A flywheel energy storage system capacity configuration method for smoothing wind power fluctuation of grid access
The flywheel energy storage system capacity configuration method, which combines frequency divider and multi-tracker optimization algorithms, solves the problem of grid frequency instability caused by wind farm power fluctuations, and achieves cost optimization and grid security improvement.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NORTH CHINA ELECTRIC POWER UNIV
- Filing Date
- 2022-08-12
- Publication Date
- 2026-07-21
AI Technical Summary
In existing technologies, flywheel energy storage systems have a single capacity configuration strategy for mitigating power fluctuations in wind farms, which increases the risk of grid frequency fluctuations and lacks an effective energy storage capacity configuration method to meet the requirements of safe and stable operation of the power system.
A frequency divider is used to separate the active power of the wind farm. Combined with a multi-tracker optimization algorithm, the capacity configuration of the flywheel energy storage system is determined by responding to high-frequency power commands. The capacity configuration of the energy storage system is optimized by considering the economics throughout the entire life cycle and grid load fluctuations.
This approach effectively mitigates wind farm power fluctuations, improves grid security, stability, and economy, and optimizes power system operating conditions while reducing equipment costs.
Smart Images
Figure CN115528725B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to a capacity configuration method for a flywheel energy storage system, and more particularly to a capacity configuration method for a flywheel energy storage system that smooths out fluctuations in wind power connected to the grid. Background Technology
[0002] The increasing penetration rate of wind power in the power grid has altered the proportion of clean energy in the power system and increased the risk of grid frequency fluctuations. Due to the strong randomness and volatility of wind energy, its large-scale grid connection inevitably disrupts the safe and stable operation of the power system. Therefore, the "Technical Regulations for Wind Farm Connection to the Power System Part 1: Onshore Wind Power," promulgated in August 2021, introduced new requirements for existing wind farms: during grid connection and wind speed increases, the active power variation of the wind farm should meet the requirements for the safe and stable operation of the power system. The limits should be determined by the power system dispatching agency based on the frequency regulation characteristics of the connected power system, and recommended values for the active power variation limits of the wind farm are provided. To meet these requirements, energy storage technology is typically used to smooth the active power output fluctuations on the wind farm side.
[0003] Among numerous energy storage technologies, flywheel energy storage systems offer advantages such as fast response, environmental friendliness, and safety and reliability, demonstrating significant advantages in assisting thermal power, wind power, and photovoltaic power in frequency regulation. Due to the random fluctuations in wind power, energy storage does not regulate in a single direction when smoothing wind power output, placing higher demands on the number of charge-discharge cycles and the depth of charge-discharge. Flywheel energy storage boasts a cycle life nearly 100 times that of battery energy storage, and its depth of charge-discharge has almost no impact on its lifespan. Therefore, employing flywheel energy storage to smooth wind farm power fluctuations is a more reasonable choice.
[0004] CN103560542A discloses a method and apparatus for suppressing power fluctuations in wind turbine generators based on flywheel energy storage. It connects a flywheel energy storage device to the power output point of the wind turbine generator, and adjusts the flywheel angular velocity of the flywheel energy storage system to utilize the momentum increment of the flywheel energy storage device to regulate the power output of the wind turbine generator, thereby achieving peak shaving, valley filling, power smoothing, and stabilizing the output voltage. CN102738828B discloses a method for mitigating the uncertainty of large-scale wind power grid-connected power fluctuations using an integrated combined generation unit. This method decomposes the large-scale wind power grid-connected power fluctuations into a superposition of predictable and uncertain components; it uses an integrated combined generation unit to perform boundary estimation on the uncertain components in step one, achieving optimal matching between traditional power sources and wind power; it obtains the spectrum of the uncertain components and analyzes it, dividing the uncertain components into four parts: ultra-high frequency, high frequency, medium frequency, and low frequency; and it uses ultra-high frequency tracking and mitigation units, high frequency tracking and mitigation units, medium frequency tracking and mitigation units, and low frequency tracking and mitigation units respectively for tracking and mitigation; thus achieving the mitigation of the uncertainty of large-scale wind power grid-connected power fluctuations.
