Published at : 27 Dec 2022
Volume : IJtech
Vol 13, No 7 (2022)
DOI : https://doi.org/10.14716/ijtech.v13i7.6202
Viktoriia Brazovskaia | Peter the Great St. Petersburg Polytechnic University, Politehnicheskaya Street 29, Saint Petersburg, 195251, Russia |
Svetlana Gutman | Peter the Great St. Petersburg Polytechnic University, Politehnicheskaya Street 29, Saint Petersburg, 195251, Russia |
This article reveals the
problem of implementing and evaluating the readiness of the energy industry to
implement digital innovations in the countries of the world. Qualitative and
quantitative methods were used to achieve the purpose of this study, namely,
the indicator system development to evaluate the level of readiness of certain
countries for the potential digitalization of the energy industry. System,
comparative and content analysis are the qualitative methods used in this work.
The quantitative methods include collecting and processing statistical
information, and fuzzy logic. As a result of the study, a list of indicators
for monitoring was determined, and based on them, a scale for evaluating readiness of the
energy industry for digitalization in the countries under consideration was
formed. Based on the formed pool of indicators, a quantitative evaluation of
the level of readiness of the electric power industry in 10 countries was
carried out and presented as an aggregated indicator of the overall evaluation
for each of the studied countries – Japan, Estonia, Iceland, Finland, Denmark,
Russia, Tanzania, Belarus, UAE, and Sweden. The uniqueness and novelty of this
study lies in the fact that based on the analysis carried out using the fuzzy
logic method, there has been formed an approach to the overall evaluation and
subsequent monitoring of the level of readiness of the energy industry for
digitalization in the countries of the world.
Electric power industry; Energy digitalization; Fuzzy logic; Indicators; Readiness for digitalization
A feature of today's days
is the penetration of information technologies into all aspects of human life.
Digital innovations play a huge role in the global world and extend to almost
all spheres of life. Technologies have entirely penetrated not only into the
social sphere – in the form of communication technologies and communications
via Internet, when almost every person in the world is connected to a single
digital space, but also in all sectors of the economy. The energy industry is
one of the most basic sectors in the economy of the Russian Federation and has
a significant impact on the country’s welfare. The comfort of people's lives depends
on the quality of the electricity supply (Kelly &
Fussell, 2019).
Digital
energy is a major part of the digital economy (Nosova et al., 2018). The essence of digital energy is the creation and development of new
producing and economic relations based on digital approaches and means. As is
already known, the emergence of digital platforms in any industry reduces
transaction costs associated with the contract conclusion, information processing,
negotiations, decision-making, etc. Therefore, the main task of digital energy
is to reduce the rapidly growing costs of integration of the distributed energy
and market transactions (Hui et al., 2022).
First, digital transformation in energy is the creation of new business models
based on the capabilities
of the digital economy (Babkin et al., 2021) in all three
sectors of the fuel and energy complex (FEC): fuel industry, electric power
industry and transportation of fuel and refined products, heat, and energy. The
main task of digital transformation in electric power industry is to increase
the reliability of electricity supply, to limit the growth of electricity
prices, as well as to develop new formats (services) of interaction with
consumers. The main goal here is to create new "smart" networks that
will contribute to the competent and ecological distribution of electricity to
consumers. Digital technologies open up new opportunities and various benefits
for the electric power industry: enhancing stability in the operation of power
systems, prospects for expanding the use of distributed generation from one
station up to an entire network with many different facilities (including those
using renewable energy sources as the main fuel), reduction of accident rates
and annual electricity losses due to improved systems of monitoring and control
of the condition of equipment and facilities, etc. (Mohd
Roseny et al., 2021).
Today there is
a global energy transition and the conventional energy system transformation.
