Energy storage system operation cost optimization function construction method and terminal

Abstract

The invention relates to the technical field of power system control, in particular to an energy storage system operation cost optimization function construction method and a terminal, and the method comprises the steps: building an efficiency function containing temperature for a PCS and a DC / DC for a micro-grid system, and constructing a target function and a power balance constraint condition by taking real-time operation cost as a target; obtaining the efficiency data of the battery, and obtaining the efficiency data of the PCS and the DC / DC at different temperature points according to the efficiency functions of the PCS and the DC / DC; temperature data and power data of the PCS and the DC / DC are obtained in real time, and target efficiency data corresponding to the battery, the PCS and the DC / DC are obtained through fitting according to the temperature data; substituting the target efficiency data into the target function and solving, and performing optimization control according to a solving result; optimization control is performed on the energy storage system, and the operation cost of the energy storage system is reduced.

Description

[0001] This divisional application is based on the mother patent of an invention patent with an application date of October 24, 2024, an application number of 202411488905.8, and a title of "An Efficiency-Based Optimization Control Method and Terminal for the Operating Cost of Energy Storage Systems". Technical Field

[0002] The present invention relates to the technical field of power system control, and particularly to a method for constructing an optimization function for the operating cost of an energy storage system and a terminal. Background Art

[0003] DC distribution networks have broad development prospects in future power systems due to their advantages such as low line losses, high power supply reliability, ease of access for distributed power sources and energy storage devices, excellent power quality, environmental friendliness, and low equipment investment. At the same time, with the continuous progress of technology and the continuous promotion of policies, DC distribution networks will achieve large-scale, intelligent, standardized, and flexible development.

[0004] The basic components of a DC microgrid consist of lithium-ion batteries or other types of energy storage batteries, photovoltaic, power conversion system (PCS) for energy storage, DC / DC converters, DC loads, and an energy management system. Load DC conversion, flexible DC networking of converters, and intelligent energy management and optimization control are the core and development trends of such grid systems. For a photovoltaic-storage-charging system, the main direction of optimization control is the effective utilization of energy and orderly charging. For scenarios with relatively fixed loads, such as daily power loads in industrial and commercial energy storage, efficiently allocating the AC power supply ratio and scheduling the power supply of photovoltaic and different string energy storage batteries become the main objectives of energy management and regulation. With the maturity of battery thermal management technology, in a general system containing the above power units, the operating temperature of the battery can be controlled in a highly efficient area with small fluctuations through liquid cooling thermal management. However, in scenarios with high requirements for equipment economy, various power converters still need to adopt air-cooled heat dissipation methods, and there is no constant temperature control in the electrical cabin. Under different climate conditions, load conditions, and heat dissipation conditions, there will be significant differences in the temperature inside the electrical cabin and the temperature of the main radiator of the converter. There are also quite significant differences in the average temperature of converters at different installation positions in the same electrical cabin.

[0005] The typical DC load is for the main industrial and commercial energy storage scenarios. The battery, PV, and AC grid jointly supply power to the load. Under the topology where there are multiple battery clusters or battery strings, and multiple PCS strings can be independently controlled, the output power of each battery string through DC / DC and the DC output power of the PCS are scheduled through the energy management system, generally based on the state of the battery. Against the backdrop of the gradual improvement of independent battery thermal management and battery consistency, factors such as the difference in converter efficiency and the difference in the temperature of the electrical compartment gradually show their impact on operating economy. A method is needed to control the power output of each converter using an optimization method considering the impact of converter efficiency differences on operating economic indicators based on the logic of electricity price peak-valley regulation. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a method and terminal for constructing an optimization function for the operating cost of an energy storage system to optimize the operating cost of the energy storage system.

[0007] To solve the above technical problem, the technical solution adopted by the present invention is as follows:

[0008] An efficiency-based optimization control method for the operating cost of an energy storage system, including the steps of:

[0009] S1. For the microgrid system, establish an efficiency function including temperature for the PCS and DC / DC, and construct an objective function and a power balance constraint condition with the real-time operating cost as the goal;

[0010] S2. Obtain the efficiency data of the battery, and obtain the efficiency data of the PCS and DC / DC at different temperature points according to the efficiency functions of the PCS and DC / DC;

[0011] S3. Real-time obtain the temperature data and power data of the PCS and DC / DC, and fit the obtained temperature data to obtain the target efficiency data corresponding to the battery, PCS, and DC / DC;

[0012] S4. Substitute the target efficiency data into the objective function and solve it, and perform optimization control according to the solution result.

