CN111832859A - Intelligent optimization energy-saving system based on industrial production line management synchronous optimization and accurate management and control - Google Patents

Abstract

The invention relates to an intelligent optimization energy-saving system based on synchronous optimization and accurate management and control of industrial production line management, which comprises: the system comprises a data acquisition and storage module, a comparison analysis module, a load analysis module, an alarm early warning module, an associated equipment linkage analysis module, an electric charge structure analysis module, an abnormal startup and shutdown module and a balance analysis module; the comparison analysis module, the load analysis module, the alarm early warning module, the associated equipment linkage analysis module, the electric charge structure analysis module, the abnormal startup and shutdown module and the balance analysis module are all connected with the data acquisition and storage module. The intelligent optimization energy-saving system provided by the embodiment of the invention utilizes the energy data, the production data and the process data of the data acquisition and storage module to establish various management optimization analysis modules. Various production data and energy data of enterprises are analyzed through the analysis modules, refinement and automation of production management are achieved, and direct conclusions and data are provided for accurate management and control of a production line, energy conservation and consumption reduction.

Description

Intelligent optimization energy-saving system based on industrial production line management synchronous optimization and accurate management and control

Technical Field

The invention belongs to the technical field of energy management and energy conservation, and particularly relates to an intelligent optimization energy-saving system based on synchronous optimization and accurate management and control of industrial production line management.

Background

Currently, the problems of energy shortage and environmental pollution become global problems, and in energy consumption of China, industry is a big household of energy consumption of China, the energy consumption accounts for about 70% of the total energy consumption of China, and energy conservation and environmental protection become increasingly concerned problems of the whole society. The traditional high-consumption and extensive industrial control management development road of energy resources is difficult to follow, the traditional economic growth mode with high consumption, high pollution and low benefit is changed, and a novel clean production road which aims at using an intelligent production system as a support and using resource-saving circular economy with low consumption, low emission and high efficiency is developed is urgent.

At present, most enterprises are low in informatization application degree, the energy management level is relatively extensive, the energy consumption condition is monitored and counted in a manual mode, and the accuracy of data statistics and analysis is poor. Many manufacturers provide energy consumption online monitoring systems and energy management center system software, and such software products can basically solve the problems of energy consumption monitoring and energy consumption statistics, but cannot effectively analyze various data of enterprises fundamentally to obtain relevant conclusions of energy conservation and consumption reduction or guarantee of stable operation of production lines. From the viewpoint of production management, such a system still does not solve the following problems of the production line:

(1) and multi-dimensional comparative analysis among different objects is lacked, and differences of energy consumption are searched. For example, the energy consumption of different teams is not compared and analyzed, and then the difference of the energy consumption of the teams is found; the links that the energy consumption and the output of a plurality of production lines are mutually compared and the main factors restricting the production or the energy consumption is relatively high are searched for are lacked; and the energy consumption data comparison between the devices with acquainted working conditions is lacked, and whether the energy consumption difference exists is searched.

(2) Potential problems cannot be found without the necessary data analysis. For example: the change of the operation data of the production equipment is not analyzed, and the abnormal trend of the operation data cannot be found in time.

(3) The running states of all equipment in the whole plant cannot be controlled by a certain area, and a hidden energy-saving space is difficult to find. The problems are the most obvious and ubiquitous problems, generally, hundreds of equipment and dozens of small to hundreds of process links are arranged on an industrial production site, attention is not high for some hidden equipment or process links or non-key links which do not affect production, and considerable energy-saving optimization space is usually reserved in the links.

(4) Whether the established process management system is effectively executed or not cannot be determined in a convenient and fast manner. After enterprises make production management systems, whether the systems are put into place or not needs manpower to be paid to supervise, but people cannot monitor the systems on site all the time, so that the management systems cannot be accurately put into place.

Disclosure of Invention

In order to solve the technical problem that various types of data of enterprises are not analyzed effectively fundamentally, the embodiment of the invention provides an intelligent optimization energy-saving system based on synchronous optimization and accurate management and control of industrial production line management.

An intelligent optimization energy-saving system based on industrial production line management synchronous optimization and accurate management and control comprises: the system comprises a data acquisition and storage module, a comparison analysis module, a load analysis module, an alarm early warning module, an associated equipment linkage analysis module, an electric charge structure analysis module, an abnormal startup and shutdown module and a balance analysis module; the comparison analysis module, the load analysis module, the alarm early warning module, the associated equipment linkage analysis module, the electric charge structure analysis module, the abnormal startup and shutdown module and the balance analysis module are all connected with the data acquisition and storage module;

the data acquisition and storage module is used for acquiring and storing data, and the stored data comprises the acquired data and data generated by the comparison analysis module, the load analysis module, the alarm early warning module, the associated equipment linkage analysis module, the electric charge structure analysis module, the abnormal startup and shutdown module and the balance analysis module;

the comparison analysis module is used for carrying out multi-dimensional comparison on the data in the data acquisition and storage module to find difference points under various conditions;

the load analysis module is used for analyzing the distribution of the load in time, the maximum load time, the maximum demand and the maximum demand time by utilizing the real-time data acquired by the data acquisition and storage module and historical data formed by processing the real-time data according to a set rule;

the alarm early warning module is used for processing and analyzing the real-time data acquired by the data acquisition and storage module to obtain data related to safe operation and economic operation and carrying out corresponding early warning or alarm;

the associated equipment linkage analysis module is used for monitoring the running state of the associated equipment in real time according to the data from the data acquisition and storage module and judging whether the potential safety interlock hazard and the idling phenomenon of the equipment occur or not according to the preset logic condition; automatically counting the idle time of equipment in a certain period and a working section and the data of waste electric quantity; carrying out comparison analysis on the data of equipment idle time and waste electric quantity in a same ratio, a ring ratio and a team target value;

the electric charge structure analysis module is used for displaying electric charge composition details according to the user electricity consumption data acquired from the data acquisition and storage module, setting monitoring related data indexes and reminding a user to adopt a corresponding control mode; analyzing the user electricity charge data, searching unreasonable conditions in the actual electricity charge of the user, and positioning corresponding electricity utilization areas and time; analyzing the constitution of the user electricity fee and the relation between each project and production operation data;

the abnormal startup and shutdown module is used for judging the running state of the host of each section of the production line in real time according to the data in the data acquisition and storage module, and judging whether the host equipment produces within a specified time period or stops producing within the specified time period according to the specified startup-allowed time period and shutdown-allowed time period of a production system or a production plan;

and the balance analysis module is used for analyzing various links of generation, transmission, distribution and consumption of various energy sources according to the data in the data acquisition and storage module and the supply and demand balance.

