CN104635684A - Cluster optimization control system for air compressor - Google Patents
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Abstract
The invention discloses a cluster optimization control system for an air compressor and belongs to the field of air-operated system energy saving. The cluster optimization control system comprises a data acquisition module, an air compressor energy consumption model, a pipeline network analysis and prediction module, an equipment operation analysis module, an optimization control module, four server-side modules and a client-side module; the data acquisition module is deployed on a data acquisition server; the four server-side modules are deployed on an application server; the client-side module is deployed on a client; the data acquisition server and the application server are connected through the Ethernet; the application server and the client are connected through the Ethernet; data information exchange is performed between the data acquisition module and the server-side module through inter-process message call; the data information exchange is performed between the data acquisition module and the server-side module through network message call; the client-side module is connected with the server-side module through a network message. The cluster optimization control system has the advantages that the cluster energy consumption of the air compressor is minimum under the condition that the demands of compressed air users change, and on the premise that the normal running of the air compressor equipment is ensured, the equipment efficiency is increased, the service life of the equipment is prolonged, energy consumption can be reduced to a certain degree, and the production running cost is reduced.
Description
Technical Field
The invention belongs to the field of energy conservation of pneumatic systems, and particularly provides an air compressor cluster optimization control system which analyzes air compressor equipment on line and provides a cluster optimization control method.
Background
In modern large industrial enterprises, compressed air is the second largest power source next to electricity. With the increasing shortage of energy sources, enterprises have built centralized air compression stations or system transformation to realize centralized monitoring of air compressors of whole plants, and to a certain extent, the stability of a compressed air pipe network is improved, but the loss rate of the pipe network is still high, and the unit consumption still has a reduced space.
In a master control room of a centralized air compressor station or an enterprise energy operation center, the optimization control is realized by centralized monitoring of all air compressor equipment, real-time alarming can be carried out on original monitoring data, trend analysis and fault analysis can be carried out on historical data, remote start-stop control of the air compressor equipment can be realized, and the like. However, factors such as the service life of the air compressor, energy consumption in the start-stop stage and the like are not considered in the control, and the demand change of a compressed air user is not considered from the system perspective, so that the adjustment of the operation mode of the air compressor cluster is too lagged.
Patent air compressor group energy-saving control system (CN101042580, a patent) applied by Kun mountain energy science and technology service Limited company published in 2012, 06, discloses an air compressor group energy-saving control system in an industrial pneumatic system, which can monitor the parameters of a pipe network and an air compressor group in an air compressor station in real time, perform optimization control and display alarm, and realize comprehensive management on the whole air compressor system. The defect of the patent is that the influence of factors such as a compressed air pipe network, air compressor equipment maintenance and the like is not considered in the optimization control method.
Most of the optimization control patents related to the air compressor group are focused on centralized monitoring of the air compressor group, deep mining of real-time monitoring data is lacked, and most of the cluster control schemes rarely consider the influence of compressed air pipe network balance.
The existing air compressor cluster control system, if used for large-scale industrial enterprises with many compressed air users, has the following disadvantages: firstly, the monitoring and loss analysis of the pressure flow of the whole compressed air pipe network are lacked, the production plan information is lacked, and the capacity of responding to the change of the demand is poor; secondly, the energy efficiency analysis of the operation of the air compressor equipment is lacked, the maintenance plan information of the air compressor equipment is lacked, and the performability of the cluster optimization control scheme is poor; and thirdly, an air compressor operation model and a cluster optimization control model are lacked, and the control scheme is difficult to ensure that all constraints are met and the optimization is realized.
Disclosure of Invention
The invention aims to provide an air compressor cluster optimization control system, which solves the three defects of the background technology, realizes the minimum energy consumption of an air compressor cluster under the condition of meeting the requirement change of a compressed air user, improves the equipment efficiency and prolongs the equipment service life on the premise of ensuring the normal operation of air compressor equipment, and can reduce the energy consumption and save the production and operation cost to a certain extent.
