A wind-solar-storage station active power optimization control method and device

Abstract

The application relates to the field of new energy power generation technology, and discloses a wind-solar-storage power station active power optimization control method and device, which comprises the following steps: determining wind-solar-storage active power control optimization variables based on active output scheduling instruction values and actual output active power values of the wind-solar-storage power station; calculating wind-solar-storage active power control costs based on the actual output active power values of the wind-solar-storage power station, wind-solar ultra-short-term power prediction values and the wind-solar-storage active power control optimization variables; constructing a wind-solar-storage power station active power optimization control model based on the wind-solar-storage active power control optimization variables and the wind-solar-storage active power control costs; and optimizing and solving the wind-solar-storage power station active power optimization control model to obtain optimal control results of the wind-solar-storage power station active power. The wind-solar-storage active power control optimization variables fully consider the active control costs of wind power, photovoltaic power and energy storage, and the wind-solar-storage active power output is optimized and controlled.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of new energy power generation, in particular to a wind-solar-storage station active power optimization control method and device. BACKGROUND

[0002] Compared with thermal power and hydropower, the output of new energy has strong uncertainty, and it is difficult to make a power generation plan in advance according to the load curve, so it is necessary to distribute active power according to the power generation characteristics of wind power, photovoltaic and energy storage. Therefore, the active power instruction distribution of the wind-solar-storage station will be coordinated control for wind power, photovoltaic and energy storage.

[0003] The active power instruction distribution of the related wind-solar-storage station is generally proportional distribution according to the installed capacity of wind power, photovoltaic and energy storage, that is, the larger the installed capacity, the larger the distribution task. However, the method of distributing active power according to the size of installed capacity is simple and easy to implement, but it does not fully consider the active control cost of wind power, photovoltaic and energy storage, resulting in a large difference in active control cost of wind-solar-storage station under different operating conditions, thereby increasing the operating cost of the wind-solar-storage station and being not conducive to improving the overall operating efficiency of the station. SUMMARY

[0004] Therefore, the present application provides a wind-solar-storage station active power optimization control method and device to solve the problem that the active power instruction distribution method of the wind-solar-storage station does not fully consider the active control cost of wind power, photovoltaic and energy storage, thereby increasing the operating cost of the wind-solar-storage station and being not conducive to improving the overall operating efficiency of the station.

[0005] In a first aspect, the present application provides a wind-solar-storage station active power optimization control method, which comprises:

[0006] Obtaining the active output scheduling instruction value issued by the power grid and the actual output active power value of the wind-solar-storage station, and determining the wind-solar-storage active power control optimization variable based on the active output scheduling instruction value and the actual output active power value of the wind-solar-storage station;

[0007] Obtaining the wind-solar ultra-short-term power prediction value, and calculating the wind-solar-storage active power control cost based on the actual output active power value of the wind-solar-storage station, the wind-solar ultra-short-term power prediction value and the wind-solar-storage active power control optimization variable;

[0008] Based on the wind-solar-storage active power control optimization variable and the wind-solar-storage active power control cost, a wind-solar-storage station active power optimization control model is constructed;

[0009] The wind-solar-storage station active power optimization control model is optimized and solved to obtain the optimal control result of the wind-solar-storage station active power.

[0010] The wind-solar-storage station active power optimization control method provided by the embodiment calculates the wind-solar-storage active power control cost based on the actual output active power value of the wind-solar-storage station, the wind-solar ultra-short-term power prediction value and the wind-solar-storage active power control optimization variable, and then constructs the wind-solar-storage station active power optimization control model based on the wind-solar-storage active power control optimization variable and the wind-solar-storage active power control cost, and then optimizes and solves the wind-solar-storage station active power optimization control model, so that the optimization control process of the wind-solar-storage station active power fully considers the active control costs of wind power, photovoltaic and energy storage, realizes the optimization control of the wind power, photovoltaic and energy storage output active power, reduces the operation cost of the wind-solar-storage station, and improves the operation benefit of the wind-solar-storage station.

[0011] In an optional implementation, the wind-solar-storage active power control cost is calculated based on the actual output active power value of the wind-solar-storage station, the wind-solar ultra-short-term power prediction value and the wind-solar-storage active power control optimization variable, and includes:

[0012] The wind turbine cluster power generation loss fee and the photovoltaic cluster power generation loss fee are calculated based on the actual output active power value of the wind-solar-storage station and the wind-solar ultra-short-term power prediction value.

[0013] The wind power equipment operation and maintenance cost fee is obtained, and the wind power active power control cost is calculated based on the wind turbine cluster power generation loss fee, the wind power equipment operation and maintenance cost fee and the wind turbine cluster active power control optimization variable in the wind-solar-storage active power control optimization variable;

[0014] The photovoltaic equipment operation and maintenance cost fee is obtained, and the photovoltaic active power control cost is calculated based on the photovoltaic cluster power generation loss fee, the photovoltaic equipment operation and maintenance cost fee and the photovoltaic cluster active power control optimization variable in the wind-solar-storage active power control optimization variable;

[0015] The battery life loss corresponding cost fee is obtained, and the energy storage active power control cost is calculated based on the energy storage cluster active power control optimization variable in the wind-solar-storage active power control optimization variable, the battery life loss corresponding cost fee and the time interval of the adjacent active power output dispatching instruction.

[0016] The wind-solar-storage active power control cost is calculated based on the wind power active power control cost, the photovoltaic active power control cost and the energy storage active power control cost.

[0017] The wind-solar-storage power station active power optimization control method provided in the embodiment calculates the wind-solar-storage active power control cost by calculating the photovoltaic cluster power generation loss cost and the wind-solar-storage active power control cost, fully considers the power generation loss cost caused by the wind-solar-storage output reduction, and calculates the wind-solar-storage active power control cost based on the wind cluster power generation loss cost, the photovoltaic cluster power generation loss cost, the cost corresponding to the battery life loss, and the active power dispatch instruction value, fully considers the influence of the operation differences of the wind power, the photovoltaic power, and the energy storage on the active power control cost, and makes the wind-solar-storage active power control cost more accurate.

