Typical operation mode automatic generation system

Abstract

The invention discloses a typical operation mode automatic generation system which comprises an initial operation mode acquisition module, a typical power grid operation mode compilation target setting module, a typical power grid operation mode adjustment principle generation module and a typical power grid operation mode compilation module. According to the invention, on the premise that the safety is guaranteed, the section transmission capacity and economy are obviously improved, sufficient adjustable space is reserved for new energy consumption, and a systematized and intelligent solution is provided for safe and economical operation of a novel power system.

Description

Technical Field

[0001] This invention relates to the field of power, specifically to an automatic generation system for typical operating modes. Background Technology

[0002] With the increasing integration of renewable energy into the grid and the deepening of power market reforms, the operation of modern power grids is becoming increasingly complex, placing higher demands on the scientific rigor, efficiency, and adaptability of operation mode formulation methods. Traditional power grid operation mode formulation relies heavily on manual experience, determining the final solution through trial and error and repeated verification. This method is not only time-consuming and labor-intensive but also struggles to achieve systematic coordination and quantitative trade-offs among multiple objectives such as safety, economy, availability, and adjustability. Specifically, traditional methods often focus on meeting the most basic safety constraints, while lacking comprehensive optimization capabilities in areas such as improving cross-sectional transmission capacity, reducing grid losses, adapting to renewable energy fluctuations, and reserving adjustment margins for dispatch operations. These methods are no longer adequate to meet the diverse demands of new power systems for operational flexibility, economy, and reliability.

[0003] Therefore, there is an urgent need for an intelligent programming strategy that can coordinate multiple objectives and has closed-loop optimization capabilities, so as to significantly improve the economy, renewable energy absorption capacity and operational regulation flexibility of the power grid while ensuring its safe and stable operation, and provide key technical support for the safe, efficient and flexible operation of the new power system. Summary of the Invention

[0004] The purpose of this invention is to provide an automatic generation system for typical operating modes, including an initial operating mode acquisition module, a typical power grid operating mode compilation target setting module, a typical power grid operating mode adjustment principle generation module, and a typical power grid operating mode compilation module;

[0005] The initial operation mode acquisition module obtains the cross section with the largest duration over the past year as the initial power grid operation mode.

[0006] The typical power grid operation mode compilation target setting module takes safety, economy, adjustability and availability as compilation targets, and constructs a multi-objective collaborative optimization framework;

[0007] The typical power grid operation mode adjustment principle generation module is used to generate typical power grid operation mode adjustment principles;

[0008] The typical power grid operation mode compilation module uses the adjustment principle of typical power grid operation mode as a constraint to solve a multi-objective collaborative optimization framework and output a typical power grid operation mode that meets the compilation objective.

[0009] Furthermore, safety is constrained by the condition of passing N-1;

[0010] Economic efficiency is achieved by minimizing network loss rate;

[0011] The adjustability is designed to maximize the capacity of conventional regulated power supplies to absorb new energy sources, and the frequency, voltage and tie-line adjustment margins are set to be greater than the preset values.

[0012] Availability is targeted at maximizing both generator output capacity and grid transmission capacity. Grid transmission capacity is calculated using PTDF (Power Grid Diversion Calculation).

[0013] Furthermore, network loss rate ; Total active power loss across the entire network; This is the reference power.

[0014] Furthermore, power grid transmission capacity ; For the generator set generalized node in the sending-end control area; For the generalized node of the load in the controlled area at the receiving end; The power generated by the generator in the sending-end control area, The power consumed by the load in the controlled area at the receiving end.

[0015] Furthermore, the multi-objective collaborative optimization framework includes constraints and objective functions;

[0016] The constraints of the multi-objective collaborative optimization framework are N-1 safety check constraints;

[0017] The multi-objective collaborative optimization framework aims to maximize the overall score.

[0018] The overall score is a weighted sum of availability, adjustability, and cost-effectiveness indicators;

[0019] Availability indicators are determined by the generator set's output capacity and the grid's transmission capacity; economic indicators are determined by the grid loss rate; and adjustability is determined by the conventional regulating power source's ability to absorb new energy sources and the frequency, voltage, and tie-line regulation margin.

[0020] Furthermore, the principles for adjusting typical power grid operation modes include prioritizing hydropower during the high-water season, prioritizing regulation capacity, maintaining equal incremental rates and economic distribution, uniformly distributing reserves, reserving margins in heavily loaded areas, and appropriately opening the ring network.