Technical scheme of the invention
The system comprises a data acquisition module, an air compressor energy consumption model, a pipe network analysis and prediction module, an equipment operation analysis module, an optimization control module, 4 server-side modules and a client-side module; the data acquisition module is deployed on a data acquisition server, the 4 server-side modules are deployed on an application server, and the client-side module is deployed on a client; the data acquisition server is connected with the application server through the Ethernet, and the application server is connected with the client through the Ethernet. The 4 server-side modules exchange data information through interprocess message calling, the data acquisition module and the server-side module exchange data information through network message calling, and the client-side module is connected with the server-side module through network message. As shown in fig. 1. The specific functions of each module are as follows:
a data acquisition module: the data required by the system comprises production operation data of the air compressor cluster, flow/pressure data of each user on the compressed air pipeline, production plan data of the user and maintenance plan data of the air compressor cluster. The data acquisition module is responsible for acquiring the four data, the first two data are acquired in real time according to an interface provided by a system (such as a monitoring system, an ERP system and the like) where the data acquisition module is located, integral operation can be carried out on data points with only instantaneous flow to obtain hour accumulated flow, the second two data can be acquired periodically or triggered to be acquired, and the data are stored in a historical database to support Oracle, SQL Server, text files and the like.
The energy consumption model of the air compressor: establishing an energy consumption model for each air compressor in the cluster, wherein the energy consumption model comprises an air compressor power consumption piecewise function and a minimum exhaust pressure function, and the specific modeling process comprises the following steps:
in a certain period T, the average gas production speed of the jth air compressor of the ith air compressor station is
1) Calculating the power consumption WijWhen the air compressor is in different working states (starting, loading and unloading), the power consumption is different, the calculation modes are different, and the relation between the power consumption and the average gas production speed when the power consumption is loaded is fitted by a mathematical statistics methodThus, it is possible to provide
Wherein, for an air compressor, WKi ijAnd WUnload ijThe basic fixed value can be obtained by integrating and calculating the input power (or current and voltage).
2) Fitting gas production speed v by using mathematical statistical methodijWith minimum exhaust pressure pNull ijIs ofij：
pNull ij＝φij(vij)
The air compressor energy consumption model is mainly used for total gas production amount prediction and cluster optimization control scheme formulation.
Pipe network analysis and prediction module: the system comprises functions of compressed air pipe network monitoring and alarming, loss analysis and total demand prediction, and mainly analyzes the use condition of compressed air so as to obtain the actual performance value and the predicted value of the total demand of the compressed air.
The instantaneous flow and pressure of each user air inlet point on the compressed air pipe network are monitored in a centralized manner, and scheduling personnel are reminded with different sounds or flashes when the instantaneous flow and pressure exceed an early warning value/an alarm value; automatically calculating the total generation F of compressed air according to the instantaneous flow information of the air compressor station and the pipe networkHair-like deviceTotal demand F of userNeed toLoss of pipe network FLoss of powerThe formula is as follows:
wherein, FBy kRepresenting the consumption of the kth user, allowing the pipe network to have a certain dynamic unbalance FLoss of powerWhen F isLoss of powerWhen the alarm value exceeds the early warning value, the prompt is given in the forms of flashing, sound and the like. And analyzing the leakage point of the pipe network by combining the flow and pressure information of each measuring point, and generating a report and informing related personnel or departments of processing in time.
Predicting the consumption of r users by combining the production plan of each user and the historical information of the consumption of the compressed air, and further obtaining the predicted value of the total demand of the compressed air
Wherein, the predicted value of the k userThe mechanism-time series model is adopted, the time series model is used during normal user production, parameters of the time series model can be corrected on line, and the mechanism model is adopted and experience data is used for correction when consumption changes caused by production increase, production reduction, halt and the like exist in production plan information of a user.As one input to the cluster optimization control module.
