CN117406685A - Intelligent control optimizing management system of building equipment suitable for green low-carbon building - Google Patents
Intelligent control optimizing management system of building equipment suitable for green low-carbon building Download PDFInfo
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Abstract
The invention belongs to the technical field of building equipment management and control, in particular to an intelligent control optimization management system of building equipment suitable for a green low-carbon building, which comprises an intelligent management and control platform, an operation mode matching evaluation module, an optimal control module of the building equipment and an operation energy consumption management decision module; according to the invention, the operation mode matching evaluation module analyzes the performance status of the operation parameters of the building equipment based on the current operation mode of the building equipment, the corresponding operation parameters of the building equipment are automatically adjusted through the building equipment optimizing control module when the matching abnormal signal is generated, the operation optimizing control of the building equipment is realized, the effective detection and accurate feedback of the operation energy consumption of the building equipment are realized through the operation energy consumption detection analysis module when the matching normal signal is generated, the safe and stable operation of the building equipment is ensured, the functions of energy conservation, low carbon and environmental protection are realized, the intelligent level and the automation level are obviously improved, and the equipment management difficulty of a green low-carbon building is reduced.
Description
Technical Field
The invention relates to the technical field of building equipment management and control, in particular to an intelligent control optimization management system for building equipment suitable for green low-carbon buildings.
Background
The green low-carbon building is a building which reduces the use of petrochemical energy sources, improves the energy efficiency and reduces the carbon dioxide emission in the whole life cycle of building materials, equipment manufacturing, building construction and building use, emphasizes the saving and recycling of resources, reduces environmental pollution and carbon emission, improves the use comfort and energy efficiency level of the building, realizes the harmony and symbiosis of people and nature, and is one of the development trends of future urban buildings;
at present, when building equipment of a green low-carbon building is managed, by setting an operation mode of the building equipment, the building equipment is operated according to the operation mode, so that the matching performance of operation parameters in the operation process of the building equipment cannot be checked and evaluated, the building equipment is automatically optimized and regulated when the matching performance is abnormal, the intelligent and automatic levels are low, the energy consumption condition of the building equipment is difficult to accurately feed back when the matching performance is normal, the equipment management difficulty of the green low-carbon building is increased, and the safety and stable operation and the low-carbon energy-saving effect of the building equipment are not guaranteed;
in view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to provide an intelligent control optimization management system for building equipment suitable for a green low-carbon building, which solves the problems that the prior art cannot correct and evaluate the matching performance of the operation parameters in the operation process of the building equipment, automatically optimize and regulate the building equipment when the matching performance is abnormal, accurately feed back the energy consumption condition of the building equipment when the matching performance is normal, increase the equipment management difficulty of the green low-carbon building and have low intelligent and automatic levels.
In order to achieve the above purpose, the present invention provides the following technical solutions:
the intelligent control optimizing management system for the building equipment suitable for the green low-carbon building comprises an intelligent control platform, an operation mode matching evaluation module, an optimizing control module for the building equipment and an operation energy consumption management decision module; the intelligent control platform acquires the current operation mode of the building equipment and sends the current operation mode of the building equipment to an operation mode matching evaluation module; the operation mode matching evaluation module analyzes the operation parameter performance status of the building equipment based on the current operation mode of the building equipment, so as to identify parameters to be adjusted and generate a matching abnormal signal or a matching normal signal;
the operation mode matching evaluation module sends a matching abnormal signal and all parameters to be adjusted to the building equipment optimizing control module through the intelligent management and control platform, and the building equipment optimizing control module automatically adjusts corresponding operation parameters of the building equipment when receiving the matching abnormal signal so as to optimally control the operation of the building equipment; and the operation mode matching performance evaluation module sends a matching performance normal signal to the operation energy consumption detection and analysis module through the intelligent management and control platform, and the operation energy consumption detection and analysis module carries out energy consumption decision management analysis on the building equipment so as to generate an energy consumption performance qualified signal or an energy consumption performance unqualified signal and sends the energy consumption performance unqualified signal to the building monitoring end through the intelligent management and control platform.
Further, the specific operation process of the operation mode matching evaluation module comprises the following steps:
acquiring real-time data of all operation parameters to be monitored in the operation process of the building equipment, acquiring preset standard data corresponding to all operation parameters based on the current operation mode of the building equipment, performing difference value calculation on the real-time data of the corresponding operation parameters and the corresponding preset standard data, taking absolute values to obtain parameter disturbance data, and performing numerical comparison on the parameter disturbance data and the preset parameter disturbance data range of the corresponding operation parameters;
if the parameter disturbance data are located in the preset parameter disturbance data range, marking the corresponding operation parameters of the building equipment as the optimal table parameters; if the parameter disturbance data are not in the preset parameter disturbance data range, marking the corresponding operation parameters of the building equipment as parameters to be adjusted; if the parameters to be adjusted exist in the current operation process of the building equipment, generating a matchability abnormal signal; if the parameters to be adjusted do not exist in the current operation process of the building equipment, generating a normal signal of matching property; and sending the abnormal signal or normal signal to the intelligent management and control platform.
