CN114818059B - Building energy-saving strategy optimization control method, device, equipment and readable storage medium - Google Patents
Building energy-saving strategy optimization control method, device, equipment and readable storage medium Download PDFInfo
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Abstract
The invention discloses a building energy-saving strategy optimization control method, a device, equipment and a readable storage medium, and belongs to the technical field of buildings. The building energy-saving strategy optimization control method comprises the following steps: acquiring operation parameters of a preset energy utilization system and preset energy utilization equipment; constructing a data model according to the operation parameters; automatically generating a plurality of energy consumption configuration schemes based on the data model; combining the plurality of energy consumption configuration schemes to establish a comprehensive energy saving scheme; and constructing an optimized data model based on the comprehensive energy-saving scheme to optimize the comprehensive energy-saving scheme. By implementing the invention, the prediction of the energy consumption condition of the non-fixed logic mode and the formulation of the strategy are realized, the instant adjustment of an energy consumption system and energy consumption equipment is realized, the unnecessary energy consumption expenditure is reduced, and a more accurate building energy-saving adjustment strategy is provided.
Description
Technical Field
The invention relates to the technical field of buildings, in particular to a building energy-saving strategy optimization control method, a device, equipment and a readable storage medium.
Background
Energy is one of the most important resources of society. The energy consumption in the building industry is intensive, accounting for about 40% of the total energy consumption. And 57% of these energy consumption are from heating, ventilation, air conditioning, lighting, etc. links according to the U.S. department of energy information. Comprehensively considering the energy consumption mechanism of the whole building and improving the energy efficiency of the building has become an international problem considered by designers and researchers.
In the prior art, most of researches are directed to the design of building materials or the research of building energy-saving equipment or devices, but along with the popularization of the internet of things, the traditional building is rapidly transformed to an intelligent building, and the building energy-saving strategy is formulated by the mode in a fixed logic manner, so that the method is not flexible enough and cannot be suitable for the intelligent building with rapid development.
Disclosure of Invention
The invention mainly aims to provide a building energy-saving strategy optimization control method, a device, equipment and a readable storage medium, which aim to solve the technical problem of how to improve the existing building energy-saving strategy so as to adapt to intelligent buildings with rapid development.
In order to achieve the above object, the present invention provides a building energy saving strategy optimization control method, which includes the following steps:
acquiring operation parameters of a preset energy utilization system and preset energy utilization equipment;
constructing a data model according to the operation parameters;
automatically generating a plurality of energy consumption configuration schemes based on the data model;
combining the plurality of energy consumption configuration schemes to establish a comprehensive energy saving scheme;
and constructing an optimized data model based on the comprehensive energy-saving scheme to optimize the comprehensive energy-saving scheme.
Optionally, the step of constructing a data model according to the operation parameters includes:
and constructing a basic data model and an energy consumption membership chart according to the operation parameters.
Optionally, the step of constructing a data model according to the operation parameters includes:
and configuring a plurality of system primary index parameters according to the data model.
Optionally, the step of automatically generating a plurality of energy consumption configurations based on the data model includes:
substituting the primary index parameters of the multiple systems into the data model respectively, and automatically generating multiple energy consumption configuration schemes corresponding to the index parameters of the multiple systems.
Optionally, the step of automatically generating a plurality of energy consumption configurations based on the data model includes:
acquiring dimension types to which the multiple energy consumption configuration schemes belong;
and classifying the multiple energy consumption configuration schemes according to the dimension types.
Optionally, the step of combining the plurality of energy consumption configuration schemes to establish an integrated energy saving scheme includes:
the multiple energy consumption configuration schemes of different classifications are combined to establish an integrated energy conservation scheme.
Optionally, the step of constructing an optimization data model based on the comprehensive energy saving scheme to optimize the comprehensive energy saving scheme includes:
constructing an optimized data model based on the comprehensive energy-saving scheme;
constructing an optimized energy-saving scheme based on the optimized data model;
performing comparative analysis based on the optimized energy-saving scheme and the comprehensive energy-saving scheme;
obtaining a comparison analysis result, and generating a proposal configuration report according to the comparison analysis result;
optimizing the comprehensive energy saving scheme according to the suggested configuration report.
