Power grid operation mode generation method and system considering conventional power supply deep peak regulation

Abstract

The invention discloses a power grid operation mode generation method and system considering conventional power supply deep peak regulation, and belongs to the technical field of power grid safety and new energy power systems. The method comprises the following steps: constructing basic operation mode data of a power grid; generating power flow active power output data of conventional power supply multi-gear depth peak regulation; transient stability model data of conventional power supply multi-gear depth peak regulation are generated; generating power flow active output data aiming at different gears of the pumped storage unit and power flow active output data of the new energy power generation unit; generating power flow reactive configuration data of the whole set of evolution operation mode on the cardinal number, and then generating power flow checking calculation data of the whole set of evolution operation mode; and generating a sorted power grid operation mode through fault checking according to the load flow checking calculation data of the whole set of evolution operation mode and the transient stability model data of the conventional power supply multi-gear depth peak regulation. According to the invention, automatic generation and sorting of the power grid operation modes under the condition of considering deep peak regulation are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid security and new energy power system, and more specifically, to a method and system for generating a power grid operation mode taking into account deep peak regulation of conventional power sources. Background Art

[0002] Based on the deep peak regulation technology of conventional power sources (thermal power units), when the power fluctuation of the power system is large, the conventional power sources can quickly adjust the output to meet the safety regulation needs of the power grid. The main ways to achieve deep peak regulation of thermal power units include flexibility transformation and technical optimization.

[0003] With the rapid development of new power systems, the regulation capacity of power grids is undergoing unprecedented changes. The large-scale access of new energy sources makes the operation of power systems highly random and uncertain. The dual uncertainty of source and load poses new challenges to the traditional power grid dispatching method. In order to adapt to this change, it is necessary not only to improve the controllability of new energy sources, but also to strengthen the flexibility of traditional energy, especially conventional thermal power units in the power system. In this context, the deep peak regulation technology of thermal power units has become one of the key means to improve the controllability and regulation capacity of power grids.

[0004] The current grid operation mode analysis and control strategies still rely heavily on traditional load forecasting. These models mainly focus on the peak-to-valley differences between power sources and loads, and do not fully consider the role and impact of conventional unit peak-shaving conditions on the grid. Since different peak-shaving depths correspond to specific grid operation modes and generator model parameters, changes in the above data directly affect the safety, stability and economy of the entire grid.

[0005] Faced with the massive combination of operating modes brought about by deep peak load regulation, how to efficiently carry out power grid mode generation and simulation analysis of its impact on system safety and stability has become an urgent problem that needs to be solved. Summary of the invention

[0006] In view of the above problems, the present invention proposes a method for generating a power grid operation mode taking into account deep peak regulation of conventional power sources, comprising:

[0007] Constructing basic operation mode data of the power grid, generating the power flow active output data of multi-gear deep peak regulation of conventional power sources according to the basic operation mode data; generating transient stability model data of multi-gear deep peak regulation of conventional power sources through actual measurement of generator parameters according to the basic operation mode data; generating the power flow active output data of different gears of the pumped storage units and the power flow active output data of the new energy power generation units according to the basic operation mode data;

[0008] Based on the tidal current active output data of the conventional power supply's multi-gear deep peak regulation, the tidal current active output data of the pumped storage units at different gears, and the tidal current active output data of the new energy power generation units, the tidal current active output data of the entire set of evolutionary operation modes are generated; based on the basic operation mode data and the tidal current active output data of the entire set of evolutionary operation modes, the tidal current initial calculation data of the entire set of evolutionary operation modes are generated; based on the tidal current initial calculation data of the entire set of evolutionary operation modes, the tidal current reactive configuration data of the entire set of evolutionary operation modes are generated;

[0009] Based on the initial calculation data of the power flow of the whole set of evolutionary operation modes and the reactive power configuration data of the power flow of the whole set of evolutionary operation modes, the power flow calculation data of the whole set of evolutionary operation modes are generated; based on the power flow calculation data of the whole set of evolutionary operation modes and the transient stability model data of multi-speed deep peak regulation of conventional power sources, the power flow verification calculation data of the whole set of evolutionary operation modes are generated; based on the power flow verification calculation data of the whole set of evolutionary operation modes, a sorted power grid operation mode is generated through fault verification.

[0010] Optional, basic grid operation data, including:

[0011] Power grid flow data and transient stability model data;

[0012] The power grid flow data includes: transmission line model data, transformer model data, busbar model data, actual / maximum active output data of conventional power sources, actual / maximum active output data of pumped storage units, and actual active output data of new energy power generation units;

[0013] The transient stability model data includes: conventional generator model data, excitation system model data, stabilizer model data, speed regulator and prime mover model data and new energy model data;

[0014] The governor and prime mover model data include: the first regulation system model GJ data, the second regulation system model GJ+ data, the electro-hydraulic servo system model data, and the series combination and single reheater steam turbine model data.

[0015] Optionally, based on the basic operation mode data, the power flow active output data of the conventional power supply multi-speed deep peak regulation is generated, including:

[0016] In the basic operation mode data, a set of generators that simultaneously meet the voltage level condition, the partition condition and the keyword condition are screened out, and a set of actual / maximum active output values ​​of the generators in the set of generators is marked;

[0017] According to the marked maximum active output value set of the generator and the given deep peak-shaving gear set of the conventional thermal power units, the power flow active data of the conventional power source multi-gear deep peak-shaving is generated.

[0018] Optionally, based on the basic operation mode data, transient stability model data of multi-gear deep peak regulation of conventional power supply is generated through actual measurement of generator parameters, including:

[0019] According to the generator set, the generator maximum active output value set and the given conventional thermal power unit deep peak-shaving gear set, based on the measured data of generator parameters and in accordance with the preset format, the transient stability model data of conventional power source multi-gear deep peak-shaving is generated.

[0020] Optional transient stability model data for multi-speed deep peak regulation of conventional power supply, including:

[0021] The first regulating system model GJ data, the second regulating system model GJ+ data, the electro-hydraulic servo system model data, and the series combination and single reheater steam turbine model data;

[0022] The first regulating system model GJ data includes: speed measurement link time constant, speed deviation dead zone, speed deviation magnification, control mode selection, PID proportional link multiple, PID differential link multiple, PID integral link multiple, PID integral link limit upper limit, PID integral link limit lower limit, PID output limit link upper limit, PID output limit link lower limit, load control feedforward coefficient, primary frequency modulation load upper limit and primary frequency modulation load lower limit;

[0023] The second regulation system model GJ+ data includes: the pure delay time of the frequency input signal, the pure delay time of the power feedback signal, the first-order inertia link time constant corresponding to the power feedback signal, the pure delay time after the frequency signal is amplified, the pure delay time of the input PID after the frequency signal is amplified, the rising rate limit of the input PID signal after the frequency signal is amplified, and the falling rate limit of the input PID signal after the frequency signal is amplified;

[0024] The electro-hydraulic servo system model data includes: rated output power of the prime mover, oil motor closing time constant, oil motor opening time constant, overspeed closing coefficient, overspeed opening coefficient, maximum stroke of the oil motor or maximum opening of the regulating valve, minimum stroke of the oil motor or minimum opening of the regulating valve, oil motor stroke feedback link time, PID module proportional amplification link multiple, PID module differential amplification link multiple, PID module integral amplification link multiple, PID module integral link output upper limit, PID module integral link output lower limit, PID module output upper limit and PID module output lower limit;

[0025] Model data for series combination and single reheater steam turbines, including: steam volume time constant, high pressure cylinder power ratio, reheater time constant, intermediate pressure cylinder power ratio, cross pipe time constant, low pressure cylinder power ratio and high pressure cylinder power natural overshoot coefficient.

[0026] Optionally, based on the basic operation mode data, generating power flow active output data for different gears of the pumped storage unit, including:

[0027] In the basic operation mode data, a set of pumped storage units that simultaneously meet the voltage level condition, the partition condition and the keyword condition is screened out, and a set of actual / maximum active output values ​​of the pumped storage units in the set of pumped storage units is marked;

[0028] According to the marked maximum active output value set of the pumped-storage unit and the given pumped-storage operating condition gear set, the power flow active output data for different gears of the pumped-storage unit are generated.