The introduction of new digital technologies and solutions, starting with
"green" energy and ending with intelligent "smart" electric
networks and technologies in the form of the "Internet of Things" (IoT)
as consumer services, causes an increase in investment costs in R&D of this
industry, as well as an increase in financing and the need for various other
developments. Nevertheless, new technologies boost to the modernization of the
energy system. For example, blockchain technology in the energy sector using to
make purchase and sale transactions between energy producers and consumers,
which will make the electricity market more accessible to consumers in the
future. To monitor the readiness of Russia and other countries for energy
digitalization and implementation of goals in this area, a set of qualitative
and quantitative indicators is needed that track the results achieved and
development trends. State and non-state institutions, international organizations,
and scientists around the world are developing and promoting various methods
for evaluating the country's readiness for a digital transition in energy, as
well as the level of energy digitalization at the moment.
The country's
readiness for energy digitalization can be explained in many ways: by
evaluating the readiness of the country itself for the energy transition, by
demonstrating the dependence and influence of the energy digitalization
indicators of enterprises on the industry, the industry on the country, as well
as by evaluating the performance indicators of the digital transformation of
the country's energy.
When forming an
approach to evaluate the country's readiness for digitalization of the power
energy industry, the following market and technological trends should be taken
into account:
1. The advent
of an increasing number of advanced consumers who actively participate in the
production of goods that they consume on their own (in Russia, electricity
consumers are allowed to sell electricity to a shared network of up to 15 kW).
2. The advent
of smart contracts – new financial technologies that allow for direct
settlement between generation and consumers of electricity (appearance in
Russia at the end of 2019).
3. The trend
towards decentralization of electricity supply (reduction of the energy
component of the cost of production) due to the ease of maintenance of the DG
(distributed generation) based on natural gas and renewable energy sources
(RES) generation facilities and the annual growth of tariffs outpacing the rate
of inflation for consumers.
4. Development
and distribution of digital intelligent control systems of the active energy
complex (AEC), which make it possible automatically solve all the tasks of the Operations
and Technology Directorate (OTD) and manage energy regimes.
In this study,
the electric power industry will be taken as a basis, since it is the basic
industry among the rest due to the provision of electricity to the remaining
ones. Based on the trends mentioned earlier, it is possible to identify four
areas (blocks) by which it is necessary to evaluate the country's readiness for
energy digitalization:
1.
"Regulation and provision of the electric power industry" that will
be presented in the form of political resolve and transparency of the country,
as well as the availability of electric energy.
2. "Safety
and sustainability of the electric power industry", which will be
expressed in the following areas: environmental sustainability and reliability,
quality of energy supply.
3.
"Electricity generation", where the main component will be the
structure of the electric power system.
4.
"Science and Innovation", the directions of which are as follows:
human capital and operational and investment efficiency of the country.
Therefore, the
purpose of this paper is to develop a system of indicators to evaluate the
level of readiness for the potential digitalization of their electric power
industry.
The methods used to
achieve the purpose of this study include systematic, comparative, and content
analysis, which belong to the category of qualitative methods. Collecting and
processing statistical information, expert procedures, fuzzy logic were used as
the methodological basis of the calculations performed in the article (Zadeh, 1965).
The sequence of
steps to achieve the study purpose:
1.
Determination of the composition and quantitative and qualitative indicators
characterizing the degree of readiness of the country's energy industry for digitalization.
2. Introduction
of a linguistic variable and formation of scales to evaluate the level of
readiness of the country's energy industry for digitalization.
3. The
indicator setting and formation of the factor value matrix.
4. Calculation
of the aggregated indicator of the readiness of the country's energy industry
for digitalization.
In this study,
the electric power industry of the Russian Federation was taken as a study
object since it is the basic industry among the rest due to electricity supply
to the remaining ones.
At the first
stage of the study, in order to create and develop a single indicator to
evaluate the readiness of the country's energy industry for digitalization for
each of the mentioned areas (blocks), the main (common) indicators were
identified, which are proposed by international organizations and used in
similar studies, articles and other sources (Table 1) (Karanina
& Bortnikov, 2020; Kholkin and Chausov, 2018).
