Energy-saving control management system based on public building

Abstract

The invention relates to the field of energy-saving management, in particular to an energy-saving control management system based on a public building, and the system comprises a region monitoring module which is used for periodically responding to a parameter standard condition so as to determine whether each target control parameter meets a control requirement or not; the standard optimization module is used for performing parameter standard optimization on each target control parameter; the area evaluation module is used for periodically responding to an area evaluation condition to determine a parameter estimation strategy of the target management area; the pre-estimation analysis module is used for executing the parameter pre-estimation strategy determined by the region evaluation module so as to determine a pre-estimation index of the target optimization parameter; and the parameter analysis module is used for determining a parameter control strategy of each target optimization parameter in response to the parameter evaluation condition, and adjusting the parameter control coefficient of the target optimization parameter, so that the effectiveness of an energy-saving control result is improved.

Description

Technical Field

[0001] The present invention relates to the field of energy-saving management, and particularly to an energy-saving control management system based on public buildings. Background Art

[0002] Public building areas often become the main areas of energy consumption due to their large scale and strong personnel mobility. Energy-saving control management can effectively improve the problem of energy consumption. However, due to the service function of public building areas, the actual comfort level needs to be ensured. Therefore, it is necessary to adjust various environmental parameters in real time according to the actual situation of public building areas. However, in the actual control process, the various data obtained for public building areas are continuously and multi-sourced, interfering with each other. Therefore, how to eliminate the interference of external influencing factors on the energy-saving control process to ensure the control effect of the environmental parameters of public buildings is an urgent problem for those skilled in the art.

[0003] Chinese Patent Publication No. CN108151235A discloses an energy-saving air-conditioning system with adaptive and sub-region control for large public buildings. The system includes a control system, a water system, a wind system, and an air handling unit. The water system exchanges heat with the circulating air in the wind system through the air handling unit, and the wind system supplies heat and cooling to the indoor area. This system sets two operating modes, heating and cooling. In winter, the heater is started to operate in the heating mode, and in summer, the cooler is started to operate in the cooling mode through the operation mode converter. Multiple heaters and coolers are provided, and the number of operating units is controlled according to different loads. When in partial load, the number of operating units of some heaters or coolers can be shut down and started to keep the system operating at the best efficiency and achieve the effect of economic operation while maintaining the best efficiency. However, the above solution has the following problems: It fails to effectively eliminate the interference of external influencing factors in the actual management area on the control process, resulting in low timeliness and effectiveness of the adjustment operation of environmental parameters. Summary of the Invention

[0004] Therefore, the present invention provides an energy-saving control management system based on public buildings to overcome the problems in the prior art that the interference of external influencing factors in the actual management area on the energy-saving control process cannot be effectively eliminated, resulting in low timeliness and effectiveness of the adjustment operation of environmental parameters.

[0005] To achieve the above object, the present invention provides an energy-saving control management system based on public buildings, including:

[0006] A regional monitoring module for obtaining various target control parameters of a target management area and periodically responding to parameter standard conditions to determine whether each target control parameter meets the control requirements;

[0007] A standard optimization module, which is connected to the area monitoring module, is used to optimize the parameter standards for each target control parameter and obtain the preferred standard values of each target control parameter;

[0008] An area evaluation module, which is connected to the area monitoring module, is used to periodically respond to area evaluation conditions to determine that the parameter estimation strategy for each key analysis parameter is to determine the data estimation strategy based on the area distribution index, or to determine the interference change index based on the change effectiveness coefficient and the area change parameter;

[0009] The data estimation strategy is to determine the dynamic interference index based on the control fluctuation coefficient and the reference change range of each deviation analysis set, or to determine the regulation radiation index based on the control execution coefficient and the proportion of the deviation area;

[0010] A prediction analysis module, which is connected to the area evaluation module and includes a first prediction analysis unit and a second prediction analysis unit, is used to execute the parameter prediction strategy determined by the area evaluation module to determine the prediction index of the target control parameter;

[0011] A parameter analysis module, which is connected to the prediction analysis module, is used to respond to parameter evaluation conditions to determine the parameter control strategy for each target optimization parameter and adjust the parameter control coefficient of the target optimization parameter;

[0012] The prediction index includes a dynamic interference index, an interference change index, and an interference change index, and the parameter control coefficient includes a proportional control coefficient, an integral control coefficient, and a differential control coefficient.

[0013] Further, the parameter standard condition responded by the area monitoring module is that if the standard difference index of any target control parameter is less than or equal to the preset standard difference index, it is determined that the target control parameter meets the control requirement, and the target control parameter is recorded as a conventional analysis parameter;

[0014] The parameter standard condition corresponding to the area monitoring module is that if the standard difference index of any target control parameter is greater than the preset standard difference index, it is determined that the target control parameter does not meet the control requirement, and the target control parameter is recorded as a key analysis parameter of the conventional analysis parameter;

[0015] The standard difference index is determined according to the area reference difference degree and the proportion of the deviation area.

[0016] Further, the standard optimization module determines the preferred standard value of each target control parameter based on formula (1),

[0017]

[0018] where, fj (X) is the j-th objective optimization function, is the optimal solution of the j-th objective optimization function of the objective control parameter, n is the number of objective optimization functions, and X is the objective control parameter for parameter standard optimization.

