Method and system for quantifying energy storage demand of power system considering frequency regulation rate and capacity

Abstract

The present invention relates to a method and system for quantifying the energy storage demand of an electric power system taking into account the frequency modulation rate and capacity. Using the output data of new energy power sources and load data as input, considering the volatility and randomness of new energy, the frequency modulation capacity and frequency modulation rate requirements of the electric power system are obtained through variational mode decomposition and Monte Carlo simulation, and the safe operation of the power grid is verified through multi-dimensional power grid operation constraints to determine whether there is a gap in the regulation capacity of the power system, and to compare the economic efficiency of configuring different regulating power sources such as electrochemical energy storage and conventional power sources, so as to obtain the precise demand of the electric power system for electrochemical energy storage. The present invention solves the problem of quantitative measurement of the configuration capacity of electrochemical energy storage, avoids insufficient or excessive configuration of the regulation resources of the power system, and can effectively improve the safety and economy of power grid construction.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system energy storage planning, and specifically relates to a method and system for quantifying power system energy storage demand taking into account frequency modulation rate and capacity. Background Art

[0002] The goal of low-carbon sustainable development of energy and electricity will promote the rapid increase of wind power, photovoltaic and other new energy power generation installed capacity, and will further increase the power grid's demand for flexible regulation resources. Due to the advantages of fast response speed, high regulation accuracy and flexible application, electrochemical energy storage is an important means to improve the flexibility and reliability of traditional power grids. The quantitative analysis of electrochemical energy storage demand in power grids with a high proportion of new energy has become a research hotspot.

[0003] As a power system regulation resource with rapid response capability, electrochemical energy storage is an important means of frequency support for power systems with a high proportion of new energy. However, there is currently a lack of scientific and complete methods to quantify and analyze the actual demand for electrochemical energy storage in power system frequency regulation. Especially after large-scale random new energy is connected to the grid, the demand for power system regulation resources will be more complicated. At the same time, electrochemical energy storage is costly, and unreasonable energy storage capacity configuration will cause huge waste of social resources. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for quantifying the energy storage demand of an electric power system taking into account the frequency modulation rate and capacity. In view of the fluctuation characteristics of new energy sources such as wind power and photovoltaic power, a method for calculating the frequency modulation rate and capacity constraints of the electric power system is proposed, and on this basis, the capacity demand of the electric power system for electrochemical energy storage is calculated.

[0005] To achieve the above object, the technical solution of the present invention is: a method for quantifying the energy storage demand of a power system taking into account the frequency modulation rate and capacity, comprising the following steps:

[0006] S1. Collect historical load data of the target power system and the time series curve of the output data of new energy power sources including wind power and photovoltaic power; the sampling frequency of the time series curve shall not be less than one minute, and the total duration shall not be less than one year to reflect the random characteristics of the output of new energy power sources; adjust the proportion of the time series curve of historical data according to the load level between the power system corresponding to the historical load data and the target power system and the proportion of new energy installed capacity;

[0007] S2. Calculate the net load timing curve P of the target power system load -P re , where P load Represents the load timing curve, P reRepresent the output time series curve of new energy; use VMD method to decompose the net load time series curve in multiple time scales to obtain the fluctuation components of different time scales, and combine Monte Carlo simulation to obtain the system frequency regulation capacity demand and frequency regulation rate demand;

[0008] S3. Consider the frequency regulation capacity and frequency regulation rate constraints, and combine the multi-dimensional operation constraints including system power balance constraints and unit operation constraints to verify the safe operation of the power grid;

[0009] S4. Based on the weak links in the operation of the power grid, namely the operation bottleneck scenario, further quantitative conclusions on the demand for electrochemical energy storage are obtained.

[0010] In one embodiment of the present invention, in step S2, the specific method of obtaining the system frequency modulation capacity and frequency modulation rate requirement by combining Monte Carlo simulation is as follows:

[0011]

[0012] Where P reg Indicates the system frequency modulation capacity requirement, and are the frequency regulation capacity requirements caused by load fluctuation and renewable energy fluctuation, which can be obtained by decomposing the net load timing curve; ΔP load and ΔP re They are the frequency regulation capacity requirements caused by load forecast deviation and new energy forecast deviation respectively; the frequency regulation capacity is calculated as follows:

[0013] The VMD method is used to decompose the net load time series curve into fluctuation components of different time scales, including high frequency (P load -P re ) 1 , medium and high frequency (P load -P re ) 2 , intermediate frequency (P load -P re ) 3 and low frequency (P load -P re ) 4 The fluctuation components of four time scales, among which the high frequency (P load -P re ) 1 Time scale <3min, medium and high frequency (P load -P re ) 2 The time scale is 3min~15min, medium frequency (P load -P re ) 3 The time scale is 15min~4h, low frequency (P load -P re) 4 The time scale is >4h;

[0014] The calculation method for frequency regulation capacity demand caused by load fluctuation and renewable energy fluctuation is as follows: take the medium and high frequency fluctuation component (P load -P re ) 2 , calculate the maximum fluctuation amplitude of the fluctuation component in each 15-minute period, and take the maximum fluctuation amplitude of all 15-minute periods as the frequency regulation capacity demand caused by load fluctuation and new energy fluctuation; the specific expression is as follows:

