Power grid ramping reserve demand evaluation method and device based on scheduling plan time sequence difference

Abstract

The application discloses a power grid climbing reserve demand evaluation method and device based on scheduling plan time sequence difference, and the method comprises the following steps: calculating the climbing increment of the minute-to-minute rolling scheduling plan and the climbing increment of the real-time scheduling plan in the corresponding period, performing minute-level average climbing uncertainty analysis according to the minute-to-minute climbing increment, and determining the climbing adjustment capacity demand curve under normal working conditions; calculating the uncertain distribution of the power generation interruption and the power reduction amount based on the adjacent day-to-day rolling plan; in combination with the contingency reserve demand, the climbing adjustment capacity demand curve under the accident working condition is determined; the climbing adjustment capacity demand under the normal working condition and the climbing adjustment capacity demand under the accident working condition are compared, and the maximum value is taken, so that the system climbing adjustment capacity demand curve is obtained. The application can accurately estimate the climbing reserve demand, is helpful for maintaining the stable operation of power balance in the real-time transaction market, solves the uncertainty of short-term load and avoids the market price soaring, and improves the flexibility of power dispatching operation.

Description

Technical Field

[0001] This invention belongs to the field of power system reserve demand assessment, and relates to the technology of power grid ramp reserve demand analysis and assessment, specifically to a method and device for assessing power grid ramp reserve demand based on scheduling plan timing differences. Background Technology

[0002] In power systems, accurately assessing reserve requirements, especially ramp-up capabilities, is crucial for developing reasonable power dispatch strategies and ensuring the safe operation of the power system.

[0003] In the current power system, based on the output and load forecasts of new energy sources at different time scales, a real-time economic dispatch plan with safety constraints can be calculated every 5 minutes, a rolling dispatch plan every 15 minutes, and a day-ahead short-term reserve every 30 minutes. These day-ahead / rolling / real-time dispatch calculations and adjustments address forecast errors and uncertainties in the power grid. With the increasing integration of new energy sources and the growing volatility and uncertainty of grid-dispatched loads, especially during peak photovoltaic power generation days when a typical deep V-shaped curve is likely to appear, insufficient upward ramping capacity poses a risk of power curtailment during peak load periods. Insufficient downward ramping capacity increases the risk of curtailment of new energy power. The high proportion of new energy integration places higher demands on the system's flexible ramping capability. Accurately estimating ramping reserve demand helps maintain stable power balance in the real-time trading market, resolves short-term load uncertainties, and avoids market price spikes. Traditionally, typical methods for determining ramp-up reserve demand analyze individual uncertainties from aspects such as load forecasting, renewable energy forecasting, and net planned exchange. It is usually difficult to deduce the correlation between various uncertainty components. To address this, this patent proposes a method for deriving the total system scheduling uncertainty at the minute level based on the time-series difference statistics of historical scheduling plans (including historical intraday rolling plans / historical real-time plans). Summary of the Invention

[0004] Purpose of the invention: To address the uncertainty of short-term loads and avoid soaring market prices, this invention proposes a method and apparatus for assessing grid ramp-up reserve demand based on the timing differences of dispatch plans.

[0005] Technical solution: The present invention provides a method for assessing grid ramp-up reserve demand based on scheduling plan timing differences, comprising the following steps:

[0006] (1) Select daily scheduling plan data from the past n years, including intraday rolling data and real-time scheduling plan data; calculate the minute-by-minute ramp increment of the intraday rolling scheduling plan and the minute-by-minute ramp increment of the real-time scheduling plan;

[0007] (2) Based on the incremental climbing speed per minute, perform minute-level average climbing uncertainty analysis to determine the climbing adjustment capacity demand curve under normal operating conditions;

[0008] (3) Based on the daily scheduling plan data of the past n years, by comparing the rolling plans of adjacent days, calculate the uncertain distribution of power generation interruption and deduction based on the rolling plans of adjacent days; combine the emergency reserve demand to determine the ramp adjustment capacity demand curve under the emergency conditions.

