INVESTIGATION OF A SENSORLESS WATER SUPPLY SYSTEM FOR EXCESS ENERGY REDISTRI-BUTION FROM WIND TURBINE
Environment-friendly and cost-effective generation of electricity from alternative sources is becoming particularly relevant in the context of rising energy prices for electricity generation, as well as due to the significant damage to Ukraine's energy system caused by the war. In certain areas...
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| Дата: | 2025 |
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| Автори: | , , , , |
| Формат: | Стаття |
| Мова: | Англійська |
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Institute of Renewable Energy National Academy of Sciences of Ukraine
2025
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Vidnovluvana energetika| _version_ | 1871103888997744640 |
|---|---|
| author | Zemlianukhina, H. Burian , S. Pechenik , M. Trotsenko , Ye. Pushkar , M. |
| author_facet | Zemlianukhina, H. Burian , S. Pechenik , M. Trotsenko , Ye. Pushkar , M. |
| author_institution_txt_mv | [
{
"author": " H. Zemlianukhina",
"institution": "National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine"
},
{
"author": "S. Burian ",
"institution": "National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine"
},
{
"author": "M. Pechenik ",
"institution": "National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine"
},
{
"author": "Ye. Trotsenko ",
"institution": "National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine"
},
{
"author": "M. Pushkar ",
"institution": "National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine"
}
] |
| author_sort | Zemlianukhina, H. |
| baseUrl_str | https://ve.org.ua/index.php/journal/oai |
| collection | OJS |
| datestamp_date | 2026-07-18T06:32:21Z |
| description | Environment-friendly and cost-effective generation of electricity from alternative sources is becoming particularly relevant in the context of rising energy prices for electricity generation, as well as due to the significant damage to Ukraine's energy system caused by the war. In certain areas, only stand-alone power generation systems can be used, as it is impractical and unprofitable to lay power grids in these areas. Such systems are usually based on a combination of wind or hydro turbines, drive motors and electric generators. It is characterised by high reliability, long service life, low cost and ease of maintenance. In times of military emergency, the operation of autonomous systems can be critical for people's lives and communication with the outside world. In addition, in such systems, the main con-sumers of electricity do not use the entire resource of energy generated by the wind turbine. Therefore, the issue of redistributing excess energy is relevant and can be solved by connecting a water supply system to provide ad-ditional potable water to consumers. At the same time, pressure instability in the hydraulic water supply network can worsen living conditions and lead to accidents and disruptions in technological processes.In connection with these challenges, there is a need to measure and stabilise the pressure in the hydraulic network, which can be done using observers of technological coordinates developed on the basis of the theory of artificial neural networks. The paper proposes a modern electromechanical control system for a turbomechanism powered by an alternative source of electrical energy, with a focus on stabilising the pressure in a hydraulic network using a pressure observer.A mathematical description of the main elements of the investigated system is given. The pressure estimator of the hydraulic network is built on the basis of artificial neural networks with a modified structure with feedback. The paper considers the operation of a sensorless pressure stabilisation system during changes in hydraulic re-sistance within the daily water consumption cycle with redistribution of excess energy generated by a wind tur-bine. The results and analysis of the developed estimator in sensorless control systems powered by a wind turbine with an electronic load controller are presented. |
| doi_str_mv | 10.36296/1819-8058.2025.1(80).100-107 |
| first_indexed | 2025-07-17T11:39:53Z |
| format | Article |
| fulltext |
100
Відновлювана енергетика. №1/2025 | Вітроенергетика
УДК 62-83: 628.12 https://doi.org/10.36296/1819-8058.2025.1(80)100-107
INVESTIGATION OF A SENSORLESS WATER SUPPLY SYSTEM FOR EXCESS ENERGY REDISTRI-BUTION
FROM WIND TURBINE
Received Sept. 20, 2024; accepted Mar. 14, 2025
Available online Apr. 01, 2025
Zemlianukhina H.1, Burian S.2, Pechenik M.3,
Trotsenko Ye.4, Pushkar M.5
Author for correspondence: Zemlianukhina Hanna,
e-mail: annzemlya@gmail.com
Environment-friendly and cost-effective generation of electricity
from alternative sources is becoming particularly relevant in the
context of rising energy prices for electricity generation, as well as
due to the significant damage to Ukraine's energy system caused
by the war. In certain areas, only stand-alone power generation
systems can be used, as it is impractical and unprofitable to lay
power grids in these areas. Such systems are usually based on a
combination of wind or hydro turbines, drive motors and electric
generators. It is characterised by high reliability, long service life,
low cost and ease of maintenance. In times of military emergency, the operation of autonomous systems can be
critical for people's lives and communication with the outside world. In addition, in such systems, the main con-
sumers of electricity do not use the entire resource of energy generated by the wind turbine. Therefore, the issue
of redistributing excess energy is relevant and can be solved by connecting a water supply system to provide ad-
ditional potable water to consumers. At the same time, pressure instability in the hydraulic water supply network
can worsen living conditions and lead to accidents and disruptions in technological processes.