The equipment operation analysis module: the method mainly analyzes key parameters of the operation of the air compressor and provides an early warning function; predicting the running state of the air compressor in a period of time in the future by combining the maintenance plan and the current state of the equipment; calculating the actual average specific power eta of each air compressor by combining the power consumption and the gas production of each air compressorijThe formula is as follows：
ηij＝Wij/Fij
And a corresponding maintenance plan can be made according to the change of the specific power.
Regulating and controlling priority operation is carried out by combining air compressor starting, loading and unloading energy consumption information, the running state of the equipment in a future period of time, specific power and the like, and the equipment state is provided for the cluster optimization control module;
an optimization control module: when the total demand of compressed air changes or the air compressor needs to be overhauled, a multi-period air compressor operation mode is formulated, wherein the priority of air compressor allocation is determined by an air compressor model, an overhaul plan and specific power. The air compressor cluster optimization control scheme obtained by the system can be operated and executed by a dispatcher through a auditor of a professional engineer. The core part of the optimization control module is to establish a multi-period optimization distribution model and solve the model, and the modeling process is as follows:
the method comprises the following steps: dividing the whole optimization cycle into a plurality of sub-cycles according to a production plan of a user, so that the total demand in each cycle is a fixed value and the total demands in two adjacent sub-cycles are different, and in the nth sub-cycle to be optimized, establishing an objective function by taking the minimum energy consumption, namely the minimum power consumption, of all air compressors as a target:
when the air compressor is loaded, the power consumption can be expressed as a function of the displacement, and the above equation becomes
Step two: establishing necessary constraints including:
1) and (3) equipment condition constraint: obtaining the state s of each air compressor in the sub-period according to the equipment maintenance planij，
The air compressor can supply compressed air during loading, and the operation mode of the air compressor is a full-load or energy-saving mode; the compressed air can not be provided in other states, and all the states consume electricity;
2) supply and demand balance constraint:
wherein,is the estimated loss amount of the pipe network, and (i, j) belongs to {(s)ij＝1)}；
3) And (3) pressure restraint: i.e. the minimum discharge pressure of all air compressors in the cluster is greater than the maximum pressure on the user side,
step three: obtaining the dispatching priority of the air compressors in the cluster through an equipment maintenance plan, the actual performance specific power of the air compressors, an energy consumption model of the air compressors and the current operation state;
step four: solving by using an improved genetic algorithm to obtain the operation mode, the average gas production speed, the minimum exhaust pressure and the total power consumption of the cluster of each air compressor in the sub-period; the optimizing process is divided into 2 stages, wherein firstly, the operating state of the air compressors is not changed as much as possible, the gas production rate of each air compressor is adjusted through a frequency converter, and secondly, under the condition that the requirement of a user cannot be met or the compressed air supply is far larger than the requirement, the standby air compressor is started or the operated air compressor is unloaded for adjustment;
step five: and summarizing the operation modes of the air compressors of all the sub-periods to form an air compressor cluster optimization control scheme of the whole period.
In the cluster optimization control process, the air compressor cluster optimization control scheme generated by the system needs to be audited by a professional engineer, and if the audit is not passed, the optimization distribution model needs to be solved again until the scheme is feasible and can be output to be executed by a dispatcher.
A client module: the method comprises the functions of compressed air pipe network flow/pressure, air compressor equipment operation monitoring and alarming, production plan query, equipment maintenance plan query, air compressor regulation and control priority query and manual adjustment, an air compressor energy consumption model, cluster optimization control scheme interaction and output, optimization control scheme execution and the like.