[0015]

[0016] Where: T represents each 15-minute period, t represents the time point within each 15-minute period;

[0017] For the frequency regulation capacity demand caused by load forecast deviation and new energy forecast deviation, assuming that the load forecast error and new energy output forecast deviation obey the normal distribution, the Monte Carlo simulation is used to obtain the frequency regulation capacity demand that meets the corresponding probability level requirements of the frequency regulation performance index; where the load forecast deviation ΔP load It can be expressed as The normal distribution of new energy sources including wind power and photovoltaic power has low load predictability. The forecast deviation distribution of wind power and photovoltaic power can be expressed as and The normal distribution of wind power and photovoltaic power generation is considered to have complementary characteristics between their forecast deviations, so the combined forecast deviation of the two is ΔP re Distribution but:

[0018]

[0019] In the formula, σ to represents the standard deviation of the combined wind and PV forecast, σ l , σ w , σ pv denote the standard deviations of load, wind power and PV forecast deviations, respectively, and ρ denotes the correlation coefficient between wind power and PV forecast deviations;

[0020] When the confidence level is 1-α, the system frequency regulation capacity demand caused by load forecast deviation and new energy forecast is:

[0021] ΔP load =[-Z α / 2 σ 1 ,Z α / 2 σ 1 ], ΔP re =[-Z α / 2 σ to ,Zα / 2 σ to ]

[0022]

[0023] In the formula, Z α / 2 is the quantile of the standard normal distribution at probability α / 2. α is 10%.

[0024] In one embodiment of the present invention, the VMD method is used to decompose the net load time series curve to obtain the high frequency (P load -P re ) 1 The frequency modulation rate requirement needs to be calculated by the following formula, and the maximum frequency modulation rate within a period of time is counted to obtain the power grid frequency modulation rate requirement:

[0025]

[0026] Where V reg Represents the maximum frequency modulation rate requirement of the system within a period of time.

[0027] In one embodiment of the present invention, step S3 is specifically implemented as follows:

[0028] The grid operation objective function is:

[0029]

[0030] Ω={P MAX ,P MIN ,RU,RD,RegU,RegD,RegV}

[0031] Where Ω is the set of slack variables, λ i The slack variables introduced to meet the grid operation constraints are all non-negative variables, including the maximum power output Minimum technical output Power ramp limit λ RU , power climbing limit λ RD , frequency increase limit λ RegU , frequency reduction limit λ RegD and FM rate limit λ RegV ,ω iis the weight of the corresponding slack variable, which can be calculated by the hierarchical analysis method. By constructing a judgment matrix and performing a consistency test, the relative importance of each restriction index in the judgment matrix refers to the priority order of the corresponding power grid operation constraint type, and the weight coefficients of each index are [0.3062, 0.3062, 0.1159, 0.1159, 0.0608, 0.0608, 0.0342], respectively. The consistency ratio CR is calculated to be 0.005, which is less than the standard value of 0.1 of the hierarchical analysis method consistency test, and the consistency test is passed.

[0032] In one embodiment of the present invention, in step S3, the operating constraints include system power balance constraints, unit output constraints, unit ramp constraints, start and stop time constraints, frequency regulation and spinning reserve capacity constraints, and frequency regulation rate constraints, wherein:

[0033] 1) Frequency regulation and spinning reserve capacity constraints

[0034] According to the power system frequency regulation capacity demand calculated in step S2, taking into account the system spinning reserve requirements, the system frequency regulation and spinning reserve capacity constraints are formed; at the same time, slack variables are introduced to determine whether the existing regulation resources meet the power grid frequency regulation capacity demand; as shown in the following formula:

[0035]

[0036] Where N g Indicates the number of conventional units in the system, N mg is the number of pumped storage units in the system, P i,t is the output of the i-th conventional unit at time t, P i,max is the maximum output of the i-th unit, P i,min is the minimum output of the i-th unit, u i,t is the start / stop flag of the i-th conventional unit at time t, represents the frequency regulation capacity provided by pumped storage unit i in a certain regional power grid at time t, To adjust the capacity requirements of the system upwards, To adjust the capacity requirements of the system downwards, The system needs to rotate up the emergency reserve capacity. Rotate the emergency reserve capacity requirement downward for the system;

[0037] 2) Frequency modulation rate constraint

[0038] According to the power system frequency regulation rate requirement calculated in step S2, the system frequency regulation rate constraint condition is formed:

[0039]

[0040] j∈{coal power, hydropower, gas unit, pumped storage unit}

[0041] In the formula, c j Different climbing rates are adopted according to the unit type;

[0042] 3) Slack variable range

[0043]

[0044] The above formula represents the range of slack variables. All slack variables are non-negative variables. Considering that the unit output is non-negative, The upper limit of is the minimum technical output of conventional unit i:

[0045]

[0046] Through the above model, the quantitative calculation results of the target power system frequency regulation capacity and frequency regulation rate shortage can be obtained.

