A Method for Constructing a Multi-State Model of Hydropower Units Considering Load Time-Sequence Fluctuations

Abstract

This invention discloses a method for constructing a multi-state model of hydropower units that takes into account load temporal fluctuations. It focuses on the impact of regional time-period water inflow restrictions and system safety constraints, corrects the outage characteristics of the hydropower unit model within a fixed period, correlates the outage characteristics of the units with load locations, and converts the unit failure rate into a dynamic calculation process. Simultaneously, considering the impact of system safety constraints, it optimizes the unit commissioning sequence under the constraints of system ramp-up capacity reserve and spinning reserve, obtaining richer system operation information, including system reliability indicators, safety margin indicators, and unit start-up and shutdown frequency, providing a reference for power system safety assessment.

Description

Technical Field

[0001] This invention belongs to the field of power system optimization and dispatching technology, specifically involving a method for constructing a multi-state model of hydropower units that takes into account the temporal fluctuations of load. Background Technology

[0002] In the past, when conducting stochastic production simulation calculations, the hydropower unit models were not detailed enough. They often used two-state unit models and equivalent power function methods to perform convolution operations to obtain the power generation of each unit and the reliability indicators of the entire system. However, this method can only reflect the failure characteristics of the units based on the forced outage rate. At the same time, the equivalent power curve is a probability curve and ignores the impact of load time-series fluctuations. Therefore, traditional stochastic production simulation is difficult to calculate the dynamic indicators within the system. With the large-scale integration of new energy sources and frequent unit start-ups and shutdowns, higher demands are placed on the accuracy of stochastic production models and the calculation results. Therefore, it is particularly important to correct the unit state output based on load time-series information. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a method for constructing a multi-state model of a hydropower unit that takes into account the temporal fluctuations of the load, in order to solve the technical problem that the hydropower unit model calculated in stochastic production simulation is too coarse.

[0004] The present invention adopts the following technical solution:

[0005] A method for constructing a multi-state model of a hydropower unit that takes into account load temporal fluctuations includes the following steps:

[0006] S1. Obtain basic technical data for power systems containing new energy sources;

[0007] S2. Construct a multi-state model of hydropower units based on the basic technical data of the power system containing new energy sources obtained in step S1;

[0008] S3. Based on the multi-state model of the hydropower unit obtained in step S2, optimize the unit commissioning sequence under the condition of considering system safety constraints, and at the same time perform random production simulation calculations to obtain operating information including system reliability indicators, adequacy indicators and total system cost.

[0009] Preferably, in step S1, the basic technical data of the power system containing new energy sources include: operating parameters of various generating units, predicted values ​​of new energy sources and loads, available power generation water volume of hydropower units, and unit maintenance plans.

[0010] Preferably, in step S2, based on the operating status, the multi-state model of the hydropower unit includes a start-stop peak-shaving unit model and a load-reducing peak-shaving unit model. The unit state probability is solved using a Markov transition matrix model. During the solution process, the state transition parameters in the start-stop peak-shaving unit model and the load-reducing peak-shaving unit model are dynamically determined by the load interval where the unit is located. The specific process is as follows: the load operating interval corresponding to the unit is determined based on the available power generation of the hydropower unit within the time period; the parameters of the multi-state model of the unit are determined based on the time sequence information of the load interval; at the same time, the equivalent generator units are merged based on the available power of the interval and the power consumed by the load, and power exchange is carried out within the equivalent units; for redundant water volume, power is adjusted by adjusting the position with adjacent thermal power units.

[0011] More preferably, the start-up and shutdown of peak-shaving unit A and load-regulating unit A′ are respectively:

[0012]

[0013]

[0014] in, Let P be the system demand rate and non-demand rate of unit i. s μ represents the probability of unit startup failure. T Let λ be the probability of unit repair. T μ represents the probability of unit failure. T λ represents the probability of repair when the unit is under rated conditions. T T represents the failure probability of the unit under rated conditions. R λ is the ramp-up time for the unit to rise from zero output to rated output. D μ represents the probability of a unit failing under reduced output conditions. D T represents the probability of repairing the unit while it is under derating conditions. R2 This refers to the ramp-up time required for the unit to climb from minimum output to rated output.

[0015] More preferably, equivalent generator units are merged when adjacent hydropower units meet the following principles:

[0016] E A1 ≤E L1

[0017] E A1 +E A2 ≥E L1 +E L2

[0018] Among them, E A1 E represents the available power generation of the first hydroelectric unit. L1 E represents the electricity that the first hydropower unit should handle within its current operating range. A2E represents the available power generation capacity of the second hydroelectric unit. L2 The amount of electricity that the second hydropower unit should handle is within the operating range of the current unit.

