CN115173404A - Combined power supply control method and system for multiple emergency power generation devices - Google Patents

Combined power supply control method and system for multiple emergency power generation devices Download PDF

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Publication number
CN115173404A
CN115173404A CN202210806424.1A CN202210806424A CN115173404A CN 115173404 A CN115173404 A CN 115173404A CN 202210806424 A CN202210806424 A CN 202210806424A CN 115173404 A CN115173404 A CN 115173404A
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China
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power generation
power supply
emergency
emergency power
equipment
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CN202210806424.1A
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Chinese (zh)
Inventor
张伟
钟鸣
阿敏夫
连杰
乌小茜
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Inner Mongolia Electric Power Research Institute of Inner Mongolia Power Group Co Ltd
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Inner Mongolia Electric Power Research Institute of Inner Mongolia Power Group Co Ltd
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Priority to CN202210806424.1A priority Critical patent/CN115173404A/en
Priority to AU2022211871A priority patent/AU2022211871A1/en
Publication of CN115173404A publication Critical patent/CN115173404A/en
Pending legal-status Critical Current

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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/40—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation wherein a plurality of decentralised, dispersed or local energy generation technologies are operated simultaneously

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The present disclosure provides a combined power supply control method and system for multiple emergency power generation devices, the method comprising: receiving the total power supply demand of the current control period; predicting the power generation estimation amount and the residual life estimation value of each emergency power generation device in the current control period by using a machine learning algorithm according to the historical sensed environment information and operation condition information of each emergency power generation device; determining at least two emergency power generation devices in the multiple emergency power generation devices as combined power supply devices in the current control period according to the estimated values of the residual lives of the multiple emergency power generation devices; and optimizing the power supply proportion of each joint power supply device by using a preset optimization algorithm, wherein the optimization algorithm converges when the difference between the total power generation amount of each joint power supply device and the total power supply demand of the current control period is minimum, and the total power generation amount of each joint power supply device is equal to the sum of the product of the estimated power generation amount of each joint power supply device and the power supply proportion of the corresponding joint power supply device.

Description

Combined power supply control method and system for multiple emergency power generation devices
Technical Field
The present disclosure relates to the field of emergency power supply, and more particularly, to a method and a system for controlling joint power supply of multiple types of emergency power generation devices.
Background
The emergency networking comprises different types of distributed sources, such as the difference of output characteristics of an emergency diesel generator car and a distributed inverter type power supply, wherein the control modes of the distributed inverter type power supply also have difference and can be divided into a voltage source mode distributed power supply and a current source mode distributed power supply. Generally speaking, in order to realize autonomous operation of an emergency networking, control needs to realize real-time balance of active power and reactive power of a system, and multiple targets such as frequency requirements, voltage quality and system stability are guaranteed. The traditional layering has a structure for clearly controlling the bearing operation, but the power regulation and the system stability are difficult to be considered. For group control of multiple emergency power supplies, an improved optimal control strategy needs to be provided for stable control of the system.
In addition to the above-mentioned optimal control of the performance of each conventional emergency power supply, how to achieve the optimal overall performance of each emergency power supply becomes a technical problem to be solved urgently.
Disclosure of Invention
The embodiment of the disclosure aims to provide a method and a system for controlling combined power supply of multiple emergency power generation devices so as to realize optimal overall comprehensive performance of each emergency power supply.
In a first aspect, the present invention provides a method for controlling joint power supply of multiple types of emergency power generation equipment, including: receiving the total power supply demand of the current control period;
according to the historical sensed environment information and operation condition information of each emergency power generation device, predicting the power generation estimation amount and the residual life estimation value of each emergency power generation device in the current control period by using a trained machine learning algorithm;
determining at least two emergency power generation devices in the plurality of emergency power generation devices as combined power supply devices in the current control period according to the estimated values of the residual life of the plurality of emergency power generation devices;
and optimizing the power supply proportion of each joint power supply device by using a preset optimization algorithm, wherein the optimization algorithm converges when the difference between the total power generation amount of each joint power supply device and the total power supply demand of the current control period is minimum, and the total power generation amount of each joint power supply device is equal to the sum of the product of the estimated power generation amount of each joint power supply device and the power supply proportion of the corresponding joint power supply device.