Furthermore, the comparison analysis module comprises a team comparison analysis submodule, a standard value comparison analysis submodule, a production line comparison analysis submodule and a same-working-condition equipment comparison analysis submodule;

the team comparison and analysis module is used for comparing the two teams, finding out difference points between the teams, analyzing the difference points and searching for difference reasons;

the standard value comparison analysis module is used for comparing and analyzing the index value and the standard value to find out the difference between the index value and the standard value;

the production line contrasts and analyzes the module and is used for contrasting each production index and energy consumption index of two similar production lines, analyzing the deviation of each index, and analyzing whether the deviation is in the normal range:

and the equipment comparison and analysis module under the same working condition is used for performing comparison and analysis on the equipment under the same working condition.

Further, the specific process of the team comparison analysis module includes:

step S1111: selecting a comparison time period and two teams for comparison, and acquiring information of the two teams in the time period from the data acquisition and storage module;

step S1112: respectively calculating the unit consumption of each team according to the acquired information of the two teams, and comparing the difference amplitude of the unit consumption of the two teams obtained through calculation;

step S1113: judging whether the difference amplitude is within a set range, if so, outputting a conclusion 1, wherein the conclusion 1 shows that the difference of the unit consumptions of the two teams is small; if the process energy consumption data of the two teams is not in the set range, analyzing the energy consumption difference and the unit consumption difference of the corresponding processes of the two teams according to the process energy consumption data of the two teams, finding out the process with larger energy consumption difference and unit consumption difference, analyzing the difference of each hour, and outputting a conclusion 2, wherein the conclusion 2 comprises the following steps: the three processes with the largest difference of unit consumption and energy consumption and the three processes with the largest difference of unit consumption and the occurrence time of the two teams and groups.

Further, the specific process of the standard value comparison analysis module includes:

step S1121: selecting conditions of contrastive analysis, wherein the conditions comprise contrastive analysis time and index name;

step S1122: acquiring index data from the data acquisition and storage module, wherein the index data comprises energy consumption data and production data necessary for calculating an index value and also comprises standard value data of a specific index;

step S1123: calculating a corresponding index value according to the index formula and the acquired index data;

step S1124: judging whether the calculated index value is in a normal range specified by a corresponding standard value, and if the index value is in the normal range specified by the corresponding standard value, prompting that the index value is normal; if the index value is not in the normal range specified by the corresponding standard value, displaying that the index value is not in the normal range; and if the compared standard value is the optimal value, displaying the core process parameter corresponding to the index value and the core process parameter corresponding to the optimal value.

Further, the specific process of the production line comparison analysis module includes:

step S1131: acquiring basic data of a first production line and a second production line from the data acquisition and storage module, wherein the first production line and the second production line adopt the same production process and two different production lines for producing the same product, and the basic data is used for calculating various indexes of the production lines;

step S1132: calculating various indexes of the first production line and the second production line;

step S1133: comparing the difference values of the corresponding indexes obtained by calculation;

step S1134: outputting a conclusion, if the difference value of the indexes is in the normal range, outputting a conclusion that the indexes of the production line are compared with normal; if the difference of the indexes exceeds the normal range, outputting the conclusion that the indexes are compared with the positions of abnormal and problematic production links.

Further, the specific process of the module for comparing and analyzing the same-working-condition equipment comprises the following steps:

step S1141: acquiring data of equipment under the same working condition from the data acquisition and storage module, and calculating equipment data, wherein the equipment data comprises average power, real-time current and running trend;

step S1142: displaying corresponding equipment data;

step S1143: outputting a comparison conclusion, and if the difference value of the equipment data of the equipment under the same working condition is within a certain threshold range, outputting a conclusion that the equipment under the same working condition is normally compared; and if the difference value of the data equipment exceeds the threshold range, outputting a conclusion that the comparison with the working condition equipment is abnormal.

Further, the specific process of the load analysis module includes:

step S121: selecting an analysis time and an analysis object;

step S122: obtaining yield data and energy consumption data from the data acquisition and storage module;

step S123: displaying an energy consumption trend and a yield trend;

step S124: displaying the maximum load, the maximum demand, the maximum load time and the maximum demand time;

step S125: and (5) giving a conclusion of adjusting production and optimizing load.

Further, the specific process of the alarm early warning module includes:

step S131: real-time data of a production field is collected through the data collecting and storing module, and the real-time data comprises electric quantity data and non-electric quantity data;

step S132: setting an alarm upper limit value and an alarm lower limit value for the real-time data, namely setting a real-time overrun alarm condition; meanwhile, setting real-time fluctuation abnormal alarm conditions for the load which runs stably under normal conditions;

step S133: judging whether a real-time overrun alarm condition and a real-time fluctuation abnormal alarm condition are met in real time according to the acquired real-time data;

step S134: carrying out early warning or alarming on the real-time data meeting the real-time overrun alarming condition and/or the real-time fluctuation abnormal alarming condition, and displaying reasons;

step S135: processing the real-time data to form historical data, setting a historical data overrun alarm condition and a historical data change trend early-warning alarm condition, carrying out early warning or alarming when the historical data overrun alarm condition and the historical data change trend early-warning alarm condition are met, and displaying reasons.

