RU2740274C1 - Method for rapid assessment of energy-saving potential of group of single-type objects and automated system for implementation thereof - Google Patents

Abstract

FIELD: physics.

SUBSTANCE: disclosed method for rapid assessment of energy-saving potential of a group of single-type objects and an automated system for its implementation relate to the field of information-analytical systems and methods of processing data in order to perform energy-deflection efficiency calculations and are intended to assess the energy-saving potential of a large group of single-type objects. Automated system for rapid assessment of energy-saving potential of a group of single-type objects includes a Collection of Information subsystem equipped with three program modules, Modelling of Standard Energy-Saving Measures for All Analysed Objects Subsystem equipped with ten program modules, the third subsystem "Extended evaluation of energy saving potential" equipped with four program modules, and Information Storage subsystem. Express-assessment method of potential energy saving, which is implemented by the above automated system, includes collection of necessary data and information on analysed objects, verification of these data and information on completeness, reliability and consistency, bringing them to a single structure for further modelling of standard energy-saving measures on all analysed objects. Simulation involves such procedures as assessment of feasibility of energy-saving measures, selection of a method of estimating energy-saving effect from implementation of any energy-saving measures, detailed assessment of energy-saving effect by measures and objects. After that, detailed assessment of energy saving potential is carried out.

EFFECT: higher efficiency of determining energy-saving potential of a large group of single-type objects.

2 cl, 1 dwg, 5 tbl

Description

The group of inventions relates to information and analytical data processing systems for the purpose of calculating energy efficiency indicators and assessing the energy saving potential for a large group of similar objects, as well as information and analytical methods for determining the energy saving potential for a large group of similar objects.

A known method for determining energy efficiency indicators and assessing the potential for energy saving by conducting an energy survey of an organization and its facilities, in which calculations are performed for current conditions and comparison of actual energy efficiency indicators with calculated ones. The method consists in the fact that a group of specialists-energy auditors conducts an energy survey (energy audit) of the organization - collects information about the organization and the objects occupied by it, for which questionnaires are developed, which are sent to the appropriate services of the organization. After filling out the survey forms, the information obtained is analyzed, the objects are inspected, the employees of the energy services and technologists are interviewed, they get acquainted with the technical documentation: resource supply and resource consumption schemes, the list and characteristics of power equipment, regulations for technological processes, they collect information on the monthly consumption of energy resources and product output, information about payment for consumed energy resources, as well as other information necessary for further work. A group of energy auditors also conducts instrumental examinations of the organization's facilities, resource supply systems and resource consumption, calculates energy efficiency indicators, evaluates the energy saving potential of individual facilities, as well as the organization (enterprise) as a whole, after which they recommend organizational and technical measures for energy saving, and draws up a report on energy survey and energy passport of the organization (enterprise). (Kuznetsov N. V., Danovskaya O. A., "Energy saving and energy audit of industrial enterprises" - M .: Publishing house "Kilowatt", 2011).

The disadvantage of this method is the high time, resource and financial costs; the length of the process and the complexity of generalizing the results for a large number of objects (a large number of organizations).

A known method for determining the potential for energy saving by comparing the volume of actual consumption of resources at a specific facility with standard or better indicators determined by the availability of statistical data on similar facilities. The known method consists in the fact that the energy saving potential (ΔE _sweat ) is understood as the difference between the actual annual energy consumption of any resource at the investigated object (E _fact ) and the results of best practices (volumes of consumption of this resource at similar objects) or the estimated consumption of the investigated object at standard working conditions (E _norms ): ΔE _sweat = E _fact - E _norms . (Internet resource http: //auditenergoservice.rf)

The disadvantages of this method are: impossibility to determine the energy saving potential for atypical objects (for which there are no analogues); determination of consumption standards for a particular object requires a large amount of data describing the characteristics of this object and implies the need to perform manual calculations to determine the E _norms ; the method using analogs does not provide the required accuracy, since it does not take into account the individual characteristics of objects. In addition, the result obtained (the energy saving potential for each resource) does not allow us to determine exactly what activities need to be carried out at the facility in order to realize the calculated energy saving potential.

A known method for determining the potential of energy saving on the basis of guidelines for calculating the effects of the implementation of measures to save energy and increase energy efficiency. This method consists in the fact that when determining the energy saving potential, experts recommend assessments of the energy saving potential in the form of ranges of possible savings in percentage ratios depending on the type of energy saving measures. (Guidelines for calculating the effects of the implementation of measures to save energy and increase energy efficiency. -
Moscow: Analytical Center for the Government of the Russian Federation, 2016).

The disadvantages of this method are a large spread (low accuracy) of the range of estimates; an incomplete list of activities that can be assessed; individual features of objects are not taken into account; the mechanism of the mutual influence of the energy-saving effect from the implementation of measures has not been determined.

The known device is the State Information System (GIS) "Energy Efficiency", including the "Expert Portal", which is a database formed by accumulating information received from users of the system - specialists of budgetary institutions of different levels of hierarchy and departmental affiliation in various areas in the field of energy saving, as well as the module "Information on energy saving and energy efficiency", which is a system for collecting data and filling out energy declarations for organizations - consumers of energy resources. The "Expert Portal" contains information on regulatory and legal documentation in the field of energy saving, energy audit, energy service, energy management, methodological support, practical energy saving and others. This information is intended to assist users in organizing and managing energy conservation at enterprises, in municipalities and regions, training in the field of energy efficiency, choosing and justifying energy saving measures, as well as compiling reports in the field of energy saving. Placing information in the system is carried out in any form and volume, including by attaching various external files. The “Information on energy saving and energy efficiency increase” module is an information system for collecting data from budget organizations on energy consumption, installed metering devices, completed and planned energy saving measures. The system is actually focused on filling out energy declarations for individual organizations, integrating the entered data in order to generalize them to higher levels of management, as well as calculating individual energy efficiency indicators. (Internet resource https://gisee.ru/).

The disadvantages of this device are as follows: GIS "Energy Efficiency" in its content is mainly an information storage system and is not intended for calculating the energy saving potential, in addition, due to the fact that information is entered into the system by users of different qualifications, and verification of the entered information there is no validity and consistency in the system, errors are possible when entering parameters into the system. It should also be noted that the list of parameters entered into the system is clearly insufficient for making correct calculations of the energy saving potential for the entire list of even typical recommended measures.

Known devices are numerous systems that perform local calculations of the energy-saving effect for one or several activities in the online mode - energy efficiency "calculators".

These devices (software modules) allow, by entering certain parameters necessary for the simplest calculations, to assess the economic effect of carrying out the standard energy-saving measures indicated in the system to save electrical energy, less often - thermal energy and calculate the possibilities of energy saving for individual buildings if they are used on them individual events.
(Internet resources: https://gisee.ru/calc/effect/, http://vashtehnik.ru/calc, http://yarko-tut.ru/auxpage_calc/, http://newtariffs.ru/kalkuljator -energosberezhenija, http: //ruslayt.rf/calc.shtml, https://www.ltcompany.com/ru/solutions/energy-efficiency-calculator/, https://x-flash.su/informaciya/calculator/ ).

The disadvantages of such devices usually consist in a limited list of calculated activities, orientation of calculations to simple algorithms (for example, replacement of lamps or lamps), the inability to generalize the results for a large group of objects, and the impossibility of taking into account the mutual influence of several events within one resource. As a rule, such programs do not analyze the reliability and consistency of the input data (for example, you can enter the negative power of electric lamps), because of this, the calculations have low reliability. In addition, the manufacturer (who is also the owner of the calculator program) is an interested person and can significantly overestimate the characteristics of his products, which will lead to incorrect calculations of the energy-saving and, accordingly, the economic effect from the implementation of the measure.

In addition, a method of accounting and an information-analytical system for accounting for energy resources are known. The known method and device relate to data collection systems using radio communication and the subsequent analysis of the information received and can be used to build information and analytical systems for accounting for energy consumption - cold and hot water, natural gas, thermal energy, electricity and other energy resources. The known energy accounting system includes fuel and energy consumption meters, communication stations, automation cabinets, and a central server. The communication station contains a GSM controller, which is a local controller for data collection and transmission and a GSM modem combined on a single hardware platform. The GSM controller simultaneously collects data from control sensors and fuel and energy consumption meters regardless of the interface settings and protocol features and establishes a GPRS connection. The communication station can simultaneously send requests received from the central server and send responses to it via several communication channels from the automation cabinets. The computers of remote workstations are connected to the central server, and the consumers of fuel and energy resources from their personal computers have the opportunity to enter the WEB-server and receive information on the consumed energy resources in physical and monetary units, as well as the results of the analysis of this information. On the central server, the database stores additional information - this is general information about the organization (name, area and volume of individual buildings and the organization as a whole, the subject of economic activity, address, phone number, names of managers, number of employees and visitors, share costs for fuel and energy resources from the amount of the expenditure side of the budget); actual and limited consumption of fuel and energy resources (water, heat energy, electricity, fuel) in dynamics for the reporting periods of time (by months, years) by individual buildings and the organization as a whole; information on the availability of metering of fuel and energy resources consumption; FER consumption in monetary terms and FER tariffs in dynamics for the reporting periods; auxiliary data required for calculations (duration of the heating period, estimated and average outside air temperature, room temperature, standard indicators of fuel and energy consumption); information on tariffs. Using the above data, data from fuel and energy consumption meters and control sensors, the following indicators are calculated: estimated and normative fuel and energy resources consumption by metering groups, specific indicators of fuel and energy resources consumption and energy saving potential. (RF patent No. 2453913 C1, "Method of accounting and information and analytical system for accounting for energy resources", priority date 31.01.2011, IPC G06F 17/00 (2006.01)).