Further, the step of determining at least two emergency power generation devices in the plurality of emergency power generation devices as the combined power supply device in the current control cycle according to the average value of the remaining lives of the plurality of emergency power generation devices includes:
calculating the average value of the residual life of the plurality of types of emergency power generation equipment;
judging whether the number of the emergency power generation equipment of which the residual life estimation value is larger than the residual life average value is larger than or equal to two in the plurality of types of emergency power generation equipment;
and when determining whether the number of the emergency power generation devices with the estimated remaining life values larger than the average remaining life value is larger than or equal to two, taking the emergency power generation devices with the estimated remaining life values larger than the average remaining life value as the combined power supply device in the current control period.
Furthermore, the multiple emergency power generation devices comprise wind power generation devices, photovoltaic power generation devices, energy storage devices, emergency diesel electric cars, hydrogen energy devices and fuel cell devices.
Further, the machine learning algorithm is a neural network algorithm, and the preset optimization algorithm is a genetic algorithm;
the step of using the emergency power generation equipment with the estimated value of the remaining life larger than the average value of the remaining life among the plurality of types of emergency power generation equipment as the combined power supply equipment in the current control period comprises the following steps:
sorting the emergency power generation equipment of which the residual life estimation value is greater than the residual life average value in the multiple types of emergency power generation equipment in sequence from large to small according to the power generation estimation quantity of the current control period, and selecting N pieces of emergency power generation equipment which are sorted in the first priority combined power supply equipment in the current control period; n is a preset numerical value;
the step of optimizing the power supply proportion of each combined power supply device by using a preset optimization algorithm comprises the following steps:
and optimizing the power supply proportion of the first priority combined power supply equipment by using a preset optimization algorithm.
Further, the step of calculating the remaining life average value of the plurality of emergency power generation devices further comprises:
and when the number of the emergency power generation equipment with the estimated residual life values larger than the average value of the residual life values in the plurality of types of emergency power generation equipment is less than two, taking the emergency power generation equipment with the maximum estimated residual life values as the combined power supply equipment in the current control period.
In a second aspect, the present invention provides a combined power supply control system for multiple kinds of emergency power generation equipment, including:
the power supply demand receiving module is used for receiving the total power supply demand of the current control period;
the comprehensive performance prediction module is used for predicting the power generation estimation amount and the residual life estimation value of each emergency power generation device in the current control period by using a trained machine learning algorithm according to historical sensed environment information and operation condition information of each emergency power generation device;
the power supply equipment determining module is used for determining at least two emergency power generation equipment in the plurality of emergency power generation equipment as combined power supply equipment in the current control period according to the estimated values of the residual life of the plurality of emergency power generation equipment;
and the power supply proportion optimizing module is used for optimizing the power supply proportion of each joint power supply device by using a preset optimizing algorithm, wherein the optimizing algorithm converges when the difference value between the total power generation amount of each joint power supply device and the total power supply demand of the current control period is minimum, and the total power generation amount of each joint power supply device is equal to the sum of the product of the estimated power generation amount of each joint power supply device and the power supply proportion of the corresponding joint power supply device.
Further, the power supply apparatus determination module includes:
the average life calculating unit is used for calculating the average value of the residual life of the plurality of types of emergency power generation equipment;
the equipment number judging unit is used for judging whether the number of the emergency power generation equipment of which the residual life estimated value is greater than the residual life average value is greater than or equal to two in the multiple types of emergency power generation equipment;
and the power supply equipment determining unit is used for taking the emergency power generation equipment with the residual life estimation value larger than the residual life average value in the plurality of types of emergency power generation equipment as the combined power supply equipment in the current control period when determining whether the number of the emergency power generation equipment with the residual life estimation value larger than the residual life average value in the plurality of types of emergency power generation equipment is larger than or equal to two.
Furthermore, the multiple emergency power generation devices comprise wind power generation devices, photovoltaic power generation devices, energy storage devices, emergency diesel power generation cars, hydrogen energy devices and fuel cell devices; the machine learning algorithm is a neural network algorithm, and the preset optimization algorithm is a genetic algorithm;
the joint power supply control system further includes:
the emergency power generation control module is used for taking the emergency power generation equipment with the maximum residual life estimation value as the combined power supply equipment in the current control period when the number of the emergency power generation equipment with the residual life estimation value larger than the residual life average value in the plurality of types of emergency power generation equipment is less than two;
the power supply equipment determining unit is further used for sequencing the emergency power generation equipment with the residual life estimation value larger than the residual life average value in the multiple types of emergency power generation equipment in sequence from large to small according to the power generation estimation quantity of the current control period, and selecting N pieces of emergency power generation equipment before sequencing as first priority combined power supply equipment in the current control period; n is a preset numerical value;
the power supply proportion optimizing module is further used for optimizing the power supply proportion of each first priority combined power supply device by using a preset optimization algorithm.