[0019] Preferably, in step S3, the random production simulation calculation includes the correction of the equivalent power function and the equivalent frequency curve, the correction of system safety constraints, and the generation of system operation indicators;

[0020] The correction of the equivalent power function and the equivalent frequency curve is as follows: After obtaining the multi-state model of the unit, the states of the units with the same power generation capacity are merged to obtain the equivalent two-state and equivalent three-state models. At the same time, according to the system reserve and ramp-up reserve requirements, the units are put into operation accordingly, and the system equivalent load frequency curve and the equivalent power function are corrected.

[0021] The modification of system safety constraints includes system ramp-up reserve constraints and spin-up reserve constraints;

[0022] System operation indicators include power system reliability indicators, power system adequacy indicators, and total power system cost.

[0023] More preferably, for the equivalent two-state model, the correction process for the equivalent load frequency curve and the equivalent energy function is as follows:

[0024]

[0025]

[0026] in, The probability of the unit reaching zero output, i.e., the equivalent unit failure rate. The equivalent repair rate of the unit is given by E, where T is the simulation period, Δx is the discrete common factor, and E is the simulation period. (i) (J) represents the insufficient charge value at point J corresponding to the equivalent charge function, K i Let the capacity of the i-th unit be C i The value after being discretized by the common factor Δx;

[0027] For the equivalent three-state model, the correction process for the equivalent load frequency curve and the equivalent energy function is as follows:

[0028] When the first segment of the unit is put into operation, it is processed according to an equivalent two-state model. When the second segment is put into operation, the influence of the first segment is first removed and then deconvolved out.

[0029]

[0030]

[0031] Subsequently, the system curves were corrected based on the three-state model of the unit:

[0032]

[0033]

[0034] in, This is the median value of the equivalent energy function curve obtained by deconvolving the first stage output of the unit when the second stage of the unit is put into operation. F is the median value of the equivalent load frequency curve obtained by deconvolution of the unit's first-stage output when the unit is put into operation for the second stage of output. (i-1) (J) represents the equivalent frequency load curve calculated after the i-1 generating units were put into operation, and E (i-1) (J) is the equivalent power function curve calculated after the i-1 generating units were put into operation. for It shifted to the right The value corresponding to the unit. These represent the rated output probability, derating output probability, and zero output probability of the equivalent three-state unit, respectively, λ. T , λ e1 , λ e2 These are the equivalent transfer rates from the rated output state to the fault state, from the rated output state to the reduced output state, and from the reduced output state to the fault state, respectively.

[0035] More preferably, the system has a ramp-up backup constraint:

[0036]

[0037] System spin-off standby constraints:

[0038]

[0039] in, For emergency backup. For load growth reserves, δ max,i (X i ) represents the load growth rate at the current load level, Δt represents the ramp-up time, and t0 represents the required spindle reserve activation time.

[0040] More preferably, the power system reliability index is:

[0041]

[0042]

[0043] The power system adequacy index BM is:

[0044]

[0045] Total cost of power system C total for:

[0046] C total =C fuel +C carbon +C d +C drop,w +C load

[0047] Where LOLP is the probability of insufficient system power, E (i) (J i () represents the equivalent charge function curve in J i The value of a point, in practical terms, signifies commissioning. The unmet power demand of the system after the unit capacity is reached, where T is the simulation dispatch period, Δx is the power dispersion common factor, EENS is the expected power shortage of the system, and E Gen E represents the expected available capacity of the generator set. load For the expected load demand, C fuel For the cost of coal consumption in thermal power, C carbon For carbon emission costs, C d For unit start-up and shutdown costs, C drop,w As punishment for abandoning water, C load This is a penalty for loss of load.

[0048] Secondly, embodiments of the present invention provide a multi-state model construction system for hydropower units that takes into account load time-series fluctuations, including:

[0049] The data module acquires basic technical data for power systems including new energy sources;

[0050] The construction module is based on the basic technical data of the power system including new energy sources obtained from the data module to construct a multi-state model of hydropower units;

[0051] The calculation module, based on the multi-state model of the hydropower unit obtained from the construction module, optimizes the unit commissioning sequence under the condition of considering system safety constraints, and performs random production simulation calculations to obtain operating information including system reliability indicators, adequacy indicators and total system cost.

[0052] Thirdly, a chip includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method for constructing a multi-state model of a hydropower unit that takes into account load timing fluctuations.