[0013] A method for constructing an optimization function for the operating cost of an energy storage system, including the steps of:

[0014] For the microgrid system, establish an efficiency function including temperature for the PCS and DC / DC, and construct an objective function and a power balance constraint condition:

[0015] The real-time operating cost consists of the cost of obtaining energy from the grid and the cost of obtaining energy from the battery;

[0016] Among them, the cost of obtaining energy from the battery is determined according to the grid electricity price at off-peak hours, the charge-discharge efficiency of the battery, and the real-time efficiency of the DC / DC used by the battery, and is expressed as a function including temperature.

[0017] To solve the above technical problems, the technical solution adopted by the present invention is:

[0018] An optimization control terminal for the operating cost of an energy storage system based on efficiency includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the above-mentioned optimization control method for the operating cost of an energy storage system based on efficiency are implemented.

[0019] A terminal for constructing an optimization function for the operating cost of an energy storage system includes a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0020] For a microgrid system, an efficiency function including temperature is established for the PCS and DC / DC, and with the real-time operating cost as the objective, an objective function and power balance constraint conditions are constructed:

[0021] The real-time operating cost consists of the cost of obtaining energy from the grid and the cost of obtaining energy from the battery;

[0022] Among them, the cost of obtaining energy from the battery is determined according to the grid electricity price at off-peak hours, the charge-discharge efficiency of the battery, and the real-time efficiency of the DC / DC used by the battery, and is expressed as a function including temperature.

[0023] The beneficial effect of the present invention is that: the method and terminal for constructing an optimization function for the operating cost of an energy storage system of the present invention consider that the operating efficiencies of the PCS and DC / DC are different at different temperatures, establish an efficiency function including temperature for the PCS and DC / DC, construct an objective function and power balance constraint conditions with the real-time operating cost as the objective, and solve the objective function based on the real-time operating conditions, so as to optimize and control the energy storage system and reduce the operating cost of the energy storage system. Description of the Drawings

[0024] Figure 1 It is a flowchart of an optimization control method for the operating cost of an energy storage system based on efficiency according to an embodiment of the present invention;

[0025] Figure 2 It is a specific flowchart of an optimization control method for the operating cost of an energy storage system based on efficiency according to an embodiment of the present invention;

[0026] Figure 3 It is a schematic structural diagram of a power system exemplified by an embodiment of the present invention;

[0027] Figure 4 Structural diagram of an efficiency - based operation cost optimization control terminal for an energy storage system according to an embodiment of the present invention;

[0028] Label description:

[0029] 1. An efficiency - based operation cost optimization control terminal for an energy storage system; 2. Processor; 3. Memory. Specific implementation manner

[0030] To describe the technical content, achieved objectives and effects of the present invention in detail, the following is described in conjunction with the implementation manners and accompanied by the drawings.

[0031] Please refer to Figure 1 and Figure 2 , an efficiency - based operation cost optimization control method for an energy storage system, including the steps:

[0032] S1. For the micro - grid system, establish efficiency functions including temperature for the PCS and DC / DC, and construct an objective function and power balance constraint conditions with the real - time operation cost as the objective;

[0033] S2. Obtain the efficiency data of the battery, and according to the efficiency functions of the PCS and DC / DC, obtain the efficiency data of the PCS and DC / DC at different temperature points;

[0034] S3. Real - time obtain the temperature data and power data of the PCS and DC / DC, and fit according to the temperature data to obtain the target efficiency data corresponding to the battery, PCS and DC / DC;

[0035] S4. Substitute the target efficiency data into the objective function and solve it, and perform optimization control according to the solution result.

