Wind power and photovoltaic power fluctuation scheduling optimization method based on credible capacity evaluation

Abstract

The invention discloses a wind power and photovoltaic power fluctuation scheduling optimization method based on credible capacity evaluation, and belongs to the technical field of power systems and control thereof, and the method comprises the following steps: collecting the installed capacity, forced outage rate data, DC power consumption and daily wind power, photovoltaic and load data of a conventional unit for wind power and photovoltaic power generation; the starting capacity of the conventional unit is determined according to the load condition, the original reliability of the power system is evaluated, a calculation sample containing multi-dimensional wind-light load correlation is generated, and the starting capacity of the conventional unit is adjusted to ensure that the difference of reliability indexes of the power system is within a certain error range before and after the wind-light new energy is accessed. Therefore, the credible capacity of the wind and light renewable energy sources is evaluated; and performing scheduling optimization on power fluctuation of wind power and photovoltaic power generation according to the credible capacity. Effective dispatching optimization of wind power and photovoltaic power fluctuation is realized, and powerful support is provided for stable and efficient operation of a power system.

Description

Technical Field

[0001] The present invention relates to the field of power systems and control technologies thereof, and in particular to a dispatch optimization method for wind power and photovoltaic power fluctuations based on credible capacity assessment. Background Art

[0002] At present, human demand for energy is growing. However, the reserves of traditional fossil fuels are decreasing, and their excessive use has aggravated environmental pollution and ecological damage. In this context, renewable energy, mainly wind power and photovoltaics, has attracted much attention due to their clean, low-carbon and renewable characteristics. In China in particular, renewable energy is regarded as a strategic emerging industry, and its installed capacity of wind power and photovoltaics has grown rapidly, making it a leader in the development of renewable energy worldwide. However, due to factors such as wind speed and light intensity, the inherent intermittent and volatile nature of wind power and solar energy has brought new challenges to the stable operation of the power system. This uncertainty complicates the accurate access of these renewable energy sources, thereby affecting the dispatch and operation of the power system.

[0003] In traditional power systems, balancing electricity supply and demand usually relies on traditional energy sources such as thermal power and hydropower. However, with the growth of the proportion of renewable energy, solving the problem of wind power and photovoltaic energy fluctuations has become a key challenge for power system dispatch. Reducing the wind and solar power abandonment rate and improving the utilization efficiency of new energy are important goals for China's renewable energy development. Wind and solar power abandonment not only wastes natural resources, but also affects economic benefits and sustainability. Therefore, optimizing the dispatch of wind and photovoltaic power generation through technical and management means to minimize the wind and solar power abandonment rate has become a pressing issue. Evaluating the value of credible capacity is crucial in this optimization process. Credible capacity refers to the reliable power output of wind and photovoltaic power generation at a specific confidence level. This assessment helps to predict and evaluate the output of these energy sources and enhance the support capacity of power system dispatch.

[0004] Assessing the value of trusted capacity can improve the ability of power system dispatchers to coordinate power resources, thereby enhancing the stability and reliability of the power system. However, current research faces many challenges in accurately predicting renewable energy output. Power system dispatch must also consider load demand, conventional energy output, and energy storage capacity. Combining these factors with trusted capacity assessment to develop optimized dispatch strategies remains a challenge. Summary of the invention

[0005] In order to solve the challenges brought by power fluctuations of wind power and photovoltaic power generation to the stable operation of the power system, the purpose of the present invention is to provide a trusted capacity value assessment technology, which aims to predict the output of renewable energy by analyzing power change data and the scheduling needs of the power system, and to formulate a more reasonable scheduling strategy while considering various power system factors.

