Regional power grid optimization scheduling method considering echelon utilization of retired power batteries

Abstract

A regional power grid optimal scheduling method considering echelon utilization of retired power batteries comprises the following steps: acquiring unit parameters of a regional power grid, and establishing a physical model of the regional power grid; setting a regional power grid power optimization scheduling objective function, a regional power grid power optimization scheduling constraint condition, a decommissioned power battery energy storage system power optimization scheduling objective function and a decommissioned power battery energy storage system power optimization scheduling constraint condition; a regional power grid optimization scheduling strategy considering energy storage multi-application scene collaboration and decommissioning power battery energy storage power station attenuation characteristics is adopted, and a regional power grid optimization scheduling model considering the decommissioning power battery energy storage power station attenuation characteristics is constructed; solving the provided model by using a solver to obtain an optimal scheduling plan; the optimization scheduling plan is automatically obtained by considering energy storage multi-application scene collaboration and the attenuation characteristics of the retired power battery energy storage power station, the method can be used for real-time scheduling of a regional power grid containing the retired power battery energy storage power station, the scheduling method is wide in applicability, and a regulation and control system is easy to implement.

Description

Technical Field

[0001] The present invention belongs to the technical fields of power systems and intelligent control, and relates to an optimized dispatching method for regional power grids considering the cascade utilization of retired power batteries. Background Art

[0002] The high-proportion access of new energy to the power grid has become an irresistible trend. With the continuous increase in the installed capacity of new energy such as wind power, the proportion of power generation of conventional power sources represented by thermal power will continue to decrease. In the future, the proportion of new energy such as wind and light in the power generation side will continue to increase. However, new energy such as wind and light has obvious anti-peak shaving characteristics and uncertainties. Therefore, reasonably configuring energy storage can effectively improve the new energy consumption ratio and provide strong support for the sustainable and healthy development of renewable energy. Traditional energy storage power stations occupy a large amount of land, will cause serious impacts on the ecological environment, have relatively high construction and operation costs, and a long construction period. In addition, they are subject to specific geographical conditions and are not applicable to all regions, with limited application scope. The retired power battery energy storage power station has significant advantages compared with other forms of traditional energy storage power stations. The retired power battery energy storage power station uses waste electric vehicle batteries, extends the service life of the batteries, and reduces waste and environmental pollution. However, the capacity of a single retired power battery energy storage power station is limited, and it is uneconomical to participate in power grid dispatching alone. Moreover, due to the previous use, the aging of retired power batteries is relatively serious, and the performance decay differences of different retired power batteries need to be considered during dispatching. Otherwise, it will lead to frequent overcharging and over-discharging of retired power batteries, which will further cause the accelerated aging of retired power batteries, a significant reduction in service life, and ultimately lead to the premature scrapping of the retired power battery energy storage power station.

[0003] Currently, the research on the participation of retired power battery energy storage in the optimized dispatching of the power system source-network-load-storage mainly focuses on the characteristics of the retired power battery energy storage power station itself and its operation mode. Karami H et al. showed that due to the different aging conditions of each retired battery energy storage power station, even if their initial performances are similar, but due to their different health states, if the attenuation characteristics of the retired power battery energy storage power station are not considered in the dispatching model, in the later use, there will also be a situation where the retired power battery energy storage power station with poor performance cannot output according to the instructions given by the dispatching center due to inconsistent health states. Zhu Jiahua et al. proposed a dispatching scheme considering the faults of retired power batteries and the attenuation characteristics of retired power battery energy storage power stations. Simulation calculations showed that considering the attenuation characteristics of retired power batteries in the dispatching scheme can improve system economy and reduce the risk of load loss during dispatching. Yu Xinyue et al. showed through simulation calculations that by considering the comprehensive benefits of energy storage in multiple application scenarios in the dispatching strategy, the economic benefits of the energy storage system can be improved, but the coordinated control between retired power energy storage power stations and their attenuation characteristics are not considered.

[0004] Most of the research on the participation of retired power battery energy storage in the optimal dispatching of the power system's source, grid, load, and storage focuses on the single performance characteristics of the energy storage power station itself or its operation mode, resulting in a single revenue model for retired power energy storage power stations. In addition, due to insufficient consideration of the attenuation characteristics of retired power battery energy storage power stations, existing dispatching algorithms are likely to cause retired power batteries to age prematurely, significantly reducing their service life and ultimately leading to the early scrapping of retired power battery energy storage power stations. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide an optimal dispatching method for regional power grids considering the cascaded utilization of retired power batteries, an optimal dispatching strategy for regional power grids considering the coordination of multiple application scenarios of energy storage and the attenuation characteristics of retired power battery energy storage power stations, and to construct an optimal dispatching model for regional power grids considering the attenuation characteristics of retired power battery energy storage power stations.

