Economical efficiency judgment and optimization method for user-side power energy storage operation mode

Abstract

The invention provides an economical efficiency judgment and optimization method for a user-side power energy storage operation mode. The method comprises the following steps: acquiring basic parameters of an energy storage system and preset parameters of a proposed operation mode; determining the cycle life of the battery in the proposed operation mode; determining a battery calendar life of the proposed operation mode; calculating the daily charge and discharge per kilowatt hour earnings of the energy storage system; determining the service life of the energy storage system in the proposed operation mode; calculating monthly dischargeable electric quantity of the energy storage system; calculating the present value of the accumulated discharge capacity in the service life of the energy storage system; determining a full-life-cycle operation and maintenance cost present value of the system; calculating the leveling charge and discharge cost LCOS of the system; calculating an energy storage system leveling charging and discharging price difference net value LNPD; and judging whether the LNPD is greater than the LCOS or not, and if so, judging that the proposed operation mode meets the economical feasibility requirement. According to the method, accurate economical efficiency judgment can be carried out on the energy storage operation mode, and the optimal operation mode is obtained.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electric power energy storage, in particular to a method for judging and optimizing the economy of a user-side electric power energy storage operation mode. BACKGROUND

[0002] User-side electric power energy storage mainly refers to an energy storage system located at industrial and commercial user sites, which realizes the storage, conversion and release of electric energy through energy storage devices (such as lithium ion batteries, lead-carbon batteries, flow batteries, etc.) to meet the user's own electricity demand, optimize electricity costs, and ensure power supply reliability. The system can realize the following main functions: 1) improve power reliability, when the power supply of the power grid fails or is unstable, the energy storage system can be quickly put into use to provide more stable power supply for industrial and commercial users, ensure the uninterrupted operation of production equipment, and reduce power loss; 2) peak clipping and valley filling, during the low valley period of electricity consumption, store electric energy by charging at low valley price, and release electric energy during the peak period of electricity consumption, so as to reduce peak electricity load and achieve the purpose of reducing peak electricity cost, while also helping to alleviate the peak-valley difference of the power grid and improve the operation efficiency of the power grid; 3) participate in demand response, respond to the demand response signal of the power grid, and adjust the charge and discharge state of the energy storage system, such as discharging during the peak load of the power grid, to assist the power grid in balancing supply and demand, thereby obtaining corresponding economic compensation and policy support; 4) improve power quality, the energy storage system can quickly compensate for voltage sag, voltage swell and flicker, etc. Power quality problems provide qualified power for industrial and commercial equipment with high requirements for power quality, and ensure the reliable operation of equipment and prolong the service life of equipment. Among them, the peak-valley price difference arbitrage based on peak clipping and valley filling is the main profit mode of industrial and commercial electric power energy storage application. Under the time-of-use electricity price policy, industrial and commercial users can store electric energy at low valley price period and release stored electric energy at peak price period by using electric power energy storage system, thereby reducing the electricity purchase cost that needs to be paid at peak price period, and realizing peak-valley price difference arbitrage.

[0003] Peak-valley price difference arbitrage has become the main driving force for the promotion of industrial and commercial energy storage due to its clear policy and mature mode. Correspondingly, the operation economy of the energy storage system is the core concern of the user. In current engineering practice, the user-side energy storage operation strategy or mode setting with economic efficiency as the goal mainly has the following problems: 1) the time value of investment and income funds is not considered (the time value of funds refers to the conversion of the value of funds in different periods into the value of funds in the same period), so that accurate economic benefit reference cannot be provided for the operation mode of the project; 2) the influence of different operation modes on the charge and discharge performance and service life of the energy storage system is ignored, resulting in inaccurate economic efficiency calculation conclusion and actual operation income less than expected.

[0004] Specifically, in current engineering practice, in order to simplify the analysis difficulty and process set for the energy storage operation mode, the performance degradation function of the battery is generally simplified as a linear degradation function with only time or cycle number as the independent variable, and the influence of the discharge depth, the charge / discharge rate and other parameters related to the operation mode on the battery performance parameters is ignored, and the influence of the changes of the battery health state and the charge / discharge cycle efficiency caused by the corresponding operation mode parameters on the operation economy is also ignored. Therefore, the result of the economic determination of the user-side power energy storage operation mode is inaccurate. SUMMARY

[0005] The present application provides a user-side power energy storage operation mode economic determination and optimization method to solve the technical problem that the result of the current user-side power energy storage operation mode economic determination is inaccurate.

[0006] To solve the above technical problems, the present application provides a user-side power energy storage operation mode economic determination method, comprising the following steps:

[0007] Obtain the basic parameters of the energy storage system and the preset parameters of the proposed operation mode; wherein the basic parameters include the battery cycle life L cyc,ref of the reference working condition, the battery calendar life L cal,ref of the reference working condition, the rated capacity E rated of the energy storage system, the discount rate r, the residual value coefficient φ of the energy storage system, the initial investment cost C1 of the energy storage system, and the operation and maintenance cost C(y, m) of each period, and the preset parameters include the discharge depth DOD s of the proposed operation mode.

[0008] According to the battery cycle life L cyc,ref of the reference working condition, the battery cycle life L cyc of the proposed operation mode is determined.

[0009] According to the battery calendar life L cal,ref of the reference working condition, the battery calendar life L cal of the proposed operation mode is determined.