[0006] In order to achieve the above technical objectives, the present application provides a dispatch optimization method for wind power and photovoltaic power fluctuations based on credible capacity evaluation, comprising the following steps:

[0007] Collect the installed capacity, forced outage rate data, DC power consumption, and daily wind power, photovoltaic and load data of conventional wind and photovoltaic power generation units, determine the startup capacity of conventional units according to the load conditions, and generate calculation samples containing multi-dimensional wind and photovoltaic load correlations by evaluating the original reliability of the power system;

[0008] Based on the calculation samples, the startup capacity of conventional units is adjusted to ensure that the difference in power system reliability indicators before and after the connection of wind and solar renewable energy is within a certain error range, thereby evaluating the credible capacity of wind and solar renewable energy;

[0009] The power fluctuations of wind power and photovoltaic power generation are dispatched and optimized based on the trusted capacity.

[0010] Preferably, in the process of determining the starting capacity of conventional units, the starting capacity of conventional units is obtained based on the peak load plus the reserve capacity, wherein the system reserve demand originates from the uncertainty of power grid operation, including accident reserve and supply and load reserve.

[0011] Preferably, in the process of adjusting the startup capacity of the conventional units, the startup capacity of the conventional units is adjusted by using the chord cut method.

[0012] Preferably, in the process of optimizing the dispatch of power fluctuations of wind power and photovoltaic power generation, the probability density function of wind power output is expressed as:

[0013]

[0014] Where k and c represent the shape parameter and scale parameter respectively.

[0015] Preferably, in the process of optimizing the dispatch of power fluctuations of wind power and photovoltaic power generation, the probability density function of photovoltaic power generation output is expressed as:

[0016]

[0017] Where P s represents the photovoltaic output, n is the number of samples, h is the bandwidth, P s ,i is a sample of the output power of the photovoltaic power station.

[0018] Preferably, in the process of obtaining the trusted capacity, the trusted capacity is expressed as:

[0019] R t {C0,d t = R t {C1+C c，td t}

[0020] In the formula, R t represents the reliability of the system at time t, and the left side of the equation does not include wind and solar energy systems; C0 refers to the system's conventional unit startup capacity after the backup capacity is set according to the load; d t represents the load of the system at time t, and the right side of the equation is the system after the access of wind and solar energy; C1 is the startup capacity of the conventional units of the system after the access of wind and solar energy; C c-t is the reliable operating capacity of wind and solar energy at time t, C c-t The ratio of the installed capacity of wind and solar energy renewable energy is the reliable operating capacity of wind and solar energy renewable energy at time t.

[0021] Preferably, in the process of evaluating the original reliability of the power system, the model used to evaluate the original reliability of the power system is expressed as:

[0022]

[0023] Where P(g) represents the distribution of system states; Y i is the i-th element of the system state vector; y i is the state of conventional unit i; q i is the forced outage rate of conventional unit i.

[0024] Preferably, in the process of scheduling optimization, the scheduling optimization is performed with minimizing the operating cost of the power system as the objective function, wherein the objective function is expressed as:

[0025]

[0026] In the formula, F i (p) is the cost characteristic function of unit i, F i (p) = aip2 + bip + ci, p is the active output of the unit, ai, bi, ci are given as constants, ST it is the startup cost of unit i in period t.

[0027] Preferably, in the process of obtaining the startup cost of unit i in period t, the startup cost ST it It is expressed as:

[0028]

[0029] In the formula, K i ,B i represents the fixed cost and cold start cost in the unit startup cost, τ i is the thermal time constant of the unit.

[0030] The present invention discloses a dispatch optimization system for wind power and photovoltaic power fluctuations based on credible capacity evaluation, comprising:

[0031] The data acquisition and processing module is used to collect the installed capacity, forced outage rate data, DC power consumption, and daily wind power, photovoltaic and load data of conventional wind power and photovoltaic power generation units, determine the startup capacity of conventional units according to the load conditions, and generate calculation samples containing multi-dimensional wind and photovoltaic load correlations by evaluating the original reliability of the power system;

[0032] The evaluation module is used to adjust the startup capacity of conventional units based on calculation samples to ensure that the difference in power system reliability indicators before and after the connection of wind and solar renewable energy is within a certain error range, thereby evaluating the credible capacity of wind and solar renewable energy;

[0033] The dispatch optimization module is used to optimize the dispatch of power fluctuations of wind power and photovoltaic power generation based on the trusted capacity.