[0019] Further, the region evaluation condition responded by the region evaluation module is that the proportion of the deviation region of a key analysis parameter is greater than the preset deviation region proportion, then it is determined that the first prediction analysis unit determines the data prediction strategy of this key analysis parameter based on the region distribution index;

[0020] The region distribution index is determined according to the deviation dispersion coefficient and the reference deviation interference coefficient. The region distribution index has a negative correlation with the deviation dispersion coefficient, and the region distribution index has a positive correlation with the reference deviation interference coefficient.

[0021] Further, the first prediction condition responded by the first prediction analysis unit is that the region distribution index is greater than the preset region distribution index, then the dynamic interference index is determined based on the control fluctuation coefficient of each deviation analysis set and the reference change range;

[0022] The dynamic interference index has a positive correlation with the control fluctuation coefficient and the reference change range respectively;

[0023] The deviation analysis set is determined by dividing the deviation region based on the region interval distance and the interference parameter correlation.

[0024] Further, the first prediction condition responded by the first prediction analysis unit is that the region distribution index is less than or equal to the preset region distribution index, then the regulation radiation index is determined based on the control execution coefficient and the proportion of the deviation region, and it is determined whether to perform a reduction adjustment on the regulation radiation index according to the interference stability index;

[0025] The radiation regulation condition responded by the first prediction analysis unit is that the interference stability index is greater than the preset interference stability index, then the regulation radiation index is increased according to the interference stability index;

[0026] The increase value of the regulation radiation index has a positive correlation with the interference stability index.

[0027] Further, the region evaluation condition corresponding to the region evaluation module is that the proportion of the deviation region of a key analysis parameter is less than or equal to the preset deviation region proportion, then it is determined that the second prediction analysis unit determines the region change parameter based on the reference change range of each interference parameter, and determines the interference change index based on the change effective coefficient and the region change parameter;

[0028] The interference change index has a positive correlation with the change effective coefficient and the region change parameter respectively.

[0029] Further, the parameter evaluation condition for which the parameter analysis module responds is that the dynamic interference index of the target optimization parameter is greater than the preset dynamic interference index, and it is determined that the proportional control coefficient is increased based on the execution standard difference index and the dynamic interference index;

[0030] The increased value of the proportional control coefficient has a positive correlation with the execution standard difference index and the dynamic interference index.

[0031] Further, the parameter evaluation condition for which the parameter analysis module responds is that the interference change index of the target optimization parameter is greater than the preset interference change index, and it is determined that the integral control coefficient is increased based on the interference change index and the reference change amplitude;

[0032] The increased value of the integral control coefficient has a positive correlation with the interference change index and the reference change amplitude.

[0033] Further, the parameter evaluation condition for which the parameter analysis module responds is that the regulation radiation index of the target optimization parameter is greater than the preset regulation radiation index, and it is determined that the derivative control coefficient is increased based on the regulation radiation index;

[0034] The increased value of the derivative control coefficient has a positive correlation with the regulation radiation index.

[0035] Compared with the prior art, the beneficial effects of the present invention are as follows. The technical solution of the present invention determines the parameter prediction strategy of the target management area according to the deviation area ratio, predicts the change conditions of various target control parameters and interference parameters in the target management area in the next control evaluation period, obtains the prediction index, and determines the parameter control strategy according to the actual state of the prediction index, and adjusts with the parameter control coefficient to ensure that the interference of external influencing factors in the actual management area on the energy-saving control process can be effectively eliminated. The present invention improves the effectiveness of the executed energy-saving control result.

[0036] Further, in the present invention, the standard optimization module optimizes the preferred standard values of various target control parameters, so that the determined preferred standard values ensure the comfort level of the target management area while ensuring the energy-saving effect of the target management area, and further ensure that the subsequent determination result of the deviation area and the prediction analysis process can effectively take into account the energy-saving effect and the comfort level. The present invention improves the effectiveness of the executed energy-saving control result.

[0037] Furthermore, in the present invention, a parameter estimation strategy for determining the target management area based on the proportion of the deviation area is adopted, enabling the analysis of the deviation causes in the target management area and the targeted analysis and estimation of the index, so as to estimate the changes in the target control parameters and interference parameters for the subsequent control evaluation period, making the determined estimation index more in line with the actual working scenario, ensuring the accuracy of the estimation result, and further ensuring the effectiveness of the adjustment result of the parameter control coefficient.

[0038] Furthermore, in the present invention, when the proportion of the deviation area in the target management area is relatively large, a data estimation strategy is determined according to the regional distribution index. When the proportion of the deviation area is relatively large, it indicates that the current target management area is greatly affected by external interference, resulting in the failure of the current regulation of the target control parameters. At this time, further analysis is carried out on the current interference situation. When the regional distribution index is relatively large, it indicates that the deviation areas are relatively concentrated. By dividing several deviation analysis sets, a dynamic interference index is determined based on the changes in the interference factors of each set and the regulation frequency of the corresponding target control parameters, that is, the dynamic change situation of the target control parameter.

