Electric power and electric quantity balance degree analysis method

Abstract

An electric power and electric quantity balance degree analysis method comprises the steps that firstly, a long-term electric quantity balance degree calculation model and a short-term electric power balance degree calculation model are constructed based on the requirement for stable operation of an electric power system; secondly, according to different time scales, substituting historical multi-year operation data of the electric power system into a corresponding electric power and electric quantity balance degree calculation model, and processing a calculation result in combination with a historical operation state of the electric power system so as to construct a stable operation evaluation system of the corresponding time scale; then, performing electric power and electric quantity balance degree calculation on the predicted operation data of the system, and evaluating a stable operation level of the system according to a calculation result so as to judge whether the system needs to adopt adjustment operation or not; and finally, establishing an adjustable force calculation model of different time scales, and evaluating the adjustable capability of the system, so that corresponding adjustment operation is adopted in the scheduling process of different time scales to improve the electric power and electric quantity balance capability of the system.

Description

Technical Field

[0001] This invention relates to the fields of new energy and power system dispatching technology, specifically to a power balance analysis method that can leverage the regulation capabilities of different energy sources and their synergistic power generation capabilities to improve the power balance level of the system. Background Technology

[0002] With the high proportion of renewable energy connected to the grid, the uncertainty on both the source and load sides has increased significantly. The traditional source-follow-load operation mode is no longer sufficient to meet the higher requirements of the new power system for power balance. Multi-energy complementary and coordinated power generation technology can better utilize the spatiotemporal complementarity between different energy sources, effectively smoothing the output fluctuations of high-proportion renewable energy and enhancing system stability. However, wind and solar power output is unstable and has stringent requirements for meteorological conditions, which means that the new power system cannot rely entirely on wind and solar power output to meet the uncertain loads of the system. In addition, hydropower, as a renewable, stable, and adjustable power source, has a certain effect on smoothing the output fluctuations of wind and solar power systems. However, large-scale hydropower also has certain impacts on the ecological environment, and its output is not only constrained by reservoir capacity and downstream flow, but also affected by the drought and flood seasons throughout the year, which limits the ability of hydropower to regulate wind and solar power output. How to allocate these regulatory resources and make them rationally matched to meet the power balance needs of the new power system during different periods of dispatching is therefore necessary to formulate a dispatching strategy that meets the system's power balance needs to ensure the safe and stable operation of the system.

[0003] Currently, comprehensive balancing of multi-energy systems and collaborative cooperation among multiple entities can effectively improve the power balance level of the system. However, it is crucial to formulate a reasonable dispatch strategy, comprehensively consider the operating characteristics of different power sources in the system, deeply explore the power generation potential of power sources, effectively utilize them in a complementary manner, and achieve mutual nesting at different time scales to improve the system's power balance capability. Existing power evaluation systems, such as the paper "Research on Power Balance of Power Systems Based on Refined Simulation," propose a power balance index and calculation method. However, these mainly focus on establishing the power balance index and its calculation method, without further combining the index to optimize the output of various power sources within the system to achieve a higher level of power balance. In new power systems, due to the high proportion and strong volatility of new energy sources, optimizing power source output based on index evaluation to ensure the real-time power balance of the system is particularly critical.

[0004] Therefore, developing a reasonable power balance evaluation system and fully leveraging the operational potential of multiple energy sources within the system are crucial for improving the power balance level and stable operation of multi-energy complementary systems. Summary of the Invention

[0005] The purpose of this invention is to address the technical problem that existing power balance evaluation methods mainly focus on establishing power balance indicators and their calculation methods, without further combining these indicators to optimize the output of various power sources within the system, thus failing to achieve a higher level of power balance. The invention proposes a power balance analysis method that can deeply leverage the operational potential of multiple energy sources in the system, improve the power balance level of multi-energy complementary systems, and ensure stable operation.

[0006] To solve the above-mentioned technical problems, the present invention proposes the following technical solution: A method for analyzing power balance includes the following steps: Step 1: To address the power balance requirements of the power system at different time scales, construct long-term power balance calculation models and short-term power balance calculation models; Step 2: Based on the established long-term power balance calculation model and short-term power balance calculation model, calculate the long-term power balance and short-term power balance of the historical operating data of the power system, and combine the calculation results with the historical operating status of the power system to formulate a stable operation evaluation method for the corresponding time scale. Step 3: Calculate the long-term and short-term power balance of the power system's predicted operating data, predict the possible stable operating range of the power system, and thus determine whether to adjust the output of flexible resources. Step 4: Establish a time-scale adjustable capacity calculation model to calculate the adjustable capacity of the power system's flexibility resources at different times, and then take corresponding adjustment operations based on the predicted stable operation level.

[0007] In step 1, the power system mainly relies on renewable energy generation, with the aim of promoting the consumption of renewable energy and reducing the consumption of fossil fuels. Therefore, the specific components of this power system mainly include: One wind power station A photovoltaic power station, One hydropower station A thermal power plant There are several energy storage power stations. Among them, wind and solar power stations are the main sources of power output for the system and are given priority to provide clean energy. However, since the output of wind and solar power has certain fluctuations and is not adjustable, its power output needs to be coordinated with hydropower stations, thermal power stations and energy storage power stations to improve the stability and reliability of power and reduce the impact of the fluctuation of wind and solar power output on the stable operation of the power system.

[0008] In step 1, the specific procedures include: 1.1) Establish a long-term power balance calculation model; 1.2) Establish a short-term power balance calculation model; In 1.1), the established long-term power balance calculation model is shown in equation (1): (1); Equation (1) comprehensively considers the output, load demand and transmission loss of each generator set in the system to calculate the power balance between the output and load of each generator set in the same period. This refers to the total number of power sources in a power system over a long time period. Internal power balance, It refers to the first A thermal power plant Total power generation during the period It refers to the first A hydropower station Total power generation during the period It refers to the first A photovoltaic power station in Total power generation during the period It refers to the first A wind power station Total power generation during the period It refers to the first A storage power station Total charging volume during the period It refers to the first A storage power station Total discharge during the period This refers to the power system in Total transmission losses during the period This refers to the power system in The total load to be borne during the period; In section 1.2), the established short-term power balance calculation model is shown in equation (2): (2): Equation (2) comprehensively considers the output and load demand of each generator set in the system and calculates the power balance of each generator set output and load at the same time. It refers to the power balance of all power sources in the power system at any given moment on a short time scale. It refers to the first A thermal power plant Power generation at any time It refers to the first A hydropower station Power generation at any given moment It refers to the first A photovoltaic power station Power generation at any time It refers to the first A wind power station Power generation at any given moment It refers to the first Taiwan's energy storage power station Charging power at any time It refers to the first Taiwan's energy storage power station Discharge power at any given time This refers to the power system in The total load that needs to be borne at any given time.

[0009] In step 2, the specific procedures include: 2.1) Divide the long-term historical operating data of the power system into two equal parts. One part is used to determine the prior distribution, and the other part is used to calculate the posterior probability and determine the classification boundary. 2.2) Based on the long-term power balance calculation results, a long-term stable operation evaluation system is constructed; 2.3) Based on the calculation results of short-term power balance, construct a short-term stable operation evaluation system.

