Sustainable Energy Investments: ESG-Centric Evaluation and Planning of Energy Projects

Abstract

The integration of Environmental, Social, and Governance (ESG) criteria in investment decision-making is increasingly critical for evaluating energy projects. This study develops a structured, quantifiable framework using the Fuzzy DEMATEL method to assess and rank ESG factors, addressing the limitations of traditional scoring-based models. The proposed methodology systematically identifies the most influential ESG criteria and accounts for their interdependencies, providing a more comprehensive decision-making tool. The analysis, based on expert evaluations, highlights the dominant role of renewable energy integration, resource efficiency, and risk management in determining project sustainability. The results demonstrate that the framework ensures a more transparent and adaptable assessment process, supporting both investors and policymakers in navigating complex energy investment landscapes. The study also establishes a scalable approach that can incorporate financial performance indicators, enhancing the practical applicability of ESG-based investment evaluation.

1. Introduction

The increasing importance of ESG criteria in investment decision-making has reshaped how energy projects are planned and evaluated. With growing pressure from regulatory bodies, financial institutions, and society, ESG compliance has become a strategic priority for governments and investors. This is particularly relevant in the energy sector, where environmental impacts, social responsibility, and corporate transparency are tightly linked to long-term sustainability. A structured ESG-based evaluation of energy investments is now essential to ensure alignment with both national recovery needs and international sustainability commitments.

This issue is especially critical for countries with transitioning and post-conflict economies, such as Ukraine. The destruction of Ukraine’s energy infrastructure caused by the Russian invasion presents both a significant challenge and an opportunity to rebuild the sector according to sustainability principles. However, rebuilding in line with ESG objectives requires decision-making tools that are both transparent and adaptable to complex economic and policy environments. In this context, investors and policymakers must be equipped with clear, measurable, and scalable methodologies to assess energy projects through the ESG lens.

There were numerous attempts to create a system for evaluation and ranking of energy projects based on different criteria. The increasing importance of the ESG principles for investment led to the usage of sustainability and renewability as base factors. For example, Büyüközkan and Karabulut [1] pointed out that economic feasibility is not a viable criterion to evaluate energy projects and that it is necessary to consider environmental and social aspects. They used a method based on two multi-criteria decision-making techniques such as AHP to determine the importance weights of evaluation criteria and VIKOR to rank energy project alternatives. Manzini, Islas, and Macías [2] offered a model based on various indicators to evaluate the environmental sustainability of energy projects. They proposed the index of environmental sustainability of energy projects (IESEP) to measure the effectiveness of the proposed alternatives. Thórhallsdóttir [3] proposed the evaluation and ranking of energy projects based on their impact on the natural environment. The procedure involved three steps: assess site values, conduct a multi-criteria analysis of development impacts, and rank the alternatives from worst to best choice based on determined environmental criteria. Ramezanzade et al. [4] proposed that to satisfy the modern requirements for energy, the best renewable energy projects should be selected using a hybrid decision-making framework, taking into account environmental, economic, technical, and social aspects. The authors used 30 sub criteria to rank the projects. Yazdani-Chamzini et al. [5] concentrated on renewable energy projects and incorporated social, economic, technological, and environmental factors for their ranking using five different multi-criteria decision making (MCDM) methods. All the researchers pointed out that economic feasibility is not enough to evaluate and rank energy projects anymore. Even if some project evaluations include environment and social criteria, this is usually limited to certain types of energy projects, and they are locally tested. There is no universal model to assess and rank all types of energy projects.

Although ESG principles are widely promoted, the current frameworks for applying them remain fragmented, overlapping, and sectorally inconsistent. There is no universal or standardized model for ESG assessment that can be applied consistently across different types of projects or geographies. Various international financial institutions, national governments, and private sector actors propose differing sets of ESG requirements, often without a clear hierarchy, structure, or sectoral specificity. As identified in our literature review, most existing evaluation approaches rely on simple scoring systems that treat ESG indicators independently, without capturing the complex interrelationships among them. Moreover, there are a lack of methodologies that transform ESG factors into quantifiable metrics usable for actual project selection and prioritization.