[0036] As can be seen from the above description, the beneficial effect of the present invention is that: an efficiency - based operation cost optimization control method for an energy storage system of the present invention considers that the operation efficiencies of the PCS and DC / DC are different at different temperatures, establishes efficiency functions including temperature for the PCS and DC / DC, constructs an objective function and power balance constraint conditions with the real - time operation cost as the objective, and solves the objective function based on the real - time operation situation, thereby optimizing the control of the energy storage system and reducing the operation cost of the energy storage system.

[0037] Furthermore, the construction of the objective function includes the steps:

[0038] When all PCSs are rectifier outputs and all batteries are discharging, within the set control interval D, there is an objective function for the real - time operation cost:

[0039] Costtotal = Cost Grid + Cost BAT ;

[0040] Wherein, Cost Grid is the cost of obtaining energy from the power grid, and Cost BAT is the cost of obtaining energy from the battery.

[0041] As can be seen from the above description, the composition of the real-time operating cost includes the cost of obtaining energy from the power grid and the cost of obtaining energy from the battery.

[0042] Furthermore, the determination of the cost Cost Grid of obtaining energy from the power grid includes:

[0043]

[0044] P PCS_j is the rectifying-direction output power of the j-th PCS, and η PCS_j is the real-time efficiency of the j-th PCS, expressed as a function of temperature and output power:

[0045] η PCS_j = f 1 (T PCS_j , P PCS_j );

[0046] G price is the real-time power grid electricity price, and N is the number of PCSs.

[0047] As can be seen from the above description, the cost of obtaining energy from the power grid needs to consider the PCS output power and the efficiency of the PCS, while the operating efficiency of the PCS needs to consider the operating temperature of the PCS.

[0048] Furthermore, the determination of the cost Cost BAT of obtaining energy from the battery includes:

[0049]

[0050] P DC_i is the output power of the i-th DC / DC, and η DC_i is the real-time efficiency of the i-th DC / DC, expressed as a function of temperature and output power:

[0051] η DC_i = f 2 (T DC_i , P DC_i );

[0052] η Charge_i and η Disharge_iare the charging efficiency and discharging efficiency of the i-th battery, which are the battery temperature T BAT_i and the cumulative discharged power Q BAT_i functions of:

[0053] η Charge_i = f 3 (T BAT_i , Q BAT_i );

[0054] η Charge_i = f 3 (T BAT_i , Q BAT_i );

[0055] G price_low is the grid electricity price at valley electricity time, η DC_Chg_i is the average efficiency of the i-th DC / DC under the charging condition of the battery at a determined charging rate, M is the number of DC / DCs, corresponding to the number of batteries.

[0056] As can be seen from the above description, the cost of obtaining energy from the battery also needs to consider the output power and efficiency of the DC / DC, and at the same time, the charging efficiency and discharging efficiency of the battery itself need to be considered.

[0057] Furthermore, the construction of the power balance constraint conditions includes the steps of:

[0058] To meet the power requirement of the DC load P Load , there is a constraint condition:

[0059]

[0060] where P PV is the sum of the input powers of all photovoltaics on the DC bus, P DC_i is the output power of the i-th DC / DC, P PCS_j is the rectifying direction output power of the j-th PCS, N is the number of PCSs, M is the number of DC / DCs, corresponding to the number of batteries.

[0061] As can be seen from the above description, the sum of the DC output powers of all M DC / DCs and the sum of the rectifying output powers of all N PCSs are equal to the difference between the DC load power and the photovoltaic power.

[0062] Furthermore, the acquisition of battery efficiency includes the steps of:

[0063] For each model among the M batteries, according to the detection data, obtain the charging efficiency values η BAT_S at the initial stage of the life Q BAT_E and the end stage of the life Q BAT of this model, and when the operating temperature is at T Chargeand the discharge efficiency value η Discharge Interpolate the charge efficiency value and the discharge efficiency value to obtain the efficiency matrix of each battery:

[0064]

[0065] As can be seen from the above description, for batteries applied to energy storage, they all need to undergo performance tests that meet national standards, including charge and discharge efficiency tests, or be obtained through the type tests of suppliers. Currently, liquid cooling thermal management methods are mainly used for energy storage batteries, which can always control the battery operating temperature within a relatively small temperature change range, and the efficiency change within this range is not significant. Therefore, set the average value of the battery operating temperature to be T BAT , and obtain the efficiency parameter, which is obtained by testing the battery at this temperature. The test principles at the initial state and the end of the battery life are the same.