[0010] According to the formula , the daily charge / discharge degree electricity income CD(y, m) of the energy storage system in y years and m months of the proposed operation mode is calculated; wherein p dw (m) represents the weighted degree price of the daily discharge period in the mth month based on the electricity price mechanism, p cw (m) represents the weighted degree price of the daily charging period in the mth month based on the electricity price mechanism, and η(y, m) represents the charge / discharge cycle efficiency of the battery in y years and m months under the proposed operation mode.

[0011] According to the battery cycle life L cyc of the proposed operation mode, the battery cycle life L cyc of the proposed operation mode is determined.cyc battery calendar life L of the proposed operation mode cal and the daily charging and discharging degree electricity income CD(y, m) of the proposed operation mode energy storage system at y year m month, determine the service life Y of the proposed operation mode energy storage system S year M S month

[0012] According to the formula , the monthly dischargeable electricity of the energy storage system in the yth year and the mth month is calculated ; wherein E rated represents the rated capacity of the energy storage system, represents the health state parameter of the energy storage system at y year m month, DOD s represents the discharge depth of the proposed operation mode, R(m) represents the number of complete charging and discharging cycles of the energy storage per day in the mth month of the proposed operation mode, and D(m) represents the calendar days in the mth month.

[0013] According to the formula , the cumulative discharge amount present value E d of the energy storage system during the service life is calculated

[0014] According to the operation and maintenance cost C(y, m) of the energy storage system at y year m month during the operation and the discount rate r, the full life cycle operation and maintenance cost present value C2(Y S , M S ) of the energy storage system is determined

[0015] According to the formula , the energy storage system levelized charging and discharging degree electricity cost LCOS is calculated; wherein φ represents the residual value coefficient of the energy storage system, and C1 represents the initial investment cost of the energy storage system.

[0016] According to the formula , the energy storage system levelized net price difference LNPD is calculated

[0017] Determine whether LNPD is greater than LCOS. If yes, it is determined that the proposed operation mode meets the economic feasibility requirement. If not, it is determined that the proposed operation mode does not meet the economic feasibility requirement.

[0018] Preferably, the battery cycle life L cyc of the proposed operation mode is obtained by the following steps:

[0019] According to the formula , the charging and discharging rate characteristic value rate rep; wherein pc(m, i) represents the percentage of the battery charge amount of the i th charging period in the m th month under the proposed operation mode to the current available capacity of the energy storage system, pd(m, i) represents the percentage of the battery discharge amount of the i th discharging period in the m th month under the proposed operation mode to the current available capacity of the energy storage system, Tc os (m, i) represents the charging operation time length of the i th charging period in the m th month under the proposed operation mode, Td os (m, i) represents the discharging operation time length of the i th discharging period in the m th month under the proposed operation mode, D(m) represents the calendar days of the m th month, A represents the total number of charging periods in the m th month under the proposed operation mode, and B represents the total number of discharging periods in the m th month under the proposed operation mode.

[0020] According to the formula , the battery cycle life L cyc of the proposed operation mode is calculated. cyc,ref ; wherein L ref refers to the battery cycle life of the reference working condition, DOD s refers to the discharge depth of the reference working condition, DOD ref refers to the discharge depth of the proposed operation mode, rate a refers to the charging and discharging rate of the rated working condition, E ref refers to the activation energy, R refers to the gas constant, and T refers to the battery working temperature of the proposed operation mode, T cal refers to the battery working temperature of the reference working condition, and a1 refers to the discharge depth influence factor, and a2 refers to the charging and discharging rate influence factor.

[0021] Preferably, the battery calendar life L cal,ref of the proposed operation mode is obtained by the following formula:

[0022]

[0023] ; wherein L ref refers to the battery calendar life of the reference working condition, b1 refers to the state of charge influence coefficient, SOC rep refers to the battery state of charge of the reference working condition, SOC S refers to the battery state of charge representation value of the proposed operation mode, and b2 refers to the state of charge influence factor.

[0024] Preferably, the service life Y S of the energy storage system under the proposed operation mode is obtained by the following formula: Wherein, D(i) represents the calendar days of the ith month, R(i) represents the number of complete charge-discharge cycles of the energy storage system in the ith month based on historical electricity consumption data and local electricity pricing mechanism, Z represents an integer, and N represents a natural number.

[0025] Preferably, the number of complete charge-discharge cycles R(i) of the energy storage system in the ith month based on historical electricity consumption data and local electricity pricing mechanism is obtained by the following formula: .

[0026] Preferably, the health state parameter of the energy storage system at the time of y years and m months is used by the following steps:

[0027] According to the formula , the cumulative number of charge-discharge cycles n(y, m) of the battery at the time of y years and m months under the proposed operation mode is calculated;

[0028] According to the formula , the health state parameter of the energy storage system at the nth charge-discharge cycle under the proposed operation mode is calculated ; wherein, , λ cyc represents the cycle aging attenuation coefficient of the battery health state, λ cal represents the calendar aging attenuation coefficient of the battery health state, φ1, φ2, φ3, φ4, φ5 represent the attenuation indexes of the cycle number, discharge depth, charge-discharge rate, calendar days of operation, and battery operating temperature of the battery health state, respectively.

[0029] Preferably, the charge-discharge cycle efficiency η(y, m) of the battery at the time of y years and m months under the proposed operation mode is obtained by the following formula:

[0030]

[0031] Wherein, η(n)=η(y, m), η0 represents the initial charge-discharge cycle efficiency of the energy storage system, k cyc represents the cycle aging attenuation coefficient of the battery charge-discharge energy efficiency, k cal represents the calendar aging attenuation coefficient of the battery charge-discharge energy efficiency, ε1, ε2, ε3, ε4 represent the attenuation indexes of the cycle number, discharge depth, charge-discharge rate, and calendar days of the battery charge-discharge energy efficiency, respectively.

