CN113972646A - Intelligent optimization energy-saving system based on economic operation diagnosis and analysis - Google Patents

Intelligent optimization energy-saving system based on economic operation diagnosis and analysis Download PDF

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Publication number
CN113972646A
CN113972646A CN202111229136.6A CN202111229136A CN113972646A CN 113972646 A CN113972646 A CN 113972646A CN 202111229136 A CN202111229136 A CN 202111229136A CN 113972646 A CN113972646 A CN 113972646A
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transformer
motor
time
real
analysis
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成静
周勇进
陆耀辉
王敏化
付学强
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WORLDWIDE ELECTRIC STOCK CO Ltd
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WORLDWIDE ELECTRIC STOCK CO Ltd
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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
    • 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
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • 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]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P80/00—Climate change mitigation technologies for sector-wide applications
    • Y02P80/10—Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier

Abstract

The invention provides an intelligent optimization energy-saving system based on economic operation diagnosis and analysis, which relates to the technical field of energy-saving optimization systems for improving the operation economy of motor transformers and comprises a data acquisition and storage module and an economic operation online analysis module, wherein the data acquisition and storage module is used for acquiring and storing real-time operation data, basic parameter data and historical operation data of electric equipment, the economic operation online analysis module establishes a characteristic analysis model according to the real-time operation data, the basic parameter data and the historical operation data of the electric equipment, the economic operation state of the electric equipment is obtained through the characteristic analysis model, and an energy-saving suggestion is generated. The problem of various energy monitoring management systems among the prior art can't carry out the analysis to the economic operation characteristic of transformer and motor, give improvement suggestion to the operation mode is solved.

Description

Intelligent optimization energy-saving system based on economic operation diagnosis and analysis
Technical Field
The invention relates to the technical field of energy-saving optimization systems, in particular to the technical field of energy-saving optimization systems for improving the running economy of motor transformers.
Background
In the development process of the enterprise, production processes, products, plans and the like can be changed along with the change of time, actual operation parameters of the motors and transformers can also be changed, the economical efficiency of the operation of the motors and transformers is closely related to the actual operation parameters, the motors and transformers need to be adjusted according to the actual operation parameters to enable the motors and transformers to be in the optimal operation state and reduce energy consumption, and in practice, because the number of the motors and transformers is large, the actual operation data amount required to be referred for parameter adjustment of the motors and transformers is large, the workload of manual measurement and calculation is large, special professional personnel is needed, and the production enterprise is difficult to realize. With the popularization and application of energy monitoring systems, energy management systems and energy saving systems in enterprises, the daily energy saving management work of the enterprises is perfected, the energy utilization efficiency and the energy saving technology of the enterprises are improved, the systems acquire a large amount of data, and the problem of acquiring the operation data of a motor transformer is solved.
Disclosure of Invention
The invention provides an intelligent optimization energy-saving system based on economic operation diagnosis and analysis, and solves the problems that various energy monitoring and management systems in the prior art cannot analyze economic operation characteristics of a motor and a transformer and give improvement suggestions to operation modes.
The technical scheme of the invention is realized as follows:
an intelligent optimization energy-saving system based on economic operation diagnosis and analysis comprises a data acquisition and storage module and an economic operation on-line analysis module,
the data acquisition and storage module is used for acquiring and storing real-time operation data, basic parameter data and historical operation data of the electric equipment,
the economic operation online analysis module establishes a characteristic analysis model according to real-time operation data, basic parameter data and historical operation data of the electric equipment, obtains the economic operation state of the electric equipment through the characteristic analysis model, and generates an energy-saving suggestion.
Further, the electric equipment comprises a motor, and the characteristic analysis model comprises a motor load characteristic analysis model, a motor energy consumption characteristic analysis model and a motor efficiency analysis model.
Further, the electric equipment comprises a transformer, and the characteristic analysis model comprises a transformer load characteristic analysis model, a transformer transmission electric energy characteristic analysis model and a transformer loss analysis model.