[0039] Furthermore, in the present invention, when the regional distribution index is relatively small, it indicates that the deviation areas are relatively dispersed at this time. At this time, there are deviations not due to the same interference factors. However, due to the relatively large proportion of the deviation area, the regulation process may cause long-term effects. The regulation radiation index is determined by controlling the execution coefficient and the proportion of the deviation area, that is, the interference situation of the adjustment of the target control parameter in the current parameter monitoring period on the target control parameter in the subsequent period. The present invention improves the effectiveness of the implemented energy-saving control result.

[0040] Furthermore, in the present invention, when the proportion of the deviation area in the target management area is relatively small, there are relatively few deviation areas at this time. The reason for the deviation of the target control parameter in the above-mentioned deviation area is often that the interference parameter in this type of deviation area changes, and the target control parameter in the deviation area is easily affected by the changing interference parameter. Therefore, an interference change index is determined based on the change effective coefficient and the regional change parameter to indicate the change situation of the subsequent interference parameter, enabling the more timely estimation of the change situation of the interference parameter, ensuring the more accurate adjustment of the parameter control coefficient in the subsequent period, and thus improving the effectiveness of the implemented energy-saving control result. Description of the Drawings

[0041] Figure 1 It is a module connection diagram of the energy-saving control management system based on public buildings according to the present invention;

[0042] Figure 2 It is a flowchart of the regional monitoring module of the present invention for determining whether each target control parameter meets the control requirements in response to the parameter standard conditions;

[0043] Figure 3 This is a flowchart of the parameter prediction strategy for the target management area determined by the regional evaluation module of the present invention in response to the regional evaluation conditions;

[0044] Figure 4 This is a flowchart of the parameter control strategy for determining the target optimization parameters of each item by the parameter analysis module of the present invention in response to the parameter evaluation conditions. Detailed implementation manners

[0045] In order to make the objectives and advantages of the present invention clearer, the present invention will be further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0046] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principle of the present invention and do not limit the protection scope of the present invention.

[0047] It should be noted that in the description of the present invention, the terms indicating directions or positional relationships such as "upper", "lower", "left", "right", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings. This is only for convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention.

[0048] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0049] Please refer to Figures 1 to 4 As shown, the present invention provides an energy-saving control and management system based on public buildings, including:

[0050] A regional monitoring module for obtaining the target control parameters of the target management area and periodically responding to the parameter standard conditions to determine whether the target control parameters meet the control requirements;

[0051] A standard optimization module connected to the regional monitoring module for optimizing the parameter standards for each target control parameter to obtain the preferred standard values of each target control parameter;

[0052] An area evaluation module, which is connected to the area monitoring module, is used to periodically respond to area evaluation conditions to determine that the parameter estimation strategy for each key analysis parameter is to determine the data estimation strategy based on the area distribution index, or to determine the interference change index based on the change effectiveness coefficient and the area change parameter;

[0053] The data estimation strategy is to determine the dynamic interference index based on the control fluctuation coefficient of each deviation analysis set and the reference change range, or to determine the regulation radiation index based on the control execution coefficient and the proportion of the deviation area;

[0054] A prediction analysis module, which is connected to the area evaluation module, includes a first prediction analysis unit and a second prediction analysis unit, and is used to execute the parameter estimation strategy determined by the area evaluation module for each target control parameter to determine the prediction index of the target control parameter;

[0055] A parameter analysis module, which is connected to the prediction analysis module, is used to respond to parameter evaluation conditions to determine the parameter control strategy for each target optimization parameter and adjust the parameter control coefficient for the target optimization parameter;

[0056] The prediction index includes a dynamic interference index, an interference change index, and an interference change index, and the parameter control coefficient includes a proportional control coefficient, an integral control coefficient, and a differential control coefficient.

[0057] Among them, the present invention is used to optimize the environmental control system of public buildings, so that on the premise of ensuring that the environmental parameters of public buildings meet the comfort requirements, it meets the energy-saving requirements. Due to the lag in the regulation of environmental parameters, the present invention can ensure the control optimization effect of the environmental control system by optimizing the control coefficient in the real-time control process. The public building area corresponding to the environmental control system that needs to be controlled and optimized is recorded as the target management area, and the environmental parameters that need to be controlled are recorded as the target control parameters. The target control parameters in the present invention include but are not limited to: environmental temperature, relative humidity, and CO2 concentration. In the present invention, the PID control method is used to adjust the target control parameters, and the parameter control coefficients all correspond to the control coefficients of the proportional control link, integral control link, and differential control link that execute PID control in the control process;

[0058] In the present invention, several control management records are applied. Any control management record records at least once the deviation parameter, deviation area ratio, area distribution index, interference parameter correlation, area interval distance, interference stability index, dynamic interference index, interference change index, and regulation radiation index during the control optimization process of the target control parameters for the target management area. And each control management record corresponds to a qualified mark, and the qualified mark records whether the timeliness and effectiveness of the adjustment operation for the target control parameters meet the user requirements. It can be understood that the user can determine whether the timeliness and effectiveness of the adjustment operation for the target control parameters meet the requirements according to the self-set indicators. For example, the self-set indicators can be, but are not limited to, the adjustment effectiveness index, and the adjustment lag index = obtained within the target management area.