[0066] Furthermore, obtaining the efficiency data of PCS and DC / DC at different temperature points includes:

[0067] Under the condition of y temperature points where the main radiator temperature of the PCS and DC / DC converters can be adjusted, test the data matrix η of the output x power point efficiencies of each model of PCS and DC / DC PCS and η DC :

[0068]

[0069] As can be seen from the above description, under the condition of y temperature points where the main radiator temperature of the PCS and DC / DC converters can be adjusted, test the data matrix η of the output x power point efficiencies of each model of their respective ones PCS and η DC , that is, the discretized values of f1 and f2 in the above text.

[0070] Furthermore, step S3 includes:

[0071] Since the installation positions and heat dissipation conditions of each PCS and DC / DC are different, the operating temperatures are different, resulting in efficiency differences. Set the control interval D, and obtain the main radiator temperatures and output powers of N PCSs and M DC / DCs at time t to form a data matrix:

[0072] P PCS (t)=[P PCS_1 (t)…P PCS_N (t)], T PCS (t)=[T PCS_1 (t)…T PCS_N (t)];

[0073] P DC(t) = [P DC_1 (t)…P DC_M (t)], T DC (t) = [T DC_1 (t)…T DC_M (t)];

[0074] And obtain the efficiency value matrix of each PCS and DC / DC of each model at time t through the interpolation method:

[0075] η PCS (t) = [η PCS_1 (t)…η PCS_N (t)];

[0076] η DC (t) = [η DC_1 (t)…η DC_M (t)].

[0077] As can be seen from the above description, by obtaining the temperature and output power of the PCS and DC / DC at the same time, a data matrix of temperature and power is established, and the corresponding efficiency matrix is obtained.

[0078] Furthermore, step S4 includes:

[0079] Substitute the target efficiency data into the target function and solve it through an optimization algorithm;

[0080] Perform optimization control according to the solution result.

[0081] As can be seen from the above description, the solution of the target function is completed through the optimization algorithm, so as to perform optimization control.

[0082] Please refer to Figure 4 , an optimization control terminal for the operating cost of an energy storage system based on efficiency, including a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the above-mentioned optimization control method for the operating cost of an energy storage system based on efficiency are implemented.

[0083] The optimization control method and terminal for the operating cost of an energy storage system based on efficiency of the present invention are applicable to the optimization control of the operating cost of an energy storage system, and particularly applicable to the optimization control of the operating cost of a DC-compliant microgrid system.

[0084] Please refer to Figure 1 and Figure 2 , Example 1 of the present invention is:

[0085] An optimization control method for the operating cost of an energy storage system based on efficiency, including the steps:

[0086] S1. For the microgrid system, establish efficiency functions including temperature for the PCS and DC / DC, and construct the objective function and power balance constraint conditions with the real-time operating cost as the goal.

[0087] In this embodiment, let the efficiency of N PCSs be η PCS_1 ~η PCS_N , and the efficiency of M DC / DCs be η DC_1 ~η DC_M . Assume that the bidirectional efficiency of each DC / DC is the same (when the bidirectional efficiency of the DC / DC is different, it does not affect the implementation of the control method in this case).

[0088] In this embodiment, M batteries correspond to M DC / DCs one by one. Assume that the charging efficiency and discharging efficiency of each battery are inversely proportional to the cumulative discharge capacity of the battery (i.e., the efficiency decreases after the battery ages).

[0089] Assume that the battery only charges at valley electricity prices and can discharge at non-valley electricity times; the charging efficiencies of M batteries are η Charge_1 ~η Charge_M , and the discharging efficiencies are η Disharge_1 ~η Disharge_M .