THE ADVANTAGES OF THE PRESENT INVENTION
The method comprises the steps of calculating the loss of a compressed air pipe network in real time, periodically obtaining a production plan of a user side and the change of the total demand of compressed air, striving for time for adjusting the operation mode of an air compressor, and effectively reducing the emptying capacity of the compressed air pipe network;
secondly, establishing an air compressor energy consumption model, and providing accurate theoretical data for air compressor cluster optimization control;
thirdly, the regulation and control priority of the air compressor is calculated based on the maintenance plan, the current operation state and the energy consumption model of the air compressor, so that the feasibility of a cluster optimization control scheme is enhanced;
according to the cluster optimization control scheme, two factors of user demand change and air compressor equipment operation are fully considered, pre-adjustment of the cluster air compressor can be achieved, the stability of an air compressor pipe network is enhanced, electric power energy consumption is reduced, and energy cost is saved.
Drawings
FIG. 1 is a system block diagram of the present invention.
FIG. 2 is a flow chart of a system generating a cluster optimization control scheme.
Detailed Description
The system comprises a data acquisition module, an air compressor energy consumption model, a pipe network analysis and prediction module, an equipment operation analysis module, an optimization control module, 4 server modules and a client module, wherein the relation among the modules is as follows: the 4 server-side modules exchange data information through interprocess message calling, the data acquisition module and the server-side module exchange data information through network message calling, and the client-side module is connected with the server-side module through network message. As shown in fig. 1.
The implementation process of the invention is described by taking the air compressor cluster optimization control of a certain enterprise as an example. The enterprise is provided with 4 centralized air compression stations and more than 30 air compressors, the average power consumption of compressed air is 0.1219m3/kwh, the loss rate of a pipe network is 10.8%, and the air compressors need to be subjected to cluster optimization control due to numerous users on the compressed air pipe network, so that the power consumption is reduced and the energy cost is saved under the condition that the user requirements are met. The specific operation steps are as follows:
the first step is as follows: according to the production process of the enterprise, the information of a compressed air pipe network, users and air compressors, scheduling rules of air compressor stations and the like are collected. The deployment requirements of the system are as follows: deploying a data acquisition module on a computer capable of providing a process data interface; the air compressor energy consumption model, the pipe network analysis and prediction module, the equipment operation analysis module and the optimization control module are arranged on a computer, and the data acquisition module is connected through a network; the client module is deployed on a computer where the monitoring system client is located, and is ensured to be connected with 4 service modules through a network.
The second step is that: in the example, the monitoring system established by the centralized air compressor station provides equipment information of the air compressor station, real-time current, gas production speed, running state and the like of each air compressor; and the ERP system provides a main production plan of a user and an equipment maintenance plan of the air compressor. According to the interfaces provided by the two systems, a data acquisition program is applied to acquire the data into a historical database, and an SQL Server database is selected;
the third step: establishing an energy consumption model for each air compressor, and calculating starting power consumption, starting time, unloading power consumption and unloading time according to historical operating data; fitting the relation between the power consumption and the average gas production rate in a loading state; fitting the relation between the gas production speed and the minimum exhaust pressure;
the fourth step: monitoring the flow and pressure of each user on the compressed air pipe network in real time, dynamically calculating the total generation amount, the total demand amount and the pipe network loss, and reminding a dispatcher in forms of flashing, sound and the like when any data index exceeds an early warning value/an alarm value; predicting the consumption of the compressed air by the production plan of each user according to the characteristics of the consumption of the compressed air, and further predicting the total demand of the compressed air;
the fifth step: carrying out early warning, alarming and monitoring on key parameters in the operation of the air compressor; counting the specific power of each air compressor; adjusting the compressed air dispatching priority according to parameters such as the maintenance plan, the current running state, the specific power and the like of the air compressor;
and a sixth step: according to the total demand change, the equipment maintenance plan and the like in the fourth step and the fifth step, the system automatically and repeatedly optimizes through the optimization control module and interacts with a professional engineer to obtain an executable air compressor cluster optimization control scheme;
the seventh step: at a client of the system, the operation conditions and alarm information of a compressed air pipe network and air compressor equipment can be inquired in real time, index parameters such as pipe network loss, compressed air power consumption and air compressor specific power can be inquired, an air compressor regulation and control priority and an energy consumption model can be inquired, an air compressor cluster optimization control scheme can be executed, and the like.