[0053] Fourthly, embodiments of the present invention provide an electronic device, including a computer program, which, when executed by the electronic device, implements the steps of the above-described method for constructing a multi-state model of a hydropower unit that takes into account load time-series fluctuations.

[0054] Compared with the prior art, the present invention has at least the following beneficial effects:

[0055] A multi-state model construction method for hydropower units that considers load temporal fluctuations is proposed. This method comprehensively considers load temporal fluctuations, scenario-specific water inflow limitations, and system safety constraints, aiming to achieve power balance and supply equilibrium. A stochastic calculation process is constructed to effectively address the problem of overly coarse hydropower unit models in stochastic production simulations, thus refining the multi-state model. Through stochastic production simulation calculations, richer system operation information is obtained, including system reliability indicators, safety margin indicators, and unit start-up and shutdown frequency, providing a reference for power system safety assessment.

[0056] Furthermore, fundamental power system data is a prerequisite for establishing mathematical models for multi-state model generation systems.

[0057] Furthermore, the multi-state model generation system is the foundation for realizing a stochastic generation simulation measurement system.

[0058] Furthermore, the random generation simulation calculation system is used to obtain system operation information, including system reliability indicators, safety margin indicators, and the number of unit start-ups and shutdowns, which is the basis for the safety assessment of the power system.

[0059] Furthermore, by setting the equivalent load frequency curve and the equivalent power function curve, the load time sequence information of the unit in the current operating range is extracted, the operating probability of the unit in the current operating range is generated, and a multi-state model of hydropower unit equipment considering load time sequence fluctuations is established in combination with the water inflow limit. This makes up for the shortcomings of the traditional stochastic production simulation model of hydropower unit which is difficult to consider the load time sequence characteristics, and refines the power output model of hydropower unit.

[0060] Furthermore, by introducing system safety constraints, the unit commissioning sequence was optimized, which improved upon the previous practice of arranging unit commissioning based on economic order during random production simulations, which ignored the system's reserve capacity requirements, and balanced system safety and economy.

[0061] Furthermore, reliability and economic indicators are introduced. The reliability indicators include the probability of power shortage (LOLP), the expected power shortage (EENS), and the power system adequacy indicator (BM). The economic indicator is the system cost (C). total The actual scheduling of staff provides a reference, helping them to have an intuitive understanding of the rationality of the current unit arrangement. Through the power system adequacy index, it is easier to discover the risk of power imbalance in production. Furthermore, the dynamic index of unit start-up and shutdown costs is included in the economic indicators, which makes up for the shortcomings of traditional random production simulation methods that ignore system dynamic information, and provides a reference for power system safety assessment.

[0062] It is understandable that the beneficial effects of the second aspect mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0063] In summary, this invention provides a multi-state model for hydropower units that considers load time-series fluctuations. By correlating hydropower output with load fluctuations while taking into account scenario inflow constraints, it refines the output model of hydropower units. At the same time, it optimizes the load-bearing sequence of units under the condition of considering system safety constraints, and finally obtains richer system operation information, including system reliability indicators, safety margin indicators, and unit start-up and shutdown frequency, providing a reference for the safety assessment of power systems.

[0064] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0065] Figure 1 This is a schematic diagram of the process of the present invention;

[0066] Figure 2 Flowchart for random production simulation calculation;

[0067] Figure 3 A schematic diagram of a computer device provided in an embodiment of the present invention;

[0068] Figure 4 This is a block diagram of a chip provided according to an embodiment of the present invention. Detailed Implementation

[0069] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0070] In the description of this invention, it should be understood that the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0071] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0072] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Additionally, the character " / " in this invention generally indicates that the preceding and following objects have an "or" relationship.

[0073] It should be understood that although terms such as first, second, third, etc., may be used in the embodiments of the present invention to describe the preset range, these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from one another. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0074] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0075] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0076] This invention provides a method for constructing a multi-state model of hydropower units that takes into account load temporal fluctuations. It comprehensively considers load temporal fluctuations, scenario-specific water inflow limitations, and system safety constraints, aiming to achieve power balance and supply equilibrium. A stochastic calculation process is constructed to effectively solve the problem of overly coarse hydropower unit models in stochastic production simulations, thus refining the multi-state model of hydropower units. Through stochastic production simulation calculations, richer system operation information can be obtained, including system reliability indicators, safety margin indicators, and unit start-up and shutdown frequency, providing a reference for power system safety assessment.