Further, the statistical process of the abnormal startup and shutdown module on abnormal startup includes:

step S1611: setting a time period for allowing the equipment to be started and an EPI limit value at the starting time of allowing the equipment to be started;

step S1612: the on-off state of the equipment is judged in real time through the data acquisition and storage module, the time of each on-off state conversion and the EPI value at the time are recorded, and the EPI value at the starting time of starting is allowed to be recorded; judging whether the starting-up time of the equipment is in a set time period allowing the equipment to be started up, and if not, giving an alarm in real time to indicate that the starting-up is abnormal; aiming at each abnormal starting, calculating the abnormal time length and the energy consumption of the abnormal time length according to the set time period of allowing the equipment to be started, the EPI limit value of the starting time of the equipment, the recorded time of each switching state of the on-off state and the EPI value of the time and the recorded EPI value of the starting time of the equipment;

the statistical process of the abnormal power-on and power-off module for abnormal power-off comprises the following steps:

step S1621: setting a time period for allowing the equipment to be powered off and an EPI limit value at the starting moment for allowing the equipment to be powered off;

step S1622: the data acquisition and storage module judges the on-off state of the equipment in real time, records the time of each on-off state conversion and the EPI value at the time, and records the EPI value at the starting time of the shutdown permission; judging whether the shutdown time of the equipment is in a set time period allowing the equipment to be shutdown, and if not, giving an alarm in real time to indicate that the shutdown is abnormal; and aiming at each abnormal shutdown, calculating the abnormal duration according to the set time period for allowing the equipment to be shut down and the recorded time for each startup and shutdown state conversion.

Further, the specific process of the balance analysis module includes:

step S171: obtaining data of each metering point from the data acquisition and storage module system;

step S172: counting the energy consumption of each level;

step S173: and calculating the loss value and the loss rate, displaying the loss value and the loss rate, and alarming when the loss value and/or the loss rate are abnormal.

The invention has the beneficial effects that: the intelligent optimization energy-saving system based on the industrial production line management synchronous optimization and the accurate management and control provided by the embodiment of the invention utilizes the energy data, the production data and the process data of the data acquisition and storage module to establish various management optimization analysis modules. Various production data and energy data of enterprises are analyzed through the analysis modules, refinement and automation of production management are achieved, and direct conclusions and data are provided for accurate management and control of a production line, energy conservation and consumption reduction.

Drawings

FIG. 1 is a schematic structural diagram of an intelligent optimization energy-saving system based on synchronous optimization and precise management and control of industrial production line management according to an embodiment of the present invention;

FIG. 2 is a schematic flow chart of a team comparison analysis module according to an embodiment of the present invention;

FIG. 3 is a schematic diagram of a detailed flowchart of a standard value comparison analysis module according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of a specific process flow of a production line contrast analysis module according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of a specific process of the comparative analysis module of the same-operating-condition device according to an embodiment of the present invention;

fig. 6 is a schematic flowchart of a load analysis module according to an embodiment of the present invention;

fig. 7 is a schematic flowchart of an alarm warning module according to an embodiment of the present invention;

fig. 8 is a schematic specific flowchart of abnormal power-on statistics of the abnormal power-on module according to the embodiment of the present invention;

fig. 9 is a schematic specific flowchart of abnormal shutdown statistics of the abnormal shutdown module according to the embodiment of the present invention;

FIG. 10 is a schematic flow chart of a balance analysis module according to an embodiment of the present invention;

fig. 11 is a schematic diagram of an association relationship between modules of an intelligent optimization energy saving system according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to specific embodiments and the accompanying drawings. Those skilled in the art will appreciate that the present invention is not limited to the drawings and the following examples.

The embodiment of the invention provides an intelligent optimization energy-saving system based on industrial production line management synchronous optimization and accurate management and control, as shown in fig. 1 and fig. 11, the system comprises: the system comprises a data acquisition and storage module 10, a comparison analysis module 11, a load analysis module 12, an alarm early warning module 13, an associated equipment linkage analysis module 14, an electric charge structure analysis module 15, an abnormal startup and shutdown module 16 and a balance analysis module 17.

The data acquisition and storage module 10 is used for acquiring and storing energy data, production data, process data and other data required by the operation of the comparative analysis module 11, the load analysis module 12, the alarm early warning module 13, the associated equipment linkage analysis module 14, the electric charge structure analysis module 15, the abnormal on-off module 16 and the balance analysis module 17, and storing various data generated by the comparative analysis module 11, the load analysis module 12, the alarm early warning module 13, the associated equipment linkage analysis module 14, the electric charge structure analysis module 15, the abnormal on-off module 16 and the balance analysis module 17.

The comparison analysis module 11 is configured to perform multidimensional comparison on the data in the data acquisition and storage module 10 to find difference points under various conditions, and analyze the difference points and difference reasons to obtain conclusions and improvement suggestions related to energy consumption optimization and operation safety.

The comparison analysis module 11 comprises a team comparison analysis submodule 111, a standard value comparison analysis submodule 112, a production line comparison analysis submodule 113 and a same-working-condition equipment comparison analysis submodule 114.

