Method for configuring capacity of multi-element energy storage system based on compressed air energy storage system

Abstract

A kind of multi-energy storage system capacity configuration method based on compressed air energy storage system, by establishing the multi-energy storage system model of compressed air energy storage system, the difference power of the multi-energy storage system based on compressed air energy storage system is calculated, and the difference power is carried out wavelet packet decomposition and reconstruction;Then energy balance adjustment is carried out, and the capacity of super capacitor, battery, compressed air energy storage system, heat storage tank, cold storage tank and the initial pressure ratio in gas chamber are optimized and configured, with the minimum economic cost and the minimum environmental protection cost as objective function, the initial population is calculated using genetic algorithm and the fitness is calculated according to the objective function, then energy balance adjustment and capacity configuration optimization are carried out, and the results are tested;The capacity of each energy storage device is obtained by obtaining the optimal solution through the TOPSIS method.

Description

Technical Field

[0001] This invention relates to the field of comprehensive energy utilization. Specifically, it relates to a method for configuring the capacity of a multi-element energy storage system based on a compressed air energy storage system. Background Technology

[0002] Current research on the optimal configuration of multi-element energy storage systems mainly focuses on the power allocation and capacity selection of batteries and supercapacitors, with relatively few studies involving compressed air energy storage systems. Furthermore, most studies treat compressed air simply as an energy storage element and employ simplified models. Research on the capacity configuration of thermal and cold storage tanks is primarily within integrated energy systems, and there is a lack of research on energy storage systems and their optimal configuration that consider the key parameters of compressed air and integrate thermal, cold, and electrical storage.

[0003] The literature "Energy Control Strategy for Hybrid Energy Storage System of Compressed Air and Supercapacitor" considers the working principle and operating characteristics of the compressed air-supercapacitor multi-element energy storage system, and proposes an adaptive control method based on a load-tracking complementary control structure, as well as an energy distribution management method by controlling the maximum efficiency point and the maximum power point.

[0004] The paper "Microgrid Composite Energy Storage Technology and Cost Analysis Including Compressed Air Energy Storage" proposes a reasonable and effective system energy management strategy for multi-element energy storage systems that include batteries, supercapacitors, and compressed air, based on the dynamic response of various energy storage methods. Both of the aforementioned papers focus on the power allocation and control strategies of energy storage devices, considering only the energy storage characteristics of compressed air energy storage systems without considering their synergistic characteristics of cooling, heating, and electricity.

[0005] Patent CN202011596819.0 establishes a game-theoretic framework for the capacity allocation of a multi-entity integrated energy system. The strategies for the wind power generation subsystem, photovoltaic power generation subsystem, combined cooling, heating, and power (CCHP) subsystem, and compressed air energy storage subsystem are defined by their respective capacities. The payoff function used in this game model is obtained based on the annual payment costs of the distributed power station. The equilibrium of the game is solved, and the configured capacities of the wind power generation subsystem, photovoltaic power generation subsystem, CCHP subsystem, and compressed air energy storage subsystem are output. This patent considers the coordinated supply of cooling, heating, and power, but it does not refine the compressed air energy storage system model and ignores the impact of its key parameters on cooling and heating output.

[0006] Current research on multi-element energy storage systems is largely focused on the microgrid field and energy storage devices, with insufficient research on multi-element energy storage systems that integrate multiple energy storage methods such as electricity, heat, and cold storage, and their optimal configuration. Some scholars have studied multi-element energy storage models coupling compressed air, batteries, and supercapacitors; however, these studies did not consider the interrelationships and influences between the main parameters of the energy storage components, especially the coupling relationships between parameters such as temperature and pressure in compressed air energy storage systems. Furthermore, they only applied the electricity storage function of compressed air energy storage systems and did not delve into their combined cooling, heating, and power (CCHP) characteristics. Summary of the Invention

[0007] To address the problems and shortcomings of the existing technology, this invention proposes a method for configuring the capacity of a multi-element energy storage system based on a compressed air energy storage system, comprising the following steps:

[0008] Step (1): Establish a multi-element energy storage system based on compressed air energy storage system. The system includes power supply equipment, energy storage equipment, heating equipment, cooling equipment, and user end. Power supply equipment includes wind power generation, photovoltaic power generation, power grid and expander power generation. Energy storage equipment includes supercapacitors, batteries, compressed air energy system, thermal storage tank, and cold storage tank. Heating equipment includes electric heating machine. Cooling equipment includes electric chiller and absorption chiller. The cooling and heating capacity of the entire system is provided by compressed air energy storage system, thermal storage tank, cold storage tank, absorption chiller, electric chiller and electric heating machine. Calculate wind power, photovoltaic power and user end load power.