In addition, in order to achieve the above object, the present invention also provides a building energy saving strategy optimization control device, including:
the acquisition module is used for acquiring operation parameters of the preset energy utilization system and the preset energy utilization equipment;
the construction module is used for constructing a data model according to the operation parameters;
the generation module is used for automatically generating various energy consumption configuration schemes based on the data model;
a combining module for combining the plurality of energy consumption configuration schemes to establish a comprehensive energy saving scheme;
and the optimization module is used for constructing an optimization data model based on the comprehensive energy-saving scheme so as to optimize the comprehensive energy-saving scheme.
In addition, in order to achieve the above object, the present invention also provides a building energy saving strategy optimization control device, including: the system comprises a memory, a processor and a building energy saving strategy optimization control program which is stored in the memory and can run on the processor, wherein the building energy saving strategy optimization control program realizes the steps of the building energy saving strategy optimization control method when being executed by the processor.
In addition, in order to achieve the above object, the present invention also provides a computer-readable storage medium having stored thereon a construction energy saving policy optimization control program which, when executed by a processor, implements the steps of the construction energy saving policy optimization control method as described above.
The invention provides a building energy-saving strategy optimization control method, a device, equipment and a readable storage medium, which solve the problems that the building energy-saving strategy formulation in the prior art is of fixed logic, is not flexible enough and cannot adapt to intelligent buildings with rapid development. In the building energy-saving strategy optimization control method, the operation parameters of a preset energy utilization system and preset energy utilization equipment are obtained; constructing a data model according to the operation parameters; automatically generating a plurality of energy consumption configuration schemes based on the data model; combining the plurality of energy consumption configuration schemes to establish a comprehensive energy saving scheme; and constructing an optimized data model based on the comprehensive energy-saving scheme to optimize the comprehensive energy-saving scheme. The prediction of the energy consumption condition of a non-fixed logic mode and the formulation of a strategy are realized, the instant adjustment of an energy consumption system and energy consumption equipment is realized, the unnecessary energy consumption expenditure is reduced, a more accurate building energy-saving adjustment strategy is provided through the multiple optimization of a data model, and the best matching can be found out from various possible structures and parameters of each energy consumption system, so that the overall efficiency is optimal, the efficiency of the system is improved, and the investment and the running cost are reduced; the system and the process thereof can be quantitatively simulated, the control links are reduced, the reliability and the stability are improved, the probability of failure is reduced to the lowest possible limit, the response output of the system is optimized, and the energy saving purpose is achieved through the optimized control scheme, so that the system is an active energy saving scheme.
Drawings
FIG. 1 is a schematic structural diagram of a building energy conservation strategy optimization control device for a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a first embodiment of the building energy conservation strategy optimization control method of the invention;
fig. 3 is a schematic structural diagram of an embodiment of the building energy-saving strategy optimization control device of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The main solutions of the embodiments of the present invention are: the building energy-saving strategy optimization control method comprises the following steps:
acquiring operation parameters of a preset energy utilization system and preset energy utilization equipment;
constructing a data model according to the operation parameters;
automatically generating a plurality of energy consumption configuration schemes based on the data model;
combining the plurality of energy consumption configuration schemes to establish a comprehensive energy saving scheme;
and constructing an optimized data model based on the comprehensive energy-saving scheme to optimize the comprehensive energy-saving scheme.
Most of researches in the prior building energy-saving design are focused on the design of building materials or the research of building energy-saving equipment or devices, but along with the popularization of the Internet of things, the traditional building is rapidly transformed into an intelligent building, and the building energy-saving strategy is formulated by the mode in a fixed logic manner, so that the method is not flexible enough and cannot be suitable for the intelligent building with rapid development.
