the organic Rankine cycle unit at time t; E PV,t is the power generation of the photovoltaic power generation equipment at time t; E WT,t is the power generation of the wind power generation equipment at time t; E grid,t is the amount of electricity purchased from the power grid at time t; E EC,t is the power consumption of the refrigerator at time t; H GB,t The heat provided by the gas boiler at time t; Htank,t is the heat stored in the hot water tank at time t; H AHP,t is the heat consumed by the absorption heat pump at time t; E CAE,out,t , E CAE,in ,t They are the discharge capacity and storage capacity of the compressed air energy storage system at time t, kWh; H ex,t is the heat generated by the heat exchanger (jacket water heat exchanger, energy storage side heat exchanger and tail heat exchanger) at time t, kWh; E load,t , H load,t and C load,t are the electricity, heating and cooling loads of the user at time t, kWh; C AHP,t is the cooling capacity of the absorption heat pump at time t; C EC,t is the cooling capacity of the electric refrigerator at time t; C waste,t is the cooling capacity abandoned at time t.

[0204] The above-constructed day-ahead optimization model selects the partial load rate of the internal combustion engine PLR ICE , the proportion of flue gas flowing into the organic Rankine cycle unit r ORC , low temperature flue gas temperature entering the tail heat exchanger T s,L , Electric refrigeration ratio r EC As the optimization variable. Among them, the partial load rate of the internal combustion engine PLR ICE Changes will significantly affect the power generation efficiency of the internal combustion engine, and thus affect the energy utilization rate of the system; adjust the proportion of flue gas flowing into the organic Rankine cycle unit according to load demand r ORC The low temperature flue gas temperature entering the rear heat exchanger T s,L , to achieve flexible output of cold, heat and electricity; at the same time, the proportion of electric refrigeration r EC Changes will significantly affect the cooling capacity of the absorption heat pump and electric chiller, and thus affect the system's power consumption and energy efficiency.

[0205] In order to improve the calculation speed, this scheme adopts a parallel genetic algorithm to solve the day-ahead optimization model. At the same time, in order to avoid premature optimization, an adaptive crossover and mutation process is introduced to avoid falling into the local optimal solution.

[0206] S40, determine the wind and solar power output data and the user's power load during the day, and determine the energy deviation between the power supply of the integrated energy system and the user's power load during the day based on the output plan of the energy supply equipment and the compressed air energy storage system, the wind and solar power output data during the day, and the user's power load during the day; use the energy deviation as a power instruction, perform variational mode decomposition on the power instruction, and obtain K An intrinsic mode function.

[0207] Specifically, based on the output plan of the energy supply equipment and the compressed air energy storage system, the wind and solar power output data within the day, and the user's power load within the day, the energy deviation between the power supply of the integrated energy system and the user's power load within the day is determined, including:

[0208] (61)

[0209] (62)

[0210] Where: Subscript t 2 is the intraday time interval, which is 1 min in this scheme; subscripts rq and rn represent the day before and the day, respectively; P HESS The power instruction that the energy storage device needs to bear; P ICE is the power of the internal combustion engine; P ORC Generating power for an organic Rankine cycle unit; P WT The power generated by the wind turbine; P PV is the photovoltaic power generation power; P grid Purchase power for the grid; P load The power of the user's electrical load; P EC It is the cooling load power of the user; P CAE is the power of the compressed air energy storage system; P SC is the power of the supercapacitor; P BAT is the power of lithium battery.

[0211] Specifically, VMD is used to generate the power instructions that the energy storage device needs to bear. P HESS Decomposition; Among them, the genetic algorithm is used to decompose the number of layers K and penalty factor α To search for the best K Intrinsic mode functions (IMFs) are

[0212] S50, according to the preset frequency standard K The intrinsic mode functions are divided to obtain high-frequency components and low-frequency components; the high-frequency components and low-frequency components are reconstructed respectively to obtain high-frequency power and low-frequency power; wherein the high-frequency power is borne by the power-type energy storage device, and the low-frequency power is borne by the energy-type energy storage device.