[0029] Optionally, generating power flow active output data of the new energy power generation unit according to the basic operation mode data includes:

[0030] In the basic operation mode data, a set of new energy power generation units that simultaneously meet the voltage level condition, the partition condition and the keyword condition are screened out, and the actual active output value set of the new energy power generation units in the set of new energy power generation units is marked;

[0031] According to the actual active power output value set of the marked new energy power generation unit, the power flow active power output data of the new energy power generation unit is generated.

[0032] Optionally, generate a set of power flow reactive configuration data for the evolutionary operation mode, including:

[0033] For the active power calculation data of the whole set of evolutionary operation modes, the initial flow calculation data of the whole set of evolutionary operation modes is generated, and the flow calculation is performed to perform classification processing, generate the reactive power configuration data of the whole set of evolutionary operation modes, and then generate the flow calculation data of the whole set of evolutionary operation modes.

[0034] Optionally, generate a sorted grid operation mode, including:

[0035] According to the flow verification calculation data of the whole set of evolutionary operation modes and the transient stability model data of the whole set of evolutionary operation mode verification calculation data, a whole set of evolutionary operation mode verification calculation data is generated, fault verification calculation is performed on the whole set of evolutionary operation mode verification calculation data, and the number of instability faults corresponding to the evolutionary modes is sorted to obtain the sorted power grid operation mode.

[0036] An optional grid operation mode with a small number of unstable faults is used as a preferred recommended grid operation mode.

[0037] On the other hand, the present invention also proposes a system for generating a power grid operation mode considering deep peak regulation of conventional power sources, comprising:

[0038] The first data generating unit is used to construct basic operation mode data of the power grid, and generate the current active output data of multi-gear deep peak regulation of conventional power sources according to the basic operation mode data; generate transient stability model data of multi-gear deep peak regulation of conventional power sources through actual measurement of generator parameters according to the basic operation mode data; generate the current active output data of different gears of the pumped storage unit and the current active output data of the new energy power generation unit according to the basic operation mode data;

[0039] The second data generating unit is used to generate the current active output data of the whole set of evolutionary operation modes based on the current active output data of the multi-gear deep peak regulation of the conventional power supply, the current active output data of the pumped storage unit at different gears and the current active output data of the new energy power generation unit; generate the current initial calculation data of the whole set of evolutionary operation modes based on the basic operation mode data and the current active output data of the whole set of evolutionary operation modes; generate the current reactive configuration data of the whole set of evolutionary operation modes based on the current initial calculation data of the whole set of evolutionary operation modes;

[0040] The output unit is used to generate the power flow calculation data of the whole set of evolutionary operation modes based on the initial power flow calculation data of the whole set of evolutionary operation modes and the power flow reactive configuration data of the whole set of evolutionary operation modes; generate the power flow verification calculation data of the whole set of evolutionary operation modes based on the power flow calculation data of the whole set of evolutionary operation modes and the transient stability model data of multi-speed deep peak regulation of conventional power sources; and generate a sorted power grid operation mode through fault verification based on the power flow verification calculation data of the whole set of evolutionary operation modes.

[0041] Optional, basic grid operation data, including:

[0042] Power grid flow data and transient stability model data;

[0043] The power grid flow data includes: transmission line model data, transformer model data, busbar model data, actual / maximum active output data of conventional power sources, actual / maximum active output data of pumped storage units, and actual active output data of new energy power generation units;

[0044] The transient stability model data includes: conventional generator model data, excitation system model data, stabilizer model data, speed regulator and prime mover model data and new energy model data;

[0045] The governor and prime mover model data include: the first regulation system model GJ data, the second regulation system model GJ+ data, the electro-hydraulic servo system model data, and the series combination and single reheater steam turbine model data.

[0046] Optionally, based on the basic operation mode data, the power flow active output data of the conventional power supply multi-speed deep peak regulation is generated, including:

[0047] In the basic operation mode data, a set of generators that simultaneously meet the voltage level condition, the partition condition and the keyword condition are screened out, and a set of actual / maximum active output values ​​of the generators in the set of generators is marked;

[0048] According to the marked maximum active output value set of the generator and the given deep peak-shaving gear set of the conventional thermal power units, the power flow active data of the conventional power source multi-gear deep peak-shaving is generated.

[0049] Optionally, based on the basic operation mode data, transient stability model data of multi-gear deep peak regulation of conventional power supply is generated through actual measurement of generator parameters, including:

[0050] According to the generator set, the generator maximum active output value set and the given conventional thermal power unit deep peak-shaving gear set, based on the measured data of generator parameters and in accordance with the preset format, the transient stability model data of conventional power source multi-gear deep peak-shaving is generated.

[0051] Optional transient stability model data for multi-speed deep peak regulation of conventional power supply, including:

[0052] The first regulating system model GJ data, the second regulating system model GJ+ data, the electro-hydraulic servo system model data, and the series combination and single reheater steam turbine model data;

[0053] The first regulating system model GJ data includes: speed measurement link time constant, speed deviation dead zone, speed deviation magnification, control mode selection, PID proportional link multiple, PID differential link multiple, PID integral link multiple, PID integral link limit upper limit, PID integral link limit lower limit, PID output limit link upper limit, PID output limit link lower limit, load control feedforward coefficient, primary frequency modulation load upper limit and primary frequency modulation load lower limit;

[0054] The second regulation system model GJ+ data includes: the pure delay time of the frequency input signal, the pure delay time of the power feedback signal, the first-order inertia link time constant corresponding to the power feedback signal, the pure delay time after the frequency signal is amplified, the pure delay time of the input PID after the frequency signal is amplified, the rising rate limit of the input PID signal after the frequency signal is amplified, and the falling rate limit of the input PID signal after the frequency signal is amplified;

[0055] The electro-hydraulic servo system model data includes: rated output power of the prime mover, oil motor closing time constant, oil motor opening time constant, overspeed closing coefficient, overspeed opening coefficient, maximum stroke of the oil motor or maximum opening of the regulating valve, minimum stroke of the oil motor or minimum opening of the regulating valve, oil motor stroke feedback link time, PID module proportional amplification link multiple, PID module differential amplification link multiple, PID module integral amplification link multiple, PID module integral link output upper limit, PID module integral link output lower limit, PID module output upper limit and PID module output lower limit;

[0056] Model data for series combination and single reheater steam turbines, including: steam volume time constant, high pressure cylinder power ratio, reheater time constant, intermediate pressure cylinder power ratio, cross pipe time constant, low pressure cylinder power ratio and high pressure cylinder power natural overshoot coefficient.

[0057] Optionally, based on the basic operation mode data, generating power flow active output data for different gears of the pumped storage unit, including:

[0058] In the basic operation mode data, a set of pumped storage units that simultaneously meet the voltage level condition, the partition condition and the keyword condition is screened out, and a set of actual / maximum active output values ​​of the pumped storage units in the set of pumped storage units is marked;

[0059] According to the marked maximum active output value set of the pumped-storage unit and the given pumped-storage operating condition gear set, the power flow active output data for different gears of the pumped-storage unit are generated.

[0060] Optionally, generating power flow active output data of the new energy power generation unit according to the basic operation mode data includes:

[0061] In the basic operation mode data, a set of new energy power generation units that simultaneously meet the voltage level condition, the partition condition and the keyword condition are screened out, and the actual active output value set of the new energy power generation units in the set of new energy power generation units is marked;

[0062] According to the actual active power output value set of the marked new energy power generation unit, the power flow active power output data of the new energy power generation unit is generated.

[0063] Optionally, generate a set of power flow reactive configuration data for the evolutionary operation mode, including:

[0064] For the active power calculation data of the whole set of evolutionary operation modes, the initial flow calculation data of the whole set of evolutionary operation modes is generated, and the flow calculation is performed to perform classification processing, generate the reactive power configuration data of the whole set of evolutionary operation modes, and then generate the flow calculation data of the whole set of evolutionary operation modes.

