Power station power equipment adjustment strategy method and device and electronic equipment

Abstract

The invention discloses an adjustment strategy method and device for power equipment of a power station and electronic equipment. The method comprises: acquiring power station data of a predetermined power station; according to the power station data, determining a first risk index corresponding to the predetermined power station under the current environment parameters; under the condition that a predetermined risk occurs in the predetermined power station, determining second risk indexes corresponding to the plurality of sub-regions according to the power station data; under the condition that the risk reasons are increased, determining a plurality of third risk indexes corresponding to the plurality of sub-regions according to the power station data; and determining a power equipment adjustment strategy corresponding to the predetermined power station according to the first risk index, the second risk indexes corresponding to the plurality of sub-regions and the plurality of third risk indexes. According to the method and the device, the technical problem that the formulated adjustment strategy cannot be effectively executed due to lack of self-adaptive adjustment capability when the operation risk of the power equipment of the power station is managed and controlled in the related technology is solved.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to a method, a device and an electronic device for adjusting a strategy of power equipment in a power station. Background Art

[0002] At present, when conducting risk management of power equipment, the method usually adopted is passive management, such as making adjustments after the risk occurs to achieve risk management of power equipment. However, due to the uncertainty of risk, when risk management of power equipment is only based on this type of passive management, it is impossible to respond to various risk events flexibly, timely and effectively. There is a technical problem that the formulated adjustment strategy cannot be effectively implemented due to the lack of adaptive adjustment ability.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] The embodiments of the present invention provide a method, device and electronic device for adjusting the power equipment strategy of a power station, so as to at least solve the technical problem in the related art that, when performing power equipment operation risk management of the power station, the formulated adjustment strategy cannot be effectively executed due to the lack of adaptive adjustment capability.

[0005] According to one aspect of an embodiment of the present invention, a method for adjusting a power equipment strategy of a power station is provided, comprising: obtaining power station data of a predetermined power station, wherein the predetermined power station includes multiple power equipment, involves multiple energy resources, and the predetermined power station includes multiple sub-areas; determining, based on the power station data, a first risk index corresponding to the predetermined power station under current environmental parameters, wherein the first risk index represents the degree of influence on real-time resource prices under the current environmental parameters; in the case of a predetermined risk occurring in the predetermined power station, determining, based on the power station data, second risk indexes corresponding to the multiple sub-areas respectively, wherein the probability of a target risk occurring in the sub-area corresponding to the corresponding second risk index; in the case of an increase in risk causes, determining, based on the power station data, multiple third risk indexes corresponding to the multiple sub-areas respectively, wherein the corresponding multiple third risk indexes represent the probability of a corresponding multiple predetermined risks occurring in the corresponding sub-area respectively; determining, based on the first risk index, the second risk indexes corresponding to the multiple sub-areas respectively, and the multiple third risk indexes, a power equipment adjustment strategy corresponding to the predetermined power station, wherein the power equipment adjustment strategy is used to adjust power parameters corresponding to the multiple power equipment.

[0006] Optionally, based on the power station data, determining a first risk index corresponding to the predetermined power station under current environmental parameters includes: when the power station data includes power parameters corresponding to the multiple power equipment, resource parameters corresponding to the multiple energy resources, and historical resource data corresponding to the predetermined power station, determining the price fluctuation coefficients corresponding to the multiple energy resources under the current environmental parameters; determining the corresponding overall energy price in the predetermined power station based on the historical resource data and the resource parameters; determining the predicted energy price of the predetermined power station based on the price fluctuation coefficients corresponding to the multiple energy resources and the resource parameters; determining the first risk index corresponding to the predetermined power station based on the overall energy prices and the predicted energy prices corresponding to the multiple energy resources.

[0007] Optionally, the corresponding overall energy price in the predetermined power station is determined based on the historical resource data and the resource parameters, including: when the power station data includes the historical resource data corresponding to the predetermined power station, determining the first predicted prices respectively corresponding to the multiple energy resources based on the historical resource data; determining the energy proportions respectively corresponding to the multiple energy resources under the current environmental parameters; determining the corresponding overall energy price in the predetermined power station based on the first predicted prices respectively corresponding to the multiple energy resources, the energy proportions and the resource parameters.

[0008] Optionally, in the event that a predetermined risk occurs in the predetermined power station, second risk indexes corresponding to the multiple sub-regions are determined based on the power station data, including: in the event that a predetermined risk occurs in the predetermined power station, determining a target area where the predetermined risk occurs from the multiple sub-regions; determining a set of influencing risk factors for the occurrence of the predetermined risk, and determining a set of assessment risk factors corresponding to other sub-regions; and determining the second risk indexes corresponding to the multiple sub-regions based on the set of influencing risk factors and the set of assessment risk factors corresponding to other sub-regions.

[0009] Optionally, in the event that the cause of risk increases, a plurality of third risk indices corresponding to the plurality of sub-areas are determined based on the power plant data, including: retrieving the initial risk indices corresponding to the plurality of sub-areas respectively; determining the increased cause of risk; and adjusting the initial risk indices corresponding to the plurality of sub-areas respectively based on the increased cause of risk, to determine a plurality of third risk indices corresponding to the plurality of sub-areas respectively.

[0010] Optionally, based on the first risk index, the second risk index corresponding to the multiple sub-areas respectively, and multiple third risk indices, the power equipment adjustment strategy corresponding to the predetermined power station is determined, including: based on the first risk index, the second risk index corresponding to the multiple sub-areas respectively, and multiple third risk indices, determining a regulating device from the multiple power devices, wherein the regulating device includes a price influencing device and an operation influencing device; determining the regulating parameters respectively corresponding to the regulating devices; determining the power equipment adjustment strategy corresponding to the predetermined power station, wherein the power equipment regulation strategy includes the regulating parameters respectively corresponding to the regulating devices.

[0011] Optionally, after determining the power equipment adjustment strategy corresponding to the predetermined power station based on the first risk index, the second risk index corresponding to the multiple sub-regions respectively, and the multiple third risk indexes, it also includes: determining the first update index corresponding to the predetermined power station, the second update index corresponding to the multiple sub-regions respectively, and the multiple third update indexes; determining the update adjustment strategy corresponding to the predetermined power station based on the first update index, the second update index corresponding to the multiple sub-regions respectively, and the multiple third update indexes.

[0012] According to one aspect of an embodiment of the present invention, a power equipment adjustment strategy device for a power station is provided, comprising: an acquisition module, configured to acquire power station data of a predetermined power station, wherein the predetermined power station includes a plurality of power equipment, involves a plurality of energy resources, and the predetermined power station includes a plurality of sub-areas; a first determination module, configured to determine, based on the power station data, a first risk index corresponding to the predetermined power station under current environmental parameters, wherein the first risk index indicates the degree of influence on real-time resource prices under the current environmental parameters; a second determination module, configured to determine, based on the power station data, second risk indexes corresponding to the plurality of sub-areas respectively in the case where a predetermined risk occurs in the predetermined power station, wherein the probability of the sub-areas corresponding to the corresponding second risk index occurring at a target risk; a third determination module, configured to determine, based on the power station data, a plurality of third risk indexes corresponding to the plurality of sub-areas respectively in the case where the risk cause increases, wherein the corresponding plurality of third risk indexes indicate the probability of the corresponding plurality of predetermined risks occurring in the corresponding sub-areas respectively; a fourth determination module, configured to determine, based on the first risk index, the second risk indexes corresponding to the plurality of sub-areas respectively, and a plurality of third risk indexes, a power equipment adjustment strategy corresponding to the predetermined power station, wherein the power equipment adjustment strategy is used to adjust power parameters corresponding to the plurality of power equipment.

[0013] According to one aspect of an embodiment of the present invention, there is provided an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the power equipment adjustment strategy method of the power station described in any one of the above.

[0014] According to one aspect of an embodiment of the present invention, a computer-readable storage medium is provided. When instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device can execute any of the above-mentioned methods for adjusting power equipment strategies of a power station.