[0018] In an optional implementation, the wind cluster power generation loss cost and the photovoltaic cluster power generation loss cost are calculated based on the actual output active power value of the wind-solar-storage power station and the wind-solar ultra-short-term power prediction value, and the calculation includes:

[0019] An adjacent active power dispatch instruction issuing time interval is obtained, the wind cluster power generation loss cost is calculated based on the wind cluster ultra-short-term power prediction value in the wind-solar ultra-short-term power prediction value, the wind cluster actual output active power value in the actual output active power value of the wind-solar-storage power station, and the adjacent active power dispatch instruction issuing time interval.

[0020] The photovoltaic cluster power generation loss cost is calculated based on the photovoltaic cluster ultra-short-term power prediction value in the wind-solar ultra-short-term power prediction value, the photovoltaic cluster actual output active power value in the actual output active power value of the wind-solar-storage power station, and the adjacent active power dispatch instruction issuing time interval.

[0021] The wind-solar-storage power station active power optimization control method provided in the embodiment calculates the wind-solar-storage active power control cost by calculating the photovoltaic cluster power generation loss cost and the wind-solar-storage active power control cost, fully considers the power generation loss cost caused by the wind-solar-storage output reduction, and calculates the wind-solar-storage active power control cost based on the wind cluster power generation loss cost, the photovoltaic cluster power generation loss cost, the cost corresponding to the battery life loss, and the active power dispatch instruction value, fully considers the influence of the operation differences of the wind power, the photovoltaic power, and the energy storage on the active power control cost, and makes the wind-solar-storage active power control cost more accurate.

[0022] In an optional implementation, the wind-solar-storage power station active power optimization control model is constructed based on the wind-solar-storage active power control optimization variable and the wind-solar-storage active power control cost, and the construction includes:

[0023] A penalty coefficient of the active control cost is obtained, and the optimization objective function is established based on the wind-solar-storage active power control cost, the wind-solar-storage active power control optimization variable, and the penalty coefficient of the active control cost.

[0024] A constraint condition of the active power change amount is obtained, and the wind-solar-storage power station active power optimization control model is constructed based on the optimization objective function and in combination with the constraint condition of the active power change amount.

[0025] This embodiment provides an optimized control method for the active power of a wind-solar-storage power storage station. An optimization objective function is established based on the active power control cost of wind, solar, and storage power, the optimized variables for active power control, and the penalty coefficient for active power control cost. Based on this objective function and the constraints of active power variation, an optimized control model for the active power of the wind-solar-storage power storage station is constructed. This model fully considers the active power control cost of wind, solar, and storage power, laying the foundation for subsequent optimized control of the active power of the wind-solar-storage power storage station.

[0026] In one optional implementation, an optimization objective function is established based on the active power control cost of wind, solar, and energy storage, the optimization variables for active power control of wind, solar, and energy storage, and the penalty coefficient of the active power control cost; wherein, the expression of the optimization objective function is as follows:

[0027]

[0028] In the above formula, f is the objective function, and ΔP max C max These represent the maximum value of the active power control optimization variables and the maximum value of the active power control cost of the wind-solar-storage power storage station, respectively. ΔP is the difference between the actual active power output of the wind-solar-storage power storage station and the active power output dispatch command value. Wind For the active power control optimization variable of the wind turbine group, ΔP PV For the active power control optimization variable of the photovoltaic cluster, ΔP S Let λ be the active power control optimization variable for the energy storage cluster, and C be the penalty coefficient for active power control costs. Wind To control the active power cost of wind power, C PV To control the cost of photovoltaic active power, C S To control the cost of active power in energy storage.

[0029] In one optional implementation, the active power optimization control model of the wind-solar-storage power storage station is optimized and solved to obtain the optimal control result of the active power of the wind-solar-storage power storage station, including:

[0030] Within the preset penalty coefficient range, the penalty coefficients of active power control costs are selected sequentially as the current penalty coefficients. The current penalty coefficients are then input into the active power optimization control model of the wind, solar and energy storage station to obtain multiple sets of control command values ​​for the allocation of active power in wind, solar and energy storage.

[0031] By using the control command value of the active power of the wind-solar-storage allocation corresponding to the minimum energy storage allocation value, the active power of the wind-solar-storage station is optimized and controlled to obtain the optimal control result of the active power of the wind-solar-storage station.

[0032] This embodiment provides an optimized control method for the active power of a wind-solar-storage power storage station. By inputting the current penalty coefficient into the optimized control model of the active power of the wind-solar-storage power storage station, multiple sets of control command values ​​for the allocated active power of wind, solar, and storage are obtained. The optimized control of the active power of the wind-solar-storage power storage station is then performed using the control command value of the allocated active power of wind, solar, and storage corresponding to the minimum energy storage allocation value. Based on the optimized control model of the active power of the wind-solar-storage power storage station, the importance of active power control cost is comprehensively considered and the number of energy storage charge and discharge cycles is reduced, thereby achieving optimized control of the active power of the wind-solar-storage power storage station.

[0033] Secondly, the present invention provides an optimized control device for the active power of a wind-solar-storage power storage station, the device comprising:

[0034] The determination module is used to obtain the active power output dispatch command value issued by the power grid and the actual active power output value of the wind, solar and energy storage station, and determine the wind, solar and energy storage active power control optimization variables based on the active power output dispatch command value and the actual active power output value of the wind, solar and energy storage station.

