Power plant intelligent power generation control optimization method based on advanced algorithm

Abstract

The application relates to the output control field of a generator set and provides an intelligent power plant power generation control optimization method based on an advanced algorithm, which comprises the following steps: determining power generation cost models corresponding to each generator set according to historical power generation data of the generator sets; performing output adjustment tests on the generator sets to determine output adjustment flexibilities of the generator sets; determining power consumption demand prediction values in a preset prediction period based on a preset demand prediction model; and determining the output sizes of the generator sets based on the power consumption demand prediction values, the load constraint ranges of the generator sets, the power generation cost models and the output adjustment flexibilities of the generator sets based on a preset generator set scheduling model.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of output control of generator sets, and particularly relates to an intelligent power plant generation control optimization method based on an advanced algorithm. BACKGROUND

[0002] If the power generation exceeds the electricity demand, it will lead to power surplus, causing resource waste, and even threatening the safe operation of the power grid; if the power generation is insufficient, it will lead to power shortage, affecting the normal electricity use of users. Therefore, by predicting the electricity demand, the power plant can arrange the start-stop plan and load scheduling of the generator set in advance to ensure the balance between supply and demand of the power system. However, there is a large hysteresis in the adjustment of boiler combustion, resulting in a long response time and being unable to adjust quickly, which makes it difficult to meet the demand for rapid adjustment of power generation. How to improve the flexibility of power generation adjustment has become a problem to be solved. Moreover, after predicting the electricity demand, how to adjust the load of multiple generator sets of the power plant according to the electricity demand, such as adjusting the load of which generator sets and how much to adjust the load of each generator set, largely depends on human judgment. How to improve the intelligence of adjusting the size of the unit output according to the electricity demand has become a problem to be solved. SUMMARY

[0003] The main purpose of the present application is to provide an intelligent power plant generation control optimization method based on an advanced algorithm, aiming to improve the intelligence and flexibility of generator set output adjustment.

[0004] In a first aspect, the present application provides an intelligent power plant generation control optimization method based on an advanced algorithm, which comprises the following steps:

[0005] According to the historical power generation data of each generator set, a power generation cost model corresponding to each generator set is determined;

[0006] The output of each generator set is adjusted for testing, and the output adjustment elasticity of each generator set is determined;

[0007] Based on a preset demand prediction model, the electricity demand prediction in a preset prediction period is determined;

[0008] Based on a preset generator set scheduling model, according to the electricity demand prediction, and the load constraint range, the power generation cost model, and the output adjustment elasticity of each generator set, the first output size of each generator set is determined, and each generator set is adjusted according to the first output size.

[0009] In some embodiments, the determination of the power generation cost model corresponding to each generator set according to the historical power generation data of each generator set comprises:

[0010] obtaining historical power generation of the generator set and historical fuel consumption corresponding to the historical power generation;

[0011] fitting the historical power generation and the corresponding historical fuel consumption to obtain a power generation-fuel consumption curve corresponding to the generator set;

[0012] deriving the power generation-fuel consumption curve to obtain a marginal fuel cost curve;

[0013] determining unit fuel costs corresponding to different power generations according to the marginal fuel cost curve to obtain a marginal cost curve as a power generation cost model corresponding to the generator set.

[0014] In some embodiments, the determining unit fuel costs corresponding to different power generations according to the marginal fuel cost curve to obtain a marginal cost curve as a power generation cost model corresponding to the generator set comprises:

[0015] obtaining fuel procurement information corresponding to a fuel batch currently used in a material management system, and determining a unit fuel price according to the fuel procurement information;

[0016] determining the unit fuel cost according to a ratio of the unit fuel price to a preset unit fuel heat value.

[0017] In some embodiments, the power output adjustment test comprises a primary frequency modulation test, a secondary frequency modulation test, and a combustion system adjustment test, and the determining power output adjustment flexibility of each of the generator sets comprises:

[0018] performing the primary frequency modulation test on the generator set multiple times to obtain a first response index of the generator set;

[0019] performing the secondary frequency modulation test on the generator set multiple times to obtain a second response index of the generator set;

[0020] performing the combustion system adjustment test on the generator set multiple times to obtain a third response index of the generator set;

[0021] determining the power output adjustment flexibility according to the first response index, the second response index, and the third response index.

[0022] In some embodiments, the performing the primary frequency modulation test on the generator set multiple times to obtain a first response index of the generator set comprises:

[0023] adjusting an intake amount of the steam turbine of the generator set;

[0024] acquire a first output response after a first preset time length and a second output response after a second preset time length after the intake air amount is adjusted;

[0025] The first response index is calculated according to the following formula:

[0026]

[0027] wherein, represents the first output response, represents the second output response, and represents the theoretical maximum output response; the second preset time length is greater than the first preset time length.

[0028] In some embodiments, the second response index of the generator set is acquired by performing the secondary frequency modulation test on the generator set multiple times, comprising:

[0029] An automatic generation control instruction is sent to each generator set, and the adjustment speed, response time and adjustment accuracy of the generator set to the automatic generation control instruction are acquired;

[0030] The second response index of the secondary frequency modulation test is determined according to the adjustment speed, response time and adjustment accuracy.