[0213] Specifically, get K After the intrinsic mode functions (IMFs) are obtained, they are reconstructed according to the response characteristics of different energy storage devices. Specifically, the energy storage devices in this scheme include power energy storage devices and energy energy storage devices; in this scheme, 1 min is selected as the response demarcation point between lithium batteries and supercapacitors, that is, the frequency is greater than 1.67×10 -2 The intrinsic mode function of Hz is used as the high-frequency component, and the frequency is less than 1.67×10 -2 The IMF between Hz is regarded as the low-frequency component.

[0214] Specifically, the high-frequency component and the low-frequency component are reconstructed respectively to obtain the high-frequency power and the low-frequency power, as shown below:

[0215] (63)

[0216] in, P H , P L are high frequency power and low frequency power respectively; is the eigenmode function; is the number of low-frequency components.

[0217] S60. Based on the high-frequency power and the low-frequency power, an energy storage optimization model is constructed with the goal of optimizing the overall economic efficiency of the power-type energy storage device and the energy-type energy storage device; the energy storage optimization model is solved to obtain the rated power and rated capacity of the power-type energy storage device, and the rated power and rated capacity of the energy-type energy storage device, respectively.

[0218] It should be noted that the rated power of the energy storage device shall not be lower than the rated power of the energy storage device. t The power of the charging and discharging tasks that need to be completed at any time, the rated power of supercapacitors and lithium batteries are as follows:

[0219] (64)

[0220] (65)

[0221] (66)

[0222] (67)

[0223] In order to avoid overcharge and over-discharge of energy storage devices during operation, the rated capacity of each energy storage device is calculated based on the maximum and minimum values ​​of the cumulative capacity during operation. The rated capacity of lithium batteries and supercapacitors are as follows:

[0224] (68)

[0225] (69)

[0226] Where: SOC SC,max and SOC SC,min They are the upper and lower limits of the state of charge of the supercapacitor respectively.

[0227] Specifically, the energy storage optimization model constructed in this solution is as follows:

[0228] (70)

[0229] (71)

[0230] (72)

[0231] Where: C all The total annual cost of lithium batteries and supercapacitors; C BAT , C SC are the investment and operation costs of lithium batteries and supercapacitors respectively; λ is the discount rate, %; Y BAT , Y SC They are the service life of lithium batteries and supercapacitors respectively; β BAT,1 , β BAT,2 , β BAT,3 They are the unit power cost, unit capacity cost, and operation and maintenance cost of lithium batteries; β SC,1 , β SC,2 , β SC,3 They are the unit power cost, unit capacity cost, and operation and maintenance cost of supercapacitors; P SC,N is the rated power of the supercapacitor; E SC,N is the rated capacity of the supercapacitor; PBAT,N is the rated power of the lithium battery; E BAT,N is the rated capacity of the lithium battery.

[0232] It can be understood that in this solution, high-frequency power and low-frequency power are obtained, so that the corresponding annual comprehensive cost sum of power-type energy storage equipment and energy-type energy storage equipment can be calculated. Through continuous iterative optimization, the rated power and rated capacity corresponding to the optimal economy are finally obtained.

[0233] In summary, this scheme proposes a collaborative optimization method that can adjust the energy output of the system hour by hour on a long time scale before the day, and then takes economy as the optimization goal, takes the key parameters of equipment operation as the optimization variables, and uses a parallel genetic algorithm to optimize the system, and obtains the optimal operation strategy of the comprehensive energy system before the day under the economic goal, which effectively improves the economy of the system; on the intraday time scale, the present invention takes into account the volatility of renewable energy and the instability of user power load in the comprehensive energy system. Supercapacitors are used as power-type energy storage devices to bear high-frequency fluctuation components, and lithium batteries are selected as short-term energy storage devices to bear low-frequency fluctuations. Then, the power borne by the hybrid energy storage system is decomposed through variational mode decomposition, and the annual operating cost is minimized as the optimization goal, and then the rated power and rated capacity of supercapacitors and lithium batteries are determined. The present invention constructs a hybrid energy storage system by combining different types of energy storage devices such as supercapacitors, lithium batteries and compressed air energy storage, which can further improve the economy of the system while ensuring peak shaving and valley filling, smoothing the fluctuations of renewable energy and user power load.

