A method and system for adjusting frequency modulation parameters of an energy storage power station

Abstract

The application provides a method and system for adjusting frequency modulation parameters of an energy storage power station, comprising: obtaining an operation state and load prediction data of a power system in a dispatch cycle; the power system at least comprising a thermal power unit and an energy storage power station; constructing a target function and a constraint condition based on the operation state and the load prediction data; the target function minimizing a sum of fuel cost of the thermal power unit, frequency modulation standby cost of the thermal power unit, loss cost of the energy storage power station and frequency modulation standby cost of the energy storage power station in the dispatch cycle; the constraint condition at least related to keeping the power system in stable frequency operation; solving the target function based on the constraint condition to obtain frequency modulation control parameters applied to the energy storage power station; the frequency modulation control parameters at least comprising virtual inertia of the energy storage power station and droop control coefficients.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of operation control of power systems, in particular to a method and system for adjusting frequency modulation parameters of energy storage power stations. BACKGROUND

[0002] Energy storage power stations can be switched between charging and discharging modes, have the function of peak shaving and valley filling, and can play an important role in future power systems. With the increasing proportion of power electronic devices such as energy storage, the inertia of the power system gradually decreases, and the frequency dynamic security problem is becoming increasingly serious. In order to improve the frequency security of the power system, energy storage power stations need to participate in the primary frequency modulation of the power grid.

[0003] Therefore, the present application provides a method and system for adjusting frequency modulation parameters of energy storage power stations. For the dispatching control of modern power systems, a day-ahead economic dispatching model considering frequency security constraints is established. The frequency modulation control parameters (virtual inertia, droop coefficient) of the energy storage power station are set as dispatching optimization variables, and are comprehensively optimized and calculated together with the power generation plan of thermal power units and the charging and discharging plan of energy storage power stations to obtain an optimal dispatching scheme that meets the frequency security constraints. The primary frequency modulation capacity of the energy storage power station is fully tapped, the optimal configuration of the frequency modulation control parameters of the energy storage power station is realized, and the dispatching decision of the dispatcher is guided. SUMMARY

[0004] The present application aims to provide a method for adjusting frequency modulation parameters of energy storage power stations, comprising obtaining the operating state and load prediction data of a power system in a dispatching period; the power system at least includes thermal power units and energy storage power stations; based on the operating state and the load prediction data, a target function and a constraint condition are constructed; the target function minimizes the sum of the fuel cost of the thermal power units, the frequency modulation standby cost of the thermal power units, the loss cost of the energy storage power stations and the frequency modulation standby cost of the energy storage power stations in the dispatching period; the constraint condition is at least related to maintaining the stable operation of the frequency of the power system; based on the constraint condition, the target function is solved to obtain frequency modulation control parameters applied to the energy storage power station; the frequency modulation control parameters at least include the virtual inertia and the droop control coefficient of the energy storage power station.

[0005] Further, the frequency modulation control parameters are issued to the energy storage power station to adjust the operating state of the energy storage power station; the operating state and load prediction data of the power system in the next dispatching period are re-obtained; based on the operating state and load prediction data of the next dispatching period, the frequency modulation control parameters of the next dispatching period are obtained, and the cycle is repeated to continuously optimize the entire power system.

[0006] Further, the expression of the target function is:

[0007]

[0008] wherein, Nt represents total scheduling period; Ng, Ne respectively represent total number of the thermal power generating units and the energy storage power stations; represents fuel cost of the thermal power generating unit i at time t; represents frequency regulation reserve cost of the thermal power generating unit i at time t; represents loss cost of the energy storage power station k at time t; represents frequency regulation reserve cost of the energy storage power station k at time t.

[0009] Further, the loss cost of the energy storage power station k at time t is expressed as:

[0010]

[0011]

[0012]

[0013]

[0014] wherein, represents loss of discharging process; represents loss of charging process; and respectively represent charging efficiency and discharging efficiency of the energy storage power station k; represents charging / discharging power of the energy storage power station k at time t.