[0031] In some embodiments, the first output size of each generator set is determined according to the power demand prediction, the load constraint range of each generator set, the power generation cost model and the output adjustment elasticity based on the preset generator set scheduling model, comprising:

[0032] According to the output adjustment elasticity, it is determined that the generator set belongs to a basic load unit or a mobile load unit;

[0033] The total load adjustment amount is determined according to the difference between the power demand prediction and the current power generation amount;

[0034] The load adjustment component corresponding to each basic load unit and mobile load unit is determined according to the load constraint range of the generator set;

[0035] The first output size of the basic load unit and the mobile load unit is adjusted based on the load adjustment component.

[0036] In some embodiments, the load adjustment component corresponding to each basic load unit and mobile load unit is determined according to the load constraint range of the generator set, comprising:

[0037] The variable load of each generator set is determined according to the load constraint range and the current load corresponding to each generator set, wherein the sum of the variable loads of the mobile load units is the total mobile variable load;

[0038] when the total load adjustment amount is less than the total variable load, determining a load adjustment component for each of the motor load units according to a proportion of a variable load of each of the motor load units in the total variable load;

[0039] when the total load adjustment amount is greater than or equal to the total variable load, determining a first load adjustment component for the base load unit, and determining a second load adjustment component according to a difference between the total load adjustment amount and the first load adjustment component, and determining a second load adjustment component for each of the motor load units according to a proportion of a variable load of each of the motor load units in the total variable load.

[0040] In some embodiments, after the first output size of the base load unit and the motor load units is adjusted based on the load adjustment component, the method further comprises:

[0041] determining a second output size of each of the power generation units according to the power generation cost model corresponding to each of the power generation units;

[0042] when the first output size of a power generation unit is less than the second output size, controlling the power generation unit to increase the first output size to the second output size;

[0043] when the first output size of a power generation unit is greater than the second output size, after the first output size is controlled to increase to the second output size, controlling the power generation unit to decrease the first output size to the second output size.

[0044] In a second aspect, the present application also provides an intelligent power plant control optimization system based on advanced algorithms, which comprises:

[0045] a cost calculation module configured to determine a power generation cost model corresponding to each of the power generation units according to historical power generation data of each of the power generation units;

[0046] an elasticity calculation module configured to determine an output adjustment elasticity of each of the power generation units by performing an output adjustment test on each of the power generation units;

[0047] a demand prediction module configured to determine a power demand prediction amount in a preset prediction period based on a preset demand prediction model;

[0048] an output adjustment module configured to determine a first output size of each of the power generation units based on a preset power generation unit scheduling model, the power demand prediction amount, a load constraint range of each of the power generation units, the power generation cost model, and the output adjustment elasticity.

[0049] The application provides an advanced algorithm-based power plant intelligent power generation control optimization method and system. The application determines a power generation cost model corresponding to each generator set according to historical power generation data of the generator sets. The application determines the power output adjustment elasticity of each generator set by performing power output adjustment tests on the generator sets. The application determines an electricity demand prediction quantity in a preset prediction period based on a preset demand prediction model. The application determines a first power output size of each generator set based on the electricity demand prediction quantity, and the load constraint range, the power generation cost model and the power output adjustment elasticity of each generator set, and adjusts each generator set according to the first power output size. The power output size of the generator set is adjusted according to the predicted electricity demand prediction quantity, the intelligence and flexibility of the power output adjustment of the generator set are improved, and the power generation cost is reduced. BRIEF DESCRIPTION OF DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0051] Figure 1 A flowchart of an advanced algorithm-based power plant intelligent power generation control optimization method provided by an embodiment of the application is shown in the figure.

[0052] Figure 2 A schematic block diagram of an advanced algorithm-based power plant intelligent power generation control optimization system provided by an embodiment of the application is shown in the figure.

[0053] Figure 3 A structural schematic block diagram of a computer device related to an embodiment of the application is shown in the figure. DETAILED DESCRIPTION

[0054] The technical solutions in the embodiments of the application will be described clearly and completely in combination with the drawings in the embodiments of the application. Obviously, the described embodiments are some embodiments of the application, not all embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the application.

[0055] The flowchart shown in the figure is only an example, not necessarily including all contents and operations / steps, and not necessarily executed in the described order. For example, some operations / steps can be decomposed, combined or partially combined, so that the actual execution order can be changed according to the actual situation.

[0056] The embodiment of the present application provides a power plant intelligent power generation control optimization method and system based on an advanced algorithm.

[0057] Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The following embodiments and features in the embodiments can be combined with each other without conflict.