[0006] To solve the above technical problems, the technical solution adopted by the present invention is: an optimal dispatching method for regional power grids considering the cascaded utilization of retired power batteries, comprising the following steps: Step 1, obtain the predicted values of load and wind power; Step 2, set the operation and maintenance costs of thermal power generating units and the revenue and loss costs of retired power battery energy storage power stations; including the operation and maintenance costs of thermal power generating units, the revenue of retired power battery energy storage, the operation loss costs of retired power battery energy storage power stations, and the life loss costs of retired power battery energy storage power stations; Step 3, define the upper-layer optimal objective of the regional power grid and establish a control model; including the upper-layer power optimal dispatching model of the regional power grid and the constraint conditions; Step 4, define the lower-layer energy storage output optimal objective and establish a control model; including the lower-layer power optimal dispatching model of the energy storage power station and the constraint conditions; Step 5, obtain the optimal output plan; Step 6, equipment installation and construction of the regulation and control system.

[0007] In Step 1, the main influencing factor of wind power is the wind speed of the wind farm, and the probability density function of the natural wind speed is shown in Equation (1): ; (1) In the formula: represents the natural wind speed; represents the shape parameter of the Boolean distribution; represents the time parameter of the Boolean distribution; The relationship between wind power and wind speed is shown in Equation (2): ; (2) In the formula, represents the actual wind power, represents the rated output power of the wind turbine; , respectively represent the cut-in and cut-out wind speeds for the start-up and locking of the wind turbine; The predicted value of the load output is given by the power grid and is revised according to the changes in the actual working conditions; After obtaining the above parameters, a physical model of the wind farm is built using the MATLAB modeling and simulation software.

[0008] In Step 2, the operating cost of the thermal power unit is mainly the coal consumption cost, and its expression is: ; (3) In the formula, At the power generation cost function of the conventional thermal power generation unit at time represents at time the output power of the th thermal power generation unit, is the coal consumption coefficient of the unit .

[0009] In Step 2, the energy storage participates in different application scenarios to obtain different economic benefits. Its benefits include increasing the consumption benefit of renewable energy, reducing the assessment benefit of new energy grid connection, peak shaving and frequency modulation ancillary service benefit, spinning reserve benefit, and delaying the power grid investment benefit; for the time scale of day-ahead scheduling, analyze the benefits and coordinated application value of energy storage in three application scenarios: peak-valley arbitrage, fluctuation suppression, and power prediction error compensation; specifically include: The benefit of energy storage in the peak-valley arbitrage scenario: ; (4) In the formula, is the on-grid electricity price of wind power, represents the discharge power of the th retired power battery energy storage power station at time, represents the charging power of the th retired power battery energy storage power station at time; The benefit of energy storage in the fluctuation suppression scenario: Applying energy storage to the scenario of suppressing wind power fluctuations, alleviating wind power fluctuations, and reducing the penalty caused by the power change exceeding the fluctuation limit. In addition, the energy storage power station suppresses the power fluctuation of the connection line between the wind-storage combined system and the power grid, reduces the change rate of the active power of the connection line, and thus obtains benefits, as shown in the following formula: ; (5) In the formula, represents the output of the wind-storage combined system, represents the wind power fluctuation penalty coefficient, Wind power fluctuation assessment electricity Wind power change limit Benefit of energy storage in the scenario of wind power prediction error compensation: Different from the fluctuation suppression assessment which examines the output fluctuation of the wind farm and the power fluctuation of the tie line, the energy storage power prediction error compensation examines the error between the predicted output of wind power and the actual output; when the wind power exceeds the allowable range of prediction error, the retired power battery energy storage power station in the wind-storage combined system needs to compensate the output of the wind farm. If it still exceeds the allowable range after compensation, a wind power prediction error penalty cost will be generated, as shown in Equation (6): ;(6) In the formula, represents the wind power prediction error penalty coefficient, Wind power prediction error assessment electricity represents the upper limit of the allowable error of wind power, represents the lower limit of the allowable error of wind power.

[0010] In Step 2, due to the electrochemical reaction inside the battery, the lithium ion concentration decreases, the thickness of the electrode and the electrolyte increases, and at the same time, precipitation substances are generated on the surface of the electrode, increasing the resistance, which in turn causes the attenuation of the battery performance and generates the degradation cost of the retired power battery energy storage power station; in addition, since the electrical energy and chemical energy cannot be completely converted during the electrochemical reaction of the battery, part of the energy will be lost inside the retired power battery energy storage power station during the charging and discharging processes of the battery due to the heat effect and self-discharge of the battery in the idle state, which is expressed as the efficiency loss electricity. Combining with the corresponding electricity price when the regional power grid interacts with the external power grid, it is converted into the efficiency loss cost; ;(7) In the formula, 、 respectively represent the charging efficiency and discharging efficiency of the th retired power battery energy storage power station; is the depth of discharge; is the maximum available capacity of the retired power battery energy storage power station; is the electricity of the retired power battery energy storage power station; is the purchase cost per unit of electricity of a new battery; is the sorting and grouping cost of retired power batteries.

[0011] In Step 2, the life loss of each charge and discharge of the retired power battery energy storage power station is mainly related to the depth of charge and discharge, which is expressed as: ;(8) Among them, An expression, as shown in Equation (9): ;(9) In the formula, and represent the coefficients of the fitting function between the life of the retired power battery energy storage power station and the depth of discharge; Among them, An expression, as shown in Equation (10): ;(10).