Further, the specific analysis process of the energy consumption decision management analysis is as follows:
setting a consumption detection period, setting a plurality of consumption detection time points in the consumption detection period, wherein the time intervals between two adjacent groups of consumption detection time points are the same; collecting energy consumption rates of the building equipment at all consumption detection points, and establishing a consumption rate set for all the energy consumption rates of the consumption detection period; summing up the consumption speed sets, calculating and taking an average value to obtain consumption speed detection values, acquiring corresponding preset consumption speed detection value ranges based on the current operation mode of the building equipment, performing numerical comparison on the consumption speed detection values and the preset consumption speed detection value ranges, and generating an energy consumption performance disqualification signal if the consumption speed detection values are not in the preset consumption speed detection value ranges;
if the consumption speed detection value is in the preset consumption speed detection value range, carrying out difference calculation on a subset with the largest value and a subset with the smallest value in the consumption speed set to obtain a consumption speed difference value; performing difference calculation on the consumption speed detection value and the median value of the preset consumption speed detection value range, taking an absolute value to obtain a consumption speed deviation value, and performing weighted summation calculation on the consumption speed deviation value and the consumption speed difference value to obtain a consumption speed evaluation value; and comparing the consumption speed evaluation value with a corresponding preset consumption speed evaluation threshold value, and generating an energy consumption performance disqualification signal if the consumption speed evaluation value exceeds the preset consumption speed evaluation threshold value.
Further, if the consumption speed evaluation value does not exceed the preset consumption speed evaluation threshold, establishing a rectangular coordinate system positioned in the first quadrant by taking time as an X axis and taking the energy consumption rate as a Y axis, drawing a plurality of energy consumption evaluation points in the rectangular coordinate system based on the energy consumption rates of all the consumption inspection points, connecting two adjacent groups of energy consumption evaluation points through line segments, and marking the connecting line segments as energy consumption lifting line segments;
drawing a straight line which is parallel to the X axis and intersects with the energy consumption lifting line segment in a rectangular coordinate system, marking the straight line as a horizontal tangent line, and marking an acute angle of an included angle formed by the energy consumption lifting line segment and the corresponding horizontal tangent line as a consumption change angle condition value; comparing the consumption change angle condition value with a corresponding preset consumption change angle condition threshold value, and marking the corresponding consumption change angle condition value as consumption change angle excess value if the consumption change angle condition value exceeds the preset consumption change angle condition threshold value; dividing the number of the consumption change angle excess values by the number of the energy consumption lifting line segments to obtain consumption excess evaluation values, summing all consumption change angle condition values, and taking an average value to obtain a consumption angle average value;
performing numerical calculation on the consumption super evaluation value and the consumption angle average value to obtain a consumption speed fine evaluation value, performing numerical comparison on the consumption speed fine evaluation value and a corresponding preset consumption speed fine evaluation threshold value, and generating an energy consumption performance failure signal if the consumption speed fine evaluation value exceeds the preset consumption speed fine evaluation threshold value; and if the consumption speed fine evaluation value does not exceed the preset consumption speed fine evaluation threshold value, generating an energy consumption performance qualification signal.
Further, the intelligent management and control platform is in communication connection with the optimization efficiency decision module, the optimization efficiency decision module collects the time when the building equipment optimization control module obtains the matching abnormal signal, and the time is marked as an optimization initial table time; the time when the building equipment optimization control module finishes the regulation and control of all parameters to be regulated is collected, and the time is marked as the optimization last table time;
calculating the time difference between the optimal last table time and the optimal initial table time to obtain an optimal running time length, calling a corresponding target running time length from the intelligent control platform, performing numerical comparison on the optimal running time length and the target running time length, and judging that the corresponding optimal control process is low in efficiency and generating an optimal low-efficiency signal if the optimal running time length exceeds the target running time length; if the optimal running time length does not exceed the target running time length, judging that the corresponding optimal control process is high in efficiency and generating an optimal high-efficiency signal; and the optimized high-efficiency signal or the optimized low-efficiency signal is sent to the intelligent control platform, and the intelligent control platform stores the quantity of the optimized control processes corresponding to the optimized high-efficiency signal or the optimized low-efficiency signal together.
Further, the target operation duration is obtained by analysis of a target operation time generation module, and the target operation time generation module is in communication connection with the intelligent control platform so as to send the generated target operation duration to the intelligent control platform for storage; the operation process of the target time-running generation module comprises the following steps:
acquiring all current parameters to be adjusted of the building equipment, and presetting each group of operation parameters of the building equipment to respectively correspond to a group of operation difficulty values, wherein the operation difficulty values are all larger than zero; marking the deviation value of the parameter disturbance data corresponding to the parameter to be adjusted compared with the corresponding preset parameter disturbance data range as parameter to be adjusted data, multiplying the parameter to be adjusted data by the corresponding operational tuning difficulty value to obtain a parameter adjustment evaluation value corresponding to the parameter to be adjusted, and carrying out summation calculation on the parameter adjustment evaluation values of all the current parameters to be adjusted of the building equipment to obtain a parameter adjustment evaluation value;
a plurality of groups of preset reference analysis value ranges are preset in advance, and each group of preset reference analysis value ranges corresponds to a group of reference optimization time length respectively; and comparing the reference evaluation value with all the preset reference evaluation value ranges one by one, marking the preset reference evaluation value range containing the reference evaluation value as a target reference evaluation range, and marking the reference optimization time length corresponding to the target reference evaluation range as a target operation and adjustment time length.