Next, we introduce a linguistic variable for the evaluation. Let the linguistic variable be "The level of readiness of the country's electric power industry for digitalization", which is described by a set of indicators in the following way (formula 1):
where x is the
designation of the variable "Readiness of the country's electric power
industry for digitalization". T is a set of values of readiness of the
country's electric power industry for digitalization: "Extremely low level
of readiness of the country's electric power industry for digitalization",
"Low level of readiness of the country's electric power industry for
digitalization", "Average level of readiness of the country's
electric power industry for digitalization", "High level of readiness
of the country's electric power industry for digitalization" and
"Extremely high level of readiness of the country's electric power
industry for digitalization". D is the definition area on the segment
[0;1].
Table 1 Evaluation indicators of the countries' readiness for digitalization in
the electric power industry
Group |
Indicator, dimension |
Data source |
Regulation and provision of the
electric power industry |
||
Political resolve and transparency |
Regulatory indicator for
sustainable development in the field of RES |
WorldBank |
Corruption Perception Index |
Transparency International |
|
Rule of law index |
World Justice Project |
|
Availability of electric |
The ratio of the average salary in
the country (net) to EE price for the population, $/kW*h |
State Statistics Services of Enerdata
countries |
EE price for industry (net),
$/kW*h |
IEA |
|
The level of the country
electrification, % |
WorldBank |
|
Safety and sustainability of the
electric power industry |
||
Environmental sustainability |
CO2 emissions per
capita, t/person |
WorldBank |
CO2 emissions for total
electricity consumption, t/MW*h |
World Bank BP Statistical Review |
|
Reliability and quality of power
supply |
SAIFI (System Average Interruption
Frequency Index) |
WorldBank |
SAIDI (System Average Interruption
Duration Index) |
||
Electricity generation |
||
Structure of the electric power
system |
The share of EE generated at the
DG facilities (including RES without hydropower) of the total EE volume, % |
WorldBank |
The share of EE produced by
coal-fired generation of the total EE volume, % |
WorldBank |
|
The share of EE produced by gas
generation and HPP of the total EE volume, % |
||
Science and innovation |
||
Human |
The total number of educational
institutions, according
to the source, pcs. |
QS (World university rating by
subject Engineering Electrical & Electronic) |
The share of jobs in the DG
segment (including RES with hydropower) of the total workforce, % |
IRENA Industry Associations |
|
Operational and investment
efficiency |
The ratio of GDP to the amount of
electricity consumed, PPP (Purchasing Power Parity) $/MW*h |
BP Statistical Review IMF |
Investment Freedom Index |
The Global Economy |
|
Access to loans |
WorldBank |
|
The share of DG investments
(including RES without hydropower) from the total investment in electricity
generation, % |
IRENA Industry associations
Countries’ specialized departments |
Each of the factors has its own area of definition. In accordance with the basic provisions of the fuzzy-set theory, if each factor is assigned the degree of its belonging to an odd set A, then this membership is expressed by the number µA(x) – the membership function on the interval [0;1]. Next, each value of the linguistic variable (which, by its construction, is a fuzzy subset of the values of the interval (0, 1)) is compared with the function of belonging of the integral indicator to one or another fuzzy subset (Gutman et al., 2021). It is possible to represent a similar function in the form of a triangular membership function m(x), described by triangular numbers of the form: b(a1, a2, a3), where a1 and a3 are the abscissas of the lower base, a2 is the abscissa of the upper point of the triangle, specifying m(x) in the domain with non-zero membership carrier x to the corresponding fuzzy subset. Thus, the Y function value will characterize the level of readiness of the country's electric power industry for digitalization, depending on selected factors. This function will be called the parameter evaluating this element. To evaluate the level of readiness of the country's electric power industry for digitalization, a scale of fuzzy values of the variable Y has been developed. Table 2 below shows a scale for evaluation of the level of readiness of the country's electric power industry for digitalization. This scale was developed on the basis of the reviewed scientific literature on the topic under consideration (Verma et al., 2020; Singh, 2019; Grabchak, 2018; Abramov et al., 2017).