[0234] Example 2

[0235] like Figure 3 As shown, based on the same inventive concept as the above embodiment, the present invention also provides a comprehensive energy system optimization design device, comprising:

[0236] A first data acquisition module is used to acquire a mathematical model of a pre-constructed integrated energy system; wherein the integrated energy system includes new energy power generation equipment, energy supply equipment, power type energy storage equipment, energy type energy storage equipment and a compressed air energy storage system;

[0237] The second data acquisition module is used to obtain the pre-defined day-ahead operation strategy of the integrated energy system, as well as the typical day hourly load data and the typical day wind and solar output data;

[0238] A day-ahead optimization module is used to construct a day-ahead optimization model based on the mathematical model of the integrated energy system, the day-ahead operation strategy of the integrated energy system, the hourly load data of the typical day, and the wind and solar output data of the typical day, with the goal of optimizing economic efficiency, solve the day-ahead optimization model, and obtain the output plan of the energy supply equipment and the compressed air energy storage system;

[0239] The deviation calculation module is used to determine the wind and solar power output data and the user's electric load during the day, and determine the energy deviation between the power supply of the integrated energy system and the user's electric load during the day based on the output plan of the energy supply equipment and the compressed air energy storage system, the wind and solar power output data during the day, and the user's electric load during the day; the energy deviation is used as the power instruction, and the power instruction is subjected to variational mode decomposition to obtain K Intrinsic mode functions;

[0240] The power decomposition module is used to divide the K The intrinsic mode functions are divided to obtain high-frequency components and low-frequency components; the high-frequency components and low-frequency components are reconstructed to obtain high-frequency power and low-frequency power; wherein the high-frequency power is borne by the power-type energy storage device, and the low-frequency power is borne by the energy-type energy storage device;

[0241] The energy storage optimization module is used to construct an energy storage optimization model based on the high-frequency power and the low-frequency power with the goal of optimizing the overall economic efficiency of the power-type energy storage device and the energy-type energy storage device; solve the energy storage optimization model to obtain the rated power and rated capacity of the power-type energy storage device, and the rated power and rated capacity of the energy-type energy storage device, respectively.

[0242] Example 3

[0243] like Figure 4As shown, the present invention also provides an electronic device 100 for implementing an integrated energy system optimization design method in Example 1; the electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on the at least one processor 102, and at least one communication bus 104. The memory 101 can be used to store the computer program 103, and the processor 102 implements the steps of the integrated energy system optimization design method in Example 1 by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101. The memory 101 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required by at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data (such as audio data) created according to the use of the electronic device 100, etc. In addition, the memory 101 may include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other non-volatile solid-state storage devices. At least one processor 102 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor 102 may be a microprocessor or the processor 102 may also be any conventional processor, etc. The processor 102 is the control center of the electronic device 100, and uses various interfaces and lines to connect various parts of the entire electronic device 100. The memory 101 in the electronic device 100 stores multiple instructions to implement a comprehensive energy system optimization design method, and the processor 102 can execute multiple instructions to achieve:

[0244] Obtaining a mathematical model of a pre-constructed integrated energy system; wherein the integrated energy system includes new energy power generation equipment, energy supply equipment, power-type energy storage equipment, energy-type energy storage equipment and a compressed air energy storage system;

[0245] Obtain the pre-defined day-ahead operation strategy of the integrated energy system, as well as typical day hourly load data and typical day wind and solar output data;

[0246] Based on the mathematical model of the integrated energy system, the day-ahead operation strategy of the integrated energy system, the hourly load data of the typical day, and the wind and solar output data of the typical day, a day-ahead optimization model is constructed with the goal of optimal economic efficiency, and the day-ahead optimization model is solved to obtain the output plan of the energy supply equipment and the compressed air energy storage system;

[0247] Determine the wind and solar power output data and the user's daily power load during the day, and determine the energy deviation between the power supply of the integrated energy system and the user's daily power load based on the output plan of the energy supply equipment and the compressed air energy storage system, the wind and solar power output data and the user's daily power load during the day; use the energy deviation as a power instruction, perform variational mode decomposition on the power instruction, and obtain K Intrinsic mode functions;

[0248] According to the preset frequency standard K The intrinsic mode functions are divided to obtain high-frequency components and low-frequency components; the high-frequency components and low-frequency components are reconstructed to obtain high-frequency power and low-frequency power; wherein the high-frequency power is borne by the power-type energy storage device, and the low-frequency power is borne by the energy-type energy storage device;

[0249] Based on the high-frequency power and low-frequency power, an energy storage optimization model is constructed with the goal of optimizing the overall economic efficiency of power-type energy storage equipment and energy-type energy storage equipment; the energy storage optimization model is solved to obtain the rated power and rated capacity of the power-type energy storage equipment, and the rated power and rated capacity of the energy-type energy storage equipment, respectively.