The invention provides a building energy-saving strategy optimization control method, which solves the technical problems that the building energy-saving strategy formulation in the prior art is of fixed logic, is not flexible enough and cannot adapt to intelligent buildings with rapid development. In the building energy-saving strategy optimization control method, the operation parameters of a preset energy utilization system and preset energy utilization equipment are obtained; constructing a data model according to the operation parameters; automatically generating a plurality of energy consumption configuration schemes based on the data model; combining the plurality of energy consumption configuration schemes to establish a comprehensive energy saving scheme; and constructing an optimized data model based on the comprehensive energy-saving scheme to optimize the comprehensive energy-saving scheme. The prediction of the energy consumption condition of a non-fixed logic mode and the formulation of a strategy are realized, the instant adjustment of an energy consumption system and energy consumption equipment is realized, the unnecessary energy consumption expenditure is reduced, a more accurate building energy-saving adjustment strategy is provided through the multiple optimization of a data model, and the best matching can be found out from various possible structures and parameters of each energy consumption system, so that the overall efficiency is optimal, the efficiency of the system is improved, and the investment and the running cost are reduced; the system and the process thereof can be quantitatively simulated, the control links are reduced, the reliability and the stability are improved, the probability of failure is reduced to the lowest possible limit, the response output of the system is optimized, and the energy saving purpose is achieved through the optimized control scheme, so that the system is an active energy saving scheme.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a building energy saving strategy optimization control device of a hardware operation environment according to an embodiment of the present invention.
As shown in fig. 1, the building energy saving strategy optimization control device may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1005 may be a high-speed random access Memory (Random Access Memory, RAM) Memory or a stable nonvolatile Memory (NVM), such as a disk Memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
Optionally, the building energy saving strategy optimization control device may further include a camera, an RF (Radio Frequency) circuit, a sensor, an audio circuit, a WiFi module, and the like. Among other sensors, such as light sensors, motion sensors, and other sensors. Specifically, the light sensor may include an ambient light sensor that may adjust the brightness of the display screen according to the brightness of ambient light, and a proximity sensor that may turn off the display screen and/or the backlight when the mobile terminal moves to the ear. As one of the motion sensors, the gravity acceleration sensor can detect the acceleration in all directions (generally three axes), and can detect the gravity and the direction when the mobile terminal is stationary, and the mobile terminal can be used for recognizing the gesture of the mobile terminal (such as horizontal and vertical screen switching, related games, magnetometer gesture calibration), vibration recognition related functions (such as pedometer and knocking), and the like; of course, the mobile terminal may also be configured with other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor, and the like, which are not described herein.
It will be appreciated by those skilled in the art that the structure shown in fig. 1 does not constitute a limitation of the building energy conservation strategy optimization control device, and may include more or fewer components than shown, or certain components in combination, or a different arrangement of components.
As shown in fig. 1, an operating system, a network communication module, a user interface module, and a building energy saving policy optimization control program may be included in a memory 1005 as one type of computer storage medium.
In the energy-saving policy optimizing control device shown in fig. 1, the network interface 1004 is mainly used for data communication with other devices; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the building energy saving strategy optimization control device of the present invention may be provided in the building energy saving strategy optimization control device, and the building energy saving strategy optimization control device invokes the building energy saving strategy optimization control program stored in the memory 1005 through the processor 1001 and performs the following operations:
acquiring operation parameters of a preset energy utilization system and preset energy utilization equipment;
constructing a data model according to the operation parameters;
automatically generating a plurality of energy consumption configuration schemes based on the data model;
combining the plurality of energy consumption configuration schemes to establish a comprehensive energy saving scheme;
and constructing an optimized data model based on the comprehensive energy-saving scheme to optimize the comprehensive energy-saving scheme.
Further, the processor 1001 may call the building energy saving policy optimization control program stored in the memory 1005, and further perform the following operations:
the step of constructing a data model according to the operation parameters comprises the following steps:
and constructing a basic data model and an energy consumption membership chart according to the operation parameters.
Further, the processor 1001 may call the building energy saving policy optimization control program stored in the memory 1005, and further perform the following operations:
the step of constructing a data model according to the operation parameters comprises the following steps:
and configuring a plurality of system primary index parameters according to the data model.