[0077] Please see Figure 1 The present invention provides a method for constructing a multi-state model of a hydropower unit that takes into account the temporal fluctuations of load, comprising the following steps:

[0078] S1. Obtain basic technical data for power systems containing new energy sources;

[0079] Basic technical data includes: operating parameters of various generating units, predicted values ​​of new energy sources and loads, available water volume for hydropower generation, and unit maintenance plans.

[0080] S2. Construct a multi-state model of hydropower units based on the basic technical data of the power system containing new energy sources obtained in step S1;

[0081] The process for generating a multi-state model of a hydropower unit specifically includes determining the load commissioning range of the hydropower unit, and solving the multi-state model of the hydropower unit and merging it with the equivalent hydropower unit based on the Markov transition matrix.

[0082] Determine the load operating range of the hydropower unit: Assume the available power generation of the hydropower unit during the simulation period is E. A The current operating range of generating units is responsible for a load of E. L Hydropower units can operate under load in the current load range when the following conditions are met.

[0083] E L ≤E A

[0084] Solving the multi-state model of a hydropower unit based on Markov transition matrices: The Markov transition matrices A and A′ for the two types of models are as follows:

[0085] Start-up and shutdown of peak-shaving unit A:

[0086]

[0087] Unit A′ for load adjustment:

[0088]

[0089] Among them, P s μ represents the probability of unit startup failure. T Let λ be the probability of unit repair. T This represents the probability of unit failure. Let be the system demand rate and non-demand rate of unit i. Physically, this represents the number of times unit i is switched in and out per unit time. The calculation process is as follows:

[0090]

[0091]

[0092] Among them, F (i-1) (J i ) and E (i-1) (J i) represents the discretized system equivalent charge function and the system equivalent load frequency curve.

[0093] After obtaining the two types of multi-state models, the stability probabilities of each state of the unit are obtained based on the Markov transition matrix:

[0094]

[0095] Merging of equivalent hydropower units: For adjacent hydropower units in the operational section, equivalent generator units are merged when the following principles are met:

[0096] E A1 ≤E L1

[0097] E A1 +E A2 ≥E L1 +E L2

[0098] At this point, two adjacent hydropower units can be combined into one equivalent hydropower unit, whose capacity and available power generation are as follows:

[0099] C e =C1+C2

[0100] E Ae =E A1 +E A2

[0101] If the unit has redundant power:

[0102] ΔE=E A -E L

[0103] Then, the power supply is adjusted with the adjacent thermal power units to absorb redundant power.

[0104] S3. Based on the multi-state model of the hydropower unit obtained in step S2, optimize the unit commissioning sequence under the condition of considering system safety constraints, and at the same time perform random production simulation calculations to obtain operating information including system reliability indicators, adequacy indicators and system economic cost information.

[0105] Please see Figure 2 For the random production simulation calculation process, it specifically includes the correction of the equivalent power function and equivalent frequency curve, the correction of system safety constraints, and the generation of system operation indicators.

[0106] Correction of equivalent power function and equivalent frequency curve: After obtaining the multi-state model of the unit, the states of units with the same generating capacity are merged to obtain equivalent two-state and equivalent three-state models. At the same time, according to the system reserve and ramp-up reserve requirements, the units are put into operation accordingly, and the equivalent load frequency curve and equivalent power function of the system are corrected.

[0107] For the equivalent two-state model, the correction process for the equivalent load frequency curve and the equivalent energy function is as follows:

[0108]

[0109]

[0110] in, The probability of the unit reaching zero output, i.e., the equivalent unit failure rate. Let be the equivalent repair rate of the unit, T be the simulation period, and Δx be the discrete common factor.

[0111] For the equivalent three-state model, the correction process for the equivalent load frequency curve and equivalent power function is as follows: When the first segment of the unit is put into operation, it is processed according to the equivalent two-state model. When the second segment is put into operation, the influence of the first segment must first be removed, that is, it is deconvolved out:

[0112]

[0113]

[0114] Subsequently, the system curves were corrected based on the three-state model of the unit:

[0115]

[0116]

[0117] in, This is the median value of the equivalent energy function curve obtained by deconvolving the first stage output of the unit when the second stage of the unit is put into operation. F is the median value of the equivalent load frequency curve obtained by deconvolution of the unit's first-stage output when the unit is put into operation for the second stage of output. (i-1) (J) represents the equivalent frequency load curve calculated after the i-1 generating units were put into operation, and E (i-1) (J) is the equivalent power function curve calculated after the i-1 generating units were put into operation. for It shifted to the right The physical meaning of the value following the unit is as follows: When the unit is put into operation and is operating normally, all units should bear the following load during the initial power output phase. The corresponding load power, but if the unit fails, The corresponding load should be borne by all generator sets except this one, which is equivalent to this generator set and the other generator sets shifting to the right together. The unit capacity corresponding to the unit, i.e. These represent the rated output probability, derating output probability, and zero output probability of the equivalent three-state unit, respectively, λ. T , λ e1 , λ e2 These are the equivalent transfer rates from the rated output state to the fault state, from the rated output state to the reduced output state, and from the reduced output state to the fault state, respectively.