Further, the motor load characteristic analysis model obtains real-time active power P of the motor through the instrument, and obtains real-time load factor beta of the motor as P/P according to the real-time active power PNIn which P isNEstablishing a real-time load rate-time characteristic model of the motor, namely a beta-t curve, for the rated power of the motor;
the motor energy consumption characteristic analysis model obtains the comparative no-load loss of the motor according to the rated parameters of the motor
ΔP0＝30％*0.2*PN/PFav
Wherein, PNIs rated power, PF, of the motoravIs the rated power factor of the motor and,
obtaining rated load loss of the motor according to rated parameters of the motor
Figure BDA0003315342080000031
Wherein eta isNIn order to be able to provide the rated efficiency of the motor,
obtaining the real-time loss of the motor according to the real-time load rate of the motor, comparing the no-load loss with the rated load loss
ΔP＝ΔP0+β2(ΔPN-ΔP0)
Establishing a real-time loss-time delta P-t curve characteristic model of the motor;
the motor efficiency analysis model is based on a real-time loss-time curve characteristic model of the motor and according to the following formula
Figure BDA0003315342080000032
Obtaining the real-time efficiency eta of the motor, and establishing a characteristic model of the real-time efficiency-time eta-t curve of the motor;
judging the economic operation state of the motor according to the real-time efficiency eta of the motor:
if eta is greater than or equal to etaNIf so, the motor is in the optimal economic operation interval;
if etaN＞η≥0.6ηNIf so, the motor is in an economic operation interval;
if eta is more than 0 and less than 0.6 etaNIf the motor is in the non-economic operation interval;
and generating a motor energy-saving suggestion according to the real-time load rate-time curve characteristic model, the real-time loss-time curve characteristic model and the real-time efficiency-time curve characteristic model of the motor.
Further, the transformer load characteristic analysis model obtains real-time apparent power S of the transformer through an instrument to obtain real-time load rate beta of the transformer as S/SN，SNEstablishing a real-time load factor-time characteristic model of the transformer, namely a beta-t curve, for the rated capacity of the transformer,
calculating to obtain the optimal load rate of the transformer according to the rated parameters of the transformer and the operation characteristics of the transformer
Figure BDA0003315342080000041
Wherein, KτThe value of the load fluctuation loss coefficient of the transformer is 1.05,
P0Zcalculating formula P for the no-load loss of the comprehensive power of the transformer0Z＝P0+KQQ0In the formula P0For no load loss, KQThe value is 0.04 and Q for the reactive economic equivalent0Calculating formula Q for the no-load excitation power of the transformer0＝I0％SNX 0.01, wherein I0% is the percentage of the no-load current of the transformer,
PKZcalculating formula P for the power loss of the rated load of the integrated power of the transformerKZ＝PK+KQQKIn the formula PKFor rated load loss, KQThe value is 0.04 and Q for the reactive economic equivalentKCalculating formula Q for rated load leakage power of transformerK＝UK％SNX 0.01, wherein UK% is short circuit voltage percentage;
the transformer transmission electric energy characteristic analysis model acquires active power, reactive power and power factor of the transformer through an instrument, establishes a real-time active power, reactive power and power factor curve characteristic model of the transformer,
acquiring active electric quantity and reactive electric quantity of a transformer through an instrument, and establishing a real-time active electric quantity and reactive electric quantity curve characteristic model of the transformer;
the transformer loss analysis model is based on a real-time load factor-time curve characteristic model of the transformer and according to the following formula
ΔP＝P0+β2PN
Obtaining the real-time loss of the transformer, and establishing a real-time loss-time delta P-t curve characteristic model of the transformer;
and judging the economic operation state of the transformer according to the real-time load rate beta of the transformer:
if it is
Figure BDA0003315342080000051
The transformer is in the optimal economic operation interval;
if 1. gtoreq.beta.is greater than 0.75 or
Figure BDA0003315342080000052
The transformer is in an economic operation interval;
if it is
Figure BDA0003315342080000053
The transformer is in a non-economic operation interval;
and generating a transformer energy-saving suggestion according to the real-time load factor-time curve characteristic model of the transformer, the real-time active power, reactive power and power factor curve characteristic model of the transformer, the real-time active electric quantity and reactive electric quantity curve characteristic model of the transformer and the real-time loss-time curve characteristic model of the transformer.