Further, the processor 1001 may call the building energy saving policy optimization control program stored in the memory 1005, and further perform the following operations:
the step of automatically generating a plurality of energy consumption configuration schemes based on the data model comprises the following steps:
substituting the primary index parameters of the multiple systems into the data model respectively, and automatically generating multiple energy consumption configuration schemes corresponding to the index parameters of the multiple systems.
Further, the processor 1001 may call the building energy saving policy optimization control program stored in the memory 1005, and further perform the following operations:
the step of automatically generating a plurality of energy consumption configuration schemes based on the data model comprises the following steps:
acquiring dimension types to which the multiple energy consumption configuration schemes belong;
and classifying the multiple energy consumption configuration schemes according to the dimension types.
Further, the processor 1001 may call the building energy saving policy optimization control program stored in the memory 1005, and further perform the following operations:
the step of combining the plurality of energy consumption configuration schemes to establish an integrated energy saving scheme includes:
the multiple energy consumption configuration schemes of different classifications are combined to establish an integrated energy conservation scheme.
Further, the processor 1001 may call the building energy saving policy optimization control program stored in the memory 1005, and further perform the following operations:
the step of constructing an optimization data model based on the comprehensive energy saving scheme to optimize the comprehensive energy saving scheme includes:
constructing an optimized data model based on the comprehensive energy-saving scheme;
constructing an optimized energy-saving scheme based on the optimized data model;
performing comparative analysis based on the optimized energy-saving scheme and the comprehensive energy-saving scheme;
obtaining a comparison analysis result, and generating a proposal configuration report according to the comparison analysis result;
optimizing the comprehensive energy saving scheme according to the suggested configuration report.
The embodiment of the invention provides a building energy-saving strategy optimization control method, and referring to fig. 2, fig. 2 is a flow diagram of an embodiment of the building energy-saving strategy optimization control method.
In this embodiment, the building energy-saving strategy optimization control method includes:
step S10, acquiring operation parameters of a preset energy utilization system and preset energy utilization equipment;
in this embodiment, the execution body is a building energy-saving policy optimization control device, and the preset energy consumption system and the preset energy consumption device are energy consumption systems and energy consumption devices in an intelligent building, such as systems for lighting, cooling, heating, fresh air, water supply, water drainage and the like, and devices for electric lamps, air conditioners, heating, water heaters and the like. In this embodiment, metadata is established by the data acquisition service, capturing and using the energy system and using the set operating parameters. Through low-cost key IoT (Internet of Things ) data, in combination with an AI (Artificial Intelligence) algorithm, more accurate energy consumption data can be predicted, an energy consumption strategy is formulated, and in combination with uncertain factor variables such as outdoor weather conditions, indoor environment conditions, people flow and the like, the operation parameters of each energy consumption system and energy consumption equipment are adjusted in real time, so that unnecessary energy consumption expenditure is reduced, and the purposes of energy conservation and emission reduction are achieved.
Step S20, constructing a data model according to the operation parameters;
it will be appreciated that after the data acquisition is completed in the foregoing step S10, the building energy-saving strategy optimization control device will construct the most basic device model data based on the acquired data, so as to provide a basic model for subsequent data analysis.
As an example, step S20 includes: and constructing a basic data model and an energy consumption membership chart according to the operation parameters.
In this embodiment, through the process, in addition to building a basic data model, different systems, such as lighting, cooling, heating, fresh air, water supply and drainage, and the like, can be built with structural dimensions, and are divided into unidirectional association, bidirectional association, multidimensional association, aggregate association and combined association, and the built association instant energy membership graph contains a basic equation of energy-saving AI deep learning, so as to prepare for subsequent evaluation work.
As an example, step S20 is followed by: and configuring a plurality of system primary index parameters according to the data model.
In this embodiment, based on the basic data model and the energy consumption membership map data of each system given in the foregoing steps, primary index parameters of the system are configured, where the primary index is calculated as first metadata, and the primary index includes energy consumption targets of each system, energy saving targets, reference parameters of cooling and heating targets in each season or quarter, and the like.