[0059] Specifically, the parameter standard condition responded by the area monitoring module is that if the standard difference index of any one target control parameter is less than or equal to the preset standard difference index, it is determined that this target control parameter meets the control requirements, and this target control parameter is recorded as a conventional analysis parameter;

[0060] The parameter standard condition corresponding to the area monitoring module is that if the standard difference index of any one target control parameter is greater than the preset standard difference index, it is determined that this target control parameter does not meet the control requirements, and this target control parameter is recorded as a key analysis parameter;

[0061] The standard difference index is determined according to the area reference difference degree and the deviation area ratio.

[0062] Among them, the target management area is divided into several spatial areas, and the floor areas corresponding to each spatial area are the same. The divided spatial areas are recorded as management sub-areas. The number of divided management sub-areas and the floor areas corresponding to each management sub-area can be set by the user according to the actual working scenario, which will not be elaborated here. Periodically collect each target control parameter for each management sub-area. In the present invention, a cyclic parameter monitoring period is applied. The duration of the parameter monitoring period can be determined by the user himself. The higher the requirements of the user for the timeliness and effectiveness of the adjustment operation for the target control parameters, the shorter the duration of the parameter monitoring period. A duration of the parameter monitoring period is provided, and the duration of the parameter monitoring period is 15 minutes. At the end of each parameter monitoring period, collect the values of each target control parameter for each management sub-area, and record them as the monitoring values of each target control parameter, and respond to the parameter standard conditions to determine whether each target control parameter meets the control requirements. In the present invention, sensors are used to obtain the monitoring values of each target control parameter. The present invention does not specifically limit the types and installation positions of the sensors used, which are easy to understand for those skilled in the art and will not be elaborated here;

[0063] For a single target control parameter, the standard difference index is the sum of the regional reference difference degree and the proportion of the deviation region. The regional reference difference degree = |regional control reference value - preferred standard value of this target control parameter| / preferred standard value of this target control parameter. The regional control reference value is the average value of the monitoring values of this target control parameter in each management sub-region within the target management region. The proportion of the deviation region = the number of deviation regions of this target control parameter within the target management region / the number of management sub-regions within the target management region. For a single management sub-region, if the deviation parameter of this management sub-region is greater than the preset deviation parameter, then this management sub-region is recorded as a deviation region. The deviation parameter = |monitoring parameter of this target control parameter in this management sub-region - preferred standard value of this target control parameter| / preferred standard value of this target control parameter;

[0064] For the values of the preset deviation parameter and the preset standard difference index, the user can determine them according to the actual working scenario. For example, the user can set them according to the control management records. The higher the requirements of the user for the timeliness and effectiveness of the adjustment operation of the target control parameter, the smaller the value of the preset deviation parameter, and the smaller the value of the preset standard difference index. A method for obtaining the value of the preset deviation parameter is provided. The minimum value of the deviation parameters of each deviation region in the control management records that meet the user's requirements for the timeliness and effectiveness of the adjustment operation of the target control parameter is recorded as the preset deviation parameter. A value of the preset deviation parameter is provided, and the value of the preset deviation parameter is 0.05. A method for obtaining the value of the preset standard difference index is provided. The minimum value of the standard difference indices of each key analysis parameter in the control management records that meet the user's requirements for the timeliness and effectiveness of the adjustment operation of the target control parameter is recorded as the preset standard difference index. A value of the preset standard difference index is provided, and the value of the preset standard difference index is 0.15.

[0065] Specifically, the standard optimization module determines the preferred standard value of each target control parameter based on formula (1),

[0066]

[0067] where f j (X) is the jth target optimization function, is the optimal solution of the jth target optimization function of the target control parameter, n is the number of target optimization functions, and X is the target control parameter for which parameter standard optimization is performed.

[0068] Among them, for a single target control parameter, the optimal solutions of each target optimization function are obtained If the target optimization function is the regional energy consumption function, the optimal solution is the numerical value of the target control parameter corresponding to the lowest energy consumption. If the target optimization function is the regional comfort function, the optimal solution is the numerical value of the target control parameter corresponding to the highest comfort level. At this time, the numerical value of the obtained target control parameter can only ensure that a single target optimization function reaches the optimal. The numerical value of the target control function obtained through formula (1) can obtain a relatively optimal solution among multiple target optimization functions, which can meet the needs of each target optimization function as much as possible. The obtained numerical value is recorded as the preferred standard value of this target control function;

[0069] In the present invention, the target optimization functions include the regional energy consumption function and the regional comfort function. The above two functions can be obtained according to the method of training the neural network BPNN, which is easy to understand for those skilled in the art. For example, the construction process of the regional energy consumption function: Obtain the target control parameters with different value ranges, and respectively form 100 combinations, representing the outdoor meteorological and indoor environmental conditions at different times of a certain day. Using DesignBuilder software, set the time step to 1 hour, and perform energy consumption simulations on the above 100 combination schemes. The simulation results are used as the training samples and test samples of the BPNN energy consumption model; Organize the data of the 100 combination schemes simulated by DesignBuilder software into an Excel table, randomly select 60 groups of data as training samples, and 40 groups of data as test samples to construct a BPNN prediction model, and record the constructed prediction model as the regional energy consumption function.

[0070] Specifically, the regional evaluation condition responded by the regional evaluation module is that the proportion of the deviation area of a key analysis parameter is greater than the preset deviation area proportion, then it is determined that the first prediction analysis unit determines the data prediction strategy of this key analysis parameter based on the regional distribution index;

[0071] The regional distribution index is determined according to the deviation dispersion coefficient and the reference deviation interference coefficient. The regional distribution index has a negative correlation with the deviation dispersion coefficient, and the regional distribution index has a positive correlation with the reference deviation interference coefficient.