[0015] In an embodiment of the present invention, power station data of a predetermined power station is obtained, wherein the predetermined power station includes multiple power equipment, involves multiple energy resources, and the predetermined power station includes multiple sub-areas. According to the power station data, a first risk index corresponding to the predetermined power station under the current environmental parameters is determined, wherein the first risk index represents the degree of influence on the real-time resource price under the current environmental parameters. In the case of a predetermined risk occurring in the predetermined power station, according to the power station data, second risk indexes corresponding to the plurality of sub-areas are determined, wherein the probability of the occurrence of the target risk in the sub-area corresponding to the corresponding second risk index. In the case of an increase in the risk cause, according to the power station data, a plurality of third risk indexes corresponding to the plurality of sub-areas are determined, wherein the corresponding plurality of third risk indexes represent the probability of the occurrence of the plurality of predetermined risks in the corresponding sub-area. According to the first risk index, the second risk index corresponding to the plurality of sub-areas and the plurality of third risk indexes, an adjustment strategy for the power equipment corresponding to the predetermined power station is determined, wherein the power equipment adjustment strategy is used to adjust the power parameters corresponding to the plurality of power equipment. In this embodiment, based on the power station and multiple sub-areas of the power station, the power station data of the power station is deeply processed and analyzed. By comprehensively considering the first risk index, the second risk index and the third risk index, a power equipment adjustment strategy can be formulated in a targeted manner to help the power station respond to various risk events more promptly and effectively, thereby achieving the technical effect of improving the risk resistance of the power station and reducing the losses caused by risks. This further solves the technical problem in related technologies that, when conducting power equipment operation risk management in power stations, the formulated adjustment strategy cannot be effectively executed due to the lack of adaptive adjustment capability. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0017] Figure 1 is a flow chart of a power equipment adjustment strategy method of a power station according to an embodiment of the present invention;

[0018] Figure 2 is a flow chart of a power equipment adjustment strategy method of a power station in an optional implementation manner of the present invention;

[0019] Figure 3 It is a flowchart of real-time acquisition of all data in a pre-collected database in an optional implementation mode of the present invention;

[0020] Figure 4 is a flow chart of forming an ex ante risk index in an optional embodiment of the present invention;

[0021] Figure 5 is a flow chart of forming an in-process risk index in an optional implementation manner of the present invention;

[0022] Figure 6 is a flow chart for recording a post-event risk index in an optional implementation manner of the present invention;

[0023] Figure 7 It is a flow chart for determining the financial loss of each accident and recording the risk library in an optional implementation mode of the present invention;

[0024] Figure 8 is a flow chart of extracting various risk indexes in real time in an optional implementation manner of the present invention;

[0025] Fig. 9 It is a module structure diagram of a power equipment adjustment strategy system of a power station provided by an optional implementation mode of the present invention; Fig.10 4 is a structural block diagram of a power equipment adjustment strategy for a power station according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] Example 1

[0029] According to an embodiment of the present invention, an embodiment of a method for adjusting a power equipment strategy of a power station is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0030] Figure 1 is a flow chart of a method for adjusting a power equipment strategy in a power station according to an embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0031] Step S102, obtaining power station data of a predetermined power station, wherein the predetermined power station includes a plurality of power equipment, involves a plurality of energy resources, and includes a plurality of sub-areas;

[0032] In step S102 provided in the present application, power plant data of a predetermined power plant is acquired.

[0033] Among them, a predetermined power station is involved, which is a pre-selected power station, which can be a thermal power station, a hydropower station or a comprehensive power station including multiple types of energy resources.

[0034] Among them, power station data is involved. The power station data is data generated and collected during the operation of the power station, which is used to reflect the operating status of the power equipment in the power station, such as the operating parameters of the power equipment, the use of energy resources, power generation, power consumption, equipment health status, environmental conditions, etc.

[0035] Among them, power equipment is involved, which is various equipment that performs power generation, transmission, transformation, distribution and consumption in the power system. For example, power generation equipment is equipment that converts energy resources into electricity, among which power generation equipment includes power station boilers, steam turbines, gas turbines, water turbines, generators, etc.

[0036] Among them, energy resources are involved, which are various energy sources used for power generation, such as coal, natural gas, hydropower, etc. The price fluctuation of energy resources is an important part of controlling the operating cost risk of power equipment in power stations.

[0037] Among them, sub-areas are involved, which are areas within the power station divided according to function, energy resource type or geographical location. Each sub-area is equipped with corresponding power equipment and energy resources to manage and control the power plant's power equipment operating cost risks. There is a certain degree of interrelationship between multiple sub-areas.

[0038] Since the power equipment in the power station will be affected by many factors during operation, such as equipment performance, operating environment, etc., these factors may cause the power equipment to convert energy resources into electricity, which may have an adverse effect on the stable operation of the power station. For example, when aging power equipment is generating electricity, it cannot efficiently use energy resources, which leads to the potential risk of increased operating costs of the power station when the same amount of electricity needs to be generated. For example, when risks occur in a certain area, it may also affect the power equipment in other areas. Therefore, in order to timely discover and deal with these potential risks, it is necessary to collect power station data to facilitate the subsequent management and control of the operating cost risks of the power equipment in the power station.

[0039] Step S104, determining a first risk index corresponding to a predetermined power plant under current environmental parameters based on the power plant data, wherein the first risk index represents the degree of impact on real-time resource prices under current environmental parameters;

[0040] Among them, environmental parameters are involved, which are external factors that affect the operation of the power equipment of the power station, such as the supply and demand relationship of energy resources. These parameters have a direct or indirect impact on the operating cost risk of the power equipment of the power station. For example, changes in the supply and demand of energy resources will affect the price of energy resources, which in turn will affect the operating cost of the power equipment of the power station, and ultimately affect the formulation of the power equipment adjustment strategy.

[0041] Among them, a first risk index is involved, which is used to represent the correlation between changes in environmental parameters and real-time resource prices, and further can reflect the impact of this correlation on the power plant's power equipment operating cost risk.

[0042] Among them, the real-time resource price is involved, which is the price of various energy resources involved in the power equipment of the power station at a specific time point.

[0043] Since different environmental parameters will have different impacts on the operating efficiency and cost of power plant power equipment, the first risk index corresponding to the scheduled power plant under the current environmental parameters is determined based on the power plant data. Its core purpose is to quantitatively evaluate the impact of environmental parameter changes on real-time resource prices to analyze the specific impact on the power generation cost risk of power plant power equipment. Therefore, determining the first risk index corresponding to the scheduled power plant under the current environmental parameters can monitor the operating cost risks that may be caused by environmental parameter fluctuations, and then guide timely response measures and formulate appropriate power plant power equipment adjustment strategies.

[0044] Step S106, when a predetermined risk occurs in a predetermined power station, second risk indexes corresponding to a plurality of sub-areas are determined according to the power station data, wherein the probability of a target risk occurring in a sub-area corresponding to a corresponding second risk index;

[0045] Among them, predetermined risks are involved, which are risk events that may occur during the operation of the power equipment of the power station and may affect the normal operation of the power equipment of the power station based on historical data, model predictions or expert evaluations, such as power equipment failures in the power station, sudden disasters, etc.

[0046] Among them, the second risk index is involved, which is used to quantify the probability value of the target risk occurring in each sub-area of ​​the power station (i.e., the risk associated with it occurring in other sub-areas) when a predetermined risk occurs in a sub-area of ​​the power station. When a predetermined risk occurs in a sub-area of ​​the power station, by analyzing the situation of the predetermined risk occurring in other sub-areas, it can help identify the risk propagation path and high-risk areas, so as to take targeted risk management measures in advance and formulate appropriate adjustment strategies for the power equipment of the power station, thereby enhancing the control of the power equipment risks of the power station.

[0047] Among them, target risk is involved. The target risk is the specific risk events associated with the risk that other sub-areas may face when a predetermined risk occurs in a sub-area of ​​the power station, such as damage to the power equipment of the power station. These events will have different degrees of impact on the power generation cost of the power equipment.