The disadvantages of this method and the system that implements it is that it is not obvious how exactly “additional information” is generated in the database on the central server, and that the entered data are not checked for reliability and consistency. Further, from the analysis of the listed "additional" parameters, it follows that some of them are not related to the actual calculation of the energy saving potential (address, phone number, names of managers), at the same time, absolutely necessary information is missing - for example, the history of the object and the owner's plans for the object (year of construction, years when the building was repaired or overhauled, whether the object is emergency, or ownerless, etc.). It is obvious that if an object, for example, is included in the renovation program, then its energy saving potential is zero and is not determined by any calculation methods, since it makes no sense to carry out energy-saving measures at an object that in the near future will no longer physically exist.

The task to be solved by the claimed group of inventions is to develop such a method for determining the rapid assessment of the energy saving potential of a large group of similar objects, the implementation of which allows performing an engineering-based assessment of the energy saving potential in conditions of partial absence of data on the objects under study, increasing the accuracy and reliability of calculations , improve the quality of the presentation of results and reduce the total time for assessing the energy saving potential, as well as in the creation of such an automated system for the rapid assessment of the energy saving potential of a large group of similar objects, which implements the above-mentioned method for assessing the energy saving potential using automated subsystems containing software modules and blocks, solving the assigned tasks using automated algorithms implemented in program codes.

The technical result, which the claimed group of inventions is aimed at, is to increase the efficiency of determining the energy saving potential of a large group of similar objects, which occurs due to the technical feasibility of performing an engineering-based assessment of the potential of a group of similar objects in conditions of partial absence of data on these objects, increasing accuracy and the reliability of calculations and estimates, reducing the total time for assessing the energy saving potential, as well as improving the quality of the presentation of the results of assessing the energy saving potential necessary for making engineering-based decisions to improve the energy efficiency of this group of objects in the context of limited funding for energy saving measures.

The specified technical result is achieved through the development of a method for rapid assessment of the energy saving potential of a group of similar objects under study, during which, in order to assess the energy saving potential for each of the investigated similar objects according to a predetermined list of parameters related to the investigated similar objects, the collection of data affecting consumption of all types of energy resources by the mentioned objects under study, which primarily include heat energy, electricity, water, natural gas, in addition, they collect data on the location and departmental subordination of the objects under study, as well as engineering, technical and financial related to the mentioned objects under study data, while the collection of the above data is carried out both manually and with the help of automated measuring systems, and in the composition of the above data, normative and reference information, data about the design features of the objects under study, data on the equipment installed on them, as well as data on the current state of the objects under study, data on the standard energy-saving measures taken at the objects under study and the plans of higher organizations in relation to the objects under study, then part of the mentioned collected data is subjected to verification for completeness, reliability and consistency, after which all the collected and verified data are combined into a structured database, on the basis of which typical energy-saving measures are then automatically simulated for each of the objects under study, while this modeling includes first assessing the feasibility of each from typical energy saving measures in relation to each of the studied objects and then assessing the energy saving effect for each consumed energy resource for each of typical energy-saving measures appropriate for carrying out at each of the investigated objects, while the assessment of the feasibility of carrying out a specific typical energy-saving measure at a particular investigated object is formed using the above-mentioned structured database based on the analysis of such parameters as the current state of the objects under study, information about the standard energy-saving measures at the objects under study and the plans of higher-level organizations in relation to the objects under study, after which the obtained assessment of feasibility is used as a criterion for the need for a subsequent assessment of the energy-saving effect of each of the typical energy-saving measures at each of the objects under study, then, using the information obtained during data collection about completeness and specific composition of the available data for each investigated object, for each investigated object and each typical energy saving measure wasp the choice of one of the methods for assessing the energy-saving effect, which are: direct calculations, which are carried out in the presence of all data on all parameters of the objects under study necessary for the calculation, including calculations using an alternative set of parameters of the objects under study, calculations with partial restoration of the missing parameters of the studied objects objects, as well as a simplified calculation with the minimum possible set of parameters of the investigated objects, a statistical assessment, which is carried out in the absence of data necessary for direct calculation, and in the presence of statistical data on the estimated value of the energy-saving effect on objects similar to the investigated ones, as well as an expert assessment, which used in the absence of data for direct calculations and at the same time in the absence of statistical data, after which one of the selected assessment methods for each investigated object for each energy-saving measure (M) for each energy res Ursa (p), the absolute value of the energy-saving effect _{ΔР nMr is estimated} in natural terms (n), then the specific energy-saving effect δР _{nMr is calculated} as the ratio of the absolute value of the energy-saving effect to the volume of consumption of this resource Р _n at the object under study:

,

,

after that, the obtained specific energy-saving effect is compared with the maximum permissible specific value of the energy-saving effect obtained by the above-mentioned method of expert evaluation, and, if the value of the above-mentioned specific energy-saving effect is higher than the maximum permissible specific value of the energy-saving effect obtained by the method of expert evaluation, for the resulting assessment energy-saving effect, the maximum permissible specific value of the energy-saving effect obtained by the method of expert assessment is taken, while for all the above-mentioned methods for assessing the energy-saving effect, the setting of automated algorithms is used based on the normative and reference information and the accumulated results of the above-mentioned assessment of the energy-saving effect, then detailed modeling of typical energy-saving measures for all investigated objects, calculating the costs of the implementation of feasible standard energy savings saving measures and their payback period for each energy resource, and then form a detailed assessment of the energy saving potential, which includes the above-mentioned absolute value of the energy-saving effect _{ΔР nMr} in physical terms (n) and the specific energy-saving effect δР _nMr , as well as the energy saving potential of each of of the studied objects (o) in kind ∆Р _it (n) for each type of energy resource (p), calculated taking into account the mutual influence of each of the n typical energy saving measures selected as appropriate for use at the object under study:

,

,

after that, the results of calculations for each resource are brought together, determining the energy saving potential in kind of all the objects under study for each energy resource by summing up the energy saving potentials ∆Р _it calculated for each of the studied objects included in the group, then they are carried out using the detailed simulation results for each of the types of energy resources, the calculation of engineering-based indicators in physical and monetary terms, and for the totality of all studied objects, the objects under study are ranked for each typical energy-saving measure in accordance with the calculated indicators, among which the absolute and / or specific value of the achieved energy-saving effect in in physical terms, the cost and / or payback period of a typical energy-saving event, and ranking in ascending or descending order using one or more impressions They are used in the future to determine the priorities for the implementation of typical energy-saving measures at the facilities included in the group, depending on the tasks set, after which the results of a detailed and detailed assessment, the values of all indicators, as well as the results of ranking objects by typical energy-saving measures are saved for further use, including for setting up algorithms for assessing energy saving potential.