[0012] In Step 3, the upper layer is the coordinated dispatching layer among the units within the regional power grid. Taking the output of thermal power units, the interactive power between the regional power grid and the external power grid, and the overall output of the energy storage system as optimization variables, with the goal of minimizing the total operating cost of the regional power grid; ;(11) In the formula, and respectively represent the electricity sales revenue and peak-valley arbitrage revenue of the wind-storage system's daily operation, represents the cost of the energy storage system, represents the cost of smoothing fluctuations of the tie line, represents the penalty cost for the output fluctuation of the wind-storage combined system, represents the penalty cost for the medium-term wind power prediction error, represents the penalty cost for wind curtailment, represents the operating cost of thermal power units, represents the interactive cost between the regional power grid and the external power grid; Conventional thermal power units basically do not start and stop within a day. Therefore, the start-stop time constraint of the unit is not considered in the constraint conditions; specifically including: Regional power grid power generation and supply balance constraint: ;(12) In the formula, represents the load power at time; Thermal reserve constraint: ;(13) In the formula, is the upper limit of the output of unit , is the maximum discharge power of the retired power battery energy storage system, represents the minimum reserve capacity; Thermal power unit constraint: The constraints of conventional generating units include the upper and lower limits of the output of generating units and the ramp rate constraint: ;(14) ;(15) In the formula, is the upper limit of the output of the th thermal power unit, is the lower limit of the output of the th thermal power unit, is the down-ramp rate of the unit, is the up-ramp rate of the unit; Energy storage charge and discharge state constraint: ;(16) In the formula, , respectively represent the discharge state and charge state of the energy storage system at the moment, and their values are 0 or 1; Energy storage charge and discharge power constraint: ;(17) Energy storage state of charge constraint: ;(18) To ensure the reliability and safety of the energy storage power station during long-term operation and reduce the life loss caused by use, it is necessary to ensure that the SOC of the energy storage power station is equal at the beginning and end of each charge and discharge cycle, as shown in Equation (19): ;(19) ;(20) In the formula, represents the state of charge of the retired power battery energy storage system at the moment, represents the rated capacity of the retired power battery energy storage system, , respectively represent the minimum and maximum values of the state of charge of the energy storage system; Energy storage output constraint under multiple application scenarios: ;(21) ;(22) In the formula, represents the output of the energy storage system used in the wind energy storage system, represents the output power of the entire energy storage system applied to the power prediction error compensation scenario, represents the output power of the entire energy storage system applied to the scenario of suppressing wind power fluctuations, all of which are the same as the total output state of the energy storage system and not greater than the output of the entire energy storage system; Constraint on selling and purchasing electricity from / to the external power grid: ;(23) ; (24) In the formula, is the maximum allowable power for the regional power grid to purchase electricity from the external power grid; is the maximum allowable power for the regional power grid to sell electricity to the external power grid.

[0013] In step 4, aiming at minimizing the life loss of the energy storage system, considering the differences in life loss of different retired power battery energy storage power stations for decision-making, an optimal scheduling model of the energy storage system based on multiple retired battery energy storage power stations is established, and the objective function is: ; (25) The constraint conditions include: Charge and discharge state constraints of retired power battery energy storage power stations: ; (26) In the formula, , respectively represent the discharge state and charge state of the retired power battery energy storage power station at time , and their values are 0 or 1; Charge and discharge power constraints of retired power battery energy storage power stations: State of charge constraints of retired power battery energy storage power stations: ; (28) ; (29) ; (30) In the formula, represents the state of charge of the retired power battery energy storage power station at time , represents the rated capacity of the retired power battery energy storage power station , respectively represent the upper and lower limits of the state of charge of the retired power battery energy storage power station .

[0014] In step 5, the optimal scheduling model of the regional power grid considering the cascade utilization of retired power batteries is simulated using the Matlab platform and solved by calling the Curobi solver, specifically including: Step 5-1, set the initial output plan of the energy storage system, input the predicted values of load and wind power, and at the same time input the time-of-use electricity price and the parameters of the energy storage system state regional power grid; Step 5-2: Set the objective function and constraints. The upper-layer regional power grid optimization scheduling model aims to minimize the total operating cost of the regional power grid, and the lower-layer energy storage system optimization scheduling model aims to minimize the life loss of the energy storage system, and their respective constraints are set. Step 5-3: Call the Gurobi solver to solve the scheduling model and obtain the decision variables of the charge and discharge plans of each energy storage power station. Step 5-4: Determine whether the maximum number of iterations is reached. Only when the maximum number of iterations is reached can the optimal scheduling plan be output.