[0058] Please refer to Figure 1 , Figure 1 A flowchart of a power plant intelligent power generation control optimization method based on an advanced algorithm provided by the embodiment of the present application is shown. The power plant intelligent power generation control optimization method based on an advanced algorithm can be used in a terminal or a server to determine the output size of each generator unit of a power plant and adjust the output size of each generator unit. The terminal can be an electronic device such as a mobile phone, a tablet computer, a notebook computer, a desktop computer, a personal digital assistant, and a wearable device. The server can be a stand-alone server, a server cluster, a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and basic cloud computing services such as big data and artificial intelligence platforms.

[0059] As shown in Figure 1 The power plant intelligent power generation control optimization method based on an advanced algorithm includes steps S101 to S104.

[0060] In step S101, a power generation cost model corresponding to each generator unit is determined according to historical power generation data of each generator unit.

[0061] For example, due to different combustion efficiencies and coal consumption rates, the power generation costs of different generator units are different, and the unit power generation cost of the same generator unit at different output levels is also different. Therefore, a power generation cost model corresponding to each generator unit is established to minimize the overall power generation cost of the power plant according to the power generation cost model of each generator unit.

[0062] In some embodiments, the power generation cost model corresponding to each generator unit is determined according to historical power generation data of each generator unit, including:

[0063] The historical power generation of the generator unit and the historical fuel consumption corresponding to the historical power generation are obtained;

[0064] The historical power generation and the corresponding historical fuel consumption are fitted to obtain a power generation-fuel consumption curve corresponding to the generator unit;

[0065] deriving the marginal fuel cost curve by derivation of the power generation-fuel consumption curve;

[0066] determining the unit fuel cost corresponding to different power generations according to the marginal fuel cost curve to obtain a marginal cost curve as the power generation cost model corresponding to the power generation unit.

[0067] For example, the total coal consumption of the power generation unit at different output levels is obtained by measuring the coal consumption and output of each power generation unit respectively, and the corresponding relationship between the power generation and the fuel consumption is fitted to obtain the power generation-fuel consumption curve. The marginal fuel cost corresponding to each unit increase in power generation can be obtained by first derivation of the power generation-fuel consumption curve, thereby obtaining the marginal fuel cost curve. According to the marginal fuel cost curve, the marginal cost curve corresponding to each unit increase in power generation, i.e., the curve of the unit fuel cost corresponding to different power generations, can be determined.

[0068] In some embodiments, the determination of the unit fuel cost corresponding to different power generations according to the marginal fuel cost curve to obtain a marginal cost curve as the power generation cost model corresponding to the power generation unit comprises:

[0069] obtaining the fuel procurement information corresponding to the fuel batch currently used in the material management system, and determining the unit fuel price according to the fuel procurement information;

[0070] determining the unit fuel cost according to the ratio of the unit fuel price to the preset unit fuel heat value.

[0071] For example, the unit fuel cost is ultimately related to the fuel price, and the fuel price fluctuates due to market factors, so the fuel prices of different batches are not the same. The total price of the fuel batch currently used can be obtained through the material management system, and the unit fuel price can be calculated by combining the procurement quantity. And the unit fuel cost is calculated according to the relationship of "unit fuel cost = unit fuel price / unit fuel heat value".

[0072] It can be understood that the material management system records the fuel procurement information corresponding to each fuel batch, including the procurement price and the procurement quantity. Moreover, since fuel cannot be purchased until it is used up, the material management system updates the remaining fuel quantity in each fuel batch according to the fuel consumption. For example, when the first batch of fuel is 10% remaining, a second batch of fuel is added, and the fuel consumption after the addition of fuel is still subtracted from the first batch of fuel. When the 10% fuel is used up, the fuel consumption is started to be subtracted from the second batch of fuel, thereby ensuring the orderliness of material management.

[0073] Step S102, adjusting the output of each power generation unit to determine the output adjustment flexibility of each power generation unit.

[0074] Exemplarily, the output size of the generator set is related to multiple factors, and different generator sets have different sensitivities, some generator sets can need a long time after adjusting the variable to have a significant change in the output size, and some generator sets can have the influence of adjusting reflected in the output size in a short time after adjusting the variable. Therefore, the output adjustment flexibility of each generator set can be determined through the output adjustment test, so as to quantify the rapid degree of the feedback of the variable adjustment of the generator set on the output size.

[0075] In some embodiments, the output adjustment test includes a primary frequency modulation test, a secondary frequency modulation test, and a combustion system adjustment test, and the output adjustment test on each generator set and the determination of the output adjustment flexibility of each generator set include:

[0076] The primary frequency modulation test is performed on the generator set for multiple times to obtain a first response index of the generator set;

[0077] The secondary frequency modulation test is performed on the generator set for multiple times to obtain a second response index of the generator set;

[0078] The combustion system adjustment test is performed on the generator set for multiple times to obtain a third response index of the generator set;

[0079] The output adjustment flexibility is determined according to the first response index, the second response index, and the third response index.

[0080] Exemplarily, the means for adjusting the output size of the generator set include combustion system adjustment, primary frequency modulation, and secondary frequency modulation, wherein the combustion system adjustment changes the combustion intensity of the boiler by adjusting the fuel supply amount and the air volume, so as to change the steam generation amount to adjust the output size; the primary frequency modulation adjusts the air intake amount of the steam turbine by adjusting the opening degree of the steam turbine admission valve to adjust the output size; and the secondary frequency modulation changes the output size of the generator set by sending instructions to the generator set through the automatic generation control (AGC).