In addition, the specified technical result is achieved through the creation of an automated system for express-assessment of the energy saving potential of a group of similar objects, which implements the above method and includes the first subsystem "Gathering information", the second subsystem "Modeling typical energy-saving measures for all investigated objects", the third subsystem "Detailed assessment of energy saving potential" and the fourth subsystem "Information storage", while the first subsystem is configured to collect data on a predetermined list of parameters related to the studied objects of the same type that affect the energy consumption of each of the objects under study, including the reference information related to the objects under study, as well as with the possibility of bringing the above data to a single structure and transferring them for processing to the second subsystem, which is made with the possibility of analyzing the feasibility of conducting each of the typical energy-saving measures in relation to each of the objects under study, while standard measures aimed at saving energy resources, such as, first of all, heat energy, electricity, water and natural gas can be taken as energy-saving measures, in addition, the second subsystem is made with the possibility of modeling typical energy-saving measures in relation to each object under study and taking into account the previously determined expediency, including the assessment or calculation of the energy-saving effect achievable in this case, in addition, the second subsystem is made with the possibility of detailing the obtained simulation results, which includes an assessment of the costs of carrying out each of the studied objects of each of the simulated typical energy-saving measures and the calculation of the terms of their payback, as well as the transfer of all the results obtained to the third subsystem, which is made with the possibility of processing received from the second subsystems of detailed results of modeling typical energy-saving measures for all types of energy resources, in addition, the third subsystem is made with the ability to form a detailed assessment of the energy-saving potential of the objects under study, which includes calculations of the mutual influence of typical energy-saving measures for each object under study and energy resource, resources and in general for the group of objects under study, calculations of engineering-based indicators, in addition, the third subsystem is made with the ability to perform ranking of objects by energy resources and simulated typical energy-saving measures, and the fourth subsystem is made with the ability to store the mentioned data collected in the first subsystem, and all the results obtained in the second and third subsystems, while the first subsystem includes the first, second and third software modules, and the first software the module is configured to check the collected data for completeness, reliability and consistency in terms of the parameters of the objects under study, affecting the energy consumption of each of the objects under study, and the first software module is equipped with the first program unit made with the ability to determine, based on the results of checking the data for completeness, criteria to select a method for assessing the energy-saving effect and transfer them to the second subsystem, the second software module is configured to process the data on the parameters of the studied objects that affect energy consumption, which are received in the system, and are formed on the basis of reference information, while the first and second software modules are made with the ability to transfer the data processed by them to the third software module, which in turn is configured to bring all the data received into it from the first and second software modules to a single structured database for their subsequent transfer into the second subsystem, which forms, on the basis of the structured database obtained from the first subsystem and the criteria for choosing a method for assessing the energy-saving effect, the detailed results of modeling typical energy-saving measures aimed at saving the above-mentioned energy resources, while the second subsystem includes program modules from the fourth to the thirteenth, the fourth software module is configured to assess the feasibility of carrying out standard energy-saving measures in relation to each of the objects under study, the fifth software module is configured to select one of the methods for assessing the energy-saving effect that can be obtained as a result of the implementation of a typical energy-saving measure at the object under study, the sixth the software module is designed to carry out detailed modeling of typical energy-saving measures for all investigated objects, including calculation of the cost of carrying out standard energy-saving measures in relation to each of the objects under study and the payback period of these typical energy-saving measures, and the program modules from the seventh to the thirteenth are made with the possibility of forming calculations and estimates of the energy-saving effect using various methods, which, depending on the the first subsystem of criteria, direct calculations performed by the seventh software module can be selected, which are carried out in the presence of all data on all parameters of the studied objects necessary for the calculation, calculations performed by the eighth software module using an alternative set of parameters of the studied objects, performed by the ninth software module calculations with partial restoration of the missing parameters of the objects under study, as well as simplified calculations performed by the tenth software module with the minimum possible set of parameters of the objects under study, performed on one by the twelfth software module, statistical evaluations that are carried out in the absence of data necessary for the calculations, and in the presence of statistical data on the estimated value of the energy-saving effect at facilities similar to the investigated ones, as well as expert assessments performed by the twelfth software module, which are carried out in the absence of data for direct calculations and the absence of statistical data, while in the thirteenth program module, restrictions are set on the values of the obtained results of calculations and estimates, while in the event that the values of the above results and estimates are higher than the maximum allowable energy-saving effect, determined in the twelfth program block by expert judgment, for the resulting estimate of the energy-saving effect take the maximum permissible specific value of the energy-saving effect, obtained by the method of expert evaluation, in addition, all program modules from the seventh to the thirteenth are equipped with program blocks executed with the ability to customize all of the above program modules, from the seventh to the thirteenth, depending on the normative and reference information related to the objects under study and information accumulated in the system, the third subsystem includes program modules from the fourteenth to the seventeenth, while the fourteenth program module is executed with the possibility of calculating the mutual influence of typical energy-saving measures with their simultaneous implementation at one facility and determining the energy-saving potential of each object under study for each energy resource, the fifteenth software module is configured to calculate the energy-saving potential of the entire group of objects under study for each energy resource as the sum of all energy-saving potentials of all of the objects under study, the sixteenth software module is made with the ability to perform calculations of engineering-based ranking indicators in physical and monetary terms for each of the investigated objects and energy resource, and the seventeenth software module is configured to rank the objects under study by typical energy-saving measures using the engineering-based ranking indicators calculated in the sixteenth software module for the entire group of objects under study for each of the energy resources or for each of the typical energy-saving measures.

The essence of the group of inventions is illustrated by a drawing, which shows a functional diagram of an automated system for rapid assessment of the energy saving potential of a group of similar objects, as well as the following tables:

Table 1 "Relationship between parameters and their values for the objects under study",

Table 2 and Table 4 "Structured database containing information about the objects under study",

Table 3 "Comparative table of characteristics of the main types of lamps",

Table 5 "Examples of expert assessments".

On the functional diagram of the claimed automated system for rapid assessment of the energy saving potential of a group of similar objects, it is shown:

- the first subsystem "Gathering information", which is equipped with the first software module "Checking data for completeness, reliability and consistency", the second software module "Processing of reference information", as well as the third software module "Bringing data to a single structure for further processing" ;

- the second subsystem "Modeling typical energy-saving measures for all investigated objects", equipped with the fourth software module "Evaluation of the feasibility of each event in relation to each object", the fifth software module "Choosing a method for assessing the energy-saving effect in the implementation of measures aimed at saving energy resources", the sixth software module "Detailed modeling of energy-saving measures for all objects", the seventh software module "Direct calculation", the eighth software module "Calculations using an alternative set of parameters", the ninth software module "Calculations with partial restoration of unfilled parameters", the tenth software module "Simplified calculations with the minimum possible set of parameters ”, the eleventh software module“ Statistical Assessment ”, the twelfth software module“ Expert Assessment ”, the thirteenth software module“ Expert Limitations of Energy Saving Modeling running effect ";

- the third subsystem "Detailed assessment of the energy saving potential", equipped with the fourteenth software module "Calculation of the mutual influence of energy saving measures for each object and each resource", the fifteenth software module "Summarizing the results of calculations for resources and in general for a group of objects", the sixteenth software module "Calculation engineering-based indicators in physical and monetary terms for each object and each resource ", the seventeenth program module" Ranking of objects by activities ";

- the fourth subsystem "Information storage".

The first subsystem is configured to carry out manual and automated data collection on a predetermined list of parameters related to the objects of the same type that affect the energy consumption of each of the objects under study, including regulatory reference information (NSI) related to the objects under study, as well as with the possibility bringing the above data to a single structure and transferring them for processing to the second subsystem.

The following should be noted here. In relation to the object under study, the term "parameter" means a formulated (formalized) description of one of the characteristics of this object, which allows, after obtaining the values of this parameter (data) for each of the objects, to distinguish the objects under study from each other (see Table 1).

It should also be noted that "data" are specific values of parameters suitable for further processing using computer technology. In our case, there is also verified data - this is data that has passed the verification. For example, the values of the "Object address" parameter for the object 1 "g. Moscow, st. Radio, 6 "and for object 2" Moscow, Radio Street, 6 "(see Table 1) from the point of view of the interpretation of the parameters, these are different values. That is, for a person it is the same address, but for a computer it is not. For the computer to correctly interpret such differently written, but implying the same, values of the parameters of the object under study, it is necessary to write a special algorithm that will process these parameter values and bring them to a uniform spelling (available for computer processing).

The first program module is equipped with a program unit PB1, made with the possibility of determining, based on the results of checking the data for completeness, criteria for choosing a method for evaluating the energy-saving effect and transferring them to the second subsystem.

The second software module is configured to process the data on the parameters of the objects under study that affect energy consumption, which are received on the basis of the reference information, entering the system, while the first and second software modules are configured to transfer the data processed by them to the third software module, which the queue is configured to bring all the data received into it from the first and second software modules to a single structured database for their subsequent transfer to the second subsystem, which forms, on the basis of the structured database obtained from the first subsystem and the criteria for choosing a method for assessing the energy-saving effect, detailed modeling results energy-saving measures aimed at saving the above-mentioned energy resources.

The second subsystem is made with the possibility of analyzing the feasibility of carrying out each of the typical energy-saving measures in relation to each of the objects under study, while the standard measures aimed at saving energy resources, such as, first of all, thermal energy, electricity, can be taken as energy-saving ones. water and natural gas. Also, the second subsystem is made with the ability to simulate typical energy-saving measures in relation to each object under study and taking into account the previously determined feasibility, including the assessment or calculation of the achievable energy-saving effect, in addition, the second subsystem is made with the possibility of detailing the obtained simulation results, an estimate of the costs of carrying out at each of the objects under study of each of the simulated standard energy-saving measures and the calculation of the terms of their payback, as well as the transfer of all the obtained simulation results to the third subsystem.