[0009] Step (2): Calculate the differential power of the multi-element energy storage system based on the compressed air energy storage system, and perform wavelet packet decomposition and reconstruction on the differential power. Then, allocate the power of the differential power after wavelet packet decomposition and reconstruction to the compressed air energy storage system power, battery power, and supercapacitor power respectively, and obtain the compressed air energy storage system power, battery power, and supercapacitor power.

[0010] Step (3) Perform energy balance adjustment on the supercapacitor, battery and compressed air energy storage system of the energy storage device to obtain the adjusted power of the supercapacitor, battery and compressed air energy storage system of the energy storage device.

[0011] Step (4): Based on the adjusted power of the supercapacitor, battery, and compressed air energy storage system obtained in step (3), calculate the rated capacity E of the supercapacitor, battery, and compressed air energy storage system. C Based on the rated capacity E of the aforementioned energy storage devices—supercapacitors, batteries, and compressed air energy storage systems— C Calculate the real-time state of charge (SOC) of the supercapacitor, battery, and compressed air energy storage system of the above energy storage devices;

[0012] Step (5) optimizes the capacity of the supercapacitor, battery, compressed air energy storage system, thermal storage tank, and cold storage tank in the energy storage equipment, as well as the initial pressure ratio in the gas storage chamber, with the objective function being the lowest economic cost and the lowest environmental impact. The constraints include upper and lower limits of equipment power, state of charge constraints, initial and final energy constraints, thermal balance constraints, cold balance constraints, thermal storage tank constraints, and cold storage tank constraints. After steps (1) and (2), a genetic algorithm is used to initialize the population and calculate the fitness according to the objective function. Then, the energy balance adjustment in steps (3) and (4) is performed. And capacity configuration optimization, and the results are verified; if the constraints are met, the population is the first generation population. Then, after selection crossover mutation, steps (3) and (4) are repeated, and the same constraints are verified. If the constraints are met, the population is merged. If not, it returns to the selection crossover mutation step. Then, non-dominated sorting and crowding calculation are performed to obtain a new population. The above steps are repeated until the termination condition is met to output the Pareto optimal solution set. The optimal solution is obtained by the TOPSIS method to obtain the capacity of supercapacitor, battery, compressed air energy storage system, thermal storage tank and cold storage tank.

[0013] Specifically, the formula for calculating the differential power of the multi-element energy storage system based on the compressed air energy storage system in step (2) is as follows:

[0014] P b =P w +P p -P load

[0015] P b For differential power, kW; P w P represents wind power; p Photovoltaic power, kW; P load The power of the user-end load is expressed in kW.

[0016] Specifically, the energy balance adjustment process in step (3) is as follows: First, its power Psc is adjusted by ΔE; ΔE is compensated by the battery to obtain the reference power Psc_r of the supercapacitor; the battery obtains new power, and then the battery power is adjusted and compensated by the compressed air energy storage system to obtain the reference power Pba_r of the battery; at the same time, the compressed air energy storage system obtains new power, and finally the compressed air energy storage system is adjusted and compensated by the power grid to obtain the reference power Pca_r of the compressed air energy storage system.

[0017] Specifically, the real-time state of charge (SOC) of the supercapacitor and the battery in step (4) is expressed as follows:

[0018]

[0019] In the formula, E(t) represents the cumulative energy change over time t.

[0020] In a compressed air energy storage system, the real-time state of charge (SOC) is represented by the pressure ratio β as follows:

[0021]

[0022] In the formula β min and β max These are the minimum and maximum pressure ratios of the compressed air energy storage system, respectively.

[0023] Specifically, the economic cost in step (5) is expressed by the following formula:

[0024] C cost =C1+C2+C3

[0025] In the formula, C cost C1 represents the total cost of the system per day, in yuan; C2 represents the initial investment depreciation cost of the system, in yuan; C3 represents the operation and management cost of the system, in yuan; and C4 represents the electricity cost purchased from the grid by the system, in yuan.

[0026] Environmental friendliness is expressed by the following formula:

[0027] CDE=E grid ·CDE grid

[0028] In the formula, CDE represents CO2 emissions, in kg; E grid This represents the electricity purchased by the system from the main power grid, in kWh; CDE grid This indicates the CO2 emission factor; kg / kWh.

[0029] Beneficial effects:

[0030] 1. This invention relates to a multi-element energy storage system based on a compressed air energy storage system. The system is powered by a combined power supply system comprised of wind power, photovoltaic (PV) power, and an energy storage system. Wind power and PV power generation serve as the primary energy source for the microgrid. A hybrid energy storage system, consisting of a compressed air energy storage system, lithium batteries, and supercapacitors, acts as the energy management device bus for the microgrid, ensuring its reliability. The heating and cooling energy is provided by the compressed air energy storage system, hot and cold water tanks, an absorption chiller, an electric chiller, and an electric heating generator. The compressed air energy storage system transfers a portion of the collected heat to the heat storage tank and stores the remainder in the heat storage tank for use during the expansion phase. Simultaneously, it recovers the final stage air to obtain cooling capacity. If the cooling load is insufficient and there is a heat surplus, the absorption chiller and electric chiller supplement the cooling capacity; if the heating load is insufficient, the electric heating generator supplements the heat. The entire system achieves rational energy distribution by controlling the start-up, shutdown, and operation mode of each key component.