[0005] In terms of energy storage capacity configuration for mitigating wind farm power fluctuations, there are many hybrid energy storage capacity configuration strategies, but fewer studies on single energy storage systems. The rationality of energy storage capacity configuration is of great significance for mitigating wind power output, improving power quality, and ensuring the economic efficiency and security of power system operation. Therefore, the capacity configuration of flywheel energy storage systems for mitigating wind power fluctuations is an important topic. Summary of the Invention
[0006] To address the shortcomings and gaps in existing technologies in related fields, this invention provides a method for configuring the capacity of a flywheel energy storage system to mitigate wind power fluctuations connected to the grid. The objective of this invention is achieved through the following technical solution:
[0007] A method for configuring the capacity of a flywheel energy storage system to mitigate power fluctuations from wind power connected to the grid, comprising:
[0008] Step 1: Initialize the cutoff frequency of the grid frequency divider to obtain the reference power command for the flywheel energy storage system;
[0009] Step 2: Determine the rated power and rated capacity of the energy storage system based on the power and capacity constraints of the flywheel energy storage system and the economic indicators of the flywheel energy storage system throughout its entire life cycle;
[0010] Step 3: Use a multi-tracker optimization algorithm to solve the objective function for the capacity configuration of the flywheel energy storage system;
[0011] Step 4: Connect the flywheel energy storage system output to the active power output of the wind farm to obtain the grid connection point fluctuation parameters;
[0012] Step 5: Update the cutoff frequency of the grid frequency divider to determine the optimized value of the flywheel energy storage system power capacity required for this wind farm.
[0013] The frequency divider in step 1 is represented as follows:
[0014]
[0015] Among them, T s The time constant of the frequency divider is related to the cutoff frequency by f = 1 / 2πT. s The cutoff frequency is updated iteratively after initialization within a certain range.
[0016] Step 2 involves constructing the full lifecycle economic indicators for the flywheel energy storage system. From manufacturing to grid connection and recycling, the expenditures of the flywheel energy storage system include fixed investment costs, operation and maintenance costs, and recycling costs. The calculation methods for expenditures that significantly impact the economic performance of the flywheel energy storage system are as follows.
[0017] Fixed investment costs are:
[0018]
[0019] Among them, C e The cost per unit capacity of the flywheel energy storage unit is 10,000 yuan / (MW·h); C a The cost per unit capacity of flywheel energy storage auxiliary facilities, in ten thousand yuan / (MW·h); C p Cost per unit power of the power conversion device PCS, in ten thousand yuan / MW; E e η represents the rated capacity of the flywheel energy storage system; η represents the charge / discharge efficiency of the flywheel energy storage system.
[0020] The operating and maintenance costs are:
[0021]
[0022] Among them, C ope The fixed operating cost per unit power is 10,000 yuan / MW.
[0023] The calculation method for the discharge benefit of a flywheel energy storage system in smoothing the active power output of a wind farm is as follows:
[0024]
[0025] Among them, C c The current energy storage discharge rate is [amount] yuan / kW·h; Let t be the discharge power of the flywheel energy storage system at time t.
[0026] The rated power and rated capacity constraints of the flywheel energy storage system are as follows:
[0027]
[0028] Among them, P ref_fess P(t) represents the reference power of the flywheel energy storage system output by the energy storage management system at time t; SOC(t) represents the energy stored in the flywheel energy storage system at time t. e This refers to the rated power of the flywheel energy storage system.
[0029] The losses in a flywheel energy storage system increase with increasing flywheel speed, as described below:
[0030]
[0031] Among them, P loss (t) represents the power loss at time t; ω(t) represents the angular velocity at time t; c1 and c2 are the loss constants.
[0032] In step 3, a multi-tracker optimization algorithm is used to solve the objective function for capacity configuration of the flywheel energy storage system. The objective function for capacity configuration of the flywheel energy storage system is:
[0033]
[0034] Among them, P N This is the rated power of the wind farm.