In connection with these challenges, there is a need to measure and stabilise the pressure in the hydraulic network,
which can be done using observers of technological coordinates developed on the basis of the theory of artificial
neural networks. The paper proposes a modern electromechanical control system for a turbomechanism powered
by an alternative source of electrical energy, with a focus on stabilising the pressure in a hydraulic network using
a pressure observer.
A mathematical description of the main elements of the investigated system is given. The pressure estimator of
the hydraulic network is built on the basis of artificial neural networks with a modified structure with feedback.
The paper considers the operation of a sensorless pressure stabilisation system during changes in hydraulic re-
sistance within the daily water consumption cycle with redistribution of excess energy generated by a wind tur-
bine. The results and analysis of the developed estimator in sensorless control systems powered by a wind turbine
with an electronic load controller are presented.
Key words: pump unit, sensorless control, wind turbine, artificial neural network, pressure stabilisation, pressure
observer.
ДОСЛІДЖЕННЯ БЕЗДАВАЧЕВОЇ СИСТЕМИ ВОДОПОСТАЧАННЯ ПРИ ПЕРЕРОЗПОДІЛІ
НАДЛИШКОВОЇ ЕНЕРГІЇ ВІД ВІТРОУСТАНОВКИ
Отримано 20 вер. 2024 р.; рекомендовано до публікації 14 бер. 2025 р.
Доступно онлайн 01 квіт. 2025 р.
Землянухіна Г. Ю.1, Бур’ян С. О.2, Печеник М. В.3,
Троценко Є. О.4, Пушкар М. В.5
Автор для кореспонденції: Землянухіна Ганна,
e-mail: annzemlya@gmail.com
Екологічні та економні способи отримання електричної
енергії з використанням альтернативних джерел набува-
ють особливого значення з огляду на зростання цін на ене-
ргоносії, які використо-вуються для виробництва елект-
рики, а також через значні пошкодження енергосистеми
1 PhD
https://orcid.org/0000-0002-9653-8416
2 Cand. of Tech. Science, Associate Professor
https://orcid.org/0000-0002-4947-0201
3 Cand. of Tech. Science, Professor
https://orcid.org/0000-0002-4527-1125
4 Cand. of Tech. Science, Associate Professor
https://orcid.org/0000-0001-9379-0061
5 Cand. of Tech. Science, Associate Professor
https://orcid.org/0000-0002-9576-6433
1, 2, 3, 4, 5 National Technical University of
Ukraine “Igor Sikorsky Kyiv Polytechnic
Institute”, Kyiv, Ukraine
1 PhD
https://orcid.org/0000-0002-9653-8416
2 канд. техн. наук, доц.
https://orcid.org/0000-0002-4947-0201
3 канд. техн. наук, проф.
https://orcid.org/0000-0002-4527-1125
4 канд. техн. наук, доц.
https://orcid.org/0000-0001-9379-0061
5 канд. техн. наук, доц
https://orcid.org/0000-0002-9576-6433
1, 2, 3, 4, 5 Національний технічний університет
України «Київський політехнічний інститут
імені Ігоря Сікорського», м. Київ, Україна
101
Відновлювана енергетика. №1/2025 | Вітроенергетика
України внаслідок війни. В окремих районах можливе за-
стосування лише автономних систем генеруван-ня елек-
тричної енергії, оскільки прокладання електричних мереж
у цих місцевостях є недоціль-ним і нерентабельним. Такі
системи зазвичай базуються на поєднанні вітро- або гідротурбін, при-водних двигунів та електричних
генераторів. Вони характеризуються високою надійністю, трива-лим терміном експлуатації, низькою
собівартістю та простотою обслуговування. В умовах воєн-ного стану робота автономних систем
може бути критично важливою для життя людей і забезпе-чення зв’язку з зовнішнім світом. Також в
таких системах основними споживачами електричної енергії використовується не весь ресурс вироб-
леної вітроустановкою енергії. Тому питання пе-рерозподілу надлишкової енергії є актуальним та
може вирішуватися підключенням системи водопостачання для забезпечення додаткових потреб спо-
живачів. Водночас нестабільність тиску в гідравлічній мережі водопостачання може погіршити побу-
тові умови, призвести до аварій і збоїв у технологічних процесах.