Further, the intelligent control platform is in communication connection with the comprehensive operation and evaluation module, the comprehensive operation and evaluation module is used for setting an operation and evaluation period, obtaining the quantity corresponding to the optimized high-efficiency signal and the optimized low-efficiency signal of the building equipment in the operation and evaluation period, marking the quantity as an excellent high-quality measured value and an excellent low-quality measured value respectively, and carrying out ratio calculation on the excellent low-quality measured value and the excellent high-quality measured value to obtain an optimized low-table value;
subtracting the target operation time length from the optimal operation time length corresponding to the optimized low-efficiency signal to obtain optimal time difference data, calculating the ratio of the optimal time difference data to the corresponding target operation time length to obtain an optimal time occupation value, summing all the optimal time occupation values in the operation period, calculating and taking an average value to obtain an optimal time analysis value; and carrying out numerical calculation on the high-low numerical measurement value, the optimized low table value and the optimal time analysis value to obtain a running evaluation table condition value, carrying out numerical comparison on the running evaluation table condition value and a preset running evaluation table condition threshold value, and generating a control early warning signal if the running evaluation table condition value exceeds the preset running evaluation table condition threshold value.
Further, if the operation and evaluation condition value does not exceed the preset operation and evaluation condition threshold value, the times of generating the energy consumption performance failure signals by the building equipment in the operation and evaluation period are obtained and marked as consumption table different frequency values, and the time difference calculation is carried out on the generation moments of the two adjacent groups of energy consumption performance failure signals to obtain consumption different difference values; comparing the consumption difference value with a preset consumption difference time threshold value, marking the corresponding consumption difference value as consumption difference time analysis value if the consumption difference value exceeds the preset consumption difference time threshold value, and calculating the ratio of the number of consumption difference time analysis values to obtain consumption difference analysis values;
and carrying out summation calculation on all consumption difference values in the operation and evaluation period, taking an average value to obtain a consumption difference condition value, carrying out numerical calculation on the consumption difference condition value, the consumption difference analysis value and the consumption table difference frequency value to obtain an operation and evaluation condition value, carrying out numerical comparison on the operation and evaluation condition value and a preset operation and evaluation condition threshold value, generating a control early warning signal if the operation and evaluation condition value exceeds the preset operation and evaluation condition threshold value, and sending the control early warning signal to a building monitoring pipe end through an intelligent control platform.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, the operation parameter performance status of the building equipment is analyzed based on the current operation mode of the building equipment through the operation mode matching evaluation module, so that parameters to be adjusted are identified, a matching abnormal signal or a matching normal signal is generated, the corresponding operation parameters of the building equipment are automatically adjusted when the matching abnormal signal is generated, the operation optimization control of the building equipment is realized, the energy consumption decision management analysis is carried out on the building equipment through the operation energy consumption detection analysis module when the matching normal signal is generated, the effective detection and accurate feedback of the operation energy consumption of the building equipment are realized, the safe and stable operation of the building equipment is ensured, the functions of energy conservation, low carbon and environmental protection are realized, the intelligent level and the automation level are remarkably improved, and the equipment management difficulty of a green low-carbon building is reduced;
2. according to the invention, the target operation time generating module is used for analyzing to obtain the target operation time length of the corresponding optimal control process, the optimal efficiency decision module is used for judging the efficiency of the corresponding optimal control process of the building equipment based on the target operation time length and through analysis, so that an optimal high-efficiency signal or an optimal low-efficiency signal is generated, the optimal control efficiency of the building equipment optimal control module can be accurately judged, the comprehensive operation evaluation module is used for comprehensively evaluating the operation and the optimal control condition of the building equipment, so as to judge whether to generate a control early warning signal, so that a manager can timely adjust the targeted control measures of the building equipment, the safe and stable operation of the building equipment is further ensured, the energy-saving, low-carbon and environment-friendly effects are realized, and the intelligent degree is remarkably improved.