[0118] Modification of system safety constraints: System safety constraints include system ramp-up reserve constraints and spin-up reserve constraints, wherein the system ramp-up reserve constraints are:

[0119]

[0120] in, For emergency backup. For load growth reserves, δ max,i (X i ) represents the load growth rate of the current load level, which is obtained based on the time-series load curve statistics, and Δt is the ramp-up time, which is taken as 15min here.

[0121] The system spin-off reserve constraint is:

[0122]

[0123] When different sections of the unit are put into operation, the system's spinning reserve and ramp reserve are adjusted according to the unit's remaining reserve capacity and ramp rate, and the unit's operation is arranged reasonably under the condition of meeting the system's safety constraints.

[0124] The generation of system operation indicators includes power system reliability indicators, adequacy indicators, and total system cost.

[0125] Reliability metrics:

[0126]

[0127]

[0128] Adequacy Indicators:

[0129] After a round of randomized production simulation, multi-state models G for various types of units were obtained. i By performing a series of convolutions of all units according to their available capacity sequence, the available capacity sequence of all units in the system can be obtained.

[0130] Gtotal =G1⊕G2⊕…⊕G N

[0131] At this point, the expected available capacity of the system units during this simulation period is:

[0132]

[0133] Based on the time-series load curve, the expected system load E during this period can be obtained. load The system sufficiency index is then:

[0134]

[0135] The total system cost includes the coal consumption cost of the thermal power unit, carbon emission cost, unit start-up and shutdown costs, and corresponding water wastage and loss-of-load penalties, namely:

[0136] C total =C fuel +C carbon +C d +C drop,w +C load

[0137] Among them, C fuel For the cost of coal consumption in thermal power, C carbon For carbon emission costs, C d For unit start-up and shutdown costs, C drop,w As punishment for abandoning water, C load This is a penalty for loss of load.

[0138] Coal consumption cost for thermal power:

[0139]

[0140] Where E G,i,m Q represents the segmented power generation of thermal power unit i. G,i,m Let be the segmented coal consumption cost of thermal power unit i.

[0141] Carbon emission costs:

[0142]

[0143] Among them, Q carbon,i The carbon emission cost per unit of electricity generated by unit i.

[0144] Unit start-up and shutdown costs:

[0145]

[0146] Among them, Q d,i For the start-up and shutdown cost of unit i, N i p represents the number of times the unit starts and stops. s,iThis represents the probability that the unit is in a standby state.

[0147] Punishment for abandoning water:

[0148]

[0149] Among them, Q drop,w Water abandonment penalty factor.

[0150] Loss of load penalty:

[0151] C load =EENS·Q load

[0152] Among them, Q load Loss of load penalty factor.

[0153] In another embodiment of the present invention, a multi-state model construction system for hydropower units that takes into account load time-series fluctuations is provided. This system can be used to implement the above-mentioned method for constructing a multi-state model for hydropower units that takes into account load time-series fluctuations. Specifically, the multi-state model construction system for hydropower units that takes into account load time-series fluctuations includes a data module, a construction module, and a calculation module.

[0154] The data module acquires basic technical data of the power system, including new energy sources.

[0155] The construction module is based on the basic technical data of the power system including new energy sources obtained from the data module to construct a multi-state model of hydropower units;

[0156] The calculation module, based on the multi-state model of the hydropower unit obtained from the construction module, optimizes the unit commissioning sequence under the condition of considering system safety constraints, and performs random production simulation calculations to obtain operating information including system reliability indicators, adequacy indicators and total system cost.

[0157] In another embodiment of the present invention, a terminal device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes 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 (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to achieve a corresponding method flow or corresponding function. The processor described in this embodiment can be used in the operation of a multi-state model construction method for hydropower units considering load timing fluctuations, including:

[0158] Acquire basic technical data of power systems containing new energy sources; construct a multi-state model of hydropower units based on the obtained basic technical data of power systems containing new energy sources; optimize the commissioning sequence of units based on the obtained multi-state model of hydropower units under the condition of considering system safety constraints, and conduct random production simulation calculations to obtain operating information including system reliability indicators, adequacy indicators and total system cost.