[0090] The construction of the objective function includes the steps:

[0091] When all PCSs are rectifying outputs and all batteries are discharging, within the set control interval D, there is an objective function for the real-time operating cost:

[0092] Cost total =Cost Grid +Cost BAT ;

[0093] Among them, Cost Grid is the cost of obtaining energy from the power grid, and Cost BAT is the cost of obtaining energy from the battery;

[0094] The determination of the cost Cost Grid of obtaining energy from the power grid includes:

[0095]

[0096] P PCS_j is the rectifying direction output power of the jth PCS, and η PCS_j is the real-time efficiency of the jth PCS, expressed as a function based on temperature and output power:

[0097] η PCS_j =f 1 (T PCS_j ,P PCS_j );

[0098] G price is the real-time grid electricity price, and N is the number of PCSs.

[0099] The cost Cost of obtaining energy from the battery BAT is determined as follows:

[0100]

[0101] P DC_i is the output power of the i-th DC / DC, and η DC_i is the real-time efficiency of the i-th DC / DC, expressed as a function of temperature and output power:

[0102] η DC_i = f 2 (T DC_i , P DC_i );

[0103] η Charge_i and η Disharge_i are the charging efficiency and discharging efficiency of the i-th battery, which are functions of the battery temperature T BAT_i and the cumulative discharge capacity Q BAT_i respectively:

[0104] η Charge_i = f 3 (T BAT_i , Q BAT_i );

[0105] η Charge_i = f 3 (T BAT_i , Q BAT_i );

[0106] G price_low is the grid electricity price at valley electricity time, and η DC_Chg_i is the average efficiency of the i-th DC / DC under the determined charging rate under the battery charging condition, and M is the number of DC / DCs, corresponding to the number of batteries.

[0107] The construction of the power balance constraint condition includes the steps:

[0108] To meet the power requirement of the DC load P Load , there is a constraint condition:

[0109]

[0110] where P PV is the sum of the input powers of all photovoltaics on the DC bus, P DC_i is the output power of the i-th DC / DC, and P PCS_jis the rectification-direction output power of the jth PCS, N is the number of PCSs, M is the number of DC / DCs, corresponding to the number of batteries.

[0111] The meaning of this formula is that the sum of the DC output powers of all M DC / DCs and the sum of the rectification output powers of all N PCSs are equal to the difference between the DC load power and the PV power.

[0112] S2. Obtain the efficiency data of the batteries, and according to the efficiency functions of the PCSs and DC / DCs, obtain the efficiency data of the PCSs and DC / DCs at different temperature points.

[0113] In this embodiment, for a set of microgrid systems, all N PCSs, all M DC / DCs, and M batteries may have different models.

[0114] The acquisition of the battery efficiency includes the steps of:

[0115] For each model among the M batteries, according to the detection data, obtain the charging efficiency value η BAT_S and the discharging efficiency value η BAT_E in two states of the initial life Q BAT and the end-of-life Q Charge and at the operating temperature of T Discharge ; interpolate the charging efficiency value and the discharging efficiency value to obtain the efficiency matrix of each battery:

[0116]

[0117] Note: (1) For batteries applied to energy storage, they all need to undergo performance tests that meet national standards, including tests of charge and discharge efficiency, or obtain them through the type tests of suppliers. Currently, liquid-cooled thermal management methods are mainly used for energy storage batteries, and the operating temperature of the batteries can always be controlled within a relatively small temperature change range, and the efficiency change within this range is not significant. In this embodiment, the average value of the battery operating temperature is controlled at T BAT , and the efficiency parameters are obtained by testing the batteries at this temperature.

[0118] (2) The efficiency test in (1) above is the test value in the initial life state, and the test value is obtained by performing the same test at the end of life.

[0119] Obtaining the efficiency data of the PCSs and DC / DCs at different temperature points includes:

[0120] Under the condition of y temperature points where the main radiator temperatures of the PCS and DC / DC converters can be adjusted, test the data matrices η PCS and η DC of the output x power point efficiencies of each model of PCS and DC / DC:

[0121]

[0122] Among them, the quantities of x and y are determined according to the test conditions.

[0123] If the system contains two types of PCSs and two types of DC / DCs, two corresponding efficiency data matrices can be obtained.

[0124] In this embodiment, the measured efficiency matrix data is stored in the memory of the microgrid energy management system.