The team comparison and analysis module 111 is used for comparing two teams, finding out difference points between the teams, analyzing the difference points and searching for difference reasons, so that energy consumption is reduced. The specific process is shown in fig. 2, and includes:

step S1111: selecting a comparison time period and two comparison teams, and acquiring information of the two teams in the time period from the data acquisition and storage module 10, wherein the time period can be one day, one month, one quarter or one year, and can also be a self-defined time period, and the acquired information includes: team yield data, team energy consumption data and process energy consumption data;

step S1112: respectively calculating the unit consumption of each team according to the acquired information of the two teams, and comparing the difference amplitude of the unit consumption of the two teams obtained by calculation, wherein the unit consumption of the team is team energy consumption data/team yield data;

step S1113: judging whether the difference amplitude is within a set range, if so, outputting a conclusion 1, wherein the conclusion 1 shows that the difference of the unit consumptions of the two teams is small; if the energy consumption data of the process of the two teams is not in the set range, analyzing the energy consumption difference and the unit consumption difference of the corresponding process of the two teams according to the energy consumption data of the process of the two teams, wherein the energy consumption of the process is the sum of the energy consumption of all equipment under the process, the unit consumption of the process is the process energy consumption data/the yield data corresponding to the process, finding the process with larger energy consumption difference and larger unit consumption difference, analyzing the difference of each hour, and outputting a conclusion 2, wherein the conclusion 2 comprises the following steps: the three processes with the largest difference of unit consumption and energy consumption and the three processes with the largest difference of unit consumption and the occurrence time of the two teams and groups.

Through the comparison between teams and groups is carried out by the team comparison and analysis module 111, difference points between teams and groups are found, then the difference points are analyzed, difference reasons are found, experience sharing of production personnel can be effectively promoted, the level is improved, and energy consumption is further reduced.

The standard value comparison and analysis module 112 is used for comparing and analyzing the index value and the standard value to find the difference between the index value and the standard value, so as to provide a direction for continuing to optimize the process and continuously saving energy and reducing consumption. The specific process is shown in fig. 3, and includes:

step S1121: selecting conditions of contrastive analysis, wherein the conditions comprise contrastive analysis time and index name;

step S1122: acquiring index data from the data acquisition and storage module 10, wherein the index data comprises energy consumption data and production data necessary for calculating an index value, and also comprises standard value data of a specific index;

the standard value is obtained from two sources, one is manually recorded, and the other is automatically obtained. The manually input standard value comprises an enterprise-defined in-enterprise control and national standard, a local standard and an admission value and an advanced value specified by an industrial standard.

The automatically obtained standard value refers to long-term data subjected to intelligent optimization, and comprises an optimal value, an average value and a corresponding production core process parameter value when the optimal value and the average value of corresponding indexes are automatically counted.

Step S1123: calculating a corresponding index value according to an index formula and the acquired index data, wherein the index formula is set by a user according to indexes;

step S1124: judging whether the calculated index value is in a normal range specified by a corresponding standard value, and if the index value is in the normal range specified by the corresponding standard value, prompting that the index value is normal; if the index value is not in the normal range specified by the corresponding standard value, displaying that the index value is not in the normal range; and if the compared standard value is the optimal value, displaying the core process parameter corresponding to the index value and the core process parameter corresponding to the optimal value, thereby providing a deviation adjusting direction for an enterprise manager.

The production line comparison and analysis module 113 is used for comparing production indexes and energy consumption indexes of two similar production lines with each other, analyzing deviation of each index, and analyzing whether the deviation is in a normal range, so that a point of abnormal production line operation is obtained, problems are solved in time, and safe operation and energy-saving operation of the production line are realized. The specific process is shown in fig. 4, and includes:

step S1131: acquiring basic data of a first production line and a second production line from the data acquisition and storage module 10, wherein the first production line and the second production line adopt the same production process and two different production lines for producing the same product, and the basic data is used for calculating various indexes of the production lines;

step S1132: calculating (matching in corresponding index formulas) indexes of the first production line and the second production line;

step S1133: comparing the difference values of the corresponding indexes obtained by calculation, wherein in general, the difference values of the indexes of two production lines with the same production process and the same product are within a normal range, and if the difference values of the indexes exceed the normal range, the problem occurs in the production link corresponding to the indexes;

step S1134: outputting a conclusion, if the difference value of the indexes is in the normal range, outputting a conclusion that the indexes of the production line are compared with normal; if the difference of the indexes exceeds the normal range, indicating that the production link corresponding to the index has a problem, outputting a conclusion that the indexes are compared with the positions of the abnormal production links with the problems.

The same-condition equipment comparison analysis module 114 is used for performing comparison analysis on equipment under the same condition. In the production line, a plurality of devices with the same working condition exist, the power of the devices is the same at adjacent process positions, but the load size and the change trend of the load of the devices are different in many cases. The difference is caused by the fact that the equipment is not adjusted to be in a good operation state, and energy consumption waste and potential safety hazards exist in the situation. The specific process is shown in fig. 5, and includes:

step S1141: acquiring data of equipment under the same working condition from the data acquisition and storage module 10, and calculating equipment data, wherein the equipment data comprises average power, real-time current and operation trend (showing data trend in unit time);

step S1142: displaying corresponding equipment data;

step S1143: outputting a comparison conclusion, and if the difference value of the equipment data of the equipment under the same working condition is within a certain threshold range, outputting a conclusion that the equipment under the same working condition is normally compared; and if the difference value of the data equipment exceeds the threshold range, outputting a conclusion that the comparison with the working condition equipment is abnormal.

The load analysis module 12 is configured to analyze distribution of load over time, maximum load time, maximum demand, and maximum demand time by using the real-time data acquired by the data acquisition and storage module 10 and historical data formed after processing the real-time data according to a certain rule, where the rule may be set according to a requirement of an enterprise. The load analysis module 12 is used to draw the conclusion of peak load shifting and production optimization. The specific process is shown in fig. 6, and includes:

step S121: selecting analysis time and analysis objects, wherein the analysis objects can be production lines, working sections, working procedures and equipment;

step S122: obtaining yield data and energy consumption data from the data acquisition and storage module 10;

step S123: showing energy consumption and yield trends, e.g. according to peak-to-valley, flat period, represented with different color backgrounds at different times of the trend plot;

step S124: displaying the maximum load, the maximum demand, the maximum load time and the maximum demand time;

step S125: and (5) giving a conclusion of adjusting production and optimizing load. In one embodiment, the system automatically matches the appropriate conclusion template based on the current query results and provides a conclusion content reminder to adjust production and optimize load. As a basis for adjusting the current production load.