[0009] (4) By comparing the ramp adjustment capacity demand under normal operating conditions and the ramp adjustment capacity demand under accident operating conditions, the system ramp adjustment capacity demand curve is obtained, thereby improving the flexibility of power dispatching and operation.

[0010] Furthermore, the implementation process of step (1) is as follows:

[0011] For the target time period [(t+10)min, (t+25)min], the minute-by-minute ramp increment of the intraday rolling plan in historical data is calculated using a 15-minute intraday rolling plan:

[0012]

[0013] Where t represents the target time, (t+10)min represents the time when the first intraday rolling plan is obtained, (t+25)min represents the time when the second intraday rolling plan is obtained, and the calculation interval between the two intraday rolling schedules is 15min; Taking the case created at time t as an example, this represents the energy target of adjustable resources in the second intraday rolling plan. This refers to the energy target of adjustable resources in the first intraday rolling plan, taking the case created at time t as an example. This represents the average minute increment of the daily rolling plan within the target time period [t+10min, t+25min].

[0014] During the target time period [t+10min, t+25min], the energy targets for the three time intervals (t+15)min, (t+20)min, and (t+25)min obtained through a real-time safety-constrained economic scheduling plan that is executed every 5 minutes are as follows: and

[0015] The required ramp increment per minute for the real-time safety-constrained economic scheduling plan over the three time intervals is as follows:

[0016]

[0017]

[0018]

[0019] Furthermore, the implementation process of step (2) is as follows:

[0020] The difference between the ramp rate of the real-time safety-constrained economic dispatch plan and the ramp rate of the intraday rolling dispatch plan represents the uncertainty faced by ramp adjustment in the plan within 10-25 minutes. This uncertainty is driven by the uncertainty of net load increase and the time difference between the intraday rolling dispatch plan and the real-time safety-constrained economic dispatch plan. The random variable ρ with a response time of 10 minutes... 10min The samples can be generated based on the intraday rolling plan and the real-time safety-constrained economic scheduling plan during period T:

[0021]

[0022] γ 10min Given a sample of uncertainties calculated based on historical clearing cases during period T, the required ramp-up adjustment capacity under normal circumstances is:

[0023] RCUPDC normal (r)=SpinVio Cost*Probablity(ρ 10min >γ)

[0024] Among them, RCUPDC normal (r) represents the ramp-up capability demand curve under normal conditions, SpinVio Cost represents the overrun cost, and Probability(ρ) 10min >γ) represents the probability that the difference in 10-minute ramp adjustment capability between the real-time safety constraint economic scheduling plan and the intraday rolling scheduling plan is greater than γ, that is, the probability of running standby violations when the ramp adjustment capability is γ.

[0025] Furthermore, the accident conditions described in step (3) include power generation interruption, generator derating, and net load increase caused by new energy unit failure.

[0026] Furthermore, the implementation process of step (3) is as follows:

[0027] The generation interruption and derating are derived by comparing two intraday rolling plan cases separated by 30 minutes; the total economic maximum limit for all dispatchable uninterrupted resources in the intraday rolling plan is calculated:

[0028]

[0029] in, This represents the maximum economic value of adjustable resources for a rolling intraday plan within the target time period [t+25, t+40], taking the case created at time t as an example.

[0030] For the same set of resources in LAC0, calculate the total economic maximum limit plus the fixed energy in MW:

[0031]

[0032] in, This indicates the maximum economic value of adjustable resources for the intraday rolling plan within the target time period [t+25, t+40], taking the case created at time t as an example. The example given is the case created at time t. For the subsequent time t+30 minutes, the energy target of the adjustable resources in the third intraday rolling plan is as follows:

[0033] Sample values ​​were calculated using the intraday rolling scheduling plan during the historical period T. This sample value is used to calculate the empirical distribution g of the uncertainty of 30-minute power outages and derating. ou,30min Considering only power generation outages, the net reduction in power generation capacity is:

[0034]

[0035] Gou 30min It is based on historical clearing cases. ou,30min The calculated sample;

[0036] Historical data shows ρ 10min and g ou,30min The correlation between the two is very small; ρ 10min +g ou,30min This represents the uncertainty encompassed by contingency reserves plus ramp-up adjustment capacity, under the conditions of generation capacity loss and network ramp-up uncertainty within a 30-minute lead time; ρ 10min +g ou,30min The probability that ρ > 0 is Probablity(ρ 10min +g ou,30min >ρ); then the slope adjustment capacity demand curve taking into account emergency reserves is:

[0037] CRRCUPDC(ρ)=VOLL*Probablity(ρ 10min +g ou,30min >ρ)

[0038] Where CRRCUPDC(ρ) represents the demand curve for contingency reserve plus ramp-up adjustment capacity, VOLL represents the load loss value, and Probablity(ρ) represents the load loss value. 10min +g ou,30min >ρ) represents the probability of load loss when the emergency reserve plus the ramp adjustment capacity is ρ;

[0039] The emergency backup requirement is set as CRRequirement, and the hill-climbing adjustment capacity demand curve under emergency conditions can be expressed as:

[0040] RCUPDC contingency (r)=CRRCUPDC(r+CRRequirement)

[0041] Among them, RCUPDC contingency (r) represents the slope adjustment capacity demand curve under accident conditions.

[0042] Furthermore, the system ramp adjustment capability demand curve RCUPDC in step (4) is as follows:

[0043] RCUPDC(r) = max(RCUPDC) normal (r),RCUPDC contingency (r)).

[0044] Based on the same inventive concept, the present invention provides an apparatus comprising a memory and a processor, wherein:

[0045] Memory is used to store computer programs that can run on a processor;

[0046] The processor is configured to, while running the computer program, execute the steps of the grid ramp-up reserve demand assessment method based on scheduling schedule timing differences as described above.

[0047] Based on the same inventive concept, the present invention provides a storage medium storing a computer program, which, when executed by at least one processor, implements the steps of the power grid ramp-up reserve demand assessment method based on scheduling plan timing differences as described above.

[0048] Beneficial Effects: Compared with existing technologies, the present invention offers the following advantages: It calculates the corresponding minute-by-minute ramp increment based on historical intraday rolling dispatch plans and real-time dispatch plans. It then analyzes the 10-minute ramp uncertainty to obtain the ramp regulation capacity demand curve under normal operating conditions. Based on historical data, it compares intraday rolling plans spaced 30 minutes apart to calculate the uncertainty of 30-minute generation interruptions and depreciation. Combined with emergency reserve requirements, it obtains the ramp regulation capacity demand curve under emergency operating conditions. By combining the ramp regulation capacity demand curves under normal and emergency operating conditions, it obtains the system ramp regulation capacity demand curve, resolving short-term load uncertainty and preventing market price spikes, thus improving the flexibility of power dispatch operations. Furthermore, by analyzing the uncertainty of minute-level ramp increments at different time series in historical n-year intraday rolling dispatch plans and real-time dispatch plans, the present invention obtains ramp regulation demand curves under normal and emergency operating conditions. This avoids the correlation problems that may exist in traditional methods of calculating ramp increments based on load forecasting and renewable energy forecasting, making ramp demand calculations more accurate and providing significant support for the construction of the ramp reserve market. Attached Figure Description

[0049] Figure 1 A flowchart of a method for assessing grid ramp-up reserve demand based on scheduling plan timing differences;

[0050] Figure 2 A flowchart for assessing net load ramping reserve demand under normal operating conditions based on historical intraday rolling and real-time scheduling ramping adjustment difference analysis.

[0051] Figure 3 This is a flowchart illustrating the implementation of net load ramping reserve demand assessment based on historical power generation capacity reduction analysis under accident conditions. Detailed Implementation

[0052] The present invention will now be described in further detail with reference to the accompanying drawings.