[0034] The present invention discloses the following technical effects:

[0035] The present invention provides more accurate power output forecasts by evaluating the credible capacity of wind power and photovoltaic power generation, thereby enhancing the decision-making ability of power system dispatchers in power resource allocation. At the same time, through credible capacity value evaluation, it optimizes the configuration of spare capacity, reduces energy waste and unnecessary power generation costs caused by inaccurate forecasts, and thus reduces operating costs.

[0036] The present invention improves the utilization efficiency of new energy, reduces the phenomenon of wind and photovoltaic power abandonment by accurately predicting the output power of wind power and photovoltaic power generation, and improves the utilization rate of renewable energy.

[0037] The present invention also provides a more reasonable electricity price strategy for power system operators to ensure the economic benefits of the power system.

[0038] The present invention constructs a comprehensive evaluation framework, combines the power fluctuation data of wind power and photovoltaic power generation with the actual operation requirements of the power system, realizes the effective scheduling optimization of wind power and photovoltaic power fluctuations, and provides strong support for the stable and efficient operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 It is the reliability assessment framework of wind and solar energy operation capacity described in the present invention;

[0041] Figure 2 It is the standby output comparison of the present invention;

[0042] Figure 3 is the power generation cost comparison described in the present invention;

[0043] Figure 4 The output power curve of the present invention is compared

[0044] Figure 5 It is a schematic diagram of the method flow of the present invention. DETAILED DESCRIPTION

[0045] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0046] like Figure 1-5 As shown, the present invention provides a method for optimizing the dispatching of wind power and photovoltaic power fluctuations based on credible capacity value evaluation, constructs a comprehensive evaluation framework, integrates the power change data of wind power and photovoltaic power generation, and combines the actual dispatching needs of the power system to improve the accuracy and efficiency of dispatching, which specifically includes the following processes:

[0047] First, in terms of model construction, detailed data collection and preprocessing were carried out, including the installed capacity of conventional units, forced outage rate data, DC power consumption, and daily wind power, photovoltaic and load data;

[0048] Then, the startup capacity of conventional units is determined according to the load conditions, and the original reliability of the power system is evaluated. A calculation sample containing multi-dimensional wind and solar load correlation is generated, and the startup capacity of conventional units is adjusted by the chord intercept method to ensure that the difference in the reliability index of the power system before and after the connection of wind and solar renewable energy is within a certain error range, thereby accurately evaluating the reliable capacity of wind and solar renewable energy.

[0049] Finally, a case analysis was carried out using historical data from an actual power system. The experimental results show that after considering the trusted capacity value, the dispatch strategy of the power system is more optimized, which effectively reduces energy waste and unnecessary power generation costs, improves the stability and reliability of the system, and provides strong support for the stable and efficient operation of the power system.

[0050] Regarding the model construction mentioned in the present invention:

[0051] Trusted capacity value assessment is an important tool to help power system dispatchers more accurately predict and evaluate wind and solar energy output, thereby enhancing the dispatching capabilities of the power system. Through this assessment, dispatchers can have a deeper understanding of the output of these renewable energy sources and develop more targeted dispatching strategies. These strategies help minimize the waste of wind and solar energy, improve the efficiency of new energy utilization, and enhance the stability of the power system. To illustrate the practical application of this assessment, the present invention takes a wind-solar complementary power system that integrates a large amount of wind power and photovoltaic resources as an example. Ensuring the stability and reliability of the system requires the allocation of backup capacity. However, the intermittent and volatile nature of wind and solar energy introduces significant output uncertainty. In order to accurately measure their trusted capacity, the present invention adopts a reliability assessment framework for the operating capacity of wind and solar renewable energy sources, such as Figure 1 shown.

[0052] First, the present invention reads the original system data, including the installed capacity of conventional units, forced outage rate data, DC power consumption, and daily wind power, photovoltaic and load data in historical data. The starting capacity of conventional units in the original system is determined according to the load conditions, and the reliability of the original system is evaluated. The starting capacity is usually the peak load plus the reserve capacity. The system reserve demand stems from the uncertainty of power grid operation, including unforeseen power grid accidents (accident reserve) and inaccurate supply and demand forecasts (load reserve).

