=Paper= {{Paper |id=Vol-2922/paper003 |storemode=property |title=Method of forming an integrated automated control system for intelligent objects |pdfUrl=https://ceur-ws.org/Vol-2922/paper003.pdf |volume=Vol-2922 |authors=Ravil Safiullin,Alexander Epishkin,Ruslan Safiullin,Tian Haotian }} ==Method of forming an integrated automated control system for intelligent objects== https://ceur-ws.org/Vol-2922/paper003.pdf

Method of forming an integrated automated control
system for intelligent objects*

Ravil Safiullin1, Alexander Epishkin2, Ruslan Safiullin1 and Tian Haotian3
1
St. Petersburg Mining University, 2, 21st Line, St Petersburg, 199106, Russia
2
St. Petersburg State University of Architecture and Civil Engineering, 2-Ya Krasnoarmey-
skaya Ulitsa, 4, St Petersburg, 190005, Russia
3
St. Petersburg Mining University, 2, 21st Line, St Petersburg, 199106, Russia
safravi@mail.ru

Abstract. The sequence of constructing the scientific and methodological appa-
ratus of the monitoring system by the energy networks of modern intelligent
buildings and structures is presented. The program for monitoring and control
of energy networks of intelligent buildings and structures based on the use of
intelligent automated systems has been substantiated. The types of support for
the control system of energy networks of intelligent buildings and structures,
when creating a local automated system for monitoring energy consumption,
are determined, which are important in the formation of many tasks that are in-
tended to perform functions at different levels and in various aspects. The result
of the study is algorithms for creating an intelligent energy management system
during the operation of engineering systems and electrical equipment of build-
ings and structures, monitoring it in real time and predicting the energy con-
sumption of buildings, which will provide the accumulation of data necessary
for optimal planning with energy resources, which will increase the validity of
the adoption solutions.

Keywords: Methodology, Energy networks, Monitoring systems, Buildings.

1 Introduction

The basis of current theoretical research on reducing the cost of energy consumption
during the operation of engineering systems and electrical equipment of intelligent
buildings and structures, and as a result, reducing the negative impact on the envi-
ronment, in the conditions of intensively changing quantitative and structural parame-
ters of intelligent technical means with limited urban planning changes, historically
established target-generating zones became both federal and regional target programs
for the modernization of the energy system within the framework of the "Smart St.
Petersburg" program. The relevance of the topic under consideration is due to the fact
that the use of automation systems that make it possible to effectively manage the

*
Copyright c 2021 for this paper by its authors. Use permitted under Creative Commons License Attribu-
tion 4.0 International (CC BY 4.0).
engineering systems of buildings is in demand both in the restoration of existing elec-
trical installations and in the design of new ones, but there is no scientific and meth-
odological apparatus for their rational construction that can effectively manage such
building systems. like lighting, heating and air conditioning and allowing you to re-
duce energy costs [1].

2 Materials and methods

As a result of the study [2], practical recommendations were developed for the forma-
tion of a monitoring system by energy networks of intelligent buildings and structures
for the rational use of intelligent technical means of systems, which contain methods,
algorithms of actions for the selection and rational functioning of intelligent technical
means, provide for specific measures to improve them. The objective necessity of
scientific substantiation and creation of a methodology for innovative technical and
technological solutions to ensure a reduction in energy consumption costs during the
operation of engineering systems and electrical equipment of intelligent buildings and
structures in various conditions has been established [3-4], which allows to reduce
energy consumption costs during the operation of the energy system by 30-35%.
All this presupposes the integration of oriented technologies for reducing energy
consumption in the management of energy networks of buildings based on a system-
targeted approach to this process. This approach is based on the provision on the rela-
tionship between the work of intelligent technical means and the energy savings gen-
erated during its operation (in the general setting) and, therefore, the possibility of
joint optimization of these processes. Models linking the work of intelligent technical
means (Ptr) and the amount of energy costs (Rd) constitute the normative-target basis
of alternative implementations of scenarios for their improvement. The optimization
criteria are based on the generalized technical and energy performance of this process.
In the process of managing the energy resources of smart buildings and structures,
three hierarchical levels of the process can be distinguished: at the regional mega-
level, at the local macro-level and at the individual micro-level. This is shown in Fig-
ure 1.
The volume of technical automation systems that make it possible to effectively
manage building systems in the n-th period should not contradict the continuing trend
of increasing energy consumption in the future n + 1 period Ftr (n + 1) > Ftr (n) (Ftr (n) not
equal 0).
The size of energy costs (Rd), Rd < Rpd = f (cr) should not be larger than the size that
can create, not exceeding the permissible.
Fig. 1. Program for monitoring and management of energy networks of intelligent buildings
and structures.

