A micro-grid island operation energy optimization scheduling and frequency stability control method

Abstract

The present application relates to the technical field of data processing, and especially relates to a micro-grid island operation energy optimization scheduling and frequency stability control method, which obtains optimal power generation of each distributed power supply at a future time by using an MPC algorithm during island operation of a target micro-grid; evaluates a power imbalance index of the target micro-grid according to a difference between actual power generation of each distributed power supply and power consumption of each load node within a neighborhood time range of a current time; obtains compensation power of optimal power generation of each distributed power supply at the future time according to an influence of a difference between actual power generation of each distributed power supply and scheduling power on voltage frequency and the power imbalance index; and realizes energy optimization scheduling and frequency stability control of the target micro-grid in an island operation state according to the optimal power generation of each distributed power supply at the future time and the compensation power, thereby improving island operation stability and robustness of the micro-grid.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method for energy optimization scheduling and frequency stability control in islanded microgrid operation. Background Technology

[0002] With the large-scale integration of distributed power sources (such as photovoltaic and wind power) and energy storage systems into distribution networks, microgrids are switching between grid-connected and islanded operation more and more frequently. When a microgrid is in islanded operation, the lack of power and frequency support from the main grid can easily lead to instantaneous power imbalances between the system's power generation and load demand, resulting in frequency fluctuations or even instability. Simultaneously, distributed power output exhibits randomness and volatility, and load demand also shows uncertain changes. Currently, based on the predicted output of distributed power sources and load demand, optimization algorithms are typically used to calculate the power allocation of each power source and energy storage device. Power output is then adjusted through droop control or energy storage compensation based on real-time detected system frequency deviations to maintain power balance and achieve frequency stability.

[0003] Traditionally, Model Predictive Control (MPC) algorithms are used for upper-level energy optimization scheduling, with the scheduling results serving as the reference power for lower-level frequency control. However, microgrid islanded systems have low inertia. When there are rapid disturbances in the actual load or distributed generation output, power imbalances can cause rapid frequency changes in a very short time. MPC performs rolling optimization based on predicted load and operating constraints, outputting the optimal power allocation result within a time interval. Its calculation and execution have a certain delay, making it difficult to respond to instantaneous power imbalances caused by sudden load changes and rapid fluctuations in distributed generation. This results in upper-level scheduling being unable to correct power allocation in a timely manner, and lower-level frequency control still requiring significant dynamic compensation. Consequently, this leads to frequent adjustments in the energy storage system, power oscillations, and decreased frequency stability.

[0004] Therefore, how to quickly stabilize the frequency while achieving optimized energy scheduling in microgrid islands has become an urgent problem to be solved. Summary of the Invention

[0005] In view of this, embodiments of the present invention provide a method for energy optimization scheduling and frequency stability control in microgrid islanded operation, so as to solve the problem of quickly stabilizing the frequency while achieving energy optimization scheduling in microgrid islanded operation.

[0006] This invention provides a method for energy optimization scheduling and frequency stability control in islanded microgrid operation, the method comprising the following steps:

[0007] During the islanded operation of the target microgrid, the voltage frequency of the target microgrid, the actual power generation of each distributed power source, and the power consumption of each load node are obtained at each time point within the preset time period up to the current time. The optimal power generation of each distributed power source in the future time is obtained using the MPC algorithm.

[0008] Based on the difference between the actual power generation of each distributed power source and the power consumption of each load node within the neighborhood time range at the current moment, the power imbalance index of the target microgrid at the current moment is evaluated.

[0009] For any distributed power source, obtain the dispatch power of the distributed power source within the preset time period. Based on the impact of the difference between the actual power generation and dispatch power of the distributed power source within the preset time period on the voltage frequency, and the power imbalance index of the target microgrid at the current moment, obtain the compensation power of the optimal power generation of the distributed power source at the future moment.

[0010] Based on the optimal power generation and compensation power of any distributed power source at a future time, the final power generation of any distributed power source at a future time is obtained. Based on the final power generation of each distributed power source in the target microgrid at a future time, the energy optimization scheduling and frequency stability control of the target microgrid in islanded operation mode are realized.

[0011] Preferably, the step of evaluating the power imbalance index of the target microgrid at the current moment based on the difference between the actual power generation of each distributed power source and the power consumption of each load node within the neighborhood time range at the current moment includes:

[0012] The current time and a preset number of times before the current time are combined into a neighborhood time period. For any time within the neighborhood time period, the absolute value of the difference between the total actual power generation of all distributed power sources in the target microgrid and the total power consumption of all load nodes is calculated to obtain the power imbalance degree at any time.

[0013] Obtain the power imbalance degree of the previous time at any given time, calculate the absolute value of the difference between the power imbalance degree of any given time and the previous time, obtain the degree of imbalance change at any given time, calculate the product between the power imbalance degree at any given time and the degree of imbalance change, and obtain the imbalance characteristic value at any given time.