Table 2 A scale for evaluation of the readiness of the country's electric power
industry for digitalization
Set of values |
Linguistic evaluation |
The general explanation of the evaluation |
Detailed explanation of factors |
0–0.333 |
Extremely low level of readiness of the country's
electric power industry for digitalization |
Electric power infrastructure is close to
nonexistent or is at very low level, electric energy is not generated or
generated in very small volumes, projects for the electric power industry
digitalization are not implemented, there are no conditions for the
development of science and innovation in the electric power industry, and the
environmental situation is at a very low level |
Extremely low level of electricity availability,
absolutely unreliable and substandard electricity supply, there are no
investments and R&D costs in the industry, electricity is generated from
non-renewable sources, RES are not used as fuel, extremely high level of
carbon emissions into the atmosphere |
0.167–0.5 |
Low level of readiness of the country's electric
power industry for digitalization |
The level of the electric power infrastructure development
is low, electricity is generated in insufficient volume, the level of
electrification is low, education in the electric power industry and
electrical engineering is at a low level, and the environmental situation is
not significant for the state |
Electricity is available, but not everywhere.
Electricity is supplied with frequent and long tripping, R&D costs in
this area are at an initial stage, the RES use as fuel is under study, and
there is a sufficiently high level of carbon emissions into the atmosphere |
0.333– 0.667 |
The average level of readiness of the country's
electric power industry for digitalization |
There is a sufficient level of electricity supply,
the electric power infrastructure is developing at a moderate pace, projects
are being developed to digitalize the electric power industry, science and
ecology are developing, and education in the electric power industry is at a
basic level |
Electricity is available in the country, the average
level of reliability and quality of electricity supply. RES has a small share
in the structure of electricity generation, mainly combustible energy sources
are used, paying attention to the education of specialists in the electric
power industry, and investment activity is available |
0.5– 0.833 |
High level of readiness of the country's electric
power industry for digitalization |
The high level is characterized by the
implementation of digital projects in electric power industry, electric power
infrastructure is developing at a rapid pace, a sufficiently high level of
the country electrification, and ecology and education in the electric power industry are the priorities in the
country's economy |
Sufficiently reliable and high-quality electricity
supply (very low risk of tripping), the RES use is quite high in the
structure of electricity generation, investment activity in the country is at
a high level, R&D costs are significant for the industry development, and
environmental development is making progress (reduction of carbon emissions
into the atmosphere)
|
Set of values |
Linguistic evaluation |
The general explanation of the evaluation |
Detailed explanation of factors |
0.667–1 |
Extremely high level of readiness of the country's
electric power industry for digitalization |
Attention is paid to the RES use. Digital
technologies are used in household and industrial areas of the electric power
industry, developed electric power infrastructure, electrification of the
country is at the highest level, digital projects are being developed and
implemented at a rapid pace, the country is environmentally friendly, and the
population is educated in the electric power industry |
The emphasis on the RES use in the structure of
electricity generation, most of the state budget consists of R&D costs, a
large number of training centers and universities with technical specialties,
carbon emissions are as low as possible, and very reliable and high-quality
power supply (the tripping risk is almost impossible) |
The factors used for modeling as input and their
values are presented below in Tables 3, 4. Using these factors, it is
possible to evaluate the level of readiness of the country's electric power
industry for digitalization.