[0047] In one embodiment of the present invention, in S4, based on the grid operation bottleneck scenario, an optimization model with annualized construction and operation and maintenance costs over the entire life cycle as the objective function is established to calculate a solution for the frequency regulation capacity shortage and obtain the capacity demand of the power system for energy storage. The optimization model is as follows:

[0048]

[0049] In the formula, f obj_C represents the objective function, i.e., the annualized construction and operation and maintenance costs over the entire life cycle, where P k and E k They represent the rated power and rated energy of the i-th candidate frequency-regulated power source or energy storage; f sys represents the system power balance constraint, spinning reserve constraint and frequency regulation rate constraint, where P g , P mg , P re , P es They represent the output of conventional units, existing pumped storage units, new energy units and candidate frequency regulation power sources, respectively. c d s are the power of new energy abandonment and load shedding respectively; f g represents the constraints of conventional units, including unit output constraints, start-stop constraints, and ramp constraints, where u g is the start-stop variable of the conventional unit; f es Characterize the constraints of candidate energy storage plants, E es , P ch / P dc , P reg They represent the variables of energy state, charge / discharge power and frequency regulation capacity of the energy storage unit.

[0050] The present invention also provides a power system energy storage demand quantification system taking into account frequency modulation rate and capacity, comprising:

[0051] The reading and preprocessing module is used to read the historical load data of the target power system and the output data time series curve data of new energy sources including wind power and photovoltaic power; and can adjust the historical data curve in proportion to the changes in the load level of the target power system and the installed capacity of new energy sources;

[0052] The frequency modulation capacity and frequency modulation rate requirement calculation module is used to obtain the system frequency modulation capacity and frequency modulation rate requirement through the variational mode decomposition method and Monte Carlo simulation method based on the data read and pre-processed;

[0053] The power grid safety operation verification module is used to determine whether the power grid has operation bottlenecks through multi-dimensional operation constraints;

[0054] The bottleneck elimination scheme formulation and relative economic comparison module is used to select various types of bottleneck elimination schemes according to the identified grid operation bottleneck results, and compare the relative economic efficiency of electrochemical energy storage and other schemes for eliminating bottleneck scenarios;

[0055] The electrochemical energy storage demand result output module is used to compare the results based on relative economic efficiency, so as to obtain quantitative conclusions on the electrochemical energy storage demand of power grids containing a high proportion of new energy.

[0056] Compared with the prior art, the present invention has the following beneficial effects: the method and system of the present invention adopt a grid bottleneck analysis and calculation method to solve the problem of calculating the grid's demand for electrochemical energy storage configuration, avoid insufficient or excessive configuration of power system regulation resources, and effectively improve the safety and economy of grid construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 The present invention is a flow chart of a method for quantitatively analyzing power system energy storage demand taking into account frequency regulation rate and capacity constraints.

[0058] Figure 2 This is a structural diagram of the power system energy storage demand quantitative analysis system taking into account frequency regulation rate and capacity constraints of the present invention.

[0059] Figure 3 It is the decomposition result of a typical day net load curve of a provincial power grid obtained by the VMD method in the application example of the present invention.

[0060] Figure 4 It is the calculation result of the frequency regulation capacity demand of a typical day of the provincial power grid in the application example of the present invention.

[0061] Figure 5 It is the calculation result of the frequency regulation rate demand of a typical day of the provincial power grid in the application example of the present invention.

[0062] Figure 6 It is the result of identifying the operating bottleneck of the provincial power grid in the application example of the present invention in 2030 taking into account the scenario of growth of installed capacity of new energy sources. DETAILED DESCRIPTION

[0063] The technical solution of the present invention is described in detail below in conjunction with the accompanying drawings.

[0064] The present invention provides a method for quantifying energy storage demand of a power system taking into account frequency modulation rate and capacity, comprising the following steps:

[0065] S1. Collect historical load data of the target power system and the time series curve of the output data of new energy power sources including wind power and photovoltaic power; the sampling frequency of the time series curve shall not be less than one minute, and the total duration shall not be less than one year to reflect the random characteristics of the output of new energy power sources; adjust the proportion of the time series curve of historical data according to the load level between the power system corresponding to the historical load data and the target power system and the proportion of new energy installed capacity;

[0066] S2. Calculate the net load timing curve P of the target power system load -P re , where P load Represents the load timing curve, P re Represent the output time series curve of new energy; use VMD method to decompose the net load time series curve in multiple time scales to obtain the fluctuation components of different time scales, and combine Monte Carlo simulation to obtain the system frequency regulation capacity demand and frequency regulation rate demand;

[0067] S3. Consider the frequency regulation capacity and frequency regulation rate constraints, and combine the multi-dimensional operation constraints including system power balance constraints and unit operation constraints to verify the safe operation of the power grid;

[0068] S4. Based on the weak links in the operation of the power grid, namely the operation bottleneck scenario, further quantitative conclusions on the demand for electrochemical energy storage are obtained.

[0069] The following is the specific implementation process of the present invention.

