METHOD FOR ASSESSING THE EFFICIENCY OF THE DISTRICT HEATING SYSTEM UNDER MARKET CONDITIONS
In response to global warming and the critical need for sustainable energy solutions, district heating systems (DHS) have emerged as an area of significant focus due to their potential to enhance resource efficiency, reduce carbon emissions, and improve economic outputs. This research addresses the...
Gespeichert in:
| Datum: | 2024 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artikel |
| Sprache: | Englisch |
| Veröffentlicht: |
Institute of Renewable Energy National Academy of Sciences of Ukraine
2024
|
| Schlagworte: | |
| Online Zugang: | https://ve.org.ua/index.php/journal/article/view/482 |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Назва журналу: | Vidnovluvana energetika |
| Завантажити файл: |  |
Institution
Vidnovluvana energetika| _version_ | 1871103819989909504 |
|---|---|
| author | Karpenko, D. Yevtukhova , T. Novoseltsev , O. |
| author_facet | Karpenko, D. Yevtukhova , T. Novoseltsev , O. |
| author_institution_txt_mv | [
{
"author": " D. Karpenko",
"institution": "Institute of General Energy, NAS of Ukraine, Kyiv, Ukraine. "
},
{
"author": "T. Yevtukhova ",
"institution": "Institute of General Energy, NAS of Ukraine, Kyiv, Ukraine. "
},
{
"author": "O. Novoseltsev ",
"institution": "Institute of General Energy, NAS of Ukraine, Kyiv, Ukraine. "
}
] |
| author_sort | Karpenko, D. |
| baseUrl_str | https://ve.org.ua/index.php/journal/oai |
| collection | OJS |
| datestamp_date | 2026-07-18T06:32:20Z |
| description | In response to global warming and the critical need for sustainable energy solutions, district heating systems (DHS) have emerged as an area of significant focus due to their potential to enhance resource efficiency, reduce carbon emissions, and improve economic outputs. This research addresses the critical issue of establishing a methodological framework for evaluating the efficiency of DHS as market relations evolve within the heating sector. The study's aim is to develop and validate methodological principles that assess the operational, economic, and technological dimensions of DHS in a competitive market landscape. The framework encompasses the complex interplay of regulatory frameworks, market dynamics, production technologies, and consumer engagement strategies. Key objectives include analyzing current challenges in implementing competitive market structures, justifying the non-linear nature of cost functions for energy producers, and developing criteria for the equitable distribution of thermal energy losses. The overarching goal is to strategically propel DHS towards greater efficiency and sustainability by using renewable energy sources (RES). The research utilizes simulation modeling in a case study of Irpin city, Ukraine, employing machine learning and computer vision technologies through the "Solvergy: Buildings" mobile application to provide rapid, detailed energy performance assessments. Results from the simulation in "Solvergy: Systems" software indicate benefits from the market conditions functioning in DHS, quantified at $727,120 per year, and highlight the cost-saving potential of the RES-based supply diversification structure. The relative market efficiency at 28.05% suggests that the market delivers high potential economic value relative to a scenario without market conditions. The study concludes that transitioning to market relations and integrating independent energy producers can lead to substantial system efficiency improvements, lower thermal energy prices, and enhanced sustainability in DHS. Suggested policy measures advocate for the modernizing of infrastructure and the implementation of efficient technologies within a competitive, consumer-oriented market environment, thereby facilitating the decarbonization process and optimizing system performance. |
| doi_str_mv | 10.36296/1819-8058.2024.4(79).6-16 |
| first_indexed | 2025-07-17T11:39:40Z |
| format | Article |
| fulltext |
6
Відновлювана енергетика. №4/2024 | Комплексні проблеми енергетичних систем на основі НВДЕ
УДК 33.021.658.264(477) https://doi.org/10.36296/1819-8058.2024.4(79)6-16
METHOD FOR ASSESSING THE EFFICIENCY OF THE DISTRICT HEATING SYSTEM UNDER MARKET
CONDITIONS
Received Sept. 04, 2024; accepted Nov. 27, 2024
Available online Dec. 11, 2024
Karpenko D.1, Yevtukhova T.2, Novoseltsev O.3
Author for correspondence: Karpenko Dmytro,
e-mail: dmytro.qua@gmail.com
Abstract. In response to global warming and the critical need for
sustainable energy solutions, district heating systems (DHS) have
emerged as an area of significant focus due to their potential to en-
hance resource efficiency, reduce carbon emissions, and improve
economic outputs. This research addresses the critical issue of es-
tablishing a methodological framework for evaluating the efficiency
of DHS as market relations evolve within the heating sector. The study's aim is to develop and validate meth-
odological principles that assess the operational, economic, and technological dimensions of DHS in a com-
petitive market landscape. The framework encompasses the complex interplay of regulatory frameworks,
market dynamics, production technologies, and consumer engagement strategies. Key objectives include an-
alyzing current challenges in implementing competitive market structures, justifying the non-linear nature of
cost functions for energy producers, and developing criteria for the equitable distribution of thermal energy
losses. The overarching goal is to strategically propel DHS towards greater efficiency and sustainability by
using renewable energy sources (RES). The research utilizes simulation modeling in a case study of Irpin city,
Ukraine, employing machine learning and computer vision technologies through the "Solvergy: Buildings"
mobile application to provide rapid, detailed energy performance assessments. Results from the simulation
in "Solvergy: Systems" software indicate benefits from the market conditions functioning in DHS, quantified
at $727,120 per year, and highlight the cost-saving potential of the RES-based supply diversification struc-
ture. The relative market efficiency at 28.05% suggests that the market delivers high potential economic
value relative to a scenario without market conditions. The study concludes that transitioning to market re-
lations and integrating independent energy producers can lead to substantial system efficiency improve-
ments, lower thermal energy prices, and enhanced sustainability in DHS. Suggested policy measures advocate
for the modernizing of infrastructure and the implementation of efficient technologies within a competitive,
consumer-oriented market environment, thereby facilitating the decarbonization process and optimizing sys-
tem performance.
Кеy words: district heating system, district heating market, thermal energy loss, renewable energy sources,
competitive bidding and auctions, multifactor optimization.
МЕТОД ОЦІНЮВАННЯ ЕФЕКТИВНОСТІ СИСТЕМ ЦЕНТРАЛІЗОВАНОГО ТЕПЛОПОСТАЧАННЯ В
УМОВАХ КОНКУРЕНЦІЇ
Отримано 04 вер. 2024 р.; рекомендовано до публікації 27 лист. 2024 р.
Доступно онлайн 11 груд. 2024 р.
Карпенко Д. С.1, Євтухова Т. О.2, Новосельцев О. В.3
Автор для кореспонденції: Карпенко Дмитро,
e-mail: dmytro.qua@gmail.com
З огляду на глобальне потепління та критичну потребу в стій-
ких енергетичних рішеннях системам централізованого теп-
лопостачання приділяють особливу увагу через їхній потенціал
до підвищення ефективності використання ресурсів, скоро-
1 Cand. of Tech. Sciences
https://orcid.org/0000-0002-8022-9782
2 Cand. of Tech. Sciences
https://orcid.org/0000-0003-4778-2479
3 Corresponding member of NAS of
Ukraine, Dr. of Tech. Sciences
https://orcid.org/0000-0001-9272-6789
1, 2, 3 Institute of General Energy, NAS of
Ukraine, Kyiv, Ukraine.
1канд. техн. наук
https://orcid.org/0000-0002-8022-9782
2 канд. техн. наук, доц.
https://orcid.org/0000-0003-4778-2479
3 чл.-кор. НАН України, д-р техн. наук
https://orcid.org/0000-0001-9272-6789
1, 2, 3 Інститут загальної енергетики
НАН України, м. Київ, Україна
7
Відновлювана енергетика. №4/2024 | Комплексні проблеми енергетичних систем на основі НВДЕ
чення викидів вуглецю та покращення економічних результатів. У цьому дослідженні розглядається ва-
жливе питання створення методологічної основи для оцінювання ефективності систем централізо-
ваного теплопостачання (СЦТ), оскільки ринкові відносини розвиваються в секторі теплопостачання.