Step S30, automatically generating a plurality of energy consumption configuration schemes based on the data model;
as an example, step S30 includes: substituting the primary index parameters of the multiple systems into the data model respectively, and automatically generating multiple energy consumption configuration schemes corresponding to the index parameters of the multiple systems.
As an example, step S30 is followed by: acquiring dimension types to which the multiple energy consumption configuration schemes belong; and classifying the multiple energy consumption configuration schemes according to the dimension types.
In this embodiment, metadata, which is the primary index parameter of the configured multiple systems, is respectively substituted into the data model, and according to the data model calculated at one time, an energy consumption configuration scheme is automatically generated, and according to multiple configuration schemes of different dimensions, the energy consumption configuration scheme is classified into a quaternary energy consumption configuration, a daily energy consumption configuration, a large, medium and small passenger flow energy consumption configuration, and a weather energy consumption configuration, and each configuration is further classified into a recommended configuration, a strict emission reduction configuration, and a comfortable configuration.
Step S40, combining the multiple energy consumption configuration schemes to establish a comprehensive energy saving scheme;
as an example, step S40 includes: the multiple energy consumption configuration schemes of different classifications are combined to establish an integrated energy conservation scheme.
In this embodiment, a comprehensive energy-saving scheme is established by combining multiple energy consumption configuration schemes generated based on the steps, that is, according to the multi-dimensional configuration, the configuration and combination are selected and combined into an overall operation scheme, the scheme is used for performing data execution, and each system device performs automatic parameter control operation according to time and other configuration data in the scheme. For example, the air conditioner operates according to the temperature and mode configured by the scheme and is turned on or off at a designated time; for example, the water heater is operated in a fast mode or a steady mode configured according to the scheme and is turned on or off at a designated time.
And S50, constructing an optimized data model based on the comprehensive energy-saving scheme to optimize the comprehensive energy-saving scheme.
As an example, step S50 includes: constructing an optimized data model based on the comprehensive energy-saving scheme; constructing an optimized energy-saving scheme based on the optimized data model; performing comparative analysis based on the optimized energy-saving scheme and the comprehensive energy-saving scheme; obtaining a comparison analysis result, and generating a proposal configuration report according to the comparison analysis result; optimizing the comprehensive energy saving scheme according to the suggested configuration report.
In this embodiment, after each energy consumption system in the intelligent building starts to operate for a period of time based on the comprehensive energy saving scheme, the operation parameters of each energy consumption system and each energy consumption device are collected again, new operation parameters are substituted into a data model established before to perform calculation, a newly generated energy saving scheme is obtained based on the data model of the secondary calculation, and the newly generated energy saving scheme is compared and analyzed with the comprehensive energy saving scheme obtained by the primary calculation, so that differences and different points of each energy saving strategy after specific implementation are obtained.
After the comparison analysis is completed, the embodiment generates the suggested configuration report, and the suggested configuration report can be provided for the user, so that the user can change the configuration in the energy-saving scheme according to the report, and the final building energy-saving strategy can achieve better energy-saving effect and also accords with the subjective intention of the user.
The embodiment provides a building energy-saving strategy optimization control method, which solves the technical problems that the building energy-saving strategy formulation in the prior art is fixed logic, is not flexible enough and cannot adapt to intelligent buildings with rapid development. In the building energy-saving strategy optimization control method, the operation parameters of a preset energy utilization system and preset energy utilization equipment are obtained; constructing a data model according to the operation parameters; automatically generating a plurality of energy consumption configuration schemes based on the data model; combining the plurality of energy consumption configuration schemes to establish a comprehensive energy saving scheme; and constructing an optimized data model based on the comprehensive energy-saving scheme to optimize the comprehensive energy-saving scheme. The method realizes the prediction of the energy consumption condition of the non-fixed logic mode and the formulation of strategies, realizes the instant adjustment of an energy consumption system and energy consumption equipment, reduces unnecessary energy consumption expenditure, and provides a more accurate building energy-saving adjustment strategy through the multiple optimization of a data model.