The alarm early warning module 13 is used for processing and analyzing the real-time data acquired by the data acquisition and storage module 10 to obtain data related to safe operation and economic operation, and performing corresponding early warning or alarm. The corresponding alarm pre-warning comprises the following steps: real-time overrun alarm, historical overrun alarm, real-time fluctuation abnormity early warning and change trend abnormity early warning. The four kinds of alarm and early warning can be performed on the variables such as voltage, current, power factor, energy consumption, unit consumption, temperature, pressure and the like collected by the data collection and storage module 10, and alarm and early warning conditions can be conveniently set. The specific process is shown in fig. 7, and includes:

step S131: real-time data of a production field is acquired through the data acquisition and storage module 10, wherein the real-time data comprises electric quantity data and non-electric quantity data, the electric quantity data comprises voltage, current and the like, and the non-electric quantity data comprises temperature, pressure and the like;

step S132: setting an alarm upper limit value and an alarm lower limit value for the real-time data, namely setting a real-time overrun alarm condition; meanwhile, a real-time fluctuation abnormity alarm condition is set for the load which runs stably under normal conditions, and the real-time fluctuation abnormity alarm condition is that the fluctuation abnormity in 20 data is not more than 3;

step S133: judging whether a real-time overrun alarm condition and a real-time fluctuation abnormal alarm condition are met in real time according to the acquired real-time data;

step S134: carrying out early warning or alarming on the real-time data meeting the real-time overrun alarming condition and/or the real-time fluctuation abnormal alarming condition, and displaying reasons;

step S135: processing the real-time data to form historical data, wherein the historical data comprises historical data of electric quantity and non-electric quantity, and the historical data comprises the electricity consumption of a team, unit consumption and the like; and setting a historical data overrun alarm condition and a historical data change trend early-warning alarm condition, carrying out early warning or alarming when the historical data overrun alarm condition and the historical data change trend early-warning alarm condition are met, and displaying reasons.

The alarm early warning module 13 can enable enterprise production management personnel to find abnormal conditions occurring in production in time through real-time alarm early warning, and can rapidly process the abnormal conditions, thereby ensuring safe, orderly and energy-saving production. And through historical data early warning and alarming, abnormal problems which are difficult to find through real-time data are displayed, and a plurality of layers of guarantees are provided for safe operation and energy-saving operation of a production line.

The associated device linkage analysis module 14 is configured to establish an association relationship between two devices that have associated operations on a production line, and record information such as idle time, idle energy consumption, and idle duration for a case where the devices are not started or stopped according to the association relationship each time. And analyzing information such as accumulated idling times, accumulated idling energy consumption, accumulated idling duration and the like from the viewpoints of equipment groups, teams, workshops and whole plants. Through accurate real-time alarm prompt, the idle running can be effectively reflected to corresponding responsible persons each time; through accurate data statistics, the idle running time, the idle running times and the idle running energy consumption are examined, and all the examinations can be based on the data, so that the operation of production personnel is further standardized, the idle running of enterprise equipment is reduced, and the running risk of the equipment is reduced.

The analysis object of the related device linkage analysis module 14 is a related device (group) having a relationship in the order of start-up and shutdown. The following situations generally exist in the actual field: the auxiliary equipment is not interlocked with the host equipment, so that the phenomena of unreasonable starting and stopping sequence, untimely shutdown of a post and the like exist, the equipment runs in an idle mode, and electric energy waste is caused; the main and auxiliary equipment (system) and process related equipment may have asynchronous start and stop, which may be necessary and inevitable due to heat dissipation, material delay and the like. However, the early start time and the delayed stop time are not accurately controlled, and a part of electric energy is wasted. The idle running waste electric quantity of each equipment in each day and each shift is not counted, and the measurement of the management and control of the associated equipment of the shift group cannot be made. Therefore, the correlation device interlock analysis module 14 can timely find the potential safety interlock hazard and the idle running phenomenon of the correlation device by collecting the operation parameters (the field data can be the current signal of the field ammeter, the signal of the circuit breaker, the switching value signal of the contactor, and the device state signal read from the DCS control system through the OPC server), and count the idle running time, the wasted electric quantity and other data, so as to provide an assessment basis for enhancing the management and control of the field correlation device.

The associated equipment linkage analysis module 14 can monitor the running state of the associated equipment in real time according to the data from the data acquisition and storage module 10, judge whether the potential safety interlock hazard and the idling phenomenon of the equipment occur according to the preset logic condition, and immediately alarm and remind when the potential safety interlock hazard and the idling phenomenon occur; automatically counting the idle time of equipment in a certain period and a working section and the data of waste electric quantity; and carrying out comparison analysis on data such as equipment idling time, wasted electric quantity and the like in terms of the same ratio, the ring ratio and the team target value, and giving a conclusion.

The electric charge structure analysis module 15 is used for automatically calculating each constituent part of the electric charge according to the power supply protocol for all the power consumption of the enterprise. For large industrial users, general electricity charges can be divided into basic electricity prices, electricity degree electricity prices and power adjusting electricity prices. The electric charge structure analysis module 15 analyzes the electric charges of the three parts in real time, and automatically provides a reasonable suggestion for optimizing the electric charge structure for the user aiming at whether each part is reasonably evaluated, so that the electric charge cost expenditure of the user is reduced.

According to the current electricity price system in China, the following rules and systems are provided: single power generation rates and two power generation rates. The single electricity price only has one electricity price, namely the electricity price is collected according to the electricity consumption, and the electricity price is irrelevant to the equipment capacity. The two part of electricity making prices are that electricity prices are divided into two parts, one part is called basic electricity prices, and the basic electricity prices are calculated according to the client power receiving capacity (kVA) or the client maximum demand (kW) and are irrelevant to the actual electricity consumption; the other part is called electricity rate and electricity rate, and electricity rate is calculated according to the actual electricity consumption of the client when calculating the electricity rate and electricity rate. At present, China only carries out two electricity prices for large industrial customers.