Drawings
For the convenience of those skilled in the art, the present invention will be further described with reference to the accompanying drawings;
FIG. 1 is a system block diagram of a first embodiment of the present invention;
FIG. 2 is a system block diagram of a second embodiment of the present invention;
fig. 3 is a system block diagram of a third embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one: as shown in fig. 1, the intelligent control and optimization management system for the building equipment suitable for the green low-carbon building comprises an intelligent control platform, an operation mode matching evaluation module, a building equipment optimization control module and an operation energy consumption management decision module, wherein the intelligent control platform is in communication connection with the operation mode matching evaluation module, the building equipment optimization control module and the operation energy consumption management decision module; the intelligent control platform acquires the current operation mode of building equipment (such as security equipment, lighting equipment, air conditioning equipment, water supply and drainage equipment and the like of a green low-carbon building), and sends the current operation mode of the building equipment to an operation mode matching evaluation module, wherein the fact that different operation modes of the building equipment are different is needed, and corresponding operation parameters of the building equipment are different;
the operation mode matching evaluation module analyzes the operation parameter performance condition of the building equipment based on the current operation mode of the building equipment, so as to identify parameters to be adjusted, generate matching abnormal signals or matching normal signals, send the matching abnormal signals and all the parameters to be adjusted to the building equipment optimizing control module through the intelligent management and control platform, and automatically adjust the corresponding operation parameters of the building equipment when the building equipment optimizing control module receives the matching abnormal signals, so that the operation of the building equipment is optimally controlled, the automatic reasonable control of the building equipment is realized, and the safe operation of the building equipment is ensured, and meanwhile, the low-carbon and energy-saving effects are achieved; the specific operation process of the operation mode matching evaluation module is as follows:
collecting real-time data of all operation parameters (such as operation current, operation voltage, operation power, continuous operation time length and the like) which are required to be monitored in the operation process of the building equipment, acquiring preset standard data corresponding to all the operation parameters based on the current operation mode of the building equipment, calculating the difference value between the real-time data corresponding to the operation parameters and the corresponding preset standard data, taking an absolute value to obtain parameter disturbance data, wherein the larger the numerical value of the parameter disturbance data is, the worse the parameter performance of corresponding parameters in the current operation process of the building equipment is, and the more in-time optimization adjustment is required; the parameter disturbance data are compared with the preset parameter disturbance data range of the corresponding operation parameters in a numerical value mode;
if the parameter disturbance data are located in the preset parameter disturbance data range, indicating that the corresponding operation parameters of the current operation process have no problem, marking the corresponding operation parameters of the building equipment as optimal table parameters; if the parameter disturbance data are not in the preset parameter disturbance data range, indicating that the corresponding operation parameters of the current operation process are abnormal, marking the corresponding operation parameters of the building equipment as parameters to be adjusted; if the parameters to be adjusted exist in the current operation process of the building equipment, which indicates that the operation condition of the current operation process of the building equipment is poor, generating a matchability abnormal signal; if the parameters to be adjusted do not exist in the current operation process of the building equipment, which indicates that the operation condition of the current operation process of the building equipment is good, a normal signal of matching is generated.
Moreover, the operation mode matching performance evaluation module sends a matching performance normal signal to the operation energy consumption detection analysis module through the intelligent management and control platform, the operation energy consumption detection analysis module carries out energy consumption decision management analysis on the building equipment so as to generate an energy consumption performance qualified signal or an energy consumption performance unqualified signal, so that effective detection and accurate feedback of the operation energy consumption of the building equipment are realized, the energy consumption performance unqualified signal is sent to a building supervision end through the intelligent management and control platform, and corresponding early warning is sent when the building supervision end receives the energy consumption performance unqualified signal, so that corresponding management personnel can timely carry out cause investigation and judgment, and carry out relevant maintenance or manual regulation on the building equipment according to the requirement, thereby ensuring the safe and stable operation of the building equipment and playing the roles of energy conservation, low carbon and environmental protection; the specific analysis process of the energy consumption decision management analysis is as follows:
setting a consumption detection period, preferably fifteen minutes; setting a plurality of consumption detection points in the consumption detection period, wherein the time intervals between two adjacent groups of consumption detection points are the same; the energy consumption rate of the building equipment at all consumption detection points is acquired, wherein the energy consumption rate is a data value representing the amount of electricity consumed in unit time, and the larger the energy consumption rate is, the faster the electricity consumption rate of the building equipment at the corresponding moment is; establishing a consumption rate set for all the energy consumption rates of the consumption detection period; summing up the consumption speed sets, calculating and taking an average value to obtain a consumption speed detection value, acquiring a corresponding preset consumption speed detection value range based on the current operation mode of the building equipment, and performing numerical comparison on the consumption speed detection value and the preset consumption speed detection value range;
if the consumption speed detection value is not in the preset consumption speed detection value range, indicating that the energy consumption condition of the building equipment is abnormal, generating an energy consumption performance disqualification signal; if the consumption speed detection value is in the preset consumption speed detection value range, calculating the difference value between the subset with the largest value and the subset with the smallest value in the consumption speed set to obtain a consumption speed difference value, wherein the larger the consumption speed difference value is, the larger the energy consumption fluctuation amplitude of the building equipment in the consumption detection period is; calculating a difference value between the consumption speed detection value and the median value of a preset consumption speed detection value range, taking an absolute value to obtain a consumption speed deviation value, and carrying out weighting summation on the consumption speed deviation value HP and the consumption speed difference value HW through an energy consumption preliminary analysis formula HX=a1 x HP+a2 x HW to obtain a consumption speed evaluation value HX;
wherein a1 and a2 are preset weight coefficients, and a2 is more than a1 and more than 1; and, the value of the consumption speed checking and evaluating value HX is in a direct proportion relation with the consumption speed deviation value HP and the consumption speed difference value HW, the larger the values of the consumption speed deviation value HP and the consumption speed difference value HW are, the larger the values of the consumption speed checking and evaluating value HX are, which indicates that the worse the energy consumption performance of the building equipment in the consumption speed checking period is, the larger the probability of abnormality is; and comparing the consumption speed evaluation value HX with a corresponding preset consumption speed evaluation threshold value, and if the consumption speed evaluation value HX exceeds the preset consumption speed evaluation threshold value, generating an energy consumption performance disqualification signal.