In the embodiment, the best matching can be found from various possible structures and parameters of each system consuming energy, so that the overall efficiency is optimal, the efficiency of the system is improved, and the investment and the operation cost are reduced; the system and the process thereof can be quantitatively simulated, the control links are reduced, the reliability and the stability are improved, the probability of failure is reduced to the lowest possible limit, the response output of the system is optimized, and the energy saving purpose is achieved through the optimized control scheme, so that the system is an active energy saving technical scheme.
According to the embodiment, more accurate energy consumption data can be predicted by combining low-cost key internet traffic (IoT) data with an AI algorithm, an energy consumption strategy is formulated, and the operation parameters of each energy consumption system and energy consumption equipment are adjusted in real time by combining uncertain factor variables such as outdoor weather conditions, indoor environment conditions and people flow, so that unnecessary energy consumption expenditure is reduced, and the aims of energy conservation and emission reduction are achieved.
In the embodiment, for the prediction of the energy consumption situation and the formulation of the strategy, which are not fixed logic modes, the system can automatically analyze the energy saving situation, establish a data model, actively learn and try the combination scheme of different mode configurations, and give the optimal energy saving and emission reduction strategy. The data model established through the deep learning calculation can be quickly reused in other project energy saving and emission reduction systems, and a new data model is established again based on factor variables, energy consumption actual conditions and the like of the target project, so that a more accurate adjustment strategy is made for the energy saving conditions of the target project.
In addition, the embodiment of the invention also provides a building energy-saving strategy optimization control device, and referring to fig. 3, fig. 3 is a schematic structural diagram of an embodiment of the building energy-saving strategy optimization control device.
In this embodiment, the building energy saving strategy optimization control device 10 includes:
an obtaining module 101, configured to obtain operation parameters of a preset energy consumption system and a preset energy consumption device;
a construction module 102, configured to construct a data model according to the operation parameters;
a generating module 103, configured to automatically generate a plurality of energy consumption configuration schemes based on the data model;
a combining module 104, configured to combine the multiple energy consumption configuration schemes to establish a comprehensive energy saving scheme;
an optimization module 105, configured to construct an optimization data model based on the comprehensive energy saving scheme to optimize the comprehensive energy saving scheme.
In addition, the embodiment of the invention also provides a computer readable storage medium, wherein the computer readable storage medium is stored with a building energy saving strategy optimization control program, and the building energy saving strategy optimization control program realizes the following operations when being executed by a processor:
acquiring operation parameters of a preset energy utilization system and preset energy utilization equipment;
constructing a data model according to the operation parameters;
automatically generating a plurality of energy consumption configuration schemes based on the data model;
combining the plurality of energy consumption configuration schemes to establish a comprehensive energy saving scheme;
and constructing an optimized data model based on the comprehensive energy-saving scheme to optimize the comprehensive energy-saving scheme.
Further, the building energy saving strategy optimization control program also realizes the following operations when being executed by the processor:
the step of constructing a data model according to the operation parameters comprises the following steps:
and constructing a basic data model and an energy consumption membership chart according to the operation parameters.
Further, the building energy saving strategy optimization control program also realizes the following operations when being executed by the processor:
the step of constructing a data model according to the operation parameters comprises the following steps:
and configuring a plurality of system primary index parameters according to the data model.
Further, the building energy saving strategy optimization control program also realizes the following operations when being executed by the processor:
the step of automatically generating a plurality of energy consumption configuration schemes based on the data model comprises the following steps:
substituting the primary index parameters of the multiple systems into the data model respectively, and automatically generating multiple energy consumption configuration schemes corresponding to the index parameters of the multiple systems.
Further, the building energy saving strategy optimization control program also realizes the following operations when being executed by the processor:
the step of automatically generating a plurality of energy consumption configuration schemes based on the data model comprises the following steps:
acquiring dimension types to which the multiple energy consumption configuration schemes belong;
and classifying the multiple energy consumption configuration schemes according to the dimension types.