The aim of this article is to develop a comprehensive framework for evaluating and ranking energy sector investment projects using ESG criteria. The framework is intended to assist stakeholders in making informed investment decisions that align with both global sustainability goals and the unique challenges of Ukraine’s post-war energy sector reconstruction. The main objectives of the research are:

• to define and structure the relevant ESG criteria applicable to energy sector projects, especially those in countries facing economic and infrastructural challenges like Ukraine;
• to create a scalable and practical model that ranks energy projects based on their adherence to ESG standards and potential for contributing to long-term sustainability and energy transition;
• to adapt the framework to address the specific needs and constraints of Ukraine’s energy sector, considering the damage caused by the war and the country’s goals for rebuilding in line with global climate and sustainability goals.

This study contributes to the literature by offering a novel approach that transforms qualitative ESG considerations into a quantifiable, decision-oriented model tailored to the energy sector. It fills a gap in current ESG assessment practice by combining regulatory compliance, best practices from international financial institutions, and national strategy into a comprehensive evaluation framework. The model also supports long-term planning for sustainable energy recovery, especially relevant for countries undergoing structural energy transformation, such as Ukraine.

2. Literature Review

To begin the literature review on the chosen topic, it is essential to reference research [6] that outlines the evolution of ESG criteria from a narrow concept to a key factor in global investment and corporate strategies. Initially rooted in the Socially Responsible Investing (SRI) movements of the 1960s and 1970s, the importance of ESG has grown significantly due to increasing concerns about climate change, corporate governance, and social responsibility. This transition underscores how ESG metrics have become vital tools for assessing both the financial and ethical performance of companies, enabling investors to evaluate risks and returns in a more comprehensive manner.

The analysis in [7] distinguishes ESG from SRI, emphasizing that while both focus on ethical investments, ESG integrates broader governance frameworks and risk management principles. The growing consensus is that ESG is not only about environmental impact but also about sustainable corporate governance and social responsibility. Despite not having an official definition under EU regulations [6], ESG is widely embraced by companies, investors, and policymakers as a key factor in sustainability-related decisions. The development of ESG is marked by its integration into financial, legal, and governance structures, making it a critical consideration for future investments and policy formulation.

In the context of this topic, it is important to mention the increasing central role of ESG in energy projects evaluation. The rising importance of ESG criteria is reshaping decision-making in the energy sector, particularly as companies transition to renewable energy sources. ESG has moved from a peripheral consideration to a central strategy for energy firms, driven by growing consumer awareness, investor expectations, and regulatory requirements. Companies are now evaluated not only on their financial outcomes but also on how well they manage environmental impacts, social responsibilities, and corporate governance. Firms that adopt strong ESG strategies can gain competitive advantages, including stakeholder trust and long-term viability. In particular, the implementation of ESG practices in the energy sector helps companies meet the growing demand for cleaner energy solutions and align with global sustainability goals. As businesses in this sector continue to adapt, the importance of ESG in guiding investment and operational decisions is expected to intensify [8].

In their 2019 study, In, Rook, and Monk [9] explored the growing integration of ESG data into investment strategies. They highlighted that the increasing importance of ESG is largely driven by advancements in data technologies, which have made ESG data more accessible and transparent. However, they also acknowledge significant challenges in the quality and reliability of ESG data due to the lack of standardized frameworks and theoretical approaches. Despite these hurdles, the authors argue that high-quality ESG data is essential for aligning investments with sustainability goals, improving risk management, and enhancing financial performance. To address these issues, they propose a user-centered approach for evaluating ESG data, which could help improve its efficacy in decision-making processes.

The second key aspect to emphasize in this research is that the ESG concept is primarily driven by industry and the real sector of the economy, with governments acting as followers by introducing relevant regulations specific to each industry to support and stimulate sustainable development. However, this creates a degree of uncertainty in the overall structure of current ESG regulations, highlighting the need for a systematic approach. Such an approach would help guide investors and market participants, ensuring their efforts are strategically aligned to maximize the efficiency of innovative growth and development.