[0035] The calculation module is used to obtain the predicted value of wind and solar ultra-short-term power, and calculate the active power control cost of wind, solar and energy storage based on the actual output active power value of the wind, solar and energy storage station, the predicted value of wind and solar ultra-short-term power, and the active power control optimization variables of wind, solar and energy storage.

[0036] The module is used to build an active power optimization control model for wind, solar and energy storage power stations based on the active power control optimization variables and the active power control cost of wind, solar and energy storage.

[0037] The solution module is used to optimize the active power control model of the wind, solar and energy storage station to obtain the optimal control result of the active power of the wind, solar and energy storage station.

[0038] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the optimized control method for active power of the wind and solar power storage station described in the first aspect or any corresponding embodiment.

[0039] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the optimized control method for active power of a wind and solar power storage station according to the first aspect or any corresponding embodiment described above.

[0040] Fifthly, the present invention provides a computer program product, including computer instructions, which are used to cause a computer to execute the optimized control method for active power of a wind and solar power storage station according to the first aspect or any corresponding embodiment described above. Attached Figure Description

[0041] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0042] Figure 1 This is a flowchart illustrating an optimized control method for the active power of a wind-solar-storage power storage station according to an embodiment of the present invention.

[0043] Figure 2 This is a flowchart illustrating another method for optimizing the control of active power in a wind and solar power storage station according to an embodiment of the present invention.

[0044] Figure 3 This is a flowchart illustrating another method for optimizing the active power control of a wind-solar-storage power storage station according to an embodiment of the present invention.

[0045] Figure 4 This is a structural block diagram of an optimized control device for active power of a wind and solar power storage station according to an embodiment of the present invention.

[0046] Figure 5 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] Unlike traditional renewable energy power plants, wind, solar, and energy storage power plants have larger capacities, more renewable energy units, and a wider variety of power sources. Therefore, active power control in wind, solar, and energy storage power plants is more complex. Considering that active power regulation in wind, solar, and energy storage power plants directly affects their operational efficiency, this invention provides an optimized active power control method for wind, solar, and energy storage power plants. Applied to server-type equipment, this method optimizes the active power output from wind, solar, and energy storage power plants from the perspective of active power control costs for the three power generation units: wind power, photovoltaics, and electrochemical energy storage (lithium-ion battery energy storage).

[0049] According to an embodiment of the present invention, an embodiment of an optimized control method for active power of a wind and solar power storage station is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0050] This embodiment provides an optimized control method for the active power of a wind, solar, and energy storage station, which can be used for the aforementioned server-type equipment. Figure 1 This is a flowchart of an optimized control method for the active power of a wind-solar-storage power storage station according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0051] Step S101: Obtain the active power output dispatch command value issued by the power grid and the actual active power output value of the wind, solar and energy storage station. Determine the wind, solar and energy storage active power control optimization variables based on the active power output dispatch command value and the actual active power output value of the wind, solar and energy storage station.

[0052] Specifically, during normal operation of a wind-solar-storage power station, the wind and solar power generation units output the maximum active power according to MPPT (Maximum PowerPoint Tracking) control to maximize power generation efficiency. When the active power output dispatch command issued by the grid is less than the actual active power output of the wind-solar-storage power station, the power station needs to implement power curtailment, which can be achieved by reducing the output active power of the wind and solar power units or by using energy storage for charging. When the active power output dispatch command issued by the grid is greater than the actual active power output of the wind-solar-storage power station, the wind and solar power units operate according to MPPT, and the energy storage system charges and discharges according to its own control logic.

[0053] Furthermore, when the active power output dispatch command value is less than the actual active power output value of the wind, solar and energy storage station, and the difference between the active power output dispatch command value and the actual active power output value of the wind, solar and energy storage station (i.e., the wind, solar and energy storage active power control optimization variable) is greater than the set threshold, it is necessary to optimize the active power control of the wind, solar and energy storage station.

[0054] Step S102: Obtain the predicted short-term power values ​​of wind and solar power, and calculate the active power control cost of wind, solar and energy storage based on the actual output active power values ​​of the wind, solar and energy storage power storage stations, the predicted short-term power values ​​of wind and solar power, and the active power control optimization variables of wind, solar and energy storage.

[0055] Specifically, the control mechanisms for wind power, photovoltaic power, and energy storage are all power electronic converters. Due to significant differences in their operating characteristics, the active power control costs differ, thus requiring an assessment and calculation of the active power control costs for wind, photovoltaic, and energy storage systems.

[0056] Furthermore, the ultra-short-term power forecast values ​​for wind and solar power are obtained from the wind and solar power forecasting system equipped at the wind and solar storage station.

[0057] Step S103: Construct an active power optimization control model for wind, solar and energy storage power stations based on the active power control optimization variables and the active power control costs of wind, solar and energy storage power stations.

[0058] Step S104: Optimize and solve the active power optimization control model of the wind-solar-storage station to obtain the optimal control result of the active power of the wind-solar-storage station.

[0059] Specifically, based on the active power optimization control model of the wind-solar-storage power station, the importance of active power control cost is comprehensively considered and the number of charging and discharging times of energy storage is reduced, thereby obtaining the change in active power of the wind, solar, and storage turbine groups. The obtained change in active power of the wind, solar, and storage turbine groups is then used to allocate active power to the wind-solar-storage power station, resulting in the optimal control result of the active power of the wind-solar-storage power station.

[0060] This embodiment provides an optimized control method for the active power of a wind-solar-storage power station. Based on the actual active power output of the power station, the predicted ultra-short-term power output of wind and solar power, and the active power control optimization variables, the method calculates the active power control cost of the power station. Then, based on these variables and the control cost, it constructs an optimized control model for the active power of the power station. Finally, it optimizes and solves this model, ensuring that the optimized control process fully considers the active power control costs of wind power, solar power, and energy storage. This achieves optimized control of the active power output of wind power, solar power, and energy storage, reducing the operating costs of the power station and improving its operational efficiency.

