A solar thermal management system and method based on the performance degradation of an energy storage system

Abstract

The present invention relates to the technical field of photovoltaic-energy storage systems, and specifically to a solar thermal management system and method based on the performance degradation of an energy storage system. The system includes: a multi-objective equation derivation module for multi-objective equations of the operating cost and carbon emissions of the photovoltaic-energy storage system; a constraint condition setting module for setting constraint conditions for the performance degradation of the energy storage system; a model linearization module for model linearization based on the piecewise linear function linearization method; and a scheduling module for formulating a power scheduling plan for the photovoltaic-energy storage system according to the health state of the energy storage system and the optimization objective. The beneficial effects are as follows: By designing the constraint conditions for the performance degradation of the energy storage system and converting them into linear constraints based on the piecewise linear function linearization method, and feeding them back to the energy management method, the influence of the reduction of the maximum available capacity and the maximum charge-discharge power of the energy storage system on energy management is considered in real time, and a reasonable energy management strategy is formulated.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic - energy storage systems, and specifically to a solar thermal management system and method based on the performance degradation of an energy storage system. Background Technique

[0002] With the rapid development of renewable energy technologies, the photovoltaic - energy storage system formed by the combination of photovoltaic and energy storage systems is considered a key approach to improving the photovoltaic penetration rate, promoting the construction of intelligent power grids, and optimizing the energy supply structure. However, as the core technology for achieving the above - mentioned goals, the energy management in the photovoltaic - energy storage system faces multiple challenges such as the performance degradation of the energy storage system during operation and the complex and diverse system optimization goals, which pose a great challenge to the safe operation of the photovoltaic - energy storage system. Therefore, it is urgent to conduct research on the multi - objective energy management method of the photovoltaic - energy storage system under the condition of energy storage system performance degradation to provide guarantee for the safe operation of the system.

[0003] Currently, regarding the energy management optimization problem of the photovoltaic - energy storage system, many scholars have conducted a large amount of research from three aspects: optimization goals, sources of decision - making data, and optimization algorithms, but there are still some deficiencies. On the one hand, the existing research has not achieved multiple optimizations of operating costs, carbon emissions, and the performance degradation of the energy storage system. On the other hand, the existing research has not considered in real - time in the optimization algorithm the impact of the performance degradation of the energy storage system (such as the reduction of the maximum available capacity, the reduction of the maximum charge - discharge power, etc.) on energy management, nor analyzed how to extend the service life of the energy storage system based on this, which will cause the system to exceed its existing maximum capacity or safety range during charge - discharge, posing a great challenge to the safe operation of the photovoltaic - energy storage system. Summary of the Invention

[0004] The purpose of the present invention is to provide a solar thermal management system and method based on the performance degradation of an energy storage system to solve the problems raised in the above - mentioned background technique.

[0005] To achieve the above - mentioned purpose, the present invention provides the following technical solution: A solar thermal management system based on the performance degradation of an energy storage system, the system includes:

[0006] A multi - objective equation derivation module for the multi - objective equations of the operating cost and carbon emissions of the photovoltaic - energy storage system;

[0007] A constraint condition setting module for setting the constraint conditions of the performance degradation of the energy storage system;

[0008] A model linearization module for model linearization based on the piece - wise linear function linearization method;

[0009] A scheduling module for formulating a power scheduling plan for the photovoltaic - energy storage system according to the health state of the energy storage system and the optimization goal.

[0010] Preferably, the multi-objective equation derivation module constructs an objective function for the system operating cost, and its calculation formula is as follows:

[0011] ————————(1)

[0012] In the formula, represents the operating cost of the PV-storage system, T represents the scheduling period, represents t the electricity purchase price at time represents t the exchange power between the PV-storage system and the power grid at time represents the sampling time interval;

[0013] In the PV-storage system, carbon emissions come from the electricity purchased from the power grid and the output of the photovoltaic power generation system; it is assumed that all the electricity purchased from the power grid is produced by traditional fossil fuel power plants, thus resulting in a large amount of CO 2 emissions, and its calculation formula is as follows:

[0014] ——————————————(2)

[0015] In the formula, represents the CO 2 emissions generated by the electricity purchased by the system from the power grid, represents the CO 2 emissions generated by traditional fossil fuel power plants when producing 1 kWh of electricity;

[0016] In addition, CO 2 emissions will also be generated during the production construction and component transportation of the photovoltaic power generation system, and its calculation formula is as follows:

[0017] ——————————(3)

[0018] In the formula, represents the CO 2 emissions generated during the production construction and component transportation of the photovoltaic power generation system, represents the CO 2 emissions generated by the photovoltaic power generation system when producing 1 kWh of electricity, represents t the output of the photovoltaic power generation system at time

[0019] The carbon emission objective equation of the PV-storage system is expressed as:

[0020] ——————————————(4)

[0021] In the formula, represents the total carbon emissions of the photovoltaic - energy storage system;

[0022] In order to comprehensively consider the operating cost and carbon emissions of the photovoltaic - energy storage system, a multi - objective function equation is constructed based on Equation (1) and Equation (4) to obtain the optimal low - carbon economic operation strategy of the system. Its mathematical expression is as follows:

[0023] ——————————(5)

[0024] In the formula, represents the optimization objective of the operating cost and carbon emissions of the photovoltaic - energy storage system.