In their 2023 article, Vorontsova, Agafonova, and Bilan [10] explored global efforts to harmonize ESG investment regulations, focusing on the tension between fragmentation and unification in different regions. While the European Union leads with comprehensive ESG frameworks like the Sustainability Taxonomy and the Sustainable Finance Disclosure Regulation (SFDR), other regions, such as the United States and Asia-Pacific, follow their own distinct paths, leading to regulatory fragmentation. The authors emphasize the EU’s leadership in setting global ESG standards but acknowledge the barriers posed by political, economic, and cultural differences that make full regulatory coordination difficult. Despite these challenges, the article notes increasing efforts towards harmonization, with initiatives like the Global Reporting Initiative (GRI) and the International Sustainability Standards Board (ISSB) moving towards greater alignment. This indicates a growing trend toward more unified global ESG regulations in response to the increasing importance of ESG considerations in international investment and governance.

Another important topic to highlight is partially investigated in the article by Dyba and Gernego (2022) [11], which focuses on how major international financial institutions (IFI) like JPMorgan Chase, Citigroup, and Goldman Sachs are increasingly integrating ESG criteria into their investment policies. The central idea is that these institutions are shifting their investment strategies to align with sustainable development goals and socially responsible investment. By adopting ESG practices, these IFIs are not only maintaining their market competitiveness but also playing a pivotal role in promoting sustainability. The article emphasizes that these institutions have developed frameworks to assess and finance projects that contribute to environmental protection, social welfare, and transparent governance. For example, JPMorgan Chase supports ESG projects by prioritizing environmental protection and social impact in its financing decisions. The European Investment Bank has also developed a comprehensive ESG investment strategy as part of its broader commitment to sustainability and climate action, which focuses only on ESG-compliant projects [12].

It is also crucial to understand that the role of ESG is growing and this trend should be taken into account in each evaluation model. The article by Li, Wang, Sueyoshi, and Wang (2021) provides a detailed analysis of the evolution and future prospects of ESG principles. It highlights the increasing global significance of ESG in promoting sustainable development and addressing environmental and societal concerns. The study reviews the progress made in ESG research since its inception in 2004, discussing key areas such as ESG’s role in risk prevention, corporate governance, and economic consequences. The authors emphasize that the importance of ESG will continue to grow, driven by the need for coordinated global efforts in sustainability and the increasing integration of ESG principles into business and investment strategies [13].

The study in [14] analyzes ESG performance across energy sub-sectors, examining the interrelationships between these factors and their impact on corporate sustainability. Using data from 576 companies, the research reveals significant variations in ESG scores among sub-sectors and highlights the need for stronger governance frameworks to better integrate with environmental and social practices.

The conclusion drawn from the literature emphasizes that ESG principles are becoming increasingly important in investment strategies across various sectors, particularly energy. This growing trend is driven by the global need for coordinated sustainability efforts and the integration of ESG into corporate governance, risk management, and investment decision-making. The importance of ESG will continue to expand as more companies and investors recognize its critical role in promoting sustainable development, mitigating risks, and aligning business strategies with ethical and environmental responsibilities. This underscores the necessity of incorporating ESG factors into any evaluation model for long-term financial and societal impact. The need for a more structured and systematized approach is further supported by Vorontsova et al. (2023), who emphasized that despite the widespread adoption of ESG principles, the global regulatory landscape remains fragmented and inconsistent, complicating practical implementation and comparison [10].

While existing research on ESG-based energy investment assessment provides valuable insights, most models rely on rigid scoring frameworks or weighted aggregations that do not account for the interdependencies among ESG criteria. This reflects a broader gap in current practice, where ESG integration often lacks methodological depth. This observation is further reinforced by Lange and Banadaki (2023), who highlight the lack of standardized quantitative tools across investment decision-making [15]. Their findings support the argument that a more robust, quantifiable approach to ESG is needed to ensure consistent application across sectors and contexts. This study addresses this limitation by applying the Fuzzy DEMATEL method, which enables a structured cause-effect analysis to identify the most influential ESG factors in investment decision-making. Unlike existing qualitative ESG assessments, our approach introduces a scalable, data-driven methodology that not only evaluates ESG criteria but also allows for the inclusion of traditional financial project metrics. By integrating expert-based fuzzy evaluations with a systematic ranking mechanism, the proposed framework enhances decision-making transparency, adaptability, and applicability for both energy policymakers and investors in complex energy investment environments.