[0061] This embodiment provides an optimized control method for the active power of a wind, solar, and energy storage station, which can be used for the aforementioned server-type equipment. Figure 2 This is a flowchart of an optimized control method for the active power of a wind-solar-storage power storage station according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps:

[0062] Step S201: Obtain the active power output dispatch command value issued by the power grid and the actual active power output value of the wind, solar, and energy storage power storage stations. Based on the active power output dispatch command value and the actual active power output value of the wind, solar, and energy storage power storage stations, determine the active power control optimization variables for wind, solar, and energy storage. For details, please refer to [link to relevant documentation]. Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0063] Step S202: Obtain the predicted short-term power values ​​of wind and solar power, and calculate the active power control cost of wind, solar and energy storage based on the actual output active power values ​​of the wind, solar and energy storage power storage stations, the predicted short-term power values ​​of wind and solar power, and the active power control optimization variables of wind, solar and energy storage.

[0064] Specifically, step S202 includes:

[0065] Step S2021: Calculate the power generation loss cost of the wind turbine group and the power generation loss cost of the photovoltaic group based on the actual output active power value of the wind-solar-storage station and the ultra-short-term power prediction value of wind and solar power.

[0066] Specifically, if the predicted short-term power output of wind and solar power is less than the actual active power output of the wind-solar-storage power storage station, the control direction of the active power of the wind-solar-storage power storage station is the same as the actual change direction of active power, and the corresponding control cost is lower; otherwise, the control cost is higher. Therefore, when considering the loss of wind and solar power generation, the difference between the predicted short-term power output of wind and solar power and the actual active power output of the wind-solar-storage power storage station is used for calculation.

[0067] In some optional implementations, step S2021 above includes:

[0068] Step a1: Obtain the time interval between the issuance of adjacent active power output dispatch instructions, and calculate the wind turbine group power generation loss cost based on the wind turbine group's ultra-short-term power forecast value in the wind and solar ultra-short-term power forecast value, the wind turbine group's actual output active power value in the actual output active power value of the wind, solar and energy storage station, and the time interval between the issuance of adjacent active power output dispatch instructions.

[0069] Specifically, the cost of power generation loss from wind turbine clusters, C W1 The calculation formula is as follows:

[0070] C W1 =(P W_predict -P W_ref )ΔT (1)

[0071] In the above formula, P W_predict P P_predict P represents the ultra-short-term power forecast value of the wind turbine cluster. W_ref ΔT represents the actual active power output of the wind turbine group, and ΔT is the time interval between the issuance of adjacent active power output dispatch commands.

[0072] Step a2: Calculate the photovoltaic power generation loss cost based on the ultra-short-term power forecast of the photovoltaic group in the ultra-short-term power forecast of wind and solar power, the actual output active power of the photovoltaic group in the actual output active power of the wind, solar and energy storage station, and the time interval between the issuance of adjacent active power output dispatch instructions.

[0073] Specifically, the cost of power generation loss from photovoltaic clusters, C P1The calculation formula is as follows:

[0074] C P1 =(P P_predict -P P_ref )ΔT (2)

[0075] In the above formula, P P_predict P represents the ultra-short-term power forecast value of the photovoltaic cluster. P_ref This represents the actual active power output of the photovoltaic cluster.

[0076] Step S2022: Obtain the operation and maintenance cost of wind power equipment, and calculate the wind power active power control cost based on the wind turbine group power generation loss cost, the wind power equipment operation and maintenance cost, and the wind turbine group active power control optimization variable in the wind-solar-storage active power control optimization variable.

[0077] Specifically, within the operating range of a wind turbine cluster, based on wind speed from low to high, the operating zone can be divided into four areas: the start-up zone, the maximum wind energy tracking zone, the constant speed zone, and the constant power zone. Active power control cannot be achieved in the start-up and constant power zones. In the maximum wind energy tracking and constant power zones, the output active power can be adjusted by changing the turbine pitch angle. When the wind power active power command value is less than the current maximum output value, wind power command tracking can be achieved by reducing power and adjusting the pitch angle. The advantage of reducing power is its low adjustment cost, but it places higher demands on the turbine control system, requiring modification of the turbine's input active power command value, and is currently less commonly used in engineering. Adjusting the pitch angle is currently the most common power regulation method, but frequent use of the pitch system accelerates its aging and increases maintenance costs. Therefore, adjusting the pitch angle is adopted as the control method for wind power active power. The cost of wind power active power control includes the cost of power generation loss due to reduced output and the operation and maintenance costs of the wind power equipment.

[0078] Furthermore, the active power control cost C of wind power Wind The calculation formula is as follows:

[0079] C W ind = C W1 +C W2 (ΔP W ind)=C W1 +C W2 (P W _ref-P W _real) (3)

[0080] In the above formula, C W2 For the operation and maintenance costs of wind power equipment, ΔP WindP represents the change in active power obtained by allocating power to the wind turbine cluster according to the active power command value from the power grid, i.e., the active power control optimization variable of the wind turbine cluster. W_real This refers to the active power output dispatch command value for wind power.

[0081] Step S2023: Obtain the operation and maintenance cost of photovoltaic equipment, and calculate the photovoltaic active power control cost based on the photovoltaic power generation loss cost, photovoltaic equipment operation and maintenance cost, and the photovoltaic active power control optimization variable in the wind, solar and energy storage active power control optimization variables.