At each level, the energy resource management process is optimized according to the
following criteria:
Optimization models are as follows:
Level 3:
P3 = ∑f (A31, A32, ..., A3n; W31, W32, ..., W3n),
(1)
R3 = ∑f (A31, A32, ..., A3n; r31, r32, ..., r3n),
where A3i, - number of intelligent building systems i; W3i and r3i - accordingly, the
amount of automation and the amount of cost reduction of one unit i of intelligent
building systems for a calendar period.
Level 2:
P2 = ∑f (q21, q22, ..., q2n; A21, A22, ..., A2n),
(2)
R2 = ∑f (g21, g22, ..., g2n; N21, N22, ..., N2n),
where q2i and g2i – accordingly, the amount of automation and the amount of cost
reduction from the operation of one unit i intelligent building systems, A2i and N2i, –
number of i intelligent building systems;
Level 1:
P1 = ∑f (ω11, ω12, ..., ω1n; A11, A12, ..., A1n),
(3)
R1 = ∑f [T2, g1l, + g1t (tp11, tp12, ..., tp1n)],
where g1l and g1t – the size of cost reduction from the operation of one unit i of
intelligent building systems; ω11 and tp11 - hourly productivity and uptime of i intelli-
gent building systems under operator control.

3 Results

Modeling is carried out both for individual buildings and structures, and for residen-
tial areas, micro districts, with a changing ratio of the number of intelligent building
systems that meet the standards.
Level 1 [5-6] optimizes the mode of operation of an individual room in a building.
The selection of intelligent building systems according to these criteria allows you to
perform optimal work with a minimum of modes not due to the energy saving proc-
ess.
When considering the functionality of any system for managing energy networks
of intelligent buildings and structures, when creating a local automated system for
monitoring energy consumption, it is important to create many types of software that
are intended to perform functions at different levels and in various aspects. Consider
the types of security that are most important in the work of this system. These include
the following: hardware and technical support; software; Information Support; organ-
izational support; metrological support; software; methodological support; methodo-
logical support [7].
Without active interaction with the environment, the system under consideration
cannot function effectively. But not only active interaction is required for this – also
archival and forecast information about the control object and from adjacent systems
is fed to the input of the integrated automated control system on the road. The main
directions of the development of this system can be briefly explained by the presented
scheme as a local automated system for monitoring energy consumption. This is
shown in Figure 2.

Fig. 2. The main directions of development of an integrated automated energy management
system.

The hardware and technical support include all server, switching and peripheral
equipment, as well as automated workstations for personnel. The composition of
server equipment includes such types as servers themselves, as well as video servers,
automatic telephone exchanges, data storage systems and other specialized server-
type devices that are located in racks and are usually placed in data centers, where a
"harness" is created to ensure their performance. From a large number of specialized
engineering systems. Switching equipment is represented by switches, routers,
routers, firewalls – everything that ensures the creation and operability of physical
channels of information transmission. Most of the switching equipment is located
together with the server room, but some also go to the communication lines and facil-
ity complexes for organizing communication with peripheral equipment.
Peripheral equipment, which is almost the most important part of the hardware and
technical support of the system, is a wide variety of equipment that is used to perform
the functions of subsystems, which is called "in places". It is difficult to give a com-
plete list of types of peripheral equipment, since everyday there are new examples of
what can be used to implement the functionality of the system. The next important
type of system support is software. Software is understood as the whole complex of
programs and documentation for them, necessary and sufficient for the operation of
this complex of programs. Programs are divided into system, application and embed-
ded. System software is an operating system, drivers in it and other basic programs
that ensure the operability and interfacing of application programs and hardware and
hardware elements. Application software is a part of information and automated sys-
tems within the system and performs application functions. Firmware is usually
hardwired into peripheral hardware and is used for low-level control of its operation.
An equally important type of system support is informational. It includes not only
information stored in databases and plying between the elements of the system, but
also all information support for the activities of systems, its subsystems and elements,
available to external factors. Therefore, when building a system, it is necessary to pay
attention not only to the logical and physical structure of databases, not only to the
composition of integration flows between subsystems, but also to the physical ele-
ments of information support.
The organizational support of the system is understood as a set of methods, proc-
esses, tools and personnel collected in specific management structures, which are
designed to organize the effective and high-quality functioning of the system. Since
the integrated automated energy management system is a very complex system, con-
sisting of many subsystems, each of which, in turn, is a full-fledged control system,
the organizational support of the system consists of the corresponding provisions of
each subsystem and is supplemented by those necessary components that cover emer-
gent system-forming properties the entire system. The organizational support usually
includes internal regulations and descriptions of business processes to maintain the
functioning of the system in various modes of operation. Service personnel and every-
thing necessary for their work is also included in the organizational support of the
system. Since the system contains many elements and special peripheral equipment
that measures various parameters of the control object and its parts, an important issue
is the availability of a unified metrological support, which is understood as a set of
metrological norms, rules and measurement procedures to meet the requirements for
accuracy and standardization. These requirements can be regulated both at the state
level and at the industry level or even within the system itself. The presence of stan-
dards in the field of accuracy and uniformity of measurement methods provides the
basis for the regulatory framework of the system.
Software is a set of algorithms, methods for solving problems and, most impor-
tantly, mathematical models for implementing the functionality of the system. Since
the intellectualization of functions in the system implies the presence of models for
predicting and planning the states of the control object and the system itself, the soft-
ware of the system and its subsystems should be developed and based on the latest
achievements of science. It should be noted that the software includes not only algo-
rithms implemented in the software, but also control scenarios, dynamic models and
other "online" mathematical tools that are used in the process of the system function-
ing.
Methodological support of the system is a set of descriptions of methods for solv-
ing problems. It is important not only at the stage of operation of the system and each
of its subsystems, but also at the design stage, when specific solutions are incorpo-
rated into the system. The decision methodology should be carefully described, un-
derstood by the system personnel and accepted for implementation. Thus, methodo-
logical support becomes, as it were, a cementing link between organizational and
software support.
In turn, methodological support (not to be confused with the previous type) is a set
of training materials and procedures for training personnel to work within the system.
And, despite the fact that with an increase in the degree of intelligence and autonomy,
the importance of the role of personnel will gradually decrease, while the need for
methodological support remains quite urgent.
When considering the functionality of any system, including the system itself, an
important issue is the many types of software that are designed to perform functions
at different levels and in different aspects, which can be seen in Figure 3.