[0053] like Figure 1 As shown, this invention proposes a method for assessing grid ramping reserve demand based on the time sequence difference of dispatch plans. First, based on historical (1-3 years) intraday rolling / real-time dispatch plan data, the ramping increment per minute of the intraday rolling dispatch plan and the ramping increment per minute of the real-time dispatch plan are calculated. Then, based on the ramping increment per minute, a 10-minute average ramping uncertainty analysis is performed to determine the ramping regulation capacity demand curve under normal operating conditions. Next, based on historical data, the 30-minute intraday rolling plan is compared to calculate the uncertain distribution of 30-minute generation interruptions and derating, and combined with contingency reserve demand, the ramping regulation capacity demand curve under contingency conditions is determined. Comparing the ramping regulation capacity demand under normal operating conditions and the ramping regulation capacity demand under contingency conditions, the system ramping regulation capacity demand curve is obtained, improving the flexibility of power dispatch operation. Specifically, the method includes the following steps:

[0054] Step 1: Select daily scheduling plan data from the past n years, including intraday rolling data and real-time scheduling plan data; calculate the minute-by-minute ramp increment of the intraday rolling scheduling plan and the minute-by-minute ramp increment of the real-time scheduling plan.

[0055] Obtain historical (1-3 years) intraday rolling / real-time scheduling plan data; based on the historical data, calculate the minute-by-minute ramp increment of the intraday rolling scheduling plan and the minute-by-minute ramp increment of the real-time scheduling plan within the corresponding time period.

[0056] Assuming a historical case is created at time t, the target real-time scheduling interval at time t is [t+5min, t+10min]. Given that day-ahead reserve may take 30 minutes to fully ramp up to the target value, ramp-up reserve needs to manage the uncertainty between t+10min and t+30min. To evaluate the ramp-up reserve demand and demand curve under normal conditions, the net load ramp-up uncertainty between [t+10min, t+30min] needs to be obtained.

[0057] For a daily rolling scheduling plan created at time t, the second interval is [t+10min, t+25min], and the target time is t+25min. There are a total of 3 real-time safety-constrained economic scheduling plans within [t+10min, t+25min].

[0058] Assumption This represents the energy target of adjustable resources in the intraday rolling plan created at time t0, with a target interval of t. RR represents the ramp adjustment capacity per minute, in MW / min.

[0059] For the target time period [t+10min, t+25min], the climbing adjustment capacity per minute calculated using the intraday rolling plan every 15 minutes is:

[0060]

[0061] Where t represents the target time, (t+10)min represents the time when the first intraday rolling plan is obtained, (t+25)min represents the time when the second intraday rolling plan is obtained, and the calculation interval between the two intraday rolling schedules is 15min; Taking the case created at time t as an example, this represents the energy target for adjustable resources (units and adjustable loads, etc.) in the second intraday rolling plan. Taking the case created at time t as an example, this represents the energy target of adjustable resources in the first intraday rolling plan. This represents the average minute increment of the daily rolling plan within the target time period [t+10min, t+25min].

[0062] During the target time periods [t+10min, t+25min], the energy targets for the three time intervals (t+15)min, (t+20)min, and (t+25)min obtained through a real-time safety-constrained economic scheduling plan that is executed every 5 minutes are as follows: and

[0063] The required ramp increment per minute for the real-time safety-constrained economic scheduling plan over three time intervals is as follows:

[0064]

[0065]

[0066]

[0067] Step 2: As Figure 2 As shown, based on the minute-level average climbing uncertainty analysis of the climbing increment per minute, the climbing adjustment capacity demand curve under normal operating conditions is determined.