[0025] Preferably, the constraint condition setting module includes:

[0026] (1) State of Charge (SOC) upper and lower limit constraints:

[0027] ——————————————(6)

[0028] In the formula, represents the SOC of the energy storage system at t moment, and represent the upper and lower limits of the SOC of the energy storage system respectively;

[0029] (2) Charge - discharge power constraints

[0030] ——————————(7)

[0031] ————————(8)

[0032] In the formula, and represent the charging and discharging power of the energy storage system at t moment respectively, and represent the maximum charging and discharging power of the energy storage system at t moment respectively;

[0033] (3) SOC conversion constraints between adjacent moments

[0034]

[0035] ————————(9)

[0036] In the formula, The SOC of the energy storage system at time t The SOC of the energy storage system at time t-1 Represents the actual maximum available capacity of the energy storage system at time t-1 Represents the charging efficiency of the energy storage system Represents the discharging efficiency of the energy storage system Is a binary variable representing the charging and discharging state of the energy storage system Represents the charging state Represents the discharging state

[0037] Preferably, the constraint condition setting module further includes:

[0038] According to the definition of State of Health (SOH), the actual maximum available capacity of the energy storage system at t time The maximum charging power And the maximum discharging power Can be expressed as:

[0039] ——————————————————(10)

[0040] ————————(11)

[0041] ——————(12)

[0042] In the formula, Represents the rated capacity of the energy storage system And Respectively represent the rated maximum charging and discharging powers of the energy storage system Represents the health state of the energy storage system at t time; Substituting formulas (10), (11) and (12) into formulas (7), (8) and (9), the constraint conditions considering the performance degradation of the energy storage system are obtained:

[0043] ————————————(13)

[0044] ——————————(14)

[0045]

[0046] ————————(15)

[0047] Comparative analysis of the impact of energy storage system performance degradation on the energy management of a photovoltaic-storage system, the actual maximum available capacity under the condition of ignoring the performance degradation of the energy storage system , the maximum charging power , and the maximum discharging power . That is, let SOH = 100% in equations (13), (14) and (15).

[0048] Preferably, the model linearization module includes:

[0049] The constraint equation (15) is a non-linear constraint equation containing binary variables and judgment conditions. Convert it into a linear constraint. Use to uniformly represent the charging and discharging power of the energy storage system. The relationship with and can be expressed as:

[0050] ——————————(16)

[0051] Then equation (15) can be further expressed as:

[0052] ——(17)

[0053] For equation (17), 3 continuous variables , and , as well as 2 0-1 variables and can be used to achieve linearization conversion. Among them, 3 continuous variables are used to linearize equation (17), and 2 0-1 variables are used to limit the values of the 3 continuous variables, so as to limit the interval where is located. The specific steps are as follows:

[0054] Find the break points of the piecewise linear function of equation (17). Equation (17) consists of two piecewise linear functions, so it has 3 break points. Let them be , and in ascending order. Their mathematical expressions are as follows:

[0055]

[0056] ——(18)

[0057] Secondly, use 3 continuous variables and 3 break points to replace the independent variable . The replacement formula is as follows:

[0058] ——————————————(19)

[0059] Then, replace the SOC calculation formula with three consecutive variables and formula (17), and the calculation formula is as follows:

[0060] ——————————————(20)

[0061] Finally, impose constraints on the three consecutive variables and two 0-1 variables to limit the interval where it is located, and the constraint conditions are as follows:

[0062] ——————————————(21)

[0063] ——————————————————(22)

[0064] ————————————————————(23)

[0065] ————————————————(24)

[0066] ————————————————————(25)

[0067] Convert the non-linear constraint formula (15) into a linear constraint condition composed of formulas (19) to (25) to facilitate the solution of the energy management method for the photovoltaic-storage system.

[0068] A solar thermal management method based on the performance degradation of the energy storage system, the method comprising the following steps:

[0069] Derive the multi-objective equation of the operating cost and carbon emissions of the photovoltaic-storage system, so as to achieve the dual optimization of the operating cost and carbon emissions as the optimization objective;

[0070] Design the performance degradation constraint conditions of the energy storage system, and feedback them to the energy management method of the photovoltaic-storage system, and adjust the maximum charge and discharge power in real time according to the health state of the energy storage system to solve the unreasonable energy management problem caused by the performance degradation of the energy storage system during the operation of the photovoltaic-storage system;

[0071] Based on the piecewise linear function linearization method, convert the non-linear constraint into a linear constraint, convert the MINLP problem into an easily solvable MILP problem, and improve the solution accuracy of the multi-objective energy management problem;

[0072] Formulate the power scheduling plan of the photovoltaic-storage system according to the health state of the energy storage system and the optimization objective.

