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CN-120879683-B - Hybrid energy storage platform capacity configuration system in micro-grid

CN120879683BCN 120879683 BCN120879683 BCN 120879683BCN-120879683-B

Abstract

The invention relates to a capacity configuration system of a hybrid energy storage platform in a micro-grid, belonging to the field of power system planning and design, and comprising a power demand subdivision module, a cost modeling module, a collaborative optimization configuration module and a collaborative optimization configuration module, wherein the power demand subdivision module is used for decomposing an acquired net load power time sequence into a high-frequency power component and a low-frequency energy component based on a preset energy storage type demarcation frequency, the cost modeling module is used for determining the annual aging cost of a super capacitor based on the high-frequency power component and determining the annual aging cost of a battery based on the low-frequency energy component, the annual aging cost of the battery comprises stress additional cost related to the power change rate of the low-frequency energy component, and the collaborative optimization configuration module is used for combining the annual aging cost of the super capacitor and the annual aging cost of the battery determined by the cost modeling module and a preset initial investment cost.

Inventors

  • WANG YIQUAN

Assignees

  • 三峡大学

Dates

Publication Date
20260512
Application Date
20250718

Claims (8)

  1. 1. The capacity configuration system of the hybrid energy storage platform in the micro-grid is characterized by comprising a power demand splitting module, a power demand splitting module and a power supply module, wherein the power demand splitting module is used for decomposing an acquired time sequence of the net load power into a high-frequency power component and a low-frequency energy component based on a preset energy storage type demarcation frequency; The system comprises a cost modeling module, a battery, a low-frequency energy component, a power supply module and a power supply module, wherein the cost modeling module is used for determining the annual ageing cost of the super capacitor based on the high-frequency power component and determining the annual ageing cost of the battery based on the low-frequency energy component; The collaborative optimization configuration module is used for combining the annual aging cost of the super capacitor and the annual aging cost of the battery, which are determined by the cost modeling module, and the preset initial investment cost, and solving the optimal capacity configuration of the super capacitor and the battery by taking the total cost of the whole life cycle of the system as a target; the parameter feedback correction module is used for dynamically correcting the power stress time constant in the cost modeling module based on the deviation between the actual health state and the predicted health state of the battery; The power stress time constant inverse solution process includes: establishing a formula I: ; in the calibration experiment, the reference group and the experiment group reach the charge-discharge power curve corresponding to the same life attenuation degree And And respective total operating time And Are measured values, and thus, the total energy throughput of the two groups And (3) with Are known and are generally not equal, due to the fact that the cost equation is other than Other parameters than are known or measurable, so that the power stress time constant can be uniquely inversely solved from the equation Is a value of (2); the cost modeling module is used for determining the annual aging cost of the battery, abandoning the traditional linear cost model, establishing a nonlinear aging cost model capable of quantifying the additional damage caused by power fluctuation, and establishing a formula II: ; in the first and second formulas, Total aging cost of the battery over an annual period; Is an annual cycle; Is the basic cost of unit energy throughput, and the unit is yuan/kWh; The low-frequency energy component is output by the power demand splitting module, and the unit kW is the unit; Representing the absolute value of the charge and discharge, and ensuring that the charge and discharge are both counted into the cost; is the rate of change of power, in kW/h; The power change rate is a standard reference of the rated power of the battery to be optimized, the rated power of the battery is unit kW; Is a power stress time constant, and the unit is the square of time ) Is a key physical quantity for representing the sensitivity of the battery to power fluctuation, and in order to ensure the mathematical rigor of the model, Is set as the dimension of So that The method is a dimensionless item, the dimensionality of the whole integral item is ensured to be a primary element/hour, and the dimensionality of the final integral result is ensured to be a primary element; The duration of the reference group experiment refers to the preset life attenuation degree of the reference group battery; a smooth charge-discharge power curve adopted by a reference group experiment; The charge-discharge power curve containing severe fluctuation is adopted in experiments of an experimental group; The duration of the experiment in the experimental group refers to the time taken for the experimental group cells to reach the same degree of life decay as the baseline group.
  2. 2. The hybrid energy storage platform capacity allocation system according to claim 1, wherein the power demand splitting module is specifically configured to: processing the time sequence of the payload power by wavelet packet transformation; The high frequency power component and the low frequency energy component are separated from the payload power time series based on the energy storage type demarcation frequency.
  3. 3. The capacity allocation system of the hybrid energy storage platform in the micro-grid according to claim 2, wherein the energy storage type demarcation frequency is determined by performing physical experiment calibration on a target battery, and the energy storage type demarcation frequency is a power change frequency corresponding to a non-linear increase inflection point of a life decay rate of the battery in a cyclic charge and discharge experiment.
  4. 4. The hybrid energy storage platform capacity allocation system according to claim 1, wherein the cost modeling module, when determining the annual aging cost of the battery, is specifically configured to: determining an annual ageing cost by accumulating instantaneous ageing costs over an annual period; The instantaneous aging cost is proportional to the absolute value of the low frequency energy component and the unit energy throughput cost is corrected by a dynamic stress factor related to the square of the power rate of change of the low frequency energy component.
  5. 5. The capacity allocation system of a hybrid energy storage platform in a micro-grid according to claim 4, wherein the power stress time constant in the dynamic stress factor is calibrated by a physical experiment, and the calibration method comprises: Performing a benchmark set experiment and an experimental set experiment on the target battery, wherein the benchmark set adopts a smooth charge-discharge curve, and the experimental set adopts a charge-discharge curve containing severe fluctuation; and solving the power stress time constant based on the cost difference when the two groups of experiments reach the same life attenuation degree.
  6. 6. The hybrid energy storage platform capacity allocation system according to claim 1, wherein the objective function of the collaborative optimization allocation module comprises: the initial investment cost is calculated according to the optimal capacity configuration to be solved and the preset unit capacity investment cost; Full life cycle running costs, the sum of discount values calculated based on a preset discount rate for the annual ageing costs of all years in the future.
  7. 7. The hybrid energy storage platform capacity allocation system in a micro grid according to claim 1, wherein the constraint conditions of the collaborative optimization allocation module comprise: A power balance constraint requiring that the sum of the output power of the supercapacitor and the battery is not less than the instantaneous value of the payload power time series; Physical constraints require that the operating power of the supercapacitor and the battery not exceed the respective rated powers, and that the rated power of the battery is associated with the product of the energy capacity and the rated charge-discharge rate.
  8. 8. The capacity configuration system of a hybrid energy storage platform in a micro grid according to claim 1, wherein the parameter feedback correction module is specifically configured to: acquiring the actual health state of the battery, and calculating the predicted health state based on the optimal capacity configuration and the actual running power data output by the collaborative optimal configuration module; determining a deviation between the actual health state and the predicted health state; and updating the power stress time constant by using the deviation by adopting a proportional-integral controller for optimizing or expanding the capacity planning of the next period.