[0014] Obtain the imbalance characteristic value at each time point within the neighborhood time period of the current time, calculate the mean of the imbalance characteristic values ​​at all times within the neighborhood time period of the current time, and obtain the power imbalance index of the target microgrid at the current time.

[0015] Preferably, the step of obtaining the compensation power for the optimal power generation of any distributed power source in the future time period based on the impact of the difference between the actual power generation and the dispatched power of any distributed power source during the preset time period on the voltage frequency, and the power imbalance index of the target microgrid at the current moment, includes:

[0016] The current time and a preset number of times before the current time are combined to form the neighborhood time period of the current time. Based on the difference between the actual power generation and the dispatch power of any distributed power source in the neighborhood time period of the current time, the output dispatch capability index of any distributed power source at the current time is obtained.

[0017] Based on the difference between the output scheduling capability index of any distributed power source at the current moment and the power imbalance index of the target microgrid at the current moment, the frequency regulation risk index of any distributed power source at the current moment is obtained.

[0018] Obtain the output scheduling capability index of any distributed power source at each moment within a preset time period up to the current moment, and based on the impact of the output scheduling capability index of any distributed power source at each moment within the preset time period up to the current moment on the voltage frequency, obtain the disturbance impact index of any distributed power source on the voltage frequency at the current moment.

[0019] Calculate the product between the frequency regulation risk index and the disturbance impact index to obtain the compensation factor for the optimal power generation of any distributed power source at a future time.

[0020] Calculate the product between the actual power generation of any distributed power source at the current moment and the compensation factor to obtain the compensation power for obtaining the optimal power generation of any distributed power source at a future moment.

[0021] Preferably, obtaining the output dispatch capability index of any distributed power source at the current moment based on the difference between the actual power generation and the dispatched power of any distributed power source in the neighborhood time period at the current moment includes:

[0022] For any time within the neighborhood time period of the current time, calculate the absolute value of the difference between the actual power generation and the dispatched power of any distributed power source at any time, obtain the range of the actual power generation of any distributed power source within the neighborhood time period of the current time, calculate the product between the absolute value of the difference and the range, and obtain the degree of power generation output fluctuation of any distributed power source at any time.

[0023] The power generation output fluctuation of any distributed power source at each time point in the neighborhood of the current time is obtained, the mean of all power generation output fluctuations is calculated, and the negative of the mean is used as the independent variable of the natural exponential function to obtain the output scheduling capability index of any distributed power source at the current time.

[0024] Preferably, obtaining the frequency regulation risk index of any distributed power source at the current moment based on the difference between the output scheduling capability index of any distributed power source at the current moment and the power imbalance index of the target microgrid at the current moment includes:

[0025] The frequency regulation risk index of any distributed power source at the current moment is obtained by normalizing the power imbalance index of the target microgrid at the current moment by subtracting the output scheduling capability index of any distributed power source at the current moment.

[0026] Preferably, the step of obtaining the disturbance impact index of any distributed power source on the voltage frequency at the current moment based on the impact of the output scheduling capability index of any distributed power source on the voltage frequency at each moment within a preset time period up to the current moment includes:

[0027] For any distributed power source at any time within a preset time period up to the current time, the negative of the output scheduling capability index is used as the independent variable of the natural exponential function to obtain the power fluctuation degree of any distributed power source at any time.

[0028] The power fluctuation level of any distributed power source at each moment within a preset time period up to the current moment is obtained to obtain a power fluctuation level data sequence. The standard voltage frequency is obtained, and the absolute value of the difference between the voltage frequency at each moment within the preset time period and the standard voltage frequency is calculated to obtain a frequency difference sequence.

[0029] Calculate the DTW distance between the power fluctuation data sequence and the frequency difference sequence, and use the negative of the DTW distance as the independent variable of the natural exponential function to obtain the disturbance impact index of the voltage and frequency of any distributed power source at the current moment.

[0030] Preferably, obtaining the final power generation of any distributed power source at a future time based on its optimal power generation and compensation power at a future time includes:

[0031] The sum of the optimal power generation of any distributed power source in the future time and the compensation power is calculated to obtain the final power generation of any distributed power source in the future time.