3. Methods

The methodology employed in this study aims to develop a comprehensive model for evaluating energy sector investment projects through the lens of ESG criteria. The framework incorporates multicriteria analysis methods to assess the sustainability and long-term value of energy projects. This section outlines the steps involved in the research, data collection, and the criteria selection process.

Systematization of ESG Framework: A critical step in developing the evaluation model involves systematizing the ESG framework for energy projects. This includes organizing and categorizing the various ESG criteria according to the specific requirements of the energy sector. The systematization process incorporates a review of existing frameworks, including those from international financial institutions and regulatory bodies. The framework is tailored specifically for energy projects, focusing on aspects like emissions reduction, renewable energy integration, community impact, and corporate governance in energy production and distribution.

Investment Policy Analysis: The study also involves a systematic analysis of investment policies related to ESG compliance in the energy sector. This analysis reviews policies from key financial institutions (e.g., European Investment Bank, World Bank) and identifies how these institutions incorporate ESG criteria into their funding decisions for energy projects. This policy analysis serves to identify trends and align the model with investment standards.

4. Results

4.1. ESG Criteria in the Context of IFI’s Investment Strategy

To develop a robust and adaptable framework for evaluating energy projects based on ESG criteria, this study employs a Multi-criteria Analysis (MCA) approach. MCA is well-suited to decision-making environments that involve multiple conflicting objectives and require both qualitative and quantitative inputs. ESG assessment, by nature, involves such trade-offs, with criteria ranging from environmental impact and financial resilience to social inclusion and governance transparency.

Among the various MCA methods available, including AHP (Analytic Hierarchy Process), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and ELECTRE, each has specific strengths but also key limitations in the context of ESG analysis. AHP, for instance, is widely used for prioritizing criteria, but assumes independence between them and relies on pairwise comparisons that may become inconsistent with a large number of variables. TOPSIS identifies ideal and negative-ideal solutions, but does not account for the causal relationships between ESG factors. ELECTRE is effective in ranking alternatives, but can be difficult to interpret and sensitive to threshold settings.

In contrast, this study applies the Fuzzy DEMATEL method, which combines the following advantages:

• It allows for the mapping of interdependencies and causal relationships between criteria (e.g., how governance factors influence environmental or social outcomes), which is not possible in additive models like AHP or TOPSIS.
• By incorporating fuzzy logic, the method captures uncertainty and vagueness in expert judgment, which is highly relevant when assessing ESG criteria that are often qualitative or context-dependent.
• It enables experts to express their views in linguistic terms (“low influence”, “high influence”, etc.), which are then transformed into triangular fuzzy numbers, ensuring a more realistic representation of subjective assessments.

These characteristics make Fuzzy DEMATEL particularly suitable for analyzing ESG systems, where indicators often overlap, interact dynamically, and lack universally agreed-upon measurement standards. Additionally, the method’s output provides not just rankings but a cause-effect diagram, which helps policymakers and investors identify which ESG criteria act as key drivers and which are more dependent, improving strategic planning and prioritization.

Beyond its technical suitability, the methodology is scalable and adaptable. While this study focuses on Ukraine’s energy sector, the structure of the model allows for the integration of new criteria or adaptation to other national contexts by updating the criteria set and reapplying the evaluation procedure. Moreover, while the current model focuses on ESG dimensions, financial and technical performance indicators can be integrated into future versions to support comprehensive investment analysis.

In summary, the Fuzzy DEMATEL approach was chosen over other MCA methods due to its ability to handle complex interrelationships, accommodate expert uncertainty, and provide transparent, actionable insights for ESG-based project evaluation.