Метою дослідження є розробка та перевірка методологічних принципів, які оцінюють операційні, еко-
номічні та технологічні аспекти СЦТ у конкурентному ринковому ландшафті. Структура охоплює
складну взаємодію нормативно-правової бази, динаміки ринку, технологій виробництва та стратегій
залучення споживачів. Серед основних цілей ‒ аналіз поточних викликів у впровадженні конкурентних
ринкових структур, обґрунтування нелінійного характеру функцій витрат для виробників енергії та
розробка критеріїв для справедливого розподілу втрат теплової енергії. Основна мета полягає в тому,
щоб стратегічно підштовхнути СЦТ до підвищення ефективності та стійкості за рахунок викорис-
тання відновлюваних джерел енергії (ВДЕ). У дослідженні використовується імітаційне моделювання в
прикладі міста Ірпінь, Україна, з використанням технологій машинного навчання та комп’ютерного
бачення через мобільний застосунок «Solvergy: Buildings» для надання швидких детальних оцінок енер-
гоефективності. Результати моделювання в програмному забезпеченні "Solvergy: Systems" вказують
на переваги функціонування СЦТ у ринкових умовах, які кількісно оцінені в 727 120 доларів США за рік, і
підкреслюють потенціал економії витрат структури диверсифікації постачання на основі ВДЕ. Відно-
сна ефективність ринку на рівні 28,05 % свідчить про те, що ринок забезпечує високий економічний по-
тенціал порівняно зі сценарієм без ринкових умов. У дослідженні зроблено висновок, що перехід до рин-
кових відносин та інтеграція незалежних виробників енергії сприятиме істотному підвищенню
ефективності системи, зниженню цін на теплову енергію та підвищенню стійкості в СЦТ. Запропоно-
вані політичні заходи спрямовані на модернізацію інфраструктури та впровадження ефективних тех-
нологій у конкурентному, орієнтованому на споживача ринковому середовищі, тим самим полегшуючи
процес декарбонізації та оптимізуючи продуктивність системи.
Ключові слова: система централізованого теплопостачання, ринок централізованого теплопоста-
чання, втрати теплової енергії, відновлювані джерела енергії, конкурентні торги та аукціони, багато-
факторна оптимізація.
List of Abbreviations and Symbols:
DHS – district heating system
DHM – district heating market
SQP – sequential quadratic programming
RES – renewable energy sources
Introduction and task statement. In the context of global
warming and the pressing need for sustainable energy so-
lutions, the efficiency of district heating systems (DHS) has
garnered significant attention. The transition to market re-
lations within the heating sector presents both opportuni-
ties and challenges for enhancing operational efficiency,
sustainability, and customer satisfaction. Evaluating the ef-
fectiveness of reforms in DHSs is essential for policy devel-
opment, strategic planning, and the technological advance-
ment of district heating infrastructures. Such assessments
have the potential to optimize resource use, reduce carbon
emissions, and improve economic outcomes for both sup-
pliers and consumers. Establishing a methodological frame-
work for evaluating the efficiency of DHSs amid the for-
mation of market relations is a critical issue for assessing
the feasibility of transitioning to more competitive, effi-
cient, and environment-friendly centralized DHSs.
The effectiveness of a district heating system can be as-
sessed through various economic, ecological, and techno-
logical efficiency indicators. However, each of these ap-
proaches must consider the current state of energy in the
region to identify the most effective strategies for enhanc-
ing system efficiency. In Ukraine, for instance, the transfor-
mation of DHSs should focus on the utilization of renewable
energy sources (RES) and customer-centric strategies,
emphasizing the significance of strategic, sustainable, and
feasible reforms aimed at improving energy efficiency, op-
erational reliability, and financial stability [1, 2].
Among the challenges confronting DHSs in Ukraine are out-
dated infrastructure, a high dependence on natural gas, fi-
nancial constraints, the necessity for modernization, and
significant air pollution stemming from emissions produced
by energy facilities [3]. Key strategies for enhancing the ef-
ficiency of DHSs in Ukraine include balancing heat demand
with production and transportation capacities, integrating
biomass as an alternative fuel source, and introducing com-
petitive market dynamics to improve the quality and acces-
sibility of heat supply services [4].
The adaptation of electricity market policies to DHSs is a
particularly relevant area of study. Numerous researchers
emphasize the necessity of establishing competitive condi-
tions in DHSs that are akin to those found in electricity sup-
ply systems. For instance, market liberalization can moti-
vate industrial heat producers to utilize waste heat as an
additional resource within district heating networks. Under
competitive conditions, the system can adopt pool and
peer-to-peer (P2P) market models, wherein the integration
of new participants into district heating systems empha-
sizes consumer choice through differentiated products, al-
lowing consumers to select their preferred heat sources [5,
8
Відновлювана енергетика. №4/2024 | Комплексні проблеми енергетичних систем на основі НВДЕ
6]. Furthermore, various trading strategies available in the
market may influence the feasibility of utilizing excess heat
and the efficiency of centralized DHSs [7, 8].
It is also crucial to implement practices that regulate third-
party access to the DHS from the production side, particu-
larly through unilateral auctions. Adopting these measures
could result in lower prices, draw in new consumers, and
facilitate the decarbonization of the heat supply sector.
Concurrently, significant attention should be directed to-
wards the role of the regulatory framework, market struc-
tures, and pricing mechanisms [9]. The economic aspects of
heat conservation and strategic system operation planning
are vital, especially in the context of transitioning to RES.
The study [10] underlines the need to revise municipal stra-
tegic energy plans and examines how local district heating
tariffs can incentivize heat savings, thereby supporting the
shift to fourth-generation district heating systems. By in-
vestigating the interactions between tariff policy, interest
rates, and heat-saving initiatives, the study underscores the
importance of aligning economic incentives with system ef-
ficiency, particularly amid technological advancements and
market uncertainty. It is noteworthy that the introduction
of competition in the DHS through market mechanisms,
such as monthly auctions, can yield numerous economic
and social benefits.
Research [11] demonstrates the feasibility and advantages
of transitioning to a competitive market in DHSs, promoting
the use of alternative energy sources, and enhancing the
overall efficiency of the system. It also underscores the im-
portance of robust political and regulatory support in ad-
vancing successful market liberalization initiatives. How-
ever, the introduction of market mechanisms is not without
its challenges; various technical, regulatory, and economic
problems accompany this process [12, 13]. Furthermore,
there exists a divergence of opinions regarding the imple-
mentation of market conditions in DHSs, particularly con-
cerning the economic justification of natural monopolies
within energy sectors. A specific study [14] indicates a sig-
nificant increase in district heating prices post-deregula-
tion, resulting in public protests and debates. Therefore,
the implementation of efficient operational practices
within existing DHSs faces numerous obstacles, especially
at the regional level, due to the presence of unique local
conditions.
Factors such as the technological structure of the DHS, the
conditions for utilizing energy sources, and weather varia-
tions can influence the efficiency of system operation un-
der various models and regulatory approaches. Conse-
quently, it is crucial to conduct system modeling to simulate
the operation of the system in both static and dynamic
modes, enabling the determination and optimization of ef-
ficiency indicators under suggested operational conditions.
Among the primary efficiency criteria, three are often em-
phasized: economic, ecological, and exergetic (or techno-
logical). These indicators are subject to multi-objective op-
timization, which significantly enhances the stability and
efficiency of district heating systems. Research [15, 16, 17]
highlights the energy and exergy benefits of integrating RES
into district heating, thereby advancing the application of
the exergy principle in system optimization.