Через ці виклики виникає потреба у вимірюванні та стабілізації тиску в гідромережі, що можливо здій-
снити за допомогою оцінювачів технологічних координат, розроблених на основі теорії шту-чних ней-
ронних мереж. У роботі запропоновано сучасну електромеханічну систему керування турбомеханіз-
мом, що живиться від альтернативного джерела електричної енергії, з акцентом на стабілізацію
тиску в гідравлічній мережі за допомогою оцінювача тиску.
Наведено математичний опис основних елементів досліджуваної системи. Оцінювач тиску гідра-вліч-
ної мережі побудовано на основі штучних нейронних мереж із модифікованою структурою зі зворотнім
зв’язком. Розглянуто роботу бездавачевої системи стабілізації тиску під час змін у гідра-влічному опорі
протягом добового циклу споживання води при перерозподілі надлишкової ене-ргії, отриманої внаслідок
живлення від вітроустановки. Презентовано результати та аналіз роботи розробленого оцінювача в
системах бездавачевого керування, що живиться від вітроустановки з електронним регулятором на-
вантаження.
Ключові слова: насосна установка, бездавачеве керування, вітроустановка, штучна нейронна мережа,
стабілізація напору, оцінювач тиску.
The list of used symbols and abbreviations:
ELC – electronic load controller
PU – pump unit
SEG – self-excited induction generator
Background. Modern technologies in the field of electricity
generation provide an extremely important contribution to
the sustainable development of society and its infrastruc-
ture. Electricity is a key resource for the functioning of var-
ious sectors of the economy, including industry, transport,
agriculture, services and household consumers. A stable
supply of electricity is essential for the smooth operation of
both small businesses and large production complexes. In
addition, electricity powers critical infrastructure facilities,
including medical institutions, water and heat supply sys-
tems, transport networks, and information and communi-
cation systems. Thus, the stability of these facilities directly
depends on the reliability of electricity generation and sup-
ply systems [1].
Electricity generation systems can be based on the use of
various energy sources, which can be divided into two main
categories: non-renewable and renewable. The first cate-
gory includes fossil fuels such as coal, natural gas and oil.
These sources have historically been the main ones for
electricity generation, as they have high energy density and
can provide a stable and constant supply of energy [2], [3].
However, they also have significant disadvantages, includ-
ing high levels of environmental pollution due to green-
house gas emissions, which contribute to global climate
change.
At the same time, renewable energy sources, such as wind,
solar, hydropower and biomass, are becoming increasingly
widespread due to their environmental friendliness. They
do not cause significant emissions of harmful substances
and do not deplete natural resources, making them a more
sustainable choice for the future [4], [5]. However, their ef-
ficiency depends on many factors, including natural condi-
tions (wind or sunlight), which can affect the stability of
electricity supply. The choice of a specific source for an
electricity generation system depends on factors such as
geographical location, resource availability, economic costs
of installation and operation, and environmental impact.
Typical power generation systems, regardless of the source
used, have a number of common components. These in-
clude energy sources, energy conversion devices (e.g. tur-
bines or photovoltaic panels), power generators, manage-
ment and control systems, and electricity distribution and
transmission systems. Depending on the type of system, it
may include a variety of technical components, such as in-
ternal combustion engines, wind turbines, solar panels,
1, 2, 3, 4, 5 Національний технічний університет
України «Київський політехнічний інститут
імені Ігоря Сікорського», м. Київ, Україна
102
Відновлювана енергетика. №1/2025 | Вітроенергетика
batteries and other devices that convert energy from a pri-
mary source into electricity.
In recent years, alternative power generation technologies,
including wind turbines, have gained special attention as
one of the most promising forms of renewable energy.
Wind turbines using self-excited induction generators
(SEGs) provide efficient electricity generation using the ki-
netic energy of the wind. However, one of the main chal-
lenges associated with their operation is the need to stabi-
lise the voltage in the system to prevent failures during
heavy loads [6]. In the case of unstable voltage, there may
be problems with generator shutdowns, which in turn leads
to interruptions in electricity supply.
Various technical solutions are proposed to solve the prob-
lem of voltage stabilisation, among which the use of elec-
tronic load controllers (ELCs) is particularly effective [7], [8].
These devices allow adjusting the voltage in the system by
automatically adjusting electrical parameters, which en-
sures stable operation of the generator even under variable
loads. One of the important advantages of such solutions is
the ability to use excess electricity to power auxiliary sys-
tems, such as water supply systems, which can use this en-
ergy for irrigation, water injection or other needs. Thus, the
introduction of such solutions not only improves the effi-
ciency of wind turbines, but also contributes to a more ra-
tional use of available energy resources.