[0032] Preferably, the weighted electricity price per kilowatt-hour ρ dw (m) of the discharge period in the mth month based on the electricity pricing mechanism and the weighted electricity price per kilowatt-hour ρ cw (m) of the charging period in the mth month based on the electricity pricing mechanism are obtained by the following formula:

[0033]

[0034] wherein, ρ c (m,i,j) represents the electricity price of the jth segment of the ith charging period in the mth month, pc(m,i,j) represents the percentage of the battery charging capacity of the jth segment of the ith charging period in the mth month to the current available capacity of the energy storage system, ρ d (m,i,k) represents the electricity price of the kth segment of the ith discharging period in the mth month, pd(m,i,k) represents the percentage of the battery discharging capacity of the kth segment of the ith discharging period in the mth month to the current available capacity of the energy storage system, A represents the total number of charging periods in the mth month in the proposed operation mode, B represents the total number of discharging periods in the mth month in the proposed operation mode, U represents the maximum value of j, and V represents the maximum value of k.

[0035] Preferably, the present value C2(Y S ,M S ) of the full life cycle operation and maintenance cost of the energy storage system is obtained by the following formula: .

[0036] The application also provides a method for determining and optimizing the economy of an operation mode of a user-side power energy storage system, comprising the following steps:

[0037] executing the method for determining and optimizing the economy of an operation mode of a user-side power energy storage system according to any one of the above;

[0038] When the net value LNPD of the difference between the flat charging and discharging electricity prices of the energy storage system is greater than the flat charging and discharging cost LCOS of the energy storage system, the present value of the full life cycle operation benefit of the energy storage system is calculated according to the formula .

[0039] The present values of the net benefits of the energy storage system in the full life cycle under various operation modes are respectively calculated according to the formula ; wherein, Φ represents an operation mode, P O (Φ) represents the present value of the full life cycle operation benefit of the energy storage system under the operation mode Φ, and C2(Φ) represents the present value of the full life cycle operation and maintenance cost of the energy storage system under the operation mode Φ.

[0040] The operation mode corresponding to the maximum is taken as the optimal operation mode.

[0041] The method for determining and optimizing the economy of an operation mode of a user-side power energy storage system provided by the application has the following beneficial effects:

[0042] (1) The present invention comprehensively considers the economic factors related to the operation mode of energy storage system, such as the initial investment of the system, the operation and maintenance costs of each period, the operating income of each period, and the residual value of the system recovery. It also considers the time value of cash flow at different stages of the entire life cycle, making the relevant economic analysis indicators more in line with the actual investment decision and economic analysis needs, and more practical reference value.

[0043] (2) Regarding the analysis of the performance changes and their impacts throughout the entire life cycle of energy storage systems, the relationship between the performance changes and operating parameters of electrochemical energy storage systems is quite complex. In current engineering practice, to simplify the relevant analysis, linear or nonlinear parameters based on the operational time or number of cycles are often used, while ignoring the influence of coupled parameters such as depth of discharge and charge / discharge rate. This invention fully considers the coupling relationship and synergistic influence of related factors in the analysis of energy storage system performance changes, thus making the analysis of energy storage system performance characterization parameters more reasonable and accurate, ensuring the accuracy of the economic determination of the operating mode, and thus solving the problem of inaccurate results in the current user-side power energy storage operating mode economic determination.

[0044] (3) Determine the service life Y of the energy storage system under the proposed operating mode. S Year M S The month is based on the battery cycle life (L) of the proposed operating model. cyc Battery calendar life L for the proposed operating model cal The daily charge and discharge revenue CD(y,m) of the energy storage system under the proposed operation mode is obtained using the time of year m. This overcomes the shortcomings of the existing technology, which only uses calendar life and cycle life as the system lifespan, resulting in weak correlation with the electricity price mechanism. It can provide a basis for accurate and reasonable lifespan determination and system update decisions during system operation.

[0045] (4) The optimal operating mode can be obtained, thereby maximizing the present value of the net income of the energy storage system throughout its entire life cycle. Attached Figure Description

[0046] Figure 1 This is a flowchart illustrating a method for determining the economic viability of a user-side power storage operation mode according to an embodiment of the present invention.

[0047] Figure 2 This is a flowchart illustrating an economic optimization method for a user-side power storage operation mode according to an embodiment of the present invention. Detailed Implementation

[0048] To make the objectives, advantages, and features of this invention clearer, the following detailed description, in conjunction with the accompanying drawings, provides a method for determining and optimizing the economic viability of a user-side power storage operation mode proposed in this invention. It should be noted that the drawings are all in a very simplified form and use non-precise scales, and are only used to facilitate and clearly illustrate the objectives of the embodiments of this invention.

[0049] In the description of this invention, the terms "first," "second," and other qualifiers are added for convenience of description and reference, and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with qualifiers such as "first" and "second" may explicitly or implicitly include one or more of that feature.