[0073] Preferably, a system operation cost objective function is constructed, and its calculation formula is as follows:

[0074] ————————(1)

[0075] In the formula, represents the operation cost of the PV - energy storage system, T represents the scheduling period, represents t the electricity purchase price at time represents t the exchange power between the PV - energy storage system and the power grid at time represents the sampling time interval;

[0076] In the PV - energy storage system, carbon emissions come from the electricity purchased from the power grid and the output of the PV power generation system; assuming that all the electricity purchased from the power grid is produced by traditional fossil fuel power plants, a large amount of CO 2 emissions are caused, and its calculation formula is as follows:

[0077] ——————————————(2)

[0078] In the formula, represents the CO 2 emissions generated by the electricity purchased by the system from the power grid, represents the CO 2 emissions generated by traditional fossil fuel power plants for producing 1 kWh of electricity;

[0079] In addition, CO 2 emissions will also be generated during the production, construction and component transportation of the PV power generation system, and its calculation formula is as follows:

[0080] ——————————(3)

[0081] In the formula, represents the CO 2 emissions generated during the production, construction and component transportation of the PV power generation system, represents the CO 2 emissions generated by the PV power generation system for producing 1 kWh of electricity, represents t the output of the PV power generation system at time

[0082] The carbon emission target equation of the PV - energy storage system is expressed as:

[0083] ——————————————(4)

[0084] In the formula, represents the total carbon emissions of the photovoltaic - energy storage system;

[0085] To comprehensively consider the operating cost and carbon emissions of the photovoltaic - energy storage system, a multi - objective function equation is constructed based on Formula (1) and Formula (4) to obtain the optimal low - carbon economic operation strategy of the system. Its mathematical expression is as follows:

[0086] ——————————(5)

[0087] In the formula, represents the optimization objectives of the operating cost and carbon emissions of the photovoltaic - energy storage system.

[0088] Preferably, the constraint conditions are set as follows:

[0089] (1) State of Charge (SOC) upper and lower limit constraints:

[0090] ——————————————(6)

[0091] In the formula, represents the SOC of the energy storage system at t time, and represent the upper and lower limits of the SOC of the energy storage system respectively;

[0092] (2) Charge - discharge power constraints

[0093] ——————————(7)

[0094] ————————(8)

[0095] In the formula, and represent the charging and discharging powers of the energy storage system at t time respectively, and represent the maximum charging and discharging powers of the energy storage system at t time respectively;

[0096] (3) SOC conversion constraints between adjacent times

[0097]

[0098] ——————(9)

[0099] In the formula, is the SOC of the energy storage system at time t, SOC of the energy storage system at time t-1 represents the actual maximum available capacity of the energy storage system at time t-1 represents the charging efficiency of the energy storage system represents the discharging efficiency of the energy storage system is a binary variable representing the charging and discharging state of the energy storage system represents the charging state represents the discharging state

[0100] Preferably, the constraint condition setting further includes:

[0101] According to the definition of State of Health (SOH), the actual maximum available capacity of the energy storage system at t time the maximum charging power and the maximum discharging power can be expressed as:

[0102] ——————————————————(10)

[0103] ————————(11)

[0104] ——————(12)

[0105] In the formula, represents the rated capacity of the energy storage system and respectively represent the rated maximum charging and discharging powers of the energy storage system represents the health state of the energy storage system at t time; Substituting formulas (10), (11) and (12) into formulas (7), (8) and (9), the constraint conditions considering the performance degradation of the energy storage system are obtained:

[0106] ————————————(13)

[0107] ——————————(14)

[0108]

[0109] ————————(15)

[0110] Comparative analysis of the impact of the performance degradation of the energy storage system on the energy management of the photovoltaic-storage system. The actual maximum available capacity under the condition of ignoring the performance degradation of the energy storage system , the maximum charging power and the maximum discharging power constraint conditions, that is, let SOH = 100% in equations (13), (14) and (15).

[0111] Preferably, the model linearization includes:

[0112] The constraint condition equation (15) is a non-linear constraint condition containing binary variables and judgment conditions. Convert it into a linear constraint, and use to uniformly represent the charging and discharging power of the energy storage system. The relationship with and can be expressed as:

[0113] ——————————(16)

[0114] Then equation (15) can be further expressed as:

[0115] ——(17)

[0116] For equation (17), 3 continuous variables , and , as well as 2 0-1 variables and can be used to achieve linearization conversion; among them, 3 continuous variables achieve the linearization of equation (17), and 2 0-1 variables limit the values of the 3 continuous variables, thereby limiting the interval where is located. The specific steps are as follows:

[0117] Find the break points of the piecewise linear function of equation (17). Equation (17) consists of two piecewise linear functions, so it has 3 break points. Let them be , and in ascending order. Their mathematical expressions are as follows:

[0118]

[0119] ————(18)

[0120] Secondly, use 3 continuous variables and 3 break points to replace the independent variable . The replacement formula is as follows:

[0121] ——————————————(19)

[0122] Then, replace the SOC calculation formula with the sum of three continuous variables in Equation (17), and the calculation formula is as follows:

[0123] ——————————————(20)

[0124] Finally, impose constraints on the three continuous variables and two 0-1 variables to limit the interval where it is located, and the constraint conditions are as follows:

[0125] ——————————————(21)

[0126] ——————————————————(22)

[0127] ————————————————————(23)

[0128] ————————————————(24)

[0129] ————————————————————(25)

[0130] The non-linear constraint Equation (15) is transformed into a linear constraint condition composed of Equations (19) to (25) to facilitate the solution of the energy management method for the photovoltaic-energy storage system.