[0010] In section 2.1), firstly, the historical operating data of the original power system is cleaned to remove obviously missing, duplicate, or abnormal data records. For outliers, reasonable threshold ranges are set for identification and correction to improve data quality. Then, the historical operating data of the power system is divided into two equal parts using random sampling: one part is used as the training set to determine the prior distribution, and the other part is used as the validation set to calculate the posterior probability and determine the classification boundary accordingly. The division process must maintain the same proportion of each class of samples in the two parts to ensure the balance and effectiveness of model training and validation.

[0011] In 2.2), for the training set portion divided in 2.1), firstly, long-term scale data is selected, and the long-term power balance result is calculated according to the long-term power balance calculation model in 1.1); then, the long-term power balance calculation result is divided into five types according to the three operating states of the power system: normal operation, mild instability operation, and severe instability operation, and the initial distribution of the five types is determined as shown in equation (3): (3); In equation (3), This refers to the normal operating state. This refers to a situation where, under mild instability conditions, the total power generation of all power sources exceeds the total load they are required to handle. In the case of ), This refers to a situation where, under mild instability conditions, the total power generation of all power sources is less than the total load they are required to handle. In the case of ), This refers to a situation where, under severe instability operation, the power generation of all power sources exceeds the total load they are required to handle. This refers to a situation where, under severe instability conditions, the power generation of all power sources is less than the total load they are required to handle. This refers to the mean value of the long-term electrical balance calculation results used for the prior distribution, which is under normal operating conditions. It refers to the standard deviation of the long-term electrical balance calculation results used for the prior distribution, which is under normal operating conditions; It refers to the average value in the long-term power balance calculation results used for a priori distribution, where the power generation of all power sources in a slightly unstable operating state is greater than the total load they need to bear. This refers to the standard deviation of the long-term power balance calculation results used for a priori distributions, where the power generation of all power sources under slightly unstable operating conditions exceeds the total load they are required to bear. It refers to the average value in the long-term power balance calculation results used for a priori distribution, where the power generation of all power sources under slightly unstable operating conditions is less than the total load they need to bear. It refers to the standard deviation of the long-term power balance calculation results used for a priori distribution, where the power generation of all power sources under slightly unstable operating conditions is less than the total load they need to bear. This refers to the average value in the long-term power balance calculation results used for a priori distribution, where the power generation of all power sources under severely unstable operating conditions exceeds the total load they need to bear. It refers to the standard deviation of the long-term power balance calculation results used for a priori distribution when the power generation of all power sources under severe instability operation is greater than the total load they need to bear. This refers to the average value in the long-term power balance calculation results used for a priori distribution, where the power generation of all power sources under severely unstable operating conditions is less than the total load they need to bear. It refers to the standard deviation of the long-term power balance calculation results used for a priori distribution when the power generation of all power sources under severe instability is less than the total load they need to bear. Based on the initial distribution, the boundaries between different operating states are determined. First, the prior probabilities are determined. For all power balance calculation results and corresponding states, the ratio of the power balance calculation result corresponding to each state to all power balance calculation results is calculated. This ratio is used as the prior distribution probability for five types, and is denoted as follows: , , , , Then, the likelihood functions for the five types are calculated, and the posterior probabilities are calculated by calling the validation set to update the long-term energy balance calculation results of the classification boundary. Meanwhile, the likelihood probability of this part of the calculation result belonging to each type is calculated, and the calculation formula is shown in equation (4): (4); Secondly, calculation based on Bayes' theorem The posterior probability for each type is calculated using the formula shown in equation (5): (5); In equation (5), The result of long-term electrical balance calculation The marginal probability does not need to be calculated during the construction process. Finally, the boundary value between different types is determined, that is, a long-term power balance calculation result is found such that the posterior probability is the same when it is in two adjacent types. Then this power balance calculation result can be used as the boundary value between the two adjacent types. The specific calculation formula is shown in Equation (6): (6); because No calculation is needed, so we can directly find the answer. time The value is used as the boundary value between adjacent types, and the long-term stable operation evaluation method is shown in Equation (7); (7); Equation (7) represents the long-term electrical balance. The different intervals in which they are located correspond to the states, states ( This indicates that the power system is in a stable operating state and no adjustment measures are required; state ( This indicates that the power system is in a state of mild instability, requiring the use of flexibility resources to balance the power supply as much as possible; state ( This indicates that the power system is in a state of severe instability and requires emergency measures such as generator shutdown and load shedding. It refers to the critical state between the normal operating state and the mild instability process of a power system. It refers to the critical state between the mild and severe instability processes of a power system. This refers to the long-term power balance. When the value is less than 1 (the power generation of the power system is less than the total load it bears), it represents the boundary value between a stable operating state and a slightly unstable operating state of the power system. This refers to the long-term power balance. When the value is less than 1, it represents the boundary between a slightly unstable operating state and a severely unstable operating state of the power system. This refers to the long-term power balance. When the value is greater than 1 (the power generation of the power system is greater than the total load it bears), it represents the boundary value between a stable operating state and a slightly unstable operating state of the power system. This refers to the long-term power balance. When the value is greater than 1, it represents the boundary value between the mild and severe instability of the power system.

[0012] In section 2.3), the short-term stable operation evaluation system is established as shown in equation (8): (8); Equation (8) represents the state corresponding to different intervals of short-term power balance, state ( This indicates that the power system is in a stable operating state and no adjustment measures are required; state ( This indicates that the power system is in a state of mild instability, requiring the use of flexibility resources to restore power balance as much as possible; state ( This indicates that the power system is in a state of severe instability and requires emergency measures such as generator shutdown and load shedding. This refers to the short-term power balance. When the value is less than 1 (the power generation of the power system is less than the total load it bears), it represents the boundary value between a stable operating state and a slightly unstable operating state of the power system. This refers to the short-term power balance. When the value is less than 1, it represents the boundary between a slightly unstable operating state and a severely unstable operating state of the power system. This refers to the long-term power balance. When the value is greater than 1 (the power generation of the power system is greater than the total load it bears), it represents the boundary value between a stable operating state and a slightly unstable operating state of the power system. This refers to the long-term power balance. When the value is greater than 1, it represents the boundary value between the mild and severe instability of the power system.

[0013] In step 3, the specific procedures include: 3.1) Based on meteorological forecast data, runoff forecast data, and load forecast data of the power system's dispatching and operation area, long-term and short-term dispatching of the power system is carried out to obtain predicted operation data of the power system at different time scales. 3.2) Based on the long-term dispatch operation data of the power system, calculate the long-term power balance during the long-term dispatch process, and at the same time, determine the operating state of the power system in each period during the long-term dispatch process based on the long-term stable operation evaluation system. 3.3) Based on the short-term time-scale dispatch operation data of the power system, calculate the short-term power balance during the short-term time-scale dispatch process, and at the same time, judge the power system operation status at each moment during the short-term time-scale dispatch process based on the short-term stable operation evaluation system. In 3.2), the long-term scale prediction operation data in 3.1) is substituted into the long-term power balance calculation model (1) to obtain the long-term power balance calculation result. The long-term power balance calculation result is then substituted into formula (7) to determine the long-term stable operation result of the power system in each time period under the long-term scale and to clarify the power system operation status in each time period. In 3.3), the short-term time scale prediction operation data in 3.1) is substituted into the short-term power balance calculation model (2) to obtain the long-term power balance calculation result. The long-term power balance calculation result is then substituted into formula (8) to determine the short-term stable operation result of the power system in each time period under the short-term time scale, and to clarify the power system operation status at each moment.