[0070] In a preferred embodiment of the present invention, Figure 1 A method for quantitatively analyzing power system energy storage demand taking into account frequency regulation rate and capacity constraints according to a preferred embodiment of the present invention comprises the following steps:

[0071] S1. Collect the historical load data of the target power system and the output data time series curves of new energy sources such as wind power and photovoltaic power. The sampling frequency of the time series curve shall not be less than one minute, and the total duration shall not be less than one year, so as to fully reflect the random characteristics of the output of new energy sources. According to the changes in the load level of the target power system and the installed capacity of new energy, the historical data curve shall be adjusted in proportion as necessary.

[0072] S2. Calculate the net load timing curve P of the target power system load -P re , where P load Represents the load timing curve, P re Represents the output time series curve of renewable energy. The variational mode decomposition (VMD) method is used to decompose the net load time series curve in multiple time scales to obtain the fluctuation components of different time scales, and the system frequency regulation capacity and frequency regulation rate requirements are obtained by combining Monte Carlo simulation.

[0073] In this step, the influence of load forecast error and renewable energy output forecast error is comprehensively considered, and Monte Carlo simulation is used to obtain the frequency regulation capacity demand of the system when meeting the probability level corresponding to the frequency regulation assessment performance index.

[0074]

[0075] Where P reg Indicates the system frequency modulation capacity requirement, and are the frequency regulation capacity requirements caused by load fluctuation and renewable energy fluctuation, which can be obtained by decomposing the net load curve; ΔP load and ΔP re They are the frequency regulation capacity requirements caused by load forecast deviation and new energy forecast deviation. The frequency regulation capacity calculation includes the following steps:

[0076] The VMD method is used to decompose the net load curve into fluctuation components of different time scales, including high frequency (P load -P re ) 1 (time scale <3min), medium and high frequency (P load -P re ) 2 (time scale 3min~15min), medium frequency (P load -P re ) 3 (time scale 15min~4h) and low frequency (P load -P re ) 4 (Time scale > 4h) Fluctuation components of four time scales.

[0077] Furthermore, the frequency regulation capacity demand caused by load fluctuation and renewable energy fluctuation is calculated as follows. load -P re ) 2 , calculate the maximum fluctuation amplitude of the fluctuation component in each 15-minute period, and take the maximum fluctuation amplitude of all 15-minute periods as the frequency regulation capacity demand caused by load fluctuation and new energy fluctuation. The specific expression is as follows:

[0078]

[0079] Where: T represents each 15-minute period, and t represents the time point within each 15-minute period.

[0080] For the frequency regulation capacity demand caused by load forecast deviation and new energy forecast deviation, assuming that the load forecast error and new energy output forecast deviation obey the normal distribution, the Monte Carlo simulation is used to obtain the frequency regulation capacity demand that meets the probability level requirement (for example, 90%) of the frequency regulation performance index (taking the CPS index as an example). load It can be expressed as The normal distribution of new energy (such as wind power and photovoltaic power) is relatively low in load predictability. The distribution of wind power and photovoltaic power forecast deviation can be expressed as and The normal distribution of wind power and photovoltaic power generation is considered to have complementary characteristics between their forecast deviations, so the combined forecast deviation of the two is ΔP re Distribution but:

[0081]

[0082] In the formula, σ to represents the standard deviation of the combined wind and PV forecast, σ l , σ w , σ pv They represent the standard deviations of load, wind power and PV forecast deviations, respectively, and ρ represents the correlation coefficient between wind power and PV forecast deviations.

[0083] When the confidence level is 1-α, the system frequency regulation capacity demand caused by load forecast deviation and new energy forecast is:

[0084] ΔP load =[-Z α / 2 σ 1 ,Z α / 2 σ 1 ], ΔP re =[-Z α / 2 σ to ,Z α / 2 σto ]

[0085]

[0086] In the formula, Z α / 2 is the quantile of the standard normal distribution at probability α / 2. α is 10%.

[0087] In addition, for the system frequency modulation rate requirement, the high-frequency component (P load -P re ) 1 , calculate the frequency modulation rate requirement according to formula (6), and count the maximum frequency modulation rate within a period (such as 1h) to obtain the power grid frequency modulation rate requirement.

[0088]

[0089] Where V reg Represents the maximum frequency regulation rate requirement of the system within a period of time. According to the frequency regulation capacity and frequency regulation rate constraints calculated in the above steps, combined with the power grid safe operation constraints, the bottleneck of the power grid is identified as described in step S3.

[0090] S3. Based on the requirements for safe operation of the power grid, taking into account the constraints of frequency regulation capacity and frequency regulation rate, and combining multi-dimensional operation constraints such as system power balance and unit operation constraints, the safe operation of the power grid is verified.