Further, if the consumption rate evaluation value HX does not exceed the preset consumption rate evaluation threshold, establishing a rectangular coordinate system in the first quadrant with time as the X axis and energy consumption rate as the Y axis, drawing a plurality of energy consumption evaluation points in the rectangular coordinate system based on the energy consumption rates of all the consumption detection points, connecting two adjacent groups of energy consumption evaluation points through line segments, and marking the connecting line segments as energy consumption lifting line segments; drawing a straight line which is parallel to the X axis and intersects with the energy consumption lifting line segment in a rectangular coordinate system, marking the straight line as a horizontal tangent line, and marking an acute angle of an included angle formed by the energy consumption lifting line segment and the corresponding horizontal tangent line as a consumption change angle condition value; the larger the value of the consumption change angle condition value is, the faster the energy consumption change of the building equipment in the corresponding interval duration is, and the more abnormal the energy consumption performance is;
comparing the consumption change angle condition value with a corresponding preset consumption change angle condition threshold value, and marking the corresponding consumption change angle condition value as consumption change angle excess value if the consumption change angle condition value exceeds the preset consumption change angle condition threshold value, which indicates that the energy consumption change of the building equipment is faster in the corresponding interval time; obtaining the number of consumption change angle excess values in the consumption detection period, dividing the number of consumption change angle excess values by the number of energy consumption lifting line segments to obtain consumption excess evaluation values, and carrying out summation calculation on all consumption change angle condition values and taking an average value to obtain a consumption angle average value;
performing numerical calculation on the consumption super evaluation value GF and the consumption angle average value GP through an energy consumption normalization analysis formula GX=ht1 and GF+ht2 to obtain a consumption speed fine evaluation value GX; wherein, ht1 and ht2 are preset weight coefficients, and ht1 is more than ht2 and more than 0; and, the larger the value of the consumption speed fine evaluation value GX is, the worse the energy consumption performance condition of the construction equipment in the consumption detection period is indicated; comparing the consumption speed fine evaluation value GX with a corresponding preset consumption speed fine evaluation threshold value, and if the consumption speed fine evaluation value exceeds the preset consumption speed fine evaluation threshold value, indicating that the energy consumption performance condition of the building equipment in the consumption detection period is poor, generating an energy consumption performance failure signal; if the consumption speed fine evaluation value GX does not exceed the preset consumption speed fine evaluation threshold value, the energy consumption performance condition of the building equipment in the consumption detection period is good, and an energy consumption performance qualified signal is generated.
Embodiment two: as shown in fig. 2, the difference between the present embodiment and embodiment 1 is that the intelligent control platform is in communication connection with the optimization efficiency decision module, and the optimization efficiency decision module collects the time when the building equipment optimization control module obtains the matching abnormal signal, and marks the time as the optimization primary table time; the time when the building equipment optimization control module finishes the regulation and control of all parameters to be regulated is collected, and the time is marked as the optimization last table time; performing time difference calculation on the optimized last table time and the optimized initial table time to obtain optimal operation time; it should be noted that, the larger the value of the optimal operation duration is, the lower the efficiency of the corresponding optimal control process is, and the slower the operation recovery process of the building equipment is;
the corresponding target operation time length is called from the intelligent control platform, the optimal operation time length is compared with the target operation time length in a numerical value mode, if the optimal operation time length exceeds the target operation time length, the efficiency of the corresponding optimal control process is judged to be low, and an optimal low-efficiency signal is generated; if the optimal running time length does not exceed the target running time length, judging that the corresponding optimal control process is high in efficiency, generating an optimal high-efficiency signal, and accurately judging the optimal control efficiency of the building equipment optimal control module so as to adjust targeted control measures; and the optimized high-efficiency signal or the optimized low-efficiency signal is sent to the intelligent control platform, and the intelligent control platform stores the quantity of the optimized control processes corresponding to the optimized high-efficiency signal or the optimized low-efficiency signal together.
Further, the target operation duration is obtained by analysis of a target operation time generation module, and the target operation time generation module is in communication connection with the intelligent control platform so as to send the generated target operation duration to the intelligent control platform for storage; the operation process of the target time-running generation module is as follows:
acquiring all current parameters to be adjusted of the building equipment, and presetting each group of operation parameters of the building equipment to respectively correspond to a group of operation difficulty values, wherein the operation difficulty values are all larger than zero; in addition, the operation and regulation difficulty value is preset by a manager and is recorded and stored in the intelligent control platform, and the larger the recovery difficulty of the corresponding operation parameters is, the larger the value of the operation and regulation difficulty value matched with the operation and regulation difficulty value is; marking the deviation value of the parameter disturbance data corresponding to the parameter to be adjusted compared with the corresponding preset parameter disturbance data range as parameter to be adjusted data, multiplying the parameter to be adjusted data by the corresponding operational tuning difficulty value to obtain a parameter adjustment evaluation value corresponding to the parameter to be adjusted, and carrying out summation calculation on the parameter adjustment evaluation values of all the current parameters to be adjusted of the building equipment to obtain a parameter adjustment evaluation value;
a plurality of groups of preset reference analysis value ranges are preset in advance, and each group of preset reference analysis value ranges corresponds to a group of reference optimization time length respectively; and all the visit optimization time lengths are preset by a manager and recorded and stored in the intelligent management and control platform, and the larger the value of the preset visit evaluation value range is, the larger the value of the visit optimization time length matched with the preset visit evaluation value range is; and comparing the reference evaluation value with all preset reference evaluation value ranges one by one, marking the preset reference evaluation value range containing the reference evaluation value as a target reference evaluation range, marking the reference optimization time length corresponding to the target reference evaluation range as target operation time length, and transmitting the target operation time length to an optimization efficiency decision module through an intelligent management and control platform, so that data support is provided for the analysis process of the optimization efficiency decision module.