[0065] Optionally, generate a sorted grid operation mode, including:

[0066] According to the flow verification calculation data of the whole set of evolutionary operation modes and the transient stability model data of the whole set of evolutionary operation mode verification calculation data, a whole set of evolutionary operation mode verification calculation data is generated, fault verification calculation is performed on the whole set of evolutionary operation mode verification calculation data, and the number of instability faults corresponding to the evolutionary modes is sorted to obtain the sorted power grid operation mode.

[0067] An optional grid operation mode with a small number of unstable faults is used as a preferred recommended grid operation mode.

[0068] In yet another aspect, the present invention further provides a computing device, comprising: one or more processors;

[0069] a processor for executing one or more programs;

[0070] When the one or more programs are executed by the one or more processors, the above-described method is implemented.

[0071] In yet another aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed, the method described above is implemented.

[0072] Compared with the prior art, the present invention has the following beneficial effects:

[0073] The present invention provides a method for generating an operation mode of a power grid taking into account deep peak regulation of conventional power sources, comprising: constructing basic operation mode data of the power grid, and generating flow active output data of deep peak regulation of multiple gears of conventional power sources according to the basic operation mode data; generating transient stability model data of deep peak regulation of multiple gears of conventional power sources through actual measurement of generator parameters according to the basic operation mode data; generating flow active output data of different gears of pumped storage units and flow active output data of new energy power generation units according to the basic operation mode data; generating a whole set of flow active output data of deep peak regulation of multiple gears of conventional power sources, flow active output data of different gears of pumped storage units and flow active output data of new energy power generation units based on the flow active output data of deep peak regulation of multiple gears of conventional power sources, flow active output data of different gears of pumped storage units and flow active output data of new energy power generation units according to the basic operation mode data. power data; based on the basic operation mode data and the active power output data of the whole set of evolutionary operation modes, generate the initial calculation data of the flow of the whole set of evolutionary operation modes; based on the initial calculation data of the flow of the whole set of evolutionary operation modes, generate the reactive configuration data of the flow of the whole set of evolutionary operation modes; based on the initial calculation data of the flow of the whole set of evolutionary operation modes and the reactive configuration data of the flow of the whole set of evolutionary operation modes, generate the flow calculation data of the whole set of evolutionary operation modes; based on the flow calculation data of the whole set of evolutionary operation modes and the transient stability model data of multi-gear deep peak regulation of conventional power sources, generate the flow verification calculation data of the whole set of evolutionary operation modes; according to the flow verification calculation data of the whole set of evolutionary operation modes, generate the sorted power grid operation modes through fault verification. The present invention realizes the automatic generation and sorting of power grid operation modes under the conditions of deep peak regulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 is a flow chart of the method of the present invention;

[0075] Figure 2 A flowchart of an embodiment of the method of the present invention;

[0076] Figure 3 It is a structural diagram of the system of the present invention. DETAILED DESCRIPTION

[0077] Now, exemplary embodiments of the present invention are described with reference to the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to disclose the present invention in detail and completely and to fully convey the scope of the present invention to those skilled in the art. The terms used in the exemplary embodiments shown in the accompanying drawings are not intended to limit the present invention. In the accompanying drawings, the same units / elements are marked with the same reference numerals.

[0078] Unless otherwise specified, the terms (including technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it is understood that the terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0079] Embodiment 1:

[0080] The present invention proposes a method for generating a power grid operation mode taking into account the deep peak regulation of conventional power sources, such as Figure 1 As shown, including:

[0081] Step 1, constructing basic operation mode data of the power grid, generating the power flow active output data of multi-gear deep peak regulation of conventional power supply according to the basic operation mode data; generating transient stability model data of multi-gear deep peak regulation of conventional power supply according to the basic operation mode data through actual measurement of generator parameters; generating power flow active output data of different gears of pumped storage units and power flow active output data of new energy power generation units according to the basic operation mode data;

[0082] Step 2: Generate the current active output data of the whole set of evolutionary operation modes based on the current active output data of the multi-gear deep peak regulation of the conventional power supply, the current active output data of the pumped storage unit at different gears, and the current active output data of the new energy power generation unit; generate the current initial calculation data of the whole set of evolutionary operation modes based on the basic operation mode data and the current active output data of the whole set of evolutionary operation modes; generate the current reactive configuration data of the whole set of evolutionary operation modes based on the current initial calculation data of the whole set of evolutionary operation modes;

[0083] Step 3: Generate the flow calculation data of the whole set of evolutionary operation modes based on the initial flow calculation data of the whole set of evolutionary operation modes and the flow reactive configuration data of the whole set of evolutionary operation modes; generate the flow verification calculation data of the whole set of evolutionary operation modes based on the flow calculation data of the whole set of evolutionary operation modes and the transient stability model data of multi-speed deep peak regulation of conventional power sources; generate the sorted power grid operation mode through fault verification based on the flow verification calculation data of the whole set of evolutionary operation modes.

[0084] Among them, the basic operation mode data of the power grid include:

[0085] Power grid flow data and transient stability model data;

[0086] The power grid flow data includes: transmission line model data, transformer model data, busbar model data, actual / maximum active output data of conventional power sources, actual / maximum active output data of pumped storage units, and actual active output data of new energy power generation units;

[0087] The transient stability model data includes: conventional generator model data, excitation system model data, stabilizer model data, speed regulator and prime mover model data and new energy model data;

[0088] The governor and prime mover model data include: the first regulation system model GJ data, the second regulation system model GJ+ data, the electro-hydraulic servo system model data, and the series combination and single reheater steam turbine model data.

[0089] According to the basic operation mode data, the power flow active output data of the conventional power supply multi-speed deep peak regulation is generated, including:

[0090] In the basic operation mode data, a set of generators that simultaneously meet the voltage level condition, the partition condition and the keyword condition are screened out, and a set of actual / maximum active output values ​​of the generators in the set of generators is marked;

[0091] According to the marked maximum active output value set of the generator and the given deep peak-shaving gear set of the conventional thermal power units, the power flow active data of the conventional power source multi-gear deep peak-shaving is generated.

[0092] According to the basic operation mode data, the transient stability model data of the conventional power supply multi-speed deep peak regulation is generated through the actual measurement of the generator parameters, including:

[0093] According to the generator set, the generator maximum active output value set and the given conventional thermal power unit deep peak-shaving gear set, based on the measured data of generator parameters and in accordance with the preset format, the transient stability model data of conventional power source multi-gear deep peak-shaving is generated.

[0094] Among them, the transient stability model data of multi-speed deep peak regulation of conventional power sources include:

[0095] The first regulating system model GJ data, the second regulating system model GJ+ data, the electro-hydraulic servo system model data, and the series combination and single reheater steam turbine model data;

[0096] The first regulating system model GJ data includes: speed measurement link time constant, speed deviation dead zone, speed deviation magnification, control mode selection, PID proportional link multiple, PID differential link multiple, PID integral link multiple, PID integral link limit upper limit, PID integral link limit lower limit, PID output limit link upper limit, PID output limit link lower limit, load control feedforward coefficient, primary frequency modulation load upper limit and primary frequency modulation load lower limit;

[0097] The second regulation system model GJ+ data includes: the pure delay time of the frequency input signal, the pure delay time of the power feedback signal, the first-order inertia link time constant corresponding to the power feedback signal, the pure delay time after the frequency signal is amplified, the pure delay time of the input PID after the frequency signal is amplified, the rising rate limit of the input PID signal after the frequency signal is amplified, and the falling rate limit of the input PID signal after the frequency signal is amplified;

[0098] The electro-hydraulic servo system model data includes: rated output power of the prime mover, oil motor closing time constant, oil motor opening time constant, overspeed closing coefficient, overspeed opening coefficient, maximum stroke of the oil motor or maximum opening of the regulating valve, minimum stroke of the oil motor or minimum opening of the regulating valve, oil motor stroke feedback link time, PID module proportional amplification link multiple, PID module differential amplification link multiple, PID module integral amplification link multiple, PID module integral link output upper limit, PID module integral link output lower limit, PID module output upper limit and PID module output lower limit;

[0099] Model data for series combination and single reheater steam turbines, including: steam volume time constant, high pressure cylinder power ratio, reheater time constant, intermediate pressure cylinder power ratio, cross pipe time constant, low pressure cylinder power ratio and high pressure cylinder power natural overshoot coefficient.