Research results [18, 19] indicate that district heating sys-
tems offer several advantages, including enhanced fuel ef-
ficiency, reduced heat production costs, and the potential
for utilizing excess heat sources, positioning them as a via-
ble and environment-friendly heating solution in densely
populated areas. Consequently, there is a need for a sys-
tematic shift in focus towards creating or reforming com-
plex regional centralized systems, as this could lead to a
synergistic effect that enhances their operational effi-
ciency. An increase in consumption volume encourages
greater participation of third parties in the market, driven
by the prospect of increased benefits, which may result in
lower thermal energy tariffs for consumers. However, it is
essential to consider each individual system on a case-by-
case basis, taking into account local factors [20, 21]. Fur-
thermore, the study [22] concludes that while DHS remains
competitive in regions with high heat density, it may en-
counter challenges in areas with low heat density. The
study underscores the importance of considering future
market dynamics, the integration of RES, and urban plan-
ning decisions in shaping the long-term competitiveness of
district heating systems. "Power-to-Heat" systems, which
facilitate the use of energy from RES for heating and hot
water supply, are gaining particular attention. These sys-
tems enable the scaling of DHSs and contribute to their flex-
ibility, resulting in a synergistic effect from integrating elec-
tric and thermal energy markets. Research findings from
studies [23, 24, 25, 26] indicate that the incorporation of
"Power-to-Heat" systems diminishes dependence on fossil
fuels during winter months and promotes a more stable op-
eration of both DHSs and power supply systems.
Subject of study. The subject of this study is the methodo-
logical framework for evaluating the effectiveness of the
DHS, particularly in the context of developing market rela-
tions. This encompasses a comprehensive analysis of exist-
ing district heating systems, the identification of efficiency
indicators, and the assessment of how market dynamics in-
fluence these systems. The research emphasizes the inter-
play between the regulatory framework, market design,
production technologies, and consumer engagement strat-
egies, all of which collectively impact the efficiency and sus-
tainability of heating systems.
Object of study. The focus of this study is on district heating
systems functioning within a competitive market land-
scape. Specifically, it investigates the operational, eco-
nomic, and technological dimensions of these systems,
evaluating ways to optimize and sustain efficiency amid
market liberalization. The research provides a comprehen-
sive analysis of market functioning mechanisms, bidding
strategies, regulatory policies, and technological innova-
tions that aim to enhance both the efficiency and reliability
of district heating services.
The purpose and objectives of the research. Develop
methodological principles for assessing the efficiency of
9
Відновлювана енергетика. №4/2024 | Комплексні проблеми енергетичних систем на основі НВДЕ
DHSs in the context of establishing market relations among
thermal energy producers.
To achieve this goal, it is essential to address the following
tasks:
− Analyze the current challenges facing DHSs from the
perspective of implementing and operating under com-
petitive conditions, and explore methodological ap-
proaches for evaluating the effectiveness of these sys-
tems, considering both economic and technological
implications.
− Determine the functional structure and operational
principles of the DHS amidst competition among ther-
mal energy producers.
− Justify the non-linear nature of cost functions for ther-
mal energy producers and heat transport organizations.
− Propose methodological principles for evaluating the
equitable distribution of thermal energy losses among
producers within the DHS during market operation.
− Develop methodological principles for assessing and op-
timizing the efficiency of the DHS in competitive condi-
tions.
The novelty of the study is determined by the systematic
solution of the high thermal energy price problem for con-
sumers by developing a detailed methodological frame-
work for assessing the efficiency of district heating systems
in the context of market liberalization. This includes the for-
mulation and validation of non-linear cost functions for
thermal energy producers and heat transport organiza-
tions, which are critical for accurately evaluating and opti-
mizing business activities within DHSs.
The practical relevance of this study is to provide the prac-
tical management and strategic planning of DHS in various
urban settings, particularly in the context of transitioning to
market-based operational frameworks. This comprehen-
sive assessment approach can be particularly beneficial for
policymakers and regulatory bodies as they devise strate-
gies to liberalize energy markets and implement competi-
tion within DHSs.
District heating system under market conditions for-
mation. To comprehend the operational principles of a DHS
based on competition, it is essential to present a straight-
forward mathematical model that effectively illustrates the
necessity of implementing such system. This model as-
sesses the efficiency of the district heating market (DHM)
by comparing two alternatives: a scenario involving a single
producer (monopoly) versus a scenario with multiple ther-
mal energy producers within the DHS (competition) [27,
28].
The term "district heating market" generally refers to a net-
work of economic interactions involving fuel and energy
suppliers, equipment vendors, energy service providers,
heat-generating organizations, heat network operators,
regulatory authorities, and thermal energy consumers. In
contrast to a monopolistic DHS, where companies oversee
the functions of production, transportation, and distribu-
tion of thermal energy, DHM provides for legal, financial,
and property separation of the municipal vertically inte-
grated monopolist. The primary aim of this separation is to
foster competitive conditions in the thermal energy pro-
duction phase, enabling independent producers to connect
to heat networks and compete with other thermal energy
producers, including utilities, based on self-determined
pricing [29, 30].
It is important to note that energy sources that produce
electricity can be utilized alongside other technological
methods to generate thermal energy. Furthermore, electric
boilers have emerged as an efficient and increasingly pop-
ular means of producing heat from RES, particularly in the
context of district heating systems. These systems can har-
ness electricity generated from RES such as wind, solar, hy-
dro, and geothermal energy. Powerful electric boilers can
be installed at a central station, where electricity generated
from RES feeds the boilers to produce substantial volumes
of hot water or steam. Thanks to smart grid technologies
and real-time monitoring, the system can balance the load
by predicting demand and regulating the boilers accord-
ingly. This synchronization with other energy sources en-
sures optimal efficiency and minimal costs for both electri-
cal and thermal energy production. Moreover, such
approaches can mitigate issues related to system frequency
instability and capacity reservation inherent in RES, thereby
enhancing economic efficiency, reliability, and environ-
mental impact [24, 31, 32].
Each energy resource, according to its intrinsic properties,
will influence the nature of the cost function. Additionally,
for a production company that supplies thermal energy to
the heating supply system and manages multiple heat gen-
eration facilities within the market, the total cost function
can become quite complex. It encompasses all costs associ-
ated with the production of thermal energy as a consuma-
ble product. The total cost function can be categorized into
several components, each representing a specific type of
expense incurred by the company.
To effectively minimize costs, carbon dioxide emissions,
and exergy throughout the year, it is crucial to utilize a di-
verse array of energy sources, including RES such as solar
collectors, air source heat pumps, and cogeneration plants.
However, several challenges need addressing, particularly
in balancing technical efficiency with economic incentives
and institutional regulations as the market for district heat-
ing becomes more competitive [33]. Specifically in Ukraine,
the approach to evaluating efficiency criteria may be inad-
equate due to unique conditions within the DHSs, such as
monopolistic structures, distinct operational characteristics
of heat networks, and the absence of a comprehensive reg-
ulatory framework that promotes competition within DHSs.
Methodological principles for assessing the efficiency of
the DHM. To evaluate the effectiveness of implementing
and functioning market relations within DHSs, a simulation
model has been developed. This model allows for a quanti-
tative assessment of the operational viability of DHM in a
10
Відновлювана енергетика. №4/2024 | Комплексні проблеми енергетичних систем на основі НВДЕ
specified district heating system. The assessment can be
based on various factors, including the configuration of ex-
isting heat networks, the volume of thermal energy con-
sumption, and the density of demand, among others.
The model identifies three types of entities within the sys-
tem: thermal energy producers, thermal energy consum-
ers, and sections of heat networks that are integrated into
a cohesive system for transporting thermal energy from
producers to consumers.
Thermal energy consumers are characterized by their an-
nual thermal energy consumption. The aggregation of this
metric across all consumers constitutes the total thermal
energy consumed within the DHS and is determined by the
following formula:
QD = ∑ Qi
D
n
i =1
, (1)
where QD is the amount of annual thermal energy con-
sumption by all consumers in the analyzed system, GJ; Qi
D
is the amount of annual thermal energy consumption by
the i-th consumer, GJ; n is the number of thermal energy
consumers in the system.