[0032] The beneficial effects of the embodiments of the present invention compared with the prior art are as follows:

[0033] This invention first assesses the power imbalance index of the target microgrid at the current moment based on the difference between the actual power generation of each distributed power source and the power consumption of each load node within the neighborhood time range. This assessment helps to identify the output change trends of loads and distributed power sources in advance, providing a benchmark for subsequent power compensation and improving the pertinence and dynamism of scheduling decisions. Then, by analyzing the impact of distributed power source output fluctuations on voltage and frequency disturbances, and the power imbalance index of the target microgrid at the current moment, the invention accurately calculates the reserved frequency regulation capacity of each distributed power source—that is, the compensation power for the optimal power generation of each distributed power source in the future. This ensures that energy storage and adjustable power sources retain necessary frequency regulation space during the scheduling phase, enhancing the system's ability to absorb sudden power fluctuations. Finally, based on the optimal power generation and compensation power of each distributed power source in the future, the invention achieves optimized energy scheduling and rapid frequency stabilization. This ensures the economic rationality of power allocation while reducing frequency offset and frequent energy storage adjustments, enabling microgrid islands to achieve rapid frequency stabilization while optimizing energy scheduling. Attached Figure Description

[0034] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 This is a flowchart of a microgrid islanding operation energy optimization scheduling and frequency stability control method provided in Embodiment 1 of the present invention. Detailed Implementation

[0036] Embodiments of this disclosure are described in detail below, with examples of these embodiments illustrated in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this disclosure, and should not be construed as limiting it.

[0037] It should be noted that the terms "first," "second," etc., used in this disclosure and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure.

[0038] To illustrate the technical solution of the present invention, specific embodiments are described below.

[0039] See Figure 1 This is a flowchart of a method for energy optimization scheduling and frequency stability control in islanded microgrid operation, as provided in Embodiment 1 of the present invention. Figure 1 As shown, the method may include:

[0040] Step S101: During the islanded operation of the target microgrid, obtain the voltage frequency of the target microgrid, the actual power generation of each distributed power source, and the power consumption of each load node at each time point within the preset time period up to the current time. Then, use the MPC algorithm to obtain the optimal power generation of each distributed power source at future time points.

[0041] Designated as the target microgrid, during islanded operation, real-time data is collected on the power generation side of the target microgrid at a sampling frequency of 100Hz. This includes the power output data of each distributed power source, such as photovoltaic power, wind power, and adjustable power sources (e.g., diesel engines, gas turbines). Simultaneously, load-side power consumption data is collected. This is achieved by using smart meters or power measurement devices configured at each load node or common bus of the target microgrid to collect three-phase voltage and current signals in real time, and obtaining the instantaneous power consumption of each load node according to the active power calculation formula. To achieve frequency stability control of the target microgrid in islanded mode, the frequency of the target microgrid's bus voltage also needs to be collected. The collected data is then normalized to obtain the voltage frequency, the actual power output of each distributed power source, and the power consumption of each load node at each moment within the 24-hour period up to the current time. The sampling frequency is not limited and can be set by the implementer according to the specific scenario.

[0042] In islanded microgrid operation, due to the system's isolation from the main grid, its inertia level is low, and power balance relies entirely on local energy supply. Upper-level energy optimization scheduling is typically based on Model Predictive Control (MPC) algorithms. This involves obtaining future load forecasts, output forecasts for each distributed power source, and electricity price signals (if participating in the market) based on the current state of the target microgrid (state of charge, actual output of each distributed power source, bus voltage, frequency, load power, etc.), and rolling forecasts of power evolution over a finite future time domain. Subsequently, an optimization problem is constructed with the objective functions of minimizing operating costs, power deviation, and constraint violations. This problem is then solved under conditions of power balance, equipment output range, and ramp-up constraints to obtain the optimal power allocation in the future time domain. The results of this type of optimization are primarily average optimal solutions over a time scale, making it difficult to respond promptly to power imbalances caused by sudden load changes or instantaneous fluctuations in distributed power source output. When a sudden disturbance occurs in a distributed power source, the imbalance between power generation and consumption is quickly reflected as a shift or even oscillation in bus voltage and frequency. Upper-level optimization, limited by computation cycles and execution delays, cannot correct power allocation in real time.

[0043] Therefore, in this embodiment of the invention, the optimal power generation of each distributed power source in the future is first obtained using the MPC algorithm, which is also the dispatch power in the future. Then, by predicting disturbances in the power generation and consumption balance relationship, and analyzing the rapid adjustment capability of each distributed power source and the impact of the output fluctuation intensity of each distributed power source on the system frequency, the optimal power generation of each distributed power source in the future is corrected. This allows the dispatch result to absorb power fluctuations, thereby enabling rapid power compensation when a momentary power imbalance occurs in the target microgrid, suppressing frequency oscillations and maintaining frequency stability, and achieving synergistic optimization of energy optimization dispatch and dynamic frequency stabilization control. The use of the MPC algorithm to obtain the optimal power generation in the future is existing technology and will not be elaborated upon here.

[0044] Step S102: Based on the difference between the actual power generation of each distributed power source and the power consumption of each load node within the neighborhood time range at the current moment, evaluate the power imbalance index of the target microgrid at the current moment.