[0050] This embodiment provides a method for determining the economic viability of user-side power storage operation modes, including the following steps:

[0051] S1. Obtain the basic parameters of the energy storage system and the preset parameters for the proposed operating mode; wherein, the basic parameters include the battery cycle life L under reference operating conditions. cyc,ref Battery calendar life (L) under reference operating conditions cal,ref Rated capacity E of the energy storage system rated The preset parameters include the discount rate r, the residual value coefficient φ of the energy storage system, the initial investment cost C1 of the energy storage system, and the operation and maintenance costs C(y,m) for each period. The preset parameters also include the depth of discharge (DOD) for the proposed operating mode. s Reference operating conditions refer to the operating conditions used by battery manufacturers when conducting performance tests on batteries. The battery's operating parameters under these reference conditions can be provided by the battery manufacturer. Proposed operating modes refer to the operating modules that users intend to use. A proposed operating mode can be a newly designed operating mode or an existing operating mode that has already been used. The preset parameters for the proposed operating mode can be represented by Φ. s It means that Φ s It can be expressed in the form of a data matrix for easy storage and retrieval; its expression can be:

[0052] (Formula 1)

[0053] Among them, depth of discharge (DOD) s The unit is %; Ac s To determine the charging parameter matrix corresponding to the proposed operating mode, it consists of charging parameters pc(m,i,j) and Tc. os (m,i,j) forms a three-dimensional matrix with dimensions 12, 1, and J, respectively, where R represents a real number; similarly, Ad s To determine the discharge parameter matrix corresponding to the proposed operating mode, it consists of the discharge parameters pd(m,i,j) and Td. os(m,i,j) is a three-dimensional matrix composed of elements, with the size of its three dimensions being 12, I, and K, respectively, where I, J, and K are positive integers.

[0054] The charge and discharge parameters in formula (1) satisfy the following constraints:

[0055] (Formula 2)

[0056] Where pc(m,i) represents the percentage (%) of the battery charging amount during the i-th charging period within the day of month m under the proposed operating model, relative to the current available capacity of the energy storage system. The upper limit of this value is DOD. s The charging period can be further divided into several segments. For example, pc(m,i,j) represents the percentage (%) of battery charging amount in the j-th segment of the i-th charging period within the m-th day of the month; pd(m,i) represents the percentage (%) of battery discharging amount in the i-th discharging period within the m-th day of the proposed operating mode, which can also be divided into several segments. For example, pd(m,i,k) represents the percentage (%) of battery discharging amount in the k-th segment of the i-th discharging period within the m-th day of the month; Tc os (m,i,j) represents the duration (h) of the j-th segment of the i-th charging runtime; Td os (m,i,k) represents the duration (h) of the kth segment of the i-th discharge operation period; the same parameter can be set to the same value for each day of each month, for example, pc(m,i) is the same value for each day of January.

[0057] S2, Battery cycle life L based on reference operating conditions cyc,ref Determine the battery cycle life L for the proposed operating model. cyc Preferably, the battery cycle life L for the proposed operating mode. cyc It is obtained through the following steps:

[0058] S21. According to the formula (Formula 3), The charge / discharge rate characterization value (rate) under the proposed operating mode was calculated. rep Where pc(m,i) represents the percentage of battery charging volume during the i-th charging period within the day of month m under the proposed operating model, relative to the current available capacity of the energy storage system; pd(m,i) represents the percentage of battery discharging volume during the i-th discharging period within the day of month m under the proposed operating model, relative to the current available capacity of the energy storage system; and Tc... os (m,i) represents the charging runtime (h) of the i-th charging period within a day in the m-th month under the proposed operating model, Td os(m, i) represents the discharge operation duration (h) of the i-th discharge period in the m-th month in the proposed operation mode, D(m) represents the calendar days of the m-th month, for example, D(0) = 0, D(1) = 31 days represents that the calendar days of the first month is 31 days, and D(2) = 28 days represents that the calendar days of the second month is 28 days. A represents the total number of charging periods in the m-th month in the proposed operation mode, and B represents the total number of discharge periods in the m-th month in the proposed operation mode.

[0059] S22, the battery cycle life L of the proposed operation mode is calculated according to the formula (Formula 4) cyc ; wherein, L cyc,ref represents the battery cycle life (times) of the reference working condition, DOD ref represents the discharge depth (%) of the reference working condition, DOD s represents the discharge depth (%) of the proposed operation mode, rate ref represents the charging and discharging rate of the rated working condition, E a represents the activation energy (the typical value range of lithium iron phosphate is about 30-50 kJ / mol), R represents the gas constant (8.314 J / (mol·K)), and T represents the battery working temperature (K) of the proposed operation mode, T ref represents the battery working temperature (K) of the reference working condition, and a1 represents the discharge depth influence factor (usually the value of lithium iron phosphate battery is 0.7-1.0, which can be provided by the equipment manufacturer), and a2 represents the charging and discharging rate influence factor (usually the value of lithium iron phosphate battery is 0.1-0.3, which can be provided by the equipment manufacturer). The battery cycle life L cyc of the proposed operation mode calculated by formula 4 is more accurate. In other embodiments, L cyc,ref may also be used as an estimate of L cyc , or an empirical / semi-empirical calculation formula using the parameters in formula 4.

