DEVELOPMENT OF SOFTWARE FOR AUTOMATIC GEOGRAPHIC INFORMATION SYSTEM OF HEAT CONSUMPTION METERING SYSTEM IN MULTICOMPARTMENT BUILDINGS

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International Journal of Civil Engineering and Technology (IJCIET)
Volume 9, Issue 12, December 201
Available online at http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=9&IType=12
ISSN Print: 0976-6308 and ISSN Online: 0976
©IAEME Publication
DEVELOPMENT OF SOFTW
AUTOMATIC
SYSTEM OF HEAT CONSU
SYSTEM IN
Andrey Aleksandrovich Larchikov, Aleksandr Viktorovich Larchikov, Dmitry
National Research University
ABSTRACT
Accurate assessment of energy consumption including heat and its fair distribution
in multicompartment buildings with centralized heating systems can become a key
factor in the field of energy
individual heat consumption is a very complicated problem, its solution is very urgent
for housing and utilities services
have resulted in development of innovative intelligent systems
engineering tools and software
this information to consumer
accounting and billing of individual heat consumption
makes it possible to improve energy saving
remote monitoring of
multicompartment buildings
determine incorrect records by metering devices
to trace for leakages and emergency situation during heat supply to consumers, thus
providing numerous advantages of this system f
Keywords: Geographic Information System, Intelligent Monitoring System; Thermal
Energy; Accounting of Individual Energy Con
Cite this Article: Andrey Aleksandrovich Larchikov, Aleksandr Viktorovich
Larchikov and Dmitry Borisovich Rygalin, Development of Software For Automatic
Geographic Information System of Heat Consumption Meteri
Multicompartment Buildings
Technology (IJCIET) 9(12
http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=9&IType=12
IJCIET/index.asp 339 editor@iaeme.com
International Journal of Civil Engineering and Technology (IJCIET)
2018, pp. 339–347, Article ID: IJCIET_09_12_03
6308 and ISSN Online: 0976-6316
Scopus Indexed
DEVELOPMENT OF SOFTWARE FOR
IC GEOGRAPHIC INFORMATI
SYSTEM OF HEAT CONSUMPTION METERING
SYSTEM IN MULTICOMPARTMENT
BUILDINGS
Borisovich Rygalin
National Research University of Electronic Technology,
Moscow, 124498, Russia
factor in the field of energy saving and efficiency improvement.
for housing and utilities services. Advantages in the field of information technologies
resulted in development of innovative intelligent systems which
engineering tools and software capable to acquire data, process results, and
this information to consumer. Application of geographic information system for
of individual heat consumption in multicompartment buildings
makes it possible to improve energy saving. The developed system would enable
remote monitoring of heat consumption at various facilities including
buildings. Intelligent analysis of the acquired data would allow to
determine incorrect records by metering devices, to plan future resource consumption
providing numerous advantages of this system for housing and utilities services
Geographic Information System, Intelligent Monitoring System; Thermal
Individual Energy Consumption.
Andrey Aleksandrovich Larchikov, Aleksandr Viktorovich
Geographic Information System of Heat Consumption Metering System In
Multicompartment Buildings, International Journal of Civil Engineering and
2), 2018, pp. 339–347.
editor@iaeme.com
037
ARE FOR
GEOGRAPHIC INFORMATION
MPTION METERING
OMPARTMENT
,
. Accounting of
Advantages in the field of information technologies
which combine
acquire data, process results, and supply
Application of geographic information system for
in multicompartment buildings
The developed system would enable
heat consumption at various facilities including
sis of the acquired data would allow to
to plan future resource consumption,
or housing and utilities services.
Geographic Information System, Intelligent Monitoring System; Thermal
Andrey Aleksandrovich Larchikov, Aleksandr Viktorovich
ng System In
International Journal of Civil Engineering and