[0015] Further, the frequency regulation reserve cost of the energy storage power station k at time t is expressed as:

[0016]

[0017]

[0018] wherein, rec k represents frequency regulation reserve cost coefficient of the energy storage power station k; represents frequency regulation reserve size of the energy storage power station k at time t; rec represents energy storage frequency regulation reserve fixed cost coefficient; represents rated capacity of the energy storage power station k.

[0019] Further, the constraint conditions at least include power balance constraint, thermal power generating unit power constraint, energy storage power station constraint, frequency change rate constraint, quasi-steady frequency constraint, frequency minimum point constraint, frequency regulation reserve constraint, control parameter adjustable range constraint and line capacity constraint.

[0020] Further, the expression of the energy storage power station constraint includes:

[0021]

[0022]

[0023]

[0024]

[0025]

[0026] wherein, represents the energy size stored by the energy storage power station k at time t; represents the energy size stored by the energy storage power station k at time t-1; represents the charging / discharging power of the energy storage power station k at time t; represents the loss power of the energy storage power station k at time t; Δt represents the time length of a scheduling period; represents the energy size of the energy storage at the beginning time of the scheduling period; represents the energy size of the energy storage at the end time of the scheduling period; and respectively represent the maximum and minimum energy storage values allowed by the energy storage power station k; represents the maximum charging / discharging power allowed by the energy storage power station k; represents the frequency modulation reserve size of the energy storage power station k at time t.

[0027] Further, the expression of the frequency modulation reserve constraint includes:

[0028]

[0029]

[0030] wherein, represents the frequency modulation reserve size of the thermal power unit i at time t; R i represents the droop control coefficient of the thermal power unit i; represents the maximum output power of the thermal power unit i; represents the quasi-steady frequency deviation threshold value; f0 represents the reference frequency; represents the frequency modulation reserve size of the energy storage power station k at time t; represents the droop control coefficient provided by the energy storage power station k at time t; represents the maximum charging / discharging power allowed by the energy storage power station k; represents the maximum frequency deviation threshold value; represents the virtual inertia provided by the energy storage power station k at time t; denotes a frequency change rate threshold.

[0031] Further, the expression of the control parameter adjustable range constraint comprises:

[0032]

[0033]

[0034] wherein, denotes a droop control coefficient provided by the energy storage power station k at time t; denotes an upper limit of the droop control coefficient that can be provided by the energy storage power station k; denotes a virtual inertia provided by the energy storage power station k at time t; denotes an upper limit of the virtual inertia that can be provided by the energy storage power station k.

[0035] The purpose of the present application is to provide a system for adjusting frequency modulation parameters of an energy storage power station, comprising an acquisition module, a construction module and a solving module; the acquisition module is used to acquire operation state and load prediction data of a power system in a dispatching period; the power system at least comprises a thermal power unit and an energy storage power station; the construction module is used to construct an objective function and a constraint condition based on the operation state and the load prediction data; the objective function minimizes the sum of fuel cost of the thermal power unit, frequency modulation reserve cost of the thermal power unit, loss cost of the energy storage power station and frequency modulation reserve cost of the energy storage power station in the dispatching period; the constraint condition is at least related to keeping the power system in stable operation; the solving module is used to solve the objective function based on the constraint condition to obtain frequency modulation control parameters applied to the energy storage power station; the frequency modulation control parameters at least comprise virtual inertia and a droop control coefficient of the energy storage power station.

[0036] The technical scheme of the embodiment of the present application has at least the following advantages and beneficial effects:

[0037] Some embodiments in the specification set up a frequency safety constraint day-ahead economic dispatching model (i.e. an objective function and a constraint condition), set frequency modulation control parameters (virtual inertia, droop coefficient) of the energy storage power station as dispatching optimization variables, perform online optimization calculation according to operation conditions of different dispatching periods in a dispatching center, and issue to each energy storage power station, so that the frequency modulation control parameters of the energy storage device can be set online.