[0021] Furthermore, the principle of prioritizing hydropower during the high-water season means that during the high-water season or peak hydropower generation season, hydropower has a higher priority than other types of generators.

[0022] The principle of prioritizing regulation capacity means that, on the basis of meeting load demand, the starting priority of thermal power units is determined according to the size of their regulation capacity; the greater the regulation capacity, the higher the starting priority.

[0023] The principle of uniform incremental rate and economic distribution means that, under the premise of meeting safety constraints, the output of all online units is uniform and the incremental rate of coal consumption tends to be consistent.

[0024] The principle of uniform distribution of backup means that when arranging equipment for power outage maintenance or as cold backup, the equipment for power outage maintenance or as cold backup should be evenly distributed geographically and electrically.

[0025] The principle of reserve capacity in heavily loaded areas means that for critical transmission sections in heavily loaded areas, the reserved reserve capacity should be greater than 20% of the maximum capacity.

[0026] The principle of appropriately unblocking the loop network means minimizing the number of electromagnetic loops while ensuring N-1 safety.

[0027] Furthermore, the adjustment capability of thermal power units includes the size of the output range and the rate of ramp-up.

[0028] Furthermore, when the typical power grid operation mode compilation module solves the multi-objective collaborative optimization framework, it takes the initial power grid operation mode as the starting point and the maximum power grid transmission capacity as the objective, and uses the SC-OPF solver to generate generator output combinations.

[0029] Furthermore, when using the SC-OPF solver to solve for the maximum grid transmission capacity, after each generator output combination is generated, power flow calculation is performed and a feasibility judgment is made. Generator output combinations that are not feasible are deleted. Feasibility means that the power flow of all lines is within the safety limit, the output of all generators is within the allowable range, and the power is balanced.

[0030] If the grid's transmission capacity cannot be increased without exceeding the line's output limit, the solver will stop calculating and report the results.

[0031] The technical effects of this invention are undeniable. Under the premise of ensuring safety, this invention can significantly improve the cross-sectional transmission capacity and economy, and reserve sufficient adjustable space for the consumption of new energy sources, providing a systematic and intelligent solution for the safe and economical operation of new power systems. Attached Figure Description

[0032] Figure 1 Generate strategies for typical operating modes. Detailed Implementation

[0033] The present invention will be further described below with reference to embodiments, but it should not be construed that the scope of the present invention is limited to the following embodiments. Various substitutions and modifications made based on ordinary technical knowledge and common practices in the art without departing from the above-described technical concept of the present invention should be included within the scope of protection of the present invention.

[0034] Example 1:

[0035] The typical operation mode automatic generation system includes an initial operation mode acquisition module, a typical power grid operation mode compilation target setting module, a typical power grid operation mode adjustment principle generation module, and a typical power grid operation mode compilation module;

[0036] The initial operation mode acquisition module obtains the cross section with the largest duration over the past year as the initial power grid operation mode.

[0037] The typical power grid operation mode compilation target setting module takes safety, economy, adjustability and availability as compilation targets, and constructs a multi-objective collaborative optimization framework;

[0038] The typical power grid operation mode adjustment principle generation module is used to generate typical power grid operation mode adjustment principles;

[0039] The typical power grid operation mode compilation module uses the adjustment principle of typical power grid operation mode as a constraint to solve a multi-objective collaborative optimization framework and output a typical power grid operation mode that meets the compilation objective.

[0040] Example 2:

[0041] The typical operation mode automatic generation system has the same technical content as Example 1, but with the safety constraint being N-1 qualification.

[0042] Economic efficiency is achieved by minimizing network loss rate;

[0043] Adjustability is designed to maximize the capacity of conventional regulating power sources to absorb renewable energy, with frequency, voltage, and tie-line regulation margins exceeding preset values. Renewable energy absorption capacity equals the ratio of actual absorbed renewable energy to total renewable energy generation. Frequency regulation margin equals the ratio of adjustable frequency capacity to net load fluctuation. Voltage regulation margin equals the ratio of adjustable reactive power capacity to voltage deviation demand. Tie-line regulation margin is the ratio of adjustable tie-line transmission capacity to planned fluctuation.

[0044] Availability is targeted at maximizing both generator output capacity and grid transmission capacity. Grid transmission capacity is calculated using PTDF (Power Grid Diversion Calculation).