Table 3 Indicators offered to evaluate the readiness of the country's electric
power industry for digitalization
Area of activity |
Designation |
Indicator |
Regulation
and provision of the electric power industry |
X1 |
Regulatory
indicator for sustainable development in the field of RES |
X2 |
The
level of the country’s electrification, % |
|
Safety
and sustainability of the electric power industry |
X3 |
CO2
emissions per capita, t/person |
X4 |
SAIFI
(System Average Interruption Frequency Index) |
|
X5 |
SAIDI
(System Average Interruption Duration Index) |
|
Electricity
generation |
X6 |
The
share of EE produced by gas generation and HPP of the total EE volume, % |
Science
and innovation |
X7 |
The
total number of educational institutions, according to the source, pcs. |
X8 |
Investment
Freedom Index |
Table 4 The values of the input indicators of the model proposed to evaluate
the readiness of the country's electric power industry for digitalization in
2019
Japan |
Estonia |
Iceland |
Finland |
Denmark |
Russia |
Tanzania |
Belarus |
UAE |
Sweden |
Min value |
Max value |
|
X1 |
77.43 |
69.91 |
76.58 |
70.57 |
79.29 |
59.86 |
41.86 |
56.73 |
72.29 |
80.43 |
13.86 |
96.57 |
X2 |
100 |
100 |
100 |
100 |
100 |
100 |
32.8 |
100 |
100 |
100 |
7.76 |
100 |
X3 |
8.7 |
9.3 |
11 |
7.7 |
5.4 |
12 |
0.2 |
6.5 |
16 |
4.1 |
0 |
41 |
X4 |
0.01 |
0.18 |
0.41 |
0.16 |
0.5 |
0.05 |
46.77 |
0.48 |
0.24 |
0.66 |
0.01 |
500 |
X5 |
0.02 |
0.3 |
0.63 |
0.2 |
0.5 |
0.17 |
20.9 |
0.51 |
0.25 |
0.61 |
0.02 |
940 |
X6 |
44.27 |
0.79 |
69.06 |
23.79 |
7.18 |
64.48 |
57.72 |
98.43 |
97.25 |
38.98 |
0 |
100 |
X7 |
16 |
1 |
2 |
4 |
3 |
11 |
1 |
8 |
3 |
5 |
0 |
84 |
X8 |
70 |
90 |
85 |
85 |
90 |
30 |
55 |
30 |
40 |
85 |
0 |
95 |
Values of the selected factors were set according to the following formula (2):
In this model, all factors are assumed to be
equivalent. For the analysis, the authors selected eight factors; hence it follows that the significance of the ri factors is calculated as r1=1/8. That is, the significance
level of each factor with their number equal to 8 will be 0.125.
According to Nedosekin’s methodology (Nordekin,
2003), if there is a set of i=1..N individual factors with
their current values xi, and each factor has its own M-level
classifier, then it is possible to determine the quantitative value of the
aggregated factor by the double convolution formula (formula 3):
where aj
– nodal points, di – the weight of the i-th factor in the
convolution, mij(xi)
is the value of the membership function of the j-th qualitative level relative
to the current value of the i-th factor, M – the number of levels of the
classifier.
The final formula for the five-level classifier will have the following form (formula 4):
where yi – nodal points of triangular
numbers, lij
is determined by the matrix table.
The nodal points are calculated by the formula (5):
According to the data obtained, calculations were carried out. Figure 1 shows the value of the integral indicator for evaluating the readiness of the electric power industry of the studied countries for digitalization. Thus, Japan had the highest value of the final indicator among the countries under study. This suggests that this country is the best prepared for the digitalization of the electric power industry, according to 2019 data. The value of the final index, equal to 0.692, is interpreted according to the membership function as follows: the readiness level of the Japanese electric power industry is 84.63% relating to the high level, and 15.37% relating to the extremely high level. This high value of the final indicator was achieved due to the high value of the regulatory index for sustainable development in the field of RES and the largest number of educational institutions in the electric power industry among the countries under study. Japan is also the leader in SAIFI (System Average Interruption Frequency Index) and SAIDI (System Average Interruption Duration Index) indices. Their values are the lowest in the world.
Figure 1
Results of
evaluation of the readiness level of the electric power industry for
digitalization
Iceland ranks
second in terms of the readiness of the electric power industry for
digitalization, with a final indicator of 0.671. This means that the level of
readiness of the Icelandic electric power industry for digitalization is 97.15%
at a high level and 2.85% at an extremely high level. It is worth noting that
Iceland is one of the countries with an extremely high share of electricity
produced by gas generation and hydroelectric power plants, and such an
indicator as a regulatory indicator for sustainable development in the field of
RES is also of high importance. However, the number of educational institutions
in electric power and electrical engineering in Iceland is extremely small.