[0035] When using a multi-tracker optimization algorithm to solve the objective function for capacity configuration of a flywheel energy storage system, the objective function values of each global tracker are sorted. In this example, level 1 is assigned to the global tracker G with the largest function value. T The highest level is assigned to the smallest G. T .
[0036] The definition of the grid connection point fluctuation parameter in step 4 is as follows:
[0037]
[0038] Where, ΔP i Let ΔP be the change in active power of the wind farm at 1 minute and 10 minutes in the i-th time period. limit_1min and ΔP limit_10min These are the active power variation limits for wind farms over 1 minute and 10 minutes. The 1-minute active power variation index for wind farms refers to the difference between the maximum and minimum active power of wind power within a 1-minute time window. The 10-minute active power change index for wind farms refers to the difference between the maximum and minimum active power of wind power within a 10-minute time window. N represents the number of times the active power of the wind farm exceeds the limit in 1 minute and 10 minutes, and λ is the ratio of the over-limit power used to judge the outer grid connection conditions. The value is zero when the grid connection conditions are met, and a penalty factor reflecting the power smoothness of the energy storage system when the conditions are not met.
[0039] In step 5, the cutoff frequency of the outer layer frequency divider is iteratively updated, and the objective function value for the optimized flywheel energy storage system capacity configuration under different cutoff frequencies is solved. This satisfies the outer layer grid connection conditions, and the power and capacity of the flywheel energy storage system corresponding to the optimized cutoff frequency value are globally optimized values.
[0040] This invention provides a method for determining the cutoff frequency and energy storage capacity of a wind farm power smoothing system by using a frequency divider to separate the active power of the wind farm and responding to high-frequency power commands through a flywheel energy storage system. This method uses the rated power and capacity of the energy storage system as constraints, considers the operating losses of the flywheel energy storage system, takes into account the economic indicators of the flywheel energy storage system throughout its entire life cycle, and uses a multi-tracker optimization algorithm to optimize the power and capacity of the flywheel energy storage system under the target of wind farm active power fluctuation grid connection conditions, thereby obtaining a globally optimized flywheel energy storage capacity configuration.
[0041] By adopting the method of this invention, both the cost of the equipment and the overall load fluctuation of the power grid are taken into account, thereby achieving cost reduction and user experience optimization under acceptable conditions. Attached Figure Description
[0042] Figure 1 This is a flowchart of the method of the present invention;
[0043] Figure 2 This is a diagram showing the flywheel energy storage system connected to a wind farm in an embodiment of the present invention;
[0044] Figure 3 This is a diagram showing the output results of the outer layer optimization model of the flywheel energy storage system in an embodiment of the present invention;
[0045] Figure 4 This is a diagram showing the output results of the inner layer optimization model of the flywheel energy storage system in an embodiment of the present invention;
[0046] Figure 5 This is a comparison diagram of the effect of flywheel energy storage on wind farm mitigation before and after in an embodiment of the present invention. Detailed Implementation
[0047] To make the objectives, technical solutions, and advantages of this invention clearer, the examples are described in detail below with reference to the accompanying drawings.
[0048] Reference Figure 1 A method for configuring the capacity of a flywheel energy storage system to mitigate wind power fluctuations connected to the grid includes the following steps:
[0049] (a) Initialize the frequency divider cutoff frequency to obtain the reference power command for the flywheel energy storage system. The frequency divider is represented as follows:
[0050]
[0051] Among them, T s The time constant of the frequency divider is related to the cutoff frequency by f = 1 / 2πT. s The cutoff frequency is updated iteratively after initialization within a certain range.
[0052] (II) Considering the power and capacity constraints of the flywheel energy storage system and the economic indicators of its entire life cycle, configure the rated power and rated capacity parameters to respond to the reference power command. The economic indicators of the flywheel energy storage system throughout its entire life cycle are constructed, including fixed investment costs, operation and maintenance costs, and recovery costs, from manufacturing to grid connection and recycling. The calculation methods for expenditures that significantly impact the economics of the flywheel energy storage system are as follows.