[0031] 2. This invention is used to configure the capacity of a multi-element energy storage system based on compressed air energy storage, fully utilizes the characteristics of energy storage devices, smooths the volatility of wind power connected to microgrids, and combines thermal and cold storage tanks to effectively manage the heat, cold, and electricity generated by the compressed air energy storage system. It can better meet users' needs for energy diversity, while achieving optimal economy and environmental protection under the premise of reliability. The capacity configuration of energy storage devices takes into account economy, reliability, and environmental protection.

[0032] 3. The multi-element energy storage system based on compressed air energy storage system of the present invention considers that the heat output of compressed air energy storage system is closely related to the pressure ratio in the gas storage chamber. Therefore, the initial pressure ratio in the gas storage chamber affects the heat output in the entire cycle. Genetic algorithm is used to optimize the initial pressure ratio in the gas storage chamber, the initial state of charge (SOC) of the supercapacitor and battery, and the capacity of the thermal storage tank and cold storage tank. The optimization results are more reasonable. Attached Figure Description

[0033] Figure 1 This is a flowchart of the multi-element energy storage system based on compressed air energy storage system of the present invention.

[0034] Figure 2 Thevenin equivalent circuit diagram for a storage battery

[0035] Figure 3 This is the equivalent circuit diagram of a supercapacitor.

[0036] Figure 4 This is a flowchart of the capacity configuration method for a multi-element energy storage system based on a compressed air energy storage system according to the present invention.

[0037] Figure descriptions: M: Electric motor; AC1 / AC2: Compressor; HE1 / HE2: Cooling heat exchanger; EX1 / EX2: Heat exchanger; P1 / P2: Pump; HE3 / HE4: Heating heat exchanger; G: Generator; AE1 / AE2: Expander; GSC: Gas storage chamber; TV1 / TV2: Throttling valve; HOT: Thermal storage tank; COT: Cold storage tank; HWT: Thermal storage tank; CWT: Cold storage tank; users: User end. Detailed Implementation

[0038] The present invention will be further described in detail below with reference to the embodiments and accompanying drawings, but the embodiments of the present invention are not limited thereto.

[0039] Step (1): Establish a multi-element energy storage system based on compressed air energy storage system. The system includes power supply equipment, energy storage equipment, heating equipment, cooling equipment, and user end. Power supply equipment includes wind power generation, photovoltaic power generation, power grid and expander power generation. Energy storage equipment includes supercapacitors, batteries, compressed air energy system, thermal storage tanks, and cold storage tanks. Heating equipment includes electric heating machines. Cooling equipment includes electric chillers and absorption chillers. The cooling and heating capacity of the entire system is provided by compressed air energy storage system, thermal storage tanks, cold storage tanks, absorption chillers, electric chillers and electric heating machines. Calculate wind power, photovoltaic power and user end load power.

[0040] Specifically, during the energy storage phase, the electric motor M drives the compressor units AC1 and AC2 to compress air. The high-temperature, high-pressure air then enters the cooling heat exchangers HE1 and HE2. Simultaneously, the heat storage medium flows from the cold storage tank COT to the cooling heat exchangers HE1 and HE2 via pump P1, cooling the high-temperature, high-pressure air. The cooled compressed air is then stored in the air storage chamber GSC via the throttle valve TV1. The heat storage medium absorbs the heat from the compressed air, and part of it is collected in the heat storage tank HOT. The remaining part exchanges heat with the heat exchanger EX2 and then enters the cold storage tank COT for use in the next cycle.

[0041] During the energy release phase, high-pressure air flows out from the gas storage chamber GSC through the throttle valve TV2 and enters the heating heat exchangers HE3 and HE4 to absorb the heat from the heat storage medium flowing out of the heat storage tank HOT. Then, the heated high-pressure air enters the expanders AE1 and AE2 to drive the generator G to generate electricity. The heat storage medium is cooled and collected in the cold storage tank COT for use in the next cycle. The air discharged from the expander is sent to the user end after waste heat recovery through the heat exchanger EX1.

[0042] During the energy storage stage, the compression process of the compressor can be considered as an adiabatic and variable process, and the outlet temperature of the i-th stage compressor is:

[0043]

[0044] In the formula, Let be the intake temperature of the i-th stage compressor, in K; The outlet air temperature of the i-th stage compressor; β c is the single-stage pressure ratio of the compressor; n is the adiabatic index of the air.