[0045] During islanded operation of a microgrid, the system cannot exchange power with the external grid and must rely on local renewable energy, energy storage, and adjustable power sources to meet electricity demand. Therefore, power generation capacity and load demand are constantly in a dynamic matching state. When electricity demand increases or power output fluctuates, if the generation side cannot keep up, the power balance will be disrupted, resulting in system frequency shift. Therefore, in this embodiment of the invention, the power imbalance index of the target microgrid at the current moment is obtained based on the difference between the actual power generation of each distributed power source and the power consumption of each load node within the neighborhood time range. This index characterizes the overall matching degree between power generation and consumption of the target microgrid at the current moment. Based on the concept of continuous prediction, the power imbalance index of the target microgrid at the current moment represents the balance between power generation and consumption in future moments, thus providing a benchmark for subsequent power compensation and improving the pertinence and dynamism of scheduling decisions.

[0046] To accurately reflect the intensity and development direction of the power imbalance of the target microgrid at the current moment, this embodiment of the invention comprehensively analyzes the degree of power imbalance change in the neighborhood at the current moment. While suppressing the influence of single-point noise, it identifies the dynamic trend of power balance change, thereby accurately determining the power balance relationship of the target microgrid islands at the current moment and obtaining the power imbalance index of the target microgrid at the current moment. This also improves the accuracy of using the power imbalance index at the current moment to characterize the balance between power generation and consumption at future moments. The method for obtaining the power imbalance index of the target microgrid at the current moment is as follows:

[0047] By performing sliding statistical analysis on historical power imbalance data (the difference between the total power generated by the generator and the total power consumed by the load), it can be seen that the power imbalance data has a significant temporal correlation in a short period of time. Its influence is mainly concentrated within five adjacent sampling points. When the time lag exceeds a certain range, the correlation decays rapidly and tends to stabilize. Further increasing the historical length significantly weakens the improvement in statistical stability, while the sensitivity to sudden changes decreases accordingly. Therefore, the current moment and the four moments before the current moment are combined into the neighborhood time period of the current moment to characterize the power imbalance state of the target microgrid at the current moment. There are no restrictions here, and implementers can set it according to the specific scenario.

[0048] For any time within the neighborhood time period, calculate the absolute value of the difference between the total actual power generation of all distributed power sources in the target microgrid and the total power consumption of all load nodes at that time, and obtain the power imbalance degree at that time.

[0049] Obtain the power imbalance degree of the previous time at any given time, calculate the absolute value of the difference between the power imbalance degree of any given time and the previous time, obtain the degree of imbalance change at any given time, calculate the product between the power imbalance degree at any given time and the degree of imbalance change, and obtain the imbalance characteristic value at any given time.

[0050] Obtain the imbalance characteristic value at each time point within the neighborhood time period of the current time, calculate the mean of the imbalance characteristic values ​​at all times within the neighborhood time period of the current time, and obtain the power imbalance index of the target microgrid at the current time.

[0051] In one embodiment, the formula for calculating the power imbalance index of the target microgrid at the current moment is:

[0052]

[0053] In the formula, The value represents the power imbalance index of the target microgrid at the current moment, and R represents the number of moments in the neighborhood of the current moment. In this embodiment of the invention, R=5. This represents the absolute value of the difference between the total actual power generation of all distributed power sources in the target microgrid and the total power consumption of all load nodes at the previous time corresponding to the r-th time in the 24-hour period up to the current time. It is also the power imbalance degree at the previous time corresponding to the r-th time. This represents the power imbalance at the r-th time interval within the neighborhood of the current time interval. Represents the absolute value symbol.

[0054] It should be noted that, The larger the value, the greater the difference between the total power generation and total power consumption of the target microgrid within the current neighborhood time period. This indicates a decrease in the matching degree between the power generation capacity and power demand of the target microgrid, and a greater likelihood that the system is in a fluctuating or unbalanced state at the current moment. The larger; The larger the value, the more drastic the change in power imbalance between adjacent moments. This increases the likelihood of unstable electricity demand or fluctuating power output within the current neighborhood, leading to a decreased match between the target microgrid's generation capacity and demand. Consequently, the system is more likely to be in a fluctuating or unbalanced state at the current moment. The larger.

[0055] Thus, the power imbalance index of the target microgrid at the current moment is obtained.

[0056] Step S103: For any distributed power source, obtain the dispatch power of the distributed power source within the preset time period. Based on the impact of the difference between the actual power generation and dispatch power of the distributed power source within the preset time period on the voltage frequency, and the power imbalance index of the target microgrid at the current moment, obtain the compensation power of the optimal power generation of the distributed power source at the future moment.