[0068] The difference between the ramp rate of the real-time safety-constrained economic dispatch plan and the ramp rate of the intraday rolling dispatch plan represents the uncertainty faced by ramp adjustment in the plan within 10-25 minutes. This uncertainty is driven by the uncertainty of net load increase and the time difference between the intraday rolling dispatch plan and the real-time safety-constrained economic dispatch plan. The random variable ρ with a response time of 10 minutes... 10min The samples can be generated based on the intraday rolling plan and the real-time safety-constrained economic scheduling plan during period T:

[0069]

[0070] γ 10min Given a sample of uncertainties calculated based on historical clearing cases during period T, the required ramp-up adjustment capacity under normal circumstances is:

[0071] RCUPDC normal (r)=SpinVio Cost*Probablity(ρ 10min >γ)

[0072] Among them, RCUPDC nomal (r) represents the ramp-up capability demand curve under normal conditions, SpinVio Cost represents the overrun cost, and Probability(ρ) 10min >γ) represents the probability that the difference in 10-minute ramp adjustment capacity between the real-time safety-constrained economic dispatch plan and the intraday rolling dispatch plan is greater than γ, that is, the probability of a violation of standby operation when the ramp adjustment capacity is γ. ρ 10minThe probability that >γ>0 represents the probability that the difference in 10-minute ramp adjustment capability between RT-SCED and LAC is greater than γ. In other words, it is the probability of a violation of standby operation when the ramp capacity RCUP(MW) = γ is cleared.

[0073] Step 3: As Figure 3 As shown, based on the daily scheduling plan data of historical n years, the uncertain distribution of power generation interruption and depreciation based on the rolling plan of adjacent days is calculated by comparing the rolling plan of adjacent days; combined with the emergency reserve demand, the ramp-up regulation capacity demand curve under the emergency condition is determined.

[0074] Based on historical data, the rolling daily plans spaced 30 minutes apart are compared to calculate the uncertain distribution of power generation interruptions and throttling amounts over 30 minutes. Combined with emergency reserve requirements, the ramp-up regulation capacity demand curve under emergency conditions is obtained. The ramp-up regulation capacity demand under normal operating conditions and the ramp-up regulation capacity demand under emergency conditions are compared, and the larger value is taken to obtain the system ramp-up regulation capacity demand curve. The specific process is as follows.

[0075] 1) Calculate the uncertain distribution of power generation interruption and derating amount over 30 minutes.

[0076] In the event of an emergency, ramp-up reserve works in conjunction with contingency reserve to address uncertainties arising from generation interruptions, generator derating, and net load increases. Similar to the net load ramp-up reserve demand assessment method under normal operating conditions, based on historical intraday rolling and real-time dispatch ramp-up adjustment difference analysis, generation interruptions and derating amounts are derived by comparing two intraday rolling plan cases separated by 30 minutes. Assuming the case occurs at 10:50, the first time interval of LAC0 covers [10:45, 11:00]. Because intraday rolling is calculated every 30 minutes, the intraday rolling plan generated 30 minutes earlier at 10:20 also has an interval to cover [10:45, 11:00].

[0077] Then, within the interval Disp set to (t, [t+25, t+40]), the total economic maximum limit for all schedulable uninterrupted resources in the rolling plan for that day can be calculated: Right now:

[0078]

[0079] in, This represents the maximum economic value of adjustable resources for a daily rolling plan within the target time period [t+25, t+40], taking the case created at time t as an example.

[0080] Then, for the same set of resources in LAC0, calculate the total economic maximum limit (if the resources are schedulable in LAC0) plus the fixed energy MW (if the resources are not schedulable in LAC0): LAC0Max. That is:

[0081]

[0082] in This indicates the maximum economic value of adjustable resources for the intraday rolling plan within the target time period [t+25, t+40], taking the case created at time t as an example. The example given is a case created at time t. For the subsequent time t+30 minutes, the energy target of the adjustable resources in the third intraday rolling plan is as follows.

[0083] Sample values ​​can be calculated based on intraday rolling plans based on historical T-periods (e.g., the past 3 years). This sample value can be used to calculate the empirical distribution g of the uncertainty of 30-minute power outages and derating. ou,30min Based on the current situation, considering only power generation shutdowns and the net reduction in power generation capacity:

[0084]

[0085] Gou 30min It is based on historical clearing cases. ou,30min The calculated sample.