[0045] Example 3:

[0046] The system automatically generates typical operating modes, with technical content identical to any one of Examples 1-2. Furthermore, it includes network loss rate. ; Total active power loss across the entire network; This is the reference power.

[0047] Example 4:

[0048] The system for automatically generating typical operating modes has the same technical content as any one of Examples 1-3, and further includes power grid transmission capacity. ; For the generator set generalized node in the sending-end control area; For the generalized node of the load in the controlled area at the receiving end; The power generated by the generator in the sending-end control area, The power consumed by the load in the controlled area at the receiving end.

[0049] Example 5:

[0050] The typical operation mode automatic generation system has the same technical content as any one of Examples 1-4. Furthermore, the multi-objective collaborative optimization framework includes constraints and objective functions.

[0051] The constraints of the multi-objective collaborative optimization framework are N-1 safety check constraints;

[0052] The multi-objective collaborative optimization framework aims to maximize the overall score.

[0053] The overall score is a weighted sum of availability, adjustability, and cost-effectiveness indicators;

[0054] Availability is determined by the generator's output capacity and the grid's transmission capacity; economic efficiency is determined by the grid loss rate; and adjustability is determined by the conventional regulating power source's ability to absorb new energy sources, as well as the frequency, voltage, and tie-line regulation margin. Specifically, availability is positively correlated with generator output capacity and grid transmission capacity; for example, a weighted sum or average of these two capacities can be used as the availability index. Economic efficiency is negatively correlated with the grid loss rate; for example, economic efficiency = 1 - grid loss rate, where the grid loss rate ranges from 0 to 100%. Adjustability is a weighted average of the conventional regulating power source's ability to absorb new energy sources, as well as the frequency, voltage, and tie-line regulation margin.

[0055] The overall score is as follows:

[0056]

[0057] In the formula, , , These are indicators of availability, adjustability, and cost-effectiveness.

[0058] Example 6:

[0059] The typical operation mode automatic generation system has the same technical content as any one of Examples 1-5. Furthermore, the adjustment principles of the typical power grid operation mode include the principle of prioritizing hydropower during the high-water season, the principle of prioritizing regulation capacity, the principle of equal incremental rate and economic distribution, the principle of uniform distribution of reserves, the principle of margin reservation in heavy load areas, and the principle of appropriately opening the ring network.

[0060] Example 7:

[0061] The typical operation mode automatic generation system has the same technical content as any one of Examples 1-6. Furthermore, the principle of prioritizing hydropower during the high-water season means that during the high-water season or the season with the largest hydropower generation, the priority of hydropower input is greater than that of other types of generators.

[0062] The principle of prioritizing regulation capacity means that, on the basis of meeting load demand, the starting priority of thermal power units is determined according to the size of their regulation capacity; the greater the regulation capacity, the higher the starting priority, that is, among thermal power units, those with strong regulation capacity are started first.

[0063] The principle of uniform incremental rate and economic distribution means that, under the premise of meeting safety constraints, the output of all online units is uniform and the incremental rate of coal consumption tends to be consistent.

[0064] The principle of uniform distribution of backup means that when arranging equipment for power outage maintenance or as cold backup, the equipment for power outage maintenance or as cold backup should be evenly distributed geographically and electrically.

[0065] The principle of reserve capacity in heavily loaded areas means that for critical transmission sections in heavily loaded areas, the reserved reserve capacity should be greater than 20% of the maximum capacity.

[0066] The principle of appropriately unblocking the loop network means minimizing the number of electromagnetic loops while ensuring N-1 safety.

[0067] Example 8:

[0068] The typical operation mode automatic generation system has the same technical content as any one of Examples 1-7. Furthermore, the adjustment capability of the thermal power unit includes the output range and the climbing rate.

[0069] Example 9:

[0070] The typical operation mode automatic generation system has the same technical content as any one of embodiments 1-8. Furthermore, when the typical power grid operation mode compilation module solves the multi-objective collaborative optimization framework, it takes the initial power grid operation mode as the starting point and the maximum power grid transmission capacity as the objective, and uses the SC-OPF solver to generate generator output combinations.