We begin the research by analyzing the investment policies of International Financial Institutions (IFIs) because these institutions play a pivotal role in shaping global investment trends, especially in sectors like energy. The recent developments in their investment policies, particularly the integration of ESG criteria, are of significant interest as they align financing decisions with global sustainability goals. This shift in focus highlights the growing emphasis on not just financial returns, but also long-term environmental and social impacts, making their policies crucial for developing a robust model to assess energy projects.

IFIs are financial organizations established by multiple countries to provide financing and support for economic development and projects on a global or regional scale. These institutions are often backed by sovereign governments and aim to facilitate investment in developing countries, stabilize financial markets, and promote sustainable development. Common IFIs include the World Bank, International Monetary Fund (IMF), and regional development banks like the European Investment Bank (EIB) or the Asian Development Bank (ADB) [12,16].

The primary focus of IFIs is to promote economic development by the provision of loans, grants, and technical assistance to countries and regions to support economic development, infrastructure projects, poverty alleviation, and capacity building. Financial stability is also a necessary prerequisite; institutions like the IMF focus on ensuring global financial stability by offering support to countries facing balance of payments problems and promoting sound economic policies. IFIs increasingly prioritize investments that align with sustainability goals, such as projects in renewable energy, climate adaptation, and social development.

To achieve the research goals, we conducted an analysis to explore the investment policies of IFIs and their focus on ESG criteria in the context of energy projects. IFIs play a crucial role in shaping global energy investments, particularly as the world shifts towards renewable energy and sustainability. By analyzing the approaches of these major institutions, we aim to understand how ESG considerations influence their financing decisions and how these criteria drive support for energy projects that contribute to decarbonization, energy efficiency, and social responsibility (

Table 1. Overview of ESG focus and investment policies of major international financial institutions (IFIs) in the energy sector.

Institutional Investor/Development Bank	Focus on Energy Projects	Key Policies/Initiatives
World Bank Group (WBG) [17]	Supports energy projects that focus on climate resilience, renewable energy, and reducing carbon emissions. Offers concessional financing through the Climate Investment Funds (CIFs) to help developing countries transition to cleaner energy. Focuses on solar, wind, and energy storage projects.	Clean Technology Fund (CTF) provides financing for low-carbon technologies. Prioritizes energy access in underserved regions through renewables. Aims to reduce emissions while promoting economic development in developing countries.
International Finance Corporation (IFC) [18]	Aims to stimulate private sector investment in renewable energy, energy efficiency, and climate-friendly projects. Focuses on emerging markets, especially those with high potential for renewable energy. Offers green bonds to fund sustainable energy infrastructure.	IFC Climate Business Department drives investment in solar, wind, and energy efficiency projects. IFC Green Bond Program raises capital for climate-smart projects. Supports sustainable energy supply chains, such as solar manufacturing and battery storage.
Green Climate Fund (GCF)Sources: [19]	Supports projects that significantly contribute to reducing emissions and adapting to climate change. Focuses on climate adaptation and resilience, particularly in vulnerable countries. Provides large-scale funding to drive renewable energy projects in developing nations.	Aims to support Paris Agreement objectives, particularly limiting temperature rise to below 2 °C. Funds projects in sectors such as energy, transport, and land use that have a major impact on climate. Supports renewable energy transitions, including wind, solar, and geothermal energy in developing regions.
Asian Development Bank (ADB) [20]	Prioritizes financing for renewable energy, energy efficiency, and climate-resilient energy infrastructure. Committed to phasing out coal financing and in-creasing support for low-carbon projects. Targets increased renewable energy adoption and decentralized energy solutions.	Climate Change Operational Framework focuses on ensuring that 75% of projects include climate adaptation by 2030. Invests in energy storage, grid integration, and large-scale renewable energy facilities. Focuses on both urban energy efficiency and rural electrification through renewables.
African Development Bank (AfDB) [21]	Focuses on renewable energy investments, particularly in solar and wind energy. Prioritizes projects that support energy access in underserved regions, particularly in sub-Saharan Africa. Seeks to mobilize private investment to scale up renewable energy infrastructure.	Desert to Power Initiative: aims to provide solar energy to millions in the Sahel region. Collaborates with governments and private sectors to expand energy access in rural areas. Focuses on clean energy projects that have the potential to reduce energy poverty while lowering emissions.
Inter-American Development Bank (IDB) [22]	Focuses on sustainable energy solutions, including solar, wind, and geothermal energy in Latin America and the Caribbean. Aims to improve energy efficiency and promote cleaner energy sources. Supports projects that help mitigate climate change and reduce environmental impacts.	Sustainable Infrastructure Framework supports climate-aligned energy projects. Invests in renewable energy projects to promote economic development and energy access. Emphasizes climate resilience in energy infrastructure in vulnerable regions.
Nordic Investment Bank (NIB) [23]	Focuses on financing renewable energy, particularly wind, hydro, and biomass projects. Promotes energy efficiency and decarbonization in the Nordic-Baltic region. Supports energy infrastructure projects that reduce emissions and increase sustainability.	NIB Environmental Bonds: raises capital for projects supporting decarbonization and sustainable energy. Invests in projects that have significant climate impact and contribute to reducing the region’s carbon footprint. Emphasizes projects that support a transition to low-carbon energy systems.
European Bank for Reconstruction and Development (EBRD) [24]	Invests in renewable energy and energy efficiency, particularly in transitioning economies. Focuses on low-carbon technologies and projects that promote energy security and decarbonization. Prioritizes energy projects that align with the Paris Agreement.	Green Economy Transition (GET): focuses on decarbonizing the economy and supporting low-carbon development. Provides funding for energy storage, smart grids, and renewable energy integration. Invests in infrastructure that enhances energy efficiency and supports clean energy transition.