The responsibility for the transportation and supply of ther-
mal energy primarily falls to the transportation organiza-
tion within the system. Each section of the heat network,
which consists of both a supply and a return pipeline, is
characterized by several parameters, including the internal
diameter of the pipeline, the method of installation (above
ground, underground, or in a channel), the type of insula-
tion, and the thickness of the insulation coating. These pa-
rameters are utilized to calculate heat and hydraulic losses
in the heat network, thereby evaluating the impact of the
spatial configuration of the system components.
Heat losses in heat networks are defined as the total of
thermal energy losses resulting from water leakage from
pipelines and the thermal energy losses due to the cooling
of the coolant within the pipelines:
QL = QO + ∑ qj
S∙lj ,
n
j = 1
(2)
where 𝑄𝑂 is amount of thermal energy losses with water
leakage from pipelines, GJ; qj
S is linear thermal energy losses
due to coolant cooling in the j-th section of the pipeline, GJ;
𝑙𝑗 is the length of the j-th section of the pipeline, m.
Thus, the simplified form of the total costs function for the
organization of transportation and supply of thermal en-
ergy can be presented as follows:
TCT(QT) = AT + BT∙QT + CT∙(𝑄𝑇)2 , (3)
where TCT is total cost of thermal energy transportation for
the year, $; AT is constant costs for the year, which do not
change depending on the amount of transferred heat, $; BT
is the linear part of the cost of transporting thermal energy
per year, which is correlated with variable costs that scale
directly with the amount of heat supplied, $/GJ; CT is
coefficient that characterizes the nonlinearity of the total
cost function of thermal energy transportation, $/GJ2; QT is
the amount of thermal energy transported per year, GJ.
The total amount of thermal energy that will be produced
in the system for a year will be the sum of heat losses in the
DHS network and the amount of annual thermal energy
consumption by consumers:
Q∑ = QT = QD+ QL (4)
In the DHM model, the concept of market share is intro-
duced as a constraint, signifying the maximum amount of
thermal energy that each producer is permitted to release
each month. The market share for the i-th manufacturer
(excluding the primary one) is computed using the market
share coefficient:
Qk
max =Q∑⋅ MS , (5)
where Qk
max is value that represents the market share as the
maximum amount of thermal energy production per year
for the k-th producer, GJ; MS - market share coefficient.
Each technological installation for thermal energy produc-
tion can be characterized by indicators of maneuverability,
particularly regarding changes in production capacity and
the minimum capacity required to maintain the heat-gen-
erating station in standby mode. The minimum annual ther-
mal energy requirement can be represented as an addi-
tional constraint for each producer within the objective
function:
Qk
min = Nk ∙ θk ∙ nhs∙ 86,4 , (6)
where Qk
min represents the market share as the minimum
amount of thermal energy production per year for the k-th
producer, GJ; Nk is installed capacity of heat-generating
equipment, MW; θk is coefficient that characterizes the
minimum possible production capacity of the installation;
nhs is the number of days of operation of the heat genera-
tion facility in the DHS per year.
A non-linear total cost function for a heat production facil-
ity is warranted due to the complexities and variations in-
herent in operating costs, maintenance costs, fuel ex-
penses, capital investments, and material costs. These
factors are interrelated and cannot be accurately or effec-
tively represented by a simplistic linear model. Therefore,
the general form of the total cost function for each thermal
energy producer can be expressed as follows:
TCk
G(Qk) = AG + BG∙Qk + CG∙(Qk)2 , (7)
where TCk
G is total cost of thermal energy production for the
year of the k-th producer, $; AG is constant costs for the
year, which do not change depending on the amount of
thermal energy produced, $; BG is the linear part of the cost
of thermal energy production per year, which is correlated
with variable costs that scale directly with the amount of
heat supplied, $/GJ; CG is coefficient that characterizes the
nonlinearity of the total cost function of thermal energy
production, $/GJ2; Qk is the amount of thermal energy pro-
duced per year by the k-th producer, GJ.
11
Відновлювана енергетика. №4/2024 | Комплексні проблеми енергетичних систем на основі НВДЕ
Accordingly, each producer, possessing a complete cost
function and a target profit level, calculates a forecasted
price for the sale of thermal energy, considering market
conditions and the actual quantity of thermal energy avail-
able for sale. This projected price is then included in their
auction bid. The formula for calculating the forecasted
price for thermal energy for each producer is as follows:
Tk
F =
TCk
G(Qk
max) + Pk
Qk
max , (8)
where Tk
F is forecast price for thermal energy for the k-th
producer, $/GJ; 𝑃𝑘 is expected annual profit for the k-th
thermal energy producer, $.
Manufacturers' bids for the auction, which specify the pa-
rameters Tk
F and Qk
max, are evaluated, and the winners are
determined. These winners will sell thermal energy at the
tariffs and in the amounts as proposed in the submitted bid.
The total thermal energy losses in the system can be di-
vided into two conventional components: intrinsic losses
for each producer and losses in the system attributable to
each producer. Thus, the total thermal energy losses in the
system can be expressed using the following formula:
QL = ∑ Qk
L
m
k=1
= ∑(Qk
LO+ Qk
LS)
m
k=1
, (9)
where Qk
L is total thermal energy losses of the k-th producer
for the year, GJ; Qk
LO is own thermal energy losses of the k-th
producer for the year, GJ; Qk
LS is thermal energy losses in the
system are attributed to the k-th producer for the year, GJ.
Each thermal energy producer, upon connecting to the
heat network, will possess a designated section of the heat
networks for the purpose of transferring thermal energy
into the DHS. Heat losses can be attributed to a specific
heat generation entity, allowing them to be classified as
fixed or determined. The losses attributable to the k-th
thermal energy producer will be calculated using the fol-
lowing formula:
Qk
LO = Qk
ON+ Сk
LO∙ Qk , (10)
where Qk
ON is thermal energy losses for the heat generation
facility's own needs for the year, GJ; Сk
LO is coefficient that
characterizes the share of thermal energy losses from the
total volume of released thermal energy by own heat net-
works; Qk is the actual value of the amount of thermal en-
ergy released by the k-th producer, GJ.
The integration of independent producers into the DHS un-
der market conditions generates uncertainty regarding the
equitable distribution of thermal energy losses. Accurately
attributing the costs of heat loss to various producers is
both challenging and essential for economic justice. Given
these considerations, the thermal energy losses in the sys-
tem attributable to the k-th producer will be calculated us-
ing the following formula [34]:
Qk
LS=(QLS- ∑ Qk
LO
m
k=1
)∙(ωφ∙φk+ωα∙αk+ωβ∙βk) , (11)
where ωφ is the weight of the criterion φk=
lk
∑ lk
m
k=1
is the
weight of the distance of the k-th producer to the centroid
of the DHS; lk is the distance of the k-th producer to the
centroid of the DHS; m is the number of thermal energy
producers in the DHS; ωα is the weight of the criterion αk =
Qk - Qk
L
∑ (Qk - Qk
L)m
k=1
is the weight of the amount of thermal energy
consumption produced by the k-th producer; 𝜔𝛽 is the
weight of the criterion βk=
Sk
∑ Sk
m
k=1
is the weight of the une-
venness of the paths of transportation and supply of ther-
mal energy in relation to the distance to the centroid in the
system of objects of thermal energy consumption for the k-
th producer of thermal energy; Sk is the level of unevenness
of the paths of transportation and supply of thermal energy
for the k-th producer.
At the same time, additional constraints for the objective
function will be the following expressions:
ωφ + ωα + ωβ = 1 , (13)
pφ
min < ωφ < pφ
max , (14)
pα
min < ωα < pα
max , (15)
pβ
min < ωβ < pβ
max , (16)
where pφ
min, pα
min, pβ
min, pφ
max, pα
max, pβ
max are minimum and
maximum values of the criterion weighting coefficients,
which need to be individually determined within the con-
text of the DHS under consideration, to ensure that all cri-
teria are fairly accounted for.