[0014] In step 4, the specific steps include: 4.1) Based on the dispatching operation of the power system on both long-term and short-term time scales, analyze the operating constraints and available output of the thermal power plants and energy storage power plants contained in the power system; 4.2) Based on the operational analysis of thermal power plants and energy storage power plants in 4.1), an adjustable power calculation model is established for different time scales; 4.3) Based on the adjustable power calculation model in 4.2), set a reasonable objective function to optimize the long-term power balance and short-term power balance; In section 4.1), based on the analysis of the long-term and short-term scheduling operation of the power system, the operating characteristics of various adjustable power sources within the power system are further sorted out. The focus is on analyzing the operating constraints of thermal power plants and energy storage power plants under different scheduling cycles. Based on the predicted load, power output and system supply and demand characteristics within the scheduling cycle, the adjustable output range of thermal power plants and energy storage power plants at different time scales is evaluated, and their adjustment capacity boundaries and operational feasibility are clarified. In step 4.2), based on the quantification of the output characteristics of thermal power plants and energy storage power plants at different time scales in 4.1), a calculation model for adjustable output at a long time scale and a calculation model for adjustable output at a short time scale are established, and the operating data of thermal power plants and energy storage power plants are substituted into the model to quantify the adjustable output of the power system at different time scales.

[0015] In section 4.1), the constraints involved are as follows: The operating constraints of thermal power plants are shown in the following formula: (9); Equation (9) includes thermal power output constraints, thermal power start-up and shutdown constraints, and thermal power ramping constraints, among which, It refers to a specific moment on a long-term or short-term timescale. It refers to the first The minimum output of a thermal power plant It refers to the first The maximum output of a thermal power plant It refers to the first A thermal power plant The duration of continuous operation at any given moment. It refers to the first A thermal power plant The duration of continuous downtime at any given moment. It refers to the first The shortest operating time for each thermal power unit. It refers to the first The shortest downtime for a thermal power plant. It refers to the first A thermal power plant The on / off state variable at any given time. It refers to the first The rate of downward ramp for a thermal power plant It refers to the first The rate of ascent for a thermal power plant. The time interval at this time scale; The operating constraints of the energy storage power station are shown in the following formula: (10); Equation (10) includes the energy storage power station capacity constraint, charging and discharging power constraint, charging and discharging state mutual exclusion constraint, and dispatching start and end period power constraint, wherein, It refers to the first A storage power station Remaining capacity at any given time It refers to the first The maximum capacity of an energy storage power station It refers to the first The charging power of an energy storage power station It refers to the first The discharge power of an energy storage power station It refers to the first The upper limit of charging power for an energy storage power station It refers to the first The upper limit of the discharge power of an energy storage power station It refers to the first The charging state variables of an energy storage power station It refers to the first Discharge state variables of an energy storage power station It refers to the first The amount of electricity generated by each energy storage power station at the start of the dispatch cycle. It refers to the first The amount of electricity generated by a single energy storage power station at the end of the dispatch cycle; The power system reserve capacity constraint is shown in the following formula: (11); In equation (11), , This is the reserve factor for the power system to new energy sources and loads; In section 4.2), the model involved is: The force calculation model that can be adjusted over a long time scale is shown in the following equation: (12); The force calculation model that can be adjusted on a short time scale is shown in the following equation: (13); The adjustable force model is shown in equation (14): (14); Equation (14) integrates the flexibility resources within the power system. Based on their operational constraints and response capabilities, and considering the nesting of long-term and short-term resources, the flexibility resources are allocated to different scheduling periods. Therefore, the long-term and short-term power system flexibility resources are quantitatively modeled according to their adjustment characteristics. The calculation results of this adjustable power model can be optimized and adjusted based on the operational constraints of the units in different scheduling periods, thereby changing the power balance level of the power system. Equation (14) represents the short-term positive adjustable power calculation model and the short-term negative adjustable power calculation model, as well as the long-term positive adjustable power calculation model and the long-term negative adjustable power calculation model. This refers to a long-term, positively adjustable output power used to increase long-term electrical balance. This refers to a long-term adjustable reverse force, used to reduce long-term electrical imbalance. This refers to the positive adjustable output of the power system when the total power generation of all power sources is less than the power consumption during long-term dispatching. This refers to the reverse adjustable output power when the power generation of all power sources exceeds the power consumption during long-term dispatching of the power system. This refers to the short-term positive adjustable force, used to increase the short-term power balance; This refers to the ability to adjust the reverse force in the short term to reduce the short-term power imbalance. This refers to the positive adjustable output of the power system when its generating capacity is less than the load demand during short-term dispatching. This refers to the reverse adjustable output of the power system when the generating capacity exceeds the load demand during short-term dispatching. Step 4.3: Based on the long-term energy balance results in Step 3.2 and the long-term adjustable power calculation model established in Step 4.2, the long-term energy balance is further optimized. The established objective function considering the long-term energy balance is shown below: (15); In Equation (15), the established objective function quantifies the flexibility adjustment resources in the power system, enabling the power system to maintain the long-term power balance within the normal operating range by rationally selecting positive and negative adjustment outputs during long-term dispatch. That is, when the long-term power balance is lower than the power balance under normal operating conditions, positive adjustment output is used, and when the long-term power balance is higher than the power balance under normal operating conditions, negative adjustment output is used. In other words, by selecting appropriate flexibility adjustment outputs, the long-term power balance of the power system is maintained within the normal operating range or the risk of severe instability is reduced, thereby stabilizing the operation of the power system. Based on the short-term power balance results in step 3.3 and the short-timescale adjustable power calculation model established in step 4.2, the short-term power balance is further optimized. The established objective function considering the short-term power balance is shown in the following formula: (16); In Equation (16), the established objective function quantifies the output of the flexible regulation resources in the power system on a shorter time scale to optimize the short-term power balance. This enables the power system to keep the short-term power balance within the normal operating range by rationally selecting positive and negative regulation outputs during short-term dispatch. Specifically, when the short-term power balance is lower than the power balance under normal operating conditions, positive regulation output is used, and when the short-term power balance is higher than the power balance under normal operating conditions, negative regulation output is used. In other words, by selecting appropriate flexible regulation outputs, the short-term power balance of the power system is kept within the normal operating range or the risk of severe instability is reduced, thereby stabilizing the operation of the power system.