[0053] Next, the present invention generates a calculation sample containing multi-dimensional wind and solar load correlations, and calculates the system reliability after the access of wind and solar energy. By using the chord intercept method to adjust the startup capacity of conventional units, it is ensured that the difference in the reliability index of the power system before and after the access of wind and solar energy is within a certain error range. At this time, the reduction in the operating capacity of conventional units is equivalent to the reliable operating capacity of wind and solar energy. Through this evaluation framework, the present invention can accurately evaluate the reliable capacity of wind and solar energy renewable energy, and provide strong support for the dispatching and operation of the power system.

[0054] In wind power generation systems, the relationship between wind speed and power output is crucial for design and operation considerations. The way wind speed is distributed is crucial for measuring its potential energy, predicting power generation capacity, and optimizing the design and operation of wind farms. Among the various models that characterize wind speed distribution, the two-parameter Weibull distribution stands out because it is suitable for capturing the skewness and long tail characteristics of wind speed data. The probability density function (PDF) of the two-parameter Weibull distribution can be expressed as:

[0055]

[0056] In the formula, k and c represent the shape parameter and scale parameter respectively.

[0057] Nonparametric kernel density estimation (KDE) is a method for estimating probability density functions without making assumptions about the distribution of data. In photovoltaic output prediction or analysis, the present invention can use KDE to estimate the probability density function of photovoltaic output. Based on the theory of nonparametric kernel density estimation, the probability density function f(P s )for:

[0058]

[0059] In the formula, P s represents the photovoltaic output, n is the number of samples, h is the bandwidth, P s,i It is a sample of the output power of a photovoltaic power station.

[0060] In the operation of the power system, reserve refers to the additional power generation capacity reserved to ensure the reliability and stability of the system operation. For new energy sources such as wind and solar energy, their output fluctuates due to natural environmental factors. Determining their operational credible capacity (OCC) is crucial for system scheduling and determination of reserve capacity. Under the premise that the system operation reliability remains unchanged, considering the system operation reserve, the OCC of wind and solar energy at each time point can be defined as the difference between the actual output of wind and solar energy at that time point and the reserve capacity reserved due to uncertain factors. The expression is:

[0061] R t {C0,d t = R t {C1+C c,t ,d t} (3)

[0062] Among them, R t represents the reliability of the system at time t, and the left side of the equation does not include wind and solar energy systems; C0 refers to the system's conventional unit startup capacity after the backup capacity is set according to the load; d trepresents the load of the system at time t, and the right side of the equation is the system after the access of wind and solar energy; C1 is the startup capacity of the conventional units of the system after the access of wind and solar energy; C c-t is the reliable operating capacity of wind and solar energy at time t, C c-t The ratio of the installed capacity of wind and solar energy renewable energy is the reliable operating capacity of wind and solar energy renewable energy at time t.

[0063] The Monte Carlo method based on importance sampling (IS) is an effective calculation method in power system reliability assessment. The reliability model of conventional units is:

[0064]

[0065] Among them, P(g) represents the distribution of system states; Y i is the i-th element of the system state vector; y i is the state of conventional unit i; q i is the forced outage rate of conventional unit i.

[0066] In power system optimization problems, the objective function is usually to minimize the operating cost of the system:

[0067]

[0068] Among them, F i (p) is the cost characteristic function of unit i, F i (p) = aip2 + bip + ci, p is the active output of the unit, ai, bi, ci are given as constants. ST it is the startup cost of unit i in period t:

[0069]

[0070] Among them, K i ,B i Represents the fixed cost and cold start cost in the unit startup cost. τ i is the thermal time constant of the unit.