[0100] According to the basic operation mode data, the power flow active output data of different gears of the pumped storage unit are generated, including:

[0101] In the basic operation mode data, a set of pumped storage units that simultaneously meet the voltage level condition, the partition condition and the keyword condition is screened out, and a set of actual / maximum active output values ​​of the pumped storage units in the set of pumped storage units is marked;

[0102] According to the marked maximum active output value set of the pumped-storage unit and the given pumped-storage operating condition gear set, the power flow active output data for different gears of the pumped-storage unit are generated.

[0103] According to the basic operation mode data, the power flow active output data of the new energy power generation unit is generated, including:

[0104] In the basic operation mode data, a set of new energy power generation units that simultaneously meet the voltage level condition, the partition condition and the keyword condition are screened out, and the actual active output value set of the new energy power generation units in the set of new energy power generation units is marked;

[0105] According to the actual active power output value set of the marked new energy power generation unit, the power flow active power output data of the new energy power generation unit is generated.

[0106] Among them, the power flow reactive configuration data of the whole set of evolutionary operation modes is generated, including:

[0107] For the active power calculation data of the whole set of evolutionary operation modes, the initial flow calculation data of the whole set of evolutionary operation modes is generated, and the flow calculation is performed to perform classification processing, generate the reactive power configuration data of the whole set of evolutionary operation modes, and then generate the flow calculation data of the whole set of evolutionary operation modes.

[0108] Among them, the grid operation mode of generating sorting includes:

[0109] According to the flow verification calculation data of the whole set of evolutionary operation modes and the transient stability model data of the whole set of evolutionary operation mode verification calculation data, a whole set of evolutionary operation mode verification calculation data is generated, fault verification calculation is performed on the whole set of evolutionary operation mode verification calculation data, and the number of instability faults corresponding to the evolutionary modes is sorted to obtain the sorted power grid operation mode.

[0110] The present invention is further described below with reference to specific cases:

[0111] like Figure 2 As shown, the specific case steps include:

[0112] Step 1: Construct basic operation mode data of the power grid, including power flow data and stability model data.

[0113] Step 2: Based on the basic operation mode data of the power grid, generate the power flow active output data of multi-speed deep peak regulation of conventional power sources.

[0114] Step 3: Based on the basic operation mode data of the power grid and actual measurement of generator parameters, generate transient stability model data for multi-speed deep peak regulation of conventional power sources.

[0115] Step 4: Based on the basic operation mode data of the power grid, generate the power flow active output data for different gears of the pumped storage units.

[0116] Step 5: Based on the basic operation mode data of the power grid, the current active output data of multi-level deep peak regulation of conventional power sources, and the current active output data of different levels of pumped storage units, generate the current active output data of new energy power generation units, and then generate the current active output data of the entire set of evolutionary operation modes.

[0117] Step 6: Based on the active power output data of the whole set of evolutionary operation modes, generate the initial calculation data of the whole set of evolutionary operation modes, perform the power flow calculation, and generate the reactive power configuration data of the whole set of evolutionary operation modes by classification. Based on the initial calculation data of the whole set of evolutionary operation modes and the power flow calculation data of the whole set of evolutionary operation modes, generate the power flow calculation data of the whole set of evolutionary operation modes.

[0118] Step 7: Generate a set of verification calculation data for the evolutionary mode based on the power flow calculation data of the entire set of evolutionary operation modes and the transient stability model data of multi-speed deep peak regulation of conventional power sources.

[0119] Step 8: Based on the verification calculation data of the whole set of evolution methods, conduct transient stability verification calculation of power grid faults to realize the ranking of power grid operation modes.

[0120] The following is an expanded description of each step:

[0121] Step 1: Construct basic grid operation mode data.

[0122] The basic grid operation mode data includes flow data and stability model data. Among them, the grid flow data includes the following models: ① Transmission line model, parameters include resistance, reactance, conductance, and susceptance; ② Transformer model, parameters include leakage reactance, ratio, and tap position; ③ Bus model, parameters include bus type, reference voltage, partition, active output value, reactive output value, active load value, reactive load value, and reactive compensation value. ④ Actual / maximum active output data of conventional power sources (i.e. conventional generators), actual / maximum active output data of pumped storage units, and actual active output data of new energy power generation units.

[0123] The grid stability simulation component data models include: conventional generator model, excitation system model, stabilizer model, governor and prime mover model, and new energy model. The governor and prime mover model data include: the first regulation system model GJ data, the second regulation system model GJ+ data, the electro-hydraulic servo system model data, and the series combination and single reheater steam turbine model data.

[0124] Step 2: Based on the basic grid operation mode data, generate the power flow active output data of multi-level deep peak regulation of conventional power sources.

[0125] According to the voltage level condition, partition condition and keyword condition, the generator set that meets the above three conditions is selected from the basic power grid operation mode data as Sg = {G1, G2, ..., G Ng}, in the Sg set, the subscripts 1 to Ng represent the generator numbers, and a total of Ng generators are included.

[0126] Suppose the generator G in the set Sg i The active output value is P(G i ), further considering the differences in power grid operation modes, the maximum active output value set of the generators in the generator set Sg in the basic operation mode is marked as:

[0127]

[0128] Among them, ρ max Subscript in a collection It indicates the power generation number, and the superscript max indicates the maximum active output of the generator.

[0129] The actual active output value set of the generators in the generator set Sg in the basic operation mode is marked as:

[0130]

[0131] Among them, the subscript in the ρ0 set Indicates the power generation number, and the superscript 0 indicates the actual active output of the generator.

[0132] Configure the conventional thermal power unit to form a deep peak load gear set L g , deep peak shaving gear L g Including 50%, 40%, 30%, 25%, and several customized peak shaving depth levels:

[0133] L g ={L g1 L g2 L g3 L g4 L g5 …L gr}

[0134] ={50% 40% 30% 25% s1%…sx%}

[0135] Among them, s1~sx represent several customized peak-shaving depth levels, totaling gr levels, L g Any element in is marked as L gi .

[0136] According to the basic operation mode of the generator set Sg The maximum active output value set of the generator and the given deep peak-shaving gear set of conventional thermal power units are used to form the power flow active output data for multi-gear deep peak-shaving of conventional power sources. The generation method is as follows:

[0137] The maximum output data of the generator in the basic operation mode is multiplied by the deep peak-shaving gear value data to generate the power flow active output data of the conventional power source multi-gear deep peak-shaving based on the gr set evolution operation mode of gr gears:

[0138] Among them i The calculation method of the power flow active output data of the conventional power source with multi-speed deep peak regulation in the evolutionary operation mode is as follows:

[0139]

[0140] Calculation method explanation: The output of the jth generator in the above i-th set of data is The calculation method is:

[0141]

[0142] Thus, the gr set evolution operation mode is formed, and the power flow active output data of conventional power supply multi-gear deep peak regulation is:

[0143]

[0144] Step 3: Generate transient stability model data for multi-speed deep peak regulation of conventional power supply through actual measurement of generator parameters.

[0145] According to the generator set Sg={G1,G2,…,G Ng}, corresponding to the deep peak-shaving gear L g In the middle gr gears, through the actual measurement of gr generator parameters, the actual measured parameters of gr sets of generators are obtained, and the transient stability model data of multi-gear deep peak regulation of conventional units in evolutionary operation mode are generated according to the format of "PSD-ST Transient Stability Program User Manual". Specifically, the transient stability model data formed by the parameter measurement include ① regulation system model GJ, ② regulation system model GJ+, ③ electro-hydraulic servo system model, ④ series combination, and single reheater turbine model.