The motor off-line economic operation analysis module acquires all historical operation data of the motor in the time period stored in the system according to the analysis time period selected by the user, judges the economic operation state of the motor through the motor load characteristic analysis model, the motor energy consumption characteristic analysis model and the motor efficiency analysis model, prompts the specific time period of non-economic operation in the operation time period, and generates a motor energy-saving suggestion.
The transformer offline economic operation analysis module acquires all historical operation data of the transformer in the time period stored in the system according to the analysis time period selected by the user, judges the economic operation state of the transformer through the transformer load characteristic analysis model, the transformer transmission electric energy characteristic analysis model and the transformer loss analysis model, prompts the specific time period of non-economic operation in the operation time period, and generates a transformer energy-saving suggestion.
The transformer single parallel operation analysis module reads historical operation data of the transformer after a user selects the analyzed transformer, if the transformer is currently in single-row operation, operation data of the transformer in each time period during parallel operation are obtained through simulation, if the transformer is currently in parallel operation, operation data of the transformer in each time period during independent operation are obtained through simulation, actual operation data and simulation data are compared, loss difference of the transformer in an actual mode and a simulation mode is obtained, and a switching suggestion of the parallel operation mode of the transformer is given.
Further, the motor energy-saving suggestion includes that the model and the capacity of the motor are changed, a variable-frequency speed regulation device of the motor is added, a voltage reduction and electricity saving device of the motor is added, and a reactive compensation device is added.
Further, the transformer energy-saving suggestion comprises the steps of adjusting the capacity of the transformer, adjusting the power factor of the transformer, adjusting the load size of the transformer in different time periods, changing the tap joint of the transformer and adding a reactive power compensation device.
The invention adopts the technical proposal to achieve the following beneficial effects:
(1) the intelligent optimization energy-saving system based on the economic operation diagnosis and analysis utilizes the real-time operation data, the basic parameter data and the historical operation data of the electric equipment collected and stored by the data collection and storage module to establish a motor load characteristic analysis model, a motor energy consumption characteristic analysis model, a motor efficiency analysis model, a transformer load characteristic analysis model, a transformer transmission electric energy characteristic analysis model and a transformer loss analysis model, carries out economic operation diagnosis on the motor and the transformer, finds the operation economy problems of the motor and the transformer, generates a diagnosis conclusion and provides an energy-saving improvement scheme, thereby expanding the energy-saving technology of the energy-saving system, increasing new energy-saving points and improving the energy-saving effect.
(2) The invention adopts a large amount of historical data and applies a big data algorithm to automatically diagnose the economic operation states of all monitored motors and transformers and directly generate energy-saving suggestions and schemes, thereby not only solving the problems of large quantity of motors and transformers, large calculated amount and large operation data measuring workload of enterprises, but also solving the problem of no professional in the enterprises without professional personnel.
(3) The system comprises an economic operation online analysis module and an economic operation offline analysis module, wherein the economic operation online analysis module is used for monitoring in real time, monitoring the heavy-duty equipment in real time and generating a diagnosis conclusion and an energy-saving suggestion scheme in time. The economic operation offline analysis module provides an analysis tool, historical data of the concerned motor and transformer can be analyzed one by one, a diagnosis conclusion and an energy-saving proposal scheme are obtained, and data and scheme reference is provided for energy-saving improvement of enterprises.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a block diagram of the present invention;
FIG. 2 is a block diagram of an online economic operation analysis module of the motor;
fig. 3 is a block diagram of a transformer online economic operation analysis module.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments of the present invention, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, an intelligent optimization energy-saving system based on economic operation diagnosis and analysis comprises a data acquisition and storage module, an economic operation on-line analysis module and an economic operation off-line analysis module,
the data acquisition and storage module is used for acquiring and storing real-time operation data, basic parameter data and historical operation data of the electric equipment, storing the data according to different time intervals and time sequences, and respectively storing the data in a real-time database, an equipment parameter configuration table and a historical database for calling the economic operation online analysis module and the economic operation offline analysis module.
The economic operation online analysis module establishes a characteristic analysis model according to real-time operation data, basic parameter data and historical operation data of the electric equipment, obtains the economic operation state of the electric equipment through the characteristic analysis model, and generates an energy-saving suggestion.
Referring to fig. 2, the electric device includes a motor, that is, the economic operation online analysis module includes a motor online economic operation analysis module, and the characteristic analysis model includes a motor load characteristic analysis model, a motor energy consumption characteristic analysis model, and a motor efficiency analysis model.