Andrey Aleksandrovich Larchikov, Aleksandr Viktorovich Larchikov and Dmitry Borisovich Rygalin
http://www.iaeme.com/IJCIET/index.asp 340 editor@iaeme.com
1. INTRODUCTION
According to statistical data, about 40% of energy are consumed for heating of residential
buildings accompanied by 36% of CO2 emissions. About 35% of buildings in EU are over 50
years old, in Russia 33% of residential buildings were built before 1970, and the issue of
efficient energy consumption is related with the age of available housing. The main portion of
equipment in Russia was commissioned more than 30 years ago, now it is overaged.
Numerous countries create laws devoted to development of heat supply. In 2012 EU adopted
directive on energy efficiency (EED) which stipulated a set of obligatory measures aimed at
improvement of energy efficiency by 20% to 2020. This directive is the core of the legislative
base for accurate accounting and metering of heat consumption in heating systems in EU
countries. On November 30, 2016 according to the program Clean Energy For All Europeans,
European Commission proposed to update Directive on the energy performance of buildings
(EPBD) in order to promote application of intelligent technologies in buildings, to normalize
the existing rules, and to accelerate retrofitting of buildings [1].
In recent years in Russia efficiency of heating supply decreases:
• Coefficient of heat utilization continuously decreases.
• Excessive heat is generated by thermal power generation plants, up to 40% of heat are
released into ambient environment.
In Russian heat supply systems local and individual adjustment of heat load is not applied
adequately. This can be attributed to absence of automated consumer connections and heating
appliances. Widely applied heat distribution system does not permit to adjust heat load in the
system. Without adjustment on consumer connection, the centralized regulation is carried out
not on the basis of current temperature of ambient air but on the basis of averaged values for
several hours. Due to the extended distance of heating networks, long time of water passing
the water temperature for the most remote consumers varies with certain delay. The network
water temperature does not conform to the continuously varying temperature of ambient air,
and its daily variations can be from 10°C to 20°C [2].
Heating expenses increase due to increase in production costs of heat supplied to
consumers. In order to reduce the expenses, complete and accurate information on heat
consumption is required. At present in order to obtain information on heat consumption heat
meters are installed in apartments. Locations of such meters are not always accessible for
inspectors and this is used by unscrupulous consumers. Completeness and accuracy of the
acquired information is low, and it is impossible to detect leakage or faulty meters without
consumer consent or application [3].
Intelligent apartment heat meters available at present in markets are characterized by
approximately the same performances as convenient portable devices. Heat meters for
apartments with single and double vertical piping arrangement operate with the temperature
difference of heat carrier of about 1°C, which, taking into account all available possibilities to
improve accuracy of temperature measurements, decreases the accuracy of heat measurements
in comparison with conventional heat meter [4, 5, 6].
This article describes the developed innovative geographic information system (GIS) of
accounting and metering of energy consumption. The GIS is based on wireless intelligent
monitoring system of individual energy consumption including heat and permits remote
monitoring of energy consumption by various facilities of housing and utilities services [6,
7].
The GIS structure and soft- and hardware package (SHP) of the GIS system of energy
monitoring in multicompartment housings are described.

Development of Software For Automatic Geographic Information System of Heat Consumption
Metering System In Multicompartment Buildings
2. SHP OF GIS FOR ENERGY CONSUMPTION MONITORING
SHP of GIS integrates individual hardware components, provides their interaction with
associated equipment, transfer, storage and analysis of the acquired information, data
exchange with external systems, control of actuating mechanisms, and interaction with end
consumers by means of client software. The GIS software is developed in Assembler in
combination with Code Composer Studio Integrated Development Environment - v4.x. The
SHP performs the following functions: generates cyclograms of temperature measurements,
converts measured voltage by temperature sensor into digital code, calculates temperature by
mathematical model, provides calculated results for storage, collection, and displaying of
temperature measurements [3, 8].
Difficulties of SHP of GIS synthesis and resource accounting can be attributed to two
main issues: necessity to provide high data accuracy and optimization of association among
components of single system [9, 10].
The data acquisition and processing system is geographically distributed and comprised of
numerous hardware components linked by communication lines and software, which in its
turn is comprised of several components, each of them solves its own task of data acquisition
and processing. The SHP of GIS is based on wireless sensor network. The network
components are illustrated in Fig. 1:
Figure 1. Component model of GIS of energy metering and accounting: 1 - Central transceiver
station; 2 - Commercial electricity meter; 3 - Current electricity meter; 4 - Input of discrete signals on
facility state; 5 - Generation of control commands for power units; 6 - Information exchange in
communication line; 7 - Heat energy meter; 8 - Water consumption meter.
The most important advantages of systems on the basis of wireless sensor networks are as
follows:
• Wireless sensor networks eliminate necessity to route cables saving resources, minimizing
times of system installation on sites, and simplifying assembling.
• Versatility, nearly unlimited possibility of expansion and scaling up.
Information model of SHP of GIS system flows is illustrated in Fig. 2.