In addition, in order to guide and encourage customers to shift peaks and fill valleys, reduce peak-valley load difference of a power grid and relieve power supply and demand contradiction during peak load periods, China implements a peak-valley time-sharing electricity price system, wherein the peak-valley time-sharing electricity price is divided into four time periods (peaks, flat sections and valleys) or three time periods (peaks, flat sections and valleys) within 24 hours a day, and each time period implements different price levels.

The electricity price in the season of rich withered water is divided into three seasons of rich water period, normal water period and dry water period according to the requirements of electricity generation and water utilization in one year, and different electricity price levels are implemented.

And (4) according to the calculated power factor, when the power factor is higher or lower than a specified standard, after the monthly electricity fee is calculated according to a specified electricity price, increasing or decreasing the electricity fee according to a percentage specified by a power factor adjusting electricity fee table. Electricity prices fall into the following categories: lighting electricity prices, non-industrial electricity prices, general industrial electricity prices, large industrial electricity prices, agricultural production electricity prices, wholesale electricity prices. Different regions execute different power price calculation methods according to different power utilization properties. For most industrial enterprises, the main category is large industrial electricity, so the electricity charge comprises basic electricity price and electric power price, wherein the basic electricity price is different due to different charging mode choices, and the electric power price is different due to different power factors and different peak-valley periods. For example, the basic electricity rate of Hubei province is 26 yuan/kVA per month when charging by capacity, and 39 yuan/kW when charging by maximum demand. When the maximum demand value is lower than 67% of the capacity, the basic electricity price is calculated in the maximum demand manner, and the basic electricity price is paid less. By reasonably selecting a basic electricity price charging mode, adjusting the electricity load of each time interval and reasonably compensating reactive power, the cost of the electricity charge of an enterprise can be effectively saved, the energy conservation and emission reduction of the whole society are facilitated, and the operation safety of a power grid is guaranteed.

Specifically, the electricity charge structure analysis module 15 is configured to obtain the electricity consumption data of the user from the data acquisition and storage module 10, display the composition details of the electricity charge of the user, set monitoring related data indexes, remind the user to adopt a corresponding management and control mode, and reduce the electricity consumption cost; analyzing the electricity charge data of the user, combining with the national electricity charge policy, exploring unreasonable conditions in the actual electricity charge of the user, positioning corresponding electricity utilization areas and time, and providing evaluation basis for the user to make targeted improvement measures; the method has the advantages that the structure of the electric charge of the user and the relation between each project and production operation data are analyzed, the user is guided to carry out detailed analysis on the electricity utilization data, the reason of the electric charge difference is revealed from historical data, scientific data support is provided for optimizing and managing the electricity charge of the user, and a system platform is provided for continuously optimizing the electricity utilization management level of the user.

The electric charge structure analysis module 15 analyzes load characteristics according to the collected electricity consumption data, comprehensively compares and analyzes the electric charge cost expenditure, prompts unreasonable charging modes and electric charge expenditures, provides a data analysis method to guide a user to analyze and compare historical electricity consumption data, helps the user improve management measures and reduces later-stage electric charge expenditures.

The abnormal on-off module 16 mainly solves the problem that production is not performed according to the requirements of a production system or a production plan. The running state of the host of each section of the production line is judged in real time, and whether the host equipment carries out production in a specified time period or stops production in the specified time period is judged according to the specified startup-allowed time period and shutdown-allowed time period of a production system or a production plan. And alarming in real time aiming at the condition that the computer is not started or stopped according to the specified time requirement every time, and simultaneously recording the starting time and the energy consumption of the abnormal state. The abnormal startup and shutdown module 16 can count abnormal energy consumption, abnormal duration and abnormal times according to teams, work sections, branch plants and whole plants, and provides a direct basis with confidence for assessment management. The abnormal startup and shutdown module 16 can standardize the operation of operators, reduce the working intensity of production managers, promote reasonable and standardized production of enterprises, reduce the production cost of enterprises, and avoid the production risk of production which is not produced according to the plan. The specific process of the abnormal power-on statistics of the abnormal power-on/off module 16 is shown in fig. 8, and includes:

step S1611: setting a time period for allowing the equipment to be started and an EPI limit value at the starting time of allowing the equipment to be started;

step S1612: the data acquisition and storage module 10 judges the on-off state of the equipment in real time, records the time of each on-off state conversion and the EPI value at the time, and records the EPI value at the starting time of starting; judging whether the starting-up time of the equipment is in a set time period allowing the equipment to be started up, and if not, giving an alarm in real time to indicate that the starting-up is abnormal; and aiming at each abnormal starting, calculating the abnormal time length and the energy consumption of the abnormal time length according to the set time period for allowing the equipment to be started, the EPI limit value at the starting time of allowing the equipment to be started, the recorded time of each switching state of the on-off state and the EPI value at the time and the recorded EPI value at the starting time of allowing the equipment to be started.

The recorded and calculated data can be stored, and query statistics and off-line analysis are facilitated.

The recorded and calculated data can be displayed, and a user can conveniently know the equipment condition.

The specific flow of the abnormal shutdown statistics of the abnormal shutdown module 16 is shown in fig. 9, and includes:

step S1621: setting a time period for allowing the equipment to be powered off and an EPI limit value at the starting moment for allowing the equipment to be powered off;

step S1622: the data acquisition and storage module 10 judges the on-off state of the equipment in real time, records the time of each on-off state conversion and the EPI value at the time, and records the EPI value at the starting time of the shutdown permission; judging whether the shutdown time of the equipment is in a set time period allowing the equipment to be shutdown, and if not, giving an alarm in real time to indicate that the shutdown is abnormal; and aiming at each abnormal shutdown, calculating the abnormal duration according to the set time period for allowing the equipment to be shut down and the recorded time for each startup and shutdown state conversion.