[0015] In Step 6, it specifically includes: Step 6-1: Install voltage sensors, current sensors, and power sensors on each unit of the selected reference regional power grid. The sensor deployment should be consistent with the data points taken in the simulation. Install retired power battery energy storage power stations with adjustable output in the regional power grid. Check that all scheduling objects can be normally scheduled locally or remotely. Step 6-2: Install a control background, servers, and other necessary communication devices according to the actual situation of the regional power grid. Establish a control object point table, and use OPC UA or other industrial automation specifications to achieve four-remote communication. Build a monitoring system on the control background and debug it. Step 6-3: Implement the simulation process to obtain the optimal scheduling parameter combination. Write a scheduling program and implant it into the background monitoring system, and debug and trial-run the scheduling program. Step 6-4: Long-term run the scheduling program, read the output of each unit of the regional power grid in real time, and find the scheduling parameters according to the predicted output values of each unit of the regional power grid to achieve the optimal scheduling of the regional power grid with retired power battery energy storage power stations.

[0016] The main beneficial effects of the present invention are as follows: Based on retired power battery energy storage power stations, a regional power grid system that can realize large-scale cascade utilization of retired power batteries is constructed, providing a feasible solution for the large-scale recycling of retired power batteries and enhancing the economic benefits of the entire life cycle of power batteries.

[0017] Combined with the attenuation characteristics of retired power batteries and the service capabilities of energy storage power stations in multiple scenarios, the comprehensive income situation of retired power battery energy storage power stations in the regional power grid is considered during scheduling, effectively enhancing the economic benefits of retired power battery energy storage power stations.

[0018] Using an original double-layer algorithm, the coupling of the regional power grid scheduling objective and the output objective of retired power battery energy storage power stations is completed, achieving the optimal overall output benefit of the system.

[0019] Introduce the income of energy storage in three scenarios: peak-valley arbitrage, fluctuation suppression, and power prediction error compensation, enhancing the economic benefits of retired power battery energy storage power stations during scheduling.

[0020] A retired power battery energy storage power station model considering attenuation characteristics is constructed.

[0021] Based on the retired power battery energy storage power station, a regional power grid system that can realize large-scale cascade utilization of retired power batteries is constructed. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The present invention will be further described below in conjunction with the drawings and embodiments.

[0023] Figure 1 It is a flow chart of the present invention.

[0024] Figure 2 It is a system architecture diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0025] As Figures 1 - 2 in, a regional power grid optimal scheduling method considering cascade utilization of retired power batteries Step 1: Obtain the load and wind power prediction values. The main influencing factor of wind power is the wind speed of the wind farm. The probability density function of the natural wind speed is shown in Equation (1): ; (1) In the formula: represents the natural wind speed; represents the shape parameter of the Boolean distribution; represents the time parameter of the Boolean distribution.

[0026] The relationship between wind power and wind speed is shown in Equation (2): ; (2) In the formula, represents the actual wind power, represents the rated output power of the wind turbine; , respectively represent the cut-in and cut-out wind speeds at which the wind turbine starts and locks.

[0027] The load output prediction value is given by the power grid and can be revised according to the changes in actual working conditions.

[0028] After the above parameters are obtained, a physical model of the wind farm is built using MATLAB simulation software.

[0029] Step 2: Set the operation and maintenance costs of thermal power generating units and the benefits and loss costs of retired power battery energy storage power stations. (1) Operation and maintenance costs of thermal power generating units The operating cost of a thermal power unit is mainly the coal consumption cost, and its expression is: ; (3) In the formula, At the power generation cost function of the conventional thermal power generation unit at time It means at time, the output power of the th thermal power generation unit, is the coal consumption coefficient of the unit .

[0030] (2) Revenue of retired power battery energy storage Energy storage participating in different application scenarios will obtain different economic benefits. Its revenue includes increasing the revenue of renewable energy consumption, reducing the revenue of new energy grid connection assessment, peak shaving and frequency modulation auxiliary service revenue, spinning reserve revenue, delaying grid investment revenue, etc. This method analyzes the revenue and its coordinated application value of energy storage in three application scenarios: peak-valley arbitrage, fluctuation suppression, and power prediction error compensation, for the time scale of day-ahead scheduling.

[0031] ① Revenue of energy storage in the peak-valley arbitrage scenario.

[0032] ; (4) In the formula, is the on-grid electricity price of wind power, It means the th retired power battery energy storage power station discharge power at time, It means the th retired power battery energy storage power station charge power at time.

[0033] ② Revenue of energy storage in the fluctuation suppression scenario.

[0034] Applying energy storage to the scenario of suppressing wind power fluctuations can relieve wind power fluctuations and reduce the penalty caused by power changes exceeding the fluctuation limit. In addition, the energy storage power station can suppress the power fluctuations of the connection line between the wind-storage combined system and the power grid, reduce the change rate of the active power of the connection line, and thus obtain revenue, as shown in the following formula: ; (5) In the formula, represents the output of the wind-storage combined system, represents the wind power fluctuation penalty coefficient, wind power fluctuation assessment electricity quantity, wind power change limit.

[0035] ③ Revenue of energy storage in the wind power prediction error compensation scenario Different from the assessment of suppressing fluctuations, which examines the output fluctuations of the wind farm and the power fluctuations of the tie line, the compensation for the prediction error of the energy storage power assesses the error between the predicted output of the wind power and the actual output. When the wind power exceeds the allowable range of the prediction error, the retired power battery energy storage power station in the wind-storage combined system needs to compensate for the output of the wind farm. If it still exceeds the allowable range after compensation, a penalty cost for the wind power prediction error will be generated, as shown in Equation (6): ;(6) In the formula, represents the penalty coefficient for the wind power prediction error, the electricity quantity for assessing the wind power prediction error, represents the upper limit of the allowable error of the wind power, represents the lower limit of the allowable error of the wind power.