[0086] Historical data shows ρ 10min and g ou,30min The correlation between the two is very small. Therefore, according to ρ 10min and g ou,30min Monte Carlo simulations were performed on the historical empirical distribution, and ρ was calculated from 10,000 random samples. 10min +g ou,30min It represents the uncertainty covered by CR+RCUP under the conditions of generation capacity loss and network ramping uncertainty within a 30-minute lead time. ρ 10min +g ou,30min The probability that ρ > 0 represents the off-load probability when CR + RCUP = ρ. The CR + RCUP demand curve (CRRCUPDC) is defined as:

[0087] CRRCUPDC(ρ)=VOLL*Probablity(ρ 10min +g ou,30min >ρ)

[0088] 2) Combining the emergency backup requirements, the slope adjustment capacity demand curve under accident conditions is obtained.

[0089] Assuming the contingency reserve requirement is set to CRRequirement, it can cover approximately 100% of generation interruptions and degradation uncertainties within 30 minutes. The RCUP demand curve under contingency conditions can be represented as:

[0090] RCUPDC contingency (r)=CRRCUPDC(r+CRRequirement)

[0091] Step 4: Compare the ramp adjustment capacity requirements under normal operating conditions and the ramp adjustment capacity requirements under accident operating conditions to obtain the system ramp adjustment capacity requirement curve, thereby improving the flexibility of power dispatching and operation.

[0092] The final RCUP demand curve can be defined as:

[0093] RCUPDC(r) = max(RCUPDC) normal (r),RCUPDC contingency (r)).

[0094] The present invention also provides an apparatus comprising a memory and a processor, wherein: the memory is used to store a computer program capable of running on the processor; and the processor is used to execute, when running the computer program, the steps of the grid ramping reserve demand assessment method based on scheduling plan timing differences as described above.

[0095] The present invention also provides a storage medium storing a computer program, which, when executed by at least one processor, implements the steps of the power grid ramp reserve demand assessment method based on scheduling plan timing differences as described above.

[0096] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0097] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0098] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0099] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0100] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A method for assessing power grid ramp-up reserve demand based on scheduling plan timing differences, characterized in that, Includes the following steps: (1) Select daily scheduling plan data from the past n years, including daily rolling scheduling plan data and real-time scheduling plan data; Calculate the minute-by-minute ramp increment of intraday rolling scheduling plan data and the minute-by-minute ramp increment of real-time scheduling plan data; (2) Based on the minute-level average climbing uncertainty analysis of the climbing increment per minute, determine the climbing adjustment capacity demand curve under normal operating conditions; (3) Based on the daily scheduling plan data of the past n years, calculate the uncertain distribution of power generation interruption and deduction based on the rolling plan of adjacent days by comparing the rolling plan of adjacent days; combine the emergency reserve demand to determine the ramp adjustment capacity demand curve under the emergency condition. (4) Compare the climbing adjustment capacity requirements under normal operating conditions and the climbing adjustment capacity requirements under accident operating conditions to obtain the system climbing adjustment capacity requirement curve; The implementation process of step (1) is as follows: For the target time period The minute ramp increment of the intraday rolling scheduling plan, calculated using a 15-minute intraday rolling scheduling plan, is as follows: in, Indicates the target time. This indicates the time when the first intraday rolling scheduling plan is obtained. This indicates the time when the second intraday rolling scheduling plan is obtained, and the calculation interval between the two intraday rolling scheduling plans is 15 minutes; Indicated by Taking the case of time-based creation as an example, the energy target of adjustable resources in the second intraday rolling scheduling plan, Indicated by Taking the case of time-based creation as an example, the energy target of adjustable resources in the first intraday rolling scheduling plan, Indicates the target time period The average minute ramp increment of the intraday rolling scheduling plan; During the target period The three time intervals obtained through the real-time safety-constrained economic scheduling plan every 5 minutes The energy targets are respectively , and ; The required ramp increment per minute for the real-time safety-constrained economic scheduling plan over the three time intervals is as follows: ； The implementation process of step (2) is as follows: The difference between the ramp rate of the real-time safety-constrained economic scheduling plan and the ramp rate of the intraday rolling scheduling plan represents... The uncertainty faced by ramp-up adjustments within the plan is driven by the uncertainty of net load increase, the time difference between intraday rolling scheduling plans and real-time safety-constrained economic scheduling plans; and a random variable with a response time of 10 minutes. The samples can be based on Generated from the intraday rolling scheduling plan and the real-time safety-constrained economic scheduling plan during the period: yes The sample of uncertain variables calculated based on historical clearing cases during the period; then the required ramp-up adjustment capacity under normal circumstances is: in, This represents the demand curve for ramp adjustment capacity under normal conditions. This indicates over-limit costs. This indicates that the difference in 10-minute ramp-up adjustment capacity between the real-time safety-constrained economic dispatch plan and the intraday rolling dispatch plan is greater than [missing information]. The probability of.