Figure 2. Information model of system flows: 1 - Data acquisition from sensors; 2 - Parameter
measurement; 3 - Parameter monitoring; 4 - Output of discrete signals of equipment state; 5 - Output
of analog signals of equipment state; 6 - Generation of control test impacts; 7 - Engineering
diagnostics of system instruments; 8 - Intermediate data processing; 9 - Data decoding; 10 - Data
transfer via communication line; 11 - Data analysis and processing on central working station; 12 -
Data displaying; 13 - Accounting of hot and cold water consumption; 14 - Accounting of heat
consumption.
Depending on heating system, thermal energy is accounted and analyzed by one of two
different flowcharts. Metering channel in both cases is arranged according to similar principle
and is equipped with flow meters of heat carrier connected to single-channel pulse meter,
SIB-1K, and wireless temperature meters, ITB-1 (WTM). Then the data after necessary
functional conversions via wireless channel are transferred to local retranslator. Calculations
of final thermal energy are performed at the system central server.
The system operates with single-channel pulse meter, SIB-1K. The wireless pulse meters
count pulses from devices with pulse output and transfer them via wireless channel to local
retranslator.
The main functions of SIB-1K are as follows:
• automatic data acquisition and processing from individual apartment meters via pulse
interface;
• provision of wireless channel with devices of upper level of SHP via RS-485 interface
(ModBus RTU protocol);
• storage of configuration data in order to provide recovery of complete operability after any
faults in SHP [7].
IYB-1 is a wireless meter of heat carrier temperature in heat exchangers of building
intended for:
1. metering heat carrier temperature at preset time interval between measurements;
2. conversion of measured temperature into digital code with predetermined error;
3. storage of measured parameters during 30-60 min;
4. storage of temporary base with the error of at least ±0.1% and possibility to be adjusted by the
System central server (or housing retranslator);
5. Wi-Fi operation in wireless sensor network;
6. generation of idle and active intervals in order to minimize operation of built-in battery;
7. transfer of measured and calculated data to local retranslator (LCT) or housing retranslator via
wireless line according to preset schedule;
8. self-testing;

9. operation in various modes in order to provide calibration, configuration, adjustment of
measurement schedule and data transfer [11].
Analysis of WTM specifications demonstrated that its application as an SHP component
would provide superior efficiency together with simultaneous achievement of maximum
operation lifetime of WTM batteries.
LRT serves a basic station for metering devices and collects, stores, and transfers data
from terminal SHP devices to housing retranslator. In order to exclude information overlay,
data exchange of all remote devices is based on time sharing. All LRT are combined into total
network by wired RS-485 interface and connected to housing retranslator. Therefore, more
than 100,000 consumers can be connected to one system (SHP).
The main purpose of the housing retranslator is data acquisition from LRT. In the housing
retranslator the acquired data are processed, archived, and transferred to the system central
server. The central server processes the data using dedicated software, then the data are
considered as consumed energy resources. Housing retranslator can also serve as the system
central server with installed special software.
The system central server is a software module comprised of data base and applications
which can be installed in housing retranslator with remote network access. The central server
is used for calculations, displaying of parameters and system control, data storage and
transfer, using various interfaces including Wi-Fi [7].
3. DETERMINATION OF SHP OF GIS DATA CONFIDENCE
We suppose that one of the concepts aimed at improvement of efficiency of control systems
of energy resources is evaluation of system quality in terms of generalized criterion: integral
confidence of data which integrates various performances of reliability, noise resistance,
confidence and response rate.
Integral data confidence is determined by probability of nondetected data distortion along
overall route of data transfer from sensor to receiver with accounting for faulty elements, data
distortion by errors and provided that the time shift between occurrence of event for transfer
and data fixation by receiver does not exceed certain range [12].
Some manufacturers of energy metering systems declare high confidence of received data
which is provided by powerful noise protecting codes, their structure is oriented at detection
of data distortion by noises in communication lines. Direct control of noises in
communication lines does not take into account probability of data error before its receipt by
coder (unit introducing excess constituent of message), that is, increased confidence is
guaranteed only for one segment of data transfer route from sensor to receiver [13].
The system quality is incomplete if the performances of data reliability and noise
protection are considered separately. Reliability often considers only these faults which lead
to nonexecution of commands. Herewith, faults leading to distortion of control commands are
not taken into account. Nonsymmetry of the required probability performances for refusal and
false activation after control commands is reflected in specifications for telemetry: normalized
level of the permissible probability of false command rejection or receiving of signals of
equipment state with nondetected distortions is by 105–107 (!) times higher than the
probability of implementation of distorted data [14].
Standard reliability index is calculated with consideration for indices of major portion of
software. A required reliability index can be detected only by reservation of main segments.
Without special measures of improvement of integral reliability, it is impossible to meet the
requirements of standard even with provision that mean time to failure of certain modules
exceeds 200,000 h. Actual reliability performance depends not only on module arrangement