[0016] Compared with the prior art, the present invention has the following technical effects: 1) This invention accurately reflects the supply and demand matching status and imbalance characteristics of the power system at different time scales by establishing a long-term power balance model and a short-term power balance model; 2) By establishing a stable operation evaluation system at different time scales, this invention can effectively map the long-term power balance and short-term power balance with the actual operating state of the power system, so as to accurately predict the operating state of the power system and take effective adjustment measures. 3) The adjustable power model established in this invention can realize the timing matching and precise allocation of resources based on the adjustment characteristics and response capabilities of flexible resources, so as to improve the overall supply and demand matching capability and operational flexibility of the power system. Attached Figure Description

[0017] The present invention will be further described below with reference to the accompanying drawings and embodiments: Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is an image showing the effect after adding adjustable force optimization over a long time scale in an embodiment of the present invention; Figure 3 This is a diagram showing the effect after short-term power balance optimization in an embodiment of the present invention. Detailed Implementation

[0018] like Figure 1 As shown, a method for analyzing power balance includes the following steps: Step 1: To address the power balance requirements of the power system at different time scales, construct long-term power balance calculation models and short-term power balance calculation models; Step 2: Based on the established long-term power balance calculation model and short-term power balance calculation model, calculate the long-term power balance and short-term power balance of the historical operating data of the power system, and combine the calculation results with the historical operating status of the power system to formulate a stable operation evaluation system for the corresponding time scale. Step 3: Calculate the long-term and short-term power balance of the power system's predicted operating data, predict the possible stable operating range of the power system, and thus determine whether to adjust the output of flexible resources. Step 4: Establish a time-scale adjustable capacity calculation model to calculate the adjustable capacity of the power system's flexibility resources at different times, and then take corresponding adjustment operations based on the predicted stable operation level.

[0019] See Figure 1As shown, the specific implementation method of step 1 of a power balance analysis method is as follows: the power system mainly relies on new energy power generation, and its purpose is to promote the consumption of new energy and reduce the consumption of fossil energy. Therefore, the specific composition of the power system mainly includes: One wind power station A photovoltaic power station, One hydropower station A thermal power plant There are several energy storage power stations. Among them, wind and solar power stations are the main sources of power output for the system and are given priority to provide clean energy. However, since the output of wind and solar power has certain fluctuations and is not adjustable, its power output needs to be coordinated with hydropower stations, thermal power stations and energy storage power stations to improve the stability and reliability of power and reduce the impact of the fluctuation of wind and solar power output on the stable operation of the power system.

[0020] In step 1, the specific procedures include: 1.1) Establish a long-term power balance calculation model; 1.2) Establish a short-term power balance calculation model.

[0021] In 1.1), the power system dispatch cycle is relatively long over a long time scale. In order to accurately describe the balance between the power generation of all power sources and the total load to be borne by the power system in each time period over a long time scale, a long-term power balance calculation model is constructed to calculate the long-term power balance under the premise of considering transmission losses. The formula involved is shown in Equation (1). In 1.2), under the short time scale, the power system dispatch cycle is short, and it is necessary to accurately depict the real-time matching relationship between the output capacity of various power sources and the load they need to bear at each moment. In order to reflect the dynamic balance characteristics between power supply and demand under the short time scale, a short-term power balance calculation model is constructed to calculate the short-term power balance. The formula involved is shown in equation (2). In 1.1), the established long-term power balance calculation model is shown in equation (1): (1); Equation (1) comprehensively considers the output, load demand and transmission loss of each generator set in the system to calculate the power balance between the output and load of each generator set in the same period. This refers to the total number of power sources in a power system over a long time period. Internal power balance, It refers to the first A thermal power plant Total power generation during the period It refers to the first A hydropower station Total power generation during the period It refers to the first A photovoltaic power station in Total power generation during the period It refers to the first A wind power station Total power generation during the period It refers to the first A storage power station Total charging volume during the period It refers to the first A storage power station Total discharge during the period This refers to the power system in Total transmission losses during the period This refers to the power system in The total load that needs to be borne during the time period.

[0022] In section 1.2), the established short-term power balance calculation model is shown in equation (2): (2); Equation (2) comprehensively considers the output and load demand of each generator set in the system and calculates the power balance of each generator set output and load at the same time. It refers to the power balance of all power sources in the power system at any given moment on a short time scale. It refers to the first A thermal power plant Power generation at any time It refers to the first A hydropower station Power generation at any given moment It refers to the first A photovoltaic power station Power generation at any time It refers to the first A wind power station Power generation at any given moment It refers to the first Taiwan's energy storage power station Charging power at any time It refers to the first Taiwan's energy storage power station Discharge power at any given time This refers to the power system in The total load that needs to be borne at any given time.

[0023] See Figure 1 As shown, the specific implementation method of step 2 of a power balance analysis method is as follows: 2.1) First, the historical operation data of the original power system is cleaned to remove obviously missing, duplicate or abnormal data records. For outliers, reasonable threshold ranges are set for identification and correction to improve data quality. Then, the historical operation data of the power system is divided into two equal parts by random sampling: one part is used as the training set to determine the prior distribution, and the other part is used as the validation set to calculate the posterior probability and determine the classification boundary accordingly. The division process should keep the proportion of each class of samples in the two parts consistent to ensure the balance and effectiveness of model training and validation.

[0024] 2.2) For the training set portion divided in 2.1), firstly, select data on a long time scale and calculate the long-term power balance result according to the long-term power balance calculation model in 1.1); then, divide the long-term power balance calculation result into five types according to the three operating states of the power system: normal operation, slight instability operation, and severe instability operation, and determine the initial distribution of the five types according to statistical principles as shown in equation (3): (3); In equation (3), This refers to the normal operating state. This refers to a situation where, under mild instability conditions, the total power generation of all power sources exceeds the total load they are required to handle. In the case of ), This refers to a situation where, under mild instability conditions, the total power generation of all power sources is less than the total load they are required to handle. In the case of ), This refers to a situation where, under severe instability operation, the power generation of all power sources exceeds the total load they are required to handle. This refers to a situation where, under severe instability conditions, the power generation of all power sources is less than the total load they are required to handle. This refers to the mean value of the long-term electrical balance calculation results used for the prior distribution, which is under normal operating conditions. It refers to the standard deviation of the long-term electrical balance calculation results used for the prior distribution, which is under normal operating conditions; It refers to the average value in the long-term power balance calculation results used for a priori distribution, where the power generation of all power sources in a slightly unstable operating state is greater than the total load they need to bear. This refers to the standard deviation of the long-term power balance calculation results used for a priori distributions, where the power generation of all power sources under slightly unstable operating conditions exceeds the total load they are required to bear. It refers to the average value in the long-term power balance calculation results used for a priori distribution, where the power generation of all power sources under slightly unstable operating conditions is less than the total load they need to bear. It refers to the standard deviation of the long-term power balance calculation results used for a priori distribution, where the power generation of all power sources under slightly unstable operating conditions is less than the total load they need to bear. This refers to the average value in the long-term power balance calculation results used for a priori distribution, where the power generation of all power sources under severely unstable operating conditions exceeds the total load they need to bear. It refers to the standard deviation of the long-term power balance calculation results used for a priori distribution when the power generation of all power sources under severe instability operation is greater than the total load they need to bear. This refers to the average value in the long-term power balance calculation results used for a priori distribution, where the power generation of all power sources under severely unstable operating conditions is less than the total load they need to bear. It refers to the standard deviation of the long-term power balance calculation results used for a priori distribution, where the power generation of all power sources under severely unstable operating conditions is less than the total load they need to bear.