In a third aspect, the present invention provides a computer-readable storage medium having instructions which, when executed by at least one processor, cause the at least one processor to perform the method of joint power supply control for a plurality of emergency power generation devices.
In a fourth aspect, the present invention provides a computer apparatus comprising:
at least one processor;
at least one memory storing computer-executable instructions,
wherein the computer executable instructions, when executed by the at least one processor, cause the at least one processor to perform the method of joint power supply control of a plurality of emergency power generation devices.
According to the method and the system for controlling the combined power supply of the multiple emergency power generation devices, at least two emergency power generation devices in the multiple emergency power generation devices are determined to be used as the combined power supply device in the current control period according to the estimated values of the residual life of the multiple emergency power generation devices; and optimizing the power supply proportion of each combined power supply device by using a preset optimization algorithm to meet the total power supply demand, namely meeting the total power supply demand of the current control period on the basis of preferentially considering the residual service life of each emergency power generation device, so that each emergency power generation device can stably supply power in a combined manner, the condition that each emergency power generation device cannot supply power in a combined manner due to the fact that the service life of a single emergency power generation device is terminated in advance relative to other power generation devices is avoided, and the overall comprehensive performance of each emergency power supply is optimized.
Drawings
In order to more clearly illustrate the embodiments or technical solutions of the present invention, the drawings used in the embodiments or technical solutions in the prior art are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a flowchart of a method of joint power supply control of a plurality of emergency power generation devices according to an embodiment of the present disclosure.
Fig. 2 is a schematic block diagram of a combined power supply control system of various emergency power generation devices according to an embodiment of the present disclosure.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
It should be noted that, in the case of no conflict, the features in the following embodiments and examples may be combined with each other; moreover, based on the embodiments in the present disclosure, all other embodiments obtained by a person of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present disclosure.
It is noted that various aspects of the embodiments are described below within the scope of the appended claims. It should be apparent that the aspects described herein may be embodied in a wide variety of forms and that any specific structure and/or function described herein is merely illustrative. Based on the disclosure, one skilled in the art should appreciate that one aspect described herein may be implemented independently of any other aspects and that two or more of these aspects may be combined in various ways. For example, an apparatus may be implemented and/or a method practiced using any number of the aspects set forth herein. Additionally, such an apparatus may be implemented and/or such a method may be practiced using other structure and/or functionality in addition to one or more of the aspects set forth herein.
Fig. 1 is a flow chart of a method of joint power supply control of a plurality of emergency power generation devices according to an embodiment of the present disclosure. As shown in fig. 1, the method for controlling the joint power supply of the plurality of emergency power generation devices includes:
step 101: and receiving the total power supply demand of the current control period. During specific operation, the total power supply demand can be determined according to the current demand of each load, and the specific determination mode is not the focus of the disclosure, and reference may be made to the prior art.
Step 102: and predicting the power generation estimation amount and the residual life estimation value of each emergency power generation device in the current control period by using a trained machine learning algorithm according to the historical sensed environment information and operating condition information of each emergency power generation device.
Step 103: and determining at least two emergency generating equipment in the plurality of emergency generating equipment as combined power supply equipment in the current control period according to the estimated values of the residual life of the plurality of emergency generating equipment.
Step 104: and optimizing the power supply proportion of each joint power supply device by using a preset optimization algorithm, wherein the optimization algorithm converges when the difference between the total power generation amount of each joint power supply device and the total power supply demand of the current control period is minimum, and the total power generation amount of each joint power supply device is equal to the sum of the product of the estimated power generation amount of each joint power supply device and the power supply proportion of the corresponding joint power supply device.
In the embodiment, at least two emergency power generation devices in the multiple emergency power generation devices are determined to be used as combined power supply devices in the current control period according to the estimated values of the residual lives of the multiple emergency power generation devices; and optimizing the power supply proportion of each combined power supply device by using a preset optimization algorithm to meet the total power supply demand, namely meeting the total power supply demand of the current control period on the basis of preferentially considering the residual service life of each emergency power generation device, so that each emergency power generation device can stably supply power in a combined manner, the condition that each emergency power generation device cannot supply power in a combined manner due to the fact that the service life of a single emergency power generation device is terminated in advance is avoided, and the overall comprehensive performance of each emergency power supply is optimal.