[0146] in:

[0147] ① The regulation system model GJ includes the following parameters: speed measurement link time constant, speed deviation dead zone, speed deviation magnification, control mode selection, PID proportional link multiple, PID differential link multiple, PID integral link multiple, PID integral link limit upper limit, PID integral link limit lower limit, PID output limit link upper limit, PID output limit link lower limit, load control feedforward coefficient, primary frequency modulation load upper limit, primary frequency modulation load lower limit;

[0148] ② The regulation system model GJ+ includes the following parameters: pure delay time of the frequency input signal, pure delay time of the power feedback signal, first-order inertia link time constant corresponding to the power feedback signal, pure delay time after the frequency signal is amplified, pure delay time of the input PID after the frequency signal is amplified, rising rate limit of the input PID signal after the frequency signal is amplified, and falling rate limit of the input PID signal after the frequency signal is amplified;

[0149] ③ The electro-hydraulic servo system model includes the following parameters: rated output power of the prime mover, closing time constant of the oil motor, opening time constant of the oil motor, overspeed closing coefficient, overspeed opening coefficient, maximum stroke of the oil motor or maximum opening of the throttle valve (per unit value), minimum stroke of the oil motor or minimum opening of the throttle valve (per unit value), time of the oil motor stroke feedback link (LVDT), multiples of the proportional amplification link of the PID module, multiples of the differential amplification link of the PID module, multiples of the integral amplification link of the PID module, upper limit of the integral link output of the PID module, lower limit of the integral link output of the PID module, upper limit of the output of the PID module, and lower limit of the output of the PID module;

[0150] ④ The series combination and single reheater steam turbine model includes the following parameters: steam volume time constant, high-pressure cylinder power ratio, reheater time constant, medium-pressure cylinder power ratio, cross-pipe time constant, low-pressure cylinder power ratio, and high-pressure cylinder power natural overmodulation coefficient.

[0151] Assume that the parameter set of the generator transient stability model in the basic operation mode is marked as:

[0152]

[0153] The data of the transient stability model of multi-gear deep peak regulation of conventional generators in the gr set evolutionary operation mode are marked as:

[0154]

[0155] Where i ranges from 1 to gr, gr is the total number of transient stability model data sets for deep peak load regulation of conventional power sources in evolutionary operation mode. It represents the transient stability model data of generator j under the i-th set of evolutionary operation mode, including a set of all the model parameters of ①~④ above.

[0156] Establish and form a set of evolutionary operation modes for conventional units with deep peak load regulation output data ρ i With τ i The matching relationship between the two is to establish a mapping map (ρ i ,τ i ), can be obtained by i Extract τ i .

[0157] Step 4: Based on the basic operation mode data of the power grid, generate the power flow active output data for different gears of the pumped storage units.

[0158] According to the voltage level condition, partition condition and keyword condition, the set of pumped storage units that meet the above three conditions is selected from the basic power grid operation mode data as Sp = {S1, S2, …, S Np}, in the Sp set, the subscripts 1 to Np represent the pumped storage units numbers, and a total of Np pumped storage units are included.

[0159] Assume that the pumped storage unit S in the set Sp i The maximum active output value is Further considering the differences in power grid operation modes, the maximum active output value set of the pumped storage units for the pumped storage set Sp in the basic operation mode is marked as:

[0160]

[0161] Among them, max In the set, the subscripts 1 to Np represent the pumped storage unit numbers, and the superscript max represents the maximum active output.

[0162] The actual active output value set of the pumped storage units for the pumped storage set Sp in the basic operation mode is marked as:

[0163]

[0164] Among them, the subscripts 1~Np in the ζ0 set represent the pumped storage unit numbers, and the superscript 0 represents the actual active output.

[0165] Configure the pumped storage unit operating gear set L p , working position L p Including 9 typical gears from -100% to 100% and several custom gears:

[0166] L p ={L p1 L p2 … L p9 … L pr}

[0167] ={-100% -75% -50% -25% 0 25% 50% 75% 100% … y%}

[0168] Among them, p1~pr represent the gear numbers, with a total of pr gears, L p Any element in is marked as L pi .

[0169] According to the pumped storage unit set Sp pumped storage unit maximum active output value set and the given pumped storage working condition gear set in the basic operation mode, the power flow active output data for different gears of the pumped storage unit are generated. The generation method is as follows:

[0170] The calculation method of the power flow active output data of the pumped storage units in different gears in the i-th evolutionary operation mode is as follows:

[0171]

[0172] Explanation of calculation method: The power generation output of the jth pumped storage unit in the above-mentioned i-th evolutionary operation mode is The calculation method is:

[0173]

[0174] Thus, the PR set of evolutionary operation modes and the power flow active output data of the pumped storage unit at different gears are formed:

[0175]

[0176] Step 5: Generate the current active power output data of the new energy power generation unit and the current active power output data of the entire set of evolutionary operation modes.

[0177] According to the voltage level condition, partition condition and keyword condition, the set of new energy power generation units that meet the above three conditions is selected from the basic power grid operation mode data as Sr = {R1, R2, ..., R Nr}, in the Sr set, the subscripts 1 to Nr represent the numbers of the renewable energy power generation units, which contain Nr pumped storage units in total.

[0178] The actual active output value set of the new energy power generation unit Sr in the basic operation mode is marked as:

[0179]

[0180] The generation method is as follows:

[0181] Step 5-1: Initialize i=1;

[0182] Step 5-2: Extract a set of data ρ from the power flow active output data of multi-gear deep peak regulation of conventional units in the gr set evolutionary operation mode i ;

[0183] Step 5-3: Initialize j=1;

[0184] Step 5-4: Extract a set of data from the pr set of power flow active output data of different gears of the pumped storage unit in the evolutionary operation mode ζ j ;

[0185] Step 5-5: Targeting ρ i , j , calculate the total change in active output of conventional power sources and pumped storage units relative to the basic operation mode:

[0186]

[0187] Then the total active power increase value that needs to be adjusted for the new energy power generation unit is:

[0188] ΣPincrease = -ΣP change

[0189] Form a set of data on the active power output of the new energy power generation unit that matches the active power of the conventional generator set and the pumped-storage unit:

[0190]

[0191] Among them,

[0192] Step 5-6: Output a set of data S on the active power output of the evolved power grid operation mode i , where S i = ρ i ∪ζ i ∪γ i ;

[0193] Step 5-7: If j < 9, then j = j + 1, and return to Step 5-4;

[0194] Step 5-8: If i < gr, then i = i + 1, and return to Step 5-2; if i >= gr, then end the operation.

[0195] Generate data on the active power output of the evolved operation mode according to the above loop process There are pr × gr sets of data in total. Replace the corresponding data in the basic operation mode of the power grid with each set of the above-generated data, then pr × gr sets of initial calculation data on the active power output of the evolved operation mode are generated Among them, replacement means updating the actual active power output data of the conventional generator set, pumped-storage unit, and new energy power generation unit in the basic mode to the active power output data of the i-th set of the evolved operation mode, then generating the initial calculation data on the active power output of the i-th set of the evolved operation mode.

[0196] Step 6: Generate data on the reactive power configuration of the entire evolved operation mode.

[0197] For the set M = {M i , i = 1 ~ pr × gr} of the initial calculation data on the active power output of the evolved operation mode generated in Step 5, there are pr × gr sets of initial calculation data on the active power output.

[0198] Step 6-1: Initialize i = 1;

[0199] Step 6-2: Perform a power flow calculation for the initial calculation data i on the active power output and classify and process:

[0200] If the power flow converges and the voltage is reasonable (the reasonable range means that the operating voltage of all busbars is between 0.95 - 1.05 pu), then no operation is performed on the initial calculation data i on the active power output;

[0201] If the power flow converges but the voltage is unreasonable, local reactive power compensation is performed for the unreasonable nodes (if the voltage is lower than 0.95, capacitive reactive power is compensated; if the voltage is higher than 1.05, inductive reactive power is compensated) to restore the voltage to the reasonable range;

[0202] If the power flow does not converge, all PQ nodes in the calculation data are set as PV nodes, and the power flow calculation is re-executed to obtain the reactive power injection Q of the conversion node in , and then the reactive power compensation value is obtained:

[0203] Q comp =(Q in -Q G +Q L )

[0204] where Qin is the reactive power injection of the node after setting the PQ node as the PV node; Q G and Q L are the reactive power output and reactive power load of the generator corresponding to the conversion node respectively. The set of reactive power compensation values of the conversion node in the initial power flow calculation data i of the evolutionary operation mode is marked as υ i .