[0072] Among them, the value of the preset deviation area proportion can be determined by the user according to the actual working scenario. For example, the user can set it according to the control management record, and provide a method for obtaining the value of the preset deviation area proportion. Record the control management record of determining the data prediction strategy based on the regional distribution index as the first prediction record, and record the minimum value of the deviation area proportion in the first prediction record that meets the requirements of the timeliness and effectiveness of the user's adjustment operation of the target control parameter as the preset deviation area proportion;

[0073] When determining the data prediction strategy for a single key analysis parameter based on the regional distribution index, this key analysis parameter is denoted as the predicted analysis parameter. The regional distribution index = ln(reference deviation interference coefficient / deviation dispersion coefficient). The deviation dispersion coefficient is the average number of the central points of the deviation regions existing within the preset analysis range of each deviation region corresponding to this predicted analysis parameter within the target management area. For a single deviation region, the preset analysis range is a circular region centered at the central point of this deviation region with a preset range length as the radius. The central points of each deviation region are the centroids of the occupied areas corresponding to each deviation region. The reference deviation interference coefficient is the average value of the regional interference coefficients of each deviation region corresponding to this predicted analysis parameter within the target management area.

[0074] For a single deviation region, the regional interference coefficient is the sum of the products of the interference degree coefficients of the interference parameters of this deviation region and the corresponding interference radiation coefficients. In the present invention, a cyclic interference monitoring period is applied, and the duration of the interference monitoring period can be determined by the user himself. The higher the requirements for the timeliness and effectiveness of the user's adjustment operation of the target control parameter, the shorter the duration of the interference monitoring period. A duration of the interference monitoring period is provided, and the duration of the interference monitoring period is 5 minutes. At the end of each interference monitoring period, the values of each interference parameter are obtained. For a single interference parameter, the interference degree coefficient = the maximum value of the value of this interference parameter obtained within the current parameter monitoring period / the maximum value of this interference parameter in the control management record. A determination method for the composition of the interference parameters for determining the regional interference coefficient and the interference radiation coefficients corresponding to each interference parameter is provided. For example, if the key analysis parameter is the environmental temperature of the target management area, the interference parameters of the deviation region include, but are not limited to: the outdoor temperature of the target management area, the outdoor wind speed, and the number of active personnel within the deviation region. When the interference parameter is the outdoor temperature of the target management area, the interference radiation coefficient has a negative correlation with the temperature radiation distance of the deviation region. For a single deviation region, the temperature radiation distance is the distance between this deviation region and the nearest sunlit wall surface. When the interference parameter is the outdoor wind speed of the target management area, the interference radiation coefficient has a negative correlation with the circulation radiation distance of the deviation region. For a single deviation region, the circulation radiation distance is the distance between this deviation region and the nearest ventilation window. When the interference parameter is the number of active personnel within the deviation region, the interference radiation coefficient has a positive correlation with the activity intensity of the deviation region. For a single deviation region, the activity intensity is the metabolic rate of the activity behavior with the highest frequency when the active personnel are located in this deviation region. The user can set according to the actual working scenario the determination methods of the interference parameters for different target control parameters and the interference radiation coefficients corresponding to each deviation region. This is easily understood by those skilled in the art and will not be elaborated here.

[0075] Specifically, the first estimation condition for the response of the first estimation and analysis unit is that the regional distribution index is greater than the preset regional distribution index. Then, the dynamic interference index is determined based on the control fluctuation coefficient of each deviation analysis set and the reference change amplitude.

[0076] The dynamic interference index is positively correlated with the control fluctuation coefficient and the reference change amplitude respectively.

[0077] The deviation analysis set is determined by dividing the deviation region based on the regional interval distance and the interference parameter correlation degree.

[0078] Among them, the value of the preset regional distribution index can be determined by the user according to the actual working scenario. For example, the user can set it according to the control management record. The control management record for determining the dynamic interference index based on the control fluctuation coefficient of each deviation analysis set and the reference change amplitude is recorded as the distribution reference record. The minimum value of the regional distribution index in the distribution reference record that meets the requirements of the timeliness and effectiveness of the user's adjustment operation for the target control parameter is recorded as the preset regional distribution index.

[0079] For a single key analysis parameter, if the regional distribution index of this key analysis parameter is greater than the preset regional distribution index, several deviation regions corresponding to this key analysis parameter are divided to obtain several deviation analysis sets. Any determined deviation analysis set meets the set division condition. The set division condition is that the regional interval distance is less than the preset regional interval distance and the interference parameter correlation degree is greater than the preset interference parameter correlation degree. For a single deviation analysis set, the interval distance between the center points of each deviation region in this deviation analysis set is detected, and the maximum value of the determined interval distance is recorded as the regional interval distance of this deviation analysis set. The interference parameter correlation degree is the average value of the parameter correlation degrees of each interference parameter corresponding to this key analysis parameter. For a single interference parameter, the parameter correlation degree = (the maximum value of the interference radiation coefficient of this interference parameter obtained in this deviation analysis set - the minimum value of the interference radiation coefficient of this interference parameter obtained in this deviation analysis set) / the average value of the interference radiation coefficient of this interference parameter obtained in this deviation analysis set.