[0057] The power imbalance index obtained from the above steps can only reflect the deviation between power generation and consumption of the target microgrid at the current moment. However, due to the influence of environmental factors and their own conditions, the output of different distributed power sources has different adjustment capabilities, and the degree of impact on voltage and frequency during power imbalance is also different. For example, photovoltaic and wind power are greatly affected by the environment, and their output fluctuates rapidly and uncontrollably. When their power changes, they are more likely to cause an imbalance between power generation and power consumption, thus leading to frequency fluctuations. On the other hand, energy storage or adjustable power sources have fast response speed and strong controllability, and can quickly compensate when power is insufficient, thus playing a supporting role in frequency stability. Therefore, after obtaining the power imbalance index of the target microgrid at the current moment, it is necessary to further reserve different frequency regulation capacities for different distributed power sources based on their regulation capabilities and the degree of influence on voltage and frequency. This will yield the compensation power for the optimal power generation of the i-th distributed power source in the future, and then correct the optimal power generation of each distributed power source obtained by the MPC algorithm in the future (i.e., the scheduling power in the future) to obtain the final power generation of each distributed power source. This power output will then be used to improve the system frequency stability while achieving optimized energy allocation.

[0058] Taking the i-th distributed power source as an example, the method for obtaining the compensation power of the optimal power generation of the i-th distributed power source in the future is as follows:

[0059] (1) Based on the difference between the actual power generation and the dispatch power of the i-th distributed power source in the neighborhood time period at the current time, obtain the output dispatch capability index of the i-th distributed power source at the current time to reflect its regulation capability.

[0060] Because the actual output of different distributed power sources in a microgrid is often difficult to execute exactly according to the optimized scheduling results due to the influence of resource conditions and equipment response characteristics, and the degree of fluctuation in actual output directly affects its ability to support power balance and frequency stability, the output scheduling capability index of the i-th distributed power source at the current moment can be obtained based on the difference between the actual power generation and the dispatched power of the i-th distributed power source in the neighborhood time period (the time period consisting of the current moment and the four time periods before the current moment). Specifically:

[0061] In the microgrid energy management system (EMS) of the target microgrid, the dispatch power of each distributed power source at each time point within the 24 hours up to the current time is obtained (i.e., the optimal power generation obtained by the MPC algorithm in the traditional way, and the power data after normalization). For any time point in the neighborhood of the current time, the absolute value of the difference between the actual power generation of the i-th distributed power source and the dispatch power at that time point is calculated. The range of the actual power generation of the i-th distributed power source in the neighborhood of the current time point is obtained. The product between the absolute value of the difference and the range is calculated to obtain the power generation output fluctuation of the i-th distributed power source at that time point.

[0062] Obtain the power generation output fluctuation of the i-th distributed power source at each time point in the neighborhood of the current time, calculate the mean of all power generation output fluctuations, and use the negative of the mean as the independent variable of the natural exponential function to obtain the output scheduling capability index of the i-th distributed power source at the current time.

[0063] In one embodiment, the formula for calculating the output scheduling capability index of the i-th distributed power source at the current moment is:

[0064]

[0065] In the formula, Let R represent the output scheduling capability index of the i-th distributed power source at the current moment, and let R represent the number of moments in the neighborhood time period of the current moment. In this embodiment of the invention, R=5. Let represent the scheduling power of the i-th distributed power source at the r-th time interval within the neighborhood of the current time interval. Let represent the actual power generation of the i-th distributed power source at the r-th time within the neighborhood time period of the current time. This represents the range of the actual power generation of the i-th distributed power source within the neighborhood time period at the current moment. This represents the natural exponential function. Represents the absolute value symbol.

[0066] It should be noted that, The larger the value, the greater the deviation between the dispatched power and the actual generated power of the i-th distributed power source. This indicates a poorer ability of the i-th distributed power source to follow dispatch instructions, and a weaker regulation capability. The smaller; The larger the value, the more unstable the power output of the i-th distributed power source, and the weaker its regulation capability. The smaller.

[0067] (2) Based on the difference between the output scheduling capability index of the i-th distributed power source at the current time and the power imbalance index of the target microgrid at the current time, obtain the frequency regulation risk index of the i-th distributed power source at the current time.

[0068] The power imbalance index of the target microgrid obtained in step S102 reflects the overall power imbalance intensity. When the power imbalance intensity is large and the regulation capability of the i-th distributed power source is insufficient, the i-th distributed power source will have difficulty compensating for the power imbalance in time, which is prone to causing bus voltage and frequency fluctuations. In this case, more frequency regulation capacity should be reserved, that is, more power compensation should be given to the i-th distributed power source to ensure frequency stability. When the difference between the imbalance power intensity and the regulation capability of the i-th distributed power source is small, or when the power imbalance intensity is small and the regulation capability is strong, it indicates that the i-th distributed power source can respond to the power imbalance in time and can ensure frequency stability. In this case, less frequency regulation capacity should be reserved, that is, less power compensation should be given to the i-th distributed power source. Therefore, based on the difference between the output dispatch capability index of the i-th distributed power source at the current moment and the power imbalance index of the target microgrid at the current moment, the frequency regulation risk index of the i-th distributed power source at the current moment can be obtained to reflect whether the regulation capability of the i-th distributed power source at the current moment can respond to the power imbalance in time, providing a benchmark for subsequent power compensation. Specifically:

[0069] The frequency regulation risk index of the i-th distributed power source at the current moment is obtained by normalizing the power imbalance index of the target microgrid at the current moment by subtracting the output dispatch capability index of the i-th distributed power source at the current moment.