[0048] Since the various sub-areas of the power station are interrelated and influence each other, it is necessary to quantitatively evaluate the probability value of the same or similar target risk (i.e. the propagation or derivation of the predetermined risk) occurring in other sub-areas when a predetermined risk occurs in a sub-area of ​​the power station, i.e. the second risk index. By analyzing the second risk index, it is possible to more effectively predict and identify potential risk propagation paths, so as to take targeted risk management measures and formulate appropriate adjustment strategies for the power equipment of the power station to ensure the overall stable operation of the power station and minimize the losses and impacts caused by risks.

[0049] Step S108, in the case where the risk cause increases, determining a plurality of third risk indexes corresponding to the plurality of sub-areas respectively according to the power plant data, wherein the corresponding plurality of third risk indexes represent the probability of the corresponding plurality of predetermined risks occurring in the corresponding sub-areas respectively;

[0050] Among them, the risk causes are involved. The risk causes are the various factors or conditions that have emerged or increased during the operation of the power equipment in the power station, which lead to the occurrence of predetermined risk events. These factors or conditions increase the uncertainty of power station operation, such as device damage, equipment abnormality, power supply failure, etc. The increase in risk causes means that the power station will face more potential risk threats, which require a more comprehensive risk management strategy to deal with.

[0051] Among them, the third risk index is involved. The third risk index is an indicator used to quantitatively evaluate the probability of multiple predetermined risk events occurring in each sub-region when the risk causes increase. The third risk index can help understand the risk status faced by each sub-region when multiple risk causes coexist, such as identifying which sub-regions are most vulnerable under new risk factors, so as to formulate appropriate power equipment strategies for power stations and provide guidance for key areas for risk response and resource optimization.

[0052] Since the increase in uncertainty in power plant operations means an increase in potential risk threats, it is necessary to determine multiple third risk indexes corresponding to multiple sub-areas based on power plant data when risk causes increase. By quantitatively evaluating the probability of each sub-area facing multiple predetermined risk events, it can help understand the risk status faced by each sub-area when multiple risk causes coexist, and provide guidance for key areas for risk management and resource optimization, such as helping to fully understand the risk status and identify the most vulnerable sub-areas under new risk factors, so that targeted power equipment strategies can be formulated to effectively respond to risks.

[0053] Step S110, determining a power equipment adjustment strategy corresponding to a predetermined power station based on the first risk index, second risk indices corresponding to multiple sub-areas, and multiple third risk indices, wherein the power equipment adjustment strategy is used to adjust power parameters corresponding to multiple power equipment.

[0054] Among them, it involves the power equipment adjustment strategy, which is a set of risk response plans for adjusting power equipment for the predetermined power station based on comprehensive consideration of the first risk index, the second risk index corresponding to multiple sub-areas, and multiple third risk indexes. For example, the output power of the generator can be adjusted to ensure that the power equipment operates in the best condition, thereby reducing power supply interruptions caused by equipment failures. Abnormal equipment or equipment with a long operating life can be maintained to improve the efficiency of energy resource utilization. By formulating a power equipment adjustment strategy, it helps the power station to respond to various risk events more promptly and effectively, thereby improving the power station's ability to resist risks and reducing losses caused by risks.

[0055] Since there are many uncertain factors in the operation of power equipment in power plants, such as equipment failure, these uncertain factors will pose potential risks to the normal operation of power equipment in power plants. By determining the power equipment adjustment strategy based on the first risk index, the second risk index and the third risk index, the specific impact of these uncertainties on power plant operations can be quantified. For example, the possible failure points of equipment can be identified in advance, maintenance and overhaul plans can be formulated, and the risk of power supply interruption caused by equipment failure can be avoided. In this way, power equipment adjustment strategies can be formulated in a targeted manner to help power plants respond to various risk events more promptly and effectively, thereby improving the power plant's ability to resist risks and reducing losses caused by risks.

[0056] Through the above steps S102-S110, the power station data of the predetermined power station is obtained, wherein the predetermined power station includes multiple power equipment, involves multiple energy resources, and the predetermined power station includes multiple sub-areas. According to the power station data, the first risk index corresponding to the predetermined power station under the current environmental parameters is determined, wherein the first risk index represents the degree of influence on the real-time resource price under the current environmental parameters. In the case of a predetermined risk occurring in the predetermined power station, the second risk indexes corresponding to the plurality of sub-areas are determined according to the power station data, wherein the probability of the occurrence of the target risk in the sub-area corresponding to the corresponding second risk index. In the case of an increase in the risk cause, the plurality of third risk indexes corresponding to the plurality of sub-areas are determined according to the power station data, wherein the corresponding plurality of third risk indexes represent the probability of the occurrence of the plurality of predetermined risks in the corresponding sub-area. According to the first risk index, the second risk indexes corresponding to the plurality of sub-areas and the plurality of third risk indexes, the power equipment adjustment strategy corresponding to the predetermined power station is determined, wherein the power equipment adjustment strategy is used to adjust the power parameters corresponding to the plurality of power equipment. In this embodiment, based on the power station and multiple sub-areas of the power station, the power station data of the power station is deeply processed and analyzed. By comprehensively considering the first risk index, the second risk index and the third risk index, a power equipment adjustment strategy can be formulated in a targeted manner to help the power station respond to various risk events more promptly and effectively, thereby achieving the technical effect of improving the risk resistance of the power station and reducing the losses caused by risks. This further solves the technical problem in related technologies that, when conducting power equipment operation risk management in power stations, the formulated adjustment strategy cannot be effectively executed due to the lack of adaptive adjustment capability.

[0057] As an optional embodiment, determining a first risk index corresponding to a predetermined power station under current environmental parameters based on power station data includes: when the power station data includes power parameters corresponding to multiple power equipment, resource parameters corresponding to multiple energy resources, and historical resource data corresponding to the predetermined power station, determining price fluctuation coefficients corresponding to multiple energy resources under current environmental parameters; determining the corresponding overall energy price in the predetermined power station based on historical resource data and resource parameters; determining the predicted energy price of the predetermined power station based on the price fluctuation coefficients and resource parameters corresponding to multiple energy resources; determining the first risk index corresponding to the predetermined power station based on the overall energy prices and predicted energy prices corresponding to multiple energy resources.

[0058] In this embodiment, a first risk index corresponding to a predetermined power plant is determined.

[0059] Among them, power parameters are involved, which are used to describe the operating status or performance of power equipment, such as current, voltage, power factor, etc. These parameters can reflect the load conditions, energy efficiency, etc. of the power equipment.

[0060] Among them, resource parameters are involved, which are the characteristics or states of energy resources. For example, for solar energy, they can be sunshine intensity, sunshine duration, etc.

[0061] Among them, historical resource data is involved, which is the data about energy resources recorded by the power station in the past period of time, such as the price and usage of energy resources. By analyzing historical resource data, it is possible to reflect the long-term trend and cyclical changes of energy resources.

[0062] Among them, the price fluctuation coefficient is involved, which is used to reflect the degree to which the price of energy resources fluctuates due to environmental factors. For example, if the price of a certain energy resource fluctuates greatly under the influence of certain environmental factors, its price fluctuation coefficient is high.

[0063] Among them, it involves predicting energy prices, which is the price obtained by estimating energy prices in the future based on current resource parameters and price fluctuation coefficients. For example, the price of wind energy in the future is predicted based on resource parameters such as wind speed and wind direction and the price fluctuation coefficient of wind energy.

[0064] Among them, the overall energy price is involved. The overall energy price is calculated based on historical resource data and resource parameters, and is used to represent the overall price of various energy resources actually used by the power station. For example, if the power station uses wind energy, solar energy and hydropower, then the overall energy price is the overall price of wind energy, solar energy and hydropower actually used by the power station calculated based on the usage of these three energy prices.