The objective function for minimizing the weighted average
price of thermal energy in a DHS operating under competi-
tive conditions is presented as follows:
Tw
M=
∑ (TCk
G(Qk)+Pk+(ACT(Q∑) +
PT
Q∑
)∙Qk
L(Qk))m
k = 1
QD → min, (17)
where Tw
M is the weighted average price per unit of thermal
energy as a result of the operation of the DHM, $/GJ; ACT is
the function of the average costs of the heat transport or-
ganization in the DHS, $/GJ; PT is the planned profit of the
heat transport organization for the year, $; Pk is planned
profit of the k-th thermal energy producer for the year, $.
Given the non-linearity present in the cost functions of
thermal energy producers and transportation organiza-
tions, the proposed solution to the problem involves the
use of Sequential Quadratic Programming (SQP) for non-lin-
ear optimization within the MATLAB software environ-
ment.
The benefits for consumers arising from the introduction of
DHM must be evaluated by comparing the cost of con-
sumed thermal energy with the weighted average tariffs for
thermal energy, both during its operation and in its ab-
sence. This difference constitutes one of the components
of the objective function for optimizing the operation of
DHM, where the market share coefficient serves as a con-
straint.
12
Відновлювана енергетика. №4/2024 | Комплексні проблеми енергетичних систем на основі НВДЕ
In the absence of DHM, the projected tariff for the main
producer is:
T1
MP =
TC1
G(Q∑
MP) + P1 + ACT(Q∑
MP) ∙ Q1
L
QD , (18)
where T1
MP is annual tariff for thermal energy from the main
producer without the operation of the DHM, $/GJ; Q∑
MPis
the total amount of thermal energy produced in the system
for a year without the operation of the DHM, GJ.
The absolute efficiency of the DHM encompasses the total
advantage to consumers resulting from the introduction of
the DHM, the cumulative profits of independent producers,
the earnings from the heat transport organization, and
compensations for losses incurred by the primary producer,
specifically when the condition U < 0 holds true. But, to
compare the success of implementing competitive condi-
tions in the DHSs of various cities, it is advisable to utilize
the relative efficiency of DHM. This relative efficiency is de-
fined as the ratio of the absolute efficiency of the market to
the total cost of thermal energy consumed over the year,
assuming a scenario where the market is not operational:
e =
QD
∙ T1
MP - ∑ TCk
G(Qk)m
k = 1 + Q1
D∙ T1
F - TC1
G(Q1) + 𝑃𝑇
T1
MP∙ QD (19)
where e is the relative efficiency of the DHM as a value that
shows the ratio of the total benefits relative to the total
cost of thermal energy in the DHS under monopoly condi-
tions, which means that an increase in benefits in the nu-
merator leads to an increase in the efficiency value.
Case study. District heating systems are vital components
of urban infrastructure, particularly in temperate climates
where seasonal heating demands are significant. This case
study examines the district heating system in Irpin city in
Ukraine, under market conditions where multiple heat pro-
ducers compete in monthly auctions to supply energy.
The assessment was conducted to evaluate the thermal en-
ergy consumption of 19 buildings within a DHS in Irpin city,
Ukraine. This study utilized the “Solvergy: Buildings” mobile
application [35, 36], which leverages machine learning and
computer vision technologies to rapidly analyze and deter-
mine the energy performance of buildings. Through AI-
based mechanisms, this mode evaluates a building's energy
class and characteristics within minutes. The objective was
to determine various characteristics like total annual heat
energy consumption, average and maximum heat energy
power consumption, and specific thermal losses and gains
through the building envelope. The calculation results were
analyzed in detail, with indicators and graphs generated for
each building. The example of building assessment process
is presented on Fig. 1.
These results provided insights into the energy perfor-
mance and highlighted areas where improvements could
be made to enhance energy efficiency. Key characteristics
of the obtained results are presented on Fig. 2.
The district heating system in Irpin city consists of three in-
tegral components: consumers, heating networks, and
producers. On the first step, it is necessary to evaluate heat
losses in the heating network during the heating period.
Fig. 1. The example of thermal energy consumption assess-
ment process for a building in “Solvergy: Buildings” mobile
application
Fig. 2. Key characteristics of the provided assessment of
the buildings in the DHS
The simulation was conducted using “Solvergy: Systems”
software [35] as a comprehensive platform for technical
and economic modeling of energy systems. This process
aimed to quantify the heat losses to understand the
amount that must be distributed between producers under
market conditions. The district heating system under study
includes 19 buildings (consumers), 130 segments of heating
networks and 4 producers of the thermal energy. The sim-
ulation project in “Solvergy: Systems” software of the DHS
in Irpin city is presented on Fig. 3.
Thus, the results of buildings assessment were imported to
the energy system simulation as a part of Solvergy software
“ecosystem”. Heat demand profiles for each of the 19
buildings were established based on historical consumption
data and weather conditions. As a result, the software per-
formed a detailed calculation of heat losses across the net-
work segments. The calculations were conducted on a tem-
poral basis (annually, monthly, daily) to capture the
dynamic nature of the heating period. The technical char-
acteristics of the system after the calculations are showed
in Table 1.
The district heating system under study operates within a
market-based framework wherein thermal energy producers
engage in monthly auctions to bid their price and quantity
for the sale of thermal energy. This energy market adheres
to a "single buyer" model, meaning that there is one central
13
Відновлювана енергетика. №4/2024 | Комплексні проблеми енергетичних систем на основі НВДЕ
entity responsible for purchasing the energy produced by all
participants. Currently, four distinct producers compete in
this market, each utilizing different energy sources and pos-
sessing unique cost structures for their operations.
Fig. 3. Developed project for energy system simulation in
“Solvergy: Systems” software
Historical weather data for Irpin was accurately integrated
to model heat demand variations over the heating period.
The main producer in this system utilizes natural gas as its
primary energy source. Historically, this entity functioned
as a monopolist before the market paradigm was estab-
lished. The environmental implications of natural gas con-
sumption, such as greenhouse gas emissions, remain signif-
icant concerns. “Independent producer 1” thermal energy
producer employs biomass in the form of wood pellets as
its energy source. Biomass is often lauded for its renewable
nature and its potential for reducing carbon emissions com-
pared to fossil fuels. Wood pellets, in particular, are a com-
pact and energy-dense form of biomass that can be easily
transported and stored. “Independent producer 2” utilizes
heat pump technology to generate thermal energy. Heat
pumps are highly efficient devices that transfer heat from
one location to another, often from the outside air, ground,
or water into buildings. “Independent producer 3” relies on
coal as its energy source. Coal has historically been a dom-
inant source of energy due to its abundance and high en-
ergy density. However, the environmental impacts of coal
have led to increased scrutiny and regulation.
In this competitive market, each producer's cost function
plays a crucial role in their bidding strategies for the
monthly auctions. As the market evolves, the interplay be-
tween these diverse energy sources and cost structures will
shape the dynamics of the DHS, influencing both economic
and environmental outcomes. The integration of RES such
as biomass and heat pumps offer a pathway toward re-
duced carbon footprints, whereas the continuing use of fos-
sil fuels like natural gas and coal underscores the challenges
of transitioning to a more sustainable energy system. The
nature of the total cost functions for each of the described
producers is presented on Fig. 4.
Table 1. The technical characteristics of DHS in Irpin city, Ukraine
Main producer, as the former monopolist, transitioning
from a dominant player to one of several competitors,
must adapt its strategies to remain viable in this newly
structured market. As the largest actor in this market, the
main producer's installed generation power is substantial,
necessitating a baseline of minimum possible thermal en-
ergy generation annually to maintain operational efficiency
and to meet market demand.