[0060] S3, the battery calendar life L cal,ref of the proposed operation mode is determined according to the battery calendar life L cal of the reference working condition. Preferably, the battery calendar life L cal of the proposed operation mode is obtained by the following formula:

[0061] (Formula 5)

[0062] ; wherein, L cal,ref represents the battery calendar life (days) of the reference working condition, and b1 represents the state of charge influence coefficient (usually 0.5-1.5, which can be provided by the equipment manufacturer), SOC refBattery state of charge (%) representing reference operating mode, SOC rep Battery state of charge representation value (%) of proposed operating mode (can be estimated according to the distribution of charging and discharging period), β2 represents state of charge influence factor (usually 0.2-0.8, which can be provided by equipment manufacturer). L cal is more accurate. In other embodiments, L cal,ref can also be used as the estimated value of L cal , or an empirical / semi-empirical calculation formula using the parameters in formula 5 is used.

[0063] S4, calculating the daily charging and discharging degree electric income CD(y, m) (yuan / kWh) of the energy storage system in y year m month of the proposed operating mode according to formula (formula 6); wherein, ρ dw (m) represents the weighted degree electric price (yuan / kWh) of the daily discharging period in the mth month based on the electricity price mechanism, ρ cw (m) represents the weighted degree electric price (yuan / kWh) of the daily charging period in the mth month based on the electricity price mechanism, and η(y, m) represents the charging and discharging cycle efficiency (%) of the battery in y year m month of the proposed operating mode. Preferably, the weighted degree electric price ρ dw (m) of the daily discharging period in the mth month based on the electricity price mechanism and the weighted degree electric price ρ cw (m) of the daily charging period in the mth month based on the electricity price mechanism are obtained by the following formula:

[0064] (formula 7)

[0065] Wherein, ρ c (m, i, j) represents the degree electric price of the jth segment of the ith charging period in the mth month, pc(m, i, j) represents the percentage of the battery charging capacity of the jth segment of the ith charging period in the mth month to the current available capacity of the energy storage system, ρ d (m, i, k) represents the degree electric price of the kth segment of the ith discharging period in the mth month, pd(m, i, k) represents the percentage of the battery discharging capacity of the kth segment of the ith discharging period in the mth month to the current available capacity of the energy storage system, A represents the total number of charging periods in the mth month under the proposed operating mode, B represents the total number of discharging periods in the mth month under the proposed operating mode, U represents the maximum value of j, and V represents the maximum value of k. ρ dw (m) and ρ cw (m) calculated by formula 7 are more accurate. In other embodiments, the ith charging period or discharging period can not be segmented.

[0066] S5. Battery cycle life L based on the proposed operating model cyc Battery calendar life L for the proposed operating model cal Given the daily charge / discharge revenue CD(y,m) of the energy storage system under the proposed operating model in year y and month m, determine the lifespan Y of the energy storage system under the proposed operating model. S Year M S Month. Preferred, Y S Year M S The month is obtained using the following formula: (Formula 8)

[0067] Where D(i) represents the number of calendar days in the i-th month, R(i) represents the number of complete charge-discharge cycles of the energy storage in the i-th month based on historical electricity consumption data and local electricity pricing mechanism, Z represents an integer, and N represents a natural number.

[0068] Preferably, the number of complete daily charge-discharge cycles R(i) of energy storage in the i-th month, based on historical electricity consumption data and the local electricity pricing mechanism, is obtained by the following formula: (Formula 9). The R(i) calculated using Formula 9 is more accurate. In other embodiments, R(i) can be set to a fixed value.

[0069] S6. According to the formula (Formula 10) Calculate the monthly electricity that the energy storage system can release in the m-th month of year y. (kWh); where E rated Indicates the rated capacity of the energy storage system. The DOD (Device Status) parameter represents the health status of an energy storage system at a given time (year and month). s R(m) represents the depth of discharge under the proposed operating mode, R(m) represents the number of complete charge-discharge cycles of the energy storage system per day in month m under the proposed operating mode, and D(m) represents the number of calendar days in month m. Preferably, the energy storage system uses the health status parameters of month m in year y. It is obtained through the following steps:

[0070] S61, According to the formula (Formula 11) Calculate the cumulative number of charge-discharge cycles n(y,m) when the battery is used for y years and m months under the proposed operating mode;

[0071] S62, According to the formula (Formula 12) calculates the health status parameters of the energy storage system during the nth charge-discharge cycle under the proposed operating mode. ;in, , λ cycCycle aging decay coefficient of battery health state, λ cal Calendar aging decay coefficient of battery health state, φ1, φ2, φ3, φ4, φ5 represent decay indexes of cycle number, discharge depth, charge-discharge rate, calendar days in operation and battery operating temperature of battery health state in turn (decay coefficients and decay indexes can be provided by equipment manufacturers). The calendar days in operation can be obtained by the following formula: (Formula 12). The η(y, m) calculated according to Formula 12 is more accurate. In other embodiments, other empirical / semi-empirical calculation formulas using parameters in Formula 12 can be used. In other embodiments, other empirical / semi-empirical calculation formulas using parameters in Formula 12 can be used.

[0072] Preferably, the charge-discharge cycle efficiency η(y, m) of the battery at y months in the proposed operation mode is obtained by the following formula:

[0073] (Formula 14)

[0074] wherein η(n) = η(y, m), η0 represents the initial charge-discharge cycle efficiency of the energy storage system (%), k cyc Cycle aging decay coefficient of battery charge-discharge energy efficiency, k cal Calendar aging decay coefficient of battery charge-discharge energy efficiency, ε1, ε2, ε3, ε4 represent decay indexes of cycle number, discharge depth, charge-discharge rate, calendar days cycle number of battery charge-discharge energy efficiency in turn (decay coefficients and decay indexes can be provided by equipment manufacturers). The η(y, m) calculated according to Formula 14 is more accurate. In other embodiments, other empirical / semi-empirical calculation formulas using parameters in Formula 14 can be used.