2. The method for assessing grid ramp-up reserve demand based on scheduling plan timing differences according to claim 1, characterized in that, The accident conditions described in step (3) include power generation interruption, generator de-rating, and net load increase caused by new energy unit failure.

3. The method for assessing grid ramp-up reserve demand based on scheduling plan timing differences according to claim 1, characterized in that, The implementation process of step (3) is as follows: By comparing two intraday rolling dispatch plans spaced 30 minutes apart, the generation interruption and derating amounts are derived; the total economic maximum limit for all dispatchable uninterrupted resources in the intraday rolling dispatch plan is calculated. in, Indicated by Taking the case of time-based creation as an example, for the target time period The economic maximum value of adjustable resources in the intraday rolling scheduling plan; for For the same set of resources, calculate the total economic maximum limit plus fixed energy. : in, Indicates Taking the case of time creation as an example, for its subsequent... At that time, during the target time period The economic maximum value of adjustable resources in the intraday rolling scheduling plan. China indicates that Taking the case of time creation as an example, for its subsequent... At that moment, the energy target for adjustable resources in the third intraday rolling scheduling plan; Through history Sample values ​​for intraday rolling scheduling plan calculation during the period This sample value is used to calculate Empirical distribution of uncertainty in power outages and derating Considering only power generation outages, the net reduction in power generation capacity is: in, It is based on historical clearing cases The calculated sample; Historical data and The correlation between the two is very small; This represents the uncertainty covered by emergency reserve plus ramp adjustment capacity, under the conditions of power generation capacity loss and network ramping uncertainty within a 30-minute lead time. The probability is The demand curve for ramp adjustment capacity, taking into account emergency backup, is as follows: in, This represents the demand curve for emergency backup capacity plus hill-climbing adjustment capacity. Indicates the load loss value. This indicates that when the emergency backup capacity plus the hill-climbing adjustment capacity is... The probability of failure at that time; Emergency standby requirements are set to The slope adjustment capacity demand curve under accident conditions can be expressed as: in This represents the slope adjustment capacity demand curve under accident conditions.

4. The method for assessing power grid ramp-up reserve demand based on scheduling plan timing differences according to claim 1, characterized in that, The system's ramp adjustment capability demand curve in step (4) for: 。 5. A device, characterized in that, Includes memory and processor, wherein: Memory is used to store computer programs that can run on a processor; A processor, configured to, while running the computer program, perform the steps of the grid ramp-up reserve demand assessment method based on scheduling plan timing differences as described in any one of claims 1 to 4.

6. A storage medium, characterized in that, The storage medium stores a computer program that, when executed by at least one processor, implements the steps of the power grid ramping reserve demand assessment method based on scheduling plan timing differences as described in any one of claims 1 to 4.

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