Meanwhile, ensuring high-precision and efficient control of
the parameters of process facilities is a critical task in mod-
ern electromechanical automation systems, in particular in
the field of turbo-mechanism control. In many cases, the
installation of traditional sensors to measure various pa-
rameters can be technically difficult and financially burden-
some [9]. For example, in hydraulic systems, where param-
eters such as pressure, fluid flow, rotational speed, and
other coordinates need to be monitored, a large number of
sensors significantly increases the cost of the system and
complicates its installation and operation. To optimise such
processes and reduce costs, parameter estimators are
widely used [10]. Estimators allow determining certain co-
ordinates based on information that is already available
and accessible in the system or values from other measur-
ing devices [11].
One of the promising approaches to the implementation of
observers is the use of artificial neural networks [12], [13].
They are capable of learning from a large amount of input
data, which makes it possible to estimate parameters that
cannot be directly measured. Low- and medium-level logic
controllers can be used for their implementation, which
makes this approach flexible and affordable [14].
In turbomechanism control systems, neural networks can
be used to estimate parameters such as pressure, perfor-
mance, mechanical power, and efficiency based on a lim-
ited number of input signals [15]. This can significantly im-
prove the efficiency of control, monitoring and
optimisation of turbo-mechanisms, while reducing the cost
of installing and maintaining sensors.
The use of artificial neural networks in turbomechanism
control systems is a relevant and promising area of re-
search, as it not only provides more accurate control and
management, but also significantly reduces the cost of tra-
ditional measurement and maintenance equipment.
Research objective. The aim of the paper is to investigate a
sensorless water supply system with a modified pressure
observer with feedback, powered by excess electrical en-
ergy generated by a wind turbine using an electronic load
controller.
The research methods are mathematical modelling in the
MATLAB application package, namely the use of Simulink
and ntstool.
Presenting of main materials. In general, the SEG voltage
stabilisation system using an ELC includes a ballast resistor
that acts as a ballast load [16].
The functional diagram of a sensorless turbomechanism
control system that uses a pressure observer based on a
modified neural network with feedback, powered by a wind
turbine generator through an electronic load controller, is
shown in Fig. 1.
In Fig. 1, an induction generator is connected to a load that
can vary from 0 % to 100 % of its rated value during opera-
tion. In parallel with the generator and the load, the ELC is
connected, which consists of a rectifier, a filtering capacitor
(СЕLC), and a ballast load, which is represented by the water
supply system under the condition of stabilising the pres-
sure in the network.
The SEG rotor is driven by the wind turbine at a constant
velocity, regardless of changes in wind speed. At the same
time, the wind velocity can vary from the nominal to the
critical one. A capacitor bank connected in parallel accord-
ing to the ‘delta’ scheme is used to ensure self-excitation of
the SEG. The capacity of this battery is calculated in such a
way that the self-excitation process is guaranteed when the
rated load is connected to the generator. For a more accu-
rate determination of the required capacity, a preliminary
calculation of the SEG self-excitation limits in the coordi-
nates ‘capacity - rotational speed - load’ is performed, as
well as an analytical determination of the static voltage
characteristics of the generator [17].
In Fig. 1. the following notations are introduced: IG – induc-
tion generator; FC – frequency converter; IM – induction
motor; PU – pump unit; NN – pump pressure observer
based on a neural network; *
2u – task for pressure; PC –
pressure regulator configured for the PI control law; KfH –
feedback coefficient for and pressure; 1 – angular velocity
of the IG rotor; С – capacity of excitation capacitors; –
pump velocity; LT – load torque on the pump motor shaft;
Р – power of the pump drive motor; І – stator current mod-
ule of the pump drive motor; Ĥ – observed value of the
pump pressure; * – given speed; Ua, Ub, Uc – stator phase
voltage; Uabc – given stator phase voltage.
103
Відновлювана енергетика. №1/2025 | Вітроенергетика
Fig. 1. Functional diagram for the investigation of a sensorless control system for the turbomechanism
One of the key functions of the ELC is to maintain a constant
load on the generator set, which ensures a constant output
voltage. In case of load changes in the system, the ballast
load, which is realised through the pumping system, is au-
tomatically connected, keeping the total power supplied to
the generator unchanged. This avoids voltage fluctuations
and ensures stable operation of the generator [18], [19].
total L balP P P ,= + (1)
where Ptotal – the total electrical power at the generator; PL
– the electrical power consumed by the load connected to
the SEG; Pbal – the electrical power consumed by the ballast
load.
For further research, the method of mathematical model-
ling based on a mathematical description of the main ele-
ments of the system was used.