[0075] S7, the cumulative discharge amount present value E d (kWh) of the energy storage system during the service life is calculated according to Formula (Formula 15); wherein r represents the discount rate.

[0076] S8, the total life cycle operation and maintenance cost present value C2(Y S ,M S ) of the energy storage system is determined according to the operation and maintenance cost C(y, m) of the energy storage system in the yth month during the operation period and the discount rate r. Preferably, C2(Y S ,M S ) is obtained by the following formula:

[0077] (Formula 16)

[0078] The total life cycle operation and maintenance cost present value C2(Y SM S ).

[0079] S9. According to the formula (Formula 17) is used to calculate the levelized cost of electricity (LCOS) of the energy storage system (yuan / kWh); where φ represents the residual value coefficient of the energy storage system and C1 represents the initial investment cost of the energy storage system.

[0080] S10, According to the formula (Formula 18) The levelized charge-discharge price difference net value LNPD (yuan / kWh) of the energy storage system is calculated.

[0081] S11. Determine if LNPD is greater than LCOS. If yes, the proposed operating model meets the economic feasibility requirements; otherwise, the proposed operating model does not meet the economic feasibility requirements. This step can be expressed using the following formula:

[0082] (Formula 19)

[0083] Here, EFE represents the function for determining the economic feasibility of the proposed operating model of the energy storage system.

[0084] The economic evaluation method for a user-side power storage operation mode provided in this embodiment has the following beneficial effects:

[0085] (1) The present invention comprehensively considers the economic factors related to the operation mode of energy storage system, such as the initial investment of the system, the operation and maintenance costs of each period, the operating income of each period, and the residual value of the system recovery. It also considers the time value of cash flow at different stages of the entire life cycle, making the relevant economic analysis indicators more in line with the actual investment decision and economic analysis needs, and more practical reference value.

[0086] (2) Regarding the analysis of the performance changes and their impacts throughout the entire life cycle of energy storage systems, the relationship between the performance changes and operating parameters of electrochemical energy storage systems is quite complex. In current engineering practice, to simplify the relevant analysis, linear or nonlinear parameters based on the operational time or number of cycles are often used, while ignoring the influence of coupled parameters such as depth of discharge and charge / discharge rate. This invention fully considers the coupling relationship and synergistic influence of related factors in the analysis of energy storage system performance changes, thus making the analysis of energy storage system performance characterization parameters more reasonable and accurate, ensuring the accuracy of the economic determination of the operating mode, and thus solving the problem of inaccurate results in the current user-side power energy storage operating mode economic determination.

[0087] (3) Determine the service life Y of the energy storage system under the proposed operating mode. S Year M SL is the cycle life of the battery according to the proposed operation mode cyc L is the calendar life of the battery according to the proposed operation mode cal and the daily charging and discharging degree electricity income CD(y, m) of the energy storage system in the yth year and the mth month according to the proposed operation mode, overcome the deficiency of weak correlation of electricity price mechanism in the prior art caused by only taking calendar life and cycle life as system service life, and can provide basis for accurate and reasonable service life judgment and system updating decision in system operation process.

[0088] As shown in Figure 2 , based on the same technical concept as the economic judgment method of the user-side power energy storage operation mode, the embodiment provides an economic optimization method of the user-side power energy storage operation mode, including the following steps:

[0089] S101, executing any one of the economic judgment methods of the user-side power energy storage operation mode described above;

[0090] S102, when the net value of the flat charging and discharging degree electricity price difference LNPD of the energy storage system is greater than the flat charging and discharging degree electricity cost LCOS of the energy storage system, the full life cycle operation income present value (yuan) of the energy storage system is calculated according to formula (Formula 20);

[0091] S103, the full life cycle net income present value (yuan) of the energy storage system under various operation modes is respectively calculated according to formula (Formula 21); wherein, represents the operation mode, P O (Φ) represents the full life cycle operation income present value (yuan) of the energy storage system under the operation mode Φ, and C2(Φ) represents the full life cycle operation and maintenance cost present value (yuan) under the operation mode Φ. The set Mode of the preset parameters corresponding to various operation modes can be expressed as follows:

[0092] (Formula 22)

[0093] S104, the operation mode corresponding to the maximum is taken as the optimal operation mode. The maximum can be expressed by the following formula:

[0094] (Formula 23)

[0095] (Formula 24)

[0096] wherein, represents The operating mode corresponding to the maximum value is the optimal operating mode. The parameters of the optimal operating mode can be solved by iterative calculation and optimization, or, based on the characteristics of the objective function being discrete, the constraints being complex, and the need for global search, algorithms such as genetic algorithms and particle swarm optimization can be used to accelerate the solution to the global optimum.

[0097] This embodiment provides an economic optimization method for user-side power storage operation mode, which can obtain the optimal operation mode and thus maximize the present value of net income of the energy storage system throughout its entire life cycle.

[0098] In summary, the economic evaluation and optimization method for user-side power storage operation mode provided by this invention has the following beneficial effects:

[0099] (1) The present invention comprehensively considers the economic factors related to the operation mode of energy storage system, such as the initial investment of the system, the operation and maintenance costs of each period, the operating income of each period, and the residual value of the system recovery. It also considers the time value of cash flow at different stages of the entire life cycle, making the relevant economic analysis indicators more in line with the actual investment decision and economic analysis needs, and more practical reference value.