[0131] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0132] The solar thermal management system and method based on the performance degradation of the energy storage system proposed by the present invention, by designing the performance degradation constraint conditions of the energy storage system and converting them into linear constraints based on the piecewise linear function linearization method, and feeding them back to the energy management method, thereby considering in real-time the impact of the reduction of the maximum available capacity and the maximum charge and discharge power of the energy storage system on energy management, and formulating a reasonable energy management strategy. This enables the photovoltaic-energy storage system to adjust the maximum charge and discharge power in real-time according to the health state of the energy storage system, avoiding exceeding its existing maximum capacity or safety range during charge and discharge, and solving the problem of shortening the service life of the energy storage system caused by unreasonable power distribution. Therefore, this method can solve the problem of unreasonable energy management caused by the performance degradation of the energy storage system during the operation of the photovoltaic-energy storage system. Brief Description of the Drawings

[0133] Figure 1 is the flow chart of the method of the present invention;

[0134] Figure 2This is the electricity price schematic diagram of the photovoltaic-storage system of the present invention. Detailed implementation manners

[0135] In order to clearly and completely describe the objectives, technical solutions of the present invention, and make the advantages more clearly understood, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are part of the embodiments of the present invention, rather than all of the embodiments, and are only used to explain the embodiments of the present invention, not to limit the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0136] Embodiment 1, the present invention provides a technical solution: a solar thermal management system based on the performance degradation of the energy storage system, the system includes:

[0137] A multi-objective equation derivation module for the multi-objective equation of the operating cost and carbon emission of the photovoltaic-storage system;

[0138] Construct an objective function for the system operating cost, and its calculation formula is as follows:

[0139] ————————(1)

[0140] In the formula, represents the operating cost of the photovoltaic-storage system, T represents the scheduling period, represents t the electricity purchase price at time represents t the exchange power between the photovoltaic-storage system and the power grid at time represents the sampling time interval;

[0141] In the photovoltaic-storage system, carbon emissions come from the electricity purchased from the power grid and the output of the photovoltaic power generation system; assuming that all the electricity purchased from the power grid is produced by traditional fossil fuel power plants, a large amount of CO 2 emissions are caused, and its calculation formula is as follows:

[0142] ————————————(2)

[0143] In the formula, represents the CO 2 emissions generated by the electricity purchased by the system from the power grid, represents the CO 2 emissions generated by traditional fossil fuel power plants when producing 1 kWh of electricity;

[0144] In addition, CO2 Emissions, and its calculation formula is as follows:

[0145] ——————————(3)

[0146] Wherein, represents the CO 2 emissions generated during the production, construction and component transportation of the photovoltaic power generation system, represents the CO 2 emissions generated when the photovoltaic power generation system produces 1 kWh of electricity, represents t the output of the photovoltaic power generation system at time

[0147] The carbon emission target equation of the photovoltaic-storage system is expressed as:

[0148] ——————————————(4)

[0149] Wherein, represents the total carbon emissions of the photovoltaic-storage system; a

[0150] In order to comprehensively consider the operating cost and carbon emissions of the photovoltaic-storage system, a multi-objective function equation is constructed based on Equations (1) and (4) to obtain the optimal low-carbon economic operation strategy of the system, and its mathematical expression is as follows:

[0151] ——————————(5)

[0152] Wherein, represents the optimization objective of the operating cost and carbon emissions of the photovoltaic-storage system.

[0153] The constraint condition setting module is used to set the constraint conditions for the performance degradation of the energy storage system; including:

[0154] (1) State of Charge (SOC) upper and lower limit constraints:

[0155] ——————————————(6)

[0156] Wherein, represents the SOC of the energy storage system at t time, and respectively represent the upper and lower limits of the SOC of the energy storage system;

[0157] (2) Charge and discharge power constraints

[0158] ——————————(7)

[0159] ————————(8)

[0160] Wherein, and respectively represent the charging and discharging powers of the energy storage system at t moment, and respectively represent the maximum charging and discharging powers of the energy storage system at t moment;

[0161] (3)SOC conversion constraint between adjacent moments

[0162]

[0163] ————(9)

[0164] Wherein, SOC of the energy storage system at time t, SOC of the energy storage system at time t-1, represents the actual maximum available capacity of the energy storage system at time t-1, represents the charging efficiency of the energy storage system, represents the discharging efficiency of the energy storage system, is a binary variable representing the charge and discharge state of the energy storage system, represents the charging state, represents the discharging state.

[0165] It also includes:

[0166] According to the definition of State of Health (SOH), the actual maximum available capacity t of the energy storage system at time , the maximum charging power and the maximum discharging power can be expressed as:

[0167] ——————————————————(10)

[0168] ————————(11)

[0169] ——————(12)

[0170] Wherein, represents the rated capacity of the energy storage system, and ​respectively represent the rated maximum charging and discharging powers of the energy storage system, represent the state of health of the energy storage system at t time; Substituting Equations (10), (11), and (12) into Equations (7), (8), and (9), the constraint conditions considering the performance degradation of the energy storage system are obtained:

[0171] ————————————(13)

[0172] ——————————(14)

[0173]

[0174] ————(15)

[0175] Comparatively analyze the impact of the performance degradation of the energy storage system on the energy management of the PV - energy storage system. Under the condition of ignoring the performance degradation of the energy storage system, the actual maximum available capacity , the maximum charging power and the maximum discharging power constraint conditions, that is, let SOH = 100% in Equations (13), (14), and (15).

[0176] Model linearization module, used for model linearization based on the piecewise linear function linearization method;

[0177] Scheduling module, used to formulate the power scheduling plan of the PV - energy storage system according to the state of health of the energy storage system and the optimization goal.