[0091] In this step, according to the safe operation requirements of the power grid, considering the frequency regulation capacity and frequency regulation rate constraints, combined with multi-dimensional operation constraints such as system power balance and unit operation constraints, the bottleneck of the power grid is identified, and the slack variables are introduced to determine whether the power grid has an operation bottleneck. The objective function is:

[0092]

[0093] Ω={P MAX ,P MIN ,RU,RD,RegU,RegD,RegV}

[0094] Where Ω is the set of slack variables, λ i The slack variables introduced to meet the grid operation constraints are all non-negative variables, including the maximum power output Minimum technical output Power ramp limit λ RU , power climbing limit λ RD , frequency increase limit λ RegU , frequency reduction limit λ RegD and FM rate limit λ RegV ,ω iis the weight of the corresponding slack variable, which can be calculated by the hierarchical analysis method. By constructing a judgment matrix and performing a consistency test, the relative importance of each restriction index in the judgment matrix refers to the priority order of the corresponding power grid operation constraint type. The weight coefficients of each index are [0.3062, 0.3062, 0.1159, 0.1159, 0.0608, 0.0608, 0.0342], and the consistency ratio CR is calculated to be 0.005, which is less than the standard value of 0.1 of the hierarchical analysis method consistency test and passes the consistency test.

[0095] In addition, in the process of solving the above objective function, constraints need to be set. In addition to system power balance constraints, unit output constraints, unit ramp constraints, and start-stop time constraints, the operating constraints also include frequency regulation and spinning reserve capacity constraints and frequency regulation rate constraints.

[0096] 1) Frequency regulation and spinning reserve capacity constraints

[0097] According to the power system frequency regulation capacity demand calculated in step S2, the system spinning reserve requirements are considered to form system frequency regulation and spinning reserve capacity constraints. At the same time, slack variables are introduced to determine whether the existing regulation resources meet the power grid frequency regulation capacity demand.

[0098] As shown in the following formula.

[0099]

[0100] Where N g Indicates the number of conventional units in the system, N mg is the number of pumped storage units in the system, P i,t is the output of the i-th conventional unit at time t, P i,max is the maximum output of the i-th unit, P i,min is the minimum output of the i-th unit, u i,t is the start / stop flag of the i-th conventional unit at time t, represents the frequency regulation capacity provided by pumped storage unit i in a certain regional power grid at time t, To adjust the capacity requirements of the system upwards, To adjust the capacity requirements of the system downwards, The system needs to rotate the emergency reserve capacity upward. Rotate the emergency reserve capacity requirement downward for the system.

[0101] 2) Frequency modulation rate constraint

[0102] According to the power system frequency regulation rate requirement calculated in step S2, the system frequency regulation rate constraint condition is formed:

[0103]

[0104] j∈{coal power, hydropower, gas unit, pumped storage unit}

[0105] In the formula, c j Different climbing rates are adopted according to the unit type.

[0106] 3) Slack variable range

[0107]

[0108] The above formula represents the range of slack variables. All slack variables are non-negative variables. Considering that the unit output is non-negative, The upper limit of is the minimum technical output of conventional unit i.

[0109]

[0110] Through the above model, the quantitative calculation results of the target power system frequency regulation capacity and frequency regulation rate shortage can be obtained.

[0111] S4: Based on the identified weak links in grid operation, i.e., operational bottleneck scenarios, the relative economic efficiency of electrochemical energy storage and other solutions for eliminating bottleneck scenarios is compared to obtain a quantitative conclusion on the demand for electrochemical energy storage.

[0112] In this step, based on the bottleneck identification results of step S3, combined with the technical and economic parameters of electrochemical energy storage and other common frequency modulation power sources, an optimization model with the annualized construction and operation and maintenance costs over the entire life cycle as the objective function is established to calculate the solution for the shortage of frequency modulation capacity and obtain the capacity demand of the power system for energy storage. Among them, the bottleneck identification model of step S3 provides the optimization model of step S4 with the scenario and probability of the existence of operation bottlenecks in the power grid. The specific model is as follows:

[0113]

[0114] In the formula, f obj_C represents the objective function, i.e., the annualized construction and operation and maintenance costs over the entire life cycle, where P k and E k They represent the rated power and rated energy of the i-th candidate frequency-regulated power source or energy storage; f sys The system power balance constraint, spinning reserve constraint and frequency modulation rate constraint are represented. For specific description, please refer to step S3, where P g , P mg , P re , P es They represent the output of conventional units, existing pumped storage units, new energy units and candidate frequency regulation power sources, respectively. c d s are the power of new energy abandonment and load shedding respectively; f grepresents the constraints of conventional units, including unit output constraints, start-stop constraints, and ramp constraints, where u g is the start-stop variable of the conventional unit; f es Characterize the constraints of candidate energy storage plants, E es , P ch (P dc ), P reg They represent the variables of energy state, charging (discharging) power and frequency regulation capacity of the energy storage unit respectively.

[0115] Figure 2 The present invention provides a power system energy storage demand quantitative analysis system taking into account frequency regulation rate and capacity constraints, the system comprising:

[0116] The reading and preprocessing module 201 is used to read the historical load data of the target power system and the output data timing curve data of new energy power sources such as wind power and photovoltaic power; and can perform necessary proportional scaling adjustments on the historical data curve according to the changes in the load level of the target power system and the installed capacity of new energy sources.