[0159] In another embodiment of the present invention, a storage medium is also provided, specifically a computer-readable storage medium (memory). This computer-readable storage medium is a memory device in a terminal device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and extended storage media supported by the terminal device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device.

[0160] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the multi-state model construction method for hydropower units considering load timing fluctuations in the above embodiments; one or more instructions in the computer-readable storage medium are loaded and executed by the processor in the following steps:

[0161] Acquire basic technical data of power systems containing new energy sources; construct a multi-state model of hydropower units based on the obtained basic technical data of power systems containing new energy sources; optimize the commissioning sequence of units based on the obtained multi-state model of hydropower units under the condition of considering system safety constraints, and conduct random production simulation calculations to obtain operating information including system reliability indicators, adequacy indicators and total system cost.

[0162] Please see Figure 3 The terminal device is a computer device. In this embodiment, the computer device 60 includes a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When executed by the processor 61, the computer program 63 implements the fluid composition calculation method in the reservoir stimulation wellbore of this embodiment. To avoid repetition, these details are not elaborated here. Alternatively, when executed by the processor 61, the computer program 63 implements the functions of each model / unit in the fluid composition calculation system in the reservoir stimulation wellbore of this embodiment. To avoid repetition, these details are not elaborated here.

[0163] Computer device 60 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. Computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will understand that... Figure 3 This is merely an example of computer device 60 and does not constitute a limitation on computer device 60. It may include more or fewer components than shown, or combine certain components, or different components. For example, computer device may also include input / output devices, network access devices, buses, etc.

[0164] The processor 61 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0165] The memory 62 can be an internal storage unit of the computer device 60, such as a hard disk or RAM of the computer device 60. The memory 62 can also be an external storage device of the computer device 60, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. equipped on the computer device 60.

[0166] Furthermore, the memory 62 may include both internal storage units of the computer device 60 and external storage devices. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 can also be used to temporarily store data that has been output or will be output.

[0167] Please see Figure 4 The terminal device is a chip. In this embodiment, the chip 600 includes a processor 622, which may be one or more, and a memory 632 for storing computer programs executable by the processor 622. The computer program stored in the memory 632 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processor 622 may be configured to execute the computer program to perform the generalizable monocular absolute depth map estimation method described above.

[0168] Additionally, chip 600 may also include a power supply component 626 and a communication component 650. The power supply component 626 can be configured to perform power management of chip 600, and the communication component 650 can be configured to enable communication of chip 600, such as wired or wireless communication. Furthermore, chip 600 may also include an input / output interface 658. Chip 600 can operate on an operating system stored in memory 632.

[0169] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0170] Case Analysis

[0171] To verify the effectiveness of the method of this invention, a virtual system was selected for case analysis. This virtual system contains 80 generating units, including 45 thermal power units and 35 hydropower units, with a total installed capacity of 21,050 MW and a maximum load of 17,922.7 MW. The effectiveness of the proposed model is verified by comparing it with the existing equivalent power function method.

[0172] Testing showed that the program developed using this method completed the adjustment process in 208.87 seconds. All calculations were performed on a computer equipped with a 12th Gen Intel(R) Core(TM) i5-12500 3.00GHz processor, and executed in MATLAB. The system metrics after randomized simulation are as follows:

[0173] Table 1 Results of Random Production Simulation

[0174]

[0175] Method 1 is the model proposed in this invention, Method 2 is the method after ignoring the forced outage rate of units and system safety constraints, and Method 3 is the equivalent power function method. As shown in Table 1 after random production, compared with the traditional equivalent power function method, the model of this invention can provide more economic indicators, such as the number of units started and stopped, start and stop costs, and other dynamic indicators. At the same time, because the influence of load time-series fluctuations and system safety constraints is considered, the actual system reliability index will be lower than the result of the traditional method, and the calculated system risk is greater. The comparison between Method 2 and Method 3 shows that the results are consistent, which verifies the correctness of the model of this invention. That is, the model in this paper is only an extension of the equivalent power function method. Under simplified conditions, the two are completely equivalent.