[0053] Fixed investment costs are:
[0054]
[0055] Among them, C e The cost per unit capacity of the flywheel energy storage unit is 10,000 yuan / (MW·h); C a The cost per unit capacity of flywheel energy storage auxiliary facilities, in ten thousand yuan / (MW·h); C p Cost per unit power of the power conversion device PCS, in ten thousand yuan / MW; E e η represents the rated capacity of the flywheel energy storage system; η represents the charge / discharge efficiency of the flywheel energy storage system.
[0056] The operating and maintenance costs are:
[0057]
[0058] Among them, C ope The fixed operating cost per unit power is 10,000 yuan / MW.
[0059] The calculation method for the discharge benefit of a flywheel energy storage system in smoothing the active power output of a wind farm is as follows:
[0060]
[0061] Among them, C c The current energy storage discharge rate is [amount] yuan / kW·h; Let t be the discharge power of the flywheel energy storage system at time t.
[0062] The rated power and rated capacity constraints of the flywheel energy storage system are as follows:
[0063]
[0064] Among them, P ref_fess P(t) represents the reference power of the flywheel energy storage system output by the energy storage management system at time t; SOC(t) represents the energy stored in the flywheel energy storage system at time t. e This refers to the rated power of the flywheel energy storage system.
[0065] The losses in a flywheel energy storage system increase with increasing flywheel speed, as described below:
[0066]
[0067] Among them, P loss (t) represents the power loss at time t; ω(t) represents the angular velocity at time t; c1 and c2 are the loss constants.
[0068] (III) A multi-tracker optimization algorithm is used to solve the objective function for the capacity configuration of the flywheel energy storage system to avoid getting trapped in local optimization. A multi-tracker optimization algorithm is used to solve the objective function for the capacity configuration of the flywheel energy storage system. The objective function for the capacity configuration of the flywheel energy storage system is:
[0069]
[0070] Among them, P N This is the rated power of the wind farm.
[0071] When using a multi-tracker optimization algorithm to solve the objective function for capacity configuration of a flywheel energy storage system, the objective function values of each global tracker are sorted. In this example, level 1 is assigned to the global tracker G with the largest function value. T The highest level is assigned to the smallest G. T .
[0072] (iv) Connect the flywheel energy storage system output to the wind farm's active power output and determine the grid connection point fluctuation parameters. The grid connection point fluctuation parameters are defined as follows:
[0073]
[0074] Where, ΔP i Let ΔP be the change in active power of the wind farm at 1 minute and 10 minutes in the i-th time period. limit_1min and ΔP limit_10min These are the active power variation limits for wind farms over 1 minute and 10 minutes. The 1-minute active power variation index for wind farms refers to the difference between the maximum and minimum active power of wind power within a 1-minute time window. The 10-minute active power change index for wind farms refers to the difference between the maximum and minimum active power of wind power within a 10-minute time window. N represents the number of times the active power of the wind farm exceeds the limit in 1 minute and 10 minutes, and λ is the ratio of the over-limit power used to judge the outer grid connection conditions. The value is zero when the grid connection conditions are met, and a penalty factor reflecting the power smoothness of the energy storage system when the conditions are not met.
[0075] (v) Update the cutoff frequency of the frequency divider to determine the optimized power capacity of the flywheel energy storage system required for this wind farm under the capacity configuration dual-layer optimization model. Iteratively update the cutoff frequency of the outer-layer frequency divider and solve for the objective function value of the optimized flywheel energy storage system capacity configuration under different cutoff frequencies. The outer-layer grid connection conditions are met, and the power and capacity of the flywheel energy storage system corresponding to the optimized cutoff frequency value are the global optimized values.