Fig. 3. Stages of decision making when using an integrated automated control system for
energy networks.

The decision support system is designed to analyze the current state of the control
object as a whole, retrospective analysis, development modeling and preparation of
decision options with justification, which leads to decision support by managers at all
levels in the organizational structure of the system, from linear management to strate-
gic energy management.
The decision support system performs the following functions: extraction and veri-
fication of knowledge about the problem area; collection of information about the
control object and the environment in which it operates; storage of archival informa-
tion about the control object; modeling the development of the control object and
environment; conclusion and ranking of recommendations by solution options; expla-
nation of solution options; support for the implementation of the decision; evaluation
of the results of the implemented solution; learning by making changes to the knowl-
edge base.
Table 1 lists the types of support that need to be worked out in the development
and implementation of decision support systems.
Table 1. Types of support required for the development and implementation of decision sup-
port systems.
Type of provision Decision support system
Hardware and Server hardware running the system core. Automated workstations of
technical system users.
Software Server and client applications that perform system functionality.
The entire array of information that is stored in the system database,
Informative
and also runs through it through integration tools.
Organizational System personnel working with its functionality.
Metrological –
Algorithms and methods for processing large amounts of information,
Mathematical
modeling, issuing recommendations, etc.
Description of methods for analyzing big data, finding patterns, deci-
Methodological
sion support.
Methodical Training materials for analysts and leadership.

The structure of the decision support system can be represented using Figure 4.

Fig. 4. The structure of the decision support system.

4 Discussion

The statistical analysis module allows you to use various mathematical methods when
analyzing large amounts of information (statistical samples), in particular, searching
for correlations and causal relationships, analyzing trends, determining statistical
patterns, etc. The situational analysis module is used for a deeper analysis of large
amounts of information in a short period of time that allows you to discover hidden
patterns, non-trivial and practically useful interpretations of data information in real
time.
In fact, all other subsystems are integrated with the decision support system, since
it is in this system that the aggregation and analysis of information about all aspects of
the system's activities are carried out. All of these subsystems transmit information to
the decision support system. In addition, in the process of implementing a specific
project, the decision support system can be integrated with the subsystems of other
blocks of the system for effective management of energy networks.
5 Conclusion

Thus, the study on the application of new intelligent technologies showed that their
use significantly increases the efficiency of managing the energy networks of build-
ings and structures, due to constant monitoring of the energy consumption of build-
ings and structures in real time and the efficiency of information transfer. At the same
time, most of the functions performed are carried out automatically without human
intervention, which allows you to reduce the number of maintenance personnel with-
out the threat of reducing the efficiency of the system. This moment is fundamental
when creating such systems in energy networks.
The use of modern systems for monitoring technical means in buildings and struc-
tures provides the possibility of intelligent interaction with individual buildings and
structures or with the energy networks of the city as a whole through information and
telecommunication technologies of technical control devices in order to increase the
efficiency of energy consumption of buildings in any conditions. The considered sys-
tem-target approach to the formation of the system allows you to take into account the
positive and negative aspects when building an integrated automated control system
for energy networks.

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