[0070] In one implementation, the formula for calculating the frequency regulation risk index of the i-th distributed power source at the current moment is:

[0071]

[0072] In the formula, This represents the frequency regulation risk index of the i-th distributed power source at the current moment. This indicates the power imbalance index of the target microgrid at the current moment. This represents the output scheduling capability index of the i-th distributed power source at the current moment. This represents the normalization function.

[0073] It should be noted that, The smaller the value, the smaller the difference between the power imbalance intensity of the target microgrid at the current moment and the regulation capability of the i-th distributed power source, or the power imbalance intensity is much smaller than the regulation capability of the i-th distributed power source. This means the regulation capability of the i-th distributed power source matches the overall operating state of the target microgrid more closely, and the i-th distributed power source is more likely to withstand power fluctuations in the target microgrid in the future. In this case, less frequency regulation capacity should be reserved, i.e., less power compensation should be provided. The smaller; The larger the value, the greater the power imbalance of the target microgrid at the current moment, indicating that the power imbalance is much greater than the regulation capability of the i-th distributed power source. The i-th distributed power source will struggle to compensate for the power imbalance in a timely manner, easily causing fluctuations in the bus voltage frequency. In this case, more frequency regulation capacity should be reserved, i.e., more power compensation should be provided to ensure frequency stability. The larger.

[0074] (3) According to the above The method of obtaining the output scheduling capability index of the i-th distributed power source at each time point in the 24 hours up to the current time is to obtain the disturbance impact index of the i-th distributed power source on the voltage frequency at the current time based on the impact of the output scheduling capability index of the i-th distributed power source at each time point on the voltage frequency.

[0075] Considering that the fluctuations in the dispatch capabilities of different distributed power sources have varying degrees of impact on the power balance of the target microgrid, and this impact is reflected in the voltage-frequency deviation, if the fluctuations in the regulation capability of the i-th distributed power source are highly synchronized with the changes in voltage frequency, it indicates that the output fluctuations of the i-th distributed power source are more likely to cause power imbalance in the target microgrid and affect the stability of voltage frequency. Therefore, based on the synchronicity between the fluctuations in the regulation capability of the i-th distributed power source and the changes in voltage frequency, we can obtain the disturbance impact index of the i-th distributed power source on voltage frequency at the current moment. Specifically:

[0076] For the output scheduling capability index of the i-th distributed power source at any time within the 24 hours up to the current time, the negative of the output scheduling capability index is used as the independent variable of the natural exponential function to obtain the power fluctuation degree of the i-th distributed power source at any time. Taking the current time as an example, the power fluctuation degree of the i-th distributed power source at the current time is denoted as... ,Right now ,in, This represents the output scheduling capability index of the i-th distributed power source at the current moment. Represents the natural exponential function;

[0077] Obtain the power fluctuation level of the i-th distributed power source at each moment within a preset time period up to the current moment, and obtain the power fluctuation level data sequence. Obtain the standard voltage frequency (Chinese standard frequency 50HZ), calculate the absolute value of the difference between the voltage frequency at each moment within 24 hours up to the current moment and the standard voltage frequency, and obtain the frequency difference sequence.

[0078] Calculate the DTW distance between the power fluctuation data sequence and the frequency difference sequence, and use the negative of the DTW distance as the independent variable of the natural exponential function to obtain the disturbance impact index of the i-th distributed power source on the voltage and frequency at the current moment.

[0079] In one embodiment, the formula for calculating the disturbance impact index of the i-th distributed power source on the voltage frequency at the current moment is:

[0080]

[0081] In the formula, This represents the impact of the i-th distributed power source on voltage and frequency disturbances at the current moment. A data sequence representing the degree of power fluctuation. Represents a frequency difference sequence. Indicates DTW distance, This represents the natural exponential function.

[0082] It should be noted that, The smaller the value, the more synchronized the data changes between the power fluctuation data sequence and the frequency difference sequence, and the greater the impact of the output scheduling capability fluctuation of the i-th distributed power source on the frequency deviation. The larger.

[0083] (3) Based on the dispatch capacity index of the i-th distributed power source at the current time and the disturbance impact index of the i-th distributed power source on the voltage frequency at the current time, obtain the compensation power of the optimal power generation of the i-th distributed power source at future times.