[0176] Table 2 Multi-state models for some units

[0177]

[0178] Table 2 presents the multi-state models of some units under the model of this invention. It can be observed that when the unit's operating capacity is lower than the base load, the unit model obtained by this invention is consistent with the traditional unit model that only considers the unit failure rate. When the unit's operating capacity is greater than the base load, the output probability of the unit changes in each state, which is a dynamic calculation process. The reason for this change is that the unit's output probability is affected by the unit's demand rate, which in turn changes with the unit's operating location. Corresponding the unit's output probability to its operating location essentially links the unit's output probability to load fluctuations, making the calculated system balance margin closer to the actual situation and preventing excessive deviations.

[0179] In summary, this invention provides a method for constructing a multi-state model of hydropower units that takes into account load temporal fluctuations. It comprehensively considers the impact of load temporal fluctuations, scenario-specific water inflow limitations, and system safety constraints on the unit's operating state. The method corrects the outage characteristics of the hydropower unit model within a fixed period, correlates the unit's outage characteristics with load location, and converts the unit failure rate into a dynamic calculation process. Simultaneously, considering the impact of system safety constraints, the method optimizes the unit commissioning sequence under the constraints of system ramp-up reserve and spinning reserve. This yields richer system operation information, including system reliability indicators, safety margin indicators, and the number of unit start-ups and shutdowns, providing a reference for power system safety assessment.

[0180] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0181] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0182] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0183] In the embodiments provided by this invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0184] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0185] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0186] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0187] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0188] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0189] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0190] The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solution based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A method for constructing a multi-state model of a hydropower unit considering load temporal fluctuations, characterized in that, Includes the following steps: S1. Obtain basic technical data for power systems containing new energy sources; S2. Based on the basic technical data of the power system including new energy sources obtained in step S1, construct a multi-state model of hydropower units. According to the operating status, the multi-state model of hydropower units includes a start-stop peak-shaving unit model and a load-reducing peak-shaving unit model. The unit state probabilities are solved using the Markov transition matrix model. During the solution process, the state transition parameters in the start-stop peak-shaving unit model and the load-reducing peak-shaving unit model are dynamically determined by the load interval where the unit is located. The specific process is as follows: determine the load operation interval corresponding to the unit based on the available power generation of the hydropower unit within the time period, and determine the parameters of the multi-state model of the unit according to the time series information of the load interval; at the same time, merge the equivalent generator units according to the available power of the interval and the power consumption of the load, and exchange power within the equivalent units; for redundant water volume, adjust the power by adjusting the position with adjacent thermal power units. Start-up and shutdown of peak-shaving units and load-regulating units They are respectively: in, For the unit The system demand rate and non-demand rate, This represents the probability of unit startup failure. For the probability of unit repair, This represents the probability of unit failure. The probability of repair when the unit is under rated conditions. This represents the probability of failure when the unit is under rated conditions. This refers to the ramp-up time for the generator unit to rise from zero output to rated output. This represents the probability of a unit failing under reduced output conditions. The probability of repairing the unit while it is under reduced capacity. The ramp-up time required for the unit to ramp up from minimum output to rated output; S3. Based on the multi-state model of the hydropower unit obtained in step S2, optimize the unit commissioning sequence under the condition of considering system safety constraints, and at the same time perform random production simulation calculations to obtain operating information including system reliability indicators, adequacy indicators and total system cost.

2. The method for constructing a multi-state model of a hydropower unit considering load time-series fluctuations according to claim 1, characterized in that, In step S1, the basic technical data of the power system including new energy sources include: operating parameters of various generating units, predicted values ​​of new energy sources and loads, available generating water volume of hydropower units, and unit maintenance plans.

3. The method for constructing a multi-state model of a hydropower unit considering load time-series fluctuations according to claim 1, characterized in that, The equivalent generating units of adjacent hydropower units shall be merged when the following principles are met: in, The available power generation capacity of the first hydroelectric unit. The electricity that the first hydropower unit should handle within the current operating range of the unit. This is the available power generation capacity of the second hydroelectric unit. The amount of electricity that the second hydropower unit should handle is within the operating range of the current unit.

4. The method for constructing a multi-state model of a hydropower unit considering load time-series fluctuations according to claim 1, characterized in that, In step S3, the random production simulation calculation includes the correction of the equivalent power function and the equivalent frequency curve, the correction of system safety constraints, and the generation of system operation indicators. The correction of the equivalent power function and the equivalent frequency curve is as follows: After obtaining the multi-state model of the unit, the states of the units with the same power generation capacity are merged to obtain the equivalent two-state and equivalent three-state models. At the same time, according to the system reserve and ramp-up reserve requirements, the units are put into operation accordingly, and the system equivalent load frequency curve and the equivalent power function are corrected. The modification of system safety constraints includes system ramp-up reserve constraints and spin-up reserve constraints; System operation indicators include power system reliability indicators, power system adequacy indicators, and total power system cost.