[0065] In the steps involved in this embodiment, when the power station data includes power parameters corresponding to multiple power equipment, resource parameters corresponding to multiple energy resources, and historical resource data corresponding to the predetermined power station, the price fluctuation coefficients corresponding to the multiple energy resources under the current environmental parameters are determined, and the corresponding overall energy price in the predetermined power station is determined based on the historical resource data and resource parameters, and the predicted energy price of the predetermined power station is determined based on the price fluctuation coefficients and resource parameters corresponding to the multiple energy resources, and the first risk index corresponding to the predetermined power station is determined based on the overall energy price and the predicted energy price corresponding to the multiple energy resources. By analyzing the historical resource data and resource parameters, it is helpful to understand the historical operating cost of the power equipment of the predetermined power station. At the same time, combined with the current environmental parameters and the price fluctuation coefficient, the uncertainty of the energy resource price in the future period can be quantitatively evaluated, so as to preliminarily grasp the future operating cost of the predetermined power station. Therefore, the first risk index corresponding to the predetermined power station determined by combining the overall energy price and the predicted energy price not only reflects the historical operating cost status of the predetermined power station, but also comprehensively considers the future operating cost status of the predetermined power station, and can comprehensively and accurately quantify and evaluate the risk level faced by the predetermined power station, so as to help the subsequent accurate formulation of the power equipment adjustment strategy of the power station.

[0066] As an optional embodiment, the corresponding overall energy price in a predetermined power station is determined based on historical resource data and resource parameters, including: when the power station data includes historical resource data corresponding to the predetermined power station, determining first predicted prices corresponding to a plurality of energy resources respectively based on the historical resource data; determining energy proportions corresponding to a plurality of energy resources respectively under current environmental parameters; determining the corresponding overall energy price in the predetermined power station based on the first predicted prices corresponding to the plurality of energy resources respectively, the energy proportions and resource parameters.

[0067] In this embodiment, the corresponding overall energy price in the predetermined power station is determined.

[0068] Among them, the first predicted price is involved, which is used to represent the estimated price of energy resources in the future based on historical resource data. For example, for wind energy, the price of wind energy resources in the future can be predicted based on wind speed, wind direction and wind energy price data in the past few years through statistical analysis or machine learning models.

[0069] Among them, the energy share is involved, which is the proportion of a certain energy resource used in the scheduled power station in the total energy resources under the current environmental parameters, reflecting the degree of dependence and usage of the scheduled power station on different energy resources.

[0070] In the steps involved in this embodiment, when the power station data includes historical resource data corresponding to the predetermined power station, the first predicted prices corresponding to the various energy resources are determined according to the historical resource data, the energy proportions corresponding to the various energy resources under the current environmental parameters are determined, and the overall energy price corresponding to the predetermined power station is determined according to the first predicted prices corresponding to the various energy resources, the energy proportions and the resource parameters. Since the price of energy resources and the energy proportions affect the operating cost of the power equipment of the power station, by determining the first predicted prices corresponding to the various energy resources, it is helpful for the power station to understand the price changes of various energy resources, and by determining the energy proportions corresponding to the various energy resources, the use of various energy resources in the power station can be evaluated. Therefore, determining the overall energy price corresponding to the predetermined power station based on the first predicted prices and energy proportions corresponding to the various energy resources can help the power station to adjust the energy resource structure used in a targeted manner and select energy resources with higher cost-effectiveness to reduce operating costs. For example, when the first predicted price of a certain energy resource is high and the energy proportion is high, a more reasonable energy procurement and operation plan can be formulated so that the energy resource can be purchased at a relatively stable price to reduce the operating cost risk of the power equipment of the power station.

[0071] As an optional embodiment, when a predetermined risk occurs in a predetermined power plant, second risk indexes corresponding to multiple sub-regions are determined based on the power plant data, including: when a predetermined risk occurs in a predetermined power plant, determining a target area where the predetermined risk occurs from multiple sub-regions; determining a set of influencing risk factors for the occurrence of the predetermined risk, and determining a set of assessment risk factors corresponding to other sub-regions; determining the second risk indexes corresponding to multiple sub-regions based on the set of influencing risk factors and the set of assessment risk factors corresponding to other sub-regions.

[0072] In this embodiment, the step of determining the second risk indexes respectively corresponding to the plurality of sub-regions is described.

[0073] Among them, the target area is involved, which is the sub-area where the predetermined risk actually occurs when the predetermined risk occurs in the predetermined power station. For example, the power station is divided into the first area, the second area, and the third area. If the first area has a power outage risk due to equipment failure, then the first area is the target area at this time.

[0074] Among them, a set of influencing risk factors is involved, which is a set of influencing factors that cause the predetermined risk to occur in the target area. For example, when the predetermined risk is equipment failure, the set of influencing risk factors that affect equipment failure may include equipment aging, maintenance frequency, recent weather conditions, etc.

[0075] Among them, it involves a set of assessment risk factors, which is a set of factors used to assess the possibility of the predetermined risk occurring in other sub-areas of non-target areas when the predetermined risk occurs in the target area. For example, the power station is divided into the first area, the second area, and the third area. When an equipment failure occurs in the first area, the set of assessment risk factors corresponding to the second area and the third area are determined. The set of assessment risk factors corresponding to the second area and the third area may include the degree of equipment aging, maintenance frequency, recent weather conditions, and the degree of correlation with the first area.

[0076] In this embodiment, when a predetermined risk occurs in a predetermined power station, a target area where the predetermined risk occurs is determined from multiple sub-areas, a set of risk factors affecting the predetermined risk is determined, and a set of assessment risk factors corresponding to other sub-areas are determined. According to the set of risk factors affecting the predetermined risk and the set of assessment risk factors corresponding to other sub-areas, second risk indexes corresponding to multiple sub-areas are determined. By determining the target area where the predetermined risk occurs and combing and analyzing the set of risk factors affecting the target area, it is helpful to analyze the nature and source of the risk. Since the sub-areas of the power station do not operate independently, but are interrelated and mutually influential, combing and analyzing the set of assessment risk factors corresponding to other sub-areas is helpful to understand the conditions of multiple other areas when the predetermined risk occurs in the target area. According to the set of risk factors affecting the predetermined risk and the set of assessment risk factors corresponding to multiple other areas, the second risk indexes corresponding to multiple sub-areas are determined. The second risk index is helpful to analyze whether the predetermined risk may spread to other sub-areas, as well as the probability and potential impact of the spread, in the case where the target area sends the predetermined risk, so as to help formulate an effective power equipment adjustment strategy.

[0077] As an optional embodiment, in the case where the risk cause increases, multiple third risk indices corresponding to the multiple sub-areas are determined based on the power plant data, including: retrieving the initial risk indices corresponding to the multiple sub-areas; determining the increased risk cause; based on the increased risk cause, adjusting the initial risk indices corresponding to the multiple sub-areas, and determining multiple third risk indices corresponding to the multiple sub-areas.

[0078] In this embodiment, a plurality of third risk indexes corresponding to the plurality of sub-regions are determined.

[0079] Among them, the initial risk index is involved. The initial risk index is the risk value of the original risk status of the sub-area of ​​the power station when the increased risk reasons are not taken into account. It reflects the probability of a predetermined risk event occurring in each sub-area under the current conditions.

[0080] Among them, the reasons for increased risks are involved, which are new factors that emerge during the operation of the power plant and may have a negative impact on the operation of the power equipment of the power plant.

[0081] In the steps involved in this embodiment, the initial risk indexes corresponding to the multiple sub-regions are retrieved, the increased risk reasons are determined, and the initial risk indexes corresponding to the multiple sub-regions are adjusted according to the increased risk reasons, and the multiple third risk indexes corresponding to the multiple sub-regions are determined. In the operation of power equipment in a power station, due to the untimely update of information or the limitations of the analysis method, the response to newly emerging risk factors (such as fluctuations in energy resource prices, accelerated equipment aging, etc.) may be slow, resulting in risk response measures lagging behind the actual risk development, thereby increasing the uncertainty of the operation of power equipment in the power station. The initial risk index is retrieved and adjusted in combination with the increased risk reasons, so that the risk assessment is more dynamic and accurate, and can timely reflect the changes in the operating environment, and provide real-time data support for the risk management of power equipment in the power station. By determining the multiple third risk indexes corresponding to the multiple sub-regions of the power station according to the increased risk reasons, the latest risk status of each sub-region can be identified, for example, which sub-regions have the highest risk after considering the increased risk reasons, thereby improving the flexibility and adaptability of the power equipment adjustment strategy of the power station, and effectively solving the problem of insufficient dynamics in the risk assessment of power equipment operation in the power station.