[0084] First, the product of the frequency regulation risk index and the disturbance impact index is calculated to obtain the compensation factor for the optimal power generation of the i-th distributed power source at future time, denoted as . ,Right now ,in, This represents the frequency regulation risk index of the i-th distributed power source at the current moment. This represents the impact of the i-th distributed power source on voltage and frequency disturbances at the current moment. The larger the value, the greater the power imbalance of the target microgrid at the current moment, indicating that the power imbalance is much greater than the regulation capacity of the i-th distributed generation. The i-th distributed generation will struggle to compensate for the power imbalance in a timely manner, easily causing fluctuations in the bus voltage frequency. In this case, the i-th distributed generation needs to be given more power compensation, i.e., more capacity needs to be reserved for frequency regulation to ensure voltage frequency stability. The larger; The larger the value, the greater the impact of the output scheduling capability fluctuation of the i-th distributed power source on the frequency deviation. Therefore, the i-th distributed power source can undertake more power compensation, that is, reserve more capacity for frequency regulation, so that frequency fluctuations can be suppressed more quickly, reducing dependence on rapid resources such as energy storage, improving the overall stability and economy of the target microgrid, and thus... The larger.

[0085] Further, the product of the actual power generation of the i-th distributed power source at the current moment and the compensation factor is calculated to obtain the compensation power for obtaining the optimal power generation of the i-th distributed power source at future moments, denoted as . ,Right now In the formula, Let represent the compensation factor for the optimal power generation of the i-th distributed power source at a future time. This represents the actual power generation of the i-th distributed power source at the current moment.

[0086] Step S104: Based on the optimal power generation and compensation power of any distributed power source at a future time, obtain the final power generation of any distributed power source at a future time. Based on the final power generation of each distributed power source in the target microgrid at a future time, realize the energy optimization scheduling and frequency stability control of the target microgrid in islanded operation mode.

[0087] After obtaining the compensation power of the optimal power generation of the i-th distributed power source at the future time through the above steps, the sum of the optimal power generation and the compensation power of the i-th distributed power source at the future time is calculated to obtain the final power generation of the i-th distributed power source at the future time, denoted as . ,Right now In the formula, This represents the optimal power generation of the i-th distributed power source at a future time (i.e., obtained using the MPC algorithm). This indicates the compensation power.

[0088] Similarly, the final power generation of each distributed power source in the target microgrid at a future time is obtained to ensure optimal energy dispatch while reserving adjustment margins to cope with transient disturbances. Furthermore, the upper-level dispatch center or energy management system (EMS) of the target microgrid issues power commands according to the final power generation of each distributed power source at the future time. This means that each distributed power source in the target microgrid outputs power according to its final power generation at the future time. Simultaneously, the system monitors power deviations and frequency changes in real time. When a sudden load change or transient power imbalance caused by distributed power source fluctuations occurs, energy storage and adjustable power sources use reserved frequency regulation capacity for rapid compensation, thereby suppressing frequency offsets, avoiding large oscillations, and achieving synchronous and coordinated control of optimized energy dispatch and rapid frequency stabilization in islanded microgrid operation.

[0089] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for energy optimization scheduling and frequency stability control in islanded operation of a microgrid, characterized in that, The aforementioned method for energy optimization scheduling and frequency stability control in islanded microgrid operation includes: During the islanded operation of the target microgrid, the voltage frequency of the target microgrid, the actual power generation of each distributed power source, and the power consumption of each load node are obtained at each time point within the preset time period up to the current time. The optimal power generation of each distributed power source in the future time is obtained using the MPC algorithm. Based on the difference between the actual power generation of each distributed power source and the power consumption of each load node within the neighborhood time range at the current moment, the power imbalance index of the target microgrid at the current moment is evaluated. For any distributed power source, obtain the dispatch power of the distributed power source within the preset time period. Based on the impact of the difference between the actual power generation and dispatch power of the distributed power source within the preset time period on the voltage frequency, and the power imbalance index of the target microgrid at the current moment, obtain the compensation power of the optimal power generation of the distributed power source at the future moment. Based on the optimal power generation and compensation power of any distributed power source at a future time, the final power generation of any distributed power source at a future time is obtained. Based on the final power generation of each distributed power source in the target microgrid at a future time, the energy optimization scheduling and frequency stability control of the target microgrid in islanded operation mode are realized.