[0025] Based on the above processing results, the boundaries between different operating states are determined. First, the prior probabilities are determined. For all long-term power balance calculation results and corresponding states, the ratio of the power balance calculation result corresponding to each state to all power balance calculation results is calculated. This ratio is used as the prior distribution probability of the five types, and is denoted as follows: , , , , Then, the likelihood functions for the five types are calculated, and the posterior probabilities are calculated by calling the validation set to update the long-term energy balance calculation results of the classification boundary. Meanwhile, the likelihood probability of this part of the calculation result belonging to each type is calculated, and the calculation formula is shown in equation (4): (4); Secondly, calculation based on Bayes' theorem The posterior probability for each type is calculated using the formula shown in equation (5): (5); In equation (5), The result of long-term electrical balance calculation The marginal probability does not need to be calculated during the construction process. Finally, the boundary value between different types is determined, that is, a long-term power balance calculation result is found such that the posterior probability is the same when it is in two adjacent types. Then this power balance calculation result can be used as the boundary value between the two adjacent types. The specific calculation formula is shown in Equation (6): (6); because No calculation is needed, so we can directly find the answer. time The value is used as the boundary value between adjacent types, and the long-term stable operation evaluation system is obtained as shown in equation (7); (7); Equation (7) represents the long-term electrical balance. The different intervals in which they are located correspond to the states, states ( This indicates that the power system is in a stable operating state and no adjustment measures are required; state ( This indicates that the power system is in a state of mild instability, requiring the use of flexibility resources to balance the power supply as much as possible; state ( This indicates that the power system is in a state of severe instability and requires emergency measures such as generator shutdown and load shedding. It refers to the critical state between the normal operating state and the mild instability process of a power system. It refers to the critical state between the mild and severe instability processes of a power system. This refers to the long-term power balance. When the value is less than 1 (the power generation of the power system is less than the total load it bears), it represents the boundary value between a stable operating state and a slightly unstable operating state of the power system. This refers to the long-term power balance. When the value is less than 1, it represents the boundary between a slightly unstable operating state and a severely unstable operating state of the power system. This refers to the long-term power balance. When the value is greater than 1 (the power generation of the power system is greater than the total load it bears), it represents the boundary value between a stable operating state and a slightly unstable operating state of the power system. This refers to the long-term power balance. When the value is greater than 1, it represents the boundary value between the mild and severe instability of the power system.

[0026] 2.3) For the training set portion divided in 2.1), firstly select data with a short time scale, and calculate the short-term power balance result according to the short-term power balance calculation model in 1.2); then, according to the processing procedure in 2.3), obtain the short-term stable operation evaluation system as shown in equation (7); (8); Equation (8) represents the state corresponding to different intervals of short-term power balance, state ( This indicates that the power system is in a stable operating state and no adjustment measures are required; state ( This indicates that the power system is in a state of mild instability, requiring the use of flexibility resources to restore power balance as much as possible; state ( This indicates that the power system is in a state of severe instability and requires emergency measures such as generator shutdown and load shedding. This refers to the short-term power balance. When the value is less than 1 (the power generation of the power system is less than the total load it bears), it represents the boundary value between a stable operating state and a slightly unstable operating state of the power system. This refers to the short-term power balance. When the value is less than 1, it represents the boundary between a slightly unstable operating state and a severely unstable operating state of the power system. This refers to the long-term power balance. When the value is greater than 1 (the power generation of the power system is greater than the total load it bears), it represents the boundary value between a stable operating state and a slightly unstable operating state of the power system. This refers to the long-term power balance. When the value is greater than 1, it represents the boundary value between the mild and severe instability of the power system.

[0027] See Figure 1 As shown, the specific implementation method of step 3 of a power balance analysis method is as follows: Step 3.1: Based on meteorological forecast data, runoff forecast data, load forecast data, etc. of the power system dispatching and operation area, systematically carry out the dispatching work of the power system at long-term and short-term time scales from different time scales. Based on multiple types of forecast data, obtain the predicted operation data of the power system at long-term and short-term time scales, that is, the power generation data and total load of all power sources of the power system at long-term and short-term time scales.

[0028] Step 3.2: Substitute the long-term scale prediction operation data from Step 3.1 into the long-term power balance calculation model (1) to obtain the long-term power balance calculation results, as shown in Table 1. Substitute the long-term power balance calculation results into formula (3) to determine the long-term stable operation results of the power system in each time period under the long-term scale and clarify the power system operation status in each time period.

[0029] Table 1: Calculation results of long-term power balance before optimization

[0030] Table 1 shows the long-term power balance calculation results of the pre-ten-day scheduling results using long-term scale predicted operating data, which includes the operating status of the power system for 10 days. As can be seen from Table 1, the power system has power imbalance in 7 out of 10 days, and all of them are related to wind and solar power curtailment.

[0031] Step 3.3: Substitute the short-term timescale predicted operation data from Step 3.1 into the short-term power balance calculation model (2) to obtain the long-term power balance calculation results, as shown in Table 2. Substitute the long-term power balance calculation results into formula (4) to determine the short-term stable operation results of the power system in each time period under the short-term timescale, and clarify the power system operation status at each moment.

[0032] Table 2: Calculation results of short-term power balance before optimization

[0033] Table 2 shows the short-term power balance calculation results of the day-ahead scheduling results using short-timescale predicted operating data, which includes the operating status of the power system for 24 hours a day. As can be seen from Table 2, the power system has a power imbalance at every moment of the day.

[0034] See Figure 1 As shown, the specific implementation method of step 4 of a power balance analysis method is as follows: Step 4.1: Based on the long-term and short-term scheduling and operation analysis of the power system, further analyze the operating characteristics of various adjustable power sources within the power system, focusing on the operating constraints of thermal power plants and energy storage power plants under different scheduling cycles. Based on the predicted load, power output, and system supply and demand characteristics within the scheduling cycle, evaluate the adjustable output range of thermal power plants and energy storage power plants at different time scales, clarify their regulation capacity boundaries and operational feasibility. The formulas involved are as follows: The operating constraints of thermal power plants are shown in the following formula: (9); Equation (9) includes thermal power output constraints, thermal power start-up and shutdown constraints, and thermal power ramping constraints, among which, It refers to a specific moment on a long-term or short-term timescale. It refers to the first The minimum output of a thermal power plant It refers to the first The maximum output of a thermal power plant It refers to the first A thermal power plant The duration of continuous operation at any given moment. It refers to the first A thermal power plant The duration of continuous downtime at any given moment. It refers to the first The shortest operating time for each thermal power unit. It refers to the first The shortest downtime for a thermal power plant. It refers to the first A thermal power plant The on / off state variable at any given time. It refers to the first The rate of downward ramp for a thermal power plant It refers to the first The rate of ascent for a thermal power plant. This represents the time interval on this time scale.

[0035] The operating constraints of the energy storage power station are shown in the following formula: (10); Equation (10) includes the energy storage power station capacity constraint, charging and discharging power constraint, charging and discharging state mutual exclusion constraint, and dispatching start and end period power constraint, wherein, It refers to the first A storage power station Remaining capacity at any given time It refers to the first The maximum capacity of an energy storage power station It refers to the first The charging power of an energy storage power station It refers to the first The discharge power of an energy storage power station It refers to the first The upper limit of charging power for an energy storage power station It refers to the first The upper limit of the discharge power of an energy storage power station It refers to the first The charging state variables of an energy storage power station It refers to the first Discharge state variables of an energy storage power station It refers to the first The amount of electricity generated by each energy storage power station at the start of the dispatch cycle. It refers to the first The amount of electricity generated by an energy storage power station at the end of the dispatch cycle.

[0036] The power system reserve capacity constraint is shown in the following formula: (11); In equation (11), , This is the reserve factor for the power system for new energy sources and loads.