[0250] Example 4

[0251] If the module / unit integrated in the electronic device 100 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. Computer-readable media may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory and read-only memory (ROM, Read-Only Memory).

[0252] Those skilled in the art will appreciate 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 aspects. Moreover, 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. The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to 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 processes and / or boxes in the flowchart and / or block diagram, may be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that instructions executed by the processor of a computer or other programmable data processing device generate instructions for implementing the functions in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", 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 representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

Claims

1. A comprehensive energy system optimization design method, characterized in that: The following steps are involved: Obtaining a mathematical model of a pre-constructed integrated energy system; wherein the integrated energy system includes new energy power generation equipment, energy supply equipment, power-type energy storage equipment, energy-type energy storage equipment and a compressed air energy storage system; Obtain the pre-defined day-ahead operation strategy of the integrated energy system, as well as typical day hourly load data and typical day wind and solar output data; Based on the mathematical model of the integrated energy system, the day-ahead operation strategy of the integrated energy system, the hourly load data of the typical day, and the wind and solar output data of the typical day, a day-ahead optimization model is constructed with the goal of optimal economic performance. The day-ahead optimization model is solved to obtain the output plan of the energy supply equipment and the compressed air energy storage system. Among them, the optimization variables of the day-ahead optimization model are: the partial load rate of the internal combustion engine PLR ICE , the proportion of flue gas flowing into the organic Rankine cycle unit r ORC , low temperature flue gas temperature entering the tail heat exchanger T s,L , Electric refrigeration ratio r EC ; Determine the wind and solar power output data and the user's daily power load during the day, and determine the energy deviation between the power supply of the integrated energy system and the user's daily power load based on the output plan of the energy supply equipment and the compressed air energy storage system, the wind and solar power output data and the user's daily power load during the day; use the energy deviation as a power instruction, perform variational mode decomposition on the power instruction, and obtain K Intrinsic mode functions; among them, the genetic algorithm is used to decompose the number of layers K and penalty factor α Conduct optimization search; According to the preset frequency standard K The intrinsic mode functions are divided to obtain high-frequency components and low-frequency components; the high-frequency components and low-frequency components are reconstructed to obtain high-frequency power and low-frequency power; the high-frequency power is borne by the power-type energy storage device, and the low-frequency power is borne by the energy-type energy storage device; 1 min is selected as the response demarcation point between lithium batteries and supercapacitors, and the frequency is greater than 1.67×10 -2 The intrinsic mode function of Hz is used as the high-frequency component, and the frequency is less than 1.67×10 -2 The IMF of Hz is taken as the low-frequency component; Based on the high-frequency power and the low-frequency power, an energy storage optimization model is constructed with the goal of optimizing the overall economic efficiency of the power-type energy storage device and the energy-type energy storage device; the energy storage optimization model is solved to obtain the rated power and rated capacity of the power-type energy storage device, and the rated power and rated capacity of the energy-type energy storage device, respectively; The new energy power generation equipment includes wind power generation equipment and photovoltaic power generation equipment; the energy supply equipment includes internal combustion engines, organic Rankine cycle units, trough solar collectors, heat storage systems, jacket water heat exchangers, tail heat exchangers, absorption heat pumps, electric refrigerators and gas boilers; power-type energy storage equipment is supercapacitors; energy-type energy storage equipment is lithium batteries; The day-ahead operation strategy of the integrated energy system is as follows: Priority is given to using electricity generated by new energy power generation equipment to meet the user's power load. If there is a surplus of electricity, the compressed air energy storage system is used to store redundant power generation; if there is a power gap, the partial load rate of the internal combustion engine is determined at this time; when the partial load rate of the internal combustion engine is greater than or equal to the preset value, the internal combustion engine and the organic Rankine cycle unit are turned on to generate electricity. If the power generation of the internal combustion engine and the organic Rankine cycle unit still cannot meet the power gap, the compressed air energy storage system is used to