[0082] As an optional embodiment, based on the first risk index, the second risk indexes corresponding to the multiple sub-regions respectively, and the multiple third risk indices, an electric power equipment adjustment strategy corresponding to the predetermined power station is determined, including: based on the first risk index, the second risk indexes corresponding to the multiple sub-regions respectively, and the multiple third risk indices, from multiple electric power equipment, determining a regulating device, wherein the regulating device includes a price influencing device and an operation influencing device; determining regulating parameters respectively corresponding to the regulating devices; determining the electric power equipment adjustment strategy corresponding to the predetermined power station, wherein the electric power equipment regulating strategy includes regulating parameters respectively corresponding to the regulating devices.

[0083] In this embodiment, the power equipment adjustment strategy corresponding to the predetermined power station is determined.

[0084] Among them, regulating equipment is involved, which is a device that has an impact on the current power station's power equipment operating cost risk status and can cope with the risk by adjusting its power parameters.

[0085] Among them, price-affecting equipment is involved. This price-affecting equipment is closely related to the price of energy resources, has an impact on the current power plant's power equipment operating cost risk, and can adjust its power parameters to cope with the risk. For example, when the price of a certain energy resource is high, the power plant will tend to increase the power of the equipment using the energy resource to generate electricity, so as to improve the utilization rate of energy resources and reduce operating costs.

[0086] Among them, the operation-affecting equipment is involved, which is related to the operation performance and status of the equipment itself, has an impact on the current power plant's power equipment operating cost risk status, and can be adjusted to deal with the risk by adjusting its power parameters. For example, the operating status of the generator set needs to be monitored in real time and adjusted as needed to avoid abnormalities that may cause power generation failures in the power plant and affect the normal operation of the power plant.

[0087] Among them, the adjustment parameters are involved, which are power parameters used to adjust the operating status or performance of the adjustment equipment to deal with risks. For example, when an overload risk is detected, that is, when the grid load suddenly increases, it may be necessary to increase the output power setting value of the generator to ensure the stability of the power supply to avoid affecting the normal operation of the power station.

[0088] In the steps involved in this embodiment, based on the first risk index, the second risk index corresponding to the plurality of sub-areas and the plurality of third risk indexes, a regulating device is determined from a plurality of power devices, wherein the regulating device includes a price influencing device and an operation influencing device, and the regulating parameters corresponding to the regulating devices are determined, and the power equipment adjustment strategy corresponding to the predetermined power station is determined, wherein the power equipment adjustment strategy includes the regulating parameters corresponding to the regulating devices. By comprehensively considering the first risk index, the second risk index and the plurality of third risk indexes, the regulating device that needs to be adjusted and the corresponding regulating parameters of the regulating device are determined from a plurality of power devices, and then the corresponding power equipment adjustment strategy is formulated. This targeted and dynamic adjustment can ensure that the equipment parameters always match the current risk status, so as to effectively deal with the risk, thereby ensuring the stable operation of the power station.

[0089] As an optional embodiment, after determining the power equipment adjustment strategy corresponding to the predetermined power station based on the first risk index, the second risk indexes corresponding to multiple sub-regions respectively, and multiple third risk indexes, it also includes: determining the first update index corresponding to the predetermined power station, the second update indexes corresponding to multiple sub-regions respectively, and multiple third update indexes; determining the update adjustment strategy corresponding to the predetermined power station based on the first update index, the second update indexes corresponding to multiple sub-regions respectively, and multiple third update indexes.

[0090] In this embodiment, an update adjustment strategy corresponding to a predetermined power station is determined.

[0091] Among them, the first update index is involved, which is used to represent the correlation between environmental parameter changes and real-time resource price updates over time, and further reflects the impact of this updated correlation on the power plant's power equipment operating cost risk.

[0092] Among them, the second update index is involved. The second update index is used to indicate the update of the probability of target risks occurring in other sub-areas (that is, the predetermined risk also occurs in other sub-areas) as time changes. This reflects the dynamic changes of risk propagation paths and high-risk areas.

[0093] Among them, the third update index is involved. The third update index is an indicator used to quantify the probabilities of multiple predetermined risk events occurring in each sub-area after being updated when new risk causes increase over time.

[0094] In the steps involved in this embodiment, a first update index corresponding to a predetermined power station, a second update index corresponding to a plurality of sub-regions, and a plurality of third update indexes are determined, and an update adjustment strategy corresponding to the predetermined power station is determined based on the first update index, the second update index corresponding to a plurality of sub-regions, and the plurality of third update indexes. By taking into account the dynamic changes of risk factors and the adaptive response of the power plant's power equipment adjustment strategy, through continuous monitoring, the first update index, the second update index, and the plurality of third update indexes are determined respectively, and the updated update adjustment strategy is determined by combining the first update index, the second update index, and the plurality of third update indexes, so as to achieve dynamic strategy adjustment of the power plant in response to operational risks, thereby ensuring the flexibility and adaptability of the power plant's power equipment adjustment strategy, and thus effectively solving the technical problem of insufficient dynamism in the power plant's power equipment operation risk assessment.

[0095] Based on the above embodiments and optional embodiments, an optional implementation is provided, which is described in detail below.

[0096] An optional implementation of the present invention provides a power plant power equipment adjustment strategy method and system, which can also be called a power plant risk management method and system, which can effectively solve the technical problem in the related technology that, when conducting power plant power equipment operation risk management, the formulated adjustment strategy cannot be effectively executed due to the lack of adaptive adjustment capability.

[0097] (I) Strategy and method for adjusting power equipment in power stations:

[0098] Figure 2is a flow chart of a power equipment adjustment strategy method of a power station in an optional implementation manner of the present invention, such as Figure 2 As shown, the optional implementation methods of the present application are described in detail below.

[0099] S1, obtaining power station data of a predetermined power station, wherein the predetermined power station includes multiple power equipment, involves multiple energy resources, and includes multiple sub-areas;

[0100] For example, real-time acquisition of all data in the pre-collected database (same as the power station data mentioned above), Figure 3 It is a flowchart of real-time acquisition of all data in the pre-collected database in an optional implementation mode of the present invention, specifically including real-time acquisition of resource information of the current state, resource information (same as the above-mentioned energy resources) including the installed capacity of thermal power, hydropower and coal-fired power generators, real-time current power supply situation, power supply situation including total power generation and total power consumption, and storing resource information and power supply situation together as a pre-collected database. The fluctuation information of power cost is obtained through two aspects. The first aspect is the acquisition of statistical data, and the second aspect is the acquisition of collected information. The statistical information mainly refers to the degree of change of various resources at present, including the price and dynamic changes of thermal power, hydropower and coal-fired power resources; the collected data mainly refers to the relationship between demand and generation during this period, and the relationship between power consumption and power supply.

[0101] S2, determining, based on the power plant data, a first risk index corresponding to the predetermined power plant under the current environmental parameters, wherein the first risk index represents the degree of impact on the real-time resource price under the current environmental parameters;

[0102] Specifically, S2 also includes:

[0103] S21, when the power station data includes power parameters corresponding to a plurality of power equipment, resource parameters corresponding to a plurality of energy resources, and historical resource data corresponding to a predetermined power station, determining price fluctuation coefficients corresponding to the plurality of energy resources under current environmental parameters;

[0104] S22, determining the corresponding overall energy price in the predetermined power station based on the historical resource data and resource parameters;

[0105] S23, determining the predicted energy price of the predetermined power station according to the price fluctuation coefficients and resource parameters corresponding to the various energy resources;

[0106] S24, determining a first risk index corresponding to the predetermined power plant according to the overall energy prices and the predicted energy prices respectively corresponding to the various energy resources.

[0107] Specifically, S22 also includes:

[0108] S221, when the power station data includes historical resource data corresponding to the predetermined power station, determining first predicted prices corresponding to the plurality of energy resources respectively according to the historical resource data;

[0109] S222, determining the energy proportions corresponding to the various energy resources under the current environmental parameters;

[0110] S223, determining the corresponding overall energy price in the scheduled power station according to the first predicted prices, energy proportions and resource parameters corresponding to the various energy resources.