Description

Hybrid energy storage platform capacity configuration system in micro-grid Technical Field The invention relates to the field of planning and design of power systems, in particular to a capacity configuration system of a hybrid energy storage platform in a micro-grid. Background The stable running of the micro-grid is highly dependent on the energy storage system, the hybrid energy storage system aims to combine the advantages of different energy storage technologies, but the existing capacity configuration method generally treats the process as a static optimization problem, and the method meets peak demands by setting sufficient capacity redundancy, but ignores the nonlinear and asymmetric effects of load power dynamic characteristics on the service life of the energy storage unit. Specifically, if the energy-type energy storage unit such as a lithium battery is frequently subjected to high-frequency and high-amplitude power impact outside the design range, irreversible internal damage can be caused, accelerated attenuation of capacity and service life is caused, the phenomenon forms a vicious circle of power impact-accelerated aging-capacity attenuation, the conventional static configuration method cannot identify and avoid the degradation coupling effect of the time scale, and the cost of the whole life cycle of the configured system is far beyond expectation, so that the reliability is reduced. The above information disclosed in the above background section is only for enhancement of understanding of the background of the disclosure and therefore it may include information that does not form the prior art that is already known to those of ordinary skill in the art. Disclosure of Invention The invention aims to provide a capacity configuration system of a hybrid energy storage platform in a micro-grid, so as to solve the problems in the background technology. The technical scheme of the invention comprises a power demand splitting module, a power demand splitting module and a power generation module, wherein the power demand splitting module is used for decomposing an acquired time sequence of net load power into a high-frequency power component and a low-frequency energy component based on a preset energy storage type demarcation frequency; The system comprises a cost modeling module, a battery, a low-frequency energy component, a power supply module and a power supply module, wherein the cost modeling module is used for determining the annual ageing cost of the super capacitor based on the high-frequency power component and determining the annual ageing cost of the battery based on the low-frequency energy component; The collaborative optimization configuration module is used for combining the annual aging cost of the super capacitor and the annual aging cost of the battery, which are determined by the cost modeling module, and the preset initial investment cost, and solving the optimal capacity configuration of the super capacitor and the battery by taking the total cost of the whole life cycle of the system as a target; And the parameter feedback correction module is used for dynamically correcting the power stress time constant in the cost modeling module based on the deviation between the actual health state and the predicted health state of the battery. Preferably, the power demand splitting module is specifically configured to: processing the time sequence of the payload power by wavelet packet transformation; The high frequency power component and the low frequency energy component are separated from the payload power time series based on the energy storage type demarcation frequency. Preferably, the energy storage type demarcation frequency is determined by carrying out physical experiment calibration on the target battery, and is the power change frequency corresponding to the nonlinear increase inflection point of the service life decay rate of the battery in the cyclic charge and discharge experiment. Preferably, the cost modeling module, when determining the annual ageing cost of the battery, is specifically configured to: determining an annual ageing cost by accumulating instantaneous ageing costs over an annual period; The instantaneous aging cost is proportional to the absolute value of the low frequency energy component and the unit energy throughput cost is corrected by a dynamic stress factor related to the square of the power rate of change of the low frequency energy component. Preferably, the power stress time constant in the dynamic stress factor is calibrated through a physical experiment, and the calibration method comprises the following steps: Performing a benchmark set experiment and an experimental set experiment on the target battery, wherein the benchmark set adopts a smooth charge-discharge curve, and the experimental set adopts a charge-discharge curve containing severe fluctuation; and solving the power stress time constant based on the cost difference when the two gro