[0205] Step 6-3: i = i + 1. If i < pr × gr, go to Step 6-2; if i >= pr × gr, end.

[0206] Replace the corresponding reactive power compensation data in the initial power flow calculation data of the entire set of evolutionary operation modes with each set of the generated reactive power compensation values of the conversion node, then pr × gr sets of power flow checking calculation data for the evolutionary operation modes are generated where the replacement means updating the reactive power compensation data in the initial power flow calculation data of the evolutionary operation mode to υ i , and then the i-th set of power flow checking calculation data for the evolutionary operation mode is generated.

[0207] Step 7: Based on the power flow checking calculation data of the evolutionary operation mode and the transient stability model data of the multi-stage deep peak shaving of conventional power sources, form a complete set of evolutionary mode checking calculation data.

[0208] According to map(ρ i ,τ i ) in Step 3, extract τ i , then form the transient stability model data matching the power flow checking calculation data of the evolutionary operation mode. That is, form the evolutionary mode checking calculation data.

[0209] Step 8: Grid fault transient stability checking calculation and grid operation mode sorting.

[0210] For the evolutionary mode verification calculation data (marked as Ci), the line N-1 / N-2 fault verification calculation is carried out, and the calculation results are statistically analyzed. If the number of unstable faults corresponding to Ci is marked as Fi, that is:

[0211] C i ={C1,C2,…,C pr×gr}

[0212] F i ={F1,F2,…,F pr×gr}

[0213] According to the size of the data in Fi, the operation modes are sorted from small to large. If there are the same elements in Fi, they are sorted according to the subscripts. Finally, the overall evaluation result of the power grid operation mode is given. The arrangement mode with the highest ranking is recommended as the priority.

[0214] The present invention can automatically take into account the influencing factors of deep peak regulation of conventional power sources, the operating conditions of pumped-storage units, and the differences in transient models of conventional units under deep peak regulation conditions, and automatically generate matching new energy power generation output data and reactive power configuration data, thereby realizing a complete set of calculation model data for safe and stable verification of the power supply network, and realizing the automatic generation and safe verification sorting of power grid operation modes under deep peak regulation conditions.

[0215] Embodiment 2:

[0216] The present invention also proposes a power grid operation mode generation system 200 considering conventional power source deep peak regulation, such as Figure 3 As shown, including:

[0217] The first data generating unit 201 is used to construct basic operation mode data of the power grid, and generate the power flow active output data of the conventional power source multi-gear deep peak regulation according to the basic operation mode data; generate the transient stability model data of the conventional power source multi-gear deep peak regulation by measuring the parameters of the generator according to the basic operation mode data; generate the power flow active output data of different gears of the pumped storage unit and the power flow active output data of the new energy power generation unit according to the basic operation mode data;

[0218] The second data generating unit 202 is used to generate the current active output data of the whole set of evolutionary operation modes based on the current active output data of the multi-gear deep peak regulation of the conventional power supply, the current active output data of the pumped storage unit at different gears, and the current active output data of the new energy power generation unit; generate the current initial calculation data of the whole set of evolutionary operation modes based on the basic operation mode data and the current active output data of the whole set of evolutionary operation modes; generate the current reactive configuration data of the whole set of evolutionary operation modes based on the current initial calculation data of the whole set of evolutionary operation modes;

[0219] The output unit 203 is used to generate the power flow calculation data of the whole set of evolutionary operation modes based on the initial power flow calculation data of the whole set of evolutionary operation modes and the power flow reactive configuration data of the whole set of evolutionary operation modes; generate the power flow verification calculation data of the whole set of evolutionary operation modes based on the power flow calculation data of the whole set of evolutionary operation modes and the transient stability model data of multi-speed deep peak regulation of conventional power sources; and generate a sorted power grid operation mode through fault verification based on the power flow verification calculation data of the whole set of evolutionary operation modes.

[0220] Among them, the basic operation mode data of the power grid include:

[0221] Power grid flow data and transient stability model data;

[0222] The power grid flow data includes: transmission line model data, transformer model data, busbar model data, actual / maximum active output data of conventional power sources, actual / maximum active output data of pumped storage units, and actual active output data of new energy power generation units;

[0223] The transient stability model data includes: conventional generator model data, excitation system model data, stabilizer model data, speed regulator and prime mover model data and new energy model data;

[0224] The governor and prime mover model data include: the first regulation system model GJ data, the second regulation system model GJ+ data, the electro-hydraulic servo system model data, and the series combination and single reheater steam turbine model data.

[0225] According to the basic operation mode data, the power flow active output data of the conventional power supply multi-speed deep peak regulation is generated, including:

[0226] In the basic operation mode data, a set of generators that simultaneously meet the voltage level condition, the partition condition and the keyword condition are screened out, and a set of actual / maximum active output values ​​of the generators in the set of generators is marked;

[0227] According to the marked maximum active output value set of the generator and the given deep peak-shaving gear set of the conventional thermal power units, the power flow active data of the conventional power source multi-gear deep peak-shaving is generated.

[0228] According to the basic operation mode data, the transient stability model data of the conventional power supply multi-speed deep peak regulation is generated through the actual measurement of the generator parameters, including:

[0229] According to the generator set, the generator maximum active output value set and the given conventional thermal power unit deep peak-shaving gear set, based on the measured data of generator parameters and in accordance with the preset format, the transient stability model data of conventional power source multi-gear deep peak-shaving is generated.

[0230] Among them, the transient stability model data of multi-speed deep peak regulation of conventional power sources include:

[0231] The first regulating system model GJ data, the second regulating system model GJ+ data, the electro-hydraulic servo system model data, and the series combination and single reheater steam turbine model data;

[0232] The first regulating system model GJ data includes: speed measurement link time constant, speed deviation dead zone, speed deviation magnification, control mode selection, PID proportional link multiple, PID differential link multiple, PID integral link multiple, PID integral link limit upper limit, PID integral link limit lower limit, PID output limit link upper limit, PID output limit link lower limit, load control feedforward coefficient, primary frequency modulation load upper limit and primary frequency modulation load lower limit;

[0233] The second regulation system model GJ+ data includes: the pure delay time of the frequency input signal, the pure delay time of the power feedback signal, the first-order inertia link time constant corresponding to the power feedback signal, the pure delay time after the frequency signal is amplified, the pure delay time of the input PID after the frequency signal is amplified, the rising rate limit of the input PID signal after the frequency signal is amplified, and the falling rate limit of the input PID signal after the frequency signal is amplified;

[0234] The electro-hydraulic servo system model data includes: rated output power of the prime mover, oil motor closing time constant, oil motor opening time constant, overspeed closing coefficient, overspeed opening coefficient, maximum stroke of the oil motor or maximum opening of the regulating valve, minimum stroke of the oil motor or minimum opening of the regulating valve, oil motor stroke feedback link time, PID module proportional amplification link multiple, PID module differential amplification link multiple, PID module integral amplification link multiple, PID module integral link output upper limit, PID module integral link output lower limit, PID module output upper limit and PID module output lower limit;

[0235] Model data for series combination and single reheater steam turbines, including: steam volume time constant, high pressure cylinder power ratio, reheater time constant, intermediate pressure cylinder power ratio, cross pipe time constant, low pressure cylinder power ratio and high pressure cylinder power natural overshoot coefficient.

[0236] According to the basic operation mode data, the power flow active output data of different gears of the pumped storage unit are generated, including:

[0237] In the basic operation mode data, a set of pumped storage units that simultaneously meet the voltage level condition, the partition condition and the keyword condition is screened out, and a set of actual / maximum active output values ​​of the pumped storage units in the set of pumped storage units is marked;

[0238] According to the marked maximum active output value set of the pumped-storage unit and the given pumped-storage operating condition gear set, the power flow active output data for different gears of the pumped-storage unit are generated.