[0117] The frequency modulation capacity and frequency modulation rate requirement calculation module 202 is used to obtain the system frequency modulation capacity and frequency modulation rate requirement through the variational mode decomposition method and the Monte Carlo simulation method according to the data obtained by reading and preprocessing.

[0118] The power grid safe operation verification module 203 is used to determine whether the power grid has an operation bottleneck through multi-dimensional operation constraints.

[0119] The bottleneck elimination plan formulation and relative economic efficiency comparison module 204 is used to select various types of bottleneck elimination plans according to the identified grid operation bottleneck results, and compare the relative economic efficiency of electrochemical energy storage and other solutions for bottleneck elimination scenarios.

[0120] The electrochemical energy storage demand result output module 205 is used to obtain a quantitative conclusion on the electrochemical energy storage demand of a power grid containing a high proportion of new energy based on the relative economic comparison results.

[0121] In order to verify the effectiveness of the present invention, the quantitative analysis method mentioned above is implemented in the following application example using relevant data of a provincial power grid. The specific steps are not repeated here, and the technical effects and implementation details are mainly given.

[0122] Application Examples

[0123] The present invention uses MATLAB software to write the method described in the present invention, calls GUROBI for solving, and demonstrates the implementation effect based on case data.

[0124] Operating environment:

[0125] AMD Ryzen53400G CPU 3.70GHz, 16GB memory, Microsoft Windows 10X64

[0126] GUROBI 9.0.3

[0127] MATLAB 2020B

[0128] Implementation results:

[0129] This application example is based on the power supply and load data of a provincial power grid, where the power supply data includes conventional units, renewable energy power generation, pumped storage units, and out-of-region transmission data. The frequency regulation capacity and frequency regulation rate of the provincial power grid in 2030 are calculated, and a quantitative analysis of the electrochemical energy storage demand is performed.

[0130] Figure 1 The figure is an overall flow chart of the method of the present invention.

[0131] Figure 2 It is the overall structure diagram of the system of the present invention.

[0132] Figure 3 It reflects the decomposition results of the net load curve of a typical day of the provincial power grid obtained by the VMD method, in which the net load curve decomposition obtains fluctuation components of different time scales, including high frequency (time scale <3min), medium and high frequency (time scale 3min~15min), medium frequency (time scale 15min~4h) and low frequency (time scale >4h) fluctuation components of four time scales. The medium and high frequency and high frequency fluctuation components can be used for system frequency regulation capacity and frequency regulation rate reference respectively.

[0133] Figure 4 It reflects the calculation results of the frequency regulation capacity demand of a typical day in the provincial power grid, including the upward frequency regulation capacity and the downward frequency regulation capacity. It is close to the 3% load output data and the 10% new energy output data. Compared with taking a certain proportion of the maximum predicted load in each period of the day, this calculation method is more in line with the actual needs of the power grid and avoids wasting resources.

[0134] Figure 5 It reflects the calculated results of the frequency regulation rate demand on a typical day of the provincial power grid, which is close to the 2% load output data and the 6% new energy output data.

[0135] Figure 6 It reflects the results of identifying operational bottlenecks for the provincial power grid in 2030 considering the scenario of growth in new energy installed capacity. Under normal circumstances, the provincial power grid has no operational bottlenecks and no mandatory energy storage demand. However, when the proportion of new energy installed capacity increases (taking the growth of wind power by 3 million kilowatts and photovoltaic power by 2 million kilowatts as an example), there will be grid operation bottleneck scenarios, and flexible resources such as energy storage will be needed to improve the safe and stable operation capabilities of the power grid.

[0136] Table 1 reflects the economic comparison of different solutions for eliminating bottlenecks in grid operation, where bottleneck scenario 1 indicates that there are bottlenecks of insufficient power down regulation, insufficient downward frequency regulation capacity, and insufficient frequency regulation rate, and bottleneck scenario 2 indicates that there are bottlenecks of insufficient downward frequency regulation capacity and insufficient frequency regulation rate. According to Table 1, pumped storage is more economical in eliminating the bottleneck of insufficient power down regulation, while electrochemical energy storage is more economical in eliminating the bottleneck of insufficient frequency regulation capacity and frequency regulation rate. Taking lithium iron phosphate batteries as an example, the energy storage demand for eliminating bottleneck scenario 2 of the provincial power grid is: 708MW, 708MWh. According to the results of this case, it can be seen that a high proportion of new energy power grid has a high demand for electrochemical energy storage technology in the scenario of eliminating the bottleneck of grid frequency regulation capacity and frequency regulation rate, and when the planned capacity of pumped storage power stations is subject to certain restrictions due to factors such as long construction period and geographical environment, the demand for electrochemical energy storage will increase further.

[0137] Table 1 Comparison of economic performance of various solutions for eliminating grid operation bottlenecks

[0138]

[0139] The above are preferred embodiments of the present invention. Any changes made according to the technical solution of the present invention, as long as the resulting functions do not exceed the scope of the technical solution of the present invention, belong to the protection scope of the present invention.