The fourth software module is made with the ability to assess the feasibility of carrying out typical energy-saving measures in relation to each of the objects under study, while the module is equipped with a PB2 software block that restricts modeling for those objects where energy-saving measures are impractical. The fifth software module is configured to select one of the methods for assessing the energy-saving effect, which can be obtained as a result of the implementation of a typical energy-saving measure at the object under study, while the choice of the assessment method for each of the objects under study and each of the standard measures is carried out using the PB3 software block , with which the fifth software module is equipped, based on the criteria for selecting a method, generated by the software block PB1 of the first subsystem. The sixth software module is made with the possibility of detailing the obtained modeling results for all the objects under study and typical energy saving measures, including the calculation of the cost of carrying out standard energy saving measures in relation to each of the objects under study and the payback period of these standard energy saving measures based on information obtained from regulatory documents on energy saving, tariffs, cost of work, materials, etc. Software modules from the seventh to the thirteenth are made with the possibility of forming calculations and estimates of the energy-saving effect using various methods, which, depending on the criteria defined in the first subsystem, can be the following: direct calculations performed in the seventh software module, which are carried out if available all data on all parameters of the investigated objects necessary for calculating the energy saving potential of the investigated objects; statistical evaluations, which are performed by the eleventh software module in the absence of data necessary for direct calculations and in the presence of statistical data on the estimated value of the energy-saving effect at facilities similar to those under study; expert assessments performed in the twelfth software module, which are carried out in the absence of data for direct calculations and the absence of statistical data. It should be noted here that direct calculations also include calculations performed in the eighth software module using an alternative set of parameters of the objects under study, calculations performed in the ninth software module with partial restoration of the missing parameters of the objects under study, as well as simplified calculations performed in the tenth software module with a minimum a possible set of parameters of the objects under study.

Program modules from the seventh to twelfth, made with the possibility of calculations and evaluations, as well as the thirteenth program module, made with the possibility of setting a limit in the amount of expert evaluations, are equipped with PBN program blocks made with the ability to configure all the mentioned program modules (from the seventh to thirteenth) in depending on regulatory and reference information related to the objects under study, as well as information accumulated in the system. In the thirteenth program module, restrictions are set on the values of the obtained results of calculations and estimates, while if the values of the above results and estimates are higher than the maximum permissible energy-saving effect, determined in the twelfth program unit by expert judgment, the maximum permissible specific value of the energy-saving effect is taken as the resulting estimate of the energy-saving effect , obtained by the method of expert evaluation.

The third subsystem, which includes software modules from the fourteenth to the seventeenth, is made with the ability to process the detailed results of modeling typical energy-saving measures received from the second subsystem (calculations and estimates of savings in physical and monetary terms, as well as an assessment of the cost of application and payback periods for each object and each appropriate measure for use), for all types of energy resources (primarily such as heat energy, electricity, water and natural gas), in addition, the third subsystem is made with the ability to form a detailed assessment of the energy saving potential of the objects under study. The fourteenth software module is configured to calculate the mutual influence of typical energy-saving measures for each of the objects under study and each of the energy resources. To do this, for each object and for each of the energy resources, calculations of the specific energy-saving effect are used, as the ratio of the absolute value of the energy-saving effect obtained as a result of modeling an event at this object, to the volume of consumption by this object of the energy resource related to this event, and then the energy saving potential is determined for this type of energy resource of this facility with the simultaneous implementation of several typical energy saving measures at this facility. The fifteenth software module is made with the ability to summarize the results of all calculations carried out in the fourteenth software module for energy resources and in general for the group of objects under study. That is, the fifteenth program module is configured to calculate the energy saving potential of the entire group of objects under study for each energy resource as the sum of all energy saving potentials of all objects under study. The sixteenth program module is configured to calculate engineering-based ranking indicators in physical and monetary terms for each object under study and each energy resource. The seventeenth software module is configured to rank the objects under study by typical energy-saving measures using the engineering-based ranking indicators of the entire group of objects under study calculated in the sixteenth program module for each of the energy resources and for each of the standard energy-saving measures.

The fourth subsystem is configured to store the above-mentioned structured data collected in the first subsystem and all results obtained in the second and third subsystems.

The operation of the claimed automated system, as well as, accordingly, the implementation of the claimed method is carried out as follows.

For each of the studied objects of the same type, according to a predetermined list of parameters of the objects of the same type, which is related to the studied objects of the same type, data are collected that affect the consumption of types of energy resources by the objects under study, which primarily include heat energy, electricity, water, natural gas. Also, they collect data on the location and departmental subordination of the objects under study, as well as engineering, technical and financial data related to the mentioned objects under study. The above data are collected both manually and using automated measuring systems. The aforementioned collected data also includes regulatory and reference information, data on the design features of the objects under study, data on the equipment installed on them, as well as data on the current state of the objects under study, data on the standard energy-saving measures taken at the objects under study and plans of higher organizations in in relation to the objects under study. All data about the objects under study is sent to the first subsystem, in the first software module of which, using automated algorithms, the manually collected data is checked for completeness, reliability and consistency, and in the second software module, normative and reference information is processed, after which all collected (manually) , the processed and verified data are sent to the third software module, where they are combined into a structured database, on the basis of which, then, in the second subsystem, using automated algorithms, typical energy-saving measures are simulated for each of the objects under study. This modeling includes first, using the fourth software module, assessing the feasibility of each of the typical energy-saving measures in relation to each of the objects under study, and then, using software modules from the fifth to thirteenth, assessing the energy-saving effect for each consumed energy resource for each of the typical energy-saving measures appropriate for carrying out at each of the studied objects. An assessment of the feasibility of carrying out a specific typical energy-saving measure at a specific object under study is formed using the above-mentioned structured database based on the analysis of such parameters of the objects under study, as the current state of the objects under study, information about the typical energy-saving measures taken at the objects under study and the plans of higher organizations in relation to the objects under study ... In this case, information about the standard energy-saving measures taken at the objects under study and the plans of higher organizations in relation to the objects under study is a collection of information (specific values of individual parameters), which makes it possible to exclude from the modeling process those typical energy-saving measures that have already been carried out at the object under study, as well as do not carry out modeling of typical energy-saving measures at all if there are plans for a major overhaul or demolition of this facility, the facility is included in the renovation program or is an object of cultural heritage (in such facilities, by law, energy saving measures cannot be carried out).

The obtained assessment of feasibility is used to limit the scope of modeling each of the typical energy-saving measures at each of the objects under study. As a result of the introduction of these restrictions, the volume of computational operations performed decreases and the speed of obtaining simulation results increases. In addition, the obtained assessment of feasibility is used as a criterion for the need for a subsequent assessment of the energy-saving effect of each of the typical energy-saving measures at each of the objects under study.

Further, using the information obtained in the data collection process on the completeness and specific composition of the available data for each object under study, for each object under study and each typical energy-saving measure, using the fifth software module, one of the methods for assessing the energy-saving effect is selected, which can be used as : direct calculations (seventh software module), which are carried out in the presence of all data on all parameters of the investigated objects necessary for the calculation, including calculations using an alternative set of parameters of the investigated objects (the eighth software module), calculations with partial restoration of the missing parameters of the investigated objects (ninth software module), as well as simplified calculations with the minimum possible set of parameters of the objects under study (tenth software module); statistical assessment (eleventh software module), which is carried out in the absence of data necessary for direct calculation, and in the presence of statistical data on the estimated value of the energy-saving effect at facilities similar to those under study; as well as expert assessment (twelfth software module), which is used in the absence of data for direct calculations and at the same time in the absence of statistical data.

It should be noted here that the information on the completeness and specific composition of the available data for each object under study is understood as a set of specific values of individual parameters, which makes it possible to choose one of the methods for calculating or assessing the energy saving potential for this object.

One of the evaluation methods selected as a result for each investigated object for each energy-saving measure (M) for each energy resource (p) using one of the sixth to twelfth blocks evaluates the absolute value of the energy-saving effect ΔP _nMr in physical terms (n), after which calculates the specific energy-saving effect δР _nMr , as the ratio of the absolute value of the energy-saving effect to the volume of consumption of this resource Р _n at the investigated object:

,

,

and then, using the thirteenth program module, the obtained specific energy-saving effect is compared with the maximum permissible specific value of the energy-saving effect obtained by the above-mentioned expert evaluation method (twelfth program module), and, if the value of the above-mentioned specific energy-saving effect is higher than the maximum permissible specific value of the energy-saving effect obtained by the method of expert evaluation, the maximum permissible specific value of the energy-saving effect obtained by the method of expert evaluation is taken as the resulting assessment of the energy-saving effect. For all of the above methods for assessing the energy-saving effect using software tuning units (PBN), based on the regulatory information and the accumulated results of the above-mentioned energy-saving effect assessment, the automated algorithms implemented in the software modules from the seventh to the thirteenth are tuned.