[0239] According to the basic operation mode data, the power flow active output data of the new energy power generation unit is generated, including:

[0240] In the basic operation mode data, a set of new energy power generation units that simultaneously meet the voltage level condition, the partition condition and the keyword condition are screened out, and the actual active output value set of the new energy power generation units in the set of new energy power generation units is marked;

[0241] According to the actual active power output value set of the marked new energy power generation unit, the power flow active power output data of the new energy power generation unit is generated.

[0242] Among them, the power flow reactive configuration data of the whole set of evolutionary operation modes is generated, including:

[0243] For the active power calculation data of the whole set of evolutionary operation modes, the initial flow calculation data of the whole set of evolutionary operation modes is generated, and the flow calculation is performed to perform classification processing, generate the reactive power configuration data of the whole set of evolutionary operation modes, and then generate the flow calculation data of the whole set of evolutionary operation modes.

[0244] Among them, the grid operation modes for generating sorting include:

[0245] According to the flow verification calculation data of the whole set of evolutionary operation modes and the transient stability model data of the whole set of evolutionary operation mode verification calculation data, a whole set of evolutionary operation mode verification calculation data is generated, fault verification calculation is performed on the whole set of evolutionary operation mode verification calculation data, and the number of instability faults corresponding to the evolutionary modes is sorted to obtain the sorted power grid operation mode.

[0246] Among them, the power grid operation mode with a small number of unstable faults is recommended as the preferred power grid operation mode.

[0247] The present invention realizes automatic generation and sequencing of power grid operation modes under deep peak regulation conditions.

[0248] Embodiment 3:

[0249] Based on the same inventive concept, the present invention also provides a computer device, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding functions, so as to implement the steps of the method in the above embodiment.

[0250] Embodiment 4:

[0251] Based on the same inventive concept, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It is understandable that the computer-readable storage medium here can include both built-in storage media in a computer device and, of course, an extended storage medium supported by the computer device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the method in the above embodiment.

[0252] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0253] 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.

[0254] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0255] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0256] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0257] 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 method for generating a power grid operation mode considering deep peak regulation of conventional power sources, characterized in that: include: Constructing basic operation mode data of the power grid, and generating power flow active output data of multi-level deep peak regulation of conventional power sources according to the basic operation mode data; According to the basic operation mode data, by measuring the parameters of the generator, the transient stability model data of the multi-gear deep peak regulation of the conventional power supply is generated; according to the basic operation mode data, the current active output data of the pumped storage unit at different gears and the current active output data of the new energy power generation unit are generated; Based on the current active output data of the conventional power supply with multiple gears for deep peak regulation, the current active output data of the pumped storage unit with different gears, and the current active output data of the new energy power generation unit, a set of current active output data of the evolutionary operation mode is generated; Based on the basic operation mode data and the power flow active output data of the whole set of evolutionary operation modes, generating the initial calculation data of the power flow of the whole set of evolutionary operation modes; Based on the initial calculation data of the power flow of the whole set of evolutionary operation modes, generating the power flow reactive configuration data of the whole set of evolutionary operation modes; Based on the initial calculation data of the power flow of the whole set of evolutionary operation modes and the reactive power configuration data of the power flow of the whole set of evolutionary operation modes, the power flow calculation data of the whole set of evolutionary operation modes are generated; based on the power flow calculation data of the whole set of evolutionary operation modes and the transient stability model data of multi-speed deep peak regulation of conventional power sources, the power flow verification calculation data of the whole set of evolutionary operation modes are generated; based on the power flow verification calculation data of the whole set of evolutionary operation modes, a sorted power grid operation mode is generated through fault verification.

2. The method according to claim 1, characterized in that The basic operation mode data of the power grid includes: Power grid flow data and transient stability model data; The power grid flow data includes: transmission line model data, transformer model data, busbar model data, actual / maximum active output data of conventional power sources, actual / maximum active output data of pumped storage units, and actual active output data of new energy power generation units; The transient stability model data includes: conventional generator model data, excitation system model data, stabilizer model data, speed regulator and prime mover model data and new energy model data; The governor and prime mover model data include: the first regulation system model GJ data, the second regulation system model GJ+ data, the electro-hydraulic servo system model data, and the series combination and single reheater steam turbine model data.

3. The method according to claim 1, characterized in that The generating of the power flow active output data of the conventional power supply multi-level deep peak regulation according to the basic operation mode data includes: In the basic operation mode data, a set of generators that simultaneously meet the voltage level condition, the partition condition and the keyword condition are screened out, and a set of actual / maximum active output values ​​of the generators in the set of generators is marked; According to the marked maximum active output value set of the generator and the given deep peak-shaving gear set of the conventional thermal power units, the power flow active data of the conventional power source multi-gear deep peak-shaving is generated.

4. The method according to claim 1, characterized in that: The method of generating transient stability model data of multi-gear deep peak regulation of conventional power supply by measuring generator parameters according to the basic operation mode data includes: According to the generator set, the generator maximum active output value set and the given conventional thermal power unit deep peak-shaving gear set, based on the measured data of generator parameters and in accordance with the preset format, the transient stability model data of conventional power source multi-gear deep peak-shaving is generated.

5. The method according to claim 4, characterized in that The transient stability model data of the conventional power supply multi-level deep peak regulation includes: The first regulating system model GJ data, the second regulating system model GJ+ data, the electro-hydraulic servo system model data, and the series combination and single reheater steam turbine model data; The first regulating system model GJ data includes: speed measurement link time constant, speed deviation dead zone, speed deviation magnification, control mode selection, PID proportional link multiple, PID differential link multiple, PID integral link multiple, PID integral link limit upper limit, PID integral link limit lower limit, PID output limit link upper limit, PID output limit link lower limit, load control feedforward coefficient, primary frequency modulation load upper limit and primary frequency modulation load lower limit; The second regulation system model GJ+ data includes: the pure delay time of the frequency input signal, the pure delay time of the power feedback signal, the first-order inertia link time constant corresponding to the power feedback signal, the pure delay time after the frequency signal is amplified, the pure delay time of the input PID after the frequency signal is amplified, the rising rate limit of the input PID signal after the frequency signal is amplified, and the falling rate limit of the input PID signal after the frequency signal is amplified; The electro-hydraulic servo system model data includes: rated output power of the prime mover, oil motor closing time constant, oil motor opening time constant, overspeed closing coefficient, overspeed opening coefficient, maximum stroke of the oil motor or maximum opening of the regulating valve, minimum stroke of the oil motor or minimum opening of the regulating valve, oil motor stroke feedback link time, PID module proportional amplification link multiple, PID module differential amplification link multiple, PID module integral amplification link multiple, PID module integral link output upper limit, PID module integral link output lower limit, PID module output upper limit and PID module output lower limit; Model data for series combination and single reheater steam turbines, including: steam volume time constant, high pressure cylinder power ratio, reheater time constant, intermediate pressure cylinder power ratio, cross pipe time constant, low pressure cylinder power ratio and high pressure cylinder power natural overshoot coefficient.

6. The method according to claim 1, characterized in that The step of generating the power flow active output data of different gears of the pumped storage unit according to the basic operation mode data includes: In the basic operation mode data, a set of pumped storage units that simultaneously meet the voltage level condition, the partition condition and the keyword condition is screened out, and a set of actual / maximum active output values ​​of the pumped storage units in the set of pumped storage units is marked; According to the marked maximum active output value set of the pumped-storage unit and the given pumped-storage operating condition gear set, the power flow active output data for different gears of the pumped-storage unit are generated.

7. The method according to claim 1, characterized in that The step of generating the power flow active output data of the new energy power generation unit according to the basic operation mode data includes: In the basic operation mode data, a set of new energy power generation units that simultaneously meet the voltage level condition, the partition condition and the keyword condition are screened out, and the actual active output value set of the new energy power generation units in the set of new energy power generation units is marked; According to the actual active power output value set of the marked new energy power generation unit, the power flow active power output data of the new energy power generation unit is generated.