[0125] S3. Obtain the temperature data and power data of the PCS and DC / DC in real time, and obtain the target efficiency data corresponding to the battery, PCS, and DC / DC by fitting according to the temperature data.

[0126] In this embodiment, by obtaining the temperature and power data of the operating PCS and DC / DC, fitting the efficiency of the operating point according to the stored data, substituting it into the real-time operating cost objective function, and obtaining the operating power of the PCS and DC / DC that minimizes the objective function value through an optimization algorithm for real-time control, so as to minimize the real-time operating cost of the system. Since the installation positions and heat dissipation conditions of each PCS and DC / DC are different, especially for a system with an air-cooled power converter, the temperatures during operation are different, resulting in efficiency differences.

[0127] Step S3 includes:

[0128] Due to different installation positions and heat dissipation conditions, the temperatures of each PCS and DC / DC during operation are different, resulting in efficiency differences. With a set control interval D, obtain the main radiator temperatures and output powers of N PCSs and M DC / DCs at time t to form data matrices:

[0129] P PCS (t) = [P PCS_1 (t)…P PCS_N (t)], T PCS (t) = [T PCS_1 (t)…T PCS_N (t)];

[0130] P DC (t) = [P DC_1 (t)…P DC_M (t)], T DC (t) = [T DC_1 (t)…T DC_M (t)];

[0131] And obtain the efficiency value matrix of each PCS and DC / DC of each type at time t through interpolation:

[0132] ηPCS (t) = [η PCS_1 (t)…η PCS_N (t)];

[0133] η DC (t) = [η DC_1 (t)…η DC_M (t)].

[0134] S4. Substitute the target efficiency data into the objective function and solve it, and perform optimization control according to the solution result;

[0135] Step S4 includes:

[0136] Substitute the target efficiency data into the objective function and solve it through an optimization algorithm;

[0137] Perform optimization control according to the solution result.

[0138] In this embodiment, with the goal of minimizing the real-time operating cost objective function at time t, solve the given value of at time t + 1.

[0139] Objective function:

[0140]

[0141] Constraint conditions:

[0142]

[0143] P DC_i (t) < P DC_i_limit , P PCS_j (t) < P PCS_j_limit ;

[0144] Among them, P DC_i_limit , P PCS_j_limit are the power limit values of the converters respectively.

[0145] Initial conditions:

[0146]

[0147] Please refer to Figure 3 , and Embodiment 2 of the present invention is:

[0148] In this embodiment, an example is given for the method for optimizing and controlling the operating cost of an energy storage system based on efficiency described in Embodiment 1 above.

[0149] Suppose there is Figure 3The shown power system has N = 2 PCSs of the same model, with the power limit of a single unit being 150 kW; M = 2 DC / DCs of the same model, with the power limit of a single unit being 120 kW; the total output power of the photovoltaic power generation unit at time t is 50 kW, and the DC load power is 500 kW; the 2 batteries are of the same model; take the valley electricity price G price_low = 0.4 / kWh, and the real-time grid electricity price G price = 0.8 / kWh.

[0150] Under the condition of the battery operating temperature T BAT in thermal management control, assume that the 2 batteries have the same initial life and end-of-life condition efficiencies: η Charge = [0.970, 0.970; 0.905, 0.905]; η Discharge = [0.975, 0.975; 0.915, 0.915]; obtain the PCS and DC / DC efficiency test matrices η PCS and η DC at 4 temperatures; the cumulative discharge electricity of the two batteries is set to 0 and 2×e5 kwh respectively, and the cumulative discharge electricity at the end of life is set to 1×e6 kwh; use the interpolation method to obtain the charge / discharge efficiencies of the 2 batteries within the control interval as 0.9700, 0.9570 and 0.9750, 0.9630 respectively.

[0151] Note: The efficiency values are for illustrative examples and do not represent actual test results.

[0152] Assume that the operating powers of the 2 PCSs at time t are:

[0153] P PCS (t) = [127, 122] kW;

[0154] The temperature is:

[0155] T PCS (t) = [38, 10];

[0156] The operating power of the DC / DC is:

[0157] P DC (t) = [105, 108] kW;

[0158] The temperature is:

[0159] T DC (t) = [0, 10].