[0036] (3)The operating loss cost of the retired power battery energy storage power station Due to the electrochemical reactions inside the battery, the concentration of lithium ions decreases, the thickness of the electrode and electrolyte increases, and at the same time, precipitation substances are generated on the surface of the electrode, increasing the resistance, which in turn causes the attenuation of the battery performance and generates the degradation cost of the retired power battery energy storage power station. In addition, because the electrical energy and chemical energy cannot be completely converted during the electrochemical reaction of the battery, part of the energy inside the retired power battery energy storage power station will be lost during use due to the heat effect during the charging and discharging processes of the battery and the self-discharge of the battery in the idle state, which can be expressed as the electricity quantity of efficiency loss. Combining with the corresponding electricity price when the regional power grid interacts with the external power grid, it can be converted into the efficiency loss cost.

[0037] ;(7) In the formula, , respectively represent the charging efficiency and discharging efficiency of the th retired power battery energy storage power station; is the depth of discharge; is the maximum available capacity of the retired power battery energy storage power station; is the electricity quantity of the retired power battery energy storage power station; is the purchase cost per unit electricity quantity of the new battery; is the sorting and grouping cost of the retired power battery.

[0038] (4)The life loss cost of the retired power battery energy storage power station The life loss of each charge and discharge of the retired power battery energy storage power station is mainly related to the depth of charge and discharge, and can be expressed as: ;(8) Among them, An expression, as shown in Equation (9): ;(9) In the formula, 、 represent the coefficients of the fitting function between the life of the retired power battery energy storage power station and the depth of discharge.

[0039] Among them, An expression, as shown in Equation (10): (10) Step 3, define the optimization objective of the upper-layer regional power grid, and establish a control model. (1) Upper-layer regional power grid power optimization dispatch model The upper layer is the coordinated dispatch layer among the units within the regional power grid. Taking the output of thermal power units, the interactive power between the regional power grid and the external power grid, and the overall output of the energy storage system as optimization variables, with the goal of minimizing the total operating cost of the regional power grid.

[0040] ;(11) In the formula, 、 respectively represent the electricity sales revenue and peak-valley arbitrage revenue of the wind energy storage system's daily operation, represents the cost of the energy storage system, represents the cost of smoothing fluctuations of the tie line, represents the penalty cost for the output fluctuation of the wind energy storage combined system, represents the penalty cost for the medium wind power prediction error, represents the penalty cost for wind curtailment, represents the operating cost of thermal power units, represents the interactive cost between the regional power grid and the external power grid.

[0041] (2) Constraint conditions Conventional thermal power units basically do not start and stop within a day. Therefore, the unit start-stop time constraint is not considered in the constraint conditions of this chapter.

[0042] ① Regional power grid power generation and supply balance constraint ;(12) In the formula, represents at the load power at the moment.

[0043] ② Thermal reserve constraint ;(13) In the formula, is the output upper limit of unit , is the maximum discharge power of the retired power battery energy storage system, Indicates the minimum reserve capacity.

[0044] ③ Thermal power unit constraints Constraints of conventional generating units include upper and lower limits of generating unit output and ramping constraints: ;(14) ;(15) In the formula, is the upper limit of the output of the th thermal power unit, is the lower limit of the output of the th thermal power unit, is the down-ramping rate of the unit, is the up-ramping rate of the unit.

[0045] ④ Energy storage charge and discharge state constraints ;(16) In the formula, , respectively represent the discharge state and charge state of the energy storage system at moment, and their values are 0 or 1.

[0046] ⑤ Energy storage charge and discharge power constraints ;(17) ⑥ Energy storage state of charge constraints ;(18) To ensure the reliability and safety of the energy storage power station during long-term operation and reduce the life loss caused by use, it is necessary to ensure that the SOC of the energy storage power station is equal at the beginning and end of each charge and discharge cycle, as shown in formula (19): ;(19) ;(20) In the formula, represents the state of charge of the retired power battery energy storage system at moment, represents the rated capacity of the retired power battery energy storage system, , respectively represent the minimum and maximum values of the state of charge of the energy storage system.

[0047] ⑦ Energy storage output constraints under multiple application scenarios ;(21) ;(22) In the formula, Indicates the output of the energy storage system for the wind - energy storage system, Indicates the output power of the entire energy storage system applied to the power prediction error compensation scenario, Indicates the output power of the entire energy storage system applied to the scenario of suppressing wind power fluctuations, which is the same as the total output state of the energy storage system and not greater than the output of the entire energy storage system.

[0048] ⑧ Constraints on power purchase and sale with the external power grid ;(23) ;(24) In the formula, is the maximum allowable power for the regional power grid to purchase electricity from the external power grid; is the maximum allowable power for the regional power grid to sell electricity to the external power grid.