[0038] The dispatching model established by some embodiments in the specification comprehensively optimizes calculation of frequency modulation control parameters (virtual inertia, droop coefficient) of the energy storage power station and power generation plans of the thermal power unit and the charging and discharging plans of the energy storage power station, introduces frequency change rate constraints, frequency minimum point constraints, quasi-steady frequency constraints and frequency modulation reserve constraints in the constraint conditions, and can obtain optimal dispatching plans meeting frequency dynamic safety constraints.

[0039] The day-ahead economic dispatching model established by some embodiments in the specification realizes optimal configuration of frequency modulation control parameters of the energy storage power station while guaranteeing frequency dynamic safety of the power system, and guarantees safe and economic operation of the power system. BRIEF DESCRIPTION OF DRAWINGS

[0040] Figure 1 An exemplary flowchart of a method for adjusting frequency modulation parameters of an energy storage power station is provided for some embodiments of the present application.

[0041] Figure 2 An exemplary module diagram of a system for adjusting frequency modulation parameters of an energy storage power station is provided for some embodiments of the present application. DETAILED DESCRIPTION

[0042] To make the objectives, technical solutions and advantages of embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. The components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0043] Figure 1 An exemplary flowchart of a method for adjusting frequency modulation parameters of an energy storage power station is provided for some embodiments of the present application. In some embodiments, flow 100 can be executed by system 200. As shown in Figure 1 flow 100 can include the following steps:

[0044] Step 110, obtaining operation state and load prediction data of the power system in a dispatching period. In some embodiments, step 110 can be executed by obtaining module 210.

[0045] The power system at least includes a thermal power unit and an energy storage power station. The dispatching period can refer to a period of adjusting the operation state of the energy storage power station. For example, the dispatching period can be 24 hours.

[0046] In some embodiments, the dispatching center can obtain the operation state and load prediction data of the power system in the dispatching period through various feasible ways, including but not limited to uploading by the thermal power plant, extracting planning content, predicting based on historical operation state and load data, etc.

[0047] At step 120, a frequency security constrained day-ahead economic dispatch model is constructed, and based on the operating state and load forecasting data, an objective function and constraint conditions of the frequency security constrained day-ahead economic dispatch model are constructed. In some embodiments, step 120 can be performed by the construction module 220.

[0048] The objective function minimizes the sum of fuel cost of thermal power units, frequency regulation reserve cost of thermal power units, loss cost of energy storage power stations, and frequency regulation reserve cost of energy storage power stations in the dispatch period. For example, the sum of fuel cost of thermal power units, frequency regulation reserve cost of thermal power units, loss cost of energy storage power stations, and frequency regulation reserve cost of energy storage power stations is minimized in the next 24 hours.

[0049] In some embodiments, the expression of the objective function is:

[0050]

[0051] wherein Nt represents the total dispatch period, for example, there can be multiple time points in each dispatch period, for a 24-hour dispatch period, there can be 24 time points, the period between each time point can be referred to as a dispatch period (e.g., 0-1h, …, 23-24h), the total dispatch period can refer to the total number of periods formed by each adjacent time point (e.g., a 24-hour dispatch period with 24 time points has a total of 24 periods); Ng, Ne represent the total number of thermal power units and energy storage power stations, respectively; represents the fuel cost of thermal power unit i at time t; represents the frequency regulation reserve cost of thermal power unit i at time t; represents the loss cost of energy storage power station k at time t; represents the frequency regulation reserve cost of energy storage power station k at time t.

[0052] Thermal power unit fuel cost is a quadratic function of unit output:

[0053]

[0054] wherein, represents the fuel cost of thermal power unit i at time t; a i , b i , c i represent the quadratic term coefficient, the linear term coefficient, and the constant term of the fuel cost function of thermal power unit i with respect to unit output, which can be uploaded to the dispatch center by each thermal power plant; is the output size of thermal power unit i at time t.