[0111] For example, obtaining a pre-collection database, conducting online price fluctuation risk analysis, and forming a pre-risk index (same as the first risk index mentioned above), Figure 4 It is a flow chart of forming an ex ante risk index in an optional implementation mode of the present invention. The process of predicting electricity cost fluctuation information (same as the above-mentioned price fluctuation coefficient) is mainly to calibrate each resource according to the degree of resource change, determine a dynamic standard price curve, and then calibrate according to the real-time electricity supply and demand relationship to determine the power generation cost fluctuation under different supply and demand conditions, and then determine the current electricity price fluctuation risk according to the power generation cost fluctuation and the supply and demand relationship curve, with different degrees of different risks. Specifically including: obtaining the pre-collection database, reading the real-time price of each resource therein; for each analyzed area, reading the total amount of each resource used for power generation; using the first calculation formula to estimate the future real-time price, the formula is as follows:

[0112]

[0113] Among them, t is time, t0 is the formula starting data corresponding to the corresponding moment in the historical data, such as in this formula, represents the starting price data, i is the fitting number, k i is the preset fitting coefficient corresponding to the i-th fitting number, which is used to reflect the price fluctuation. N is the total number of fitting numbers. A t is the estimated future real-time price at time t, where the fitting number is the i-th level, and i is numbered from 1 to N, where i is the coefficient of the power corresponding to the i-th fitting number.

[0114] The second calculation formula is used to estimate the future real-time resource ratio (same as the above energy ratio), the formula is as follows:

[0115]

[0116] Among them, t is time, t0 is the formula starting data corresponding to the corresponding moment in the historical data, such as in this formula, represents the starting resource proportion data, j i is the preset resource analysis coefficient corresponding to the i-th fitting number, B tis the future real-time resource ratio at time t. It should be noted that the resource analysis function is also a coefficient, similar to k i , the first and second calculation formulas are both polynomial fitting.

[0117] The real-time total amount of resources is set according to the preset total amount adjustment table of resources, wherein the total amount adjustment table of resources indicates how the total amount of resources in different time periods will be adjusted in advance, for example, more photovoltaic resources during the day and less photovoltaic resources at night.

[0118] The overall resource price of the real-time area (same as the overall energy price mentioned above) is calculated using the third calculation formula, and the formula is as follows:

[0119] D t =C t ×B t ×A t

[0120] Among them, D t is the overall resource price of the real-time region, C t is the total amount of real-time resources at time t;

[0121] Obtain the historical curve of supply and demand relationship, and use the fourth calculation formula to calculate the corresponding price fluctuation coefficient under different supply and demand differences (same as the above price fluctuation coefficient) according to the historical curve. The formula is as follows:

[0122] {Q s}=arg mins∈TT(Q s ×(ET-FT)-P s )

[0123] Among them, ET is the total amount of electricity that can be supplied in the supply and demand relationship curve, in units of power, FT is the total amount of electricity consumed in the supply and demand relationship curve, in units of power, TT is the historical data set, s is the historical data number, P s is the price corresponding to the historical data number s, {Qs} is the optimal price volatility coefficient set, {Q s} contains at least one price volatility coefficient, arg mins∈TT() is used to extract Q s ×(ET-FT)-P s The function of the optimal price volatility coefficient corresponding to the minimum.

[0124] The real-time price is calculated using the fifth calculation formula according to the price fluctuation coefficient (same as the above-mentioned predicted energy price). It should be noted that the future price is estimated. The formula is as follows:

[0125] G={Q s}×(ET-FT)

[0126] Among them, G is the real-time price.

[0127] The sixth calculation formula is used to calculate the ex ante risk index (same as the first risk index mentioned above), and the formula is as follows:

[0128] F1=(D t -G)÷G

[0129] Among them, F1 is the ex ante risk index.

[0130] Among them, risk (same as the above-mentioned operating cost risk) refers to uncertain factors that usually lead to losses. In power plants, the risks faced by power plants mainly include: (1) Power generation cost risk: refers to the fluctuation of power generation costs due to changes in electricity prices. (2) Transaction risk: refers to the risk of transaction system failure or system shock due to the uncertainty of the operation status of the power system.

[0131] S3, when a predetermined risk occurs in a predetermined power station, second risk indices corresponding to a plurality of sub-regions are determined according to the power station data, wherein the probability of a target risk occurring in a sub-region corresponding to a corresponding second risk index;

[0132] Specifically, S3 also includes:

[0133] S3 1, in the case where a predetermined risk occurs in a predetermined power station, determining a target area for sending the predetermined risk from a plurality of sub-areas;

[0134] S32, determining a set of risk factors influencing the occurrence of a predetermined risk, and determining a set of assessment risk factors corresponding to a plurality of other regions respectively;

[0135] S33, determining second risk indexes corresponding to the plurality of sub-regions respectively according to the set of influencing risk factors and the sets of assessment risk factors corresponding to the plurality of other regions respectively.

[0136] For example, after a risk event occurs, determine whether there is an in-process risk and form an in-process risk index (same as the second risk index mentioned above). Figure 5 It is a flow chart of forming an in-process risk index in an optional implementation mode of the present invention. In the process of risk occurrence, there may be many collateral reactions caused by risks, mainly the risk caused by information asymmetry. In terms of information asymmetry, two aspects are mainly considered. The first aspect is that it is necessary to compare the current event risk focus range and the difference in the focus range between each device. According to the degree of difference, the degree of change of the corresponding quantity is further concerned. If it exceeds the preset range and there is no mutual concern, it is considered that there is an in-process risk; on the other hand, there is a risk of mismatch in the judgment margin. For the same indicator, there is a mismatch in the corresponding risk assessment range.

[0137] Specifically, it includes: judging whether a risk has occurred at the current moment, and if so, initiating in-process risk assessment. For example, if an overload or excessive voltage fluctuation occurs, the data type that currently generates the risk is judged for the area where the risk has occurred, and a risk set is formed based on the data type;

[0138] The relationship between the judgment risk set and the judgment criteria of other areas is direct. If there is an area that meets the seventh calculation formula, the formula is as follows:

[0139] H∩HB≠0

[0140] Among them, HB is the judgment standard set of the region, and H is the risk set;

[0141] If the conditions are met, it is considered that there is an incident risk, and the incident risk index is calculated using the eighth calculation formula, which is as follows:

[0142] F2=R(H∩HB)÷R(H)

[0143] Among them, F2 is the risk index during the event (same as the second risk index mentioned above), and R() is a function for extracting the number of set elements.

[0144] S4, in the case where the risk causes increase, determining a plurality of third risk indexes corresponding to the plurality of sub-areas respectively according to the power station data, wherein the corresponding plurality of third risk indexes represent probabilities corresponding to the occurrence of a plurality of predetermined risks in the corresponding sub-areas respectively;

[0145] Specifically, S4 also includes:

[0146] S41, retrieving initial risk indexes corresponding to the plurality of sub-regions respectively;

[0147] S42, determine the reasons for the increased risk;

[0148] S43, adjusting the initial risk indexes corresponding to the plurality of sub-regions respectively according to the reasons for the increased risk, and determining a plurality of third risk indexes corresponding to the plurality of sub-regions respectively.

[0149] For example, record each accident, mark the risk cause, and record the post-accident risk index (same as the third risk index mentioned above). Figure 6 It is a flow chart of recording post-event risk index in an optional implementation manner of the present invention.

[0150] Specifically include:

[0151] Determine whether a new accident has occurred at the current moment. If so, record the corresponding risk cause;

[0152] If the risk cause is recorded and the judgment criteria of which area overlap, the corresponding area is set to the ninth calculation formula as the risk association function, where the overlap of judgment criteria means that each accident has a risk cause;

[0153] If the accident that occurs at the current moment is an existing accident, the ninth calculation formula of the corresponding area is updated. That is, if the type of accident cause corresponding to an accident is increased, the risk index of each area that overlaps with this risk cause needs to be updated again. For example, if the voltage exceeds the limit, the original risk cause is only price fluctuation. However, after actual analysis, it is found that this is not the cause, but device damage. Then the risk cause is updated to the corresponding cause library. And associated with the range corresponding to each area where the voltage exceeds the limit.