[0045] The total power consumption of the compressor is:

[0046]

[0047] In the formula: W c The total power consumption of the compressor is p0; the ambient pressure is p0 in Pa; V is the total power consumption of the compressor. gsc The volume of the gas storage chamber is m. 3 ;Rg Let J be the gas constant, kg. -1 ·K -1 T0 is the ambient temperature, K; β min β is the minimum pressure ratio of the gas storage chamber; max c is the maximum pressure ratio of the gas storage chamber. p The specific heat of air at constant pressure is J·kg -1 ·K -1 .

[0048] The compressor outlet air is cooled by the heat storage medium in the cooling heat exchanger, and the outlet temperature of the i-th stage cooling heat exchanger is:

[0049]

[0050] In the formula Let T be the outlet air temperature of the i-th stage cooling heat exchanger, in K; cold Let K be the temperature of the cold storage tank, and ε be the heat exchanger efficiency.

[0051] The heat generated during the entire air compression process can be expressed as:

[0052] Q h =∫c s (T hot -T0)dm (4)

[0053] In the formula Q h The heat generated during the entire air compression process is J;c s Specific heat capacity of the heat storage medium, J·kg -1 ·K -1 ;T hot t is the temperature of the heat storage tank, K; m is the mass of the heat storage medium, kg; T0 is the ambient temperature, K.

[0054] In a gas storage chamber with constant wall temperature, the relationship between pressure and temperature versus time can be obtained:

[0055]

[0056]

[0057] In the formula, T is the temperature of the gas storage chamber, K; p is the pressure ratio of the gas storage chamber; T in q represents the temperature of the compressed air at the inlet of the gas storage chamber, in K. c Mass flow rate of compressed air at the inlet of the gas storage chamber, kg·s -1 k is the convective heat transfer coefficient, W·m -2 ·K -1 A gsc The surface area of ​​the gas storage chamber is m. 2 ;T w The wall temperature of the gas storage chamber, K; cv The specific heat capacity of air at constant volume, J·kg -1 ·K -1 V gsc The volume of the gas storage chamber is m. 3 .

[0058] During the interval between energy storage and energy release, the changes in pressure and temperature over time in the constant-wall-temperature gas storage chamber can be expressed as:

[0059]

[0060]

[0061] The relationship between pressure, temperature, and time in the gas storage chamber during the energy release process is as follows:

[0062]

[0063]

[0064] In the formula, q e The mass flow rate of high-pressure air at the outlet of the gas storage chamber is expressed in kg·s. -1 .

[0065] Compressed air from the gas storage chamber enters the heating heat exchanger to absorb heat. The outlet air temperature of the i-th stage heating heat exchanger is:

[0066]

[0067] In the formula, Let be the outlet air temperature of the i-th stage heat exchanger, in K; Let be the inlet temperature of the i-th stage heat exchanger, K; ε be the heat exchanger efficiency.

[0068] The heated high-pressure air eventually enters the expander for expansion, and the outlet air temperature of the expander is:

[0069]

[0070] In the formula, Let β be the outlet temperature of the i-th stage expander, in K; e is the single-stage pressure ratio of the expander; n is the air adiabatic index.

[0071] The expansion work generated by the system is:

[0072]

[0073] In the formula, W e For the expansion generated by the system

[0074] The cooling capacity of the system is:

[0075]

[0076] In the formula: T e,outlet The outlet temperature of the final stage expander, in K.

[0077] The Thevenin equivalent circuit model structure of a storage battery is as follows: Figure 2 As shown, it is mainly composed of open-circuit voltage U OCV ohmic internal resistance R S Polarization internal resistance R P and polarization capacitor C P It consists of four parts.

[0078] According to Kirchhoff's laws and the law of conservation of energy, we obtain...

[0079]

[0080] U L =U OCV -U P -I L ·R s (16)

[0081]

[0082] In the formula, U P U is the polarization voltage, V; L For terminal voltage, V; I L For battery current, A, P L Power input or output by the battery, in W.

[0083] The simplified equivalent circuit diagram of a supercapacitor is as follows: Figure 3 As shown, the ideal capacitor C sc and equivalent series resistance R sc Series connection. Assuming that each individual supercapacitor has the same resistance and capacitance values, the characteristics of resistance and capacitance do not change after being connected in series and parallel. Therefore, the equivalent model of a simple supercapacitor bank can be represented by an RC network.

[0084] Supercapacitor current:

[0085]

[0086] In the formula C sc Let F be the capacitance of an ideal capacitor.

[0087] Internal voltage of a supercapacitor:

[0088]

[0089] In the formula U sc0 Let V be the initial internal voltage.

[0090] Supercapacitor terminal voltage:

[0091]

[0092] In the formula R sc The resistance is the equivalent series resistance, expressed in Ω.