8. The method according to claim 1, characterized in that The generating of the power flow reactive configuration data of the whole set of evolutionary operation modes includes: For the active power calculation data of the whole set of evolutionary operation modes, the initial flow calculation data of the whole set of evolutionary operation modes is generated, and the flow calculation is performed to perform classification processing, generate the reactive power configuration data of the whole set of evolutionary operation modes, and then generate the flow calculation data of the whole set of evolutionary operation modes.

9. The method according to claim 1, characterized in that: The power grid operation mode of generating the ranking includes: According to the flow verification calculation data of the whole set of evolutionary operation modes and the transient stability model data of the whole set of evolutionary operation mode verification calculation data, a whole set of evolutionary operation mode verification calculation data is generated, fault verification calculation is performed on the whole set of evolutionary operation mode verification calculation data, and the number of instability faults corresponding to the evolutionary modes is sorted to obtain the sorted power grid operation mode.

10. The method according to claim 9, characterized in that The grid operation mode with a small number of unstable faults is the preferred grid operation mode.

11. A system for generating a power grid operation mode taking into account deep peak regulation of conventional power sources, characterized in that: include: A first data generating unit is used to construct basic operation mode data of the power grid, and generate power flow active output data of multi-speed deep peak regulation of conventional power sources according to the basic operation mode data; According to the basic operation mode data, by measuring the parameters of the generator, the transient stability model data of the multi-gear deep peak regulation of the conventional power supply is generated; according to the basic operation mode data, the current active output data of the pumped storage unit at different gears and the current active output data of the new energy power generation unit are generated; A second data generating unit is used to generate the current active output data of the whole set of evolutionary operation modes based on the current active output data of the conventional power supply multi-gear deep peak regulation, the current active output data of the pumped storage unit at different gears, and the current active output data of the new energy power generation unit; Based on the basic operation mode data and the power flow active output data of the whole set of evolutionary operation modes, generating the initial calculation data of the power flow of the whole set of evolutionary operation modes; Based on the initial calculation data of the power flow of the whole set of evolutionary operation modes, generating the power flow reactive configuration data of the whole set of evolutionary operation modes; The output unit is used to generate the power flow calculation data of the whole set of evolutionary operation modes based on the initial power flow calculation data of the whole set of evolutionary operation modes and the power flow reactive configuration data of the whole set of evolutionary operation modes; generate the power flow verification calculation data of the whole set of evolutionary operation modes based on the power flow calculation data of the whole set of evolutionary operation modes and the transient stability model data of multi-speed deep peak regulation of conventional power sources; and generate a sorted power grid operation mode through fault verification based on the power flow verification calculation data of the whole set of evolutionary operation modes.

12. The system according to claim 11, characterized in that The basic operation mode data of the power grid includes: Power grid flow data and transient stability model data; The power grid flow data includes: transmission line model data, transformer model data, busbar model data, actual / maximum active output data of conventional power sources, actual / maximum active output data of pumped storage units, and actual active output data of new energy power generation units; The transient stability model data includes: conventional generator model data, excitation system model data, stabilizer model data, speed regulator and prime mover model data and new energy model data; The governor and prime mover model data include: the first regulation system model GJ data, the second regulation system model GJ+ data, the electro-hydraulic servo system model data, and the series combination and single reheater steam turbine model data.

13. The system according to claim 11, characterized in that The generating, according to the basic operation mode data, the power flow active output data of the conventional power supply multi-gear deep peak regulation includes: In the basic operation mode data, a set of generators that simultaneously meet the voltage level condition, the partition condition and the keyword condition are screened out, and a set of actual / maximum active output values ​​of the generators in the set of generators is marked; According to the marked maximum active output value set of the generator and the given deep peak-shaving gear set of the conventional thermal power units, the power flow active data of the conventional power source multi-gear deep peak-shaving is generated.

14. The system according to claim 11, characterized in that The method of generating transient stability model data of multi-gear deep peak regulation of conventional power supply by measuring generator parameters according to the basic operation mode data includes: According to the generator set, the generator maximum active output value set and the given conventional thermal power unit deep peak-shaving gear set, based on the measured data of generator parameters and in accordance with the preset format, the transient stability model data of conventional power source multi-gear deep peak-shaving is generated.

15. The system according to claim 14, characterized in that The transient stability model data of the conventional power supply multi-level deep peak regulation includes: The first regulating system model GJ data, the second regulating system model GJ+ data, the electro-hydraulic servo system model data, and the series combination and single reheater steam turbine model data; The first regulating system model GJ data includes: speed measurement link time constant, speed deviation dead zone, speed deviation magnification, control mode selection, PID proportional link multiple, PID differential link multiple, PID integral link multiple, PID integral link limit upper limit, PID integral link limit lower limit, PID output limit link upper limit, PID output limit link lower limit, load control feedforward coefficient, primary frequency modulation load upper limit and primary frequency modulation load lower limit; The second regulation system model GJ+ data includes: the pure delay time of the frequency input signal, the pure delay time of the power feedback signal, the first-order inertia link time constant corresponding to the power feedback signal, the pure delay time after the frequency signal is amplified, the pure delay time of the input PID after the frequency signal is amplified, the rising rate limit of the input PID signal after the frequency signal is amplified, and the falling rate limit of the input PID signal after the frequency signal is amplified; The electro-hydraulic servo system model data includes: rated output power of the prime mover, oil motor closing time constant, oil motor opening time constant, overspeed closing coefficient, overspeed opening coefficient, maximum stroke of the oil motor or maximum opening of the regulating valve, minimum stroke of the oil motor or minimum opening of the regulating valve, oil motor stroke feedback link time, PID module proportional amplification link multiple, PID module differential amplification link multiple, PID module integral amplification link multiple, PID module integral link output upper limit, PID module integral link output lower limit, PID module output upper limit and PID module output lower limit; Model data for series combination and single reheater steam turbines, including: steam volume time constant, high pressure cylinder power ratio, reheater time constant, intermediate pressure cylinder power ratio, cross pipe time constant, low pressure cylinder power ratio and high pressure cylinder power natural overshoot coefficient.

16. The system according to claim 11, characterized in that The step of generating the power flow active output data of different gears of the pumped storage unit according to the basic operation mode data includes: In the basic operation mode data, a set of pumped storage units that simultaneously meet the voltage level condition, the partition condition and the keyword condition is screened out, and a set of actual / maximum active output values ​​of the pumped storage units in the set of pumped storage units is marked; According to the marked maximum active output value set of the pumped-storage unit and the given pumped-storage operating condition gear set, the power flow active output data for different gears of the pumped-storage unit are generated.

17. The system according to claim 11, characterized in that The step of generating the power flow active output data of the new energy power generation unit according to the basic operation mode data includes: In the basic operation mode data, a set of new energy power generation units that simultaneously meet the voltage level condition, the partition condition and the keyword condition are screened out, and the actual active output value set of the new energy power generation units in the set of new energy power generation units is marked; According to the actual active power output value set of the marked new energy power generation unit, the power flow active power output data of the new energy power generation unit is generated.

18. The system according to claim 11, characterized in that The generating of the power flow reactive configuration data of the whole set of evolutionary operation modes includes: For the active power calculation data of the whole set of evolutionary operation modes, the initial flow calculation data of the whole set of evolutionary operation modes is generated, and the flow calculation is performed to perform classification processing, generate the reactive power configuration data of the whole set of evolutionary operation modes, and then generate the flow calculation data of the whole set of evolutionary operation modes.

19. The system according to claim 11, characterized in that The power grid operation mode of generating the ranking includes: According to the flow verification calculation data of the whole set of evolutionary operation modes and the transient stability model data of the whole set of evolutionary operation mode verification calculation data, a whole set of evolutionary operation mode verification calculation data is generated, fault verification calculation is performed on the whole set of evolutionary operation mode verification calculation data, and the number of instability faults corresponding to the evolutionary modes is sorted to obtain the sorted power grid operation mode.

20. The system according to claim 19, characterized in that The grid operation mode with a small number of unstable faults is the preferred grid operation mode.

21. A computer device, characterized in that: include: one or more processors; a processor for executing one or more programs; When the one or more programs are executed by the one or more processors, the method according to any one of claims 1 to 10 is implemented.

22. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed, the method according to any one of claims 1 to 10 is implemented.

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