Source: Developed by the authors based on sources [17,18,19,20,21,22,23,24].

).

The analysis reveals IFIs are increasingly embedding ESG criteria into their energy investment policies, prioritizing renewable energy, energy efficiency, and decarbonization. Key applicability advice includes aligning the model with IFI ESG standards, incorporating flexible financing mechanisms like green bonds, allowing for regional customization, and ensuring adaptability across public and private sectors. Based on the analysis, the following criteria can be formulated (

Table 2. ESG criteria for energy projects based on IFI investment policies.

Criteria	Description	Category (E, S, G)
Key Required Criteria
Carbon Emission Reduction	Projects must significantly reduce greenhouse gas emissions, aligning with climate goals.	E
Environmental Impact Minimization	Projects must minimize harm to natural ecosystems, protecting biodiversity and resources.	E
Social Inclusivity and Community Impact	Projects should provide social benefits, including job creation and energy access for underserved communities.	S
Transparent Governance and Accountability	Strong governance with clear reporting, ethical management, and stakeholder accountability.	G
Additional Criteria
Innovation and Technology Adoption	Use of advanced technologies (e.g., smart grids, energy storage) for a resilient infrastructure.	E, G
Alignment with Regional Development Goals	Addresses specific regional needs, such as rural energy access or climate resilience.	S, E
Financial Sustainability and Risk Mitigation	Includes financial planning, risk management, and adaptive strategies for sustainable returns.	G
Circular Economy Practices	Emphasizes resource efficiency, waste reduction, and the use of recycled materials.	E

Source: Developed by the authors.

).

Both required and desired criteria for evaluating energy projects in alignment with ESG principles were outlined. Key required criteria are essential for compliance with IFI investment strategies, ensuring projects meet baseline sustainability and governance expectations. In contrast, additional criteria are not mandatory, but enhance a project’s attractiveness to investors by contributing to resilience, innovation, and regional development goals.

4.2. EU Regulatory Requirements

The EU has established a comprehensive framework of regulations and directives to guide sustainable development, particularly in sectors like energy where environmental and social impacts are significant. Within the analysis, we need to focus on the key EU regulations and directives relevant to the energy sector, highlighting their role in promoting ESG principles. Some of these policies are descriptive, serving as broad strategic guidelines that outline the EU’s vision for sustainability and climate action, such as the European Green Deal and Fit for 55. These frameworks set the direction and goals for member states, providing a roadmap without prescribing detailed implementation measures. On the other hand, specific regulations like the EU Taxonomy Regulation and Sustainable Finance Disclosure Regulation (SFDR) introduce clear, enforceable standards that directly impact investment and operational practices within the energy sector. This distinction between strategic directives and detailed regulations demonstrates the EU’s layered approach to sustainability, allowing for flexibility in policy adaptation while ensuring accountability and measurable progress across sectors.