[0076] See the accompanying drawings for reference. Figure 1 This is a flowchart of the method of the present invention. (Attached) Figure 2 This is a diagram illustrating the connection of the flywheel energy storage system to a wind farm in an embodiment of the present invention; (Attached) Figure 2 The diagram illustrates the connection methods for the wind turbine, flywheel energy storage unit, and external power grid. (See attached diagram.) Figure 3 This is a diagram showing the output results of the outer layer optimization model of the flywheel energy storage system in this embodiment of the invention; (Attached) Figure 4 This is an output diagram of the inner-layer optimization model of the flywheel energy storage system in an embodiment of the present invention. The state of the wind turbine and flywheel energy storage can achieve a relatively optimized energy allocation, but this energy allocation may not be optimal for the power grid. For the power grid, it is necessary to suppress overall fluctuations. Figure 5 This is a comparison chart showing the effect of flywheel energy storage on wind farm mitigation before and after implementation in an embodiment of the present invention. From... Figure 5 As can be seen from the data, in the long term, power fluctuations are adjusted through the grid load. Using the method of this invention, short-term power fluctuations caused by the randomness of wind power can be effectively suppressed. Short-term fluctuations caused by the randomness of wind power have a significant impact on both the grid and users. This invention combines inner-layer optimization and outer-layer optimization. Guided by the outer-layer optimization objective, it suppresses large short-term power fluctuations, playing a crucial role in the safe and efficient operation of the grid.
[0077] Finally, it should be noted that the above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.
Claims
1. A method for configuring the capacity of a flywheel energy storage system to mitigate wind power fluctuations connected to the grid, characterized in that, include: Step 1: Initialize the cutoff frequency of the grid frequency divider to obtain the reference power command for the flywheel energy storage system; Step 2: Determine the rated power and rated capacity of the flywheel energy storage system based on its power and capacity constraints, as well as its economic indicators throughout its entire lifecycle. The formulas for obtaining the rated power and rated capacity of the flywheel energy storage system itself in Step 2 are as follows: ， Among them, P ref_fess (t) represents the reference power of the flywheel energy storage system output by the energy storage management system at time t; SOC(t) represents the energy stored in the flywheel energy storage system at time t; Pe represents the rated power of the flywheel energy storage system. Step 3: Use a multi-tracker optimization algorithm to solve the objective function for the capacity configuration of the flywheel energy storage system; The objective function is: ， Among them, P N This refers to the rated power of the wind farm. Step 4: Connect the flywheel energy storage system output to the active power output of the wind farm to obtain the grid connection point fluctuation parameters; the grid connection point fluctuation parameters in Step 4 are defined as follows: ， Where, ΔP i Let ΔP be the change in active power of the wind farm at 1 minute and 10 minutes in the i-th time period. limit_1min and ΔP limit_10min The limits for active power variation in wind farms over 1 minute and 10 minutes are set. The active power change index of a wind farm in 1 minute refers to the difference between the maximum and minimum active power of wind power within a time window of 1 minute. λ is the active power change index of a wind farm over 10 minutes, which refers to the difference between the maximum and minimum active power of wind power within a time window of 10 minutes; N is the number of times the active power change of the wind farm exceeds the limit in 1 minute and 10 minutes; λ is the ratio of the power exceeding the limit. Step 5: Update the cutoff frequency of the grid frequency divider to determine the optimized value of the flywheel energy storage system power capacity required for this wind farm.
2. The method for configuring the capacity of a flywheel energy storage system to mitigate wind power fluctuations connected to the grid, as described in claim 1, is characterized in that... In step 3, the multi-tracker optimization algorithm sorts the objective function values of each global tracker, assigns level 1 to the global tracker GT with the largest function value, and assigns the highest level to the GT with the smallest function value.
3. The flywheel energy storage system capacity configuration method for smoothing wind power fluctuations connected to the grid according to claim 1, characterized in that, The method for solving the optimized value of the flywheel energy storage system power capacity in step 5 is to iteratively update the cutoff frequency of the outer layer frequency divider and solve the objective function value of the optimized flywheel energy storage system capacity configuration under different cutoff frequencies. The external grid connection conditions are met, and the power and capacity of the flywheel energy storage system corresponding to the optimized cutoff frequency value are the global optimized values.