The simulation-based analysis demonstrates clear eco-
nomic benefits from implementing market conditions in
DHSs. The optimal distribution of thermal energy produc-
tion among various producers and the resulting lower
weighted average price underscore the potential for cost
savings and efficiency gains. The model also highlights the
importance of equitable loss allocation and the necessity
for compensatory mechanisms for key producers. The op-
timization results of the DHS under market conditions are
presented in Table 2.
Fig. 4. Total cost function for each thermal energy producer
These results suggest a significant role for independent
producers in meeting the overall thermal energy demand,
highlighting the efficiency of a diversified supply structure.
Name Total annual
heat energy
consumption
Total annual
heat losses in
networks
Average
thermal
energy power
consumption
Maximum
thermal
energy power
consumption
Electricity
consumption
for heat
transmission
Network
length
Unit GJ GJ MW MW kWh km
Value 63617.05 3034.7 4.05 5.78 45959.27 6.42
14
Відновлювана енергетика. №4/2024 | Комплексні проблеми енергетичних систем на основі НВДЕ
The optimal weighted price of thermal energy is signifi-
cantly lower than the main producer's price, demonstrat-
ing the potential cost savings from implementing market
conditions. At the same time, weighting factors reflect the
relative importance of each criterion in the overall optimi-
zation process, indicating that distance to the centroid is
the most significant factor in current DHS.
The economic benefits for market participants in DHM sim-
ulation are presented in Table 3.
Table 3. The economic benefits for market participants
Parameter Unit Value
Market share (MS) % 30
Main producer loss (U) $ 0
Consumers benefit (V) $ 651120
Producers Benefit (P) $ 75000
Transportation Benefit (H) $ 1000
Absolute market efficiency (E) $ 727120
Relative market efficiency (e) % 28.05
The simulation results indicate a considerable benefit to
consumers from the introduction of market conditions,
quantified at $651,120. Producers also realize a significant
benefit of $75,000, while the transportation organization
sees a modest gain of $1,000. The relative market effi-
ciency of 0.2805 suggests that the market delivers 28.05%
of the potential economic value relative to a scenario with-
out market conditions.
Conclusions
The shift to market dynamics in DHSs is a strategic move
aimed at optimizing system efficiency. Market liberaliza-
tion introduces competitive pressures that can lower con-
sumer prices, increase service quality, and drive technolog-
ical innovation.
Policymakers should prioritize creating a supportive regu-
latory environment that encourages competition, protects
consumers, and incentivizes the adoption of RES. Consider-
ation of local conditions and unique characteristics of each
DHS is crucial for the successful implementation and opti-
mization of market-based heating systems.
The diversification of energy sources, as evidenced by the
integration of biomass, heat pumps, and RES, can signifi-
cantly bolster system efficiency and sustainability. This
integration reduces dependency on fossil fuels, mitigating
carbon emissions and advancing environmental objectives.
Methodological principles for determining and optimizing
the weighted average price for thermal energy, as well as
the efficiency of DHM, are proposed in the context of inde-
pendent thermal energy producers competing within the
system. This framework enables the modeling of DHSs
from a market perspective, supporting strategic planning
and decision-making for the implementation of such pro-
jects in real DHSs.
The case study of Irpin city, Ukraine, demonstrates the
practical application of the developed methodological prin-
ciples. The introduction of competitive market conditions
in Irpin's DHS led to significant economic benefits for con-
sumers, producers, and the transport organization, high-
lighting the potential gains from market liberalization.
REFERENCES
1. S. Bogut, D. White. White paper on transforming district
heating in Ukraine: Assessment and recommendations,
USAID, 2020. https://energysecurityua.org/wp-con-
tent/uploads/2021/04/050G-DH_White-Pa-
per_for_DEC-2021-02-02-ENG.pdf
2. Tuchynskyi, B., Kudria, S., Ivanchenko, I., Ivanchuk, V.
Inevitability of Ukraine’s transition to renewable en-
ergy. Vidnovluvana Energetika. 2020. (4(63), 6-21.
https://doi.org/10.36296/1819-8058.2020.4(63).6-21
3. A. Zaporozhets, V. Babak, A. Sverdlova, L. Scherbak, Y.
Kuts. Review of the state of air pollution by energy ob-
jects in Ukraine. System Research in Energy, 2022. Vol.
71, pp. 42-52. https://doi.org/10.15407/sren-
ergy2022.02.042
4. K. Engelmann, M. Čavar, J. Buganova, S. Martinkrista, J.
Čižman, M. Mladenović, K. Tomliak, M. Shlapak. Im-
proving the performance of District Heating Systems in
Central and Eastern Europe. 2020. https://keep-
warmeurope.eu/fileadmin/user_upload/Re-
sources/Deliverables/KeepWarm_D5.2_Develop-
ment_of_Multi-level_policy_Plans.pdf
5. A. Faria, T. Soares, J. M. Cunha, Z. Mourão. Liberalized
market designs for district heating networks under the
Table 2. The optimization results of the distribution of thermal energy production and prices of thermal energy
among the main and independent producers
Producer
Optimal
Qk, GJ
Optimal weighting factors
Monopoly price,
$/GJ
Optimal
weighted price,
$/GJ ωφ ωα ωβ
Main producer 16977
0.5 0.2 0.3
39.22
28.99
Independent producer 1 19996 -
Independent producer 2 19996 -
Independent producer 3 6649 -
15
Відновлювана енергетика. №4/2024 | Комплексні проблеми енергетичних систем на основі НВДЕ
EMB3Rs platform. Sustainable Energy, Grids and Net-
works. 2022. Vol. 29. https://doi.org/10.1016/j.se-
gan.2021.100588
6. A. Faria, T. Soares, J. M. Cunha, Z. Mourão. Mutual-ben-
efit of district heating market and network operation
for prosumers integration. Energy Sources, Part B: Eco-
nomics, Planning, and Policy. 2023. Vol. 18.
https://doi.org/10.1080/15567249.2023.2280568
7. B. Doračić, M. Pavičević, T. Pukšec, N. Duić. Bidding
strategies for excess heat producers participating in a
local wholesale heat market. Energy Reports. 2022. Vol.
8, pp. 3692-3703.
https://doi.org/10.1016/j.egyr.2022.02.307
8. I. Blanco, D. Guericke, A. N. Andersen, H. Madsen. Op-
erational Planning and Bidding for District Heating Sys-
tems with Uncertain Renewable Energy Production. En-
ergies. 2018. Vol. 12, p. 3310.
https://doi.org/10.3390/en11123310
9. A. Pažėraitė, V. Lekavičius, R. Gatautis. District heating
system as the infrastructure for competition among
producers in the heat market. Renewable and Sustain-
able Energy Reviews. 2022. Vol. 169.
https://doi.org/10.1016/j.rser.2022.112888
10. S. Djørup, K. Sperling, S. Nielsen, P. Østergaard, T. J.
Zinck, P. Sorknæs, H. Lund, D. Drysdale. District Heating
Tariffs, Economic Optimisation and Local Strategies
during Radical Technological Change. Energies. 2020.
Vol. 13, p. 1172. https://doi.org/10.3390/en13051172
11. D. Korsakaite, D. Bieksa, E. Bieksiene. Third-party access
in district heating: Lithuanian case analysis. Competi-
tion and Regulation in Network Industries. 2018. Vol.
19, pp. 218-241.
https://doi.org/10.1177/1783591719837410
12. V. Bürger, J. Steinbach, L. Kranzl, A. Müller. Third party
access to district heating systems - Challenges for the
practical implementation. Energy Policy. 2019, Vol.
132, pp. 881-892. https://doi.org/10.1016/j.en-
pol.2019.06.050
13. K. Bauermann. German Energiewende and the heating
market – Impact and limits of policy. Energy Policy.