[0049] Step 4: Define the optimization objective of the lower - layer energy storage output and establish a control model, (1) Lower - layer energy storage power optimization dispatch model Taking the minimum life loss of the energy storage system as the goal, considering the differences in life losses of different retired power battery energy storage power stations for decision - making, an energy storage system optimization dispatch model based on multiple retired power battery energy storage power stations is established. The objective function can be obtained as: ;(25) (2) Constraint conditions ① Charge - discharge state constraints of retired power battery energy storage power stations ;(26) In the formula, , respectively represent the discharge state and charge state of the retired power battery energy storage power station at time

[0050] ② Charge - discharge power constraints of retired power battery energy storage power stations ;(27) ③ State - of - charge constraints of retired power battery energy storage power stations ;(28) ;(29) ;(30) In the formula, represents the state - of - charge of the retired power battery energy storage power station at time represents the retired power battery energy storage power station rated capacity and respectively represent the upper and lower limits of the state of charge of the retired power battery energy storage power station .

[0051] Step 4: Obtain the optimal output plan The optimal dispatching model of the regional power grid considering the cascade utilization of retired power batteries is simulated using the Matlab platform and solved by calling the Curobi solver. The specific implementation process is shown in Figure 1 .

[0052] (1) Set the initial output plan of the energy storage system, input the predicted values of load and wind power, and at the same time input the regional power grid parameters such as time-of-use electricity price and energy storage system status.

[0053] (2) Set the objective function and constraints. The upper-layer optimal dispatching model of the regional power grid takes the minimum total operating cost of the regional power grid as the objective function, and the lower-layer optimal dispatching model of the energy storage system takes the minimum life loss of the energy storage system as the objective function, and sets their respective constraints.

[0054] (3) Call the Gurobi solver to solve the dispatching model to obtain decision variables such as the charge and discharge plans of each energy storage power station.

[0055] Judge whether the maximum number of iterations is reached. Only when the maximum number of iterations is reached can the optimal dispatching plan be output.

[0056] In the above method, a regional power grid system that can realize the large-scale cascade utilization of retired power batteries is constructed based on the retired power battery energy storage power station, providing a feasible solution for the large-scale recycling of retired power batteries and improving the economic benefits of the entire life cycle of power batteries.

[0057] Combined with the attenuation characteristics of retired power batteries and the service capabilities of energy storage power stations in multiple scenarios, the comprehensive revenue situation of retired power battery energy storage power stations in the regional power grid is considered during dispatching, effectively improving the economic benefits of retired power battery energy storage power stations.

[0058] An original double-layer algorithm is adopted to complete the coupling of the regional power grid dispatching target and the output target of the retired power battery energy storage power station, realizing the optimal overall output benefit of the system.

[0059] The revenue of energy storage in three scenarios of peak-valley arbitrage, fluctuation suppression, and power prediction error compensation is introduced to improve the economic benefits of retired power battery energy storage power stations during dispatching. A model of retired power battery energy storage power stations considering attenuation characteristics is constructed. A regional power grid system that can realize the large-scale cascade utilization of retired power batteries is constructed based on the retired power battery energy storage power station.

[0060] The above embodiments are only the preferred technical solutions of the present invention and should not be regarded as limitations on the present invention. The embodiments in this application and the features in the embodiments can be arbitrarily combined with each other without conflict. The protection scope of the present invention shall be the technical solutions recorded in the claims, including the equivalent replacement solutions of the technical features in the technical solutions recorded in the claims. That is, the equivalent replacement improvements within this scope are also within the protection scope of the present invention.

Claims

1. A regional power grid optimization dispatching method considering the cascade utilization of retired power batteries, characterized in that: The steps include: Step 1, obtaining load and wind power forecast values; Step 2: Set the operation and maintenance costs of thermal power generating units and the income and loss costs of retired power battery energy storage power stations; including the operation and maintenance costs of thermal power generating units, the income of retired power battery energy storage, the operation loss costs of retired power battery energy storage power stations, and the life loss costs of retired power battery energy storage power stations; Step 3, define the optimization target of the upper regional power grid and establish a control model; including the upper regional power grid power optimization dispatch model and constraint conditions; Step 4: define the optimization target of the lower-level energy storage output and establish a control model, including the power optimization scheduling model and constraint conditions of the lower-level energy storage power station; Step 5, obtaining the optimal output plan; Step 6: Equipment installation and control system construction.

2. The regional power grid optimization dispatching method considering the cascade utilization of retired power batteries according to claim 1 is characterized in that: In step 1, the main influencing factor of wind power is the wind speed of the wind farm. The probability density function of the natural wind speed is shown in formula (1): ； (1) Where: Indicates the natural wind speed; represents the shape parameter of the Boolean distribution; represents the time parameter of the Boolean distribution; The relationship between wind power and wind speed is shown in formula (2): ； (2) In the formula, represents the actual wind power, Indicates the rated output power of the wind turbine; , Respectively represent the cut-in and cut-out wind speeds for starting and locking of wind turbines; The load output forecast value is given by the power grid and revised according to the changes in actual working conditions; After the above parameters are obtained, the MATLAB modeling and simulation software is used to build a physical model of the wind farm.