[0100] (2) Regarding the analysis of the performance changes and their impacts throughout the entire life cycle of energy storage systems, the relationship between the performance changes and operating parameters of electrochemical energy storage systems is quite complex. In current engineering practice, to simplify the relevant analysis, linear or nonlinear parameters based on the operational time or number of cycles are often used, while ignoring the influence of coupled parameters such as depth of discharge and charge / discharge rate. This invention fully considers the coupling relationship and synergistic influence of related factors in the analysis of energy storage system performance changes, thus making the analysis of energy storage system performance characterization parameters more reasonable and accurate, ensuring the accuracy of the economic determination of the operating mode, and thus solving the problem of inaccurate results in the current user-side power energy storage operating mode economic determination.

[0101] (3) Determine the service life Y of the energy storage system under the proposed operating mode. S Year M S The month is based on the battery cycle life (L) of the proposed operating model. cyc Battery calendar life L for the proposed operating model cal The daily charge and discharge revenue CD(y,m) of the energy storage system under the proposed operation mode is obtained using the time of year m. This overcomes the shortcomings of the existing technology, which only uses calendar life and cycle life as the system lifespan, resulting in weak correlation with the electricity price mechanism. It can provide a basis for accurate and reasonable lifespan determination and system update decisions during system operation.

[0102] (4) The optimal operating mode can be obtained, thereby maximizing the present value of the net income of the energy storage system throughout its entire life cycle.

[0103] The above description is only the description of the preferred embodiments of the present application, and is not any limitation on the scope of the present application. Any change and modification made by the person skilled in the art according to the above disclosure is within the protection scope of the present application.

Claims

1. A method for determining the economic viability of a user-side power storage operation mode, characterized in that, Includes the following steps: Obtain the basic parameters of the energy storage system and the preset parameters for the proposed operating mode; wherein, the basic parameters include the battery cycle life L under reference operating conditions. cyc,ref Battery calendar life (L) under reference operating conditions cal,ref Rated capacity E of the energy storage system rated The preset parameters include the discount rate r, the residual value coefficient φ of the energy storage system, the initial investment cost C1 of the energy storage system, and the operation and maintenance costs C(y,m) for each period. The preset parameters also include the depth of discharge (DOD) for the proposed operating mode. s ; Based on the reference operating conditions, the battery cycle life L cyc,ref Determine the battery cycle life L for the proposed operating model. cyc ; Battery calendar life L based on reference operating conditions cal,ref Determine the battery calendar life L for the proposed operating model. cal ; According to the formula The daily charge-discharge revenue CD(y,m) of the energy storage system under the proposed operating model in year y and month m is calculated; where ρ dw (m) represents the weighted average electricity price for the intraday discharge period in month m based on the electricity pricing mechanism, ρ cw (m) represents the weighted electricity price for the daily charging period in the m-th month based on the electricity price mechanism, and η(y,m) represents the charge-discharge cycle efficiency of the battery when it is used for y years and m months under the proposed operating model. Based on the battery cycle life L of the proposed operating model cyc Battery calendar life L for the proposed operating model cal Given the daily charge / discharge revenue CD(y,m) of the energy storage system under the proposed operating model in year y and month m, determine the lifespan Y of the energy storage system under the proposed operating model. S Year M S moon; According to the formula The monthly electricity that the energy storage system can release in the m-th month of year y is calculated. Among them, E rated Indicates the rated capacity of the energy storage system. The DOD (Device Status) parameter represents the health status of an energy storage system at a given time (year and month). s R(m) represents the depth of discharge under the proposed operating mode, R(m) represents the number of complete charge-discharge cycles of the energy storage in the day under the proposed operating mode in month m, and D(m) represents the number of calendar days in month m. According to the formula The present value E of the cumulative discharge over the lifespan of the energy storage system is calculated. d Where r represents the discount rate; Based on the operation and maintenance cost C(y,m) in the m-th month of year y during the operation of the energy storage system and the discount rate r, determine the present value C2(Y) of the total life-cycle operation and maintenance cost of the energy storage system. S M S ); According to the formula The levelized cost of electricity (LCOS) of the energy storage system is calculated; where φ represents the residual value factor of the energy storage system and C1 represents the initial investment cost of the energy storage system. According to the formula The levelized charge-discharge rate difference (LNPD) of the energy storage system is calculated. Determine whether LNPD is greater than LCOS. If yes, the proposed operating model is deemed to meet the economic feasibility requirements; otherwise, the proposed operating model is deemed not to meet the economic feasibility requirements.

2. The method for determining the economic viability of a user-side power storage operation mode as described in claim 1, characterized in that, Battery cycle life L for the proposed operating model cyc It is obtained through the following steps: According to the formula The charge / discharge rate characterization value (rate) under the proposed operating mode is calculated. rep ; Where pc(m,i) represents the percentage of battery charging amount during the i-th charging period of the day in month m under the proposed operating model, relative to the current available capacity of the energy storage system; pd(m,i) represents the percentage of battery discharging amount during the i-th discharging period of the day in month m under the proposed operating model, relative to the current available capacity of the energy storage system; and Tc... os (m,i) represents the charging runtime during the i-th charging period within a day in the m-th month under the proposed operating model, Td os (m,i) represents the discharge runtime of the i-th discharge period within the day in the m-th month under the proposed operating model, D(m) represents the number of calendar days in the m-th month, A represents the total number of charging periods within the day in the m-th month under the proposed operating model, and B represents the total number of discharge periods within the day in the m-th month under the proposed operating model. According to the formula The battery cycle life L of the proposed operating mode was calculated. cyc Among them, L cyc,ref The DOD indicates the battery cycle life under reference operating conditions. ref Depth of discharge (DOD) indicates the reference operating condition. s Indicates the discharge depth of the proposed operating mode, rate ref E represents the charge / discharge rate under rated operating conditions. a R represents the activation energy, R represents the gas constant, and T represents the battery operating temperature under the proposed operating mode. ref α1 represents the battery operating temperature under reference conditions, α2 represents the depth of discharge influence factor, and α2 represents the charge / discharge rate influence factor.