[0154] The formula is as follows:

[0155] X j =1÷(1÷X jq -1), YIN∩HB j ≠0

[0156] Among them, HB j is the judgment standard of the jth region, YIN is the set of risk reasons, X jq is the probability of occurrence of all risks in the jth region at the current moment, X j is the total risk before updating for the jth region;

[0157] The probability of occurrence of all risks in each region at the current moment is taken as the ex post risk index, where the probability of occurrence is the probability of the risk occurring.

[0158] S5, determining a power equipment adjustment strategy corresponding to a predetermined power station based on the first risk index, the second risk indexes corresponding to the plurality of sub-areas, and the plurality of third risk indexes, wherein the power equipment adjustment strategy is used to adjust power parameters corresponding to the plurality of power equipment.

[0159] Specifically, S5 also includes:

[0160] S51, determining a regulating device from a plurality of power devices according to the first risk index, the second risk indexes corresponding to the plurality of sub-regions respectively, and the plurality of third risk indexes, wherein the regulating device includes a price influencing device and an operation influencing device;

[0161] S52, determining adjustment parameters corresponding to the adjustment devices respectively;

[0162] S53, determining a power equipment adjustment strategy corresponding to the predetermined power station, wherein the power equipment adjustment strategy includes adjustment parameters corresponding to the adjustment equipment respectively.

[0163] S54, determining a first update index corresponding to the predetermined power station, second update indexes corresponding to the plurality of sub-areas, and a plurality of third update indexes;

[0164] S55 , determining an update adjustment strategy corresponding to the predetermined power station according to the first update index, the second update indexes corresponding to the plurality of sub-areas respectively, and the plurality of third update indexes.

[0165] For example, determine the losses incurred in each accident, record the risk database, and extract the pre-accident risk index, in-accident risk index, and post-accident risk index in real time. Figure 7 This is a flow chart of determining the loss of each accident and recording the risk library in an optional implementation of the present invention. Specifically, it includes: determining the loss of each accident, if it exceeds the preset value, it is recorded in the risk library; if it does not exceed the preset value, it is not included in the risk library. Among them, the loss caused by the risk is calculated in real time, and the risk number that generates strong interference is determined and set in the risk library, while for weak risks, no processing is done. Figure 8 It is a flowchart of real-time extraction of various risk indexes in an optional implementation mode of the present invention, by real-time display of risk assessment indexes before, during and after the event, and marking the current risk scheduling and management situation, specifically including real-time extraction of pre-risk index, in-event risk index and post-risk index, and displaying them on the screen through curves, wherein the above three indexes are the risk levels before, during and after the accident calculated previously; marking whether there is risk adjustment at the current moment, and if so, the adjustment process is recorded; wherein adjustment means that each time a new risk appears, it needs to be recorded. Record through a spreadsheet, and mark the corresponding time. Record the time and corresponding information of the entire adjustment process, and display it on the screen through a table.

[0166] (II) For the power equipment adjustment strategy system of the power station:

[0167] The system mainly consists of six modules, namely, pre-collection module, pre-analysis module, in-process adjustment module, post-adjustment module, risk scheduling module and risk display module. Through modular design, a system suitable for different structures is realized. The system can achieve closed-loop, reliable and efficient execution through collection, analysis and control. Fig. 9 It is a module structure diagram of a power plant power equipment adjustment strategy system provided by an optional implementation mode of the present invention.

[0168] like Fig. 9 As shown, the pre-collection module is used to obtain all data of the pre-collection database in real time;

[0169] The pre-analysis module is connected to the pre-collection module and is used to obtain the pre-collection database, conduct online price fluctuation risk analysis, and form a pre-risk index;

[0170] The in-process adjustment module is connected to the pre-process analysis module and is used to determine whether there is an in-process risk after a risk event occurs, and to form an in-process risk index;

[0171] The post-event adjustment module is connected to the in-event adjustment module and is used to record each accident, mark the risk cause, and record the post-event risk index;

[0172] The risk scheduling module, connected to the post-adjustment module, is used to determine the financial losses generated in each accident and record the risk database;

[0173] The risk display module is connected to the risk scheduling module and is used to extract the pre-risk index, the mid-risk index and the post-risk index in real time.

[0174] Through the above optional implementation, at least the following beneficial effects can be achieved:

[0175] (1) Compared with the related art, the present invention determines the power equipment adjustment strategy corresponding to the predetermined power station by comprehensively considering the first risk index, the second risk index and multiple third risk indexes, wherein the first risk index, the second risk index and the third risk index respectively reflect the correlation between the change of environmental parameters and the resource price, the possibility of risk propagation between sub-regions and the change of risk status caused by the new risk reasons. These indexes together constitute a complete framework for power station risk assessment, providing a comprehensive and accurate information basis for formulating power equipment adjustment strategies. This targeted and dynamic adjustment can ensure that the power equipment adjustment strategy of the power station always matches the current risk status, so as to effectively deal with risks and ensure the stable operation of the power station.

[0176] (2) Compared with the related art, the first risk index corresponding to the scheduled power station is determined by combining the overall energy price and the predicted energy price. It not only reflects the historical operating cost status of the scheduled power station, but also comprehensively considers the future operating cost status of the scheduled power station, and can comprehensively and accurately quantify and evaluate the risk level faced by the scheduled power station, thereby facilitating the accurate formulation of the subsequent power equipment adjustment strategy for the power station.

[0177] (3) Compared with the related art, the present invention further considers the interrelationship and influence between the various sub-areas of the power station, and quantitatively evaluates the probability value of the same or similar target risk occurring in other sub-areas when a predetermined risk occurs in a sub-area of ​​the power station, i.e., the second risk index. By analyzing the second risk index, it can help to more effectively predict and identify potential risk propagation paths, so as to take targeted risk management measures and formulate appropriate adjustment strategies for the power equipment of the power station to ensure the overall stable operation of the power station and minimize the losses and impacts caused by risks.

[0178] (4) Compared with the related art, the present invention makes the risk assessment more dynamic and accurate by retrieving the initial risk index and adjusting it in combination with the increased risk reasons, which can timely reflect the changes in the operating environment and provide real-time data support for the risk management of power equipment in the power station. By determining multiple third risk indexes corresponding to multiple sub-areas of the power station according to the increased risk reasons, the latest risk status of each sub-area can be identified, thereby improving the flexibility and adaptability of the power equipment adjustment strategy of the power station, and effectively solving the technical problem of insufficient dynamics in the risk assessment of power equipment operation in the power station.

[0179] (5) Compared with the related art, the present invention determines the power equipment adjustment strategy based on the first risk index, the second risk index and the third risk index, and quantifies the specific impact of these uncertainties on the operation of the power station, so that the power equipment adjustment strategy can be formulated in a targeted manner, helping the power station to respond to various risk events more promptly and effectively, thereby improving the risk resistance of the power station and reducing the losses caused by risks.

[0180] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0181] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods of various embodiments of the present invention.

[0182] Example 2

[0183] According to an embodiment of the present invention, there is also provided a device for implementing the above-mentioned power plant power equipment adjustment strategy method. Fig.10 is a structural block diagram of a power equipment adjustment strategy for a power station according to an embodiment of the present invention, such as Fig.10As shown, the device includes: an acquisition module 1002, a first determination module 1004, a second determination module 1006, a third determination module 1008 and a fourth determination module 1010. The device is described in detail below.