[0093] Supercapacitor power:

[0094]

[0095] The thermal storage tank HWT is used to store excess heat and will supply it to users and for absorption chiller refrigeration when needed. Its heat at time t is as follows:

[0096] Q hw (t)=Q hw (t-1)+[Q re,caes (t)+Q dr (t)-(Q re (t)+Q xr (t))]Δτ (22)

[0097] In the formula: Q hw (t) represents the heat stored in the thermal storage tank at time t, in J; Q hw (t-1) represents the amount of heat stored in the thermal storage tank at time t-1, in J; Q re,caes (t) represents the output thermal power (W) of the compressed air energy storage system to the heat load at time t; Q dr (t) represents the output thermal power of the electric heating engine at time t, in W; Q re (t) represents the thermal power required by the user at time t, in W; Q xr (t) represents the absorbed heat power of the absorption chiller at time t, in W; Δτ is the interval time, in s.

[0098] The cold storage tank (CWT) is used to store excess cooling capacity from the compressed air output and to supplement cooling when the cooling capacity generated by the compressed air is insufficient to meet the cooling load. Its cooling capacity at time t is as follows:

[0099] Q leng,hw (t)=Q leng,hw (t-1)+[Q l,caes (t)+Q xl (t)+Q dl (t)-Q leng (t)]Δτ (23)

[0100] In the formula, Q hw (t) represents the amount of cold stored in the cold storage tank at time t, J; Q hw (t-1) represents the amount of cold stored in the cold storage tank at time t-1, J; Q l,caes(t) represents the refrigeration power of compressed air energy storage expansion at time t, in W; Q xl (t) represents the output cooling power of the absorption chiller at time t, in W; Q dl (t) represents the output cooling power of the electric chiller at time t, in W; Q leng (t) represents the cooling power required by the user at time t, in W.

[0101] Electric refrigeration / heating units are used to supplement cooling / heating when the cooling / heating load is not met. Their cooling / heating output is as follows:

[0102] Q d =E g η d (twenty four)

[0103] In the formula Q d For the amount of cold / heat produced, J;E g Represents the amount of electricity used for cooling / heating, in J; η d The efficiency of electric cooling / heating.

[0104] Step (2): Calculate the differential power of the multi-element energy storage system based on the compressed air energy storage system, and perform wavelet packet decomposition and reconstruction on the differential power. Then, allocate the power of the differential power after wavelet packet decomposition and reconstruction to the compressed air energy storage system power, battery power, and supercapacitor power respectively, and obtain the compressed air energy storage system power, battery power, and supercapacitor power.

[0105] The formula for calculating the differential power of a multi-element energy storage system based on compressed air energy storage is as follows:

[0106] P b =P w +P p -P load (25)

[0107] P b For differential power, kW; P w P represents wind power; p Photovoltaic power, kW; P load User-side load power, in kW;

[0108] The wavelet packet decomposition algorithm is as follows:

[0109]

[0110] In the formula These are the low-frequency coefficients of the nth level wavelet packet decomposition; P represents the high-frequency coefficients of the nth-level wavelet packet decomposition; n-1,0 (t) represents the reconstructed signal from the (n-1)th level wavelet packet decomposition; a k-2lb represents the low-pass filter coefficients of wavelet packet decomposition. k-2l These are the high-pass filter coefficients for wavelet packet decomposition;

[0111] The reconstruction algorithm is as follows:

[0112]

[0113] In the formula: P n,0 (t) represents the low-frequency signal reconstructed from the nth wavelet packet; P n,1 (t) represents the high-frequency signal reconstructed from the nth wavelet packet; h l-2k The low-pass filter coefficients for wavelet packet reconstruction; g l-2k High-pass filter coefficients for wavelet packet reconstruction; and These are low-frequency reconstruction coefficients; and These are the high-frequency reconstruction coefficients.

[0114] The differential power is then allocated through wavelet packet decomposition and reconstruction to the compressed air energy storage system, battery power, and supercapacitor power, respectively. The power allocation calculation method is as follows:

[0115]

[0116] S n,i P represents the signal of the i-th node in the n-th layer after reconstruction. caes Power of the compressed air energy storage system; P bat P represents the battery power. sc This refers to the power of the supercapacitor.

[0117] Step (3) involves energy balance adjustment of the supercapacitor, battery, and compressed air energy storage system of the energy storage device to obtain the adjusted power of the supercapacitor, battery, and compressed air energy storage system.

[0118] Specifically, the energy storage power is assumed to be negative and the energy release power to be positive. To ensure continuous operation of the system, i.e., the energy state at the initial state is not greater than the energy state at the final state, and considering the energy loss and energy storage efficiency issues in the energy storage system during the energy storage and release process, energy balance adjustment is required after obtaining the power changes of the three energy storage elements. The specific process is as follows: Since the supercapacitor has the highest power frequency and the smallest amount of electricity, its power Psc is first adjusted, and the adjustment amount is ΔE, which is calculated by equation (29); ΔE is compensated by the battery to obtain the reference power Psc_r of the supercapacitor; the battery obtains new power, and the battery power is then adjusted, which is compensated by the compressed air energy storage system to obtain the reference power Pba_r of the battery; at the same time, the compressed air energy storage system obtains new power, and finally the compressed air energy storage system is adjusted, which is compensated by the main grid to obtain the reference power Pca_r of the compressed air energy storage system.