Embodiment III: as shown in fig. 3, the difference between the present embodiment and embodiments 1 and 2 is that the intelligent control platform is in communication connection with a comprehensive evaluation module, and the comprehensive evaluation module is configured to set an evaluation period, preferably, the evaluation period is five days; the method comprises the steps of obtaining the quantity corresponding to the optimized high-efficiency signal and the optimized low-efficiency signal of the building equipment in the operation period, marking the quantity as an excellent high-number measured value and an excellent low-number measured value respectively, and carrying out ratio calculation on the excellent low-number measured value and the excellent high-number measured value to obtain an optimized low-table value; subtracting the target operation time length from the optimal operation time length corresponding to the optimized low-efficiency signal to obtain optimal time difference data, calculating the ratio of the optimal time difference data to the corresponding target operation time length to obtain an optimal time occupation value, summing all the optimal time occupation values in the operation period, calculating and taking an average value to obtain an optimal time analysis value;
calculating the optimal low number measured value WY, the optimal low table value WT and the optimal time analysis value WK according to a formula WR=fy1 xWY+fy2 xWT+fy3 xWK to obtain an operation evaluation table value WR, wherein fy1, fy2 and fy3 are preset proportionality coefficients, and fy1 is more than fy3 and more than fy2 is more than 0; and the larger the value of the operation and assessment table condition value WR is, the worse the optimal control effect on the building equipment is, and the manager is required to strengthen equipment supervision and system optimization adjustment; comparing the operation evaluation condition value WR with a preset operation evaluation condition threshold value, and generating a control early warning signal if the operation evaluation condition value WR exceeds the preset operation evaluation condition threshold value, which indicates that the optimizing control effect on the building equipment is poor;
if the operation and evaluation table condition value does not exceed the preset operation and evaluation table condition threshold value, the times of generating the energy consumption performance failure signals by the building equipment in the operation and evaluation period are obtained and marked as consumption table different frequency values, and the time difference calculation is carried out on the generation moments of the two adjacent groups of energy consumption performance failure signals to obtain consumption difference values; the larger the value of the differential consumption difference value is, the smaller the interval duration between the generation moments of the adjacent two groups of energy consumption performance disqualification signals is; comparing the consumption difference value with a preset consumption difference time threshold value, marking the corresponding consumption difference value as consumption difference time analysis value if the consumption difference value exceeds the preset consumption difference time threshold value, and calculating the ratio of the number of consumption difference time analysis values to obtain consumption difference analysis values;
summing all consumption difference values in the operation and evaluation period, calculating and taking an average value to obtain a consumption difference condition value, and carrying out numerical calculation on the consumption difference condition value QW, the consumption difference analysis value QD and the consumption meter difference frequency value QK through a formula QY= (kp2+kp3 QK)/(kp1 QW+0.682), wherein kp1, kp2 and kp3 are preset proportionality coefficients, and kp2 is more than kp1 and more than kp3 is more than 0; and, the larger the value of the operational condition value QY is, the more abnormal the operation condition of the building equipment in the operational period is, and the more the manager needs to strengthen the equipment supervision; and comparing the operation and assessment condition value QY with a preset operation and assessment condition threshold value, and generating a control early warning signal if the operation and assessment condition value QY exceeds the preset operation and assessment condition threshold value.
Further, the comprehensive operation and assessment module sends the control early warning signal to the building supervision end through the intelligent control platform, the building supervision end sends corresponding early warning when receiving the control early warning signal, and the manager should timely adjust the targeted control measures of the building equipment in the follow-up process, such as increasing the maintenance frequency and maintenance time of the building equipment, or strengthening the knowledge training and building equipment supervision of the manager, and improving and optimizing the system functions continuously, thereby ensuring the safe and stable operation of the building equipment, playing a role in energy conservation, low carbon and environmental protection, and improving the intelligent degree obviously.