2016. Vol. 94, pp. 235-246.
https://doi.org/10.1016/j.enpol.2016.03.041
14. D. Magnusson, J. Palm. Between natural monopoly
and third party access - Swedish district heating mar-
ket in transition. Monopolies: Theory, Effectiveness
and Regulation. 2011. pp. 1-33. https://www.re-
searchgate.net/publication/285726324_Between_nat-
ural_monopoly_and_third_party_access_-_Swe-
dish_district_heating_market_in_transition
15. H. Dorotić, T. Puksec, N. Duic. Economical, environmen-
tal and exergetic multi-objective optimization of district
heating systems on hourly level for a whole year. Ap-
plied Energy. 2019. Vol. 251.
https://doi.org/10.1016/j.apenergy.2019.113394
16. L. Frölke. Market Design for Future District Heating Sys-
tems. DTU Wind and Energy Systems. 2023.
https://doi.org/10.11581/dtu.00000253
17. J. v. Woerden. A conceptual model to grasp the district
heating market. 2015. https://www.seman-
ticscholar.org/paper/A-conceptual-model-to-grasp-
the-district-heating-A-Woerden
18. C. H. Hansen, O. Gudmundsson. The competitiveness of
district heating compared to individual heating. Green
Energy Association. 2018. https://danskfjern-
varme.dk/media/zulfbv0j/the-competitiveness-of-dis-
trict-heating-compared-to-individual-heating.pdf
19. Kovalko О. M., Kovalko N. M., Yevtukhova T.O., Novo-
seltsev O.V. Communal heat and power engineering:
energy efficiency, management structure, energy ser-
vice services. Kyiv: NAS of Ukraine, In-stitute of General
Energy. 2023. URL: https://web.nlu.org.ua/ob-
ject.html?id=2196
20. P. Söderholm, L. Wårell. Market opening and third party
access in district heating networks. Energy Policy. 2011.
Vol. 39, pp. 742-752. https://doi.org/10.1016/j.en-
pol.2010.10.048
21. E. Landelius, M. Astrom. District heat price model anal-
ysis, Malardalen University Sweden, 2019.
https://www.divapor-
tal.org/smash/get/diva2:1325101/FULLTEXT01.pdf
22. U. Persson, S. Werner. Heat distribution and the future
competitiveness of district heating. Applied Energy.
2011. Vol. 88, pp. 568-576.
https://doi.org/10.1016/j.apenergy.2010.09.020
23. M. Schindler, L. Gnam, M. Puchegger, K. Medwenitsch,
P. Jasek. Optimization-Based Operation of District Heat-
ing Networks: A Case Study for Two Real Sites. Energies.
2023. Vol. 16, № 2120. Pp. 1-15.
https://doi.org/10.3390/en16052120
24. V. P. Babak, M. M. Kulyk. Increasing the efficiency and
security of integrated power system op-eration through
heat supply electrification in Ukraine. Science and Inno-
vation. 2023. Vol. 19, № 5, Pp. 100-116.
https://doi.org/10.15407/scine19.05.100
25. Derii, V., Teslenko, O., Lenchevsky, E., Denisov, V.,
Maistrenko, N. Prospects and Energy-Economic Indica-
tors of Thermal energy Production Through Direct Use
of Electricity from Renewable Sources in Modern Heat
Generators. In: Zaporozhets, A. (eds) Systems, Decision
and Control in Energy IV. Studies in Systems, Decision
and Control. 2023.Vol. 454. Springer, Cham.
https://doi.org/10.1007/978-3-031-22464-5_27
26. Leshchenko I., Shulzhenko S., Kaplin M., Maistrenko N.,
Shcherbina Ye. Assessment of the greenhouse gases re-
duction by the oil and gas sector of Ukraine to meet in-
ternational climate agreements. In: Zaporozhets A., Po-
pov O. (eds) Systems, Decision and Control in Energy IV.
Studies in Systems, Decision and Control, Springer,
16
Відновлювана енергетика. №4/2024 | Комплексні проблеми енергетичних систем на основі НВДЕ
Cham. 2023. – vol 456. – Р. 199-212.
https://doi.org/10.1007/978-3-031-22500-0_13
27. V. Deshko, D. Karpenko. Analysis of conditions for the
creation of the local thermal energy mar-ket in Ukraine.
Municipal Economy of Cities. 2018. 7(146). pp. 68–76.
https://doi.org/ 10.33042/2522-1809-2018-7-146-68-76
28. V. Deshko, D. Karpenko. Analysis of aspects and simula-
tion modeling of the thermal energy mar-ket in
Ukraine. Management of technological processes in en-
ergy technologies under the general editor-ship of An-
atoliy M. Pavelko. 2019. Kielce, Politechnika Swie-
tokrzyska, 7-4. http://bc.tu.kielce.pl/366/1/M-120.pdf
29. V. Deshko, D. Karpenko. Functional Structure of the Lo-
cal Thermal Energy Market in District Heat-ing. 2019
IEEE 6th International Conference on Energy Smart Sys-
tems (ESS). 2019. Kyiv, Ukraine, pp. 343-346.
https://doi.org/10.1109/ESS.2019.8764211
30. A. Mahnitko, Y. Veremiichuk, V. Deshko, D. Karpenko.
Scenario Analysis for Increasing Efficiency Level of the
Autonomous Generation Object in Central Heat Supply.
2019 IEEE 60th International Scientific Conference on
Power and Electrical Engineering of Riga Tech-nical Uni-
versity (RTUCON), Riga, Latvia. 2019. pp. 1-7.
https://doi.org/10.1109/RTUCON48111.2019.8982299
31. M. K. Oleksandra Hotra, V. Babak, S. Kovtun, O. Zgurovets,
J. Mroczka, P. Kisała. Organisation of the Structure and
Functioning of Self-Sufficient Distributed Power Genera-
tion. Energies. 2024. Vol. 27.
https://doi.org/10.3390/en17010027
32. Khilko, V. Measures to support renewable energy in
Ukraine. Vidnovluvana Energetika. 2021. (3(66), 6-17.
https://doi.org/10.36296/1819-8058.2021.3(66).6-17
33. Kuznietsov, M. Complex use of renewable energy sour-
ces – results of the scientific and practical conference
2023. Vidnovluvana Energetika. 2023. (2(73), 6-10.
https://doi.org/10.36296/1819-8058.2023.2(73).6-10
34. D. S. Karpenko, T. O. Yevtukhova, O. V. Novoseltsev, O.
I. Teslenko. Market features of heat pro-ducers contri-
bution to losses in district heating system networks. Sci-
entific notes of Taurida National V.I. Vernadsky Univer-
sity. Series: Technical Sciences. 2024. Vol. 35 (3).
https://doi.org/10.32782/2663-5941/2024.3.1/37
35. Innovative Tools for Energy Efficiency Assessment.
Solvergy. (n.d.). https://solvergy.org/
36. P. A. Østergaard, A. N. Andersen, P. Sorknæs. The busi-
ness-economic energy system modelling tool ener-
gyPRO. Energy. 2022. Vol. 257.