[0178] Include:

[0179] The constraint condition Equation (15) is a non - linear constraint condition containing binary variables and judgment conditions. Convert it into a linear constraint. Use to uniformly represent the charging and discharging powers of the energy storage system. The relationship with and can be expressed as:

[0180] ——————————(16)

[0181] Then Equation (15) can be further expressed as:

[0182] ——(17)

[0183] For Equation (17), 3 continuous variables , and , as well as 2 0 - 1 variables and , a linearized conversion is achieved; among them, 3 continuous variables achieve the linearization of equation (17), and 2 0-1 variables limit the values of the 3 continuous variables, thereby limiting the interval where it is located. The specific steps are as follows:

[0184] Find the breakpoints of the piecewise linear function in equation (17). Equation (17) consists of two linear functions, so it has 3 breakpoints. Let them be respectively in ascending order , and , and their mathematical expressions are as follows:

[0185]

[0186] ——(18)

[0187] Secondly, use 3 continuous variables and 3 breakpoints to replace the independent variable , and the replacement formula is as follows:

[0188] ——————————————(19)

[0189] Then, use 3 continuous variables and equation (17) to replace the SOC calculation formula. The calculation formula is as follows:

[0190] ——————————————(20)

[0191] Finally, impose constraints on 3 continuous variables and 2 0-1 variables to limit the interval where it is located. The constraint conditions are as follows:

[0192] ——————————————(21)

[0193] ——————————————————(22)

[0194] ————————————————————(23)

[0195] ————————————————(24)

[0196] ————————————————————(25)

[0197] The non-linear constraint equation (15) is transformed into a linear constraint condition composed of equations (19) to (25) to facilitate the solution of the energy management method for the photovoltaic-storage system.

[0198] Example 2. Referring to the appendix Figure 1 , based on Example 1, a solar thermal management method based on the performance degradation of the energy storage system is proposed. The method includes the following steps:

[0199] Derive the multi-objective equations for the operating cost and carbon emissions of the photovoltaic-storage system, so as to achieve the dual optimization of the operating cost and carbon emissions as the optimization objectives; in order to explore the curtailment rate of the photovoltaic-storage system itself, this method constructs an objective function for the operating cost of the system on the premise that only power can be purchased from the power grid. The calculation formula is as follows:

[0200] ————————(1)

[0201] In the formula, represents the operating cost of the photovoltaic-storage system, T represents the scheduling period, represents t the electricity purchase price at time represents t the exchanged power between the photovoltaic-storage system and the power grid at time represents the sampling time interval.

[0202] In the photovoltaic-storage system, carbon emissions mainly come from the electricity purchased from the power grid and the output of the photovoltaic power generation system. This method assumes that all the electricity purchased from the power grid is produced by traditional fossil fuel power plants, which will therefore result in a large amount of CO 2 emissions. The calculation formula is as follows:

[0203] ——————————————(2)

[0204] In the formula, represents the CO 2 emissions generated by the electricity purchased by the system from the power grid, represents the CO 2 emissions generated by traditional fossil fuel power plants when producing 1 kWh of electricity.

[0205] In addition, CO 2 emissions will also be generated during the production, construction and component transportation of the photovoltaic power generation system. The calculation formula is as follows:

[0206] ——————————(3)

[0207] In the formula, Indicates the CO 2 emissions generated during the production, construction, and component transportation of the photovoltaic power generation system, Indicates the CO 2 emissions generated when the photovoltaic power generation system produces 1 kWh of electricity, Indicates t the output of the photovoltaic power generation system at time

[0208] Therefore, the carbon emission target equation of the photovoltaic-storage system can be expressed as:

[0209] ——————————————(4)

[0210] In the formula, represents the total carbon emissions of the photovoltaic-storage system;

[0211] To comprehensively consider the operating cost and carbon emissions of the photovoltaic-storage system, this method constructs a multi-objective function equation based on equations (1) and (4) to obtain the optimal low-carbon economic operation strategy of the system. Its mathematical expression is as follows:

[0212] ——————————(5)

[0213] In the formula, represents the optimization objective of the operating cost and carbon emissions of the photovoltaic-storage system.

[0214] Design the performance degradation constraint conditions of the energy storage system and feedback them to the energy management method of the photovoltaic-storage system. Adjust the maximum charge and discharge power in real time according to the health state of the energy storage system to solve the problem of unreasonable energy management caused by the performance degradation of the energy storage system during the operation of the photovoltaic-storage system; (1) State of Charge (SOC) upper and lower limit constraints

[0215] ————————————————(6)

[0216] In the formula, represents the SOC of the energy storage system at t time, and respectively represent the upper and lower limits of the SOC of the energy storage system.

[0217] (2) Charge and discharge power constraints

[0218] ——————————(7)

[0219] ————————(8)

[0220] In the formula, and respectively represent the charging and discharging powers of the energy storage system at t moment, and respectively represent the maximum charging and discharging powers of the energy storage system at t moment.

[0221] (3) SOC conversion constraint between adjacent moments

[0222]

[0223] ————(9)

[0224] In the formula, SOC of the energy storage system at time t, SOC of the energy storage system at time t - 1, represents the actual maximum available capacity of the energy storage system at time t - 1, represents the charging efficiency of the energy storage system, represents the discharging efficiency of the energy storage system, is a binary variable representing the charging and discharging state of the energy storage system, represents the charging state, represents the discharging state.