The working principle of the invention is as follows: when the system is used, the operation mode matching evaluation module analyzes the operation parameter performance condition of the building equipment based on the current operation mode of the building equipment, so that parameters to be adjusted are identified, a matching abnormal signal or a matching normal signal is generated, and when the matching abnormal signal is generated, the corresponding operation parameters of the building equipment are automatically adjusted through the building equipment optimization control module, so that the operation optimization control of the building equipment is realized, and the safe operation of the building equipment is ensured, and meanwhile, the low-carbon and energy-saving effects are realized; when the matching normal signal is generated, the building equipment is subjected to energy consumption decision management analysis through the operation energy consumption detection analysis module, so that an energy consumption performance qualified signal or an energy consumption performance unqualified signal is generated, effective detection and accurate feedback of the operation energy consumption of the building equipment are realized, so that corresponding management personnel can timely conduct cause investigation and judgment and maintain or manually regulate and control the building equipment, safe and stable operation of the building equipment is guaranteed, the effects of energy conservation, low carbon and environmental protection are achieved, the intelligent level and the automation level are remarkably improved, and the equipment management difficulty of a green low-carbon building is reduced.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation. The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (8)
1. The intelligent control optimizing management system for the building equipment suitable for the green low-carbon building is characterized by comprising an intelligent control platform, an operation mode matching evaluation module, an optimizing control module for the building equipment and an operation energy consumption management decision module; the intelligent control platform acquires the current operation mode of the building equipment and sends the current operation mode of the building equipment to an operation mode matching evaluation module; the operation mode matching evaluation module analyzes the operation parameter performance status of the building equipment based on the current operation mode of the building equipment, so as to identify parameters to be adjusted and generate a matching abnormal signal or a matching normal signal;
the operation mode matching evaluation module sends a matching abnormal signal and all parameters to be adjusted to the building equipment optimizing control module through the intelligent management and control platform, and the building equipment optimizing control module automatically adjusts corresponding operation parameters of the building equipment when receiving the matching abnormal signal so as to optimally control the operation of the building equipment; and the operation mode matching performance evaluation module sends a matching performance normal signal to the operation energy consumption detection and analysis module through the intelligent management and control platform, and the operation energy consumption detection and analysis module carries out energy consumption decision management analysis on the building equipment so as to generate an energy consumption performance qualified signal or an energy consumption performance unqualified signal and sends the energy consumption performance unqualified signal to the building monitoring end through the intelligent management and control platform.
2. The intelligent control optimization management system for building equipment suitable for a green low-carbon building according to claim 1, wherein the specific operation process of the operation mode matching evaluation module comprises the following steps:
acquiring real-time data of all operation parameters to be monitored in the operation process of the building equipment, acquiring preset standard data corresponding to all operation parameters based on the current operation mode of the building equipment, performing difference value calculation on the real-time data of the corresponding operation parameters and the corresponding preset standard data, taking absolute values to obtain parameter disturbance data, and performing numerical comparison on the parameter disturbance data and the preset parameter disturbance data range of the corresponding operation parameters;
if the parameter disturbance data are located in the preset parameter disturbance data range, marking the corresponding operation parameters of the building equipment as the optimal table parameters; if the parameter disturbance data are not in the preset parameter disturbance data range, marking the corresponding operation parameters of the building equipment as parameters to be adjusted; if the parameters to be adjusted exist in the current operation process of the building equipment, generating a matchability abnormal signal; if the parameters to be adjusted do not exist in the current operation process of the building equipment, generating a normal signal of matching property; and sending the abnormal signal or normal signal to the intelligent management and control platform.
3. The intelligent control and optimization management system for the building equipment suitable for the green low-carbon building according to claim 1, wherein the specific analysis process of the energy consumption decision management analysis is as follows:
setting a consumption detection period, setting a plurality of consumption detection time points in the consumption detection period, wherein the time intervals between two adjacent groups of consumption detection time points are the same; collecting energy consumption rates of the building equipment at all consumption detection points, and establishing a consumption rate set for all the energy consumption rates of the consumption detection period; summing up the consumption speed sets, calculating and taking an average value to obtain a consumption speed detection value, acquiring a corresponding preset consumption speed detection value range based on the current operation mode of the building equipment, and generating an energy consumption performance failure signal if the consumption speed detection value is not in the preset consumption speed detection value range;
if the consumption speed detection value is in the preset consumption speed detection value range, carrying out difference calculation on a subset with the largest value and a subset with the smallest value in the consumption speed set to obtain a consumption speed difference value; performing difference calculation on the consumption speed detection value and the median value of the preset consumption speed detection value range, taking an absolute value to obtain a consumption speed deviation value, and performing weighted summation calculation on the consumption speed deviation value and the consumption speed difference value to obtain a consumption speed evaluation value; and if the consumption rate evaluation value exceeds a preset consumption rate evaluation threshold value, generating an energy consumption performance disqualification signal.
4. The intelligent control optimizing management system for building equipment suitable for green low-carbon building according to claim 3, wherein if the consumption speed evaluation value does not exceed a preset consumption speed evaluation threshold value, a rectangular coordinate system positioned in a first quadrant is established by taking time as an X axis and energy consumption rate as a Y axis, a plurality of energy consumption evaluation points are drawn in the rectangular coordinate system based on the energy consumption rates of all consumption inspection points, two adjacent groups of energy consumption evaluation points are connected through line segments, and the connecting line segments are marked as energy consumption lifting line segments;
drawing a straight line which is parallel to the X axis and intersects with the energy consumption lifting line segment in a rectangular coordinate system, marking the straight line as a horizontal tangent line, and marking an acute angle of an included angle formed by the energy consumption lifting line segment and the corresponding horizontal tangent line as a consumption change angle condition value; if the consumption change angle condition value exceeds a preset consumption change angle condition threshold value, marking the corresponding consumption change angle condition value as consumption change angle excess value; dividing the number of the consumption change angle excess values by the number of the energy consumption lifting line segments to obtain consumption excess evaluation values, summing all consumption change angle condition values, and taking an average value to obtain a consumption angle average value;
performing numerical calculation on the consumption super evaluation value and the consumption angle average value to obtain a consumption speed fine evaluation value, and if the consumption speed fine evaluation value exceeds a preset consumption speed fine evaluation threshold value, generating an energy consumption performance disqualification signal; and if the consumption speed fine evaluation value does not exceed the preset consumption speed fine evaluation threshold value, generating an energy consumption performance qualification signal.