[0071] For the example verification of the technology provided by the present invention:

[0072] In order to verify the effectiveness of the proposed method, an experimental evaluation was carried out. Figure 2A comparative analysis of power system reserve output is provided, highlighting the impact of considering the trusted capacity value. Significantly, before considering the trusted capacity, the power system reserve output is quite large, having to cope with potential power fluctuations and emergency situations of wind and PV facilities. However, this high reserve output not only increases operating costs but can also hinder system efficiency. By introducing the trusted capacity value, the power system reserve output is optimized. This is attributed to the fact that the trusted capacity assessment model provides a more accurate reflection of the actual generating capacity and reliability of wind and PV plants. System dispatchers can use these assessments to make more precise reserve output arrangements. In addition, Figure 2 The results show that the fluctuations in the reserve output of the power system become more stable after taking into account the trusted capacity. This stability is attributed to the model's ability to predict the power fluctuations of wind and photovoltaic power plants, allowing the system to adjust the reserve output accordingly. This stability helps maintain system operation and enhance its reliability.

[0073] Figure 3 The figure shows the comparison of power generation costs before and after considering the trusted capacity value. As can be seen from the figure, the power generation cost drops significantly after considering the trusted capacity value. By introducing the trusted capacity value assessment, system dispatchers can more accurately predict the actual power generation capacity and reliability of wind power and photovoltaic power plants, which helps to reduce over- or under-dispatch due to inaccurate predictions, thereby reducing unnecessary power generation costs. After considering the trusted capacity value, the system can optimize the reserve output according to the actual power generation capacity of wind power and photovoltaic power plants. This means that when the reliable capacity of wind power and photovoltaic power plants is high, the system can reduce the reserve output, thereby reducing the costs associated with the reserve output. By accurately predicting and dispatching the output of wind power and photovoltaic power plants, the system can manage its resources more efficiently, reduce resource waste and unnecessary conversion losses, thereby improving overall system efficiency and reducing power generation costs. Power fluctuations in wind power and photovoltaic power plants may cause imbalances in system supply and demand, resulting in imbalance costs. The introduction of trusted capacity value helps the system to more accurately predict and respond to these fluctuations, thereby reducing imbalance costs.

[0074] Figure 4 The figure shows the comparison of the power system output power before and after considering the trusted capacity value. It can be seen from the figure that the output power curve of the power system becomes more stable after considering the trusted capacity value. The introduction of the trusted capacity value enables the system to more accurately predict the power output of wind and photovoltaic power plants. Due to various factors such as weather conditions, the power output of wind and photovoltaic power plants is highly volatile. However, by evaluating the trusted capacity value, the system can predict the reliable output range of these power plants, so that their fluctuation characteristics can be better considered in the scheduling process, making the output power curve of the entire system more stable.

[0075] The present invention constructs a comprehensive evaluation framework, combines the power fluctuation data of wind power and photovoltaic power generation with the actual operation requirements of the power system, realizes the effective scheduling optimization of wind power and photovoltaic power fluctuations, and provides strong support for the stable and efficient operation of the power system.

[0076] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0077] In the description of the present invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0078] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A dispatch optimization method for wind power and photovoltaic power fluctuations based on credible capacity assessment, characterized in that: The following steps are involved: Collect the installed capacity, forced outage rate data, DC power consumption, and daily wind power, photovoltaic and load data of conventional wind and photovoltaic power generation units, determine the startup capacity of conventional units according to the load conditions, and generate calculation samples containing multi-dimensional wind and photovoltaic load correlations by evaluating the original reliability of the power system; Based on the calculation sample, the startup capacity of conventional units is adjusted to ensure that the difference in the reliability index of the power system before and after the connection of wind and solar renewable energy is within a certain error range, thereby evaluating the credible capacity of wind and solar renewable energy; According to the trusted capacity, the power fluctuations of wind power and photovoltaic power generation are dispatched and optimized.

2. The dispatch optimization method for wind power and photovoltaic power fluctuation based on credible capacity assessment according to claim 1 is characterized by: In the process of determining the starting capacity of conventional units, the starting capacity of conventional units is obtained based on the peak load plus the reserve capacity, among which the system reserve demand originates from the uncertainty of power grid operation, including accident reserve and supply and load reserve.