Sweden ranks
third in terms of the readiness of the electric power industry for
digitalization. Its final indicator reaches a value of 0.668, which indicates
that the level of readiness of the electric power industry for digitalization
is 98.53% at a high level and 1.47% – at an extremely high level. In addition,
Sweden has the largest regulatory index for sustainable development in the
field of RES, an extremely high index of investment freedom and a fairly large
number of educational institutions among the countries under study. Carbon
emissions per capita are the lowest not only among the countries represented,
but also around the world.
Finland and
Belarus have approximately the same level of readiness of the electric power
industry for digitalization by the value of the final indicator: 0.6502 and
0.6504, respectively. Classifying the values of these indices, it can be
concluded that the level of readiness of the electric power industry of Finland
and Belarus for digitalization is 89.94% and 90.04% at a high level and 10.06%
and 9.96% at an average level, respectively. This value of the final indicator
of Finland was facilitated by the extremely high value of the regulatory
indicator for sustainable development in the field of RES and the extremely low
share of electricity produced by gas generation and HPP. In Belarus, on the
contrary: the regulatory indicator for sustainable development in the field of
RES is at an average level and is one of the lowest among the countries
studied, and the share of electricity produced by gas generation and HPP
reaches almost the maximum possible value worldwide. In addition, Finland has
an extremely high index of investment freedom, which cannot be said about
Belarus – the index of investment freedom is at an extremely low level. The
total number of educational institutions in electric power and electrical
engineering in all the countries under study is at an extremely low level. However,
among the countries represented, Belarus has this indicator value above the
average level, while Finland has the opposite.
In sixth place
by the readiness of the electric power industry are the UAE, which final
indicator is 0.6492. It is interpreted as follows: the readiness level of the
UAE electric power industry is 89.33% at a high level and 10.67% at an average
level. It is worth saying that carbon emissions per capita in the country have
the maximum value among the countries under study. The share of electric energy
produced by gas generation and HPP reaches almost the maximum possible value
worldwide, as well as in Belarus, and the index of investment freedom is at a
low level.
The final
indicator of Russia has a value of 0.6478. This indicates that the level of
readiness of the country's electric power industry is 88.51% at a high level
and 11.49% at a low level. This level is achieved by the average value of the
regulatory index for sustainable development in the field of RES, sufficiently
large carbon emissions per capita among the countries studied, an extremely low
value of the index of investment freedom and a sufficiently large share of electricity
produced by gas generation and HPP. The SAIFI and SAIDI indicators in Russia
have rather low values. In addition, Russia ranks second in the number of
educational institutions in the electric power industry among the countries
studied in this work.
Denmark, with a
final indicator of 0.6464, ranks 8th in the ranking of the countries
represented. Interpreting the values of the final indicator, we can say that
the level of readiness of the Danish electric power industry for digitalization
is 87.46% at a high level and 12.36% at an average level. It is worth noting
that the regulatory index for sustainable development in the field of RES has
an extremely high value (after Sweden), and Denmark also has one of the highest
indices of investment freedom. Carbon emissions per capita reach rather low
values. However, the share of electricity produced by gas generation and HPP is
the smallest among the countries represented. The number of educational
institutions in electric energy is small as well.
Estonia's final
indicator is 0.6407. This indicator value is interpreted as follows: the level
of readiness of the Estonian electric power industry for digitalization is
84.23% at a high level and 15.77% at an average level. The value of the
investment freedom index has an extremely high level (as in Denmark). However,
the share of electricity produced by gas generation and HPP is extremely small
(almost reaches the minimum value worldwide), as well as the number of
educational institutions in the electric power industry. The regulatory
indicator for sustainable development in the field of RES has an average value
relative to other countries.
The lowest
value of the final indicator was found in Tanzania – 0.6364. This suggests that
Tanzania is least ready for the digitalization of the electric power industry.