The above-mentioned combined power supply control method for multiple emergency power generation devices also includes at least one of the following various preferred embodiments:
the first method comprises the following steps: the step of determining at least two emergency power generation devices in the plurality of emergency power generation devices as combined power supply devices in the current control period according to the average value of the remaining life of the plurality of emergency power generation devices comprises:
calculating the average value of the residual life of the plurality of types of emergency power generation equipment;
judging whether the number of the emergency power generation equipment of which the residual life estimation value is larger than the residual life average value is larger than or equal to two in the plurality of types of emergency power generation equipment;
and when determining whether the number of the emergency power generation devices with the estimated remaining life values larger than the average remaining life value is larger than or equal to two, taking the emergency power generation devices with the estimated remaining life values larger than the average remaining life value as the combined power supply device in the current control period.
And the second method comprises the following steps: the multiple emergency power generation devices comprise wind power generation devices, photovoltaic power generation devices, energy storage devices, emergency diesel power generation cars, hydrogen energy devices and fuel cell devices.
And the third is that: the machine learning algorithm is a neural network algorithm. During specific operation, according to historically sensed environment information (such as wind resource data, wind speed, wind direction, weather transformation information and the like) and operation condition information (such as rotating speed, torque, pitch angle, yaw angle and the like) of each emergency power generation device, the specific implementation process of predicting the power generation estimation amount and the residual life estimation value of each emergency power generation device in the current control period by using the trained neural network can refer to the prior art.
The preset optimization algorithm is a genetic algorithm. The genetic algorithm is an existing algorithm structure and is concretely and briefly described as follows:
randomly generating a plurality of individuals as an initial population by using a genetic algorithm model;
each individual is a multi-dimensional vector, the dimension of the vector is the same as the number of the emergency power generation devices, for example, when the plurality of emergency power generation devices comprise a wind power generation device, a photovoltaic power generation device, an energy storage device, an emergency diesel power generation vehicle, a hydrogen energy device and a fuel cell device, the dimension of each individual is 6, and the vector is represented as (G) 1 ,G 2 ,G 3 ,G 4 ,G 5 ,G 6 ) G in the vector 1 ,G 2 ,G 3 ,G 4 ,G 5 ,G 6 The power supply proportions of the wind power generation equipment, the photovoltaic power generation equipment, the energy storage equipment, the emergency diesel generating car, the hydrogen energy equipment and the fuel cell equipment are respectively corresponded;
if the estimated power generation amounts of the current control cycles of the wind power generation equipment, the photovoltaic power generation equipment, the energy storage equipment, the emergency diesel power generation car, the hydrogen energy equipment and the fuel cell equipment are respectively expressed as F 1 ,F 2 ,F 3 ,F 4 ,F 5 ,F 6 Where the total power demand for the current control cycle is denoted as Q, then according to 1/((F) 1 G 1 +F 2 G 2 +F 3 G 3 +F 4 G 4 +F 5 G 5 +F 6 G 6 ) -Q) calculating the fitness of each individual;
and continuously optimizing and calculating by using the genetic algorithm model until the individuals with the maximum fitness are used as the optimal power supply proportion of wind power generation equipment, photovoltaic power generation equipment, energy storage equipment, an emergency diesel power generation vehicle, hydrogen energy equipment and fuel cell equipment when the genetic algorithm model is converged.
Fourthly, the step of calculating the average value of the remaining life of the plurality of emergency power generation devices further comprises the following steps:
when the number of the emergency power generation equipment with the residual life estimation value larger than the residual life average value in the plurality of types of emergency power generation equipment is less than two, the emergency power generation equipment with the maximum residual life estimation value is used as the combined power supply equipment in the current control period;
fifth, the step of using the emergency power generation equipment with the estimated remaining life value larger than the average remaining life value among the plurality of types of emergency power generation equipment as the combined power supply equipment in the current control period includes:
sorting the emergency power generation equipment of which the residual life estimation value is greater than the residual life average value in the multiple types of emergency power generation equipment in sequence from large to small according to the power generation estimation quantity of the current control period, and selecting N pieces of emergency power generation equipment which are sorted in the first priority combined power supply equipment in the current control period; n is a preset numerical value;
the step of optimizing the power supply proportion of each combined power supply device by using a preset optimization algorithm comprises the following steps:
and optimizing the power supply proportion of each first priority combined power supply device by using a preset optimization algorithm.