The mathematical model of SEG, represented in an orthog-
onal coordinate system rotating at an arbitrary velocity, is
described by a system of nonlinear differential equations
[20]:
1
1 1 1 e 1
2
2 2 n 1 e 2
d
U R i J ,
dt
d
R i (p )J ,
dt
= − −
= − + −
(2)
where
0 1
J
1 0
−
=
,
T
1 1d 1q = ,
T
2 2d 2q = –
vectors of stator and rotor flux linkages;
T
1 1d 1qi i i = ,
T
2 2d 2qi i i = – vectors of stator and rotor currents;
T
1 1d 1qU U U = – stator voltage vector; 1R , 2R – active
resistances of the stator and rotor; np – number of pole
pairs; e – angular velocity of rotation of an arbitrary coor-
dinate system d-q.
The mathematical model of the induction pump motor is
based on the classical system in the stator a-b coordinates
[21]. The frequency converter of the PU is configured in ac-
cordance with the quadratic frequency control law [22]. To
maintain a stable pressure in the hydraulic network, a pres-
sure regulator is used that implements the PI control law;
details of the mathematical description of this regulator
can be found in [23].
The dynamics of transient processes in a single-unit PU, tak-
ing into account the hydraulic network, is described by the
system of equations [24]:
2
20n
st n2
n
2
20n
n2
n
L
HdQ
H (а а)Q ,
dt
H
H a Q ,
gQH
T ,
= − − +
= −
=
(3)
where Q – pump productivity; H – pump pressure; 0nH –
nominal pressure at zero supply at the nominal speed; n
– nominal speed of the pump; – pump integration time
constant; stH – geodetic height of the water level; na –
nominal hydraulic resistance of the pump; a – hydraulic re-
sistance of the network; – density of water; g – free fall
acceleration; – pump efficiency; t – time.
In the model of a water supply system, the operation of
consumers is approximated by a given hydraulic resistance
determined on the basis of a typical water flow curve,
LoadIG
aU
bU
cU
1ω
С
aU
bU
cU
IM ωFC
+
-
PC
fHK
PU
HNN
РІ
Rectifier
ERLC
LT
ω*
*
2u
104
Відновлювана енергетика. №1/2025 | Вітроенергетика
which is selected depending on the operating conditions
and the scope of the electromechanical system.
When modelling neural networks, special attention should
be paid to their mathematical description. In general, the
neuronal equation is described as follows [12]:
m
i i j ij i
j 1
y ( x w b ),
=
= + (4)
where x1, x2, … xm – neuron inputs; wi1,wi2, …, wim – weight
coefficients of synaptic connections; bi – displacement of
the neuron; λi(.) – activation function of the neuron.
To solve the problem of estimating technological parame-
ters in a continuous conveying system, the NARX neural
network with feedback was chosen. The modified structure
of the coordinate estimator improves the accuracy of de-
termining the output parameter under conditions of varia-
ble dynamic influences, in particular, the hydraulic re-
sistance of the network. Neural networks with feedback
can function with incomplete or noisy data, efficiently pro-
cessing large amounts of information and performing dis-
tributed processing on multiple nodes, which makes them
suitable for working with large-scale data sets.
For investigation, a neural network consisting of two layers
was used: the first layer with 10 neurons and the output
layer with 1 neuron. The equations describing the function-
ing of neurons in a two-layer network with 10 neurons,
three input signals and feedback for the tasks of estimating
the pressure in a pumping unit are as follows:
11 12 13 1 1 1 21 22 23 2 2 2
31 32 33 3 3 3 41 42 43 4 4 4
51 52 53 5 5 5 61 62 63 6 6 6
ˆ ˆ ˆН c(th((Рw w Іw b Н) / a )w th((Рw w Іw b Н) / a )w
ˆ ˆth((Рw w Іw b Н) / a )w th((Рw w Іw b Н) / a )w
ˆ ˆth((Рw w Іw b Н) / a )w th((Рw w Іw b Н) / a )w
= + + + + + + + + + +
+ + + + + + + + + + +
+ + + + + + + + + + +
+ 71 72 73 7 7 7 81 82 83 8 8 8
91 92 93 9 9 9 101 102 103 10 10 10
ˆ ˆth((HРw w Іw b Н) / a )w th((Рw w Іw b Н) / a )w
ˆ ˆth((Рw w Іw b Н) / a )w th((Рw w Іw b Н) / a )w b),
+ + + + + + + + + +
+ + + + + + + + + + +
(5)
where c – coefficient of inclination of the linear activation
function; Р, ω, І – neuron inputs (power, velocity, stator cur-
rent module); wi1, wi2, wi3, …, wim – weight coefficients of
synaptic connections; bi – displacement of the neuron; a1 –
coefficient of inclination of the hyperbolic tangent function
tansig.