[0160] Meet the constraint conditions:

[0161]

[0162] P DC_i(t)<P DC_i_limit ,P PCS_j (t)<P PCS_j_limit 。

[0163] Note: The temperature value is an example and does not represent the actual operation result.

[0164] The efficiency value matrices of two PCSs and DC / DC at time t are obtained by interpolation method.

[0165] η PCS (t) = [0.9497, 0.9508];

[0166] η DC (t) = [0.9528, 0.9493];

[0167] Note: The efficiency value is the calculation result according to the example; the interpolation method is not limited, and in this embodiment, the "spline" method can be used to fit the efficiency function and obtain the interpolation.

[0168] Taking the control interval D as 60s, using the above data at time t and the neural network optimization algorithm, calculate the power that minimizes the real-time operation cost objective function in the period of t + 1 as:

[0169] P PCS (t + 1) = [61.37, 149.48] kW;

[0170] P DC (t + 1) = [120.00, 119.15] kW;

[0171] Cost total (t + 1) = 4.8867 yuan / 60s.

[0172] As a comparison, at time t + 1, it still runs under the initial conditions in 3 without optimization, and calculate Cost total (t + 1) = 5.2069 yuan / 60s.

[0173] The third embodiment of the present invention is:

[0174] An optimization control terminal 1 for the operation cost of an energy storage system based on efficiency, including a processor 2, a memory 3, and a computer program stored in the memory 3 and operable on the processor 2. When the processor 2 executes the computer program, it implements the steps in the optimization control method for the operation cost of an energy storage system based on efficiency described in the above embodiment one or two.

[0175] In summary, the optimization control method and terminal for the operating cost of an energy storage system provided by the present invention consider the different operating efficiencies of the PCS and DC / DC at different temperatures, establish efficiency functions including temperature for the PCS and DC / DC, construct an objective function and power balance constraint conditions with the real-time operating cost as the target, and solve the objective function based on the real-time operating conditions, thereby optimizing the control of the energy storage system and reducing the operating cost of the energy storage system.

[0176] The control method for the series-connected energy storage system based on efficiency optimization of the present invention, under the condition of considering temperature inconsistency, enables the converter with higher efficiency to increase its output, thereby optimizing the control of the operating cost. During the period when the electricity price of peak-valley electricity price implementation is high and the load fluctuation is small, the electricity cost is minimized through this method.

[0177] Meanwhile, considering the influence of the efficiencies of batteries with different lifetimes on the operating cost, the algorithm can automatically balance the discharge power of batteries in different lifetime stages, optimize the utilization rate of battery assets, and make the lifetimes of batteries measured by the Regge electricity tend to be consistent.

[0178] The above are only the embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. All equivalent transformations made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in related technical fields, are equally included in the patent protection scope of the present invention.

Claims

1. A method for constructing an energy storage system operation cost optimization function, characterized in that: Includes steps: For the microgrid system, an efficiency function including temperature is established for PCS and DC / DC, and the objective function and power balance constraints are constructed with real-time operating cost as the target: The real-time operation cost is composed of the cost of obtaining energy from the power grid and the cost of obtaining energy from the battery; The cost of obtaining energy from the battery is determined based on the grid electricity price during off-peak hours, the battery charging and discharging efficiency, and the real-time efficiency of the DC / DC used by the battery, and is expressed as a function including temperature.

2. A method for constructing an energy storage system operation cost optimization function according to claim 1, characterized in that: The construction of the objective function is specifically as follows: When all PCSs are rectified output and all batteries are discharged, within the set control interval D, the objective function of the real-time operation cost is: Cost total =Cost Grid +Cost BAT ; Among them, Cost Grid is the cost of obtaining energy from the grid. BAT is the cost of getting energy from the battery.

3. A method for constructing an energy storage system operation cost optimization function according to claim 2, characterized in that: Cost of getting energy from the grid Grid The determination includes: P PCS_j is the output power in the rectified direction of the jth PCS, η PCS_j is the real-time efficiency of the jth PCS, expressed as a function based on temperature and output power: η PCS_j =f1(T PCS_j ,P PCS_j ); G price is the real-time grid electricity price, and N is the number of PCSs.