generate electricity. If the power generation of the compressed air energy storage system still cannot meet the power gap, electricity is purchased from the power grid to meet the power gap; when the partial load rate of the internal combustion engine is less than the preset value, the compressed air energy storage system is directly used to generate electricity. If the power generation of the compressed air energy storage system still cannot meet the power gap, electricity is purchased from the power grid to meet the power gap; The absorption heat pump and the electric refrigeration machine work together to meet the user's cooling load. If there is a cooling capacity gap, the gas boiler will provide heat to the absorption heat pump to make up for the cooling capacity gap. The trough solar collector and the tail heat exchanger jointly meet the user's heat load. If there is excess heat, the heat storage system will store the excess heat; if there is a heat gap, the heat storage system will provide heat. If the heat storage system still cannot meet the heat gap, the gas boiler will be turned on to make up for the heat gap; The current optimization model is as follows: Construct the objective function with the goal of economic optimization: Where: OMC It represents the economic target operation and maintenance cost of the integrated energy system; C ope , C grid , C gas They are operation and maintenance costs, grid electricity purchase costs, and natural gas purchase costs; c ope,i Indicates the device i Unit capacity cost; E i,t For equipment i exist t Always contribute; m i For equipment i quantity; c gas is the price of natural gas; N gas,t for t Total natural gas consumption of the system at any given moment, including t Gas consumption of internal combustion engine at any time N ICE,t and gas consumption of gas boilers N GB,t ; c grid,t for t The electricity purchase price at any given moment; E grid,t for t Purchase electricity at any time; Determine the constraints of the day-ahead optimization model as follows: Where: E ICE,t is the power generation of the internal combustion engine at time t; E ORC,t is the power generation of the organic Rankine cycle unit at time t; E PV,t is the power generation of the photovoltaic power generation equipment at time t; E WT,t is the power generation of the wind power generation equipment at time t; E grid,t is the amount of electricity purchased from the power grid at time t; E EC,t is the power consumption of the refrigerator at time t; H GB,t The heat provided by the gas boiler at time t; H tank,t is the heat stored in the hot water tank at time t; H AHP,t is the heat consumed by the absorption heat pump at time t; E CAE,out,t , E CAE,in ,t They are the discharge capacity and storage capacity of the compressed air energy storage system at time t respectively; H ex,t is the heat generated by the heat exchanger at time t; E load,t , H load,t and C load,t are the electricity, heating and cooling loads of the user at time t respectively; C AHP,t is the cooling capacity of the absorption heat pump at time t; C EC,t is the cooling capacity of the electric refrigerator at time t; C waste,t is the amount of cooling abandoned at time t; Based on the output plan of the energy supply equipment and the compressed air energy storage system, the wind and solar power output data within the day, and the user's power load within the day, the energy deviation between the power supply of the integrated energy system and the user's power load within the day is determined, including: Where: Subscript t 2 is the intraday time interval, which is 1 min; subscripts rq and rn represent the day before and the day, respectively; P HESS The power instruction that the energy storage device needs to bear; P ICE is the power of the internal combustion engine; P ORC Generating power for an organic Rankine cycle unit; P WT The power generated by the wind turbine; P PV is the photovoltaic power generation power; P grid Purchase power for the grid; P load The power of the user's electrical load; P EC It is the cooling load power of the user; P CAE is the power of the compressed air energy storage system; P SC is the power of the supercapacitor; P BAT is the power of lithium battery; Reconstruct the high-frequency component and the low-frequency component respectively to obtain the high-frequency power and the low-frequency power, including: Wherein, t represents the time; P H , P L are high frequency power and low frequency power respectively; is the eigenmode function; is the number of low-frequency components; K represents the number of intrinsic mode functions; An energy storage optimization model is constructed with the goal of optimizing the overall economic efficiency of power-type energy storage equipment and energy-type energy storage equipment; wherein the energy storage optimization model is as follows: Where: C all The total annual cost of lithium batteries and supercapacitors; C BAT , C SC They are the investment and operating costs of lithium batteries and supercapacitors; λ is the discount rate; Y BAT , Y SC They are the service life of lithium batteries and supercapacitors respectively; β BAT,1 , β BAT,2 , β BAT,3 They are the unit power cost, unit capacity cost, and operation and maintenance cost of lithium batteries; β SC,1 , β SC,2 , β SC,3 They are the unit power cost, unit capacity cost, and operation and maintenance cost of supercapacitors; P SC,N is the rated power of the supercapacitor; E SC,N is the rated capacity of the supercapacitor; P BAT,N is the rated power of the lithium battery; E BAT,N is the rated capacity of the lithium battery.