[0071] Example 10:

[0072] The typical operation mode automatic generation system has the same technical content as any one of Examples 1-9. Further, when using the SC-OPF solver to solve for the maximum power grid transmission capacity, after generating each generator output combination, power flow calculation is performed and a feasibility judgment is made. Generator output combinations that are not feasible are deleted. Feasibility means that the power flow of all lines is within the safety limit, the output of all generators is within the allowable range, and the power is balanced.

[0073] If the grid's transmission capacity cannot be increased without exceeding the line's output limit, the solver will stop calculating and report the results.

[0074] Example 11:

[0075] The system automatically generates usage instructions for typical operating modes, including the following steps:

[0076] First, a multi-objective collaborative optimization framework was established, with security as the hard constraint and economy, availability, and adjustability as the core. Each objective was quantified into a weighted comprehensive utility function and sub-indicator limits. Second, human expert experience was innovatively introduced and digitized into efficient adjustment principles to guide the optimization algorithm in exploring the direction of fastest improvement in indicators. Subsequently, a closed-loop optimization process based on historical data initialization and small-step iterative adjustments was designed. For the four objectives, definitions and calculation methods based on N-1 verification, PTDF / SC-OPF, network loss sensitivity analysis, and adjustment margin configuration were given. Finally, the effectiveness of the proposed strategy was verified through a case study of a provincial power grid. The results show that this method can significantly improve the cross-sectional transmission capacity and economy while ensuring safety, and reserves sufficient adjustability space for renewable energy consumption, providing a systematic and intelligent solution for the safe and economical operation of new power systems.

[0077] The objectives for developing typical operating modes are as follows:

[0078] Security:

[0079] To ensure the safety and stability of the power grid, except for reasons such as structural defects in the power grid, N-1 must be qualified.

[0080] Economic efficiency:

[0081] Minimize line losses (excluding the electricity market).

[0082] Adjustability:

[0083] Without considering energy storage, the goal is to maximize the capacity of conventional regulating power sources to absorb new energy sources, while ensuring sufficient margins in frequency, voltage, and tie-line regulation.

[0084] Availability:

[0085] Maximize the power generation capacity of the generator set and the grid transmission capacity.

[0086] 1. Security: N-1 security check is directly adopted, and the calculation result is pass / fail, which is a hard constraint.

[0087] 2. Economic efficiency: The level of energy loss and operating cost control in the process of power grid transmission and distribution.

[0088] algorithm:

[0089] Network loss rate: The total active power loss of the entire network is obtained through power flow calculation, \\sum\\Delta P, and the network loss rate r = (\\sum\\Delta P / P_{supply}) \\times 100\\.

[0090] Unit electricity purchase cost: Total cost / Total purchased electricity. In optimization, the generation cost can be indirectly minimized through the equal incremental rate criterion or market price ranking.

[0091] 3. Availability:

[0092] Define the “sending-end control area (Area_S)” and the “receiving-end control area (Area_R)”: For example, Area_S is the generator set generalized node, and Area_R is the load generalized node.

[0093] Identifying "Transmission Sections": Through PTDF analysis, a set of lines, such as {L1, L2, L3, L4}, is identified. When power flows from Area_S to Area_R, the power flow increment of this set of lines accounts for the largest portion of the increment from S to R. These lines collectively constitute a transmission section. We call this set Critical_Interface_Lines. PDDF performs a first-order Taylor expansion on the power flow calculation, linearizing the calculation process to improve efficiency.

[0094] Calculate the maximum transmission capacity of the cross-section: Under the premise of satisfying all safety constraints, how much power max (P_transfer) can Area_S transmit to Area_R at most?

[0095] Objective Function:

[0096] Maximize P_transfer = (ΣP_Gi for i in Area_S) - (ΣP_Di for i inArea_S)

[0097] This formula directly calculates the total power generated by all generators within Area_S, subtracts the total power consumed by all loads within Area_S, and what remains is the power that must be sent outside through the cross-section.

[0098] Construct the SC-OPF solver. Its operation can be described as follows:

[0099] 1) The solver starts from an initial, feasible running point (such as the typical approach from the previous year). At this point, P_transfer may be a small value (such as 3000MW).

[0100] 2) The solver's goal is to maximize P_transfer. It will try various methods to increase the net output of Area_S (for example, to make the coal-fired power units in Area_S generate more power).

[0101] 3) Simulation Verification: Each time a new generator output combination is tried, the solver immediately performs a power flow calculation (this is an internal step of SC-OPF) to check:

[0102] Are the power flow P_l of all lines within the safety limits?