4. A method for constructing an energy storage system operation cost optimization function according to claim 2, characterized in that: Cost of getting energy from batteries BAT The determination includes: P DC_i is the output power of the i-th DC / DC, η DC_i is the real-time efficiency of the i-th DC / DC, expressed as a function based on temperature and output power: η DC_i =f2(T DC_i ,P DC_i ); η Charge_i and η Disharge_i are the charging efficiency and discharging efficiency of the ith battery, and are the battery temperature T BAT_i And the cumulative discharge capacity Q BAT_i Function: η Charge_i =f3(T BAT_i ,Q BAT_i ); η Charge_i =f3(T BAT_i ,Q BAT_i ); G price_low is the grid electricity price during off-peak hours, η DC_Chg_i is the average efficiency of the i-th DC / DC at a certain charging rate under battery charging conditions, and M is the number of DC / DCs, corresponding to the number of batteries.

5. The method for constructing an energy storage system operation cost optimization function according to claim 1, characterized in that: The construction of the power balance constraint condition comprises the steps of: To meet the DC load P Load The power requirement is subject to the following constraints: Among them, P PV is the sum of all photovoltaic input power on the DC bus, P DC_i is the output power of the ith DC / DC, P PCS_j is the output power in the rectification direction of the jth PCS, N is the number of PCSs, and M is the number of DC / DCs, which corresponds to the number of batteries.

6. A terminal for constructing an energy storage system operation cost optimization function, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the following steps are implemented: For the microgrid system, an efficiency function including temperature is established for PCS and DC / DC, and the objective function and power balance constraints are constructed with real-time operating cost as the target: The real-time operation cost is composed of the cost of obtaining energy from the power grid and the cost of obtaining energy from the battery; The cost of obtaining energy from the battery is determined based on the grid electricity price during off-peak hours, the battery charging and discharging efficiency, and the real-time efficiency of the DC / DC used by the battery, and is expressed as a function including temperature.

7. The energy storage system operation cost optimization function construction terminal according to claim 6, characterized in that: The construction of the objective function is specifically as follows: When all PCSs are rectified output and all batteries are discharged, within the set control interval D, the objective function of the real-time operation cost is: Cost total =Cost Grid +Cost BAT ; Among them, Cost Grid is the cost of obtaining energy from the grid. BAT is the cost of getting energy from the battery.

8. The energy storage system operation cost optimization function construction terminal according to claim 7, characterized in that: Cost of getting energy from the grid Grid The determination includes: P PCS_j is the output power in the rectified direction of the jth PCS, η PCS_j is the real-time efficiency of the jth PCS, expressed as a function based on temperature and output power: η PCS_j =f1(T PCS_j ,P PCS_j ); G price is the real-time grid electricity price, and N is the number of PCSs.

9. The energy storage system operation cost optimization function construction terminal according to claim 7, characterized in that: Cost of getting energy from batteries BAT The determination includes: P DC_i is the output power of the i-th DC / DC, η DC_i is the real-time efficiency of the i-th DC / DC, expressed as a function based on temperature and output power: η DC_i =f2(T DC_i ,P DC_i ); η Charge_i and η Disharge_i are the charging efficiency and discharging efficiency of the ith battery, and are the battery temperature T BAT_i And the cumulative discharge capacity Q BAT_i Function: η Charge_i =f3(T BAT_i ,Q BAT_i ); η Charge_i =f3(T BAT_i ,Q BAT_i ); G price_low is the grid electricity price during off-peak hours, η DC_Chg_i is the average efficiency of the i-th DC / DC at a certain charging rate under battery charging conditions, and M is the number of DC / DCs, corresponding to the number of batteries.

10. The energy storage system operation cost optimization function construction terminal according to claim 6, characterized in that: The construction of the power balance constraint condition comprises the steps of: To meet the DC load P Load The power requirement is subject to the following constraints: Among them, P PV is the sum of all photovoltaic input power on the DC bus, P DC_i is the output power of the ith DC / DC, P PCS_j is the output power in the rectification direction of the jth PCS, N is the number of PCSs, and M is the number of DC / DCs, which corresponds to the number of batteries.

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