[0037] Step 4.2: Based on the quantification of the output characteristics of thermal power plants and energy storage power plants at different time scales in Step 4.1, establish a calculation model for adjustable output at long time scales and a calculation model for adjustable output at short time scales. Substitute the operating data of thermal power plants and energy storage power plants into the model to quantify the adjustable output of the power system at different time scales. The formulas involved are as follows: The force calculation model that can be adjusted over a long time scale is shown in the following equation: (12); The force calculation model that can be adjusted on a short time scale is shown in the following equation: (13); The adjustable force model is shown in equation (13): (14); Equation (14) integrates the flexibility resources within the power system. Based on their operational constraints and response capabilities, and considering the nesting of long-term and short-term resources, the flexibility resources are allocated to different scheduling periods. Therefore, the long-term and short-term power system flexibility resources are quantitatively modeled according to their adjustment characteristics. The calculation results of this adjustable power model can be optimized and adjusted based on the operational constraints of the units in different scheduling periods, thereby changing the power balance level of the power system. Equation (14) represents the short-term positive adjustable power calculation model and the short-term negative adjustable power calculation model, as well as the long-term positive adjustable power calculation model and the long-term negative adjustable power calculation model. This refers to a long-term, positively adjustable output power used to increase long-term electrical balance. This refers to a long-term adjustable reverse force, used to reduce long-term electrical imbalance. This refers to the positive adjustable output of the power system when the total power generation of all power sources is less than the power consumption during long-term dispatching. This refers to the reverse adjustable output power when the power generation of all power sources exceeds the power consumption during long-term dispatching of the power system. This refers to the short-term positive adjustable force, used to increase the short-term power balance; This refers to the ability to adjust the reverse force in the short term to reduce the short-term power imbalance. This refers to the positive adjustable output of the power system when its generating capacity is less than the load demand during short-term dispatching. This refers to the reverse adjustable output of the power system when the generating capacity exceeds the load demand during short-term dispatching. Step 4.3: Based on the long-term energy balance results in Step 3.2 and the long-term adjustable power calculation model established in Step 4.2, the long-term energy balance is further optimized. The established objective function considering the long-term energy balance is shown below: (15); In Equation (15), the established objective function quantifies the flexibility adjustment resources in the power system, enabling the power system to maintain its long-term power balance within the normal operating range by rationally selecting positive and negative adjustment outputs during long-term dispatch. That is, when the long-term power balance is lower than the power balance under normal operating conditions, positive adjustment output is used; when the long-term power balance is higher than the power balance under normal operating conditions, negative adjustment output is used. In other words, by selecting appropriate flexibility adjustment outputs, the long-term power balance of the power system is maintained within the normal operating range or the risk of severe instability is reduced, thereby stabilizing the operation of the power system. The method can be applied to the Yunnan Provincial Key Research and Development Program project: Research and Application of Key Technologies for Integrated Wind-Solar-Hydro-Storage Access to Yunnan Power Grid and Friendly Interaction with UHVDC (202503AA080001). The operation results are shown in Table 3. Table 3: Optimized Long-Term Power Balance

[0038] From Table 3 and Figure 2 As can be seen, after incorporating the long-term adjustable strength optimization, compared with Table 1, the long-term power balance is at an ideal value in each time period of the long-term scale, verifying that the proposed strategy can significantly improve the power system's adaptability to long-term power deviation.

[0039] Based on the short-term power balance results in step 3.3 and the short-timescale adjustable power calculation model established in step 4.2, the short-term power balance is further optimized. The established objective function considering the short-term power balance is shown in the following formula: (16); In Equation (16), the established objective function quantifies the output of the flexible regulation resources in the power system on a shorter time scale to optimize the short-term power balance. This allows the power system to maintain its short-term power balance within the normal operating range by rationally selecting positive and negative regulation outputs during short-term dispatch. Specifically, when the short-term power balance is lower than the power balance under normal operating conditions, positive regulation output is used; when the short-term power balance is higher than the power balance under normal operating conditions, negative regulation output is used. In other words, by selecting appropriate flexible regulation outputs, the short-term power balance of the power system can be maintained within the normal operating range or the risk of severe instability can be reduced, thereby stabilizing the operation of the power system. The operating results are shown in Table 4. Table 4: Optimized Short-Term Power Balance

[0040] From Table 4 and Figure 3 It can be seen that after short-term power balance optimization, compared with the short-term power balance results at times 3, 4, 5 and 6 in Table 2, the power balance at each time point under the short time scale is significantly improved.

Claims

1. A method for analyzing the balance of electricity supply and demand, characterized in that, Includes the following steps: Step 1: To address the power balance requirements of the power system at different time scales, construct long-term power balance calculation models and short-term power balance calculation models; Step 2: Based on the established long-term power balance calculation model and short-term power balance calculation model, calculate the long-term power balance and short-term power balance of the historical operating data of the power system, and combine the calculation results with the historical operating status of the power system to formulate a stable operation evaluation method for the corresponding time scale. Step 3: Calculate the long-term and short-term power balance of the power system's predicted operating data, predict the possible stable operating range of the power system, and thus determine whether to adjust the output of flexible resources. Step 4: Establish a time-scale adjustable capacity calculation model to calculate the adjustable capacity of the power system's flexibility resources at different times, and then take corresponding adjustment operations based on the predicted stable operation level.

2. The method according to claim 1, characterized in that, In step 1, the power system mainly relies on renewable energy generation, with the aim of promoting the consumption of renewable energy and reducing the consumption of fossil fuels. Therefore, the specific components of this power system mainly include: One wind power station A photovoltaic power station, One hydropower station A thermal power plant There are several energy storage power stations. Among them, wind and solar power stations are the main sources of power output for the system and are given priority to provide clean energy. However, since the output of wind and solar power has certain fluctuations and is not adjustable, its power output needs to be coordinated with hydropower stations, thermal power stations and energy storage power stations to improve the stability and reliability of power and reduce the impact of the fluctuation of wind and solar power output on the stable operation of the power system.

3. The method according to claim 1, characterized in that, In step 1, the specific procedures include: 1.1) Establish a long-term power balance calculation model; 1.2) Establish a short-term power balance calculation model; In 1.1), the established long-term power balance calculation model is shown in equation (1): （1）； Equation (1) comprehensively considers the output, load demand and transmission loss of each generator set in the system to calculate the power balance between the output and load of each generator set in the same period. This refers to the total number of power sources in a power system over a long time period. Internal power balance, It refers to the first A thermal power plant Total power generation during the period It refers to the first A hydropower station Total power generation during the period It refers to the first A photovoltaic power station in Total power generation during the period It refers to the first A wind power station Total power generation during the period It refers to the first A storage power station Total charging volume during the period It refers to the first A storage power station Total discharge during the period This refers to the power system in Total transmission losses during the period This refers to the power system in The total load to be borne during the period; In section 1.2), the short-term power balance calculation model is shown in equation (2): （2）： Equation (2) comprehensively considers the output and load demand of each generator set in the system and calculates the power balance of each generator set output and load at the same time. It refers to the power balance of all power sources in the power system at any given moment on a short time scale. It refers to the first A thermal power plant Power generation at any time It refers to the first A hydropower station Power generation at any given moment It refers to the first A photovoltaic power station Power generation at any time It refers to the first A wind power station Power generation at any given moment It refers to the first Taiwan's energy storage power station Charging power at any time It refers to the first Taiwan's energy storage power station Discharge power at any given time This refers to the power system in The total load that needs to be borne at any given time.