[0103] Are all generator outputs within permissible limits?

[0104] Has the power been kept balanced?

[0105] 4) Constraint Activation: As P_transfer increases, we will find that the power flow P_L3 of a certain line (such as L3) within the section reaches its safe limit F_lim_L3 first. At this point, if we forcibly increase P_transfer again, P_L3 will exceed the limit, and the solution becomes infeasible.

[0106] Availability:

[0107] 5) Judgment: The solver found that no matter how it adjusted the output of other generators within Area_S, it could not continue to increase P_transfer without causing L3 to exceed its limit. The L3 line became the bottleneck line (BindingConstraint) or the weakest link.

[0108] 6) Reaching the endpoint: The solver stops calculating and reports the results. The corresponding P_transfer value at this point is the maximum transmission capacity P_transfer_max of that section under the current power grid structure and safety criteria.

[0109] 4. Adjustability: Adjustment margin and speed of the generator set.

[0110] Calculate the net load for the past year: P_NetLoad(t) = P_D_actual(t) - P_RES_actual(t). This is the "rigid" load in the power grid that must be borne by conventional power sources and tie lines.

[0111] Net Load Ramp: ΔP_NetLoad(t) = P_NetLoad(t) - P_NetLoad(t-1). The sign and magnitude of this value directly reflect the amount of power that needs to be increased or decreased.

[0112] Increase demand: When ΔP_NetLoad(t) >> 0 (net load increases sharply), a large increase in reserve is required.

[0113] Reduce demand: When ΔP_NetLoad(t) << 0 (net load drops sharply), a large amount of reserve needs to be reduced.

[0114] Statistical Analysis and Pattern Recognition:

[0115] Calculations: Statistical analysis of the maximum value and 95th percentile of ΔP_NetLoad over the past year, the maximum and minimum power of curtailed solar power and wind power, and the maximum and minimum upward and downward adjustment rates over the past year.

[0116] Forecast the load for the next year and calculate the above indicators.

[0117] By weighting historical data (including curtailed solar power output in historical indicators) and future indicators, the required regulatory demand for the proposed method is derived.

[0118] Overall Indicators:

[0119] The above availability, adjustability, and economic indicators are weighted and averaged to obtain the result.

[0120] 2. Adjustment strategies

[0121] Layer 1: Topology and Backup Decisions (The Skeleton & Fortress)

[0122] The goal of this layer is to answer a fundamental question: "What is the basic structure of the power grid? Which components are operational and which are on standby?"

[0123] Follow these principles

[0124] Principle 1: Electromagnetic Loop Decoupling: Prioritize decoupling unnecessary electromagnetic loops to form a clear radial network. This directly defines the main power flow paths of the power grid and is the most powerful means to improve availability (simplifying power flow and clarifying responsibilities) and security (preventing disordered power flow transfer after N-1).

[0125] Principle 2: Reserve backup lines in heavily loaded areas: When configuring transmission modes, it is essential to consciously ensure that the power flow of critical transmission sections (such as the "West-to-East Power Transmission" channel) is far from its safety limit, and to clearly designate 1-2 lines as "hot backups". This directly defines the upper limit of system availability and safety margin.

[0126] Principle 3: Maintenance and Alternative Plans: When scheduling equipment shutdowns, adhere to the principle of "uniform electrical distance distribution" to ensure that no power supply island or defense vacuum is created due to maintenance in one area. This defines the system's resilience to Nk (k>1) faults or planned failures beyond N-1.

[0127] Second layer: Adjustment capability configuration (The Buffer & Response Force)

[0128] After the first layer defines the "skeleton," the next step is to "configure the muscle and nerve response system" for this skeleton.

[0129] Core task: Based on load forecasts and renewable energy generation forecasts for the future (tomorrow, next week, next month), calculate the maximum upward / downward demand that the system may face.

[0130] Method: Analyze net load fluctuations in historical data and combine them with future forecasts to calculate forward-looking reserve demand.

[0131] Increased margin: Ensure that in the worst-case scenario of "new high load + sharp drop in renewable energy", there are enough units to quickly increase power output.

[0132] Reduce margin: Ensure that in the worst-case scenario of "new low load + large generation of new energy", there are enough units (especially hydropower and gas turbines) that can perform deep peak shaving or shutdown to make room for new energy.