[0119] The formula for calculating the adjustment amount is as follows:

[0120] ΔE=∑P s ×ΔT×η s -∑P r ×ΔT / η r (29)

[0121] In the formula, ηs and ηr are the charging and discharging efficiencies of the energy storage system, respectively; Es and Er are the stored energy and released energy of the energy storage system in one calculation cycle, respectively; Ps and Pr are the stored energy power and released energy power, respectively.

[0122] The adjusted power of the energy storage element is as follows:

[0123] P new =P old +ΔE / T (30)

[0124] In the formula P new The power is expressed in kW; P. old The value represents the power before adjustment, in kW, and T is a time period, in seconds.

[0125] The compensated power of the energy storage element is as follows:

[0126] P ac =P bc -ΔE / T (31)

[0127] In the formula P ac Power after compensation, expressed in kW; P bc This indicates the power before compensation, in kW.

[0128] Step (4): Based on the adjusted power of the supercapacitor, battery, and compressed air energy storage system obtained in step (3), calculate the required rated capacity E of the supercapacitor, battery, and compressed air energy storage system. C Based on the rated capacity E required by the aforementioned energy storage devices, including supercapacitors, batteries, and compressed air energy storage systems... C Calculate the real-time state of charge (SOC) of the above energy storage device;

[0129] Specifically, based on the power allocation calculations described above, the reference powers of the three energy storage components—supercapacitor, battery, and compressed air energy storage system—are Psc_r, Pba_r, and Pca_r, respectively; Psc_r, Pba_r, and Pca_r are denoted as matrix P. R The reference power P R The maximum absolute value is the rated power P of the energy storage system. c The three power values ​​are accumulated separately, and the cumulative energy reference value E within one cycle is calculated. R Then the required rated capacity E for each type of energy storage system can be calculated using equation (32). C Using this capacity value as a known condition, we performed operational calculations for three types of energy storage systems.

[0130]

[0131] In the formula, P R The reference power is ΔT, where ΔT is the time step; E is the reference power for each type of energy storage. Rmax and E Rmin The maximum and minimum values ​​of the cumulative energy; SOC max and SOC min These represent the maximum and minimum allowed values ​​of the State of Charge (SOC) for each type of energy storage system; SOC0 is the initial value of the SOC for each type of energy storage system. To ensure continuous operation of the system, the energy storage system needs to meet the balance of stored / released energy during a typical day, meaning that the state variables at the end of the day are not less than their initial values.

[0132] The real-time state of charge (SOC) in supercapacitors and batteries is expressed as follows:

[0133]

[0134] In the formula, E(t) represents the cumulative energy change over time t.

[0135] In a compressed air energy storage system, the real-time state of charge (SOC) is represented by the pressure ratio β as follows:

[0136]

[0137] In the formula β min and βmax These are the minimum and maximum pressure ratios of the compressed air energy storage system, respectively.

[0138] Step (5) optimizes the configuration of the capacity of the supercapacitor, battery, compressed air energy storage system, thermal storage tank, and cold storage tank of the energy storage equipment; as well as the initial pressure ratio in the gas storage chamber. The objective function is to minimize economic cost and environmental impact. The constraints include upper and lower limits of equipment power, state of charge constraints, initial and final energy constraints, thermal balance constraints, cold balance constraints, thermal storage tank constraints, and cold storage tank constraints.

[0139] Specifically, such as Figure 4 As shown, the heat output of the compressed air energy storage system is closely related to the pressure ratio inside the storage chamber, so the initial pressure ratio inside the storage chamber affects the heat output of the entire cycle. A genetic algorithm is used to optimize the initial pressure ratio inside the storage chamber and the capacity of the supercapacitor, battery, compressed air energy storage system, thermal storage tank, and cold storage tank. After steps (1) and (2), the population is initialized using a genetic algorithm and the fitness is calculated according to the objective function. Then, steps (3) and (4) are performed to adjust the energy balance and optimize the capacity configuration, and the results are verified. If the constraints are met, the population is the first generation. Then, steps (3) and (4) are repeated after selection, crossover and mutation, and the same constraints are verified. If the constraints are met, the population is merged. If not, the process returns to the selection, crossover and mutation step. Then, non-dominated sorting and crowding calculation are performed to obtain a new population. The above steps are repeated until the termination condition is met and the Pareto optimal solution set is output. The optimal solution is obtained by using the TOPSIS method to obtain the capacity of each energy storage device.