The motor online economic operation analysis module is used for acquiring data such as current, voltage, active power, reactive power, active electric quantity, reactive electric quantity and the like of a motor from a motor real-time database according to a set time interval for the motor which is set to be analyzed online, acquiring data such as rated power, rated efficiency, rated power factor and the like of the motor from a motor parameter configuration table, acquiring historical data such as active power, reactive power, active electric quantity, reactive electric quantity and the like of the motor from a motor historical database, and establishing a motor load characteristic analysis model, a motor energy consumption characteristic analysis model and a motor efficiency analysis model.
The motor load characteristic analysis model obtains real-time active power P of the motor through an instrument, and obtains real-time load factor beta of the motor as P/P according to the real-time active power PNIn which P isNEstablishing a real-time load rate-time characteristic model of the motor, namely a beta-t curve, for the rated power of the motor;
the motor energy consumption characteristic analysis model obtains the comparative no-load loss of the motor according to the rated parameters of the motor
ΔP0＝30％*0.2*PN/PFav
Wherein, PNIs rated power, PF, of the motoravIs the rated power factor of the motor and,
obtaining rated load loss of the motor according to rated parameters of the motor
Figure BDA0003315342080000081
Wherein eta isNIn order to be able to provide the rated efficiency of the motor,
obtaining the real-time loss of the motor according to the real-time load rate of the motor, comparing the no-load loss with the rated load loss
ΔP＝ΔP0+β2(ΔPN-ΔP0)
Establishing a real-time loss-time delta P-t curve characteristic model of the motor;
the motor efficiency analysis model is based on a real-time loss-time curve characteristic model of the motor and according to the following formula
Figure BDA0003315342080000091
Obtaining the real-time efficiency eta of the motor, and establishing a characteristic model of the real-time efficiency-time eta-t curve of the motor;
judging the economic operation state of the motor according to the real-time efficiency eta of the motor:
if eta is greater than or equal to etaNIf so, the motor is in the optimal economic operation interval;
if etaN＞η≥0.6ηNIf so, the motor is in an economic operation interval;
if eta is more than 0 and less than 0.6 etaNIf the motor is in the non-economic operation interval;
and diagnosing according to historical characteristics and results of the economic operation characteristics of the motor in the last day, judging non-economic operation and giving an alarm to obtain a conclusion whether the current motor is economical to operate, automatically generating an alarm when the current motor is not economical, and generating a motor energy-saving suggestion and scheme according to a real-time load rate-time curve characteristic model, a real-time loss-time curve characteristic model and a real-time efficiency-time curve characteristic model of the motor. The motor energy-saving proposal and the scheme comprise the steps of replacing the model and the capacity of the motor, adding a variable-frequency speed regulation device of the motor, adding a voltage-reducing and electricity-saving device of the motor, adding a reactive compensation device and the like.
Referring to fig. 3, the power consumption equipment includes a transformer, i.e., the economic operation online analysis module includes a transformer online economic operation analysis module, and the characteristic analysis model includes a transformer load characteristic analysis model, a transformer transmission power characteristic analysis model and a transformer loss analysis model.
The transformer online economic operation analysis module is used for acquiring data such as current, voltage, active power, reactive power, active electric quantity, reactive electric quantity, power factor and the like of a transformer from a transformer real-time database according to a set time interval for the transformer set to be analyzed online, acquiring data such as rated capacity, no-load loss, no-load current percentage, impedance voltage percentage and the like of the transformer from a transformer parameter configuration table, acquiring historical data such as active power, reactive power, active electric quantity, reactive electric quantity and the like of the transformer from a transformer historical database, and establishing a transformer load characteristic analysis model, a transformer transmission electric energy characteristic analysis model and a transformer loss analysis model.