[0082] Specifically, the power control mechanism of a photovoltaic power generation unit mainly adopts a power electronic converter, which normally operates in MPPT control mode. When the photovoltaic active power output dispatch command value is less than the maximum actual output active power value of the photovoltaic group, due to the large number of photovoltaic inverters, the power output of some photovoltaic inverters can be limited by controlling the operating point of some photovoltaic inverters to the lower limit of economic operation, while ensuring that the power generation unit can disconnect from the grid without shutting down. Therefore, the photovoltaic active power control cost includes the cost of power generation loss of the photovoltaic group caused by the reduction in output, as well as the operation and maintenance cost of photovoltaic equipment caused by the control.

[0083] Furthermore, the photovoltaic active power control cost C PV The calculation formula is as follows:

[0084] C PV =C P1 +C P2 (ΔP PV ) = C P1 +C P2 (P P _ref-P P _real) (4)

[0085] In the above formula, C P1 C is the cost of power generation loss for the photovoltaic cluster. P2 ΔP represents the operation and maintenance costs of photovoltaic equipment. PV P represents the change in active power obtained by allocating power to the photovoltaic (PV) cluster according to the grid's active power command value; that is, the active power control optimization variable for the PV cluster. P_real This refers to the active power output dispatch command value for photovoltaic systems.

[0086] Step S2024: Obtain the cost corresponding to battery life loss, and calculate the energy storage active power control cost based on the energy storage cluster active power control optimization variables in the wind, solar and energy storage active power control optimization variables, the cost corresponding to battery life loss, and the time interval between the issuance of adjacent active power output scheduling commands.

[0087] Specifically, the energy storage unit can achieve bidirectional control of active power through charging and discharging. When the energy storage discharge increases the output, the energy storage active power control cost includes the electrical energy lost during discharge (which is a positive value) and the cost corresponding to the loss of battery life. When the energy storage charge increases the output, the energy storage active power control cost includes the electrical energy increased during charging (which is a negative value) and the cost corresponding to the loss of battery life.

[0088] Furthermore, the active power control cost of energy storage C S The calculation formula is as follows:

[0089] C S =ΔP S ΔT+C S2 (ΔP S )=ΔP S ΔT+C S2 (P S _ref-P S _real) (5)

[0090] In the above formula, ΔP S C represents the change in active power obtained by allocating power to the energy storage cluster according to the active power command value from the power grid, i.e., the active power control optimization variable of the energy storage cluster. S2 P represents the cost corresponding to the loss of battery life. S_ref P represents the actual active power output of the energy storage cluster. S_real This refers to the active power output dispatch command value for energy storage.

[0091] Step S2025: Calculate the active power control cost of wind, solar and energy storage based on the active power control cost of wind power, photovoltaic power and energy storage.

[0092] Specifically, the sum of the active power control costs of wind power, photovoltaic power, and energy storage is taken as the active power control cost of wind, solar, and energy storage.

[0093] This embodiment provides an optimized control method for the active power of a wind-solar-storage power station. By calculating the power generation loss cost of the photovoltaic group and the active power control cost of wind, solar, and storage, it fully considers the power generation loss cost caused by the reduction of wind, solar, and storage output. Furthermore, it calculates the active power control cost of wind, solar, and storage based on the power generation loss cost of the wind turbine group, the power generation loss cost of the photovoltaic group, the cost corresponding to battery life loss, and the active power output dispatch command value. This fully considers the impact of the operational differences of wind power, photovoltaic, and energy storage on the active power control cost, making the active power control cost of wind, solar, and storage more accurate.

[0094] Step S203: Construct an active power optimization control model for wind, solar and energy storage power stations based on the active power control optimization variables and the active power control costs of wind, solar and energy storage power stations.

[0095] Specifically, step S203 includes:

[0096] Step S2031: Obtain the penalty coefficient of active power control cost, and establish an optimization objective function based on the active power control cost of wind, solar and energy storage, the optimization variables of active power control of wind, solar and energy storage, and the penalty coefficient of active power control cost.

[0097] Step S2032: Obtain the constraints on the change in active power, and construct an active power optimization control model for the wind, solar and energy storage station based on the optimization objective function and the constraints on the change in active power.

[0098] Specifically, the expression for the active power optimization control model of the wind-solar-storage station is as follows:

[0099]

[0100] In the above formula, f is the objective function, and ΔP max C max These represent the maximum value of the active power control optimization variable for wind-solar-storage power storage stations and the maximum value of the active power control cost for wind-solar-storage power storage stations, respectively; ΔP W_max ΔP W_min These represent the maximum and minimum values ​​of the active power control optimization variables for the wind turbine cluster (the maximum value is determined based on the ultra-short-term power forecast of the wind turbine cluster; the minimum value can be 0, i.e., it does not participate in active power control); ΔP P_max ΔP P_min These are the maximum and minimum values ​​of the active power control optimization variables for the photovoltaic (PV) cluster (the maximum value is determined based on the ultra-short-term power forecast of the PV cluster; the minimum value can be 0, i.e., it does not participate in active power control); ΔP S_max ΔP S_min These are the maximum and minimum values ​​of the active power control optimization variables for the energy storage cluster (determined according to the energy storage charging and discharging limit requirements); ΔP is the difference between the actual active power output of the wind-solar-storage power station and the active power output dispatch command value; λ is the penalty coefficient for active power control costs.

[0101] Step S204 involves optimizing the active power control model of the wind-solar-storage power storage station to obtain the optimal control result for the active power of the station. For details, please refer to [link to relevant documentation]. Figure 1 Step S104 of the illustrated embodiment will not be described again here.

[0102] This embodiment provides an optimized control method for the active power of a wind-solar-storage power storage station. An optimization objective function is established based on the active power control cost of wind, solar, and storage power, the optimized variables for active power control, and the penalty coefficient for active power control cost. Based on this objective function and the constraints of active power variation, an optimized control model for the active power of the wind-solar-storage power storage station is constructed. This model fully considers the active power control cost of wind, solar, and storage power, laying the foundation for subsequent optimized control of the active power of the wind-solar-storage power storage station.