[0081] The method provided by the embodiments of the present application determines the sensitivity of the output size response of each generator set when the primary frequency modulation, the secondary frequency modulation, and the combustion system adjustment are performed, that is, the first response index, the second response index, and the third response index of each generator set are respectively determined through multiple primary frequency modulation tests, secondary frequency modulation tests, and combustion system adjustment tests.

[0082] The multiple primary frequency modulation tests, the secondary frequency modulation tests, and the combustion system adjustment tests can be tests at different output levels or different adjustment levels.

[0083] In some embodiments, the multiple primary frequency modulation tests are performed on the generator set to obtain a first response index of the generator set, including:

[0084] Adjusting the intake amount of the steam turbine of the generator set;

[0085] Obtaining a first output response after a first preset time period and a second output response after a second preset time period after the adjustment of the intake amount;

[0086] The first response index is calculated according to the following formula:

[0087]

[0088] wherein, △P1 represents the first output response, △P2 represents the second output response, △P E represents a theoretical maximum output response; the second preset time period is greater than the first preset time period.

[0089] For example, the effect of primary frequency modulation on the output size is not immediate, but appears after a period of time after primary frequency modulation. Therefore, it can be understood that the change amplitude of the output size is different at different times after primary frequency modulation. The output responses at different times after primary frequency modulation can be obtained, and the first response index can be calculated based on the output responses at different times.

[0090] wherein, the first output response is the change amount between the output size measured after waiting for a first preset time period after primary frequency modulation and the original output size; the second output response is the change amount between the output size measured after waiting for a second preset time period after primary frequency modulation and the original output size. Specifically, the first preset time period can be 10 seconds, and the second preset time period can be 20 seconds, but is not limited thereto. The theoretical maximum output response represents the maximum output adjustment amount that can be provided during primary frequency modulation, which can be obtained by the frequency modulation characteristics of the generator set, and will not be described herein.

[0091] In some embodiments, the multiple secondary frequency modulation tests are performed on the generator set to obtain a second response index of the generator set, including:

[0092] The automatic generation control instruction is sent to each generator set, and the adjustment rate, the response time, and the adjustment accuracy of the generator set to the automatic generation control instruction are obtained;

[0093] The second response index of the frequency modulation test is determined according to the adjustment rate, the response time and the adjustment accuracy.

[0094] For example, the frequency modulation is performed by issuing an AGC instruction to the generator set, and the output size of the generator set is sampled after the frequency modulation is performed, so as to obtain the adjustment rate, the response time and the adjustment accuracy. The adjustment rate represents the rate of change of the output size with time, the response time represents the time length required for the change amount of the output size to be greater than a preset value, and the adjustment accuracy represents the error between the actual output size after the frequency modulation and the theoretically achievable output size.

[0095] For example, different weights are set for the adjustment rate, the response time and the adjustment accuracy, and the second response index is obtained by weighting the adjustment rate, the response time and the adjustment accuracy.

[0096] For example, the combustion system adjustment test can be an adjustment of the combustion intensity to different degrees, and the third response index is determined according to the response amplitude of the output size after the adjustment, which is not described herein.

[0097] In step S103, the power demand prediction amount in a preset prediction period is determined based on a preset demand prediction model.

[0098] For example, the change of the power demand has periodicity and seasonality, and the time series model can be used to input the time series of the historical power consumption to predict the power demand in a future period of time. For example, the ARIMA model is used to convert a non-stationary sequence into a stationary sequence through difference, and then the autoregressive (AR) and moving average (MA) are combined for modeling. Of course, the demand prediction model can also be implemented based on a regression model, which is not described herein.

[0099] In step S104, the first output size of each generator set is determined based on the power demand prediction amount, the load constraint range of each generator set, the power generation cost model and the output adjustment elasticity, and each generator set is adjusted according to the first output size.

[0100] For example, the generator set usually has a load constraint range, for example, the technical minimum load of a thermal power generator set is usually 35% to 85% of the rated load. When adjusting the power, it is necessary to ensure that the power of the unit is not lower than the technical minimum load, so as to avoid equipment damage or efficiency reduction. Therefore, in addition to the power generation cost model, the output adjustment elasticity and the power demand prediction amount, the load constraint range of each generator set is also included in the basis for determining the first output size.

[0101] In some embodiments, the first output size of each of the power generation units is determined according to the power consumption demand prediction, and the load constraint range of each of the power generation units, the power generation cost model, and the output adjustment elasticity, including:

[0102] According to the output adjustment elasticity, it is determined that the power generation unit belongs to a basic load unit or a mobile load unit;

[0103] According to the difference between the power consumption demand prediction and the current power generation, the total load adjustment amount is determined;

[0104] According to the load constraint range of the power generation unit, the corresponding load adjustment component of each of the basic load unit and the mobile load unit is determined;

[0105] The first output size of the basic load unit and the mobile load unit is adjusted based on the load adjustment component.