And the recorded and calculated data can be stored, so that query statistics and off-line analysis are facilitated.

The recorded and calculated data can be displayed, and a user can conveniently know the equipment condition.

The balance analysis module 17 is used for analyzing various links of generation, transmission, distribution, consumption and the like of various energy sources of an enterprise according to the idea of supply and demand balance. The transmission efficiency and the loss value can be analyzed step by step according to a multi-stage energy metering network established by an enterprise. Through the balance analysis module 17, the enterprise energy management personnel can find the abnormal condition of energy loss in time, and the energy waste is avoided. The specific process is shown in fig. 10, and includes:

step S171: obtaining data of each metering point from the data acquisition and storage module 10;

step S172: counting the energy consumption of each level;

step S173: and calculating the loss value and the loss rate, displaying the loss value and the loss rate, and alarming when the loss value and/or the loss rate are abnormal.

Further, the intelligent optimization energy-saving system further comprises a display module (not shown in the figure) for displaying data generated by the comparison analysis module, the load analysis module, the alarm early warning module, the associated device linkage analysis module, the electricity charge structure analysis module, the abnormal startup and shutdown module and the balance analysis module.

An embodiment of the present invention further provides a computer-readable storage medium storing a computer program for executing the foregoing method.

An embodiment of the present invention further provides a computer device, which includes a processor and the above computer-readable storage medium operatively connected to the processor, where the processor executes a computer program in the computer-readable storage medium.

Those of skill in the art will understand that the logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be viewed as implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.

More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.

It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.

In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

The embodiments of the present invention have been described above. However, the present invention is not limited to the above embodiment. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. The utility model provides an intelligent optimization economizer system based on synchronous optimization of industrial production line management and accurate management and control which characterized in that, this system includes: the system comprises a data acquisition and storage module, a comparison analysis module, a load analysis module, an alarm early warning module, an associated equipment linkage analysis module, an electric charge structure analysis module, an abnormal startup and shutdown module and a balance analysis module; the comparison analysis module, the load analysis module, the alarm early warning module, the associated equipment linkage analysis module, the electric charge structure analysis module, the abnormal startup and shutdown module and the balance analysis module are all connected with the data acquisition and storage module;

the data acquisition and storage module is used for acquiring and storing data, and the stored data comprises the acquired data and data generated by the comparison analysis module, the load analysis module, the alarm early warning module, the associated equipment linkage analysis module, the electric charge structure analysis module, the abnormal startup and shutdown module and the balance analysis module;

the comparison analysis module is used for carrying out multi-dimensional comparison on the data in the data acquisition and storage module to find difference points under various conditions;

the load analysis module is used for analyzing the distribution of the load in time, the maximum load time, the maximum demand and the maximum demand time by utilizing the real-time data acquired by the data acquisition and storage module and historical data formed by processing the real-time data according to a set rule;

the alarm early warning module is used for processing and analyzing the real-time data acquired by the data acquisition and storage module to obtain data related to safe operation and economic operation and carrying out corresponding early warning or alarm;

the associated equipment linkage analysis module is used for monitoring the running state of the associated equipment in real time according to the data from the data acquisition and storage module and judging whether the potential safety interlock hazard and the idling phenomenon of the equipment occur or not according to the preset logic condition; automatically counting the idle time of equipment in a certain period and a working section and the data of waste electric quantity; carrying out comparison analysis on the data of equipment idle time and waste electric quantity in a same ratio, a ring ratio and a team target value;

the electric charge structure analysis module is used for displaying electric charge composition details according to the user electricity consumption data acquired from the data acquisition and storage module, setting monitoring related data indexes and reminding a user to adopt a corresponding control mode; analyzing the user electricity charge data, searching unreasonable conditions in the actual electricity charge of the user, and positioning corresponding electricity utilization areas and time; analyzing the constitution of the user electricity fee and the relation between each project and production operation data;

the abnormal startup and shutdown module is used for judging the running state of the host of each section of the production line in real time according to the data in the data acquisition and storage module, and judging whether the host equipment produces within a specified time period or stops producing within the specified time period according to the specified startup-allowed time period and shutdown-allowed time period of a production system or a production plan;

and the balance analysis module is used for analyzing various links of generation, transmission, distribution and consumption of various energy sources according to the data in the data acquisition and storage module and the supply and demand balance.

2. The system of claim 1, wherein the comparative analysis module comprises a team comparative analysis submodule, a standard value comparative analysis submodule, a production line comparative analysis submodule and a same-working-condition equipment comparative analysis submodule;

the team comparison and analysis module is used for comparing the two teams, finding out difference points between the teams, analyzing the difference points and searching for difference reasons;

the standard value comparison analysis module is used for comparing and analyzing the index value and the standard value to find out the difference between the index value and the standard value;

the production line contrasts and analyzes the module and is used for contrasting each production index and energy consumption index of two similar production lines, analyzing the deviation of each index, and analyzing whether the deviation is in the normal range:

and the equipment comparison and analysis module under the same working condition is used for performing comparison and analysis on the equipment under the same working condition.

3. The system of claim 2, wherein the specific process of the team comparison analysis module comprises:

step S1111: selecting a comparison time period and two teams for comparison, and acquiring information of the two teams in the time period from the data acquisition and storage module;

step S1112: respectively calculating the unit consumption of each team according to the acquired information of the two teams, and comparing the difference amplitude of the unit consumption of the two teams obtained through calculation;

step S1113: judging whether the difference amplitude is within a set range, if so, outputting a conclusion 1, wherein the conclusion 1 shows that the difference of the unit consumptions of the two teams is small; if the process energy consumption data of the two teams is not in the set range, analyzing the energy consumption difference and the unit consumption difference of the corresponding processes of the two teams according to the process energy consumption data of the two teams, finding out the process with larger energy consumption difference and unit consumption difference, analyzing the difference of each hour, and outputting a conclusion 2, wherein the conclusion 2 comprises the following steps: the three processes with the largest difference of unit consumption and energy consumption and the three processes with the largest difference of unit consumption and the occurrence time of the two teams and groups.