The transformer load characteristic analysis model obtains the real-time apparent power S of the transformer through an instrument to obtain the real-time load rate beta of the transformer as S/SN，SNEstablishing a real-time load factor-time characteristic model of the transformer, namely a beta-t curve, for the rated capacity of the transformer,
calculating to obtain the optimal load rate of the transformer according to the rated parameters of the transformer and the operation characteristics of the transformer
Figure BDA0003315342080000101
Wherein, KτThe value of the load fluctuation loss coefficient of the transformer is 1.05,
P0Zcalculating formula P for the no-load loss of the comprehensive power of the transformer0Z＝P0+KQQ0In the formula P0For no load loss, KQThe value is 0.04 and Q for the reactive economic equivalent0Calculating formula Q for the no-load excitation power of the transformer0＝I0％SNX 0.01, wherein I0% is the percentage of the no-load current of the transformer,
PKZcalculating formula P for the power loss of the rated load of the integrated power of the transformerKZ＝PK+KQQKIn the formula PKFor rated load loss, KQThe value is 0.04 and Q for the reactive economic equivalentKCalculating formula Q for rated load leakage power of transformerK＝UK％SNX 0.01, wherein UK% is short circuit voltage percentage;
the transformer transmission electric energy characteristic analysis model acquires active power, reactive power and power factor of the transformer through an instrument, establishes a real-time active power, reactive power and power factor curve characteristic model of the transformer,
acquiring active electric quantity and reactive electric quantity of a transformer through an instrument, and establishing a real-time active electric quantity and reactive electric quantity curve characteristic model of the transformer;
the transformer loss analysis model is based on a real-time load factor-time curve characteristic model of the transformer and according to the following formula
ΔP＝P0+β2PN
Obtaining the real-time loss of the transformer, and establishing a real-time loss-time delta P-t curve characteristic model of the transformer;
and judging the economic operation state of the transformer according to the real-time load rate beta of the transformer:
if it is
Figure BDA0003315342080000113
The transformer is in the optimal economic operation interval;
if 1. gtoreq.beta.is greater than 0.75 or
Figure BDA0003315342080000111
The transformer is in an economic operation interval;
if it is
Figure BDA0003315342080000112
The transformer is in a non-economic operation interval;
and simultaneously, generating a transformer energy-saving suggestion and scheme according to a real-time load rate-time curve characteristic model of the transformer, a real-time active power curve characteristic model of the transformer, a real-time reactive power curve characteristic model of the transformer and a real-time loss-time curve characteristic model of the transformer. The transformer energy-saving proposal and scheme comprises the steps of adjusting the capacity of the transformer, adjusting the power factor of the transformer, adjusting the load size of the transformer in different time periods, changing the tap joint of the transformer, adding a reactive power compensation device and the like.
The economic operation offline analysis module comprises a motor offline economic operation analysis module, a transformer offline economic operation analysis module and a transformer single parallel operation analysis module.
The motor offline economic operation analysis module acquires all historical operation data of the motor in the time period, which are stored in the system, according to the analysis time period selected by the user, judges the economic operation state of the motor through the motor load characteristic analysis model, the motor energy consumption characteristic analysis model and the motor efficiency analysis model, prompts the specific time period in which the motor is in non-economic operation in the operation time period, and generates a motor energy-saving suggestion.
The transformer offline economic operation analysis module acquires all historical operation data of the transformer in the time period, which are stored in the system, according to the analysis time period selected by a user, judges the economic operation state of the transformer through the transformer load characteristic analysis model, the transformer transmission electric energy characteristic analysis model and the transformer loss analysis model, prompts the specific time period in which the transformer is in non-economic operation in the operation time period, and generates a transformer energy-saving suggestion.
The transformer single parallel operation analysis module reads historical operation data of the transformers after users select the analyzed transformers, if the transformers are currently in single-row operation, operation data of the transformers in each time period in parallel operation are obtained through simulation, if the transformers are currently in parallel operation, operation data of the transformers in each time period in independent operation are obtained through simulation, actual operation data and simulation data are compared, loss difference of the transformers in actual and simulation states is obtained, and a switching suggestion of the parallel operation mode of the transformers is given.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (10)

1. An intelligent optimization energy-saving system based on economic operation diagnosis and analysis is characterized by comprising a data acquisition and storage module and an economic operation on-line analysis module,
the data acquisition and storage module is used for acquiring and storing real-time operation data, basic parameter data and historical operation data of the electric equipment,
the economic operation online analysis module establishes a characteristic analysis model according to real-time operation data, basic parameter data and historical operation data of the electric equipment, obtains the economic operation state of the electric equipment through the characteristic analysis model, and generates an energy-saving suggestion.