[0055] Thermal power unit frequency regulation reserve cost is proportional to the reserve capacity size of the unit:

[0056]

[0057] wherein, rgci(t) represents the frequency regulation reserve cost of the thermal power unit i at time t; rgc i rgci(t) represents the frequency regulation reserve cost of the thermal power unit i at time t; rgc rgci(t) represents the frequency regulation reserve cost of the thermal power unit i at time t; rgc

[0058] The loss cost of the energy storage power station is related to the charging and discharging power thereof, and in some embodiments, the loss cost of the energy storage power station k at time t is expressed as:

[0059]

[0060]

[0061]

[0062]

[0063] wherein, represents the loss of the discharging process; represents the loss of the charging process; and respectively represent the charging efficiency and the discharging efficiency of the energy storage power station k; represents the charging / discharging power of the energy storage power station k at time t. represents discharging, at this time represents charging, at this time represents no charging and no discharging, at this time Since in the objective function, when the optimal solution is reached, is equal to and the larger one of the two. respectively represent the charging efficiency and the discharging efficiency of the energy storage power station k.

[0064] In some embodiments, the frequency regulation reserve cost of the energy storage power station k at time t is expressed as:

[0065]

[0066]

[0067] wherein, rec k represents the frequency regulation reserve cost coefficient of the energy storage power station k; represents the frequency regulation reserve size of the energy storage power station k at time t; rec represents the energy storage frequency regulation reserve fixed cost coefficient; represents the rated capacity of the energy storage power station k.

[0068] Some embodiments in the specification can ensure that the ratio of the frequency regulation reserve to the rated capacity of each energy storage power station is the same by setting the frequency regulation reserve cost coefficient to be inversely proportional to the rated capacity, so that the frequency regulation reserve capacity matches the rated capacity of the energy storage power station, balancing the benefits between power stations.

[0069] The constraint condition is at least related to maintaining the stable operation of the power system frequency. The stable operation of the power system frequency can mean that the frequency jump of the power system is within a controllable range.

[0070] In some embodiments, the constraint condition at least includes a power balance constraint, a thermal power unit power constraint, an energy storage power station constraint, a frequency change rate constraint, a quasi-steady frequency constraint, a frequency minimum point constraint, a frequency regulation reserve constraint, a control parameter adjustable range constraint, and a line capacity constraint.

[0071] The expression of the power balance constraint can be:

[0072]

[0073] wherein, represents the output size of the thermal power unit i at time t; represents the charging / discharging power of the energy storage power station k at time t; represents the predicted load size of the node d at time t, which can be obtained at least according to historical electricity consumption load prediction; Nd represents the total number of nodes of the power system, which can be obtained from power system planning. The power balance constraint ensures that the sum of the thermal power unit output and the net injection power of the energy storage power station is equal to the predicted load size of the current power system.

[0074] The expression of the thermal power unit power constraint can include:

[0075]

[0076]

[0077]

[0078]

[0079] wherein, represents the output size of the thermal power unit i at time t; represents the frequency regulation reserve size of the thermal power unit i at time t; Rup i represents the maximum ramping amount of the thermal power unit i; RdownRdown i represents the maximum ramping-up amount of the thermal power unit i; represents the maximum output power of the thermal power unit i; represents the minimum output power of the thermal power unit i. Rup i , Rdown i , The four parameters can be uploaded to the dispatching center by each thermal power plant.

[0080] The thermal power unit power constraint requires that the output power of the thermal power unit be between the minimum output power and the maximum output power , and the ramping-up amount and the ramping-down amount of the thermal power unit be less than the maximum ramping-up amount Rup i and the maximum ramping-down amount Rdown i .