Further, using the sixth software module, detailed modeling of typical energy-saving measures is carried out for each of the objects under study and each of the standard energy-saving measures, calculating the costs of implementing appropriate standard energy-saving measures and the payback period for each energy resource, after which all the detailed results obtained simulations are sent to the third subsystem, where the formation of a detailed assessment of the energy saving potential is carried out, which consists in calculating the mutual influence of typical energy saving measures for each investigated object and each energy resource (fourteenth software module), summarizing the results of calculations for energy resources and, in general, for the group of objects under study ( fifteenth program module), the calculation of engineering-based indicators in physical and monetary terms for each investigated object and each energy eh resource (sixteenth program module), as well as in the ranking of the objects under study by typical energy-saving measures (seventeenth program module) in accordance with the calculated indicators. Calculation of the mutual influence of typical energy-saving measures for each investigated object and each energy resource includes the use of the previously calculated for each event the absolute values of the energy-saving effect _{ΔР nMr} in physical terms (n) and the specific values of the energy-saving effect δР _nMr to calculate the energy saving potential _{∆Р it} in in physical terms (n) of each of the objects under study (o) for each type of energy resource (p), taking into account the mutual influence of each of the n typical energy saving measures selected as appropriate for use at the object under study:

The summation of the calculation results for each energy resource (the fifteenth program module) is the determination of the energy saving potential in natural terms of all the objects under study for each energy resource by summing up the energy saving potentials ∆Р _it calculated for each of the objects under study included in the group. Then, using the detailed modeling results for each of the types of energy resources, the calculation of engineering-based indicators in physical and monetary terms (the sixteenth program module) is carried out, and for the totality of all objects under study, the objects under study are ranked for each typical energy-saving measure in accordance with the calculated indicators, among which can be used the absolute and / or specific value of the achieved energy-saving effect in kind, the cost and / or the payback period of a typical energy-saving measure (seventeenth program module). Ranking in ascending or descending order using one or more indicators is used in the future to determine the priorities for the implementation of typical energy-saving measures at the facilities included in the group, depending on the tasks set, after which the results of a detailed and detailed assessment, the values of all indicators, and Also, the results of ranking objects by typical energy-saving measures are saved for further use, including for setting up algorithms for assessing the potential for energy-saving.

The implementation of the claimed method and, accordingly, the operation of the claimed automated system can be clearly seen in the following example.

Data on the objects under study, obtained from automated measuring systems, data on objects collected manually and normative reference information (NSI) are fed through the user interfaces to the first subsystem "Information Gathering". At the same time, in the first software module, using the appropriate automated algorithms, the data that are collected manually are checked for completeness, reliability and consistency.

By checking the data for completeness is understood as the automated detection of the missing data by the system for each object under study for each of the parameters. For example, in table 1 for object 3 there is no (not filled in) the number of elevators in the building and the heated area of the object.

A plausibility check is the correlation of the value of a parameter under test with a predefined format or range of values. For example, the value of parameter 7 in table 1 for object 1 is not reliable, since the number of lifts can only be an integer.

Consistency check is the correlation of the values of several parameters related to one object, according to any formula or set of information. For example, in Table 1 for object 1, the value of parameter 8 (total area of the object) is indicated equal to 10,047 sq. M, and the value of parameter 9 (heated area of the facility) is 11,250 sq. M. There is an obvious contradiction between these parameters (the heated area of the object cannot be larger than its total area), i.e. it is necessary to clarify the value of which of the parameters is indicated incorrectly (or it may be that they are both indicated incorrectly). The likelihood that both parameters are indicated incorrectly is additionally confirmed by the fact that if we divide the total area of object 1 by the number of storeys of the object (parameter 6), it turns out that the area of one floor is about 838 sq. M, which is significantly less than the area indicated in the table. object (building) in terms of 2560 sq.m. (parameter 10).

After checking the data entered manually, all the data using the third program module are brought to a single structure for further processing. An example of such a structure is Table 2, in which the elements of the database structure in relation to the objects under study are formed (only a part of the parameters collected for each object is shown). It should be said that a single structure is formed not only by the form of a table containing sections and subsections, but also by the values taken by parameters - for example, the addresses of objects are formed according to a single principle, the functional purpose of an object is formed through a list (a parameter cannot take an arbitrary text value), etc. .d.

From a comparison of the parameter values in tables 1 and 2 for objects 1-3, it can be seen that structured table 2 contains the values that have passed the validation and consistency checks, as well as empty fields. As will be shown below, the analysis of information on the specific composition of uncompleted parameter values makes it possible to automatically form criteria according to which one of the methods for assessing the energy-saving effect is selected for each object and each energy-saving measure in the second subsystem.

The structured database transferred after its formation from the first subsystem to the second subsystem can contain the values of several hundred parameters for each of the objects under study, of which there can be from several thousand (a small city or Moscow region) to several million throughout Russia. The processing of such a volume of information is possible only in automatic mode and requires significant computing resources. In order to reduce the volume of computational operations performed and increase the speed of obtaining simulation results, using the fourth software module, the feasibility of carrying out each event at each of the objects under study is assessed and the corresponding modeling restrictions are set.

An example of a feasibility assessment (Table 2): the value of the F-39 parameter for object 3 is 1, which means that this object is emergency (see also Table 1). It is unreasonable to carry out any energy saving measures at the emergency facility until it is repaired. Obviously, this object does not need to carry out modeling of any measures in order to determine its energy saving potential, therefore it is equal to zero. For object 4, as can be seen from Table 2, its demolition is planned in 2022 (parameter F-38). This means that for this object it is advisable to carry out only some of the activities that can pay off relatively quickly (the usual payback period for such a typical event should be less than the time remaining before the planned demolition of the building), while activities that usually have a long payback period, it is impractical to carry out. Programming the algorithms set forth above and similar reasoning allows in the automatic mode to work out for each of the objects for each of the measures, restrictions on further modeling.

The choice of the method for assessing the energy-saving effect for each of the objects and for each of the measures that are feasible for use is carried out by the fifth software module, taking into account the restrictions established in the fourth software module. The criteria for choosing one of the methods for assessing the energy saving effect are set by the first software module after checking the collected data for completeness.

The assessment of the expected energy-saving effect from the application of a typical measure at the object under study by various methods using software modules seven through twelve is discussed below using an example.

According to the wording presented in the Federal Law "On Energy Saving and on Improving Energy Efficiency and on Amendments to Certain Legislative Acts of the Russian Federation" dated 23.11.2009 No. 261-FZ, "energy saving is the implementation of organizational, legal, technical, technological, economic and other measures aimed at reducing the volume of energy resources used while maintaining the corresponding beneficial effect from their use. " The word “measures” in the specified law is precisely the measures in the field of energy saving and energy efficiency (EE), which allow to reduce the volume of resource consumption at the facility. E&E activities differ for different types of resources and different types of facilities, as well as regional conditions and are described by regulatory and departmental documents that establish an indicative list of activities in the field of energy efficiency (see Order of the Ministry of Economic Development dated February 17, 2010 No. 61 "On approval of an indicative list of measures in the field of energy conservation and energy efficiency, which can be used to develop regional, municipal programs in the field of energy conservation and energy efficiency").

The description of the proposed method and the information system that implements it is given on the example of a typical event in the field of E&E "replacement of incandescent lamps with LED", then - event number 16 or M16 (the number of the event is selected conditionally).

This measure provides for the replacement of incandescent lamps usually used for lighting purposes with more energy efficient LED lamps (consuming less electricity due to lower electrical power) at the same level of illumination (luminous flux), that is, preserving the beneficial effect of their use (Table 3).

Direct calculation methods are implemented for each of the standard activities by the seventh software module.

In the general case, if the electric power P _{elni of} each of the n incandescent lamps to be replaced and the number of hours per year t _i that each of them is in the on state are _known , then the energy saving effect _{ΔР nM16 is} calculated using the reference data on the power P _{esdi of} LED lamps with the same luminous flux (preservation of the beneficial effect), which will replace incandescent lamps during the event:

It should be noted that the word "can", which is used here and hereinafter when describing methods of calculations and evaluations, is understood in the sense that the claimed method is not limited to the examples of the following methods and formulas, which are generally known. The use of one or another calculation and assessment method for each of the standard activities is inextricably linked with a predetermined list of parameters that will be collected using the information system manually or using automated measuring systems, as well as from sources of reference data and processed in the first subsystem.

In the context of what has been said in practice, for activities similar to M16, involving the replacement of a large number of elements of the same type that differ from each other in different values of their technical characteristics and the operating time of these elements, it is irrational to use the direct calculation method, since this will require collecting data on a large number the elements of equipment installed at the investigated object (for event M16 - electric lamps) and their operating time, which will lead to an unjustifiably large predetermined list of parameters included in a structured database.

Thus, for event M16 for any of the objects, it is impossible to use the direct calculation method due to the lack of the necessary data, and the fifth software module analyzes for each of the objects the possibility of calculating using other methods.

Calculation methods using an alternative set of parameters for each of the typical activities are implemented by the eighth software module.