[0080] For the values of the preset regional interval distance and the relevance of the preset interference parameter, the user can determine them according to the actual working scenario. For example, the user can set them according to the control management records. The higher the requirements of the user for the timeliness and effectiveness of the adjustment operation of the target control parameter, the smaller the value of the preset regional interval distance and the greater the relevance of the preset interference parameter. A method for obtaining the value of the preset regional interval distance is provided. The average value of the regional interval distances of each deviation analysis set in the control management records that meet the user's requirements for the timeliness and effectiveness of the adjustment operation of the target control parameter is recorded as the preset regional interval distance. A method for obtaining the relevance of the preset interference parameter is provided. The minimum value of the interference parameter relevance of each deviation analysis set in the control management records that meet the user's requirements for the timeliness and effectiveness of the adjustment operation of the target control parameter is recorded as the preset interference parameter relevance;

[0081] For a single deviation analysis set, the control fluctuation coefficient is the number of times of adjustment determined for this key analysis parameter within the current parameter acquisition period, the reference change amplitude is the average value of the regional change parameters of each deviation region within this deviation analysis set, and the dynamic interference index k is the number of deviation analysis sets determined, and c s is the reference change amplitude of the s-th deviation analysis set, and p s is the control fluctuation coefficient of the s-th deviation analysis set.

[0082] Specifically, the first estimation analysis unit responds to the first estimation condition that the regional distribution index is less than or equal to the preset regional distribution index, then determines the regulation radiation index based on the control execution coefficient and the proportion of the deviation region, and determines whether to perform a reduction adjustment on the regulation radiation index according to the interference stability index;

[0083] The radiation regulation condition to which the first estimation analysis unit responds is that the interference stability index is greater than the preset interference stability index, then increases the regulation radiation index according to the interference stability index;

[0084] The increase value of the regulation radiation index has a positive correlation with the interference stability index.

[0085] Among them, for the key analysis parameter with a single regional distribution index less than or equal to the preset regional distribution index, the regulation radiation index is the product of the control execution coefficient and the proportion of the deviation region. The control execution coefficient = the maximum working power of the control device for this key analysis parameter within the current parameter monitoring period / the maximum working power of the control device for this key analysis parameter. The interference stability index = 1 / the maximum value of the interference fluctuation parameters of each interference parameter in the next parameter monitoring period;

[0086] For a single interference parameter, obtain the values of this interference parameter obtained each time in the control management record during the fluctuation analysis stage on the date of the current parameter monitoring period, and record the moment within the date when each value is obtained, and record it as the historical interference detection moment. In the next parameter monitoring period, the interference fluctuation parameter of this interference parameter m is the number of historical interference detection moments existing in the next parameter monitoring period, gt is the reference interference value at the t-th historical interference detection moment in the next parameter monitoring period, and g0 is the average value of the reference interference values at each historical interference detection moment in the next parameter monitoring period. For a single historical interference detection moment, the reference interference value is the average value of the values of this interference parameter obtained at the same historical interference detection moment on different dates during the fluctuation analysis stage. The end date of the fluctuation analysis stage is the date of the current parameter monitoring period, and the duration of the fluctuation analysis stage can be set by the user according to the actual working scenario. Provide a value for the duration of the fluctuation analysis stage. The value of the duration of the fluctuation analysis stage is 15 days;

[0087] The value of the preset interference stability index can be determined by the user according to the actual working scenario. For example, the user can set it according to the control management record. The higher the requirements of the user for the timeliness and effectiveness of the adjustment operation of the target control parameter, the smaller the value of the preset interference stability index. Provide a method for obtaining the value of the preset interference stability index. Record the control management record for increasing the regulation radiation index according to the interference stability index as the radiation adjustment record, and record the minimum value of the interference stability index in the radiation adjustment records that meet the user's requirements for the timeliness and effectiveness of the adjustment operation of the target control parameter as the preset interference stability index.

[0088] Specifically, the corresponding area evaluation condition of the area evaluation module is that the proportion of the deviation area of a key analysis parameter is less than or equal to the preset deviation area proportion, then it is determined that the second prediction analysis unit determines the area change parameter based on the reference change amplitude of each interference parameter, and determines the interference change index based on the change effective coefficient and the area change parameter;

[0089] The interference change index is positively correlated with the change effective coefficient and the area change parameter respectively.

[0090] Among them, for the key analysis parameters where the proportion of a single deviation region is less than or equal to the preset deviation region proportion, the region change parameter is the average value of the reference change amplitudes of each interference parameter. For a single interference parameter, the reference change amplitude = |the maximum value of the reference interference value at each historical interference detection moment within the next parameter monitoring period of this interference parameter - the maximum value obtained by this interference parameter within the current parameter monitoring period| / the maximum value obtained by this interference parameter within the current parameter monitoring period. The interference change index is the product of the region change parameter and the change effective coefficient. The change effective coefficient is determined according to the interference radiation coefficient of the key interference parameter of each deviation region. Denote the interference parameter with the largest reference change amplitude as the key interference parameter. The change effective coefficient = the average value of the interference radiation coefficients of each deviation region for the key interference parameter / the average value of the number of center points of the deviation regions existing within the preset analysis range of each deviation region corresponding to this key analysis parameter in the target management region.