2. The method for energy optimization scheduling and frequency stability control in islanded microgrid operation according to claim 1, characterized in that, The method of evaluating the power imbalance index of the target microgrid at the current moment based on the difference between the actual power generation of each distributed power source and the power consumption of each load node within the neighborhood time range at the current moment includes: The current time and a preset number of times before the current time are combined into a neighborhood time period. For any time within the neighborhood time period, the absolute value of the difference between the total actual power generation of all distributed power sources in the target microgrid and the total power consumption of all load nodes is calculated to obtain the power imbalance degree at any time. Obtain the power imbalance degree of the previous time at any given time, calculate the absolute value of the difference between the power imbalance degree of any given time and the previous time, obtain the degree of imbalance change at any given time, calculate the product between the power imbalance degree at any given time and the degree of imbalance change, and obtain the imbalance characteristic value at any given time. Obtain the imbalance characteristic value at each time point within the neighborhood time period of the current time, calculate the mean of the imbalance characteristic values ​​at all times within the neighborhood time period of the current time, and obtain the power imbalance index of the target microgrid at the current time.

3. The method for energy optimization scheduling and frequency stability control in islanded microgrid operation according to claim 1, characterized in that, The step of obtaining the compensation power for the optimal power generation of any distributed power source in the future time period based on the impact of the difference between the actual power generation and the dispatched power of any distributed power source during the preset time period on the voltage frequency, and the power imbalance index of the target microgrid at the current moment, includes: The current time and a preset number of times before the current time are combined to form the neighborhood time period of the current time. Based on the difference between the actual power generation and the dispatch power of any distributed power source in the neighborhood time period of the current time, the output dispatch capability index of any distributed power source at the current time is obtained. Based on the difference between the output scheduling capability index of any distributed power source at the current moment and the power imbalance index of the target microgrid at the current moment, the frequency regulation risk index of any distributed power source at the current moment is obtained. Obtain the output scheduling capability index of any distributed power source at each moment within a preset time period up to the current moment, and based on the impact of the output scheduling capability index of any distributed power source at each moment within the preset time period up to the current moment on the voltage frequency, obtain the disturbance impact index of any distributed power source on the voltage frequency at the current moment. Calculate the product between the frequency regulation risk index and the disturbance impact index to obtain the compensation factor for the optimal power generation of any distributed power source at a future time. Calculate the product between the actual power generation of any distributed power source at the current moment and the compensation factor to obtain the compensation power for obtaining the optimal power generation of any distributed power source at a future moment.

4. The method for energy optimization scheduling and frequency stability control in islanded microgrid operation according to claim 3, characterized in that, The step of obtaining the output dispatch capability index of any distributed power source at the current moment based on the difference between the actual power generation and the dispatched power of any distributed power source in the neighborhood time period at the current moment includes: For any time within the neighborhood time period of the current time, calculate the absolute value of the difference between the actual power generation and the dispatched power of any distributed power source at any time, obtain the range of the actual power generation of any distributed power source within the neighborhood time period of the current time, calculate the product between the absolute value of the difference and the range, and obtain the degree of power generation output fluctuation of any distributed power source at any time. The power generation output fluctuation of any distributed power source at each time point in the neighborhood of the current time is obtained, the mean of all power generation output fluctuations is calculated, and the negative of the mean is used as the independent variable of the natural exponential function to obtain the output scheduling capability index of any distributed power source at the current time.

5. The method for energy optimization scheduling and frequency stability control in islanded microgrid operation according to claim 3, characterized in that, The step of obtaining the frequency regulation risk index of any distributed power source at the current moment based on the difference between the output scheduling capability index of any distributed power source at the current moment and the power imbalance index of the target microgrid at the current moment includes: The frequency regulation risk index of any distributed power source at the current moment is obtained by normalizing the power imbalance index of the target microgrid at the current moment by subtracting the output scheduling capability index of any distributed power source at the current moment.

6. The method for energy optimization scheduling and frequency stability control in islanded microgrid operation according to claim 3, characterized in that, The step of obtaining the disturbance impact index of any distributed power source on the voltage frequency at the current moment based on the impact of the output scheduling capability index of any distributed power source on the voltage frequency at each moment within a preset time period up to the current moment includes: For any distributed power source at any time within a preset time period up to the current time, the negative of the output scheduling capability index is used as the independent variable of the natural exponential function to obtain the power fluctuation degree of any distributed power source at any time. The power fluctuation level of any distributed power source at each moment within a preset time period up to the current moment is obtained to obtain a power fluctuation level data sequence. The standard voltage frequency is obtained, and the absolute value of the difference between the voltage frequency at each moment within the preset time period and the standard voltage frequency is calculated to obtain a frequency difference sequence. Calculate the DTW distance between the power fluctuation data sequence and the frequency difference sequence, and use the negative of the DTW distance as the independent variable of the natural exponential function to obtain the disturbance impact index of the voltage and frequency of any distributed power source at the current moment.

7. The method for energy optimization scheduling and frequency stability control in islanded microgrid operation according to claim 1, characterized in that, The step of obtaining the final power generation of any distributed power source at a future time based on its optimal power generation and compensation power at a future time includes: The sum of the optimal power generation of any distributed power source in the future time and the compensation power is calculated to obtain the final power generation of any distributed power source in the future time.

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