2. The intelligent energy-saving optimization system based on economic operation diagnosis and analysis as claimed in claim 1, wherein the electric equipment comprises a motor, and the characteristic analysis model comprises a motor load characteristic analysis model, a motor energy consumption characteristic analysis model and a motor efficiency analysis model.
3. The intelligent energy-saving optimization system based on economic operation diagnosis and analysis as claimed in claim 1, wherein the electric equipment comprises a transformer, and the characteristic analysis model comprises a transformer load characteristic analysis model, a transformer transmission electric energy characteristic analysis model and a transformer loss analysis model.
4. The intelligent energy-saving optimization system based on economic operation diagnosis and analysis as claimed in claim 2, wherein the motor load characteristic analysis model obtains real-time active power P of the motor through a meter, and obtains real-time load factor β of the motor according to the real-time active power P＝P/PNIn which P isNEstablishing a real-time load rate-time characteristic model of the motor, namely a beta-t curve, for the rated power of the motor;
the motor energy consumption characteristic analysis model obtains the comparative no-load loss of the motor according to the rated parameters of the motor
ΔP0＝30％*0.2*PN/PFav
Wherein, PNIs rated power, PF, of the motoravIs the rated power factor of the motor and,
obtaining rated load loss of the motor according to rated parameters of the motor
Figure FDA0003315342070000021
Wherein eta isNIn order to be able to provide the rated efficiency of the motor,
obtaining the real-time loss of the motor according to the real-time load rate of the motor, comparing the no-load loss with the rated load loss
ΔP＝ΔP0+β2(ΔPN-ΔP0)
Establishing a real-time loss-time delta P-t curve characteristic model of the motor;
the motor efficiency analysis model is based on a real-time loss-time curve characteristic model of the motor and according to the following formula
Figure FDA0003315342070000022
Obtaining the real-time efficiency eta of the motor, and establishing a characteristic model of the real-time efficiency-time eta-t curve of the motor;
judging the economic operation state of the motor according to the real-time efficiency eta of the motor:
if eta is greater than or equal to etaNIf so, the motor is in the optimal economic operation interval;
if etaN＞η≥0.6ηNIf so, the motor is in an economic operation interval;
if eta is more than 0 and less than 0.6 etaNIf the motor is in the non-economic operation interval;
and generating a motor energy-saving suggestion according to the real-time load rate-time curve characteristic model, the real-time loss-time curve characteristic model and the real-time efficiency-time curve characteristic model of the motor.
5. The intelligent energy-saving optimization system based on economic operation diagnosis and analysis as claimed in claim 3, wherein the transformer load characteristic analysis model obtains real-time apparent power S of the transformer through a meter to obtain real-time load rate β ═ S/S of the transformerN，SNEstablishing a real-time load factor-time characteristic model of the transformer, namely a beta-t curve, for the rated capacity of the transformer,
calculating to obtain the optimal load rate of the transformer according to the rated parameters of the transformer and the operation characteristics of the transformer
Figure FDA0003315342070000031
Wherein, KτThe value of the load fluctuation loss coefficient of the transformer is 1.05,
P0Zcalculating formula P for the no-load loss of the comprehensive power of the transformer0Z＝P0+KQQ0In the formula P0For no load loss, KQThe value is 0.04 and Q for the reactive economic equivalent0Calculating formula Q for the no-load excitation power of the transformer0＝I0％SNX 0.01, wherein I0% is the percentage of the no-load current of the transformer,
PKZcalculating formula P for the power loss of the rated load of the integrated power of the transformerKZ＝PK+KQQKIn the formula PKFor rated load loss, KQThe value is 0.04 and Q for the reactive economic equivalentKCalculating formula Q for rated load leakage power of transformerK＝UK％SNX 0.01, wherein UK% is short circuit voltage percentage;
the transformer transmission electric energy characteristic analysis model acquires active power, reactive power and power factor of the transformer through an instrument, establishes a real-time active power, reactive power and power factor curve characteristic model of the transformer,
acquiring active electric quantity and reactive electric quantity of a transformer through an instrument, and establishing a real-time active electric quantity and reactive electric quantity curve characteristic model of the transformer;
the transformer loss analysis model is based on a real-time load factor-time curve characteristic model of the transformer and according to the following formula
ΔP＝P0+β2PN
Obtaining the real-time loss of the transformer, and establishing a real-time loss-time delta P-t curve characteristic model of the transformer;
and judging the economic operation state of the transformer according to the real-time load rate beta of the transformer:
if it is
Figure FDA0003315342070000041
The transformer is in the optimal economic operation interval;
if 1. gtoreq.beta.is greater than 0.75 or
Figure FDA0003315342070000042
The transformer is in an economic operation interval;
if it is
Figure FDA0003315342070000043
The transformer is in a non-economic operation interval;
and generating a transformer energy-saving suggestion according to the real-time load factor-time curve characteristic model of the transformer, the real-time active power, reactive power and power factor curve characteristic model of the transformer, the real-time active electric quantity and reactive electric quantity curve characteristic model of the transformer and the real-time loss-time curve characteristic model of the transformer.