2. A comprehensive energy system optimization design device, characterized in that: include: A first data acquisition module is used to acquire a mathematical model of a pre-constructed integrated energy system; wherein the integrated energy system includes new energy power generation equipment, energy supply equipment, power type energy storage equipment, energy type energy storage equipment and a compressed air energy storage system; The second data acquisition module is used to obtain the pre-defined day-ahead operation strategy of the integrated energy system, as well as the typical day hourly load data and the typical day wind and solar output data; The day-ahead optimization module is used to construct a day-ahead optimization model based on the mathematical model of the integrated energy system, the day-ahead operation strategy of the integrated energy system, the hourly load data of the typical day, and the wind and solar output data of the typical day, with the goal of optimal economic performance, solve the day-ahead optimization model, and obtain the output plan of the energy supply equipment and the compressed air energy storage system; wherein, the optimization variables of the day-ahead optimization model are: the partial load rate of the internal combustion engine PLR ICE , the proportion of flue gas flowing into the organic Rankine cycle unit r ORC , low temperature flue gas temperature entering the tail heat exchanger T s,L , Electric refrigeration ratio r EC ; The deviation calculation module is used to determine the wind and solar power output data and the user's electric load during the day, and determine the energy deviation between the power supply of the integrated energy system and the user's electric load during the day based on the output plan of the energy supply equipment and the compressed air energy storage system, the wind and solar power output data during the day, and the user's electric load during the day; the energy deviation is used as the power instruction, and the power instruction is subjected to variational mode decomposition to obtain K Intrinsic mode functions; The power decomposition module is used to divide the K The intrinsic mode functions are divided to obtain high-frequency components and low-frequency components; the high-frequency components and low-frequency components are reconstructed to obtain high-frequency power and low-frequency power; the high-frequency power is borne by the power-type energy storage device, and the low-frequency power is borne by the energy-type energy storage device; 1 min is selected as the response demarcation point between lithium batteries and supercapacitors, and the frequency is greater than 1.67×10 -2 The intrinsic mode function of Hz is used as the high-frequency component, and the frequency is less than 1.67×10 -2 The IMF of Hz is taken as the low-frequency component; An energy storage optimization module is used to construct an energy storage optimization model based on the high-frequency power and the low-frequency power with the goal of optimizing the overall economic efficiency of the power-type energy storage device and the energy-type energy storage device; solve the energy storage optimization model to obtain the rated power and rated capacity of the power-type energy storage device, and the rated power and rated capacity of the energy-type energy storage device, respectively; The new energy power generation equipment includes wind power generation equipment and photovoltaic power generation equipment; the energy supply equipment includes internal combustion engines, organic Rankine cycle units, trough solar collectors, heat storage systems, jacket water heat exchangers, tail heat exchangers, absorption heat pumps, electric refrigerators and gas boilers; power-type energy storage equipment is supercapacitors; energy-type energy storage equipment is lithium batteries; The day-ahead operation strategy of the integrated energy system is as follows: Priority is given to using electricity generated by new energy power generation equipment to meet the user's power load. If there is a surplus of electricity, the compressed air energy storage system is used to store redundant power generation; if there is a power gap, the partial load rate of the internal combustion engine is determined at this time; when the partial load rate of the internal combustion engine is greater than or equal to the preset value, the internal combustion engine and the organic Rankine cycle unit are turned on to generate electricity. If the power generation of the internal combustion engine and the organic Rankine cycle unit still cannot meet the power gap, the compressed air energy storage system is used to generate electricity. If the power generation of the compressed air energy storage system still cannot meet the power gap, electricity is purchased from the power grid to meet the power gap; when the partial load rate of the internal combustion engine is less than the preset value, the compressed air energy storage system is directly used to generate electricity. If the power generation of the compressed air energy storage system still cannot meet the power gap, electricity is purchased from the power grid to meet the power gap; The absorption heat pump and the electric refrigeration machine work together to meet the user's cooling load. If there is a cooling capacity gap, the gas boiler will