3. The regional power grid optimization dispatching method considering the cascade utilization of retired power batteries according to claim 1 is characterized in that: In step 2, the operating cost of the thermal power unit is mainly the coal consumption cost, which is expressed as: ； (3) In the formula, exist The power generation cost function of conventional thermal power generating units at time, Indicated in Moment The output power of thermal power generating units, For the crew Coal consumption coefficient.

4. The regional power grid optimization dispatching method considering the cascade utilization of retired power batteries according to claim 1 is characterized in that: In step 2, energy storage participating in different application scenarios will obtain different economic benefits, including increasing the benefits of renewable energy consumption, reducing the benefits of new energy grid connection assessment, peak and frequency regulation auxiliary service benefits, spinning reserve benefits, and delayed grid investment benefits. Based on the time scale of day-ahead dispatch, the benefits of energy storage in the three application scenarios of peak-valley arbitrage, fluctuation smoothing, and power forecast error compensation and their coordinated application value are analyzed. Specifically, they include: The benefits of energy storage in peak-valley arbitrage scenarios: ；(4) In the formula, The on-grid electricity price of wind power is Indicates Retired power battery energy storage power stations The discharge power at the moment, Indicates Retired power battery energy storage power stations Charging power at the moment; Benefits of energy storage in volatility smoothing scenarios: Energy storage is applied to the scenario of smoothing wind power fluctuations, alleviating wind power fluctuations and reducing penalties caused by power changes exceeding fluctuation limits. In addition, energy storage power stations smooth out power fluctuations in the interconnection lines between the wind and storage combined system and the power grid, reducing the rate of change of active power in the interconnection lines and thus obtaining benefits, as shown in the following formula: ；(5) In the formula, represents the output of the wind-storage combined system, represents the wind power fluctuation penalty coefficient, Wind power fluctuation assessment power, Wind power variation limit; Benefits of energy storage in wind power forecast error compensation scenario: Unlike fluctuation smoothing, which assesses the fluctuation of wind farm output and interconnection line power, energy storage power prediction error compensation assesses the error between wind power prediction output and actual output. When wind power exceeds the allowable range of prediction error, the retired power battery energy storage station in the wind-storage combined system needs to compensate for the wind farm output. If it still exceeds the allowable range after compensation, a wind power prediction error penalty cost will be incurred, as shown in formula (6): ；(6) In the formula, represents the wind power prediction error penalty coefficient, Wind power forecast error assessment power, Indicates the upper limit of the error allowed for wind power. Indicates the lower limit of the allowable error of wind power.

5. The regional power grid optimization dispatching method considering the cascade utilization of retired power batteries according to claim 1 is characterized in that: In step 2, due to the electrochemical reaction inside the battery, the lithium ion concentration decreases, the thickness of the electrode and the electrolyte increases, and the reaction on the electrode surface produces precipitates, which increases the resistance, thereby causing the battery performance to decay, resulting in the degradation cost of the retired power battery energy storage station. In addition, since the electrical energy and chemical energy cannot be completely converted during the electrochemical reaction of the battery, the battery charging and discharging process is accompanied by thermal effects and the battery will self-discharge when idle, which will cause the retired power battery energy storage station to lose some energy when in use, which is expressed as efficiency loss electricity. Combined with the corresponding electricity price when the regional power grid interacts with the external power grid, it is converted into efficiency loss cost. ； (7) In the formula, , Respectively represent The charging efficiency and discharging efficiency of retired power battery energy storage power stations; is the discharge depth; The maximum available capacity of the retired power battery energy storage power station; The electricity of retired power battery energy storage power stations; The purchase cost per unit of power for new batteries; The cost of sorting and grouping retired power batteries.