for selected data type but, to a higher extent, on general structure of control system of energy
resources.
Let us demonstrate that the reliability indices by some manufacturers in fact do not
comply with the requirements of standard. With this aim we analyze the structure of system
segment (Fig. 3) which determines reliability performance only for this function.
Since individual quality performances do not reflect integral quality of control system in
power engineering, we propose evaluation procedure of system data integral confidence. In
order to obtain integral performance of data confidence, it is necessary:
• to consider for possible distortions (leading or not leading to rejection) along overall route of
data transfer from sensor to receiver, moreover, identical approach should be applied to
distortions caused by noises and other external factors, and to distortions due to faulty
elements of hard- and software;
• to consider for actual response rate [13].
Figure 3. Structure of route for reliability prediction.
In order to determine the system integral confidence , it is necessary to report
analytically acquired values, for instance, for function - (or similar index for other
data types), really achievable time of data transfer to receiver , predetermined maximum
permissible time of data transfer .
Since integrates indices of confidence, noise resistance and accuracy, during
estimation of data integral confidence (or other information) in the system, while
determining , it is recommended to use the set of inequalities:
=
at ≤
× ƒ ≥
(1)
Communication of
selected module line
with sensor
Internal interface
of transmitter
Hard- and software of
transmitter internal
interface controller
Equipment of
linear adapter
of transmitter
Equipment of
linear adapter
of receiver
Communicatio
n line between
remote and
central stations
Hard- and software
of receiver internal
interface controller
Internal
interface
of
receiver
Interface with
processing PC
Hard- and
software for
selected line
Remote PC and
software for
selected line
Hard- and software for
visualization of
selected line data
Hard- and
software for
selected line

The function ƒ( !
!
"#$) can be preset for each control system and even for certain data types
according to importance of data transfer in predetermined time.
While substantiating concept of arrangement of efficient control systems for energy
resources, it has been demonstrated that integral confidence of overall route of data transfer
, for instance, for , should be described as follows:
= + ∑ &
' (2)
where (the first sum term) corresponds to calculated integral data confidence
provided by input of discrete signals (remote signal system); &
(the second component)
corresponds to nondetected faults of all modules included into data transfer route from source
module to data display device.
The second component equals to probability of the fact that in any module of the route
will occur non-detected faults the number of which is not lower than the code distance d=6 of
polynomial generated by data source module.
Let us assume that the number of elements in module is 104
(average number of elements
in module with numerous microcircuits) and probability of fault of one (integral) element is
not higher than 10-7
(spreadsheet data for modern integral circuits). Then
&
= (10)
∗ 10+,
) -
=10+'.
(3)
It is obvious that upon the use of even 10 modules into the transfer route, the
supplemental constituent reducing integral confidence is 10+'.
.
Therefore, it is shown that the proposed concept provides the level of integral data
confidence of channels TY, , which exceeds the most stringent requirements of standard
relating to only one performance: confidence.
The integral performance of confidence integrates indices of confidence, reliability, noise
resistance, and response rate, hence, it is the most reliable criterion of system data quality.
Control system of energy resources includes numerous actual factors leading to distortion
of single transferred data, that is, it is necessary to repeat data transfer, since there is no
receipt confirming nondistorted data acceptance. These factors naturally decrease system
efficiency but, in order to simplify calculations, they are not considered [13].
4. CONCLUSION
This work discusses GIS with SHP for metering on heat resources in multi compartment
buildings. Peculiar feature of the system is that its SHP structure is modular, its fabrication is
mainly comprised of assembling, programming, and adjustment of all components: house
retranslator, local retranslator, WTM, SIB.
The developed GIS hard- and software is based on:
• intelligent networks;
• intelligent analysis of input data;
• data protection technology;
• possibility of uninterrupted operation;
• accounting of heat resources of distributed facilities with geographic reference to each facility;
• possibility to acquire, process, provide analytic information for various facilities suitable for
further application;

• modular approach with grouping by energy types and capability to activate individual
modules.
ACKNOWLEDGMENTS
This work was supported by the Ministry of Education and Science of the Russian Federation,
Agreement No. 14.578.21.0208 dated 03.10.2016, unique identifier: RFMEFI57816X0208.
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