[0140] The objective function and constraints are as follows:

[0141] The objective function is as follows:

[0142] (1) Economic Costs

[0143] C cost =C1+C2+C3 (35)

[0144] In the formula, C cost C1 represents the total cost of the system per day, in yuan; C2 represents the initial investment depreciation cost of the system, in yuan; C3 represents the operation and management cost of the system, in yuan; and C4 represents the electricity cost purchased from the grid by the system, in yuan.

[0145]

[0146] In the formula, i represents the i-th device, which here refers to batteries, supercapacitors, electric heating engines, electric chillers, absorption chillers, compressed air energy storage related equipment; N represents the total number of devices; m represents the service life of each device; k represents the equipment depreciation rate (interest rate); C i E represents the capacity investment cost of the i-th device, in yuan / kWh; di P represents the rated capacity of the i-th device, in kWh; t represents time, in kWh. i (t) represents the output power of the i-th device at time t, in kW; P yi Let represent the annual output power of the i-th device, in kW.

[0147]

[0148] In the formula, C2 represents the system's operation and management costs, in yuan; C mi This represents the operating and management cost coefficient of the i-th device.

[0149]

[0150] In the formula, C3 represents the system's cost of purchasing electricity from the main power grid, in yuan; C grid (t) represents the grid electricity price at time t, in yuan / kW; P grid (t) represents the amount of electricity (kW) that the system purchases from the grid at time t.

[0151] (2) Environmental friendliness

[0152] CDE=E grid ·CDE grid (39)

[0153] In the formula, CDE represents CO2 emissions, in kg; E grid This represents the electricity purchased by the system from the main power grid, in kWh; CDE grid This indicates the CO2 emission factor; kg / kWh.

[0154] The constraints are as follows:

[0155] Power upper and lower limits constraints for each device

[0156]

[0157] In the formula: P i (t) represents the output electrical power of the i-th device at time t, in kW; Let represent the minimum output power of the i-th device at time t, in kW; Let represent the maximum output power of the i-th device at time t, in kW.

[0158] State of charge constraints

[0159] SOC min ≤SOC(t)≤SOC max (41)

[0160] In the formula, SOC min State of Charge (SOC) represents the minimum state of charge of an energy storage device. max The maximum state of charge of the energy storage device

[0161] Initial and final energy constraints

[0162] SOC end ≥SOC0 (42)

[0163] In the formula, SOC end SOC0 represents the final state of charge of the energy storage device; SOC0 represents the initial state of charge of the energy storage device.

[0164] Thermal equilibrium constraint

[0165] Q r,caes (t)+Q dr (t)+Q r,hw (t)=Q re (t)+Q xr (t) (43)

[0166] In the formula, Q r,caes (t) represents the output thermal power of the compressed air energy storage system at time t, in kW; Q dr (t) represents the output thermal power of the electric heating engine at time t, in kW; Q r,hw (t) represents the output thermal power of the thermal storage tank at time t, in kW; Q re (t) represents the thermal power required by the user at time t, in kW; Q xr (t) represents the absorbed heat power of the absorption chiller at time t, in kW.

[0167] Cold equilibrium constraint

[0168] Q xl (t)+Q dl (t)+Q leng,hw (t)=Q leng (t) (44)

[0169] In the formula, Q xl (t) represents the output cooling power of the absorption chiller at time t, in kW; Q dl (t) represents the output cooling power of the electric chiller at time t, in kW; Q l,caes (t) represents the compressed air energy storage expansion and refrigeration power at time t, kW; Q leng,hw (t) represents the cooling power output of the cold storage tank at time t, in kW; Q leng(t) represents the cooling power required by the user at time t, in kW.

[0170] thermal storage tank constraints

[0171]

[0172] In the formula, Q hw (t) represents the heat storage value of the heat storage tank at time t, in kWh; This indicates the minimum heat storage capacity of the thermal storage tank, expressed in kWh. This indicates the maximum heat storage capacity of the thermal storage tank, expressed in kWh.

[0173] Cold storage tank constraints

[0174]

[0175] In the formula, Q cw (t) represents the heat storage value of the cold storage tank at time t, in kWh; This indicates the minimum heat storage capacity of the cold storage tank, expressed in kWh. This indicates the maximum heat storage capacity of the cold storage tank, expressed in kWh.