[0103] This embodiment provides an optimized control method for the active power of a wind, solar, and energy storage station, which can be used for the aforementioned server-type equipment. Figure 3 This is a flowchart of an optimized control method for the active power of a wind-solar-storage power storage station according to an embodiment of the present invention, such as... Figure 3 As shown, the process includes the following steps:

[0104] Step S301: Obtain the active power output dispatch command value issued by the power grid and the actual active power output value of the wind, solar, and energy storage power storage station. Based on the active power output dispatch command value and the actual active power output value of the wind, solar, and energy storage power storage station, determine the active power control optimization variables for wind, solar, and energy storage. For details, please refer to [link to relevant documentation]. Figure 2 Step S201 of the illustrated embodiment will not be described again here.

[0105] Step S302: Obtain the predicted short-term power values ​​for wind and solar power. Calculate the active power control cost for wind, solar, and energy storage based on the actual output active power of the wind, solar, and energy storage power storage stations, the predicted short-term power values, and the active power control optimization variables. For details, please refer to [link to relevant documentation]. Figure 2 Step S202 of the illustrated embodiment will not be described again here.

[0106] Step S303: Construct an active power optimization control model for wind, solar, and energy storage power generation stations based on the active power control optimization variables and the active power control costs. For details, please refer to [link to relevant documentation]. Figure 2 Step S203 of the illustrated embodiment will not be described again here.

[0107] Step S304: Optimize and solve the active power optimization control model of the wind-solar-storage station to obtain the optimal control result of the active power of the wind-solar-storage station.

[0108] Specifically, step S304 includes:

[0109] Step S3041: Select the penalty coefficient of active power control cost sequentially within the preset penalty coefficient range as the current penalty coefficient, and input the current penalty coefficient into the active power optimization control model of the wind-solar-storage power station to obtain multiple sets of control command values ​​for the distribution of active power of wind, solar and storage power.

[0110] For example, the preset penalty coefficient range is [0.3, 0.7]. Within the range of [0.3, 0.7], λ values ​​are selected and input sequentially at intervals of 0.05. The active power optimization control model of the wind-solar-storage power station is used to calculate the active power control command values ​​for wind power, photovoltaic and energy storage allocation, thereby obtaining multiple sets of wind-solar-storage active power control optimization variables.

[0111] Step S3042: Optimize the active power control of the wind-solar-storage power storage station using the control command value of the active power allocation corresponding to the minimum energy storage allocation value, and obtain the optimal control result of the active power of the wind-solar-storage power storage station.

[0112] Specifically, the set of active power control optimization variables of wind, solar and energy storage with the smallest energy storage allocation value is selected as the final active power change of the wind, solar and energy storage group. The active power of the wind, solar and energy storage group is allocated to the wind, solar and energy storage station using the obtained active power change, so as to obtain the optimal control result of the active power of the wind, solar and energy storage station.

[0113] This embodiment provides an optimized control method for the active power of a wind-solar-storage power storage station. By inputting the current penalty coefficient into the optimized control model of the active power of the wind-solar-storage power storage station, multiple sets of control command values ​​for the allocated active power of wind, solar, and storage are obtained. The optimized control of the active power of the wind-solar-storage power storage station is then performed using the control command value of the allocated active power of wind, solar, and storage corresponding to the minimum energy storage allocation value. Based on the optimized control model of the active power of the wind-solar-storage power storage station, the importance of active power control cost is comprehensively considered and the number of energy storage charge and discharge cycles is reduced, thereby achieving optimized control of the active power of the wind-solar-storage power storage station.

[0114] This embodiment also provides an optimized control device for the active power of a wind-solar-storage power storage station. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0115] This embodiment provides an optimized control device for the active power of a wind-solar-storage power storage station, such as... Figure 4 As shown, it includes:

[0116] The module 401 is used to obtain the active power output dispatch command value issued by the power grid and the actual active power output value of the wind, solar and energy storage station, and to determine the wind, solar and energy storage active power control optimization variables based on the active power output dispatch command value and the actual active power output value of the wind, solar and energy storage station.

[0117] Calculation module 402 is used to obtain the predicted value of wind and solar ultra-short-term power, and calculate the active power control cost of wind, solar and energy storage based on the actual output active power value of the wind, solar and energy storage station, the predicted value of wind and solar ultra-short-term power, and the active power control optimization variables of wind, solar and energy storage.

[0118] Module 403 is used to construct an active power optimization control model for wind, solar and energy storage power stations based on the active power control optimization variables and the active power control cost of wind, solar and energy storage.

[0119] The solver module 404 is used to optimize the active power control model of the wind-solar-storage power storage station and obtain the optimal control result of the active power of the wind-solar-storage power storage station.

[0120] In some alternative implementations, the computing module 402 includes:

[0121] The first calculation unit is used to calculate the power generation loss cost of wind turbine groups and the power generation loss cost of photovoltaic groups based on the actual output active power value of wind, solar and energy storage stations and the ultra-short-term power prediction value of wind and solar.

[0122] The second calculation unit is used to obtain the operation and maintenance costs of wind power equipment, and calculate the active power control cost of wind power based on the power generation loss cost of wind turbine group, the operation and maintenance costs of wind power equipment, and the active power control optimization variables of wind, solar and storage active power control optimization variables.

[0123] The third calculation unit is used to obtain the operation and maintenance costs of photovoltaic equipment, and calculates the photovoltaic active power control cost based on the photovoltaic power generation loss cost, photovoltaic equipment operation and maintenance costs, and the photovoltaic active power control optimization variable in the wind, solar and energy storage active power control optimization variable.

[0124] The fourth calculation unit is used to calculate the active power control cost of energy storage based on the active power control optimization variables of the energy storage cluster, the cost corresponding to battery life loss, and the time interval between the issuance of adjacent active power output scheduling commands in the active power control optimization variables of wind, solar and energy storage.