Claims

1. A method for quantifying the energy storage demand of power systems taking into account frequency regulation rate and capacity, It is characterized in that The steps include: S1. Collect historical load data of the target power system and the time series curve of the output data of new energy power sources including wind power and photovoltaic power; the sampling frequency of the time series curve shall not be less than one minute, and the total duration shall not be less than one year to reflect the random characteristics of the output of new energy power sources; adjust the proportion of the historical data time series curve according to the load level between the power system corresponding to the historical load data and the target power system and the proportion of new energy installed capacity; S2. Calculate the net load timing curve P of the target power system load -P re , where P load Represents the load timing curve, P re Represents the timing curve of new energy output; The VMD method is used to decompose the net load time series curve into multiple time scales to obtain the fluctuation components of different time scales, and the system frequency regulation capacity demand and frequency regulation rate demand are obtained by combining Monte Carlo simulation. S3. Consider the frequency regulation capacity and frequency regulation rate constraints, and combine the multi-dimensional operation constraints including system power balance constraints and unit operation constraints to verify the safe operation of the power grid; S4. Based on the weak links in the operation of the power grid, i.e. the operation bottleneck scenario, further quantify the demand for electrochemical energy storage; In step S2, the specific method of obtaining the system frequency modulation capacity and frequency modulation rate requirement by combining Monte Carlo simulation is as follows: Where P reg Indicates the system frequency modulation capacity requirement, and They are the frequency regulation capacity requirements caused by load fluctuation and renewable energy fluctuation, respectively, which are obtained by decomposing the net load timing curve; ΔP load and ΔP re They are the frequency regulation capacity requirements caused by load forecast deviation and new energy forecast deviation respectively; the frequency regulation capacity is calculated as follows: The VMD method is used to decompose the net load time series curve into fluctuation components of different time scales, including high frequency (P load -P re ) 1 , medium and high frequency (P load -P re ) 2 , intermediate frequency (P load -P re ) 3 and low frequency (P load -P re ) 4 The fluctuation components of four time scales, among which the high frequency (P load -P re ) 1 Time scale <3min, medium and high frequency (P load -P re ) 2 The time scale is 3min~15min, medium frequency (P load -P re ) 3 The time scale is 15min~4h, low frequency (P load -P re ) 4 The time scale is >4h; The calculation method for frequency regulation capacity demand caused by load fluctuation and renewable energy fluctuation is as follows: take the medium and high frequency fluctuation component (P load -P re ) 2 , calculate the maximum fluctuation amplitude of the fluctuation component in each 15-minute period, and take the maximum fluctuation amplitude of all 15-minute periods as the frequency regulation capacity demand caused by load fluctuation and new energy fluctuation; the specific expression is as follows: Where: T represents each 15-minute period, t represents the time point within each 15-minute period; For the frequency regulation capacity demand caused by load forecast deviation and new energy forecast deviation, assuming that the load forecast error and new energy output forecast deviation obey the normal distribution, the Monte Carlo simulation is used to obtain the frequency regulation capacity demand that meets the probability level requirements of the frequency regulation performance indicators. The load forecast deviation ΔP load Expressed as N(0,σ l 2 ), including wind power and photovoltaic new energy, has low load predictability. The forecast deviation distribution of wind power and photovoltaic is expressed as and The normal distribution of wind power and photovoltaic power generation is considered to have complementary characteristics between their forecast deviations, so the combined forecast deviation of the two is ΔP re Distribution but: In the formula, σ to represents the standard deviation of the combined wind and PV forecast, σ l , σ w , σ pv denote the standard deviations of load, wind power and PV forecast deviations, respectively, and ρ denotes the correlation coefficient between wind power and PV forecast deviations; When the confidence level is 1-α, the system frequency regulation capacity demand caused by load forecast deviation and new energy forecast is: ΔP load =[-Z α / 2 s 1 ,Z α / 2 s 1 ], ΔP re =[-Z α / 2 s to ,Z α / 2 s to ] In the formula, Z α / 2 is the quantile of the standard normal distribution at probability α / 2.

2. The method for quantifying the energy storage demand of the power system taking into account the frequency modulation rate and capacity according to claim 1, It is characterized in that α is taken as 10%.

3. The method for quantifying the energy storage demand of the power system taking into account the frequency modulation rate and capacity according to claim 1, It is characterized in that The VMD method is used to decompose the net load time series curve to obtain the high frequency (P load -P re ) 1 The frequency modulation rate requirement needs to be calculated by the following formula, and the maximum frequency modulation rate within a period of time is counted to obtain the power grid frequency modulation rate requirement: Where V reg Represents the maximum frequency modulation rate requirement of the system within a period of time.