[0133] The third layer: Economic fine-tuning (The Fine-Tuning)

[0134] Core task: Within the "big framework" of the network topology determined by the first layer and the power-on mode and backup configuration determined by the second layer, minimize our defined EDI index by fine-tuning generator output and switching reactive power compensation equipment.

[0135] At this point, the problem has been greatly simplified.

[0136] The number of control variables has been reduced: the number of generators that need to be optimized is fixed (the second layer is already determined), and their output range is also limited (downward / upward adjustment margins need to be considered).

[0137] The objective is singular and clear: only the economic objective of EDI remains.

[0138] An approximate linearization method is employed: optimization within this "framework" significantly reduces nonlinearity, iterating using gradient descent following the sequence of "first-order Taylor expansion -> sensitivity calculation -> small-step adjustment -> verification." Because the adjustments at this stage are merely "fine-tuning," it's unlikely that they will immediately undermine the safety foundation established by the first and second layers.

[0139] 4. Principles for Adjusting Power Grid Operation Mode (This section corresponds to step 4 in the overall process)

[0140] Principle 1 (Prioritize Hydropower During High Water Season): "During high water season or peak hydropower generation season, put as many hydropower units into operation as possible."

[0141] Principle 2 (Priority of Adjustment Capability): "On the basis of meeting load demand, priority should be given to starting thermal power units with strong adjustment capabilities (wide output range, rapid ramp-up)."

[0142] Principle 3 (Equal incremental rate and economic distribution): "Under the premise of meeting safety constraints, the output of all online units should be as uniform as possible, and their incremental rate of coal consumption should be consistent."

[0143] Principle 4 (Even Distribution of Backup): "When arranging equipment outages for maintenance or as cold backups, they should be distributed as evenly as possible geographically and electrically."

[0144] Principle 5 (Margin Reserve for Heavy-Load Areas): "Sufficient reserve capacity must be reserved for critical transmission sections in heavy-load areas."

[0145] Principle 6 (Appropriately Unlock the Loop Network): "Under the premise of satisfying N-1 safety, appropriately unlock the electromagnetic loop network."

[0146] This study takes a provincial power grid in China (containing approximately 500 nodes and 100 main generating units) as the research object. The typical business scenario is "power transmission from western hydropower bases to eastern load centers." Comparison methods include: (A) traditional manual experience-based compilation method; (B) pure mathematical optimization algorithm without expert rules; and (C) the human-machine collaborative strategy proposed in this paper.

[0147] Results Analysis

[0148] Transmission capacity enhancement: Method (C), through SC-OPF optimization, increases the transmission limit of the main section of the "West-to-East Power Transmission" project from 7800MW in Method (A) to 9100MW, an increase of 16.7%, while ensuring safety. Compared with Method (B), the convergence speed of the method in this paper is improved by about 40% due to expert rule guidance.

[0149] Economic Improvement: Under the same transmission power, the network loss rate of method (C) is reduced by 0.25 percentage points compared with method (A), resulting in an annualized energy saving of approximately 120 million kWh. This is attributed to the full utilization of loss-sensitive lines by the "direct-connection regulation" principle.

[0150] Enhanced adjustability: Method (C) proactively configures a high proportion of reserve capacity (up to 70% during peak periods) for the scenario of large-scale new energy generation, which increases the annual new energy consumption rate in the region from 95.1% in Method (A) to 98.5%, exceeding the national consumption target.

[0151] Computational efficiency: Method (C) takes about 45 minutes for a single full-process calculation, which is much shorter than the nearly 3 hours of Method (B), thus meeting the requirements for practical engineering application.

[0152] This paper addresses the new requirements of modern power systems for grid operation mode planning, proposing an intelligent planning strategy that integrates multi-objective optimization, human-machine collaboration, and forward-looking prediction. This strategy effectively solves challenges such as multi-objective trade-offs and excessive computational complexity by quantifying objectives, solidifying expert experience, and designing an efficient iterative process. Case studies demonstrate that this method can significantly improve the grid's transmission capacity, economy, and renewable energy absorption, providing strong intelligent support for dispatching decisions.