[0125] The fifth calculation unit is used to calculate the active power control cost of wind, solar and energy storage based on the active power control cost of wind power, active power control cost of photovoltaic power and active power control cost of energy storage.

[0126] In some alternative implementations, the first computing unit includes:

[0127] The first calculation subunit is used to obtain the time interval between the issuance of adjacent active power output dispatch instructions, and calculate the power generation loss cost of the wind turbine group based on the wind turbine group's ultra-short-term power forecast value in the wind and solar ultra-short-term power forecast value, the wind turbine group's actual output active power value in the actual output active power value of the wind, solar and energy storage station, and the time interval between the issuance of adjacent active power output dispatch instructions.

[0128] The second calculation subunit is used to calculate the photovoltaic power generation loss cost based on the ultra-short-term power forecast of the photovoltaic group in the ultra-short-term power forecast of wind and solar power, the actual output active power of the photovoltaic group in the actual output active power of the wind, solar and energy storage station, and the time interval between the issuance of adjacent active power output dispatch instructions.

[0129] In some alternative implementations, building module 403 includes:

[0130] Establish a unit to obtain the penalty coefficient of active power control cost, and establish an optimization objective function based on the active power control cost of wind, solar and energy storage, the optimization variables of active power control of wind, solar and energy storage, and the penalty coefficient of active power control cost;

[0131] A construction unit is used to obtain the constraints of active power change. Based on the optimization objective function, the active power optimization control model of the wind-solar-storage station is constructed in combination with the constraints of active power change.

[0132] In some optional implementations, the expression for the optimization objective function in the building unit is as follows:

[0133]

[0134] In the above formula, f is the objective function, and ΔP max C max These represent the maximum value of the active power control optimization variables and the maximum value of the active power control cost of the wind-solar-storage power storage station, respectively. ΔP is the difference between the actual active power output of the wind-solar-storage power storage station and the active power output dispatch command value. Wind For the active power control optimization variable of the wind turbine group, ΔP PV For the active power control optimization variable of the photovoltaic cluster, ΔP S Let λ be the active power control optimization variable for the energy storage cluster, and C be the penalty coefficient for active power control costs. Wind To control the active power cost of wind power, C PV To control the cost of photovoltaic active power, C S To control the cost of active power in energy storage.

[0135] In some alternative implementations, the solver module 404 includes:

[0136] The selection unit is used to sequentially select the penalty coefficient of active power control cost within the preset penalty coefficient range as the current penalty coefficient. The current penalty coefficient is then input into the active power optimization control model of the wind, solar and energy storage station to obtain multiple sets of control command values ​​for the allocation of active power in wind, solar and energy storage.

[0137] The optimization control unit is used to optimize the active power of the wind-solar-storage power storage station by using the control command value of the active power allocation corresponding to the minimum energy storage allocation value, so as to obtain the optimal control result of the active power of the wind-solar-storage power storage station.

[0138] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0139] In this embodiment, the active power optimization control device for a wind and solar power storage station is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0140] This invention also provides a computer device having the above-described features. Figure 4 The diagram shows an optimized control device for the active power of a wind and solar power storage station.

[0141] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 5 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 5 Take a processor 10 as an example.

[0142] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0143] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0144] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0145] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0146] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0147] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0148] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0149] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. An optimized control method for active power of a wind-solar-storage power storage station, characterized in that, The method includes: Obtain the active power output dispatch command value issued by the power grid and the actual active power output value of the wind, solar and energy storage station; determine the wind, solar and energy storage active power control optimization variables based on the active power output dispatch command value and the actual active power output value of the wind, solar and energy storage station. Obtain the predicted short-term power values ​​of wind and solar power, and calculate the active power control cost of wind, solar and energy storage based on the actual output active power value of the wind, solar and energy storage power storage station, the predicted short-term power values ​​of wind and solar power, and the active power control optimization variables of wind, solar and energy storage. Based on the active power control optimization variables of wind, solar and energy storage and the active power control cost of wind, solar and energy storage, an active power optimization control model for wind, solar and energy storage power stations is constructed. The optimal control model for the active power of the wind-solar-storage station is optimized and solved to obtain the optimal control result for the active power of the wind-solar-storage station. The calculation of the active power control cost based on the actual output active power value of the wind-solar-storage power station, the predicted ultra-short-term power value of wind and solar power, and the active power control optimization variables of wind, solar, and storage includes: The power generation loss costs of the wind turbine group and the power generation loss costs of the photovoltaic group are calculated based on the actual active power output of the wind-solar-storage station and the ultra-short-term power prediction values ​​of the wind and solar power. Obtain the operation and maintenance cost of wind power equipment, and calculate the active power control cost of wind power based on the power generation loss cost of the wind turbine group, the operation and maintenance cost of wind power equipment, and the active power control optimization variable of the wind, solar and storage active power control optimization variable of the wind turbine group. Obtain the operation and maintenance cost of photovoltaic equipment, and calculate the photovoltaic active power control cost based on the photovoltaic power generation loss cost, the operation and maintenance cost of photovoltaic equipment, and the photovoltaic active power control optimization variable in the wind, solar and energy storage active power control optimization variable; Obtain the cost corresponding to battery life loss, and calculate the energy storage active power control cost based on the energy storage cluster active power control optimization variable in the wind, solar and energy storage active power control optimization variable, the cost corresponding to battery life loss and the time interval between the issuance of adjacent active power output scheduling commands. The active power control cost of wind power, photovoltaic power, and energy storage is calculated based on the active power control cost of wind power, photovoltaic power, and energy storage. The construction of the active power optimization control model for wind, solar, and energy storage power stations based on the active power control optimization variables and the active power control costs of wind, solar, and energy storage includes: Obtain the penalty coefficient for active power control cost, and establish an optimization objective function based on the active power control cost of wind, solar and energy storage, the optimization variables of active power control of wind, solar and energy storage, and the penalty coefficient for active power control cost; Obtain the constraints on the change in active power, and construct the active power optimization control model of the wind-solar-storage station based on the optimization objective function and the constraints on the change in active power.