[0106] For example, a power generation unit with poor flexibility can bear basic load, and a power generation unit with good flexibility can bear variable load. Therefore, according to the output adjustment elasticity obtained in step S102, the power generation units are divided into basic load units and mobile load units. Specifically, the first response index, the second response index, the third response index, etc. are spliced to obtain an output adjustment elasticity vector. The output adjustment elasticity vector is input into a preset machine learning model to obtain the classification result of each power generation unit as a basic load unit or a mobile load unit according to the first response index, the second response index, and the third response index. Of course, it is not limited to this, and the basic load unit and the mobile load unit can also be divided according to the size of the output adjustment elasticity. For example, the output adjustment elasticity is less than a preset threshold, which is a basic load unit. This is not limited here.

[0107] For example, the difference between the power consumption demand prediction and the current power generation is taken as the total load adjustment amount, so as to allocate the total load adjustment amount to each power generation unit. The output of each power generation unit is adjusted by a certain size, i.e. the load adjustment component of each power generation unit, and the processing size of each power generation unit is adjusted to the first output size according to the load adjustment component.

[0108] In some embodiments, the corresponding load adjustment component of each of the basic load unit and the mobile load unit is determined according to the load constraint range of each of the power generation units, including:

[0109] According to the corresponding load constraint range of each of the power generation units and the current load, the variable load of each of the power generation units is determined, wherein the sum of the variable loads of the mobile load units is the total mobile variable load;

[0110] determining, when the total load adjustment amount is less than the total variable load of the motorized load units, a load adjustment component for each of the motorized load units according to a proportion of the variable load of each of the motorized load units in the total variable load of the motorized load units;

[0111] determining, when the total load adjustment amount is greater than or equal to the total variable load of the motorized load units, a first load adjustment component for the base load unit, and determining a second load adjustment component according to a difference between the total load adjustment amount and the first load adjustment component, and determining a second load adjustment component for each of the motorized load units according to a proportion of the variable load of each of the motorized load units in the total variable load of the motorized load units.

[0112] For example, the variable load of each of the generator units is determined according to the corresponding load constraint range and the current load of each of the generator units. Specifically, when the power generation needs to be reduced, the variable load of each of the generator units is obtained by subtracting the minimum load constraint from the current load; when the power generation needs to be increased, the variable load of each of the generator units is obtained by subtracting the current load from the maximum load constraint.

[0113] For example, when the total load adjustment amount is less than the sum of the variable loads of the motorized load units, i.e., the total load adjustment amount is less than the total variable load of the motorized load units, it means that the total load adjustment amount can be directly distributed to each of the motorized load units to enable the total power output to be rapidly changed. In this case, the load adjustment component for each of the motorized load units is determined according to a proportion of the variable load of each of the motorized load units in the total variable load of the motorized load units.

[0114] On the contrary, when the total load adjustment amount is greater than or equal to the total variable load of the motorized load units, the total load adjustment amount needs to be distributed to the motorized load units and the base load unit. It can be understood that the base load unit has poor sensitivity, and a large adjustment gradient, for example, 1 MW, can be preset. If the difference between the total load adjustment amount and the total variable load of the motorized load units is less than 1 MW, the base load unit only needs to bear 1 MW of adjustment amount. Otherwise, the first load adjustment component of the base load unit is continuously increased according to the adjustment gradient until the first load adjustment component is greater than the difference between the total load adjustment amount and the total variable load of the motorized load units. Then, the difference between the total load adjustment amount and the first load adjustment component is taken as the second load adjustment component, which is distributed to each of the motorized load units in proportion.

[0115] By preferentially adjusting the power output of the motorized load units, the total power output of the power plant can be rapidly changed according to the demand prediction, and the flexibility of power generation adjustment is improved.

[0116] In some embodiments, after the first power output of the base load unit and the motorized load units is adjusted based on the load adjustment component, the method further comprises:

[0117] determine a second output size of each of the power generators according to the power generation cost model corresponding to each of the power generators;

[0118] when the first output size of a power generator is smaller than the second output size, control the power generator to increase the first output size to the second output size;

[0119] when the first output size of a power generator is larger than the second output size, after the control of the power generator to increase the first output size to the second output size, control the power generator to decrease the first output size to the second output size.

[0120] For example, the method provided by the embodiment of the present application can preferentially adjust the output size of the power generator with mobile load, so as to improve the adjustment speed of the output size of the power plant. However, the power generation strategy determined in this way may not be economical. Therefore, after the first output size is determined, the power generation strategy can be slowly adjusted to the second output size with lower cost, so as to ensure the flexibility of the output size response and improve the economy of the power generation strategy.

[0121] For example, the second output size with optimal cost is determined according to the power generation cost model corresponding to each power generator. Specifically, the power generation cost can be used as the objective function to perform optimization by using a butterfly optimization model.