Through implementing this system of operation at this enterprise, the production operation condition of compressed air system has obviously improved, because can carry out the preliminary adjustment according to the plan, has strengthened the stability of compressed air pipe network for the average power consumption of compressed air, pipe network loss rate index decline.
The invention can be applied to industrial enterprises which are built with centralized air compressor stations and compressed air pipe networks, is beneficial to improving the operation stability of the compressed air pipe networks, reducing the power consumption of the air compressor stations and saving the energy cost.
Claims (3)
1. The utility model provides an air compressor machine cluster optimal control system which characterized in that: the system comprises a data acquisition module, an air compressor energy consumption model, a pipe network analysis and prediction module, an equipment operation analysis module, an optimization control module, 4 server-side modules and a client-side module; the data acquisition module is deployed on a data acquisition server, the 4 server-side modules are deployed on an application server, and the client-side module is deployed on a client; the data acquisition server is connected with the application server through the Ethernet, and the application server is connected with the client through the Ethernet. The 4 server-side modules exchange data information through interprocess message calling, the data acquisition module and the server-side module exchange data information through network message calling, and the client-side module is connected with the server-side module through network message; the functions of the modules are as follows:
a data acquisition module: the data required by the system comprises production operation data of the air compressor cluster, flow/pressure data of each user on the compressed air pipeline, production plan data of the user and maintenance plan data of the air compressor cluster; the data acquisition module is responsible for acquiring the four data, the first two data are acquired in real time according to an interface provided by a system where the data acquisition module is located, integral operation can be carried out on data points only with instantaneous flow to obtain hour accumulated flow, the second two data can be acquired periodically or triggered to be acquired, and are stored in a historical database to support Oracle, SQL Server and text files;
the energy consumption model of the air compressor: establishing an energy consumption model for each air compressor in the cluster, wherein the energy consumption model comprises an air compressor power consumption piecewise function and a minimum exhaust pressure function; the method is used for total gas production amount prediction and cluster optimization control scheme formulation;
pipe network analysis and prediction module: the system comprises functions of compressed air pipe network monitoring and alarming, loss analysis and total demand prediction, wherein the functions are used for analyzing the use condition of compressed air so as to obtain an actual performance value and a predicted value of the total demand of the compressed air; the instantaneous flow and pressure of each user air inlet point on the compressed air pipe network are monitored in a centralized manner, and when the instantaneous flow and pressure exceed the early warning value/alarm value, scheduling personnel are reminded by different sounds or flashes, so that the total generation amount, the total demand amount and the pipe network loss of the compressed air pipe network are calculated; the predicted value of the compressed air of each user adopts a mechanism-time series model, the time series model is used during normal user production, the parameters of the time series model can be corrected on line, the mechanism model is adopted when the consumption changes caused by production increase, production reduction, shutdown and the like in the production plan information of the user, and the empirical data is used for correction;
the equipment operation analysis module: analyzing key parameters of the operation of the air compressor and providing an early warning function; predicting the running state of the air compressor in a period of time in the future by combining the maintenance plan and the current state of the equipment; calculating the actual average specific power of each air compressor by combining the power consumption and the gas production rate of each air compressor; regulating and controlling priority operation is carried out by combining the starting, loading and unloading energy consumption information of the air compressor, the running state of the equipment in a period of time in the future and the specific power, and the equipment state is provided for the cluster optimization control module;