Further training of the neural network for the implementa-
tion of the pressure observer was carried out using the Le-
venberg-McWardt method (trainlm) to solve the problem
of function approximation [25], using the MATLAB ntstool
application package.
Based on the above mathematical description of the key el-
ements of the electromechanical system, a model was cre-
ated in the MATLAB SimPowerSystems and Simulink envi-
ronments. The model is used to study a water supply
system with a modified structure of the pressure estimator
under conditions of stabilisation of the head in the hydrau-
lic system when powered by excess energy generated by a
wind turbine (Fig. 1). The modelling was carried out for an
installation with the following parameters: the power of
the SEG was 5.5 kW, the induction drive motor was 4 kW,
and the pump was 3.7 kW.
One of the typical water consumption patterns during the
daily cycle in residential water supply systems was chosen
for the research [23], [26]. The graph of changes in the hy-
draulic resistance of the network is shown in Fig. 2. The
start of the daily cycle is 5 s earlier, as the generator and
engine must first be accelerated. Conventionally, the cycle
is divided into four main phases: morning (6:00-12:00), day-
time (12:00-17:00), evening (17:00-21:00) and nighttime
(21:00-6:00). The highest load on the system occurs in the
morning and evening, when the hydraulic resistance of the
network is minimal. The gradual nature of the resistance
change is explained by the fact that processes in liquid
transport systems are subject to minor fluctuations. This
helps to improve the accuracy of training sets for the neural
network that estimates pressure, although there is no sig-
nificant impact on other system parameters. The increase
in the amount of training data, however, complicates the
modelling of such processes both in the time dimension
and in terms of memory usage of computing devices [27].
Fig. 2. Graph of changes in hydraulic resistance in the hy-
draulic network of the system
Further studies were carried out for the following values of
electric power Pbal and the level of pressure stabilisation in
the hydraulic network to meet the needs of consumers:
− from 0 s to 7 s (morning cycle period) Pbal = 1.65 kW,
which corresponds to 30% of the total generator power
Ptotal; pressure stabilisation level – 5 m
105
Відновлювана енергетика. №1/2025 | Вітроенергетика
− from 7 s to 15 s (daytime period of the cycle) Pbal = 2.75
kW, which corresponds to 50% of Ptotal; pressure stabili-
sation level – 10 m.
− from 15 s to 22 s (evening period of the cycle) Pbal = 0
kW, which corresponds to 0% of Ptotal.
− from 22 s to 30 s (night period of the cycle) Pbal = 4.95
kW, which is 90% of Ptotal; pressure stabilisation level –
40 m.
The results of the investigation are shown in Figs. 3–5.
Fig. 3. Transients in a sensorless control system: actual H
and observed Ĥ pump pressure
Fig. 4. Transients in a sensorless control system:
pump performance
From the graphs in Figs. 3–5, it can be seen that in the pro-
cess of investigating the sensorless control system of the
turbomechanism with a modified pressure estimator and
feedback, which is powered by a wind turbine using an elec-
tronic load controller to redistribute excess electrical en-
ergy, the system successfully stabilises the pressure in the
hydraulic network within the daily cycle with high accuracy
at the corresponding specified levels. When comparing the
estimated pressure value in the sensorless control system
with the actual pressure value obtained using a pressure
sensor, the estimation error varies from 0% to 14%. Such
errors are caused by abrupt changes in the hydraulic re-
sistance of the network. At night, oscillatory processes are
observed due to the low resistance of the hydraulic net-
work. Since the pump acts as a ballast load, the developed
system can be used for additional tasks in water supply sys-
tems, such as irrigation or pumping water into tanks.
The results of the investigation have confirmed that the de-
veloped pressure observer can be effectively used in sen-
sorless pressure stabilisation systems in hydraulic networks
powered by wind turbines when redistributing excess en-
ergy.
Fig. 5. Transients in a sensorless control system: velocity of
the pump drive motor
Conclusions. Based on the research, the following conclu-
sions have been formulated:
A sensorless water supply system with a modified feedback
pressure estimator was developed, which is powered by a
wind turbine using an electronic load controller under con-
ditions of stabilising the pressure of the hydraulic network.
This system allows the pumping unit to be used as a ballast
load in an autonomous network, which makes it possible to
consume excess energy and meet the needs of consumers,
such as pumping water into reservoirs and irrigation.