6. The regional power grid optimization dispatching method considering the cascade utilization of retired power batteries according to claim 1 is characterized in that: In step 2, the life loss of each charge and discharge of the retired power battery energy storage power station is mainly related to the charge and discharge depth, which can be expressed as: ； (8) in, The expression is shown in formula (9): ；(9) In the formula, , The coefficients representing the fitting function between the life of the retired battery energy storage power station and the depth of discharge; in, The expression is shown in formula (10): ；(10)。 7. The regional power grid optimization dispatching method considering the cascade utilization of retired power batteries according to claim 1 is characterized in that: In step 3, the upper layer is the coordination and dispatching layer between the units within the regional power grid, with the output of thermal power units, the interactive power between the regional power grid and the external power grid, and the overall output of the energy storage system as optimization variables, and the goal is to minimize the total operating cost of the regional power grid; ； (11) In the formula, , They represent the daily electricity sales revenue and peak-valley arbitrage revenue of the wind-storage system, represents the energy storage system cost, represents the smooth fluctuation cost of the tie line, represents the penalty cost of output fluctuation of wind-storage combined system, represents the stroke power prediction error penalty cost, represents the penalty cost of wind curtailment, represents the operating cost of thermal power units, represents the interaction cost between the regional power grid and the external power grid; Conventional thermal power units are basically not started or shut down within one day. Therefore, the start and stop time constraints of the units are not considered in the constraints. The specific constraints include: Regional power grid power generation and supply balance constraints: ；(12) In the formula, Indicated in Load power at the moment; Hot standby constraints: ；(13) In the formula, For the crew The upper limit of output, is the maximum discharge power of the retired power battery energy storage system, Indicates the minimum spare capacity; Constraints on thermal power units: Conventional generator set constraints include upper and lower output limits and ramp constraints: ；(14) ；(15) In the formula, For the The output limit of each thermal power unit is For the The lower limit of the output of each thermal power unit is is the unit's down-slope rate, is the climbing rate of the unit; Energy storage charging and discharging state constraints: ；(16) In the formula, , Respectively expressed in The discharge state and charge state of the energy storage system at the moment, whose value is 0 or 1; Energy storage charging and discharging power constraints: ；(17) Energy storage state of charge constraints: ；(18) In order to ensure the reliability and safety of the energy storage power station in long-term operation and reduce the life loss caused by use, it is necessary to ensure that the SOC of the energy storage power station is equal at the beginning and end of each charging and discharging cycle, as shown in formula (19): ；(19) ；(20) In the formula, Indicated in The state of charge of the retired power battery energy storage system at the moment, Indicates the rated capacity of the retired power battery energy storage system, , Respectively represent the minimum and maximum value of the state of charge of the energy storage system; Energy storage output constraints in multiple application scenarios: ；(21) ；(22) In the formula, Indicates the output of the energy storage system used for the wind storage system, Represents the output power of the entire energy storage system applied to the power prediction error compensation scenario, Indicates the output power of the entire energy storage system used to suppress wind power fluctuations, which is the same as the total output state of the energy storage system and is not greater than the output of the entire energy storage system; Restrictions on electricity sales and purchases from external power grids: ；(23) ；(24) In the formula, The maximum permissible power for the regional power grid to purchase electricity from external power grids; The maximum allowable power for the regional power grid to sell electricity to external power grids.

8. The regional power grid optimization dispatching method considering the cascade utilization of retired power batteries according to claim 1 is characterized in that: In step 4, the goal is to minimize the life loss of the energy storage system, and the difference in life loss of different retired power battery energy storage power stations is taken into account for decision making. An energy storage system optimization scheduling model based on multiple retired battery energy storage power stations is established, and the objective function is: ； (25) The constraints include: Retired power battery energy storage station charging and discharging status constraints: ；(26) In the formula, , Respectively Decommissioned power battery energy storage power station The discharge state and charge state of the , whose value is 0 or 1; Retired power battery energy storage power station charging and discharging power constraints: ；(27) Constraints on the state of charge of retired power battery energy storage power stations: ；(28) ；(29) ；(30) In the formula, express Decommissioned power battery energy storage power station The state of charge, Represents retired power battery energy storage power station Rated capacity, , Represents retired power battery energy storage power stations The upper and lower limits of the state of charge.

9. The regional power grid optimization dispatching method considering the cascade utilization of retired power batteries according to claim 1 is characterized in that: In step 5, the regional power grid optimization dispatch model considering the cascade utilization of retired power batteries is simulated using the Matlab platform and the Curobi solver is called for solution, which specifically includes: Step 5-1, set the initial energy storage system output plan, input load and wind power forecast values, and input time-of-use electricity price, energy storage system status, and regional power grid parameters; Step 5-2, setting objective functions and constraints; the upper-level regional power grid optimization dispatching model takes the minimum total operating cost of the regional power grid as the objective function, and the lower-level energy storage system optimization dispatching model takes the minimum life loss of the energy storage system as the objective function, and sets their respective constraints; Step 5-3, calling the Gurobi solver to solve the scheduling model and obtain the decision variables of the charging and discharging plan of each energy storage power station; Step 5-4, determine whether the maximum number of iterations has been reached. Only when the maximum number of iterations has been reached can the optimal scheduling plan be output.

10. The regional power grid optimization dispatching method considering the cascade utilization of retired power batteries according to claim 1 is characterized in that: Step 6 specifically includes: Step 6-1: Install voltage sensors, current sensors and power sensors in each unit of the selected reference regional power grid. The sensor deployment should be consistent with the data points taken in the simulation; install a retired power battery energy storage power station with adjustable output in the regional power grid; check that all dispatch objects can be normally dispatched locally or remotely; Step 6-2: Install the control background, server and other necessary communication equipment according to the actual situation of the regional power grid, establish a control object point table, use OPC UA or other industrial automation specifications to achieve four-remote communication, build a monitoring system in the control background and debug it; Step 6-3, implement the simulation process, obtain the optimal scheduling parameter combination, write the scheduling program and implant it into the background monitoring system, debug and test run the scheduling program; Step 6-4, long-term operation of the dispatching program, real-time reading of the output of each unit of the regional power grid, and searching for dispatching parameters based on the output forecast of each unit of the regional power grid to achieve optimized dispatching of the regional power grid including retired power battery energy storage power stations.

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