an optimization control module: when the total demand of compressed air changes or the air compressor needs to be overhauled, a multi-period air compressor operation mode is formulated, wherein the priority of air compressor allocation is determined by an air compressor model, an overhaul plan and specific power; the air compressor cluster optimization control scheme obtained by the system needs to be operated and executed by a dispatcher through a professional engineer auditor; in the cluster optimization control flow, the air compressor cluster optimization control scheme generated by the system needs to be audited by a professional engineer, if the audit is not passed, the optimization distribution model needs to be solved again until the feasible side of the scheme is output and handed to a dispatcher for execution;
a client module: the method comprises the functions of compressed air pipe network flow/pressure, air compressor equipment operation monitoring and alarming, production plan query, equipment maintenance plan query, air compressor regulation and control priority query and manual adjustment, an air compressor energy consumption model, cluster optimization control scheme interaction and output, optimization control scheme execution and the like;
2. the air compressor machine cluster optimizing control system of claim 1, characterized in that: the modeling process of the air compressor energy consumption model is as follows:
in a certain period T, the average gas production speed of the jth air compressor of the ith air compressor station is
1) Calculating the power consumption WijWhen the air compressor is in different working states (starting, loading and unloading), the power consumption is different, the calculation modes are different, and the relation between the power consumption and the average gas production speed when the power consumption is loaded is fitted by a mathematical statistics methodThus, it is possible to provide
Wherein, for an air compressor, WKi ijAnd WUnload ijBasically, a fixed value can be obtained by integrating and calculating the input power (or current and voltage);
2) fitting gas production speed v by using mathematical statistical methodijWith minimum exhaust pressure pNull ijIs ofij：
pNull ij＝φij(vij)。
3. The air compressor machine cluster optimizing control system of claim 1, characterized in that: the core part of the optimization control module is to establish a multi-period optimization distribution model and solve the model, and the specific steps are as follows:
the method comprises the following steps: dividing the whole optimization cycle into a plurality of sub-cycles according to a production plan of a user, so that the total demand in each cycle is a fixed value and the total demands in two adjacent sub-cycles are different, and in the nth sub-cycle to be optimized, establishing an objective function by taking the minimum energy consumption, namely the minimum power consumption, of all air compressors as a target:
when the air compressor is loaded, the power consumption can be expressed as a function of the displacement, and the above equation becomes
Step two: establishing necessary constraints including:
1) and (3) equipment condition constraint: obtaining the state s of each air compressor in the sub-period according to the equipment maintenance planij，
The air compressor can supply compressed air during loading, and the operation mode of the air compressor is a full-load or energy-saving mode; the compressed air can not be provided in other states, and all the states consume electricity;
2) supply and demand balance constraint:
wherein,is the estimated loss amount of the pipe network, and (i, j) belongs to {(s)ij＝1)}；
3) And (3) pressure restraint: i.e. the minimum discharge pressure of all air compressors in the cluster is greater than the maximum pressure on the user side,
step three: obtaining the dispatching priority of the air compressors in the cluster through an equipment maintenance plan, the actual performance specific power of the air compressors, an energy consumption model of the air compressors and the current operation state;
step four: solving by using an improved genetic algorithm to obtain the operation mode, the average gas production speed, the minimum exhaust pressure and the total power consumption of the cluster of each air compressor in the sub-period; the optimizing process is divided into 2 stages, wherein firstly, the operating state of the air compressors is not changed as much as possible, the gas production rate of each air compressor is adjusted through a frequency converter, and secondly, under the condition that the requirement of a user cannot be met or the compressed air supply is far larger than the requirement, the standby air compressor is started or the operated air compressor is unloaded for adjustment;
step five: and summarizing the operation modes of the air compressors of all the sub-periods to form an air compressor cluster optimization control scheme of the whole period.
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Cited By (36)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN105736344A (en) * | 2016-04-07 | 2016-07-06 | 红云红河烟草(集团)有限责任公司 | Air compressor unit optimal control system |
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| CN109164704A (en) * | 2018-08-07 | 2019-01-08 | 大连理工大学 | A kind of air compressor machine group Optimization Scheduling based on mixed model |
| CN109002005A (en) * | 2018-08-15 | 2018-12-14 | 江南大学 | A kind of intelligent pneumatic data acquisition control terminal |
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