Fig. 2 is a schematic block diagram of a combined power supply control system of a plurality of emergency power generation devices according to an embodiment of the present disclosure. The embodiment shown in fig. 1 may be used to explain the present embodiment. As shown in fig. 2: a combined power supply control system for multiple emergency power generation devices, comprising:
a power supply demand receiving module 201, configured to receive a total power supply demand of a current control period;
the comprehensive performance prediction module 202 is configured to predict, according to the historically sensed environment information and operating condition information of each emergency power generation equipment, a power generation estimation amount and a remaining life estimation value of each emergency power generation equipment in the current control period by using a trained machine learning algorithm;
a power supply equipment determining module 203, configured to determine, according to the estimated remaining life values of the multiple types of emergency power generation equipment, that at least two emergency power generation equipment in the multiple types of emergency power generation equipment serve as joint power supply equipment in a current control cycle;
and the power supply proportion optimizing module 204 is configured to optimize the power supply proportion of each joint power supply device by using a preset optimization algorithm, where the optimization algorithm converges when a difference between a total power generation amount of each joint power supply device and a total power supply demand of a current control period is minimum, and the total power generation amount of each joint power supply device is equal to a sum of a product of a power generation estimation amount of each joint power supply device and a power supply proportion of a corresponding joint power supply device.
Preferably, the power supply device determining module includes:
the average life calculating unit is used for calculating the average value of the residual life of the plurality of types of emergency power generation equipment;
the equipment number judging unit is used for judging whether the number of the emergency power generation equipment of which the residual life estimated value is greater than the residual life average value is greater than or equal to two in the multiple types of emergency power generation equipment;
and the power supply equipment determining unit is used for taking the emergency power generation equipment with the residual life estimation value larger than the residual life average value in the multiple types of emergency power generation equipment as the combined power supply equipment in the current control period when determining whether the number of the emergency power generation equipment with the residual life estimation value larger than the residual life average value in the multiple types of emergency power generation equipment is larger than or equal to two.
Preferably, the multiple emergency power generation devices comprise wind power generation devices, photovoltaic power generation devices, energy storage devices, emergency diesel power generation cars, hydrogen energy devices and fuel cell devices; the machine learning algorithm is a neural network algorithm, and the preset optimization algorithm is a genetic algorithm;
the joint power supply control system further includes:
and the emergency generating control module (not shown in the figure) is used for taking the emergency generating equipment with the maximum residual life estimated value as the combined power supply equipment in the current control period when the number of the emergency generating equipment with the residual life estimated values larger than the residual life average value in the plurality of types of emergency generating equipment is less than two.
Preferably, the power supply equipment determining unit is further configured to sort emergency power generation equipment of which the remaining life estimation value is greater than the remaining life average value among the plurality of types of emergency power generation equipment in sequence from large to small according to the power generation estimation amount of the current control period, and select N pieces of emergency power generation equipment before the sorting as first priority combined power supply equipment in the current control period; n is a preset numerical value; the power supply proportion optimizing module is further used for optimizing the power supply proportion of each first priority combined power supply device by using a preset optimizing algorithm.
In the embodiment, at least two emergency power generation devices in the multiple emergency power generation devices are determined to be used as combined power supply devices in the current control period according to the estimated values of the residual lives of the multiple emergency power generation devices; and optimizing the power supply proportion of each combined power supply device by using a preset optimization algorithm to meet the total power supply demand, namely meeting the total power supply demand of the current control period on the basis of preferentially considering the residual service life of each emergency power generation device, so that each emergency power generation device can stably supply power in a combined manner, the condition that each emergency power generation device cannot supply power in a combined manner due to the fact that the service life of a single emergency power generation device is terminated in advance is avoided, and the overall comprehensive performance of each emergency power supply is optimal.
The present invention also provides a computer apparatus comprising: at least one processor; at least one memory storing computer-executable instructions, wherein the computer-executable instructions, when executed by the at least one processor, cause the at least one processor to perform the method of joint power supply control for a plurality of emergency power generation devices.
The present invention also provides a computer readable medium having stored thereon computer instructions which, when executed by a processor, cause the processor to execute the method of joint power supply control of a plurality of emergency power generation apparatuses.
In this case, the program code itself read from the storage medium can realize the functions of any of the above-described embodiments, and thus the program code and the storage medium storing the program code constitute a part of the present invention.