4. The method according to claim 3, characterized in that, In step 2, the specific procedures include: 2.1) Divide the long-term historical operating data of the power system into two equal parts. One part is used to determine the prior distribution, and the other part is used to calculate the posterior probability and determine the classification boundary. 2.2) Based on the long-term power balance calculation results, a long-term stable operation evaluation system is constructed; 2.3) Based on the calculation results of short-term power balance, construct a short-term stable operation evaluation system.

5. The method according to claim 4, characterized in that, In section 2.1), firstly, the historical operating data of the original power system is cleaned to remove obviously missing, duplicate, or abnormal data records. For outliers, reasonable threshold ranges are set for identification and correction to improve data quality. Then, the historical operating data of the power system is divided into two equal parts using random sampling: one part is used as the training set to determine the prior distribution, and the other part is used as the validation set to calculate the posterior probability and determine the classification boundary accordingly. The division process must maintain the same proportion of each class of samples in the two parts to ensure the balance and effectiveness of model training and validation.

6. The method according to claim 4 or 5, characterized in that, In 2.2), for the training set portion divided in 2.1), firstly, long-term scale data is selected, and the long-term power balance result is calculated according to the long-term power balance calculation model in 1.1); then, the long-term power balance calculation result is divided into five types according to the three operating states of the power system: normal operation, mild instability operation, and severe instability operation, and the initial distribution of the five types is determined as shown in equation (3): （3）； In equation (3), This refers to the normal operating state. This refers to a situation where, under mild instability conditions, the total power generation of all power sources exceeds the total load they are required to handle. In this situation, This refers to a situation where, under mild instability conditions, the total power generation of all power sources is less than the total load they are required to handle. In this situation, This refers to a situation where, under severe instability operation, the power generation of all power sources exceeds the total load they are required to handle. This refers to a situation where, under severe instability conditions, the power generation of all power sources is less than the total load they are required to handle. This refers to the mean value of the long-term electrical balance calculation results used for the prior distribution, which is under normal operating conditions. It refers to the standard deviation of the long-term electrical balance calculation results used for the prior distribution, which is under normal operating conditions; It refers to the average value in the long-term power balance calculation results used for a priori distribution, where the power generation of all power sources in a slightly unstable operating state is greater than the total load they need to bear. This refers to the standard deviation of the long-term power balance calculation results used for a priori distributions, where the power generation of all power sources under slightly unstable operating conditions exceeds the total load they are required to bear. It refers to the average value in the long-term power balance calculation results used for a priori distribution, where the power generation of all power sources under slightly unstable operating conditions is less than the total load they need to bear. It refers to the standard deviation of the long-term power balance calculation results used for a priori distribution, where the power generation of all power sources under slightly unstable operating conditions is less than the total load they need to bear. This refers to the average value in the long-term power balance calculation results used for a priori distribution, where the power generation of all power sources under severely unstable operating conditions exceeds the total load they need to bear. It refers to the standard deviation of the long-term power balance calculation results used for a priori distribution when the power generation of all power sources under severe instability operation is greater than the total load they need to bear. This refers to the average value in the long-term power balance calculation results used for a priori distribution, where the power generation of all power sources under severely unstable operating conditions is less than the total load they need to bear. It refers to the standard deviation of the long-term power balance calculation results used for a priori distribution when the power generation of all power sources under severe instability is less than the total load they need to bear. Based on the initial distribution, the boundaries between different operating states are determined. First, the prior probabilities are determined. For all power balance calculation results and corresponding states, the ratio of the power balance calculation result corresponding to each state to all power balance calculation results is calculated. This ratio is used as the prior distribution probability for five types, and is denoted as follows: , , , , ; Then, the likelihood functions for the five types are calculated, and the posterior probabilities are calculated by calling the validation set to update the long-term energy balance calculation results of the classification boundary. Meanwhile, the likelihood probability of this part of the calculation result belonging to each type is calculated, and the calculation formula is shown in equation (4): （4）； Secondly, calculation based on Bayes' theorem The posterior probability for each type is calculated using the formula shown in equation (5): （5）； In equation (5), The result of long-term electrical balance calculation The marginal probability does not need to be calculated during the construction process. Finally, the boundary value between different types is determined, that is, a long-term power balance calculation result is found such that the posterior probability is the same when it is in two adjacent types. Then this power balance calculation result can be used as the boundary value between the two adjacent types. The specific calculation formula is shown in Equation (6): （6）； because No calculation is needed, so we can directly find the answer. time The value is used as the boundary value between adjacent types, and the long-term stable operation evaluation method is shown in Equation (7); （7）； Equation (7) represents the long-term electrical balance. The different intervals in which they are located correspond to the states, states ( This indicates that the power system is in a stable operating state and no adjustment measures are required; state ( This indicates that the power system is in a state of mild instability, requiring the use of flexibility resources to balance the power supply as much as possible; state ( This indicates that the power system is in a state of severe instability and requires emergency measures such as generator shutdown and load shedding. It refers to the critical state between the normal operating state and the mild instability process of a power system. It refers to the critical state between the mild and severe instability processes of a power system. This refers to the long-term power balance. When the value is less than 1, it represents the boundary between a stable operating state and a slightly unstable operating state of the power system. This refers to the long-term power balance. When the value is less than 1, it represents the boundary between a slightly unstable operating state and a severely unstable operating state of the power system. This refers to the long-term power balance. When the value is greater than 1, it represents the boundary between a stable operating state and a slightly unstable operating state of the power system. This refers to the long-term power balance. When the value is greater than 1, it represents the boundary value between the mild and severe instability of the power system.

7. The method according to claim 4 or 5, characterized in that, In section 2.3), the short-term stable operation evaluation system is established as shown in equation (8): （8）； Equation (8) represents the state corresponding to different intervals of short-term power balance. This indicates that the power system is in a stable operating state and no adjustment measures are required; state This indicates that the power system is in a state of mild instability, requiring the use of flexibility resources to restore power balance as much as possible; state This indicates that the power system is in a state of severe instability and requires emergency measures such as generator shutdown and load shedding. This refers to the short-term power balance. When the value is less than 1, it represents the boundary between a stable operating state and a slightly unstable operating state of the power system. This refers to the short-term power balance. When the value is less than 1, it represents the boundary between a slightly unstable operating state and a severely unstable operating state of the power system. This refers to the long-term power balance. When the value is greater than 1, it represents the boundary between a stable operating state and a slightly unstable operating state of the power system. This refers to the long-term power balance. When the value is greater than 1, it represents the boundary value between the mild and severe instability of the power system.