[0081] In some embodiments, the expression of the energy storage power station constraint includes:

[0082]

[0083]

[0084]

[0085]

[0086]

[0087] wherein, represents the energy storage size of the energy storage power station j at time t, which is related to the energy storage value at the previous time and the charging / discharging power in the current time period; represents the energy storage size of the energy storage power station j at time t-1; represents the charging / discharging power of the energy storage power station j at time t; represents the loss power of the energy storage power station k at time t; Δt represents the time length of a dispatching time period; represents the energy storage size of the energy storage at the beginning time of the dispatching period; represents the energy storage size of the energy storage at the end time of the dispatching period; and respectively represent the maximum and minimum energy storage values allowed by the energy storage power station k; represents the maximum charging / discharging power allowed by the energy storage power station k; represents the frequency modulation reserve size of the energy storage power station k at time t.

[0088] The energy storage station constraint requires that the energy storage size of the energy storage station at the end of a dispatch cycle equals its initial energy storage. The energy storage of the energy storage station is between its upper and lower limit values. The charging and discharging power of the energy storage station is between its maximum charging / discharging power. The parameters can be uploaded by each energy storage station to the dispatch center.

[0089] The expression of the frequency rate of change constraint can include:

[0090]

[0091]

[0092] wherein, Jt represents the total inertia of the system at each time point; P base P0 represents the reference power of the entire network, for example, 50 Hz; Pimax,i represents the maximum output power of the thermal power unit i; Rk represents the maximum charging / discharging power allowed by the energy storage station k; H i Ji represents the inertia of the thermal power unit i; Rk,t represents the virtual inertia provided by the energy storage station k at time t, which can be obtained by solving the objective function; f0 represents the reference frequency; ΔP represents the power disturbance, which can be obtained by setting in advance; Rk,t represents the virtual inertia provided by the energy storage station k at time t, which can be obtained by solving the objective function; f0 represents the reference frequency; ΔP represents the power disturbance, which can be obtained by setting in advance; Rk,t represents the virtual inertia provided by the energy storage station k at time t, which can be obtained by solving the objective function; f0 represents the reference frequency; ΔP represents the power disturbance, which can be obtained by setting in advance. The frequency rate of change constraint can convert the maximum frequency rate of change constraint into a linear constraint with respect to the total inertia of the system.

[0093] The expression of the quasi-steady frequency constraint can include:

[0094]

[0095]

[0096] wherein, Jt represents the total damping of the system at each time point; P base P0 represents the reference power of the entire network; D0 represents the damping provided by the load; Pimax,i represents the maximum output power of the thermal power unit i; Rk represents the maximum charging / discharging power allowed by the energy storage station k; R i Kp,i represents the droop control coefficient of the thermal power unit i; Rk,t represents the droop control coefficient provided by the energy storage station k at time t, which can be obtained by solving the objective function; f0 represents the reference frequency; ΔP represents the power disturbance, which can be obtained by setting in advance; Rk,t represents the droop control coefficient provided by the energy storage station k at time t, which can be obtained by solving the objective function; f0 represents the reference frequency; ΔP represents the power disturbance, which can be obtained by setting in advance. The quasi-steady frequency constraint indicates that the system should have sufficient damping to ensure the safety of the quasi-steady frequency.

[0097] The expression for the frequency minimum point constraint can be

[0098]

[0099] in, Represents the total inertia of the system at each moment; Represents the total system damping at each moment. Since the lowest frequency point is a nonlinear function of the system inertia and damping and cannot be directly embedded in the optimization model, the original constraints need to be piecewise linearized before the scheduling model is calculated. Represent the normal vector elements corresponding to inertia and damping in the pth linear segment, b p represents the offset of the pth linear segment, and P represents the total number of segments. Equation (24) is the linear approximation result of the frequency minimum point constraint. This approximation process is performed before the day-ahead scheduling calculation. The frequency minimum point constraint consists of a set of linear inequality constraints, and its corresponding feasible region is the intersection of a set of linear inequalities, that is, a convex set.