4. The method for quantifying the energy storage demand of a power system taking into account frequency modulation rate and capacity according to claim 1, It is characterized in that The step S3 is specifically implemented as follows: The grid operation objective function is: Ω={P MAX ,P MIN ,RU,RD,RegU,RegD,RegV} Where Ω is the set of slack variables, λ i The slack variables introduced to meet the grid operation constraints are all non-negative variables, including the maximum power output Minimum technical output Power ramp limit λ RU , power climbing limit λ RD , frequency increase limit λ RegU , frequency reduction limit λ RegD and FM rate limit λ RegV ,ω i is the weight of the corresponding slack variable, which is calculated by the hierarchical analysis method. By constructing a judgment matrix and performing a consistency test, the relative importance of each restriction index in the judgment matrix refers to the priority order of the corresponding power grid operation constraint type, and the weight coefficients of each index are [0.3062, 0.3062, 0.1159, 0.1159, 0.0608, 0.0608, 0.0342], respectively. The consistency ratio CR is calculated to be 0.005, which is less than the standard value of 0.1 of the hierarchical analysis method consistency test, and the consistency test is passed.

5. The method for quantifying the energy storage demand of the power system taking into account the frequency regulation rate and capacity according to claim 1, It is characterized in that In step S3, the operating constraints include system power balance constraints, unit output constraints, unit ramp constraints, start and stop time constraints, frequency regulation and spinning reserve capacity constraints, and frequency regulation rate constraints, where: 1) Frequency regulation and spinning reserve capacity constraints According to the power system frequency regulation capacity demand calculated in step S2, taking into account the system spinning reserve requirements, the system frequency regulation and spinning reserve capacity constraints are formed; at the same time, slack variables are introduced to determine whether the existing regulation resources meet the power grid frequency regulation capacity demand; as shown in the following formula: Where N g Indicates the number of conventional units in the system, N mg is the number of pumped storage units in the system, P i,t is the output of the i-th conventional unit at time t, P i,max is the maximum output of the i-th unit, P i,min is the minimum output of the i-th unit, u i,t is the start / stop flag of the i-th conventional unit at time t, represents the frequency regulation capacity provided by pumped storage unit i in a certain regional power grid at time t, To adjust the capacity requirements of the system upwards, To adjust the capacity requirements of the system downwards, The system needs to rotate up the emergency reserve capacity. Rotate the emergency reserve capacity requirement downward for the system; 2) Frequency modulation rate constraint According to the power system frequency regulation rate requirement calculated in step S2, the system frequency regulation rate constraint condition is formed: j∈{coal power, hydropower, gas unit, pumped storage unit} In the formula, c j Different climbing rates are adopted according to the unit type; 3) Slack variable range The above formula represents the range of slack variables. All slack variables are non-negative variables. Considering that the unit output is non-negative, The upper limit of is the minimum technical output of conventional unit i: The quantitative calculation results of the target power system frequency regulation capacity and frequency regulation rate shortage are obtained.

6. The method for quantifying the energy storage demand of a power system taking into account frequency modulation rate and capacity according to claim 1, It is characterized in that In S4, based on the grid operation bottleneck scenario, an optimization model with the annualized construction and operation and maintenance costs over the entire life cycle as the objective function is established to calculate the solution to the frequency regulation capacity shortage and obtain the capacity demand of the power system for energy storage. The optimization model is as follows: In the formula, f obj_C represents the objective function, i.e., the annualized construction and operation and maintenance costs over the entire life cycle, where P k and E k They represent the rated power and rated energy of the i-th candidate frequency-regulated power source or energy storage; f sys represents the system power balance constraint, spinning reserve constraint and frequency regulation rate constraint, where P g , P mg , P re , P es They represent the output of conventional units, existing pumped storage units, new energy units and candidate frequency regulation power sources, respectively. c ,d s are the power of new energy abandonment and load shedding respectively; f g represents the constraints of conventional units, including unit output constraints, start-stop constraints, and ramp constraints, where u g is the start and stop variable of the conventional unit; f es Characterize the constraints of candidate energy storage plants, E es , P ch / P dc , P reg They represent the variables of energy state, charge / discharge power and frequency regulation capacity of the energy storage unit.

7. A system for quantifying energy storage demand of a power system taking into account frequency modulation rate and capacity, executing the method for quantifying energy storage demand of a power system taking into account frequency modulation rate and capacity as claimed in any one of claims 1 to 6, It is characterized in that include: The reading and preprocessing module is used to read the historical load data of the target power system and the output data timing curve data of new energy power sources including wind power and photovoltaic power; And according to the changes in the target power system load level and the installed capacity of new energy, the historical data curve is scaled and adjusted proportionally; The frequency modulation capacity and frequency modulation rate requirement calculation module is used to obtain the system frequency modulation capacity and frequency modulation rate requirement through the variational mode decomposition method and Monte Carlo simulation method based on the data read and pre-processed; The power grid safety operation verification module is used to determine whether the power grid has operation bottlenecks through multi-dimensional operation constraints; The bottleneck elimination scheme formulation and relative economic comparison module is used to select various types of bottleneck elimination schemes according to the identified grid operation bottleneck results, and compare the relative economic efficiency of electrochemical energy storage and other schemes for eliminating bottleneck scenarios; The electrochemical energy storage demand result output module is used to compare the results based on relative economic efficiency, so as to obtain quantitative conclusions on the electrochemical energy storage demand of power grids containing a high proportion of new energy.

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