3. The dispatch optimization method for wind power and photovoltaic power fluctuation based on credible capacity assessment according to claim 2 is characterized by: In the process of adjusting the startup capacity of conventional units, the startup capacity of conventional units is adjusted by using the chord cut method.

4. The dispatch optimization method for wind power and photovoltaic power fluctuation based on credible capacity assessment according to claim 3 is characterized by: In the process of optimizing the dispatch of wind power and photovoltaic power generation power fluctuations, the probability density function of wind power output is expressed as: Where k and c represent the shape parameter and scale parameter respectively.

5. The dispatch optimization method for wind power and photovoltaic power fluctuation based on credible capacity assessment according to claim 4 is characterized by: In the process of optimizing the dispatch of wind power and photovoltaic power generation power fluctuations, the probability density function of photovoltaic power generation output is expressed as: Where P s represents the photovoltaic output, n is the number of samples, h is the bandwidth, P s ,i is a sample of the output power of the photovoltaic power station, K(u) is the kernel function, which defines how to weight each observation. u is the standardized distance, which measures the relative distance between the estimated point and the observed value.

6. The dispatch optimization method for wind power and photovoltaic power fluctuation based on credible capacity assessment according to claim 5 is characterized by: In the process of obtaining the trusted capacity, the trusted capacity is expressed as: R{C0,d t }=R t {C1+C c，t ,d t } In the formula, R t represents the reliability of the system at time t, and the left side of the equation does not include wind and solar energy systems; C0 refers to the system's conventional unit startup capacity after the backup capacity is set according to the load; d t represents the load of the system at time t, and the right side of the equation is the system after the access of wind and solar energy; C1 is the startup capacity of the conventional units of the system after the access of wind and solar energy; C c-t is the reliable operating capacity of wind and solar energy at time t, C c-t The ratio of the installed capacity of wind and solar energy renewable energy is the reliable operating capacity of wind and solar energy renewable energy at time t.

7. The dispatch optimization method for wind power and photovoltaic power fluctuation based on credible capacity assessment according to claim 6 is characterized by: In the process of evaluating the original reliability of the power system, the model used to evaluate the original reliability of the power system is expressed as: Where P(g) represents the distribution of system states; Y i is the i-th element of the system state vector; y i is the state of conventional unit i; q i is the forced outage rate of conventional unit i.

8. The dispatch optimization method for wind power and photovoltaic power fluctuation based on credible capacity assessment according to claim 7 is characterized by: In the process of dispatch optimization, the dispatch optimization is performed with minimizing the operating cost of the power system as the objective function, wherein the objective function is expressed as: In the formula, F i (p) is the cost characteristic function of unit i, F i (p) = aip2 + bip + ci, p is the active output of the unit, ai, bi, ci are given as constants, ST it is the startup cost of unit i in period t.

9. The dispatch optimization method for wind power and photovoltaic power fluctuation based on credible capacity assessment according to claim 8 is characterized by: In the process of obtaining the startup cost of unit i in period t, the startup cost ST it It is expressed as: In the formula, K i ,B i represents the fixed cost and cold start cost in the unit startup cost, τ i is the thermal time constant of the unit, represents the state quantity related to unit i at time t-1, u it is the control variable of unit i at time t.

10. The dispatch optimization method for wind power and photovoltaic power fluctuation based on credible capacity assessment according to claim 9, characterized in that: The scheduling optimization system for implementing the scheduling optimization method comprises: The data acquisition and processing module is used to collect the installed capacity, forced outage rate data, DC power consumption, and daily wind power, photovoltaic and load data of conventional wind power and photovoltaic power generation units, determine the startup capacity of conventional units according to the load conditions, and generate calculation samples containing multi-dimensional wind and photovoltaic load correlations by evaluating the original reliability of the power system; An evaluation module is used to adjust the startup capacity of conventional units based on the calculation samples to ensure that the difference in reliability indicators of the power system before and after the connection of wind and solar renewable energy is within a certain error range, thereby evaluating the credible capacity of wind and solar renewable energy; The scheduling optimization module is used to optimize the scheduling of power fluctuations of wind power and photovoltaic power generation according to the trusted capacity.

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