5. The method for constructing a multi-state model of a hydropower unit considering load time-series fluctuations according to claim 4, characterized in that, For the equivalent two-state model, the correction process for the equivalent load frequency curve and the equivalent energy function is as follows: in, The probability of the unit reaching zero output, i.e., the equivalent unit failure rate. The equivalent repair rate of the unit. For the simulation period, For discrete common factors, For the equivalent charge function in The corresponding low battery value, For the first Taiwanese unit capacity Discrete Common Factor Discrete post-values; For the equivalent three-state model, the correction process for the equivalent load frequency curve and the equivalent energy function is as follows: When the first segment of the unit is put into operation, it is processed according to an equivalent two-state model. When the second segment is put into operation, the influence of the first segment is first removed and then deconvolved out. Subsequently, the system curves were corrected based on the three-state model of the unit: in, This is the median value of the equivalent energy function curve obtained by deconvolving the first stage output of the unit when the second stage of the unit is put into operation. This is the median value of the equivalent load frequency curve obtained by deconvolving the first stage output of the unit when the second stage of the unit is put into operation. Before commissioning The equivalent frequency load curve obtained after calculating the unit. Before commissioning The equivalent energy function curve obtained after calculating the unit's power output. for It shifted to the right The value corresponding to the unit. , , These represent the rated output probability, derating output probability, and zero output probability of the equivalent three-state unit, respectively. , , These are the equivalent transfer rates from the rated output state to the fault state, from the rated output state to the reduced output state, and from the reduced output state to the fault state, respectively.

6. The method for constructing a multi-state model of a hydropower unit considering load time-series fluctuations according to claim 4, characterized in that, System ramp-up backup constraints: System spin-off standby constraints: in, For emergency backup. Reserved for load growth The load growth rate is the current load level. For the time spent climbing the hill, The required rotational standby time.

7. The method for constructing a multi-state model of a hydropower unit considering load time-series fluctuations according to claim 4, characterized in that, The reliability indicators of the power system are: Power system adequacy index for: Total cost of power system for: in, The probability of insufficient system power. For the equivalent charge function curve in The value of a point, in practical terms, signifies commissioning. The unmet power demand of the system after the unit capacity is reached. To simulate the scheduling cycle, The power discrete common factor, As the system power is insufficient, For the expected available capacity of the generator set, Assuming expected load demand, For the cost of coal consumption in thermal power plants, For carbon emission costs, For the cost of starting and stopping the unit, As punishment for abandoning water, This is a penalty for loss of load.

8. A system for constructing a multi-state model of a hydropower unit that takes into account the temporal fluctuations of load, characterized in that, include: The data module acquires basic technical data for power systems including new energy sources; The construction module, based on the basic technical data of the power system including new energy sources obtained from the data module, constructs a multi-state model of hydropower units. According to the operating state, the multi-state model of hydropower units includes a start-stop peak-shaving unit model and a load-reducing peak-shaving unit model. The unit state probabilities are solved using a Markov transition matrix model. During the solution process, the state transition parameters in the start-stop peak-shaving unit model and the load-reducing peak-shaving unit model are dynamically determined by the load interval where the unit is located. The specific process is as follows: The load operating interval corresponding to the unit is determined based on the available power generation of the hydropower unit within the time period; the parameters of the multi-state model of the unit are determined based on the time series information of the load interval; simultaneously, equivalent generating units are merged based on the available power in the interval and the power consumed by the load, and power exchange occurs within the equivalent units; for redundant water volume, power is adjusted by adjusting the position with adjacent thermal power units. Start-up and shutdown of peak-shaving units and load-regulating units They are respectively: in, For the unit The system demand rate and non-demand rate, This represents the probability of unit startup failure. For the probability of unit repair, This represents the probability of unit failure. The probability of repair when the unit is under rated conditions. This represents the probability of failure when the unit is under rated conditions. This refers to the ramp-up time for the generator unit to rise from zero output to rated output. This represents the probability of a unit failing under reduced output conditions. The probability of repairing the unit while it is under reduced capacity. The ramp-up time required for the unit to ramp up from minimum output to rated output; The calculation module, based on the multi-state model of the hydropower unit obtained from the construction module, optimizes the unit commissioning sequence under the condition of considering system safety constraints, and performs random production simulation calculations to obtain operating information including system reliability indicators, adequacy indicators and total system cost.

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