[0091] Specifically, when the parameter evaluation condition responded to by the parameter analysis module is that the dynamic interference index of the target optimization parameter is greater than the preset dynamic interference index, it is determined that the proportional control coefficient is increased based on the execution standard difference index and the dynamic interference index.

[0092] The increase value of the proportional control coefficient has a positive correlation with the execution standard difference index and the dynamic interference index.

[0093] Specifically, when the parameter evaluation condition responded to by the parameter analysis module is that the interference change index of the target optimization parameter is greater than the preset interference change index, it is determined that the integral control coefficient is increased based on the interference change index and the reference change amplitude.

[0094] The increase value of the integral control coefficient has a positive correlation with the interference change index and the reference change amplitude.

[0095] Specifically, when the parameter evaluation condition responded to by the parameter analysis module is that the regulation radiation index of the target optimization parameter is greater than the preset regulation radiation index, it is determined that the derivative control coefficient is increased based on the regulation radiation index.

[0096] The increase value of the derivative control coefficient has a positive correlation with the regulation radiation index.

[0097] Among them, the target optimization parameter is the target control parameter for which the estimated index is determined. For a single target optimization parameter, when the dynamic interference index is greater than the preset dynamic interference index, it indicates that the target optimization parameter is likely to have relatively frequent fluctuations in the next parameter monitoring period. In this case, the proportional control coefficient is adjusted to increase to ensure timely response to parameter changes. The increase value of the proportional control coefficient is positively correlated with the proportional adjustment parameter. The proportional adjustment parameter = ln(execution standard difference index × dynamic interference index). The execution standard difference index is the average value of the deviation change parameters of each parameter monitoring period in the execution analysis stage. At the end of each parameter monitoring period, the deviation change parameters of each parameter monitoring period are detected. For a single parameter monitoring period, the deviation change parameter is the absolute value of the difference between the regional reference difference of the target optimization parameter obtained at the end of this parameter monitoring period and the regional reference difference of the target optimization parameter obtained at the end of the previous parameter monitoring period. The end time of the execution analysis stage is the end time of the current parameter monitoring period. The duration of the execution analysis stage can be determined by the user according to the actual working scenario. Here, a duration of the execution analysis stage is provided, and the duration of the execution analysis stage is ten times that of the parameter monitoring period. When the interference change index is greater than the preset interference change index, it indicates that the deviation area determined in the current parameter monitoring period is caused by the change of the interference parameter, and the impact caused by the change of the interference parameter will continue to the subsequent parameter detection periods. By increasing the integral control coefficient, the deviation caused by long-term continuous interference can be eliminated. The increase value of the integral control coefficient is positively correlated with the integral adjustment parameter. The integral control coefficient = ln(interference change index × average value of the reference change amplitudes of each deviation area). When the regulation radiation index is greater than the preset regulation radiation index, it indicates that the adjustment result executed in the current parameter monitoring period is likely to have a greater impact on the target control parameter in the subsequent parameter monitoring periods. By increasing the differential control coefficient, the impact of equipment inertia caused by the conditional process can be eliminated;

[0098] The values of the preset dynamic interference index, the preset interference change index, and the preset regulation radiation index can be determined by the user according to the actual working scenario. For example, the user can set them according to the control management records. The higher the requirements of the user for the timeliness and effectiveness of the adjustment operation of the target control parameter, the smaller the value of the preset dynamic interference index, the smaller the value of the preset interference change index, and the smaller the value of the preset regulation radiation index. A method for obtaining the value of the preset dynamic interference index is provided. The control management record for increasing the adjustment of the proportional control coefficient is recorded as the dynamic reference record. The minimum value of the dynamic interference index of the target optimization parameter in the dynamic reference record that meets the user's requirements for the timeliness and effectiveness of the adjustment operation of the target control parameter is recorded as the preset dynamic interference index. A method for obtaining the value of the preset interference change index is provided. The control management record for increasing the adjustment of the integral control coefficient is recorded as the interference reference record. The minimum value of the interference change index of the target optimization parameter in the dynamic reference record that meets the user's requirements for the timeliness and effectiveness of the adjustment operation of the target control parameter is recorded as the preset interference change index. A method for obtaining the value of the preset regulation radiation index is provided. The control management record for increasing the adjustment of the derivative control coefficient is recorded as the interference reference record. The minimum value of the regulation radiation index of the target optimization parameter in the regulation reference record that meets the user's requirements for the timeliness and effectiveness of the adjustment operation of the target control parameter is recorded as the preset regulation radiation index.