5. The intelligent control optimization management system for the building equipment, which is applicable to the green low-carbon building, according to claim 2, is characterized in that the intelligent control platform is in communication connection with an optimization efficiency decision module, and the optimization efficiency decision module acquires the time when the building equipment optimization control module acquires the matching abnormal signal and marks the time as an optimization initial table time; the time when the building equipment optimization control module finishes the regulation and control of all parameters to be regulated is collected, and the time is marked as the optimization last table time;
calculating the time difference between the optimal last table time and the optimal initial table time to obtain an optimal running time length, calling a corresponding target running time length from the intelligent control platform, performing numerical comparison on the optimal running time length and the target running time length, and judging that the corresponding optimal control process is low in efficiency and generating an optimal low-efficiency signal if the optimal running time length exceeds the target running time length; if the optimal running time length does not exceed the target running time length, judging that the corresponding optimal control process is high in efficiency and generating an optimal high-efficiency signal; and the optimized high-efficiency signal or the optimized low-efficiency signal is sent to the intelligent control platform, and the intelligent control platform stores the quantity of the optimized control processes corresponding to the optimized high-efficiency signal or the optimized low-efficiency signal together.
6. The intelligent control and optimization management system for the building equipment, which is applicable to the green low-carbon building, according to claim 5, is characterized in that the target operation and adjustment time length is obtained by analysis of a target operation and adjustment time length generation module, and the target operation and adjustment time length generation module is in communication connection with the intelligent control platform so as to send the generated target operation and adjustment time length to the intelligent control platform for storage; the operation process of the target time-running generation module comprises the following steps:
acquiring all current parameters to be adjusted of the building equipment, and presetting each group of operation parameters of the building equipment to respectively correspond to a group of operation difficulty values, wherein the operation difficulty values are all larger than zero; marking the deviation value of the parameter disturbance data corresponding to the parameter to be adjusted compared with the corresponding preset parameter disturbance data range as parameter to be adjusted data, multiplying the parameter to be adjusted data by the corresponding operational tuning difficulty value to obtain a parameter adjustment evaluation value corresponding to the parameter to be adjusted, and carrying out summation calculation on the parameter adjustment evaluation values of all the current parameters to be adjusted of the building equipment to obtain a parameter adjustment evaluation value;
a plurality of groups of preset reference analysis value ranges are preset in advance, and each group of preset reference analysis value ranges corresponds to a group of reference optimization time length respectively; and comparing the reference evaluation value with all the preset reference evaluation value ranges one by one, marking the preset reference evaluation value range containing the reference evaluation value as a target reference evaluation range, and marking the reference optimization time length corresponding to the target reference evaluation range as a target operation and adjustment time length.
7. The intelligent control optimization management system for the building equipment suitable for the green low-carbon building according to claim 5, wherein the intelligent control platform is in communication connection with a comprehensive operation and evaluation module, the comprehensive operation and evaluation module is used for setting an operation and evaluation period, obtaining the quantity corresponding to the optimized high-efficiency signal and the optimized low-efficiency signal of the building equipment in the operation and evaluation period, marking the optimized high-efficiency signal and the optimized low-efficiency signal as an excellent high-quality measured value and an excellent low-quality measured value respectively, and calculating the ratio of the excellent low-quality measured value to the excellent high-quality measured value to obtain an optimized low-table value;
subtracting the target operation time length from the optimal operation time length corresponding to the optimized low-efficiency signal to obtain optimal time difference data, calculating the ratio of the optimal time difference data to the corresponding target operation time length to obtain an optimal time occupation value, summing all the optimal time occupation values in the operation period, calculating and taking an average value to obtain an optimal time analysis value; and carrying out numerical calculation on the high-low numerical value, the optimized low table value and the optimal time analysis value to obtain a running evaluation table condition value, and generating a control early warning signal if the running evaluation table condition value exceeds a preset running evaluation table condition threshold value.
8. The intelligent control and optimization management system for the building equipment suitable for the green low-carbon building according to claim 7, wherein if the operation and evaluation condition value does not exceed a preset operation and evaluation condition threshold value, the number of times that the building equipment generates the energy consumption performance failure signal in the operation and evaluation period is obtained and marked as an energy consumption performance failure signal different frequency value, and the time difference calculation is performed on the generation moments of the two adjacent groups of energy consumption performance failure signals to obtain an energy consumption difference value; if the consumption difference value exceeds the preset consumption difference time threshold value, marking the corresponding consumption difference value as consumption difference time analysis value, and carrying out ratio calculation on the number of consumption difference time analysis values and the number of consumption difference value to obtain consumption difference analysis values;
and carrying out summation calculation on all consumption difference values in the operation and evaluation period, taking an average value to obtain a consumption difference condition value, carrying out numerical calculation on the consumption difference condition value, the consumption difference analysis value and the consumption meter difference frequency value to obtain an operation and evaluation fine condition value, generating a control early warning signal if the operation and evaluation fine condition value exceeds a preset operation and evaluation fine condition threshold value, and sending the control early warning signal to a building monitoring end through an intelligent control platform.
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