[0225] Furthermore, in this method, the performance degradation of the energy storage system during operation is used as a constraint condition so that the established energy management method can take into account the impact of the reduction of the maximum available capacity and the maximum charging and discharging powers of the energy storage system on the energy management of the PV - energy storage system. According to the definition of the State of Health (SOH), the actual maximum available capacity t of the energy storage system at moment, the maximum charging power and the maximum discharging power can be expressed as:

[0226] ——————————————————(10)

[0227] ————————(11)

[0228] ————(12)

[0229] In the formula, represents the rated capacity of the energy storage system, and respectively represent the rated maximum charging and discharging powers of the energy storage system, Indicates the health state of the energy storage system at t the moment.

[0230] Furthermore, substituting equations (10), (11) and (12) into equations (7), (8) and (9), the constraint conditions considering the performance degradation of the energy storage system are obtained.

[0231] ————————————(13)

[0232] ——————————(14)

[0233]

[0234] ——————(15)

[0235] Comparatively analyze the impact of the performance degradation of the energy storage system on the energy management of the PV - energy storage system. Under the condition of ignoring the performance degradation of the energy storage system, the constraints of the actual maximum available capacity , the maximum charging power and the maximum discharging power are such that SOH = 100% in equations (13), (14) and (15).

[0236] Based on the piece - wise linear function linearization method, the non - linear constraints are converted into linear constraints, and the MINLP problem is converted into an easily solvable MILP problem to improve the solution accuracy of the multi - objective energy management problem; the constraint condition equation (15) is a non - linear constraint condition containing binary variables and judgment conditions. To convert it into a linear constraint, this paper uses to uniformly represent the charging and discharging power of the energy storage system. The relationship with and can be expressed as:

[0237] ——————————(16)

[0238] Then equation (15) can be further expressed as:

[0239] ——(17)

[0240] For equation (17), 3 continuous variables , and , as well as 2 0 - 1 variables and , a linearization transformation is achieved. Among them, 3 continuous variables achieve the linearization of formula (17), and 2 0-1 variables limit the values of the 3 continuous variables, thereby limiting the interval where it is located. The specific steps are as follows:

[0241] First, find the breakpoints of the piecewise linear function in formula (17). Formula (17) consists of two linear functions, so it has 3 breakpoints. Let them be , and in ascending order. Their mathematical expressions are as follows:

[0242]

[0243] ————(18)

[0244] Secondly, use 3 continuous variables and 3 breakpoints to replace the independent variable , and the replacement formula is as follows:

[0245] ——————————————(19)

[0246] Then, use 3 continuous variables and formula (17) to replace the SOC calculation formula. The calculation formula is as follows:

[0247] ——————————————(20)

[0248] Finally, impose constraints on 3 continuous variables and 2 0-1 variables to limit the interval where it is located. The constraint conditions are as follows:

[0249] ——————————————(21)

[0250] ——————————————————(22)

[0251] ————————————————————(23)

[0252] ————————————————(24)

[0253] ————————————————————(25)

[0254] It can be seen that the non-linear constraint formula (15) can be transformed into the linear constraint conditions composed of formulas (19) to (25), so as to facilitate the solution of the energy management method of the photovoltaic-storage system.

[0255] Formulate the power scheduling plan of the photovoltaic-storage system according to the health status of the energy storage system and the optimization goal.

[0256] Example 3, based on Example 2, the following example is proposed:

[0257] The experimental data comes from the California Integrated Energy System dataset in the United States and is used for the multi-objective energy management method considering the performance degradation of the energy storage system in the photovoltaic-storage system. In addition, in order to verify the effectiveness of the proposed method, 7 scenarios are set according to whether the performance degradation of the energy storage system, carbon emissions and operating costs are considered, and whether the energy storage system is configured: (1) no energy storage system is configured; (2) carbon emissions are considered; (3) operating costs are considered; (4) carbon emissions and operating costs are considered; (5) carbon emissions and performance degradation of the energy storage system are considered; (6) operating costs and performance degradation of the energy storage system are considered; (7) carbon emissions, operating costs and performance degradation of the energy storage system are considered, that is, the method proposed in this patent.

[0258] In order to simulate the operation of the system, Table 1 gives the relevant parameters of the photovoltaic-storage system, Figure 2 showing the change of the system electricity price over time.

[0259] Table 1

[0260] The performance results of the patented technology on the test data

[0261]

[0262] Table 2 shows the carbon emissions, light curtailment rate, and operating costs of the patented technology on the test data. It can be seen that the method proposed in this patent can make the carbon emissions close to those of the energy management method targeting carbon emissions, while making the operating costs close to those of the energy management method targeting operating costs. Therefore, the patented technology can comprehensively consider the advantages of both, thereby achieving the dual optimization of carbon emissions and operating costs. In addition, after considering the performance degradation of the energy storage system, the system's carbon emissions, light curtailment rate, and operating costs all increase. This is because the performance degradation of the energy storage system leads to a reduction in its available capacity and a decline in its spatio-temporal transfer ability. Further, Table 3 shows the service life of the energy storage system of the patented technology on the test data. The analysis shows that the energy storage system of the patented technology has the longest service life, reaching 1887 days, serving 94 days more than the multi-objective optimization energy management method that does not consider the performance degradation of the energy storage system. In addition, after considering the performance degradation of the energy storage system, the service life of the energy storage system in all scenarios increases significantly. Among them, the service life of the energy management method targeting operating costs increases by 98 days, while the service life of the energy management method targeting carbon emissions increases by 223 days. This is because incorporating the performance degradation of the energy storage system as a constraint into the energy management method established in this patent can provide true and reliable information on the degradation state of the energy storage system for formulating energy management strategies, avoiding the use capacity and charge-discharge speed exceeding the battery's tolerance during long-term use, thereby extending its service life.