8. The method according to claim 1, characterized in that, In step 3, the specific procedures include: 3.1) Based on meteorological forecast data, runoff forecast data, and load forecast data of the power system's dispatching and operation area, long-term and short-term dispatching of the power system is carried out to obtain predicted operation data of the power system at different time scales. 3.2) Based on the long-term dispatch operation data of the power system, calculate the long-term power balance during the long-term dispatch process, and at the same time, determine the operating state of the power system in each period during the long-term stable operation evaluation system. 3.3) Based on the short-term time-scale dispatch operation data of the power system, calculate the short-term power balance during the short-term time-scale dispatch process, and at the same time, judge the power system operation status at each moment during the short-term time-scale dispatch process based on the short-term stable operation evaluation system. In 3.2), the long-term scale prediction operation data in 3.1) is substituted into the long-term power balance calculation model (1) to obtain the long-term power balance calculation result. The long-term power balance calculation result is then substituted into formula (7) to determine the long-term stable operation result of the power system in each time period under the long-term scale and to clarify the power system operation status in each time period. In 3.3), the short-term time scale predicted operation data in 3.1) is substituted into the short-term power balance calculation model (2) to obtain the long-term power balance calculation result. The long-term power balance calculation result is then substituted into formula (8) to determine the short-term stable operation result of the power system in each time period under the short-term time scale, and to clarify the power system operation status at each moment.

9. The method according to claim 1, 2, 3, 4, 5, or 8, characterized in that, In step 4, the specific procedures include: 4.1) Based on the dispatching operation of the power system on both long-term and short-term time scales, analyze the operating constraints and available output of the thermal power plants and energy storage power plants contained in the power system; 4.2) Based on the operational analysis of thermal power plants and energy storage power plants in 4.1), an adjustable power calculation model is established for different time scales; 4.3) Based on the adjustable power calculation model in 4.2), set a reasonable objective function to optimize the long-term power balance and short-term power balance; In section 4.1), based on the analysis of the long-term and short-term scheduling operation of the power system, the operating characteristics of various adjustable power sources within the power system are further sorted out. The focus is on analyzing the operating constraints of thermal power plants and energy storage power plants under different scheduling cycles. Based on the predicted load, power output and system supply and demand characteristics within the scheduling cycle, the adjustable output range of thermal power plants and energy storage power plants at different time scales is evaluated, and their adjustment capacity boundaries and operational feasibility are clarified. In step 4.2), based on the quantification of the output characteristics of thermal power plants and energy storage power plants at different time scales in 4.1), a calculation model for adjustable output at a long time scale and a calculation model for adjustable output at a short time scale are established, and the operating data of thermal power plants and energy storage power plants are substituted into the model to quantify the adjustable output of the power system at different time scales.

10. The method according to claim 9, characterized in that, In section 4.1), the constraints involved are as follows: The operating constraints of thermal power plants are shown in the following formula: （9）； Equation (9) includes thermal power output constraints, thermal power start-up and shutdown constraints, and thermal power ramping constraints, among which, It refers to a specific moment on a long-term or short-term timescale. It refers to the first The minimum output of a thermal power plant It refers to the first The maximum output of a thermal power plant It refers to the first A thermal power plant The duration of continuous operation at any given moment. It refers to the first A thermal power plant The duration of continuous downtime at any given moment. It refers to the first The shortest operating time for each thermal power unit. It refers to the first The shortest downtime for a thermal power plant. It refers to the first A thermal power plant The on / off state variable at any given time. It refers to the first The rate of downward ramp for a thermal power plant It refers to the first The rate of ascent for a thermal power plant. The time interval at this time scale; The operating constraints of energy storage power stations are shown in the following formula: （10）； Equation (10) includes the energy storage power station capacity constraint, charging and discharging power constraint, charging and discharging state mutual exclusion constraint, and dispatching start and end period power constraint, wherein, It refers to the first A storage power station Remaining capacity at any given time It refers to the first The maximum capacity of an energy storage power station It refers to the first The charging power of an energy storage power station It refers to the first The discharge power of an energy storage power station It refers to the first The upper limit of charging power for an energy storage power station It refers to the first The upper limit of the discharge power of an energy storage power station It refers to the first The charging state variables of an energy storage power station It refers to the first Discharge state variables of an energy storage power station It refers to the first The amount of electricity generated by each energy storage power station at the start of the dispatch cycle. It refers to the first The amount of electricity generated by a single energy storage power station at the end of the dispatch cycle; The power system reserve capacity constraint is shown in the following formula: （11）； In equation (11), , This is the reserve factor for the power system to new energy sources and loads; In section 4.2), the model involved is: The force calculation model that can be adjusted over a long time scale is shown in the following equation: （12）； The force calculation model that can be adjusted on a short time scale is shown in the following equation: （13）； The adjustable force model is shown in equation (14): （14） Equation (14) integrates the flexibility resources within the power system. Based on their operational constraints and response capabilities, and considering the nesting of long-term and short-term resources, the flexibility resources are allocated to different scheduling periods. Therefore, the long-term and short-term power system flexibility resources are quantitatively modeled according to their adjustment characteristics. The calculation results of this adjustable power model can be optimized and adjusted based on the operational constraints of the units in different scheduling periods, thereby changing the power balance level of the power system. Equation (14) represents the short-term positive adjustable power calculation model and the short-term negative adjustable power calculation model, as well as the long-term positive adjustable power calculation model and the long-term negative adjustable power calculation model. This refers to a long-term, positively adjustable output power used to increase long-term electrical balance. This refers to a long-term adjustable reverse force, used to reduce long-term electrical imbalance. This refers to the positive adjustable output of the power system when the total power generation of all power sources is less than the power consumption during long-term dispatching. This refers to the reverse adjustable output power when the power generation of all power sources exceeds the power consumption during long-term dispatching of the power system. This refers to the short-term positive adjustable force, used to increase the short-term power balance; This refers to the ability to adjust the reverse force in the short term to reduce the short-term power imbalance. This refers to the positive adjustable output of the power system when its generating capacity is less than the load demand during short-term dispatching. This refers to the reverse adjustable output of the power system when the generating capacity exceeds the load demand during short-term dispatching. Step 4.3: Based on the long-term energy balance results in Step 3.2 and the long-term adjustable power calculation model established in Step 4.2, the long-term energy balance is further optimized. The established objective function considering the long-term energy balance is shown below: （15）； In Equation (15), the established objective function quantifies the flexibility adjustment resources in the power system, enabling the power system to maintain the long-term power balance within the normal operating range by rationally selecting positive and negative adjustment outputs during long-term dispatch. That is, when the long-term power balance is lower than the power balance under normal operating conditions, positive adjustment output is used, and when the long-term power balance is higher than the power balance under normal operating conditions, negative adjustment output is used. In other words, by selecting appropriate flexibility adjustment outputs, the long-term power balance of the power system is maintained within the normal operating range or the risk of severe instability is reduced, thereby stabilizing the operation of the power system. Based on the short-term power balance results in step 3.3 and the short-timescale adjustable power calculation model established in step 4.2, the short-term power balance is further optimized. The established objective function considering the short-term power balance is shown in the following equation: （16）； In Equation (16), the established objective function quantifies the output of the flexible regulation resources in the power system on a shorter time scale to optimize the short-term power balance. This enables the power system to keep the short-term power balance within the normal operating range by rationally selecting positive and negative regulation outputs during short-term dispatch. Specifically, when the short-term power balance is lower than the power balance under normal operating conditions, positive regulation output is used, and when the short-term power balance is higher than the power balance under normal operating conditions, negative regulation output is used. In other words, by selecting appropriate flexible regulation outputs, the short-term power balance of the power system is kept within the normal operating range or the risk of severe instability is reduced, thereby stabilizing the operation of the power system.

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