2. The method according to claim 1, characterized in that, The calculation of power generation loss costs for wind turbine clusters and photovoltaic clusters based on the actual active power output of the wind-solar-storage power storage station and the ultra-short-term power forecast values ​​of wind and solar power includes: The time interval between the issuance of adjacent active power output dispatch instructions is obtained, and the wind turbine group power generation loss cost is calculated based on the wind and solar ultra-short-term power forecast value in the wind and solar ultra-short-term power forecast value, the wind turbine group actual output active power value in the wind, solar and energy storage station actual output active power value, and the time interval between the issuance of adjacent active power output dispatch instructions. The photovoltaic power generation loss cost is calculated based on the ultra-short-term power forecast of the photovoltaic cluster in the ultra-short-term power forecast of the wind and solar power, the actual active power output of the photovoltaic cluster in the actual active power output of the wind, solar and energy storage station, and the time interval between the issuance of adjacent active power output dispatch instructions.

3. The method according to claim 1, characterized in that, An optimization objective function is established based on the active power control cost of wind, solar, and energy storage, the optimization variables for active power control of wind, solar, and energy storage, and the penalty coefficient of the active power control cost; wherein, the expression of the optimization objective function is as follows: In the above formula, To optimize the objective function, , These represent the maximum values ​​of the active power control optimization variables and the maximum active power control cost of the wind-solar-storage power storage station, respectively. This is the difference between the actual active power output of the wind, solar, and energy storage station and the active power output dispatch command value. Optimization variables for active power control of wind turbine clusters. Optimization variables for active power control of photovoltaic clusters. Optimization variables for active power control of energy storage clusters The penalty coefficient for effective cost control. To control the cost of active power in wind power, To control the cost of photovoltaic active power, To control the cost of active power in energy storage.

4. The method according to claim 1, characterized in that, The optimization solution of the active power optimization control model of the wind-solar-storage station to obtain the optimal control result of the active power of the wind-solar-storage station includes: Within a preset penalty coefficient range, the penalty coefficients of active power control costs are selected sequentially as the current penalty coefficients. The current penalty coefficients are then input into the active power optimization control model of the wind, solar and energy storage station to obtain multiple sets of control command values ​​for the allocation of active power in wind, solar and energy storage. The active power of the wind-solar-storage power storage station is optimized by using the control command value of the active power allocation corresponding to the minimum energy storage allocation value, so as to obtain the optimal control result of the active power of the wind-solar-storage power storage station.

5. An optimized control device for active power in a wind-solar-storage power storage station, characterized in that, The device includes: The determination module is used to obtain the active power output dispatch command value issued by the power grid and the actual active power output value of the wind, solar and energy storage station, and determine the wind, solar and energy storage active power control optimization variables based on the active power output dispatch command value and the actual active power output value of the wind, solar and energy storage station. The calculation module is used to obtain the wind and solar ultra-short-term power prediction value, and calculate the wind, solar and energy storage active power control cost based on the actual output active power value of the wind, solar and energy storage station, the wind and solar ultra-short-term power prediction value and the wind, solar and energy storage active power control optimization variables. A construction module is used to construct an active power optimization control model for wind, solar and energy storage power stations based on the active power control optimization variables and the active power control cost of wind, solar and energy storage. The solution module is used to optimize and solve the active power optimization control model of the wind-solar-storage station to obtain the optimal control result of the active power of the wind-solar-storage station. The calculation module includes: The first calculation unit is used to calculate the power generation loss cost of wind turbine groups and the power generation loss cost of photovoltaic groups based on the actual output active power value of wind, solar and energy storage stations and the ultra-short-term power prediction value of wind and solar. The second calculation unit is used to obtain the operation and maintenance costs of wind power equipment, and calculate the active power control cost of wind power based on the power generation loss cost of wind turbine group, the operation and maintenance costs of wind power equipment, and the active power control optimization variables of wind, solar and storage active power control optimization variables. The third calculation unit is used to obtain the operation and maintenance costs of photovoltaic equipment, and calculates the photovoltaic active power control cost based on the photovoltaic power generation loss cost, photovoltaic equipment operation and maintenance costs, and the photovoltaic active power control optimization variable in the wind, solar and energy storage active power control optimization variable. The fourth calculation unit is used to calculate the energy storage active power control cost based on the energy storage cluster active power control optimization variables in the wind, solar and energy storage active power control optimization variables, the cost corresponding to battery life loss and the time interval between the issuance of adjacent active power output scheduling commands. The fifth calculation unit is used to calculate the active power control cost of wind, solar and energy storage based on the active power control cost of wind power, active power control cost of photovoltaic power and active power control cost of energy storage. The building blocks include: Establish a unit to obtain the penalty coefficient of active power control cost, and establish an optimization objective function based on the active power control cost of wind, solar and energy storage, the optimization variables of active power control of wind, solar and energy storage, and the penalty coefficient of active power control cost; A construction unit is used to obtain the constraints of active power change. Based on the optimization objective function, the active power optimization control model of the wind-solar-storage station is constructed in combination with the constraints of active power change.

6. A computer device, characterized in that, include: The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the optimized control method for active power of the wind and solar power storage station as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the optimized control method for the active power of the wind and solar power storage station as described in any one of claims 1 to 4.

8. A computer program product, characterized in that, It includes computer instructions, which are used to cause a computer to execute the optimized control method for the active power of the wind and solar power storage station as described in any one of claims 1 to 4.

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