Examples of the storage medium for supplying the program code include a floppy disk, a hard disk, a magneto-optical disk, an optical disk (e.g., CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD + RW), a magnetic tape, a nonvolatile memory card, and a ROM. Alternatively, the program code may be downloaded from a server computer via a communications network.
Further, it should be clear that the functions of any one of the above-described embodiments may be implemented not only by executing the program code read out by the computer, but also by causing an operating system or the like operating on the computer to perform a part or all of the actual operations based on instructions of the program code.
Further, it is to be understood that the program code read out from the storage medium is written to a memory provided in an expansion board inserted into the computer or to a memory provided in an expansion unit connected to the computer, and then a CPU or the like mounted on the expansion board or the expansion unit is caused to perform part or all of the actual operations based on instructions of the program code, thereby realizing the functions of any of the embodiments described above.
It should be noted that not all steps and modules in the above flows and system structure diagrams are necessary, and some steps or modules may be omitted according to actual needs. The execution order of the steps is not fixed and can be adjusted as required. The system structures described in the above embodiments may be physical structures or logical structures, that is, some modules may be implemented by the same physical entity, or some modules may be implemented by a plurality of physical entities separately, or some components may be implemented together in a plurality of independent devices.
In the above embodiments, the hardware unit may be implemented mechanically or electrically. For example, a hardware element may comprise permanently dedicated circuitry or logic (such as a dedicated processor, FPGA or ASIC) to perform the corresponding operations. The hardware elements may also comprise programmable logic or circuitry, such as a general purpose processor or other programmable processor, that may be temporarily configured by software to perform the corresponding operations. The specific implementation (mechanical, or dedicated permanent, or temporarily set) may be determined based on cost and time considerations.
While the invention has been shown and described in detail in the drawings and in the preferred embodiments, it is not intended to limit the invention to the embodiments disclosed, and it will be apparent to those skilled in the art that various combinations of the code auditing means in the various embodiments described above may be used to obtain further embodiments of the invention, which are also within the scope of the invention.

Claims (10)

1. A combined power supply control method for multiple types of emergency power generation equipment is characterized by comprising the following steps:
receiving the total power supply demand of the current control period;
according to the historical sensed environment information and operation condition information of each emergency power generation device, predicting the power generation estimation amount and the residual life estimation value of each emergency power generation device in the current control period by using a trained machine learning algorithm;
determining at least two emergency generating equipment in the multiple types of emergency generating equipment as combined power supply equipment in the current control period according to the estimated values of the residual life of the multiple types of emergency generating equipment;
and optimizing the power supply proportion of each joint power supply device by using a preset optimization algorithm, wherein the optimization algorithm converges when the difference between the total power generation amount of each joint power supply device and the total power supply demand of the current control period is minimum, and the total power generation amount of each joint power supply device is equal to the sum of the product of the estimated power generation amount of each joint power supply device and the power supply proportion of the corresponding joint power supply device.
2. The method for controlling joint power supply to a plurality of emergency power generating apparatuses according to claim 1, wherein the step of determining at least two emergency power generating apparatuses of the plurality of emergency power generating apparatuses as the joint power generating apparatuses in the current control period based on the average value of the remaining lives of the plurality of emergency power generating apparatuses comprises:
calculating the average value of the residual life of the plurality of types of emergency power generation equipment;
judging whether the number of the emergency power generation equipment of which the residual life estimation value is larger than the residual life average value is larger than or equal to two in the plurality of types of emergency power generation equipment;
and when determining whether the number of the emergency power generation devices with the estimated remaining life values larger than the average remaining life value is larger than or equal to two, taking the emergency power generation devices with the estimated remaining life values larger than the average remaining life value as the combined power supply device in the current control period.
3. The method of claim 2, wherein the plurality of emergency power generation devices comprise a wind power generation device, a photovoltaic power generation device, an energy storage device, an emergency diesel-electric vehicle, a hydrogen energy device, and a fuel cell device.
4. The method of claim 3, wherein the machine learning algorithm is a neural network algorithm and the predetermined optimization algorithm is a genetic algorithm;
the step of using the emergency power generation equipment with the estimated value of the remaining life larger than the average value of the remaining life among the plurality of types of emergency power generation equipment as the combined power supply equipment in the current control period comprises the following steps:
sorting the emergency power generation equipment of which the residual life estimation value is greater than the residual life average value in the multiple types of emergency power generation equipment in sequence from large to small according to the power generation estimation quantity of the current control period, and selecting N pieces of emergency power generation equipment which are sorted in the first priority combined power supply equipment in the current control period; n is a preset numerical value;
the step of optimizing the power supply proportion of each combined power supply device by using a preset optimization algorithm comprises the following steps:
and optimizing the power supply proportion of each first priority combined power supply device by using a preset optimization algorithm.