[0122] When the first output size is adjusted to the second output size, some power generators need to increase the output size, and some power generators need to decrease the output size. In order to avoid the situation of power supply shortage and affect the residential power consumption, the power generators with the need to increase the output size are preferentially adjusted, and the power generators with the need to decrease the output size are adjusted after the output size of the power generators with the need to increase the output size is increased to the position.

[0123] The power plant intelligent power generation control optimization method based on advanced algorithm provided by the present application determines the power generation cost model corresponding to each power generator according to the historical power generation data of each power generator, performs output adjustment test on each power generator, determines the output adjustment elasticity of each power generator, determines the power consumption demand prediction in a preset prediction period based on a preset demand prediction model, determines the first output size of each power generator based on a preset power generator scheduling model, the power consumption demand prediction, the load constraint range of each power generator, the power generation cost model and the output adjustment elasticity, and adjusts each power generator according to the first output size. Since the output size of the power generator is adjusted according to the predicted power consumption demand prediction, the intelligence and flexibility of the output adjustment of the power generator are improved, and the power generation cost is reduced.

[0124] Please refer toFigure 2 , Figure 2 A schematic block diagram of an advanced algorithm-based intelligent power plant generation control optimization system is provided for an embodiment of the present application.

[0125] As shown in Figure 2 , the present application also provides an advanced algorithm-based intelligent power plant generation control optimization system, which comprises:

[0126] a cost calculation module 110 configured to determine a generation cost model corresponding to each generator set according to historical generation data of the generator set;

[0127] a flexibility calculation module 120 configured to determine output adjustment flexibility of each generator set by performing output adjustment tests on the generator set;

[0128] a demand prediction module 130 configured to determine an electricity demand prediction in a preset prediction period based on a preset demand prediction model;

[0129] an output adjustment module 140 configured to determine a first output size of each generator set based on a preset generator set scheduling model, the electricity demand prediction, and a load constraint range of the generator set, the generation cost model, and the output adjustment flexibility;

[0130] In some embodiments, the determination of the generation cost model corresponding to each generator set according to the historical generation data of the generator set comprises:

[0131] obtaining historical generation amount of the generator set and historical fuel consumption amount corresponding to the historical generation amount;

[0132] fitting the historical generation amount and the corresponding historical fuel consumption amount to obtain a generation amount-fuel consumption amount curve corresponding to the generator set;

[0133] deriving the generation amount-fuel consumption amount curve to obtain a marginal fuel cost curve;

[0134] determining unit fuel cost corresponding to different generation amounts according to the marginal fuel cost curve to obtain a marginal cost curve as the generation cost model corresponding to the generator set.

[0135] In some embodiments, the determination of the unit fuel cost corresponding to different generation amounts according to the marginal fuel cost curve to obtain a marginal cost curve as the generation cost model corresponding to the generator set comprises:

[0136] obtaining fuel procurement information corresponding to a fuel batch currently used in a material management system, and determining a unit fuel price according to the fuel procurement information;

[0137] determine the unit fuel cost according to a ratio of the unit fuel price to a preset unit fuel heat value.

[0138] In some embodiments, the power adjustment test includes a primary frequency modulation test, a secondary frequency modulation test, and a combustion system adjustment test, and the power adjustment test for each of the generator sets to determine the power adjustment flexibility of each of the generator sets includes:

[0139] performing the primary frequency modulation test for the generator set multiple times to obtain a first response index of the generator set;

[0140] performing the secondary frequency modulation test for the generator set multiple times to obtain a second response index of the generator set;

[0141] performing the combustion system adjustment test for the generator set multiple times to obtain a third response index of the generator set;

[0142] determining the power adjustment flexibility according to the first response index, the second response index, and the third response index.

[0143] In some embodiments, the performing the primary frequency modulation test for the generator set multiple times to obtain a first response index of the generator set includes:

[0144] adjusting the intake amount of the steam turbine of the generator set;

[0145] obtaining a first power response after a first preset time period of adjusting the intake amount and a second power response after a second preset time period;

[0146] calculating the first response index according to the following formula:

[0147]

[0148] wherein, P1 represents the first power response, P2 represents the second power response, and Pmax represents a theoretical maximum power response; the second preset time period is greater than the first preset time period.

[0149] In some embodiments, the performing the secondary frequency modulation test for the generator set multiple times to obtain a second response index of the generator set includes:

[0150] sending an automatic generation control instruction to each of the generator sets to obtain an adjustment rate, a response time, and an adjustment accuracy of the generator set for the automatic generation control instruction;

[0151] determining the second response index of the secondary frequency modulation test according to the adjustment rate, the response time, and the adjustment accuracy.

[0152] In some embodiments, the first output size of each of the power generation units is determined based on the power consumption demand prediction, the load constraint range of each of the power generation units, the power generation cost model, and the output adjustment elasticity, and comprises:

[0153] The output adjustment elasticity is used to determine whether the power generation unit belongs to a basic load unit or a mobile load unit;

[0154] The load adjustment total amount is determined according to the difference between the power consumption demand prediction and the current power generation amount;

[0155] The load adjustment component corresponding to each of the basic load units and the mobile load units is determined according to the load constraint range of the power generation unit;

[0156] The first output size of the basic load unit and the mobile load unit is adjusted based on the load adjustment component.