Classifying the value of this indicator, we can conclude that the level of
readiness of the country's electric power industry is 81,68% at a high level
and 18.32% at an average level. This indicator value was facilitated by a
rather low value of the regulatory index for sustainable development in the
field of RES (the lowest among the countries under study), a very small number
of educational institutions in the electric power industry, as well as very
high values of the SAIFI and SAIDI indices (the highest among the countries
represented). In addition, it is worth noting that the level of electrification
in all countries except Tanzania has the maximum value in the world, while in
Tanzania, the country electrification level is extremely low. However, the
share of electricity produced by gas generation and HPP is at an average level
among other countries, and carbon emissions per capita reach almost the minimum
value worldwide. Since the main trends in the digital transformation of energy
are decentralization, decarbonization and digitalization, it is necessary to
develop these areas for a faster and more successful increase in the level of
readiness of Russian energy for digitalization and transition to a new level.
The main
recommendations for improving the readiness of the electric power industry of
the Russian Federation for digitalization are the following:
1) increase in the efficiency of current assets
and cost efficiency (it is necessary to increase labor productivity, remove
inefficient capacities, etc.);
2) investing in new assets, such as energy storage
units and charging stations for electric vehicles, etc.;
3) increasing digital technological potential
through the development and implementation of pilot projects and improving
digital competencies;
4) development of new services in the electric
power industry (consulting in energy efficiency, etc.).
In addition, in
external perspective, it is necessary to investigate the issues and barriers
that hinder the development of digitalization in the electric power industry.
It is necessary to create and establish foundations and private organizations
that will allocate finance and invest in the new digital technologies and
solutions in energy development. It is also necessary to work out the issues
related to state support for digitalization and digital transformation of the
electric power industry by creating special agencies. Organizations and
companies that will primarily and purposefully engage in the electric power
industry development and allocate funds from their budget for the
implementation of investment projects.
In internal
perspective, attention should be paid to the development and promotion of
digital competencies in companies, as well as the promotion of an innovative
culture. A huge prospect will be the exchange of experience in energy industry
digitalization between organizations in the country, as well as adopt he best
solutions and practices.
It is also
worth noting that the process of updating digitalization programs in Russia and
digital strategies in companies, taking into account the development and
priorities of each fuel and energy sector, the implementation of digital
projects, as well as the interaction and exchange of experience between the Russian
and international energy markets contribute to a faster and better increase in
the level of readiness and the level of digitalization of the energy industry
in the country.
Within this
study, a certain pool of indicators was collected that evaluate the level of
readiness of countries’ electric power industry for digitalization. The
quantitative evaluation of the readiness level of the electric power industry
in 10 countries was performed based on a fuzzy-multiple approach. Based on the
obtained results, it can be concluded that in 2019, the readiness level of the
electric power industry of the Russian Federation was 88.51% at a high level
and 11.49% at an average level. In comparison with other countries represented,
Russia is on 7th place. The values of some of its indicators are lower, that
indicates the need to change the policy of regulating the digitalization of
energy industry in the country and use a foreign experience to increase the
readiness level of the energy industry of the Russian Federation for
digitalization. Based on the collected pool of indicators it can be concluded
that in order to increase this level, Russia needs to take the following
actions: to increase the use of renewable energy sources; to develop distributed
power generation and involve consumers in the use of individual decentralized
sources of electricity; to develop and implement their own digital and
information technologies that will be able to manage and regulate independently
the processes of consumption, distribution, generation and pricing of
electricity, as well as monitor the condition of equipment and make timely
decisions in the "smart" power system; to develop the mass use of
electric transport with the possibility of providing mobile electrified trains
with their own energy carriers from the network and their recovery if
necessary; to improve the education system in electric power industry,
electrical engineering and, in general, energy industry in order to increase
the level of digital competencies in this area, as well as to retrain and
re-educate personnel for the country’s new energy. Thus, the implementation of
all the above recommendations and proposals on digitalization of the electric
power industry and energy industry until 2025 will allow Russia to maintain the
level of competitiveness in this area and will also contribute to a fairly
rapid increase in the readiness level and the level of the country's electric
power industry for digitalization.
The
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