To obtain the value of the energy-saving effect _{ΔР nM16} , an alternative set of parameters can be used, for example (see table 2 and its continuation - table 4):

P _eolne = F-154 - the total power of incandescent lamps available at the facility (which are planned to be replaced during the event);

t _a = F-220 -srednegodovoe time (hours), during which the facility included lighting,

then to calculate _{ΔР nM16} for each object, you can use the formula:

_{ΔР nM16} = (P _eoln - P _eols ) * t _os , [kW * h] (2),

where P _eols is the total power of LED lamps [kW], planned to be installed instead of incandescent lamps, and which can be determined on the basis of such regulatory and reference indicators as the average luminous efficiency K _from which for incandescent lamps (K _solar ) and for LED lamps ( K _sols ) takes different values (table 3):

P _eols = P _eols * K _solar / K _sols , [kW] (3).

After reducing formulas (2) and (3) to one formula (4), the value of the energy-saving effect obtained using an alternative set of parameters will be for the first object (see table 2 and table 4):

_{ΔР nM16} = P _eoln * (1 – K _solar / K _sols ) * t _os = 6.375 * (1 - 17/90) * 5840 =

= 30198 [kW * h]. (4).

Accordingly, the value of the specific energy-saving effect δР _nM16 for the first facility, taking into account the fact that the annual consumption of the resource (electricity) P _ne at the facility is equal to 146,024 [kW * h], will be (table 4):

δP _nM16 = ΔP _nM16 / P _ne = 30198/146024 = 20.7 [%] (5).

Calculation methods with partial restoration of unfilled parameters for each of the standard measures are implemented by the ninth software module.

If there is not enough data for direct calculation or calculation based on an alternative set of parameters, it is possible to recover some of the unfilled data using automated algorithms.

Tables 2 and 4 show an example of a structured database. Cells with a yellow background show fields that were not initially filled in during data collection (“blank” fields). In this case, for example, for objects 2 and 3, "empty" fields of parameters F-151 and F-153 contain the values shown in red font.

For example, for the third object, the values of the parameters F-150 and F-152 coincide (the total number of lamps is equal to the number of incandescent lamps), which means that the parameters of F-151, F-153, F-155 are equal to 0 (restored). In this case, the total power of incandescent lamps (parameter F-154) can also be approximately estimated (restored). Since there are no other lamps at this facility (warehouse), all the electrical power allocated for lighting is consumed by incandescent lamps, that is, it can be assumed that the total power of incandescent lamps (the "recoverable" parameter F-154) is approximately equal to the one known for object 3 of electrical power allocated for lighting (F-121). Dividing the restored value of the F-154 (1000 W) parameter by the number of F-152 lamps (18), we obtain that the average power value of one incandescent lamp is 55.6, which corresponds to the range in which the average value of the electric power of one incandescent lamp can be ... After automatic restoration of the F-154 parameter, the absolute value of the energy-saving effect can be calculated by the formula (4), and the specific value - by the formula 5 (see table 4).

Simplified calculation methods with the minimum possible set of parameters for each of the typical activities are implemented by the tenth software module.

For the M16 event, the minimum possible set of parameters for the calculation are 2 parameters: F-34 - the functional purpose of the object and F-151 = N _ell - the number of incandescent lamps at the object.

The calculation can be carried out based on two assumptions (object 6, tables 2 and 4):

- the electrical power of any incandescent lamp used at the facility is in the range from 40 to 100 W;

- the time (number of hours per year) of lighting use corresponds to the normative and statistical time typical for similar objects in this region.

Then the value of the energy-saving effect obtained using the minimum set of parameters can be approximately calculated by the formula (see formula (4)):

_{ΔР nM16} = N _ell * (0.100 + 0.040) / 2 * (1 – K _solar / K _sols ) * t _ossr , [kW * h] (6),

where t _ossr can be determined by calculating the average operating time of lighting for similar objects by analyzing the data accumulated in the system, and the specific value of δР _nM16 can be determined by the formula:

δР _nM16 = _{ΔР nM16} / P _normal , [%] (7),

where the average value of electricity consumption P _standard can be obtained based on regional standards for individual residential buildings in which metering devices are not installed (since the volume of electricity consumption is not indicated for object 6).

Statistical evaluation methods for each of the typical activities are implemented by the eleventh software module.

Objects 5 and 7 (Tables 2 and 4) can serve as an example of the implementation of the method of statistical evaluation. Table 2 shows that for these objects one of the key parameters necessary for the calculation (the number of incandescent lamps) is not indicated.

For object 5, which is a typical residential building of a known series (parameter F-60, the value is equal to I-522), you can use a statistical sample of the already calculated i values of _{ΔР nM16i} for this series of buildings based on the data stored in the system. Suppose that the system stores information on M objects. Then it can be assumed that the absolute value of _{ΔР nM16} for the 5th object can be estimated as the average value from M:

and the specific value of δР _nM16 , since the 5th object has information about electricity consumption (parameter F-184 = P _ne in Table 4 for object 5 is filled), can be determined by the formula:

δР _nM16 = _{ΔР nM16sr} / P _ne . (nine).

For object 7, tables 2 and 4 do not indicate anything, except that the object is an individual residential building (parameter F-34) with an area of 186 sq.m. (parameter F-70 = S _about ). For object 7, which is an object of individual construction, it is possible to use a statistical sample of the already calculated i values of ΔP _nM16i for similar objects based on the data stored in the system. Suppose that the system stores information on N objects of individual housing construction. Then it can be assumed that the absolute value of _{ΔР nM16av} for 7 object can be estimated as the average value of N similar to formula (8). Since to calculate δР _НМ16 it is also required to know P _ne, (for object 7 it is not indicated in Table 4), it can be estimated through the specific indicator k _ees - the average electricity consumption per unit of total area for individual residential construction objects:

after which the total electricity consumption P _nei for object 7 can be calculated by the formula:

P _nei = S _about * k _ee [kW * h], (11),

and then calculate δР _nM16 by formula (9).

Expert assessment methods for each of the typical activities are implemented by the twelfth software module.

The expert assessment is the result of the generalized opinion of the expert community in the field of energy saving in relation to measures aimed at saving energy resources, for example, as set out in the "Methodological recommendations for calculating the effects of the implementation of measures to save energy and increase energy efficiency" (Analytical Center for the Government of the Russian Federation . National Research University, Moscow Power Engineering Institute, Moscow 2016). Within the framework of the proposed method and the automated system that implements it, the method of expert evaluation is used if the data required for calculations or statistical evaluations is insufficient. To apply the expert judgment, it is necessary to know only the volume of resource consumption, the saving of which the measure is aimed at (if the volume of resource consumption is unknown, then no assessment is possible, since there is no subject of savings).

The ranges of possible expert assessments from the implementation of various energy saving measures in the lighting and power supply systems of buildings are shown in Table 5.

In Tables 2 and 4 for the M16 event, an example of the application of an expert assessment (Table 5) can be object 8, for which only the volume of electricity consumption is indicated from the entire list of characteristics (parameters).

The specific energy-saving effect can, for example, be defined as the arithmetic mean of the range of expert judgment (clause 1 of Table 5):

δР _nM16 = (70 + 55) / 2 = 62.5%, (12),

then the absolute value of the energy-saving effect will be:

ΔР_nM16 = δР_nM16 * P_ne [kWh]. (13).

The verification of the results obtained by one of the methods for evaluating the results for each object and each event and, if necessary, the introduction of restrictions on the simulation results is carried out by the thirteenth program block, which imposes expert restrictions on the results obtained in order to exclude unreliable values of calculations and estimates.

For example, the value of parameter M16-1 ( _{ΔР nM16} ) for object 2, (obtained by a calculation method with partial restoration of unfilled parameters, see parameter M16-3 in Table 4 for this object) is 6 706 [kW * h], and the specific value of δP _nM16 (parameter M16-2) is equal to 26.3 [%].

Taking into account the fact that for the purpose of lighting at the second object, according to the assessment of an energy saving specialist, about 30% of the total electricity consumption is spent (parameter F-200 in Table 4), then the power consumption P _nos for lighting purposes is:

R _nos = 0.3 * R _ne = 0.3 * 25299 = 7590 [kW * h], (14),

and the specific value of the energy-saving effect related to the consumption of electricity for lighting (and not to the total consumption) will be:

δP _nM16bw = _∆PnM16 / _Pbw = _6706/7590 = 88.4 [%]. (15).

At the same time, according to an expert assessment (clause 1 of Table 5), the specific value of the energy-saving effect (saving) when replacing incandescent lamps with fluorescent or LED lamps should not exceed 70% of the electricity they consume.

In this case, in the thirteenth program block, the final assessment for such an event / object is recalculated to a value corresponding to the maximum permissible (maximum) specific expert assessment:

_{ΔР nM16 (total)} = _{ΔР nM16} * 70 / 88.4 = 5313 [kW * h], (16),

and the specific value of δР _{nM16 (total)} will be for this object:

δР _{nM16 (total)} = _{ΔР nM16 (total)} / Р _ne = 5313/25299 = 21.0 [%]. (17).