The design and training of a pumping unit pressure ob-
server is based on artificial neural networks, which ensures
the implementation of the principle of sensorless control of
turbomechanisms. Removing pressure sensors from the
system reduces its cost. The use of a neural network with
feedback allows for accurate modelling of dynamic pro-
cesses with an error of up to 15% in estimating process co-
ordinates. Dynamic errors are associated with abrupt
changes in the hydraulic resistance of the network.
Research was conducted on a sensorless control system for
a turbomechanism with a modified pressure estimator with
feedback, which is powered by a wind turbine while redis-
tributing excess energy. When comparing the estimated
pressure values obtained in the sensorless system with the
106
Відновлювана енергетика. №1/2025 | Вітроенергетика
actual pressure measured by the sensor, it was found that
the estimation error ranges from 0% to 14%.
The results of the investigation can be recommended for
use in the design of new or reconstruction of existing con-
trol systems for pumping systems powered by a wind tur-
bine with a self-excited induction generator, provided that
the wind turbine velocity is constant.
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| id | veorgua-article-511 |
| institution | Vidnovluvana energetika |
| keywords_txt_mv | keywords |
| language | English |
| last_indexed | 2026-07-19T01:15:22Z |
| publishDate | 2025 |
| publisher | Institute of Renewable Energy National Academy of Sciences of Ukraine |
| record_format | ojs |
| resource_txt_mv | veorgua/f5/f6acf1e1ec5484fc6d409deaa0270ef5.pdf |
| spelling | veorgua-article-5112026-07-18T06:32:21Z INVESTIGATION OF A SENSORLESS WATER SUPPLY SYSTEM FOR EXCESS ENERGY REDISTRI-BUTION FROM WIND TURBINE ДОСЛІДЖЕННЯ БЕЗДАВАЧЕВОЇ СИСТЕМИ ВОДОПОСТАЧАННЯ ПРИ ПЕРЕРОЗПОДІЛІ НАДЛИШКОВОЇ ЕНЕРГІЇ ВІД ВІТРОУСТАНОВКИ Zemlianukhina, H. Burian , S. Pechenik , M. Trotsenko , Ye. Pushkar , M. pump unit, sensorless control, wind turbine, artificial neural network, pressure stabilisation, pressure observer. насосна установка, бездавачеве керування, вітроустановка, штучна нейронна мережа, стабілізація напору, оцінювач тиску. Environment-friendly and cost-effective generation of electricity from alternative sources is becoming particularly relevant in the context of rising energy prices for electricity generation, as well as due to the significant damage to Ukraine's energy system caused by the war. In certain areas, only stand-alone power generation systems can be used, as it is impractical and unprofitable to lay power grids in these areas. Such systems are usually based on a combination of wind or hydro turbines, drive motors and electric generators. It is characterised by high reliability, long service life, low cost and ease of maintenance. In times of military emergency, the operation of autonomous systems can be critical for people's lives and communication with the outside world. In addition, in such systems, the main con-sumers of electricity do not use the entire resource of energy generated by the wind turbine. Therefore, the issue of redistributing excess energy is relevant and can be solved by connecting a water supply system to provide ad-ditional potable water to consumers. At the same time, pressure instability in the hydraulic water supply network can worsen living conditions and lead to accidents and disruptions in technological processes.In connection with these challenges, there is a need to measure and stabilise the pressure in the hydraulic network, which can be done using observers of technological coordinates developed on the basis of the theory of artificial neural networks. The paper proposes a modern electromechanical control system for a turbomechanism powered by an alternative source of electrical energy, with a focus on stabilising the pressure in a hydraulic network using a pressure observer.A mathematical description of the main elements of the investigated system is given. The pressure estimator of the hydraulic network is built on the basis of artificial neural networks with a modified structure with feedback. The paper considers the operation of a sensorless pressure stabilisation system during changes in hydraulic re-sistance within the daily water consumption cycle with redistribution of excess energy generated by a wind tur-bine. The results and analysis of the developed estimator in sensorless control systems powered by a wind turbine with an electronic load controller are presented. Екологічні та економні способи отримання електричної енергії з використанням альтернативних джерел