5. The combined power supply control method of a plurality of emergency power generation devices according to claim 4, wherein the step of calculating the average value of the remaining life of the plurality of emergency power generation devices is further followed by:
and when the number of the emergency power generation equipment with the estimated residual life values larger than the average value of the residual life values in the plurality of types of emergency power generation equipment is less than two, taking the emergency power generation equipment with the maximum estimated residual life values as the combined power supply equipment in the current control period.
6. A joint power supply control system for multiple emergency power generation devices, comprising:
the power supply demand receiving module is used for receiving the total power supply demand of the current control period;
the comprehensive performance prediction module is used for predicting the power generation estimation amount and the residual life estimation value of each emergency power generation device in the current control period by using a trained machine learning algorithm according to historical sensed environment information and operation condition information of each emergency power generation device;
the power supply equipment determining module is used for determining at least two emergency power generation equipment in the plurality of emergency power generation equipment as combined power supply equipment in the current control period according to the estimated values of the residual life of the plurality of emergency power generation equipment;
and the power supply proportion optimizing module is used for optimizing the power supply proportion of each joint power supply device by using a preset optimizing algorithm, wherein the optimizing algorithm converges when the difference value between the total power generation amount of each joint power supply device and the total power supply demand of the current control period is minimum, and the total power generation amount of each joint power supply device is equal to the sum of the product of the estimated power generation amount of each joint power supply device and the power supply proportion of the corresponding joint power supply device.
7. The combined power supply control system of a plurality of emergency power generating devices according to claim 6, wherein the power supply device determining module includes:
the average life calculating unit is used for calculating the average value of the residual life of the plurality of types of emergency power generation equipment;
the equipment number judging unit is used for judging whether the number of the emergency power generation equipment of which the residual life estimated value is greater than the residual life average value is greater than or equal to two in the multiple types of emergency power generation equipment;
and the power supply equipment determining unit is used for taking the emergency power generation equipment with the residual life estimation value larger than the residual life average value in the plurality of types of emergency power generation equipment as the combined power supply equipment in the current control period when determining whether the number of the emergency power generation equipment with the residual life estimation value larger than the residual life average value in the plurality of types of emergency power generation equipment is larger than or equal to two.
8. The combined power supply control system of multiple emergency power generation devices according to claim 7, wherein the multiple emergency power generation devices include a wind power generation device, a photovoltaic power generation device, an energy storage device, an emergency diesel-electric vehicle, a hydrogen energy device, and a fuel cell device; the machine learning algorithm is a neural network algorithm, and the preset optimization algorithm is a genetic algorithm;
the joint power supply control system further includes:
the emergency power generation control module is used for taking the emergency power generation equipment with the maximum residual life estimation value as the combined power supply equipment in the current control period when the number of the emergency power generation equipment with the residual life estimation value larger than the residual life average value in the plurality of types of emergency power generation equipment is less than two;
the power supply equipment determining unit is further used for sequencing the emergency power generation equipment with the residual life estimation value larger than the residual life average value in the multiple types of emergency power generation equipment in sequence from large to small according to the power generation estimation quantity of the current control period, and selecting N pieces of emergency power generation equipment before sequencing as first priority combined power supply equipment in the current control period; n is a preset numerical value;
the power supply proportion optimizing module is further used for optimizing the power supply proportion of each first priority combined power supply device by using a preset optimization algorithm.
9. A computer-readable storage medium, wherein instructions in the computer-readable storage medium, when executed by at least one processor, cause the at least one processor to perform a method of joint power supply control of a plurality of emergency power generation devices according to any one of claims 1-5.
10. A computer device, comprising:
at least one processor;
at least one memory storing computer-executable instructions,
wherein the computer-executable instructions, when executed by the at least one processor, cause the at least one processor to perform a method of joint power supply control of a plurality of emergency power generation devices as set forth in any one of claims 1-5.
CN202210806424.1A 2022-07-08 2022-07-08 Combined power supply control method and system for multiple emergency power generation devices Pending CN115173404A (en)

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