[0099] So far, the technical solution of the present invention has been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0100] The above are only the preferred embodiments of the present invention and are not used to limit the present invention; for those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An energy-saving control and management system based on public buildings, characterized in that, Including: A region monitoring module, configured to obtain various target control parameters of a target management region, and periodically respond to parameter standard conditions to determine whether each target control parameter meets the control requirements; A standard optimization module, connected to the region monitoring module, configured to perform parameter standard optimization for each target control parameter to obtain preferred standard values of each target control parameter; A region evaluation module, connected to the region monitoring module, configured to periodically respond to region evaluation conditions to determine that the parameter prediction strategy for each key analysis parameter is to determine a data prediction strategy based on a region distribution index, or to determine an interference change index based on a change effectiveness coefficient and a region change parameter; The data prediction strategy is to determine a dynamic interference index based on a control fluctuation coefficient and a reference change amplitude of each deviation analysis set, or to determine a regulation radiation index based on a control execution coefficient and a deviation region proportion; A prediction analysis module, connected to the region evaluation module, including a first prediction analysis unit and a second prediction analysis unit, configured to execute the parameter prediction strategy determined by the region evaluation module for each target control parameter to determine a prediction index of the target control parameter; A parameter analysis module, connected to the prediction analysis module, configured to respond to parameter evaluation conditions to determine a parameter control strategy for each target optimization parameter, and adjust the parameter control coefficient of the target optimization parameter; The prediction index includes a dynamic interference index, an interference change index, and an interference change index, and the parameter control coefficient includes a proportional control coefficient, an integral control coefficient, and a differential control coefficient.

2. The energy-saving control and management system based on public buildings according to claim 1, wherein The parameter standard condition to which the region monitoring module responds is that if the standard difference index of any one target control parameter is less than or equal to a preset standard difference index, it is determined that the target control parameter meets the control requirements, and the target control parameter is recorded as a conventional analysis parameter; The parameter standard condition corresponding to the region monitoring module is that if the standard difference index of any one target control parameter is greater than the preset standard difference index, it is determined that the target control parameter does not meet the control requirements, and the target control parameter is recorded as a key analysis parameter of the conventional analysis parameter; The standard difference index is determined according to the region reference difference degree and the deviation region proportion.

3. The energy-saving control and management system based on public buildings according to claim 2, wherein, The standard optimization module determines the preferred standard value of each target control parameter based on formula (1), Among them, f j (X) is the j-th objective optimization function, is the optimal solution of the j-th objective optimization function of the objective control parameter, n is the number of objective optimization functions, and X is the objective control parameter for parameter standard optimization.

4. The energy-saving control and management system based on public buildings according to claim 3, wherein The region evaluation condition to which the region evaluation module responds is that if the deviation region proportion of a key analysis parameter is greater than a preset deviation region proportion, it is determined that the first prediction analysis unit determines the data prediction strategy of the key analysis parameter based on the region distribution index; The region distribution index is determined according to a deviation dispersion coefficient and a reference deviation interference coefficient, and the region distribution index has a negative correlation with the deviation dispersion coefficient, and the region distribution index has a positive correlation with the reference deviation interference coefficient.

5. The energy-saving control and management system based on public buildings according to claim 4, characterized in that, The first prediction condition to which the first prediction analysis unit responds is that if the region distribution index is greater than a preset region distribution index, a dynamic interference index is determined based on the control fluctuation coefficient and the reference change amplitude of each deviation analysis set; The dynamic interference index is positively correlated with the control fluctuation coefficient and the reference change amplitude respectively; The deviation analysis set is determined by dividing the deviation area based on the regional interval distance and the interference parameter correlation.

6. The energy-saving control and management system based on public buildings according to claim 5, characterized in that, The first estimation analysis unit responds to the first estimation condition that the regional distribution index is less than or equal to the preset regional distribution index, then determines the regulation radiation index based on the control execution coefficient and the proportion of the deviation area, and determines whether to reduce the regulation radiation index according to the interference stability index; The radiation regulation condition to which the first estimation analysis unit responds is that the interference stability index is greater than the preset interference stability index, then the regulation radiation index is increased according to the interference stability index; The increase value of the regulation radiation index is positively correlated with the interference stability index.

7. The energy-saving control and management system based on public buildings according to claim 6, characterized in that The regional evaluation condition corresponding to the regional evaluation module is that the proportion of the deviation area with a key analysis parameter is less than or equal to the preset deviation area proportion, then it is determined that the second estimation analysis unit determines the regional change parameter based on the reference change amplitude of each interference parameter, and determines the interference change index based on the change effective coefficient and the regional change parameter; The interference change index is positively correlated with the change effective coefficient and the regional change parameter respectively.

8. The energy-saving control and management system based on public buildings according to claim 7, wherein, The parameter evaluation condition to which the parameter analysis module responds is that the dynamic interference index of the target optimization parameter is greater than the preset dynamic interference index, then it is determined that the proportional control coefficient is increased based on the execution standard difference index and the dynamic interference index; The increase value of the proportional control coefficient is positively correlated with the execution standard difference index and the dynamic interference index.

9. The energy-saving control and management system based on public buildings according to claim 8, wherein The parameter evaluation condition to which the parameter analysis module responds is that the interference change index of the target optimization parameter is greater than the preset interference change index, then it is determined that the integral control coefficient is increased based on the interference change index and the reference change amplitude; The increase value of the integral control coefficient is positively correlated with the interference change index and the reference change amplitude.

10. The energy-saving control and management system based on public buildings according to claim 9, characterized in that, The parameter evaluation condition to which the parameter analysis module responds is that the regulation radiation index of the target optimization parameter is greater than the preset regulation radiation index, then it is determined that the differential control coefficient is increased based on the regulation radiation index; The increase value of the differential control coefficient is positively correlated with the regulation radiation index.

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