[0100] The expression of frequency regulation reserve constraint can be

[0101]

[0102]

[0103] in, represents the frequency regulation reserve size of thermal power unit i at time t; R i represents the droop control coefficient of thermal power unit i; represents the maximum output power of thermal power unit i; represents the quasi-steady-state frequency deviation threshold; f0 represents the reference frequency; represents the frequency regulation reserve size of energy storage power station k at time t; represents the droop control coefficient provided by the energy storage station j at time t; Indicates the maximum charge / discharge power allowed by energy storage station j; Indicates the maximum frequency deviation threshold; represents the virtual inertia provided by the energy storage station j at time t; In some embodiments, the expression for the control parameter adjustable range constraint includes:

[0104]

[0105]

[0106] in, represents the droop control coefficient provided by the energy storage station k at time t; represents an upper bound of the droop control coefficient that the energy storage power station k can provide; represents the virtual inertia provided by the energy storage power station k at time t; represents an upper bound of the virtual inertia that the energy storage power station k can provide. All of them can be uploaded to the dispatch center by each energy storage power station.

[0107] The expression of the line capacity constraint can include:

[0108]

[0109]

[0110] In the formula, represents the maximum power capacity allowed by the transmission line L; represents the transmission distribution coefficient of the thermal power unit output the net injection power of the energy storage power station and the load prediction power The line capacity constraint ensures that the bidirectional power flow of the transmission line L does not exceed its maximum power capacity.

[0111] Some embodiments in the specification can ensure that three important frequency dynamic indicators (maximum frequency change rate, maximum frequency deviation, quasi-steady frequency deviation) do not exceed the limit through the frequency change rate constraint, the quasi-steady frequency constraint and the frequency minimum point constraint, thereby ensuring the frequency dynamic safety of the power system.

[0112] Some embodiments in the specification can establish the coupling relationship between the frequency modulation control parameters and the frequency modulation reserve by increasing the frequency modulation reserve constraint, realize the collaborative optimization of the frequency modulation control parameters and the power generation plan, and ensure the sufficiency of the frequency modulation reserve of the power system.

[0113] Step 130, solving the objective function based on the constraint conditions to obtain the frequency modulation control parameters applied to the energy storage power station. In some embodiments, step 130 can be performed by the solving module 230.

[0114] In some embodiments, the frequency security constrained day-ahead economic dispatch model composed of the objective function and the constraint conditions can be solved by calling various commercial solvers, including but not limited to Gurobi, Cplex, etc. By solving the frequency security constrained day-ahead economic dispatch model, the thermal power unit generation plan, the energy storage power station charging and discharging plan and the energy storage power station frequency modulation control parameter instruction that meet the frequency dynamic safety can be obtained, i.e., the decision variable set Ω:

[0115]

[0116] In the formula, represents the output of the thermal power unit i at time t; represents the frequency modulation reserve of the thermal power unit i at time t; represents the charging / discharging power of the energy storage power station k at time t; represents the energy size stored by the energy storage power station k at time t; represents the frequency modulation reserve size of the energy storage power station k at time t; represents the virtual inertia provided by the energy storage power station k at time t; represents the droop control coefficient provided by the energy storage power station k at time t.

[0117] the variables related to the energy storage power station in the decision variable set Ω are issued to each energy storage power station to realize online optimization configuration of the frequency modulation control parameters of the energy storage power station.

[0118] The frequency modulation control parameters at least include the virtual inertia and the droop control coefficient of the energy storage power station. The dispatching center can issue the frequency modulation control parameters to each energy storage power station to control the running state of the energy storage power station in the dispatching period.

[0119] In some embodiments, the frequency modulation control parameters are also issued to the energy storage power station to adjust the running state of the energy storage power station; the running state and the load prediction data of the power system in the next dispatching period are re-acquired; the frequency modulation control parameters in the next dispatching period are obtained based on the running state and the load prediction data in the next dispatching period, and the cycle is repeated to continuously optimize the entire power system.