[0176] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, and are not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical applications, or improvements to the prior art of the embodiments, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for configuring the capacity of a multi-element energy storage system based on compressed air energy storage, characterized in that: The method includes the following steps: Step (1): Establish a multi-element energy storage system based on compressed air energy storage system. The system includes power supply equipment, energy storage equipment, heating equipment, cooling equipment, and user end. Power supply equipment includes wind power generation, photovoltaic power generation, power grid and expander power generation. Energy storage equipment includes supercapacitors, batteries, compressed air energy storage system, thermal storage tank, and cold storage tank. Heating equipment includes electric heating machine. Cooling equipment includes electric chiller and absorption chiller. The cooling and heating capacity of the entire system is provided by compressed air energy storage system, thermal storage tank, cold storage tank, absorption chiller, electric chiller and electric heating machine. Calculate wind power, photovoltaic power and user end load power. Step (2): Calculate the differential power of the multi-element energy storage system based on the compressed air energy storage system, and perform wavelet packet decomposition and reconstruction on the differential power. Then, allocate the power of the differential power after wavelet packet decomposition and reconstruction to the compressed air energy storage system power, battery power, and supercapacitor power respectively, and obtain the compressed air energy storage system power, battery power, and supercapacitor power. Step (3) Perform energy balance adjustment on the supercapacitor, battery and compressed air energy storage system of the energy storage device to obtain the adjusted power of the supercapacitor, battery and compressed air energy storage system of the energy storage device. Step (4): Based on the adjusted power of the supercapacitor, battery, and compressed air energy storage system obtained in step (3), calculate the rated capacity E of the supercapacitor, battery, and compressed air energy storage system. C Based on the rated capacity E of the aforementioned energy storage devices—supercapacitors, batteries, and compressed air energy storage systems— C Calculate the real-time state of charge (SOC) of the supercapacitor, battery, and compressed air energy storage system of the above energy storage devices; Step (5) optimizes the capacity of the supercapacitor, battery, compressed air energy storage system, thermal storage tank, and cold storage tank in the energy storage equipment, as well as the initial pressure ratio in the gas storage chamber, with the objective function being the lowest economic cost and the lowest environmental impact. The constraints include upper and lower limits of equipment power, state of charge constraints, initial and final energy constraints, thermal balance constraints, cold balance constraints, thermal storage tank constraints, and cold storage tank constraints. After steps (1) and (2), a genetic algorithm is used to initialize the population and calculate the fitness according to the objective function. Then, the energy balance adjustment in steps (3) and (4) is performed. And capacity configuration optimization, and the results are verified; if the constraints are met, the population is the first generation population. Then, after selection crossover mutation, steps (3) and (4) are repeated, and the same constraints are verified. If the constraints are met, the population is merged. If not, it returns to the selection crossover mutation step. Then, non-dominated sorting and crowding calculation are performed to obtain a new population. The above steps are repeated until the termination condition is met to output the Pareto optimal solution set. The optimal solution is obtained by the TOPSIS method to obtain the capacity of supercapacitor, battery, compressed air energy storage system, thermal storage tank and cold storage tank.

2. The capacity configuration method for a multi-element energy storage system based on a compressed air energy storage system according to claim 1, characterized in that: The formula for calculating the differential power of the multi-element energy storage system based on the compressed air energy storage system in step (2) is as follows: P b =P w +P p -P load P b For differential power, kW; P w P represents wind power; p Photovoltaic power, kW; P load The power of the user-end load is expressed in kW.

3. The capacity configuration method for a multi-element energy storage system based on a compressed air energy storage system according to claim 1, characterized in that: The specific process of energy balance adjustment in step (3) is as follows: First, its power Psc is adjusted by ΔE; ΔE is compensated by the battery to obtain the reference power Psc_r of the supercapacitor; the battery obtains new power, and then the battery power is adjusted and compensated by the compressed air energy storage system to obtain the reference power Pba_r of the battery; at the same time, the compressed air energy storage system obtains new power, and finally the compressed air energy storage system is adjusted and compensated by the power grid to obtain the reference power Pca_r of the compressed air energy storage system.

4. The capacity configuration method for a multi-element energy storage system based on a compressed air energy storage system according to claim 1, characterized in that: In step (4), the real-time state of charge (SOC) of the supercapacitor and the battery is expressed as follows: In the formula, E(t) is the cumulative energy change within time t, and SOC0 is the initial value of the state of charge (SOC) of the energy storage device. In a compressed air energy storage system, the real-time state of charge (SOC) is represented by the pressure ratio β as follows: In the formula, βmin and βmax are the minimum and maximum pressure ratios of the compressed air energy storage system, respectively.

5. The capacity configuration method for a multi-element energy storage system based on a compressed air energy storage system according to claim 1, characterized in that: The economic cost in step (5) is expressed by the following formula: C cost =C1+C2+C3 In the formula, C cost C1 represents the system's total cost per day, in yuan; C2 represents the system's initial investment depreciation cost, in yuan; C3 represents the system's operation and management cost, in yuan; and C4 represents the system's electricity purchase cost from the grid, in yuan. Environmental friendliness is expressed by the following formula: CDE=E grid ·CDE grid In the formula, CDE represents CO2 emissions, in kg; E grid This represents the electricity purchased by the system from the main power grid, in kWh; CDE grid This indicates the CO2 emission factor; kg / kWh.

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