[0184] The acquisition module 1002 is used to acquire the power station data of the predetermined power station, wherein the predetermined power station includes multiple power equipment, involves multiple energy resources, and the predetermined power station includes multiple sub-areas; the first determination module 1004 is connected to the above-mentioned acquisition module 1002, and is used to determine, based on the power station data, a first risk index corresponding to the predetermined power station under the current environmental parameters, wherein the first risk index represents the degree of influence on the real-time resource price under the current environmental parameters; the second determination module 1006 is connected to the above-mentioned first determination module 1004, and is used to determine, based on the power station data, the second risk indexes corresponding to the multiple sub-areas respectively in the case of a predetermined risk occurring in the predetermined power station, wherein the corresponding second risk index a probability of a target risk occurring in a sub-area corresponding to the number; a third determination module 1008, connected to the above-mentioned second determination module 1006, for determining, when the risk cause increases, a plurality of third risk indices corresponding to the plurality of sub-areas, respectively, based on the power plant data, wherein the corresponding plurality of third risk indices represent the probability of a plurality of predetermined risks occurring in the corresponding sub-areas, respectively; a fourth determination module 1010, connected to the above-mentioned third determination module 1008, for determining, based on the first risk index, the second risk indices corresponding to the plurality of sub-areas, respectively, and the plurality of third risk indices, a power equipment adjustment strategy corresponding to the predetermined power station, wherein the power equipment adjustment strategy is used to adjust power parameters corresponding to a plurality of power equipment.

[0185] It should be noted here that the above-mentioned acquisition module 1002, the first determination module 1004, the second determination module 1006, the third determination module 1008 and the fourth determination module 1010 correspond to steps S102 to S110 in the method for implementing the power equipment adjustment strategy of the power station, and the instances and application scenarios implemented by the multiple modules are the same as the corresponding steps, but are not limited to the contents disclosed in the above-mentioned embodiment 1.

[0186] Example 3

[0187] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor, wherein the processor is configured to execute instructions to implement any of the above-mentioned methods for adjusting the power equipment strategy of the power station.

[0188] Example 4

[0189] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided. When instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device can execute any of the above-mentioned methods for adjusting power equipment strategies of a power station.

[0190] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0191] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0192] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0193] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0194] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0195] If the integrated unit is implemented in the form of 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, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0196] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A power equipment adjustment strategy method for a power station, characterized in that: include: Acquiring power station data of a predetermined power station, wherein the predetermined power station includes a plurality of power equipment, involves a plurality of energy resources, and includes a plurality of sub-areas; Determining, based on the power plant data, a first risk index corresponding to the predetermined power plant under current environmental parameters, wherein the first risk index represents the degree of impact on real-time resource prices under the current environmental parameters; In the case where a predetermined risk occurs in the predetermined power station, second risk indexes corresponding to the plurality of sub-areas are determined according to the power station data, wherein the probability of the target risk occurring in the sub-area corresponding to the corresponding second risk index; In the case where the risk causes increase, determining a plurality of third risk indexes corresponding to the plurality of sub-areas respectively according to the power station data, wherein the corresponding plurality of third risk indexes represent probabilities corresponding to the occurrence of a plurality of predetermined risks respectively in the corresponding sub-areas; Based on the first risk index, the second risk indices corresponding to the multiple sub-areas and multiple third risk indices, the power equipment adjustment strategy corresponding to the predetermined power station is determined, wherein the power equipment adjustment strategy is used to adjust the power parameters corresponding to the multiple power equipment.

2. The method according to claim 1, characterized in that: Determining, according to the power plant data, a first risk index corresponding to the predetermined power plant under current environmental parameters, includes: In the case where the power station data includes power parameters corresponding to the plurality of power devices, resource parameters corresponding to the plurality of energy resources, and historical resource data corresponding to the predetermined power station, determining price fluctuation coefficients corresponding to the plurality of energy resources under the current environmental parameters; Determining the corresponding overall energy price in the predetermined power station based on the historical resource data and the resource parameters; Determining the predicted energy price of the predetermined power station according to the price fluctuation coefficients respectively corresponding to the multiple energy resources and the resource parameters; A first risk index corresponding to the predetermined power station is determined according to the overall energy prices and the predicted energy prices respectively corresponding to the multiple energy resources.

3. The method according to claim 2, characterized in that Determining the corresponding overall energy price in the predetermined power station according to the historical resource data and the resource parameters includes: In a case where the power station data includes historical resource data corresponding to the predetermined power station, determining first predicted prices corresponding to the plurality of energy resources respectively according to the historical resource data; Determine the energy proportions corresponding to the multiple energy resources respectively under the current environmental parameters; The corresponding overall energy price in the predetermined power station is determined according to the first predicted prices respectively corresponding to the multiple energy resources, the energy proportions and the resource parameters.

4. The method according to claim 1, characterized in that: In the case where a predetermined risk occurs in the predetermined power station, determining second risk indexes respectively corresponding to the plurality of sub-areas according to the power station data includes: In the case where a predetermined risk occurs to the predetermined power station, determining a target area for sending the predetermined risk from the multiple sub-areas; Determine a set of risk factors influencing the occurrence of the predetermined risk, and determine a set of assessment risk factors corresponding to other sub-areas respectively; According to the set of influencing risk factors and the sets of assessment risk factors corresponding to other sub-regions respectively, second risk indexes corresponding to the plurality of sub-regions respectively are determined.

5. The method according to claim 1, characterized in that In the case where the risk causes increase, determining a plurality of third risk indexes corresponding to the plurality of sub-areas respectively according to the power plant data includes: Retrieving initial risk indexes corresponding to the multiple sub-areas respectively; Identify the increased reasons for the increased risk; According to the increased risk reason, initial risk indexes corresponding to the plurality of sub-regions are adjusted to determine a plurality of third risk indexes corresponding to the plurality of sub-regions.

6. The method according to claim 1, characterized in that Determining a power equipment adjustment strategy corresponding to the predetermined power station according to the first risk index, the second risk indexes corresponding to the plurality of sub-areas respectively, and a plurality of third risk indexes, includes: According to the first risk index, the second risk indexes corresponding to the plurality of sub-areas respectively, and the plurality of third risk indexes, a regulating device is determined from the plurality of power devices, wherein the regulating device includes a price influencing device and an operation influencing device; Determining adjustment parameters corresponding to the adjustment devices respectively; An electric power equipment adjustment strategy corresponding to the predetermined power station is determined, wherein the electric power equipment adjustment strategy includes adjustment parameters corresponding to the adjustment equipment respectively.

7. The method according to any one of claims 1 to 6, characterized in that: After determining the power equipment adjustment strategy corresponding to the predetermined power station according to the first risk index, the second risk indexes corresponding to the plurality of sub-areas respectively, and the plurality of third risk indexes, the method further includes: Determine a first update index corresponding to the predetermined power station, a second update index corresponding to each of the plurality of sub-areas, and a plurality of third update indexes; An update adjustment strategy corresponding to the predetermined power station is determined according to the first update index, the second update indexes respectively corresponding to the plurality of sub-areas, and a plurality of third update indexes.

8. A power equipment adjustment strategy device for a power station, characterized in that: include: An acquisition module, used for acquiring power station data of a predetermined power station, wherein the predetermined power station includes a plurality of power equipments, involves a plurality of energy resources, and includes a plurality of sub-areas; A first determination module is used to determine, based on the power plant data, a first risk index corresponding to the predetermined power plant under current environmental parameters, wherein the first risk index represents the degree of impact on the real-time resource price under the current environmental parameters; A second determination module is used to determine, when a predetermined risk occurs in the predetermined power station, second risk indexes corresponding to the plurality of sub-areas respectively according to the power station data, wherein the probability of a target risk occurring in the sub-area corresponding to the corresponding second risk index; A third determination module is used to determine, in the case where the risk cause increases, a plurality of third risk indexes corresponding to the plurality of sub-areas respectively according to the power station data, wherein the corresponding plurality of third risk indexes represent probabilities corresponding to the occurrence of a plurality of predetermined risks in the corresponding sub-areas respectively; The fourth determination module is used to determine the power equipment adjustment strategy corresponding to the predetermined power station based on the first risk index, the second risk indexes corresponding to the multiple sub-areas respectively, and multiple third risk indices, wherein the power equipment adjustment strategy is used to adjust the power parameters corresponding to the multiple power equipment.

9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the power equipment adjustment strategy method of the power station as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: When the instructions in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the power equipment adjustment strategy method of a power station as claimed in any one of claims 1 to 7.

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