6. The intelligent energy-saving optimization system based on economic operation diagnosis and analysis as claimed in claim 4, further comprising a motor offline economic operation analysis module, wherein the motor offline economic operation analysis module acquires all historical operation data of the motor in the period stored in the system according to the analysis time period selected by the user, judges the economic operation state of the motor through the motor load characteristic analysis model, the motor energy consumption characteristic analysis model and the motor efficiency analysis model, prompts a specific time period in which the motor is in non-economic operation in the operation period, and generates a motor energy-saving suggestion.
7. The intelligent energy-saving optimization system based on economic operation diagnosis and analysis as claimed in claim 5, further comprising a transformer offline economic operation analysis module, wherein the transformer offline economic operation analysis module acquires all historical operation data of the transformer in the period stored in the system according to the analysis period selected by the user, judges the economic operation state of the transformer through a transformer load characteristic analysis model, a transformer transmission electric energy characteristic analysis model and a transformer loss analysis model, prompts a specific time period of non-economic operation in the operation period, and generates a transformer energy-saving suggestion.
8. The intelligent energy-saving optimization system based on economic operation diagnosis and analysis as claimed in claim 1, further comprising a transformer single parallel operation analysis module, wherein the transformer single parallel operation analysis module reads historical operation data of the transformer after a user selects the analyzed transformer, if the transformer is currently in single-column operation, operation data of the transformer in each time period in parallel operation are obtained through simulation, if the transformer is currently in parallel operation, operation data of the transformer in each time period in independent operation are obtained through simulation, actual operation data and simulation data are compared, loss difference of the transformer in actual and simulation states is obtained, and a switching suggestion of the parallel operation mode of the transformer is given.
9. An intelligent energy-saving optimization system based on economic operation diagnosis and analysis as claimed in claim 6, wherein the motor energy-saving advice comprises the replacement of motor models and capacities, the addition of a motor variable frequency speed regulation device, the addition of a motor step-down power saver and the addition of a reactive power compensation device.
10. The intelligent energy-saving system based on economic operation diagnostic analysis according to claim 7, wherein the transformer energy-saving advice comprises adjusting transformer capacity, adjusting transformer power factor, adjusting load size of the transformer in different time periods, changing transformer taps, and adding reactive power compensation devices.
CN202111229136.6A 2021-10-21 2021-10-21 Intelligent optimization energy-saving system based on economic operation diagnosis and analysis Pending CN113972646A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116068396A (en) * 2023-03-29 2023-05-05 深圳市昱森机电有限公司 Method and related device for testing motor performance based on artificial intelligence
CN116111885A (en) * 2023-03-10 2023-05-12 苏州上舜精密工业科技有限公司 Rotating speed control method and system of brushless direct current motor

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116111885A (en) * 2023-03-10 2023-05-12 苏州上舜精密工业科技有限公司 Rotating speed control method and system of brushless direct current motor
CN116111885B (en) * 2023-03-10 2023-11-24 苏州上舜精密工业科技有限公司 Rotating speed control method and system of brushless direct current motor
CN116068396A (en) * 2023-03-29 2023-05-05 深圳市昱森机电有限公司 Method and related device for testing motor performance based on artificial intelligence
CN116068396B (en) * 2023-03-29 2023-06-20 深圳市昱森机电有限公司 Method and related device for testing motor performance based on artificial intelligence

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