[0263] In summary, the method proposed in this patent can not only achieve the dual optimization of the operating costs and carbon emissions of the photovoltaic-energy storage system, but also adjust the maximum charge-discharge power in real time according to the health status of the energy storage system, solve the problem of unreasonable energy management caused by the performance degradation of the energy storage system during operation, and effectively extend the service life of the energy storage system.

[0264] Table 2

[0265] The carbon emissions, light curtailment rate, and operating costs of the patented technology on the test data

[0266]

[0267] Table 3

[0268] The service life of the energy storage system of the patented technology on the test data

[0269]

[0270] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A solar thermal management system based on energy storage system performance degradation, characterized in that: The system comprises: Multi-objective equation derivation module, used for multi-objective equations of photovoltaic-energy storage system operation cost and carbon emissions; A constraint condition setting module, used to set the constraint conditions for performance degradation of the energy storage system; Model linearization module, used for model linearization based on piecewise linear function linearization method; model linearization module includes: Use P b (t) represents the charging and discharging power of the energy storage system, and P b-charge (t) and P b-discharge The relationship between (t) can be expressed as: Among them, P b-charge (t) and P b-discharge (t) represent the charging and discharging power of the energy storage system at time t, respectively; Then the constraints under the condition of energy storage system performance degradation are: In the formula, Indicates the rated capacity of the energy storage system, and They represent the maximum rated charging and discharging power of the energy storage system, SOC(t) represents the SOC of the energy storage system at time t, SOC(t-1) represents the SOC of the energy storage system at time t-1, SOH(t) represents the health status of the energy storage system at time t, SOH(t-1) represents the health status of the energy storage system at time t-1, η ch Represents the charging efficiency of the energy storage system, η dis Indicates the discharge efficiency of the energy storage system; For formula (17), three continuous variables w1(t), w2(t) and w3(t), and two 0-1 variables z1(t) and z2(t) can be used to realize linear transformation; the three continuous variables realize the linearization of formula (17), and the two 0-1 variables limit the values ​​of the three continuous variables, thereby limiting P b The specific steps for the interval where (t-1) is located are as follows: Find the dividing point of the piecewise linear function of formula (17). Formula (17) consists of two linear functions, so it has three dividing points. Let them be b1, b2 and b3 in increasing order. The mathematical expression is as follows: Secondly, the independent variable P was replaced by three continuous variables and three cut-off points. b (t-1), the replacement formula is as follows: Then, the SOC calculation formula is replaced by three continuous variables and formula (17), and the calculation formula is as follows: Finally, constraints are imposed on the three continuous variables and the two 0-1 variables to limit P b The interval where (t-1) is located has the following constraints: w1(t)+w2(t)+w3(t)=1——————————————(21) z1(t)+z2(t)=1——————————————————(22) w1(t)≤z1(t)————————————————————(23) w2(t)≤z1(t)+z2(t)————————————————(24) w3(t)≤Z2(t)————————————————————(25) The nonlinear constraint is transformed into a linear constraint consisting of equations (19) to (25) to facilitate the solution of the energy management method of the photovoltaic-energy storage system; The scheduling module is used to formulate a power scheduling plan for the photovoltaic-energy storage system based on the health status of the energy storage system and the optimization objectives.

2. A solar thermal management system based on energy storage system performance degradation according to claim 1, characterized in that: The multi-objective equation derivation module constructs the system operation cost objective function, and its calculation formula is as follows: In the formula, O system represents the operating cost of the photovoltaic-energy storage system, T represents the scheduling period, c spot (t) represents the electricity purchase price at time t, P grid (t) represents the exchange power between the photovoltaic-energy storage system and the grid at time t, and Δt represents the sampling time interval; In the photovoltaic-energy storage system, carbon emissions come from the electricity purchased from the grid and the output of the photovoltaic power generation system; assuming that all the electricity purchased from the grid is produced from traditional fossil fuel power plants, thus resulting in a large amount of CO2 emissions, the calculation formula is as follows: In the formula, C grid Represents the CO2 emissions generated by the electricity purchased by the system from the grid, It represents the CO2 emissions generated by producing 1 kWh of electricity in a traditional fossil fuel power plant; In addition, CO2 emissions are also generated during the production and construction of photovoltaic power generation systems and the transportation of components. The calculation formula is as follows: In the formula, C pv Represents CO2 emissions generated during the production and construction of photovoltaic power generation systems and the transportation of components. P represents the CO2 emissions generated by the photovoltaic power generation system to produce 1kWh of electricity. pv_generation (t) represents the output of the photovoltaic power generation system at time t; The carbon emission target equation of the photovoltaic-energy storage system is expressed as: C system =min(C grid +C pv )———————————————(4) In the formula, C system Represents the total carbon emissions of the PV-storage system; In order to comprehensively consider the operating cost and carbon emissions of the photovoltaic-energy storage system, a multi-objective function equation is constructed based on equations (1) and (4) to obtain the optimal low-carbon economic operation strategy of the system. Its mathematical expression is as follows: C multi-objective =C system +O system ——————————(5) In the formula, C multi-objective Represents the optimization target of the operating cost and carbon emission of the photovoltaic-energy storage system.