Further, the building energy saving strategy optimization control program also realizes the following operations when being executed by the processor:
the step of combining the plurality of energy consumption configuration schemes to establish an integrated energy saving scheme includes:
the multiple energy consumption configuration schemes of different classifications are combined to establish an integrated energy conservation scheme.
Further, the building energy saving strategy optimization control program also realizes the following operations when being executed by the processor:
the step of constructing an optimization data model based on the comprehensive energy saving scheme to optimize the comprehensive energy saving scheme includes:
constructing an optimized data model based on the comprehensive energy-saving scheme;
constructing an optimized energy-saving scheme based on the optimized data model;
performing comparative analysis based on the optimized energy-saving scheme and the comprehensive energy-saving scheme;
obtaining a comparison analysis result, and generating a proposal configuration report according to the comparison analysis result;
optimizing the comprehensive energy saving scheme according to the suggested configuration report.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (6)
1. The building energy-saving strategy optimization control method is characterized by comprising the following steps of:
acquiring operation parameters of a preset energy utilization system and preset energy utilization equipment;
constructing a data model according to the operation parameters;
configuring a plurality of system primary index parameters according to the data model;
substituting the primary index parameters of the multiple systems into the data model respectively, and automatically generating multiple energy consumption configuration schemes corresponding to the index parameters of the multiple systems;
acquiring dimension types to which the multiple energy consumption configuration schemes belong; classifying the plurality of energy consumption configuration schemes according to the dimension type;
combining the plurality of energy consumption configuration schemes of different classifications to establish a comprehensive energy saving scheme;
and constructing an optimized data model based on the comprehensive energy-saving scheme to optimize the comprehensive energy-saving scheme.
2. The building energy saving strategy optimization control method according to claim 1, wherein the step of constructing a data model according to the operation parameters comprises:
and constructing a basic data model and an energy consumption membership chart according to the operation parameters.
3. The building energy saving strategy optimization control method according to claim 1 or 2, wherein the step of constructing an optimization data model based on the comprehensive energy saving strategy to optimize the comprehensive energy saving strategy comprises:
constructing an optimized data model based on the comprehensive energy-saving scheme;
constructing an optimized energy-saving scheme based on the optimized data model;
performing comparative analysis based on the optimized energy-saving scheme and the comprehensive energy-saving scheme;
obtaining a comparison analysis result, and generating a proposal configuration report according to the comparison analysis result;
optimizing the comprehensive energy saving scheme according to the suggested configuration report.
4. The utility model provides a building energy saving strategy optimization control device which characterized in that, building energy saving strategy optimization control device includes:
the acquisition module is used for acquiring operation parameters of the preset energy utilization system and the preset energy utilization equipment;
the construction module is used for constructing a data model according to the operation parameters; configuring a plurality of system primary index parameters according to the data model;
the generation module is used for substituting the primary index parameters of the multiple systems into the data model respectively and automatically generating multiple energy consumption configuration schemes corresponding to the index parameters of the multiple systems; acquiring dimension types to which the multiple energy consumption configuration schemes belong; classifying the plurality of energy consumption configuration schemes according to the dimension type;
the combination module is used for combining the multiple energy consumption configuration schemes of different classifications to establish a comprehensive energy saving scheme;
and the optimization module is used for constructing an optimization data model based on the comprehensive energy-saving scheme so as to optimize the comprehensive energy-saving scheme.
5. A building energy conservation strategy optimization control device, characterized in that the building energy conservation strategy optimization control device comprises: a memory, a processor and a construction energy saving policy optimization control program stored on the memory and executable on the processor, which when executed by the processor, implements the steps of the construction energy saving policy optimization control method according to any one of claims 1 to 3.
6. A computer-readable storage medium, wherein a building energy saving policy optimization control program is stored on the computer-readable storage medium, which when executed by a processor, implements the steps of the building energy saving policy optimization control method according to any one of claims 1 to 3.
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