provide heat to the absorption heat pump to make up for the cooling capacity gap. The trough solar collector and the tail heat exchanger jointly meet the user's heat load. If there is excess heat, the heat storage system will store the excess heat; if there is a heat gap, the heat storage system will provide heat. If the heat storage system still cannot meet the heat gap, the gas boiler will be turned on to make up for the heat gap; The current optimization model is as follows: Construct the objective function with the goal of economic optimization: Where: OMC It represents the economic target operation and maintenance cost of the integrated energy system; C ope , C grid , C gas They are operation and maintenance costs, grid electricity purchase costs, and natural gas purchase costs; c ope,i Indicates the device i Unit capacity cost; E i,t For equipment i exist t Always contribute; m i For equipment i quantity; c gas is the price of natural gas; N gas,t for t Total natural gas consumption of the system at any given moment, including t Gas consumption of internal combustion engine at any time N ICE,t and gas consumption of gas boilers N GB,t ; c grid,t for t The electricity purchase price at any given moment; E grid,t for t Purchase electricity at any time; Determine the constraints of the day-ahead optimization model as follows: Where: E ICE,t is the power generation of the internal combustion engine at time t; E ORC,t is the power generation of the organic Rankine cycle unit at time t; E PV,t is the power generation of the photovoltaic power generation equipment at time t; E WT,t is the power generation of the wind power generation equipment at time t; E grid,t is the amount of electricity purchased from the power grid at time t; E EC,t is the power consumption of the refrigerator at time t; H GB,t The heat provided by the gas boiler at time t; H tank,t is the heat stored in the hot water tank at time t; H AHP,t is the heat consumed by the absorption heat pump at time t; E CAE,out,t , E CAE,in ,t They are the discharge capacity and storage capacity of the compressed air energy storage system at time t respectively; H ex,t is the heat generated by the heat exchanger at time t; E load,t , H load,t and C load,t are the electricity, heating and cooling loads of the user at time t respectively; C AHP,t is the cooling capacity of the absorption heat pump at time t; C EC,t is the cooling capacity of the electric refrigerator at time t; C waste,t is the amount of cooling abandoned at time t; Based on the output plan of the energy supply equipment and the compressed air energy storage system, the wind and solar power output data within the day, and the user's power load within the day, the energy deviation between the power supply of the integrated energy system and the user's power load within the day is determined, including: Where: Subscript t 2 is the intraday time interval, which is 1 min; subscripts rq and rn represent the day before and the day, respectively; P HESS The power instruction that the energy storage device needs to bear; P ICE is the power of the internal combustion engine; P ORC Generating power for an organic Rankine cycle unit; P WT The power generated by the wind turbine; P PV is the photovoltaic power generation power; P grid Purchase power for the grid; P load The power of the user's electrical load; P EC It is the cooling load power of the user; P CAE is the power of the compressed air energy storage system; P SC is the power of the supercapacitor; P BAT is the power of lithium battery; Reconstruct the high-frequency component and the low-frequency component respectively to obtain the high-frequency power and the low-frequency power, including: Wherein, t represents the time; P H , P L are high frequency power and low frequency power respectively; is the eigenmode function; is the number of low-frequency components; K represents the number of intrinsic mode functions; An energy storage optimization model is constructed with the goal of optimizing the overall economic efficiency of power-type energy storage equipment and energy-type energy storage equipment; wherein the energy storage optimization model is as follows: Where: C all The total annual cost of lithium batteries and supercapacitors; C BAT , C SC They are the investment and operating costs of lithium batteries and supercapacitors; λ is the discount rate; Y BAT , Y SC They are the service life of lithium batteries and supercapacitors respectively; β BAT,1 , β BAT,2 , β BAT,3 They are the unit power cost, unit capacity cost, and operation and maintenance cost of lithium batteries; β SC,1 , β SC,2 , β SC,3 They are the unit power cost, unit capacity cost, and operation and maintenance cost of supercapacitors; P SC,N is the rated power of the supercapacitor; E SC,N is the rated capacity of the supercapacitor; P BAT,N is the rated power of the lithium battery; E BAT,N is the rated capacity of the lithium battery.

3. An electronic device, characterized in that: It comprises a processor and a memory, wherein the processor is used to execute a computer program stored in the memory to implement the comprehensive energy system optimization design method as claimed in claim 1.

4. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by the processor, the integrated energy system optimization design method according to claim 1 is implemented.

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