It should be noted here that the above formulas and methods are well-known, and the purpose of their application is to automate the assessment of the energy-saving effect using a combination of methods that makes it possible to obtain the final values for each object and for each event, despite the absence of certain initial data. In this case, the choice of the assessment method by the fifth software module is carried out in such a way that, depending on the composition of the initial data, when choosing the assessment method, one can switch from more accurate (calculated) assessment methods to less accurate (statistical and expert). As a result (see Table 4, parameters M16-1, M16-2, M16-3) for each facility and each event, it is possible to calculate the values of the absolute and specific energy-saving effect, which can be obtained as a result of the implementation of energy-saving measures.

After performing all calculations and assessments and, if necessary, bringing the obtained results to the final values using the thirteenth software module, detailed modeling of energy-saving measures for all objects is performed using the sixth software module. Detailed modeling is understood as carrying out by well-known methods of calculating the cost of implementing an event and its simple payback period.

Detailed modeling of energy saving measures is carried out using data included in a structured database and related to specific objects, as well as regulatory and reference information - tariffs, cost of materials and work, etc. The results of detailed modeling are structured by resource type and transferred to the third subsystem, in which a detailed assessment of the energy saving potential is performed.

Within the framework of the proposed method of express assessment and the automated system that implements it, the energy-saving potential is understood as the cumulative energy-saving effect of the entire group of objects under study, which can be achieved as a result of all energy-saving measures that are reasonable for use at each of the objects under study for all types of resources.

A detailed assessment of the energy saving potential within the framework of the proposed method of express assessment and the automated system that implements it is understood as a set of representations (generalized forms of displaying information) formed on the basis of engineering-based indicators, which allows to determine, in conditions of limited funding, the priorities for the implementation of energy-saving measures by types of resources and activities , both for all investigated objects, and for an arbitrary sample from a group of objects included in the totality of all investigated objects.

The determination of the energy saving potential of each of the objects for each of the resources is performed by the fourteenth program unit.

In order to determine the potential for energy saving (saving) of any resource of one object, it is necessary to take into account that as a result of modeling for this object for this resource, several measures can be selected. At the same time, the total energy-saving effect (resource saving) that can be achieved at this facility cannot be determined as the sum of energy-saving effects achieved as a result of the implementation of each of the selected measures.

For example (table 5) if one object is to carry out measure 1 (replacement of lamps with energy efficient ones, saving δР _n up to 70% of initial consumption) and measure 5 (installation of motion sensors to turn off lighting in the absence of personnel, saving δР _n up to 70%), then simply summing up the savings achieved would lead to a clearly implausible result (the total savings would be 140%). Obviously, the implementation of several measures within the framework of saving 1 resource leads to the need to calculate the total energy-saving effect (the energy saving potential of this resource at this facility), taking into account the mutual influence of measures on each other.

The method of accounting for the mutual influence of measures proposed within the framework of the proposed method and the automated system that implements it can be explained using the previous example. Suppose, at the facility, the initial consumption of electricity P _ne1 for lighting was
100 kWh After the implementation of measure 1, the savings δР _Н1 amounted to 70%, that is, the consumption of electricity Р _Нэ2 decreased and became equal to 30 kW * h. Then, after the implementation of measure 5, a 70 percent saving is also achieved, but not from the initial consumption (100 kW * h), but from the consumption of electricity, which became after the introduction of the 1st measure. Thus, the total consumption Р _{ne1 + 2} after the introduction of 2 measures will be:

R _{ne1 + 2} = R _ne1 * (1- δR _n1 ) * (1- δR _n2 ) = 30 * 0.3 = 9 [kWh], (18),

that is, savings (100-9) = 81 kWh will be achieved, which is 81% of the initial consumption (and not 140% at all).

The generalized formula that implements the proposed principle allows calculating the value of the energy-saving effect that can be achieved at the facility ΔР _it in the case of the simultaneous implementation of n measures (M) aimed at saving one resource:

(19).

(19).

The fifteenth software module brings together the results of calculations for resources and for a group of objects as a whole. The reduction of the calculation results is carried out by summing up the energy saving potentials obtained using formula (19) for objects and for each resource. The results obtained are included in a structured database in relation to each object and reflect its individual characteristics.

The fifteenth software module calculates engineering-based indicators in physical and monetary terms for each object and each resource. Under engineering-based indicators within the framework of the proposed method of express assessment and the automated system that implements it, we mean any indicators that can be used to understand the processes associated with the consumption of energy resources, as well as their savings, expressed in natural and monetary terms. For example, for such a resource as electricity, in relation to one object or an arbitrarily formed (on a territorial, departmental basis or by any other parameter contained in a structured database principle) a group of objects can be defined:

- electricity consumption (in kWh and in rubles);

- energy saving potential (in kWh and in rubles);

- specific electricity consumption (in kWh and in rubles) per resident or employee / visitor of the institution;

- the cost of an energy-saving event or a group of events (in rubles), etc.

As part of the description of the proposed method of express-assessment and the automated system that implements it, the term "engineering-based" is used in the sense that the calculation of any of the indicators is based on the initial data verified for completeness, reliability and consistency, as well as on the results of calculations and estimates based on on engineering approaches to assessing the potential of energy saving and regulatory and technical indicators used to form a detailed assessment of the potential for energy saving.

The seventeenth software module ranks objects by activities, placing objects for each of the standard activities in ascending or descending order, depending on the task at hand.

As a result, the ideas necessary for analysis, prioritization and decision-making on the implementation of energy-saving measures in the context of limited funding are formed.

The implementation of the claimed group of inventions makes it possible to achieve the technical feasibility of performing an engineering-based assessment of the energy saving potential of a group of similar objects in the conditions of a partial lack of data on these objects, increasing the accuracy and reliability of calculations and estimates, reducing the total time for assessing the energy saving potential, as well as improving the quality of presentation of results assessing the energy saving potential necessary for making engineering-based decisions to improve the energy efficiency of the specified group of objects in the context of limited funding for energy saving measures, which significantly increases the efficiency of determining the energy saving potential of a large group of similar objects.

Method for express assessment of energy saving potential

groups of similar objects and a system for its implementation

Table 1

Method for express assessment of energy saving potential

groups of similar objects and a system for its implementation

table 2

Method for express assessment of energy saving potential

groups of similar objects and a system for its implementation

Table 3

Method for express assessment of energy saving potential

groups of similar objects and a system for its implementation

Table 4

Method for express assessment of energy saving potential

groups of similar objects and a system for its implementation

Table 5

No. Name of the event Range of possible
saving resources,% one Replacing incandescent lamps with fluorescent, LED up to 55-70% of the electricity they consume 2 Replacement of fluorescent lamps with lamps of the same type with a higher quality phosphor (energy efficiency class A, A +) up to 25% of the electricity they consume 3 The use of ballasts for energy efficient gas discharge lamps 15-20% of the electricity they consume 4 Optimization of the lighting system by installing several switches and dividing the lighting area into zones or by sectional regulation of the luminous flux level (dimming) 10-15% of the electricity they consume 5 Installation of motion sensors to turn off the lighting in the absence of personnel From 10% to 70% of the electricity they consume, depending on the operating mode of the lighting before installing the sensors 6 Selection of the optimal wall colors, furniture items for staff 8-15% savings 7 Keeping skylights clean 6-11% savings

Claims (6)