4. The system of claim 2, wherein the specific process of the standard value-versus-analysis module comprises:

step S1121: selecting conditions of contrastive analysis, wherein the conditions comprise contrastive analysis time and index name;

step S1122: acquiring index data from the data acquisition and storage module, wherein the index data comprises energy consumption data and production data necessary for calculating an index value and also comprises standard value data of a specific index;

step S1123: calculating a corresponding index value according to the index formula and the acquired index data;

step S1124: judging whether the calculated index value is in a normal range specified by a corresponding standard value, and if the index value is in the normal range specified by the corresponding standard value, prompting that the index value is normal; if the index value is not in the normal range specified by the corresponding standard value, displaying that the index value is not in the normal range; and if the compared standard value is the optimal value, displaying the core process parameter corresponding to the index value and the core process parameter corresponding to the optimal value.

5. The system of claim 2, wherein the specific process of the production line contrastive analysis module comprises:

step S1131: acquiring basic data of a first production line and a second production line from the data acquisition and storage module, wherein the first production line and the second production line adopt the same production process and two different production lines for producing the same product, and the basic data is used for calculating various indexes of the production lines;

step S1132: calculating various indexes of the first production line and the second production line;

step S1133: comparing the difference values of the corresponding indexes obtained by calculation;

step S1134: outputting a conclusion, if the difference value of the indexes is in the normal range, outputting a conclusion that the indexes of the production line are compared with normal; if the difference of the indexes exceeds the normal range, outputting the conclusion that the indexes are compared with the positions of abnormal and problematic production links.

6. The system of claim 2, wherein the specific process of the under-condition equipment comparison analysis module comprises:

step S1141: acquiring data of equipment under the same working condition from the data acquisition and storage module, and calculating equipment data, wherein the equipment data comprises average power, real-time current and running trend;

step S1142: displaying corresponding equipment data;

step S1143: outputting a comparison conclusion, and if the difference value of the equipment data of the equipment under the same working condition is within a certain threshold range, outputting a conclusion that the equipment under the same working condition is normally compared; and if the difference value of the data equipment exceeds the threshold range, outputting a conclusion that the comparison with the working condition equipment is abnormal.

7. The system of claim 1, wherein the specific process of the load analysis module comprises:

step S121: selecting an analysis time and an analysis object;

step S122: obtaining yield data and energy consumption data from the data acquisition and storage module;

step S123: displaying an energy consumption trend and a yield trend;

step S124: displaying the maximum load, the maximum demand, the maximum load time and the maximum demand time;

step S125: and (5) giving a conclusion of adjusting production and optimizing load.

8. The system of claim 1, wherein the specific process of the alarm and pre-warning module comprises:

step S131: real-time data of a production field is collected through the data collecting and storing module, and the real-time data comprises electric quantity data and non-electric quantity data;

step S132: setting an alarm upper limit value and an alarm lower limit value for the real-time data, namely setting a real-time overrun alarm condition; meanwhile, setting real-time fluctuation abnormal alarm conditions for the load which runs stably under normal conditions;

step S133: judging whether a real-time overrun alarm condition and a real-time fluctuation abnormal alarm condition are met in real time according to the acquired real-time data;

step S134: carrying out early warning or alarming on the real-time data meeting the real-time overrun alarming condition and/or the real-time fluctuation abnormal alarming condition, and displaying reasons;

step S135: processing the real-time data to form historical data, setting a historical data overrun alarm condition and a historical data change trend early-warning alarm condition, carrying out early warning or alarming when the historical data overrun alarm condition and the historical data change trend early-warning alarm condition are met, and displaying reasons.

9. The system according to claim 1, wherein the statistical process of abnormal power-on by the abnormal power-on/off module includes:

step S1611: setting a time period for allowing the equipment to be started and an EPI limit value at the starting time of allowing the equipment to be started;

step S1612: the on-off state of the equipment is judged in real time through the data acquisition and storage module, the time of each on-off state conversion and the EPI value at the time are recorded, and the EPI value at the starting time of starting is allowed to be recorded; judging whether the starting-up time of the equipment is in a set time period allowing the equipment to be started up, and if not, giving an alarm in real time to indicate that the starting-up is abnormal; aiming at each abnormal starting, calculating the abnormal time length and the energy consumption of the abnormal time length according to the set time period of allowing the equipment to be started, the EPI limit value of the starting time of the equipment, the recorded time of each switching state of the on-off state and the EPI value of the time and the recorded EPI value of the starting time of the equipment;

the statistical process of the abnormal power-on and power-off module for abnormal power-off comprises the following steps:

step S1621: setting a time period for allowing the equipment to be powered off and an EPI limit value at the starting moment for allowing the equipment to be powered off;

step S1622: the data acquisition and storage module judges the on-off state of the equipment in real time, records the time of each on-off state conversion and the EPI value at the time, and records the EPI value at the starting time of the shutdown permission; judging whether the shutdown time of the equipment is in a set time period allowing the equipment to be shutdown, and if not, giving an alarm in real time to indicate that the shutdown is abnormal; and aiming at each abnormal shutdown, calculating the abnormal duration according to the set time period for allowing the equipment to be shut down and the recorded time for each startup and shutdown state conversion.

10. The system of claim 1, wherein the specific process of the balance analysis module comprises:

step S171: obtaining data of each metering point from the data acquisition and storage module system;

step S172: counting the energy consumption of each level;

step S173: and calculating the loss value and the loss rate, displaying the loss value and the loss rate, and alarming when the loss value and/or the loss rate are abnormal.

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