[0157] In some embodiments, the load adjustment component corresponding to each of the basic load units and the mobile load units is determined according to the load constraint range of the power generation unit, and comprises:

[0158] The variable load of each of the power generation units is determined according to the load constraint range of each of the power generation units and the current load, wherein the sum of the variable loads of the mobile load units is the mobile variable total load;

[0159] When the load adjustment total amount is less than the mobile variable total load, the load adjustment component borne by each of the mobile load units is determined according to the proportion of the variable load of each of the mobile load units in the mobile variable total load;

[0160] When the load adjustment total amount is greater than or equal to the mobile variable total load, the first load adjustment component of the basic load unit is determined, and the second load adjustment component is determined according to the difference between the load adjustment total amount and the first load adjustment component, and the second load adjustment component borne by each of the mobile load units is determined according to the proportion of the variable load of each of the mobile load units in the mobile variable total load.

[0161] In some embodiments, after the first output size of the basic load unit and the mobile load unit is adjusted based on the load adjustment component, the method further comprises:

[0162] The output size of each of the power generation units is determined according to the power generation cost model corresponding to each of the power generation units, and the output size is the second output size;

[0163] When the first output of the generator set is less than the second output, the generator set is controlled to increase the first output to the second output.

[0164] When the first output of the generator set is greater than the second output, after controlling the generator set to increase the first output to the second output, the generator set is then controlled to decrease the first output to the second output.

[0165] For example, the above-described method system can be implemented as a computer program, which can be used in, for example... Figure 3 It runs on the computer device shown.

[0166] Please see Figure 3 , Figure 3 This is a schematic block diagram illustrating the structure of a computer device provided in an embodiment of this application. The computer device may be a server or a terminal.

[0167] like Figure 3 As shown, the computer device includes a processor, a memory, and a network interface connected via a system bus, wherein the memory may include a storage medium and internal memory.

[0168] The storage medium can store the operating system and computer programs. These computer programs include program instructions that, when executed, cause the processor to perform any intelligent power generation control optimization method for power plants based on advanced algorithms.

[0169] The processor provides computing and control capabilities, supporting the operation of the entire computer device.

[0170] The internal memory provides an environment for the execution of computer programs stored in the storage medium. When the computer program is executed by the processor, it enables the processor to execute any intelligent power generation control optimization method for power plants based on advanced algorithms.

[0171] This network interface is used for network communication, such as sending assigned tasks. Those skilled in the art will understand that... Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0172] It should be appreciated that a processor can be a Central Processing Unit (CPU), the processor can also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs) or other programmable logic devices, discrete gates or transistor logic components, discrete hardware components, etc. The general purpose processor can be a microprocessor or the processor can be any conventional processor.

[0173] It should be understood that the terms used herein in the specification and the appended claims are merely used for the purpose of describing particular embodiments and are not intended to limit the present application. As used in this specification and the appended claims, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0174] It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items, and that the term "at least one of' as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. It is to be noted that, as used in this specification and the appended claims, the terms "comprise", "comprising", "include", "including", or any other similar types of terminology are intended to be open ended and to mean including, but not limited to.

[0175] The above-mentioned sequence numbers of the embodiments of the present application are only for description, and do not represent advantages or disadvantages of the embodiments. The above description is merely specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any modifications or replacements within the technical scope disclosed by the present application can be easily conceived by those skilled in the art, and these modifications or replacements shall be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. An advanced algorithm based intelligent power generation control optimization method for power plants, characterized by, The method comprises: determining a corresponding power generation cost model of each of the power generators according to historical power generation data of each of the power generators; performing power output adjustment test on each of the power generators to determine power output adjustment elasticity of each of the power generators, wherein the power output adjustment elasticity is used to quantify the rapid degree of feedback on the power output size after variable adjustment of the power generator; determining power consumption demand prediction in a preset prediction period based on a preset demand prediction model; determining a first power output size of each of the power generators based on the power consumption demand prediction, load constraint range of each of the power generators and the power output adjustment elasticity according to a preset power generator scheduling model, and adjusting each of the power generators according to the first power output size, and slowly adjusting the power output size of each of the power generators to a second power output size which is determined to be the cost-optimal according to the corresponding power generation cost model of each of the power generators after the power output size of each of the power generators is adjusted to the first power output size.

2. The advanced algorithm based power plant intelligent power generation control optimization method of claim 1, wherein, The method comprises: obtaining historical power generation amount of the power generator and historical fuel consumption amount corresponding to the historical power generation amount; fitting the historical power generation amount and the corresponding historical fuel consumption amount to obtain a power generation amount-fuel consumption amount curve corresponding to the power generator; deriving the power generation amount-fuel consumption amount curve to obtain a marginal fuel cost curve; determining unit fuel cost corresponding to different power generation amounts according to the marginal fuel cost curve to obtain a marginal cost curve as the power generation cost model corresponding to the power generator.