Claims

1. A system for automatically generating typical operating modes, characterized in that: It includes an initial operation mode acquisition module, a typical power grid operation mode compilation target setting module, a typical power grid operation mode adjustment principle generation module, and a typical power grid operation mode compilation module; The initial operation mode acquisition module obtains the cross section with the largest duration over the past year as the initial power grid operation mode. The typical power grid operation mode compilation target setting module takes safety, economy, adjustability and availability as compilation targets, and constructs a multi-objective collaborative optimization framework; The typical power grid operation mode adjustment principle generation module is used to generate typical power grid operation mode adjustment principles; The typical power grid operation mode compilation module uses the adjustment principle of typical power grid operation mode as a constraint to solve a multi-objective collaborative optimization framework and output a typical power grid operation mode that meets the compilation objective.

2. The typical operation mode automatic generation system according to claim 1, characterized in that: Safety is contingent upon meeting N-1 requirements; Economic efficiency is achieved by minimizing network loss rate; The adjustability is designed to maximize the capacity of conventional regulated power supplies to absorb new energy sources, and the frequency, voltage and tie-line adjustment margins are set to be greater than the preset values. Availability is aimed at maximizing the output capacity of generator sets and the transmission capacity of the power grid.

3. The typical operation mode automatic generation system according to claim 2, characterized in that: Network loss rate ; Total active power loss across the entire network; This is the reference power.

4. The typical operation mode automatic generation system according to claim 2, characterized in that: Power grid transmission capacity ; For the generator set generalized node in the sending-end control area; For the generalized node of the load in the controlled area at the receiving end; The power generated by the generator in the sending-end control area, The power consumed by the load in the controlled area at the receiving end.

5. The typical operation mode automatic generation system according to claim 1, characterized in that: A multi-objective collaborative optimization framework includes constraints and objective functions; The constraints of the multi-objective collaborative optimization framework are N-1 safety check constraints; The multi-objective collaborative optimization framework aims to maximize the overall score. The overall score is a weighted sum of availability, adjustability, and cost-effectiveness indicators; Availability indicators are determined by the generator set's output capacity and the grid's transmission capacity; economic indicators are determined by the grid loss rate; and adjustability is determined by the conventional regulating power source's ability to absorb new energy sources and the frequency, voltage, and tie-line regulation margin.

6. The typical operation mode automatic generation system according to claim 1, characterized in that: Typical power grid operation adjustment principles include the principle of prioritizing hydropower during the high-water season, the principle of prioritizing regulation capacity, the principle of equal incremental rate and economic distribution, the principle of uniform reserve distribution, the principle of reserving margin in heavy-load areas, and the principle of appropriately opening the ring network.

7. The typical operation mode automatic generation system according to claim 6, characterized in that: The principle of prioritizing hydropower during the high-water season means that during the high-water season or peak hydropower generation season, hydropower has a higher priority than other types of generators. The principle of prioritizing regulation capacity means that, on the basis of meeting load demand, the starting priority of thermal power units is determined according to the size of their regulation capacity; the greater the regulation capacity, the higher the starting priority. The principle of uniform incremental rate and economic distribution means that, under the premise of meeting safety constraints, the output of all online units is uniform and the incremental rate of coal consumption tends to be consistent. The principle of uniform distribution of backup means that when arranging equipment for power outage maintenance or as cold backup, the equipment for power outage maintenance or as cold backup should be evenly distributed geographically and electrically. The principle of reserve capacity in heavily loaded areas means that for critical transmission sections in heavily loaded areas, the reserved reserve capacity should be greater than 20% of the maximum capacity. The principle of appropriately unblocking the loop network means minimizing the number of electromagnetic loops while ensuring N-1 safety.

8. The typical operation mode automatic generation system according to claim 7, characterized in that: The regulating capacity of thermal power units includes the size of the output range and the rate of rate of climb.

9. The typical operation mode automatic generation system according to claim 1, characterized in that: When the typical power grid operation mode compilation module solves the multi-objective collaborative optimization framework, it takes the initial power grid operation mode as the starting point and the maximum power grid transmission capacity as the objective, and uses the SC-OPF solver to generate generator output combinations.

10. The typical operation mode automatic generation system according to claim 9, characterized in that: When using the SC-OPF solver to solve for the maximum power grid transmission capacity, after each generator output combination is generated, power flow calculation is performed and a feasibility assessment is conducted. Generator output combinations that are not feasible are deleted. Feasibility means that the power flow of all lines is within the safety limit, the output of all generators is within the allowable range, and the power remains balanced. If the grid's transmission capacity cannot be increased without exceeding the line's output limit, the solver will stop calculating and report the results.

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