набува-ють особливого значення з огляду на зростання цін на енергоносії, які використовуються для виробництва елект-рики, а також через значні пошкодження енергосистеми України внаслідок війни. В окремих районах можливе за-стосування лише автономних систем генеруван-ня елек-тричної енергії, оскільки прокладання електричних мереж у цих місцевостях є недоціль-ним і нерентабельним. Такі системи зазвичай базуються на поєднанні вітро- або гідротурбін, при-водних двигунів та електричних генераторів. Вони характеризуються високою надійністю, трива-лим терміном експлуатації, низькою собівартістю та простотою обслуговування. В умовах воєн-ного стану робота автономних систем може бути критично важливою для життя людей і забезпе-чення зв’язку з зовнішнім світом. Також в таких системах основними споживачами електричної енергії використовується не весь ресурс вироб-леної вітроустановкою енергії. Тому питання пе-рерозподілу надлишкової енергії є актуальним та може вирішуватися підключенням системи водопостачання для забезпечення додаткових потреб спо-живачів. Водночас нестабільність тиску в гідравлічній мережі водопостачання може погіршити побу-тові умови, призвести до аварій і збоїв у технологічних процесах.Через ці виклики виникає потреба у вимірюванні та стабілізації тиску в гідромережі, що можливо здій-снити за допомогою оцінювачів технологічних координат, розроблених на основі теорії шту-чних ней-ронних мереж. У роботі запропоновано сучасну електромеханічну систему керування турбомеханіз-мом, що живиться від альтернативного джерела електричної енергії, з акцентом на стабілізацію тиску в гідравлічній мережі за допомогою оцінювача тиску.Наведено математичний опис основних елементів досліджуваної системи. Оцінювач тиску гідра-вліч-ної мережі побудовано на основі штучних нейронних мереж із модифікованою структурою зі зворотнім зв’язком. Розглянуто роботу бездавачевої системи стабілізації тиску під час змін у гідра-влічному опорі протягом добового циклу споживання води при перерозподілі надлишкової ене-ргії, отриманої внаслідок живлення від вітроустановки. Презентовано результати та аналіз роботи розробленого оцінювача в системах бездавачевого керування, що живиться від вітроустановки з електронним регулятором на-вантаження. Institute of Renewable Energy National Academy of Sciences of Ukraine 2025-03-31 Article Article application/pdf https://ve.org.ua/index.php/journal/article/view/511 10.36296/1819-8058.2025.1(80).100-107 Vidnovluvana energetika ; No. 1(80) (2025): Scientific and applied Journal renewable energy ; 100-107 Возобновляемая энергетика; ##issue.no## 1(80) (2025): Scientific and applied Journal renewable energy ; 100-107 Відновлювана енергетика; № 1(80) (2025): Науково-прикладний журнал Відновлювана енергетика; 100-107 2664-8172 1819-8058 10.36296/1819-8058.2025.1(80) en https://ve.org.ua/index.php/journal/article/view/511/420 Copyright (c) 2025 H. Zemlianukhina, S. Burian , M. Pechenik , Ye. Trotsenko , M. Pushkar https://creativecommons.org/licenses/by-nc-nd/4.0 |
| spellingShingle | pump unit sensorless control wind turbine artificial neural network pressure stabilisation pressure observer. Zemlianukhina, H. Burian , S. Pechenik , M. Trotsenko , Ye. Pushkar , M. INVESTIGATION OF A SENSORLESS WATER SUPPLY SYSTEM FOR EXCESS ENERGY REDISTRI-BUTION FROM WIND TURBINE |
| title | INVESTIGATION OF A SENSORLESS WATER SUPPLY SYSTEM FOR EXCESS ENERGY REDISTRI-BUTION FROM WIND TURBINE |
| title_alt | ДОСЛІДЖЕННЯ БЕЗДАВАЧЕВОЇ СИСТЕМИ ВОДОПОСТАЧАННЯ ПРИ ПЕРЕРОЗПОДІЛІ НАДЛИШКОВОЇ ЕНЕРГІЇ ВІД ВІТРОУСТАНОВКИ |
| title_full | INVESTIGATION OF A SENSORLESS WATER SUPPLY SYSTEM FOR EXCESS ENERGY REDISTRI-BUTION FROM WIND TURBINE |
| title_fullStr | INVESTIGATION OF A SENSORLESS WATER SUPPLY SYSTEM FOR EXCESS ENERGY REDISTRI-BUTION FROM WIND TURBINE |
| title_full_unstemmed | INVESTIGATION OF A SENSORLESS WATER SUPPLY SYSTEM FOR EXCESS ENERGY REDISTRI-BUTION FROM WIND TURBINE |
| title_short | INVESTIGATION OF A SENSORLESS WATER SUPPLY SYSTEM FOR EXCESS ENERGY REDISTRI-BUTION FROM WIND TURBINE |
| title_sort | investigation of a sensorless water supply system for excess energy redistri-bution from wind turbine |
| topic | pump unit sensorless control wind turbine artificial neural network pressure stabilisation pressure observer. |
| topic_facet | pump unit sensorless control wind turbine artificial neural network pressure stabilisation pressure observer. насосна установка бездавачеве керування вітроустановка штучна нейронна мережа стабілізація напору оцінювач тиску. |
| url | https://ve.org.ua/index.php/journal/article/view/511 |
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