https://doi.org/10.1016/j.energy.2022.124792
|
| id | veorgua-article-482 |
| institution | Vidnovluvana energetika |
| keywords_txt_mv | keywords |
| language | English |
| last_indexed | 2026-07-19T01:14:16Z |
| publishDate | 2024 |
| publisher | Institute of Renewable Energy National Academy of Sciences of Ukraine |
| record_format | ojs |
| resource_txt_mv | veorgua/f6/c51eebf5ced29e3ca9e922cecd5c65f6.pdf |
| spelling | veorgua-article-4822026-07-18T06:32:20Z METHOD FOR ASSESSING THE EFFICIENCY OF THE DISTRICT HEATING SYSTEM UNDER MARKET CONDITIONS МЕТОД ОЦІНЮВАННЯ ЕФЕКТИВНОСТІ СИСТЕМ ЦЕНТРАЛІЗОВАНОГО ТЕПЛОПОСТАЧАННЯ В УМОВАХ КОНКУРЕНЦІЇ Karpenko, D. Yevtukhova , T. Novoseltsev , O. district heating system, district heating market, thermal energy loss, renewable energy sources, competitive bidding and auctions, multifactor optimization. система централізованого теплопостачання, ринок централізованого теплопостачання, втрати теплової енергії, відновлювані джерела енергії, конкурентні торги та аукціони, багато-факторна оптимізація. In response to global warming and the critical need for sustainable energy solutions, district heating systems (DHS) have emerged as an area of significant focus due to their potential to enhance resource efficiency, reduce carbon emissions, and improve economic outputs. This research addresses the critical issue of establishing a methodological framework for evaluating the efficiency of DHS as market relations evolve within the heating sector. The study's aim is to develop and validate methodological principles that assess the operational, economic, and technological dimensions of DHS in a competitive market landscape. The framework encompasses the complex interplay of regulatory frameworks, market dynamics, production technologies, and consumer engagement strategies. Key objectives include analyzing current challenges in implementing competitive market structures, justifying the non-linear nature of cost functions for energy producers, and developing criteria for the equitable distribution of thermal energy losses. The overarching goal is to strategically propel DHS towards greater efficiency and sustainability by using renewable energy sources (RES). The research utilizes simulation modeling in a case study of Irpin city, Ukraine, employing machine learning and computer vision technologies through the "Solvergy: Buildings" mobile application to provide rapid, detailed energy performance assessments. Results from the simulation in "Solvergy: Systems" software indicate benefits from the market conditions functioning in DHS, quantified at $727,120 per year, and highlight the cost-saving potential of the RES-based supply diversification structure. The relative market efficiency at 28.05% suggests that the market delivers high potential economic value relative to a scenario without market conditions. The study concludes that transitioning to market relations and integrating independent energy producers can lead to substantial system efficiency improvements, lower thermal energy prices, and enhanced sustainability in DHS. Suggested policy measures advocate for the modernizing of infrastructure and the implementation of efficient technologies within a competitive, consumer-oriented market environment, thereby facilitating the decarbonization process and optimizing system performance. З огляду на глобальне потепління та критичну потребу в стійких енергетичних рішеннях системам централізованого теплопостачання приділяють особливу увагу через їхній потенціал до підвищення ефективності використання ресурсів, скорочення викидів вуглецю та покращення економічних результатів. У цьому дослідженні розглядається важливе питання створення методологічної основи для оцінювання ефективності систем централізованого теплопостачання (СЦТ), оскільки ринкові відносини розвиваються в секторі теплопостачання. Метою дослідження є розробка та перевірка методологічних принципів, які оцінюють операційні, економічні та технологічні аспекти СЦТ у конкурентному ринковому ландшафті. Структура охоплює складну взаємодію нормативно-правової бази, динаміки ринку, технологій виробництва та стратегій залучення споживачів. Серед основних цілей ‒ аналіз поточних викликів у впровадженні конкурентних ринкових структур, обґрунтування нелінійного характеру функцій витрат для виробників енергії та розробка критеріїв для справедливого розподілу втрат теплової енергії. Основна мета полягає в тому, щоб стратегічно підштовхнути СЦТ до підвищення ефективності та стійкості за рахунок використання відновлюваних джерел енергії (ВДЕ). У дослідженні використовується імітаційне моделювання в прикладі міста Ірпінь, Україна, з використанням технологій машинного навчання та комп’ютерного бачення через мобільний застосунок «Solvergy: Buildings» для надання швидких детальних оцінок енергоефективності. Результати моделювання в програмному забезпеченні "Solvergy: Systems" вказують на переваги функціонування СЦТ у ринкових умовах, які кількісно оцінені в 727 120 доларів США за рік, і підкреслюють потенціал економії витрат структури диверсифікації постачання на основі ВДЕ. Відносна ефективність ринку на рівні 28,05 % свідчить про те, що ринок забезпечує високий економічний потенціал порівняно зі сценарієм без ринкових умов. У дослідженні зроблено висновок, що перехід до ринкових відносин та інтеграція незалежних виробників енергії сприятиме істотному підвищенню ефективності системи, зниженню цін на теплову енергію та підвищенню стійкості в СЦТ. Запропоновані політичні заходи спрямовані на модернізацію інфраструктури та впровадження ефективних технологій у конкурентному, орієнтованому на споживача ринковому середовищі, тим самим полегшуючи процес декарбонізації та оптимізуючи продуктивність системи. Institute of Renewable Energy National Academy of Sciences of Ukraine 2024-12-10 Article Article application/pdf https://ve.org.ua/index.php/journal/article/view/482 10.36296/1819-8058.2024.4(79).6-16 Vidnovluvana energetika ; No. 4(79) (2024): Scientific and applied Journal renewable energy ; 6-16 Возобновляемая энергетика; ##issue.no## 4(79) (2024): Scientific and applied Journal renewable energy ; 6-16 Відновлювана енергетика; № 4(79) (2024): Науково-прикладний журнал Відновлювана енергетика; 6-16 2664-8172 1819-8058 10.36296/1819-8058.2024.4(79) en https://ve.org.ua/index.php/journal/article/view/482/391 Copyright (c) 2024 D. Karpenko, T. Yevtukhova , O. Novoseltsev https://creativecommons.org/licenses/by-nc-nd/4.0 |
| spellingShingle | district heating system district heating market thermal energy loss renewable energy sources competitive bidding and auctions multifactor optimization. Karpenko, D. Yevtukhova , T. Novoseltsev , O. METHOD FOR ASSESSING THE EFFICIENCY OF THE DISTRICT HEATING SYSTEM UNDER MARKET CONDITIONS |
| title | METHOD FOR ASSESSING THE EFFICIENCY OF THE DISTRICT HEATING SYSTEM UNDER MARKET CONDITIONS |
| title_alt | МЕТОД ОЦІНЮВАННЯ ЕФЕКТИВНОСТІ СИСТЕМ ЦЕНТРАЛІЗОВАНОГО ТЕПЛОПОСТАЧАННЯ В УМОВАХ КОНКУРЕНЦІЇ |
| title_full | METHOD FOR ASSESSING THE EFFICIENCY OF THE DISTRICT HEATING SYSTEM UNDER MARKET CONDITIONS |
| title_fullStr | METHOD FOR ASSESSING THE EFFICIENCY OF THE DISTRICT HEATING SYSTEM UNDER MARKET CONDITIONS |
| title_full_unstemmed | METHOD FOR ASSESSING THE EFFICIENCY OF THE DISTRICT HEATING SYSTEM UNDER MARKET CONDITIONS |
| title_short | METHOD FOR ASSESSING THE EFFICIENCY OF THE DISTRICT HEATING SYSTEM UNDER MARKET CONDITIONS |
| title_sort | method for assessing the efficiency of the district heating system under market conditions |
| topic | district heating system district heating market thermal energy loss renewable energy sources competitive bidding and auctions multifactor optimization. |
| topic_facet | district heating system district heating market thermal energy loss renewable energy sources competitive bidding and auctions multifactor optimization. система централізованого теплопостачання ринок централізованого теплопостачання втрати теплової енергії відновлювані джерела енергії конкурентні торги та аукціони багато-факторна оптимізація. |
| url | https://ve.org.ua/index.php/journal/article/view/482 |
| work_keys_str_mv | AT karpenkod methodforassessingtheefficiencyofthedistrictheatingsystemundermarketconditions AT yevtukhovat methodforassessingtheefficiencyofthedistrictheatingsystemundermarketconditions AT novoseltsevo methodforassessingtheefficiencyofthedistrictheatingsystemundermarketconditions AT karpenkod metodocínûvannâefektivnostísistemcentralízovanogoteplopostačannâvumovahkonkurencíí AT yevtukhovat metodocínûvannâefektivnostísistemcentralízovanogoteplopostačannâvumovahkonkurencíí AT novoseltsevo metodocínûvannâefektivnostísistemcentralízovanogoteplopostačannâvumovahkonkurencíí |