3. A solar thermal management method based on energy storage system performance degradation, applying the solar thermal management system based on energy storage system performance degradation according to any one of claims 1-2, characterized in that: The method comprises the following steps: Derive the multi-objective equations of the operating cost and carbon emissions of the photovoltaic-energy storage system, so as to achieve dual optimization of operating cost and carbon emissions as the optimization target; Design the performance degradation constraints of the energy storage system and feed them back to the energy management method of the photovoltaic-energy storage system. Adjust the maximum charge and discharge power in real time according to the health status of the energy storage system to solve the unreasonable energy management problem caused by the performance degradation of the energy storage system during the operation of the photovoltaic-energy storage system. Based on the piecewise linear function linearization method, nonlinear constraints are converted into linear constraints, and MINLP problems are converted into MILP problems that are easy to solve, thereby improving the accuracy of solving multi-objective energy management problems. b (t) represents the charging and discharging power of the energy storage system, and P b-charge (t) and P b-discharge The relationship between (t) can be expressed as: Among them, P b-charge (t) and P b-discharge (t) represent the charging and discharging power of the energy storage system at time t, respectively; Then the constraints under the condition of energy storage system performance degradation are: In the formula, Indicates the rated capacity of the energy storage system, and They represent the maximum rated charging and discharging power of the energy storage system, SOC(t) represents the SOC of the energy storage system at time t, SOC(t-1) represents the SOC of the energy storage system at time t-1, SOH(t) represents the health status of the energy storage system at time t, SOH(t-1) represents the health status of the energy storage system at time t-1, η ch Represents the charging efficiency of the energy storage system, η dis Indicates the discharge efficiency of the energy storage system; For formula (17), three continuous variables w1(t), w2(t) and w3(t), and two 0-1 variables z1(t) and z2(t) can be used to realize linear transformation; the three continuous variables realize the linearization of formula (17), and the two 0-1 variables limit the values ​​of the three continuous variables, thereby limiting P b The specific steps for the interval where (t-1) is located are as follows: Find the dividing point of the piecewise linear function of formula (17). Formula (17) consists of two linear functions, so it has three dividing points. Let them be b1, b2 and b3 in increasing order. The mathematical expression is as follows: Secondly, the independent variable P was replaced by three continuous variables and three cut-off points. b (t-1), the replacement formula is as follows: Then, the SOC calculation formula is replaced by three continuous variables and formula (17), and the calculation formula is as follows: Finally, constraints are imposed on the three continuous variables and the two 0-1 variables to limit P b The interval where (t-1) is located has the following constraints: w1(t)+w2(t)+w3(t)=1——————————————(21) z1(t)+z2(t)=1——————————————————(22) w1(t)≤z1(t)————————————————————(23) w2(t)≤z1(t)+z2(t)————————————————(24) w3(t)≤z2(t)————————————————————(25) The nonlinear constraint is transformed into a linear constraint consisting of equations (19) to (25) to facilitate the solution of the energy management method of the photovoltaic-energy storage system; Formulate a power dispatch plan for the photovoltaic-energy storage system based on the health status and optimization objectives of the energy storage system.

4. A solar thermal management method based on energy storage system performance degradation according to claim 3, characterized in that: The system operation cost objective function is constructed, and its calculation formula is as follows: In the formula, O system represents the operating cost of the photovoltaic-energy storage system, T represents the scheduling period, c spot (t) represents the electricity purchase price at time t, P grid (t) represents the exchange power between the photovoltaic-energy storage system and the grid at time t, and Δt represents the sampling time interval; In the photovoltaic-energy storage system, carbon emissions come from the electricity purchased from the grid and the output of the photovoltaic power generation system; assuming that all the electricity purchased from the grid is produced from traditional fossil fuel power plants, thus resulting in a large amount of CO2 emissions, the calculation formula is as follows: In the formula, C grid Represents the CO2 emissions generated by the electricity purchased by the system from the grid, It represents the CO2 emissions generated by producing 1 kWh of electricity in a traditional fossil fuel power plant; In addition, CO2 emissions are also generated during the production and construction of photovoltaic power generation systems and the transportation of components. The calculation formula is as follows: In the formula, C pv Represents CO2 emissions generated during the production and construction of photovoltaic power generation systems and the transportation of components. P represents the CO2 emissions generated by the photovoltaic power generation system to produce 1kWh of electricity. pv_generation (t) represents the output of the photovoltaic power generation system at time t; The carbon emission target equation of the photovoltaic-energy storage system is expressed as: In the formula, C system Represents the total carbon emissions of the PV-storage system; In order to comprehensively consider the operating cost and carbon emissions of the photovoltaic-energy storage system, a multi-objective function equation is constructed based on equations (1) and (4) to obtain the optimal low-carbon economic operation strategy of the system. Its mathematical expression is as follows: C multi-objective =C system +O system ——————————(5) In the formula, C multi-objective Represents the optimization target of the operating cost and carbon emission of the photovoltaic-energy storage system.

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