1. A method of express assessment of the energy saving potential of a group of investigated objects of the same type, during which, in order to assess the energy saving potential for each of the investigated objects of the same type, according to a predetermined list of parameters related to the investigated objects of the same type, data are collected that affect the consumption of all types of energy resources, which primarily include thermal energy, electricity, water, natural gas, in addition, they collect data on the location and departmental subordination of the objects under study, as well as engineering, technical and financial data related to the mentioned objects under study, while the collection of the above data is carried out both manually and with the help of automated measuring complexes, and in the composition of the above data, normative and reference information, data on the design features of the objects under study, data on the equipment installed on them, as well as data on the current state of the objects under study, data on the typical energy-saving measures taken at the objects under study and the plans of higher organizations in relation to the objects under study, then part of the mentioned collected data is checked for completeness, reliability and consistency using automated algorithms , after which all the collected and verified data are combined into a structured database, on the basis of which the modeling of typical energy-saving measures for each of the objects under study is then automatically carried out, while this modeling includes first assessing the feasibility of carrying out each of the standard energy-saving measures in relation to each from the objects under study and then assessing the energy-saving effect for each consumed energy resource for each of the typical energy-saving measures appropriate for conduct at each of the objects under study, while the assessment of the feasibility of carrying out a specific typical energy-saving measure at a specific study object is formed using the above-mentioned structured database based on the analysis of such parameters as the current state of the objects under study, information about the standard energy-saving measures taken at the objects under study, and plans of higher organizations in relation to the objects under study, after which the obtained assessment of feasibility is used as a criterion for the need for a subsequent assessment of the energy-saving effect of each of the typical energy-saving measures at each of the objects under study, then, using the information obtained in the data collection process about the completeness and specific composition of the available data for each investigated object, for each investigated object and each typical energy-saving measure, one of the methods for assessing energy-saving effect, which are: direct calculations, which are carried out in the presence of all data on all parameters of the investigated objects necessary for the calculation, including calculations using an alternative set of parameters of the investigated objects, calculations with partial restoration of the missing parameters of the investigated objects, as well as a simplified calculation with the minimum possible set of parameters of the objects under study, a statistical assessment, which is carried out in the absence of data necessary for direct calculation, and in the presence of statistical data on the estimated value of the energy-saving effect on objects similar to the investigated ones, as well as expert judgment, which is used in the absence of data for direct calculations and at the same time in the absence of statistical data, after which one of the selected assessment methods for each object under study for each energy-saving measure (M) for each energy resource (p) perform an assessment of the absolute value of energy saving effect _{ΔР nMr} in natural terms (n), then the specific energy-saving effect δР _{nMr is calculated} as the ratio of the absolute value of the energy-saving effect to the volume of consumption of this resource Р _n at the object under study:

, after that, the obtained specific energy-saving effect is compared with the maximum permissible specific value of the energy-saving effect obtained by the above-mentioned method of expert evaluation, and, if the value of the above-mentioned specific energy-saving effect is higher than the maximum permissible specific value of the energy-saving effect obtained by the method of expert evaluation, for the resulting assessment energy-saving effect, the maximum permissible specific value of the energy-saving effect obtained by the method of expert assessment is taken, while for all the above-mentioned methods for assessing the energy-saving effect, the setting of automated algorithms is used based on the normative and reference information and the accumulated results of the above-mentioned assessment of the energy-saving effect, then detailed modeling of typical energy-saving measures for all investigated objects, calculating the costs of the implementation of feasible standard energy savings saving measures and their payback period for each energy resource, and then form a detailed assessment of the energy saving potential, which includes the above-mentioned absolute value of the energy-saving effect _{ΔР nMr} in physical terms (n) and the specific energy-saving effect δР _nMr , as well as the energy saving potential of each of of the studied objects (o) in kind ∆Р _it (n) for each type of energy resource (p), calculated taking into account the mutual influence of each of the n typical energy saving measures selected as appropriate for use at the object under study:

, after that, the results of calculations for each resource are brought together, determining the energy saving potential in kind of all the objects under study for each energy resource by summing up the energy saving potentials ∆Р _it calculated for each of the studied objects included in the group, then they are carried out using the detailed simulation results for each of the types of energy resources, the calculation of engineering-based indicators in physical and monetary terms, and for the totality of all studied objects, the objects under study are ranked for each typical energy-saving measure in accordance with the calculated indicators, among which the absolute and / or specific value of the achieved energy-saving effect in in physical terms, the cost and / or payback period of a typical energy-saving event, and ranking in ascending or descending order using one or more impressions They are used in the future to determine the priorities for the implementation of typical energy-saving measures at the facilities included in the group, depending on the tasks set, after which the results of a detailed and detailed assessment, the values of all indicators, as well as the results of ranking objects by typical energy-saving measures are saved for further use, including for setting up algorithms for assessing energy saving potential. 2. An automated system for express assessment of the energy saving potential of a group of similar objects, which includes the first subsystem "Information Gathering", the second subsystem "Modeling typical energy-saving measures for all investigated objects", the third subsystem "Detailed assessment of the energy saving potential" and the fourth subsystem "Information storage ", While the first subsystem is made with the possibility of collecting data on a predetermined, related to the objects of the same type, the list of parameters affecting the energy consumption of each of the objects under study, including reference information related to the objects under study, as well as with the possibility of bringing the mentioned above the data to a single structure and their transfer for processing to the second subsystem, which is made with the possibility of analyzing the feasibility of carrying out each of the typical energy-saving measures in relation to each of the objects under study, while As energy-saving ones, standard measures can be taken aimed at saving energy resources, such as, first of all, heat energy, electricity, water and natural gas, in addition, the second subsystem is made with the ability to simulate typical energy-saving measures in relation to each investigated object and with taking into account the previously determined expediency, including the assessment or calculation of the energy-saving effect achievable in this case, in addition, the second subsystem is made with the possibility of detailing the obtained modeling results, which includes an estimate of the costs of carrying out each of the simulated standard energy-saving measures at each of the studied objects and calculating the timing of their payback, as well as the transfer of all the results obtained to the third subsystem, which is designed to process the detailed results of modeling of typical energy-saving measures for all types of energy received from the second subsystem physical resources, in addition, the third subsystem is made with the possibility of forming a detailed assessment of the energy saving potential of the objects under study, which includes calculations of the mutual influence of typical energy-saving measures for each object under study and energy resource, summarizing the results of calculations for energy resources and in general for the group of objects under study, calculations of engineering-based indicators, in addition, the third subsystem is configured to perform ranking of objects by energy resources and simulated typical energy-saving measures, and the fourth subsystem is configured to store the above data collected in the first subsystem and all results obtained in the second and third subsystems, while the first subsystem includes the first, second and third software modules, and the first software module is configured to check the collected data for completeness, reliability and consistency according to the parameters of the objects under study, affecting the energy consumption of each of the objects under study, as well as the first software module is equipped with the first software unit made with the possibility of determining, based on the results of checking the data for completeness, criteria for choosing a method for assessing the energy-saving effect and transferring them to the second subsystem, the second software module is configured to process the data on the parameters of the objects under study that affect energy consumption, which are received on the basis of the reference information, and the first and second software modules are configured to transfer the data processed by them to the third software module, the queue is configured to bring all the data received into it from the first and second software modules to a single structured database for their subsequent transfer to the second subsystem, which forms on the basis of the data received from the first subsystem х and criteria for choosing a method for assessing energy-saving effect, detailed results of modeling typical energy-saving measures aimed at saving the above-mentioned energy resources, while the second subsystem includes software modules from the fourth to thirteenth, the fourth software module is configured to assess the feasibility of carrying out typical energy-saving measures in relation to each of the objects under study, the fifth program module is configured to select one of the methods for assessing the energy-saving effect, which can be obtained as a result of the implementation of a typical energy-saving measure on the object under study, the sixth program module is made with the ability to conduct detailed modeling of typical energy-saving measures for all the objects under study, including the calculation of the cost of carrying out typical energy-saving measures in relation to each of the studied objects projects and payback periods of the specified typical energy-saving measures, and the program modules from the seventh to the thirteenth are made with the possibility of forming calculations and estimates of the energy-saving effect using various methods, which, depending on the criteria defined in the first subsystem, can be selected performed by the seventh software module direct calculations, which are carried out in the presence of all data on all parameters of the objects under study necessary for the calculation, calculations performed by the eighth software module using an alternative set of parameters of the objects under study, performed by the ninth software module calculations with partial restoration of missing parameters of the objects under study, as well as performed by the tenth software the module simplified calculations with the minimum possible set of parameters of the objects under study, performed by the eleventh software module statistical evaluations, which are carried out in the absence of data necessary for calculations, and in the presence of statistical data on the estimated value of the energy-saving effect on objects similar to those under study, as well as expert assessments performed by the twelfth software module, which are carried out in the absence of data for direct calculations and the absence of statistical data, while restrictions are set in the thirteenth software module on the values of the obtained results of calculations and estimates, while in the case if the values of the above results and estimates are higher than the maximum permissible energy-saving effect, determined in the twelfth program block by an expert assessment, the maximum permissible specific value of the energy-saving effect obtained by the method of expert assessment is taken as the resulting assessment of the energy-saving effect , in addition, all the program modules from the seventh to the thirteenth are equipped with program blocks made with the possibility of setting all the mentioned program modules, from the seventh to the thirteenth, depending on from the normative and reference information related to the objects under study and the information accumulated in the system, the third subsystem includes program modules from the fourteenth to the seventeenth, while the fourteenth program module is designed to calculate the mutual influence of typical energy-saving measures while simultaneously implementing them on one object and determining the energy saving potential of each object under study for each energy resource, the fifteenth software module is configured to calculate the energy saving potential of the entire group of objects under study for each energy resource as the sum of all energy saving potentials of all the objects under study, the sixteenth software module is configured to perform calculations of engineering-based indicators ranking in physical and monetary terms for each of the objects under study and energy resource, and the seventeenth software module is configured to rank the objects under study by standard energy-saving measures using the engineering-based ranking indicators of the entire group of objects under study calculated in the sixteenth software module for each of the energy resources or for each of the standard energy-saving measures.

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