[0120] In some embodiments, the running state and the load prediction data of the power system can be acquired at regular time intervals. For example, the running state and the load prediction data are acquired once every 24 hours. The next dispatching period can refer to the dispatching period after the running state and the load prediction data of the power system are acquired. For example, the dispatching period is 24 hours, the time point of acquiring the running state and the load prediction data for the first time is 12:00, and the first dispatching period is 24 hours after 12:00; the time point of acquiring the running state and the load prediction data for the second time is 12:00 the next day, and the second dispatching period is 24 hours after 12:00 the next day. Steps 110-130 are repeated to realize online optimization configuration of the frequency modulation control parameters of the energy storage power station.

[0121] Figure 2 An exemplary module diagram of a system for adjusting frequency modulation parameters of an energy storage power station according to some embodiments of the present application is provided. As shown in Figure 2 the system 200 includes an acquisition module 210, a construction module 220, and a solving module 230.

[0122] The obtaining module 210 is configured to obtain an operating state of a power system in a scheduling period and load prediction data; the power system at least includes thermal power units and energy storage power stations. For more information about the obtaining module 210, see Figure 1 and the related description.

[0123] The constructing module 220 is configured to construct an objective function and constraint conditions based on the operating state and the load prediction data; the objective function minimizes a sum of fuel cost of the thermal power units, frequency regulation reserve cost of the thermal power units, loss cost of the energy storage power stations and frequency regulation reserve cost of the energy storage power stations in the scheduling period; the constraint conditions are at least related to maintaining stable operation of a frequency of the power system. For more information about the constructing module 220, see Figure 1 and the related description.

[0124] The solving module 230 is configured to solve the objective function based on the constraint conditions to obtain frequency regulation control parameters applied to the energy storage power stations; the frequency regulation control parameters at least include virtual inertia and droop control coefficients of the energy storage power stations. For more information about the solving module 230, see Figure 1 and the related description.

[0125] The above merely describes preferred embodiments of the present application but is not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method of adjusting frequency modulation parameters of a pumped storage power station, characterized in that, Comprising obtaining operation state and load prediction data of a power system in a dispatch period; the power system at least includes thermal power units and energy storage power stations; based on the operation state and the load prediction data, constructing a target function and constraint conditions; the target function minimizes the sum of fuel cost of the thermal power units, frequency modulation reserve cost of the thermal power units, loss cost of the energy storage power stations and frequency modulation reserve cost of the energy storage power stations in the dispatch period; the constraint conditions are at least related to keeping the power system frequency stable operation; the expression of the target function is: Wherein, Nt represents the total scheduling period; Ng, Ne respectively represent the total number of thermal power units and energy storage power stations; represents the fuel cost of thermal power unit i at time t; represents the frequency modulation standby cost of thermal power unit i at time t; represents the loss cost of energy storage power station k at time t; represents the frequency modulation standby cost of energy storage power station k at time t; t represents the time variable; i represents the thermal power unit variable; k represents the energy storage power station variable; the constraint conditions include frequency change rate constraint, quasi-steady frequency constraint and frequency modulation reserve constraint, the expression of the frequency change rate constraint includes: wherein, Jt represents the total system inertia at each time instant; P base P0 represents the reference power of the whole network; Pimax represents the maximum output power of the thermal power unit i; Hk represents the maximum charge / discharge power allowed by the energy storage station k; i Ji represents the inertia of the thermal power unit i; Jk(t) represents the virtual inertia provided by the energy storage station k at time instant t; f0 represents the reference frequency; ΔP represents the power disturbance; fmax represents the frequency variation rate threshold; the expression of the quasi-steady frequency constraint includes: wherein, represents the total system damping at each time; P base represents the reference power of the whole network; D0represents the damping provided by the load; represents the maximum output power of the thermal power unit i; represents the maximum charge / discharge power allowed by the energy storage station k; R i represents the droop control coefficient of the thermal power unit i; represents the droop control coefficient provided by the energy storage station k at time t; f0represents the reference frequency, and ΔP represents the power disturbance; represents the quasi-steady frequency deviation threshold value; the expression of the frequency modulation reserve constraint includes: wherein, represents the frequency modulation reserve size of the thermal power unit i at time t; R i represents the droop control coefficient of the thermal power unit i; represents the maximum output power of the thermal power unit i; represents the quasi-steady frequency deviation threshold value; f0represents the reference frequency; represents the frequency modulation reserve size of the energy storage power station k at time t; represents the droop control coefficient provided by the energy storage power station k at time t; represents the maximum charge / discharge power allowed by the energy storage power station k; represents the maximum frequency deviation threshold value; represents the virtual inertia provided by the energy storage power station k at time t; f lim represents the frequency change rate threshold value; solving the target function based on the constraint conditions to obtain frequency modulation control parameters applied to the energy storage power stations; the frequency modulation control parameters at least include virtual inertia and droop control coefficient of the energy storage power stations.