3. The advanced algorithm based power plant intelligent power generation control optimization method of claim 2, wherein, The method comprises: obtaining fuel procurement information corresponding to a fuel batch currently used in a material management system, and determining unit fuel price according to the fuel procurement information; determining the unit fuel cost according to a ratio of the unit fuel price to a preset unit fuel heat value.

4. The advanced algorithm based power plant intelligent power generation control optimization method of claim 1, wherein, The power output adjustment test comprises primary frequency modulation test, secondary frequency modulation test and combustion system adjustment test, and the method comprises: performing the primary frequency modulation test on the power generator for multiple times to obtain a first response index of the power generator; performing the secondary frequency modulation test on the power generator for multiple times to obtain a second response index of the power generator; performing the combustion system adjustment test on the power generator for multiple times to obtain a third response index of the power generator; determining the power output adjustment elasticity according to the first response index, the second response index and the third response index.

5. The advanced algorithm based power plant intelligent power generation control optimization method of claim 4, wherein, The method comprises: adjusting the intake amount of the steam turbine of the power generator; obtaining first power output response after a first preset time length and second power output response after a second preset time length after the intake amount is adjusted; The first response index is calculated according to the following formula: wherein, represents a first output response, represents a second output response, represents a theoretical maximum output response; the second preset time length is greater than the first preset time length.

6. The advanced algorithm based power plant intelligent power generation control optimization method of claim 4, wherein, The second response index of the generator set is obtained by performing the secondary frequency modulation test multiple times on the generator set, including: An automatic generation control instruction is sent to each generator set, and an adjustment rate, a response time and an adjustment accuracy of the generator set to the automatic generation control instruction are obtained; A second response index of the secondary frequency modulation test is determined according to the adjustment rate, the response time and the adjustment accuracy.

7. The advanced algorithm based power plant intelligent power generation control optimization method of claim 1, wherein, The first output size of each generator set is determined based on the preset generator set scheduling model, the electricity demand prediction, and the load constraint range, the power generation cost model and the output adjustment elasticity of each generator set, including: According to the output adjustment elasticity, it is determined whether the generator set belongs to a basic load unit or a mobile load unit; A total load adjustment amount is determined according to the difference between the electricity demand prediction and the current power generation amount; A load adjustment component corresponding to each of the basic load unit and the mobile load unit is determined according to the load constraint range of the generator set; The first output size of the basic load unit and the mobile load unit is adjusted based on the load adjustment component.

8. The advanced algorithm based power plant intelligent power generation control optimization method of claim 7, wherein, The load adjustment component corresponding to each of the basic load unit and the mobile load unit is determined according to the load constraint range and the current load of each generator set, including: The variable load of each generator set is determined according to the load constraint range and the current load of each generator set, wherein the sum of the variable loads of the mobile load units is a total mobile variable load; When the total load adjustment amount is less than the total mobile variable load, the load adjustment component borne by each mobile load unit is determined according to the proportion of the variable load of each mobile load unit in the total mobile variable load; When the total load adjustment amount is greater than or equal to the total mobile variable load, a first load adjustment component of the basic load unit is determined, and a second load adjustment component is determined according to the difference between the total load adjustment amount and the first load adjustment component, and a second load adjustment component borne by each mobile load unit is determined according to the proportion of the variable load of each mobile load unit in the total mobile variable load.

9. The advanced algorithm based power plant intelligent power generation control optimization method of claim 7, wherein, After adjusting the first output size of the basic load unit and the mobile load unit based on the load adjustment component, the method further includes: A second output size of each generator set with optimal cost is determined according to the power generation cost model corresponding to each generator set; When the first output size of a generator set is less than the second output size, the output size of the generator set is increased to the second output size; When the first output size of a generator set is greater than the second output size, after the output size of the generator set with the first output size less than the second output size is increased to the second output size, the output size of the generator set with the first output size greater than the second output size is reduced to the second output size.

10. An advanced algorithm based intelligent power generation control optimization system for power plants characterized in that, The system includes: a cost calculation module, configured to determine a power generation cost model corresponding to each of the power generators according to historical power generation data of the power generators; an elasticity calculation module, configured to perform an output adjustment test on each of the power generators to determine output adjustment elasticity of each of the power generators, wherein the output adjustment elasticity is used to quantify a rapid degree of feedback on the output size after variable adjustment of the power generators; a demand prediction module, configured to determine an electricity demand prediction in a preset prediction period based on a preset demand prediction model; an output adjustment module, configured to determine a first output size of each of the power generators based on a preset power generator scheduling model, the electricity demand prediction, and a load constraint range of each of the power generators and the output adjustment elasticity, and to slowly adjust the output size of each of the power generators to a second output size that is determined to be optimal in cost according to the power generation cost model corresponding to each of the power generators after the output size of each of the power generators is adjusted to the first output size.

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