3. The method for determining the economic viability of a user-side power storage operation mode as described in claim 2, characterized in that, Battery calendar life L for proposed operating model cal It is obtained through the following formula: ， Among them, L cal,ref The battery calendar life under reference operating conditions is represented by β1, which represents the state of charge (SOC) factor. ref State of charge (SOC) indicates the battery's state of charge under reference operating conditions. rep β2 represents the battery state of charge characterization value for the proposed operating mode, and β2 represents the state of charge influence factor.

4. The method for determining the economic viability of a user-side power storage operation mode as described in claim 3, characterized in that, Determine the lifespan Y of the energy storage system under the proposed operating mode. S Year M S The month is obtained using the following formula: ， Where D(i) represents the number of calendar days in the i-th month, R(i) represents the number of complete charge-discharge cycles of the energy storage in the i-th month based on historical electricity consumption data and local electricity pricing mechanism, Z represents an integer, and N represents a natural number.

5. The method for determining the economic viability of a user-side power storage operation mode as described in claim 4, characterized in that, The number of complete charge-discharge cycles R(i) of the daily energy storage in the i-th month, based on historical electricity consumption data and the local electricity pricing mechanism, is obtained through the following formula: .

6. The method for determining the economic viability of a user-side power storage operation mode as described in claim 5, characterized in that, Health status parameters of the energy storage system at year y and month m It is obtained through the following steps: According to the formula The cumulative number of charge-discharge cycles n(y,m) when the battery is used for y years and m months under the proposed operating model is calculated. According to the formula The health status parameters of the energy storage system during the nth charge-discharge cycle under the proposed operating mode were calculated. ;in, , λ cyc The cyclic aging degradation coefficient, λ, represents the battery's health status. cal The calendar aging degradation coefficients represent the battery health status. φ1, φ2, φ3, φ4, and φ5 represent the degradation index of the battery health status based on the number of cycles, depth of discharge, charge / discharge rate, calendar days of operation, and battery operating temperature, respectively.

7. The method for determining the economic viability of a user-side power storage operation mode as described in claim 6, characterized in that, The charge-discharge cycle efficiency η(y,m) of the battery when it is used for y years and m months under the proposed operating model is obtained by the following formula: ， Where η(n) = η(y,m), η0 represents the initial charge-discharge cycle efficiency of the energy storage system, and k cyc k represents the cycle aging degradation coefficient that indicates the energy efficiency of battery charging and discharging. cal The calendar aging degradation coefficients represent the battery charge and discharge energy efficiency. ε1, ε2, ε3, and ε4 represent the degradation exponents of the battery charge and discharge energy efficiency based on the number of cycles, depth of discharge, charge and discharge rate, and number of calendar days, respectively.

8. The method for determining the economic viability of a user-side power storage operation mode as described in claim 1, characterized in that, The weighted average electricity price ρ for the daily discharge period in month m based on the electricity pricing mechanism. dw (m) and the weighted average electricity price ρ for the intraday charging period in month m based on the electricity pricing mechanism. cw (m) is obtained through the following formula: ， Where, ρ c (m,i,j) represents the electricity price for the j-th segment of the i-th charging period within a day in month m, pc(m,i,j) represents the percentage of battery charging amount in the j-th segment of the i-th charging period within a day in month m relative to the current available capacity of the energy storage system, and ρ d (m,i,k) represents the electricity price of the k-th segment of the i-th discharge period within a day in month m, pd(m,i,k) represents the percentage of battery discharge in the k-th segment of the i-th discharge period within a day in month m relative to the current available capacity of the energy storage system, A represents the total number of daily charging periods in month m under the proposed operating model, B represents the total number of daily discharge periods in month m under the proposed operating model, U represents the maximum value of j, and V represents the maximum value of k.

9. The method for determining the economic viability of a user-side power storage operation mode as described in claim 1, characterized in that, The present value of the total lifecycle operation and maintenance cost of an energy storage system, C2(Y). S M S It can be obtained through the following formula: 。 10. An economic optimization method for user-side power storage operation mode, characterized in that, Includes the following steps: The economic evaluation method for a user-side power storage operation mode as described in any one of claims 1 to 9; When the levelized cost per kilowatt-hour (LNPD) of the energy storage system is greater than the levelized cost per kilowatt-hour (LCOS) of the energy storage system, according to the formula... The present value of the operating revenue over the entire life cycle of the energy storage system is calculated. According to the formula The present value of the net income over the entire life cycle of the energy storage system under various operating modes is calculated respectively; where Φ represents the operating mode, P O (Φ) represents the present value of the operating revenue of the energy storage system throughout its entire life cycle under operating mode Φ, and C2(Φ) represents the present value of the operation and maintenance costs throughout its entire life cycle under operating mode Φ. The largest The corresponding operating model is the optimal operating model.

Images