2. The method of claim 1, wherein, Further comprising issuing the frequency modulation control parameters to the energy storage power stations to adjust the operation state of the energy storage power stations; re-obtaining operation state and load prediction data of the power system in the next dispatch period; based on the operation state and the load prediction data of the next dispatch period, obtaining frequency modulation control parameters of the next dispatch period, and cycling in this way to continuously optimize the entire power system.

3. The method of claim 1, wherein, the loss cost of the energy storage power station k at time t is expressed as: wherein, represents the losses of the discharging process; represents the losses of the charging process; and respectively represent the charging efficiency and the discharging efficiency of the energy storage plant k; represents the charging / discharging power of the energy storage plant k at time instant t.

4. The method of claim 1, wherein, The frequency regulation reserve cost of the energy storage power station k at time t The expression is: wherein rec k represents the frequency modulation reserve cost coefficient of the energy storage power station k; represents the frequency modulation reserve size of the energy storage power station k at time t; rec represents the frequency modulation reserve fixed cost coefficient of the energy storage; represents the rated capacity of the energy storage power station k.

5. The method of claim 1, wherein, The constraint conditions at least include power balance constraint, thermal power unit power constraint, energy storage power station constraint, frequency change rate constraint, quasi-steady frequency constraint, frequency minimum point constraint, frequency modulation reserve constraint, control parameter adjustable range constraint and line capacity constraint.

6. The method of claim 5, wherein, The expression of the energy storage power station constraint includes: wherein, represents the energy size stored by the energy storage plant k at time t; represents the energy size stored by the energy storage plant k at time t-1; represents the charging / discharging power of the energy storage plant k at time t; represents the loss power of the energy storage plant k at time t; Δt represents the length of a scheduling period; represents the energy size of the energy storage at the beginning of the scheduling period; represents the energy size of the energy storage at the end of the scheduling period; and respectively represent the maximum and minimum energy storage values allowed by the energy storage plant k; represents the maximum charging / discharging power allowed by the energy storage plant k; represents the frequency regulation reserve size of the energy storage plant k at time t.

7. The method of claim 1, wherein, The expression of the control parameter adjustable range constraint includes: wherein, represents the droop control coefficient provided by the energy storage plant k at time t; represents the upper bound of the droop control coefficient that can be provided by the energy storage plant k; represents the virtual inertia provided by the energy storage plant k at time t; represents the upper bound of the virtual inertia that can be provided by the energy storage plant k.

8. A system for adjusting frequency modulation parameters of an energy storage power station using the method of any one of claims 1-7, characterized in that, comprising an acquisition module, a construction module and a solving module; The acquisition module is used to obtain operation state and load prediction data of a power system in a dispatch period; the power system at least includes thermal power units and energy storage power stations; The construction module is used to construct a target function and constraint conditions based on the operation state and the load prediction data; the target function minimizes the sum of fuel cost of the thermal power units, frequency modulation reserve cost of the thermal power units, loss cost of the energy storage power stations and frequency modulation reserve cost of the energy storage power stations in the dispatch period; the constraint conditions are at least related to keeping the power system frequency stable operation; The solving module is used to solve the target function based on the constraint conditions to obtain frequency modulation control parameters applied to the energy storage power stations; the frequency modulation control parameters at least include virtual inertia and droop control coefficient of the energy storage power stations.

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