The EU Taxonomy Regulation (Regulation No. 2020/852) establishes a clear classification system for environmentally sustainable economic activities within the EU, designed to direct investment towards projects that support Europe’s environmental objectives. It defines technical criteria for activities to qualify as sustainable, requiring them to make a substantial contribution to one of six environmental objectives while avoiding significant harm to the others. The regulation also mandates comprehensive environmental impact reporting for companies, enabling investors to make informed choices and incorporate sustainability into their investment strategies. Additionally, public institutions use the taxonomy to shape policies for ecological transition. Since 1 January 2023, large companies and financial market participants are required to disclose the extent of their alignment with the EU Taxonomy’s sustainability criteria [25].

The EU Taxonomy Regulation provides a structured classification system for defining environmentally sustainable economic activities within the EU. It identifies six environmental objectives—such as climate change mitigation, pollution prevention, and circular economy transition—and sets technical screening criteria that outline specific requirements for each activity to be considered sustainable. Additionally, the regulation enforces the “Do No Significant Harm” (DNSH) principle, ensuring that projects contributing to one objective do not adversely impact others. This comprehensive framework includes minimum social safeguards, requiring that projects respect human and labor rights and uphold fair governance practices, especially crucial for sectors with broad environmental and social impacts, such as energy.

The EU Taxonomy Regulation is highly significant for energy projects, as it sets clear benchmarks for sustainability that these projects must meet to qualify as “green” investments. Meeting Taxonomy criteria enhances a project’s credibility, making it eligible for sustainable financing options, such as green bonds and EU grants. Moreover, alignment with the Taxonomy helps energy projects support the EU’s broader goals for carbon neutrality by 2050, offering a competitive advantage in an increasingly sustainability-focused market.

Another important regulation is the Corporate Sustainability Reporting Directive (CSRD), an EU regulation aimed at enhancing and standardizing sustainability reporting across the corporate sector. Adopted to replace and expand upon the Non-Financial Reporting Directive (NFRD), the CSRD introduces more stringent and detailed reporting requirements on ESG metrics. The directive seeks to improve transparency, ensuring that companies provide consistent, reliable, and comparable information about their sustainability impacts. It will be rolled out in phases, starting in 2024, and will eventually cover a broad range of companies operating within the EU [26].

The CSRD is particularly significant for energy companies and projects as it mandates in-depth disclosure on environmental impacts, resource usage, emissions, and climate resilience. For energy projects, meeting CSRD standards means providing detailed information on how they contribute to or mitigate climate change, use natural resources, and manage environmental risks. This level of transparency can improve investor confidence and attract capital from stakeholders focused on ESG compliance.

In addition to the EU Taxonomy Regulation, SFDR, and CSRD, several other EU regulations play a critical role in guiding sustainable investments and energy project development. These policies—such as the Energy Efficiency Directive, Environmental Impact Assessment, EU Green Bond Standard, Fit for 55 Package, and Circular Economy Action Plan—are particularly relevant to the energy sector. Together, they offer comprehensive criteria that not only meet compliance requirements but also enhance the attractiveness of projects by aligning with the EU’s climate, environmental, and resource efficiency goals:

• The Energy Efficiency Directive (EED), originally introduced in 2012 and revised in 2018, sets binding measures for EU member states to achieve energy savings and improve overall energy efficiency, with the aim of meeting a 32.5% efficiency improvement by 2030. This directive targets various sectors, including public buildings, industry, and consumer services, mandating specific actions like the annual renovation of at least 3% of public buildings to high energy standards. Member states are required to develop and submit National Energy and Climate Plans detailing their strategies for meeting these targets. For energy projects, the EED underscores the importance of energy efficiency as a core criterion, making it a crucial directive for investors interested in sustainable, compliant projects across the EU [27];
• The Environmental Impact Assessment (EIA) Directive, under Directive 2011/92/EU, mandates that large-scale projects with potentially significant environmental impacts undergo a thorough assessment before approval. This process requires developers to evaluate and disclose potential effects on factors like biodiversity, pollution, and natural resources, integrating environmental considerations into early project planning. The EIA applies broadly across sectors, including energy, ensuring that projects align with EU environmental goals by mitigating negative impacts. This directive is crucial for energy projects, as it requires them to meet rigorous environmental safeguards, thus aligning with investor priorities for transparent, sustainable, and environmentally responsible projects [28];
• The EU Green Bond Standard (EU GBS) is a voluntary framework designed to enhance the integrity of green bond issuances across the EU by setting criteria that ensure funds raised are used for environmentally sustainable projects. The EU GBS requires alignment with the EU Taxonomy to confirm eligibility, ensuring that green bonds finance projects that significantly contribute to one or more environmental objectives. Issuers must develop a bond framework and provide reporting on the use of proceeds, along with an external review for added transparency and investor confidence. This standard is particularly beneficial for energy projects that meet these criteria, as it provides access to sustainable financing options and aligns them with investor expectations for verified environmental impact [29];
• The Fit for 55 Package is an EU policy initiative that aims to reduce greenhouse gas emissions by 55% by 2030, supporting the EU’s commitment to climate neutrality by 2050. This comprehensive package includes multiple legislative components, such as the revised EU Emissions Trading System (ETS), the Renewable Energy Directive, and the Carbon Border Adjustment Mechanism, all aimed at tightening emissions limits across sectors, including energy and transport. Fit for 55 establishes ambitious targets that shape the regulatory landscape for energy projects by promoting renewables, enforcing emissions reductions, and incentivizing green technologies. Projects that align with these stringent requirements enhance their attractiveness to investors focused on forward-looking, climate-aligned investments [30];
• The Circular Economy Action Plan, part of the European Green Deal, focuses on transitioning from a linear to a circular economy by promoting sustainable resource use, waste reduction, and recycling practices, especially in high-impact sectors like electronics, plastics, and construction. It introduces policies for extending product lifecycles, minimizing waste, and enhancing recycling to reduce the EU’s dependency on finite resources. For energy projects, the plan encourages using sustainable materials and integrating circular economy practices, such as efficient resource management and waste reduction, into project design and implementation. Adhering to this plan enhances a project’s appeal to investors by aligning it with EU sustainability goals and promoting long-term resource conservation [31].

The essential EU regulatory requirements that serve as both mandatory and additional criteria for evaluating energy projects have been outlined. Mandatory criteria ensure compliance with EU standards, while additional criteria, though not required, increase a project’s attractiveness to investors by emphasizing sustainability, resilience, and alignment with EU goals. Based on the analysis, the following criteria can be formulated (

Table 3. Key regulatory criteria for sustainable energy projects.

Criteria	Description	Category (E, S, G)
Key Required Criteria
Alignment with Sustainability Standards	Projects should meet established sustainability standards (such as a Taxonomy framework) to be classified as environmentally friendly, focusing on emissions reduction and climate adaptation.	E
Comprehensive Environmental Assessment	Projects with significant environmental impacts should undergo an environmental assessment to protect biodiversity and natural resources.	E
Transparency and Disclosure	Projects should maintain transparent reporting on environmental, social, and governance (ESG) factors, including clear information on sustainability practices and risks.	G
Energy Efficiency	Projects must demonstrate efficient use of energy, incorporating technology and design practices that minimize energy consumption and enhance resource efficiency.	E
Community and Social Benefits	Projects should address social benefits, such as local job creation, fair labor practices, and contributions to community development, especially in underserved areas.	S
Additional Criteria
Emissions Reduction and Climate Goals	Projects that proactively support emissions reduction targets and renewable energy goals align with global climate commitments and are more attractive for investment.	E
Green Financing Compatibility	Projects that qualify for green financing instruments (e.g., green bonds) enhance their investment appeal by aligning with sustainable finance standards.	E, G
Resource Circularity	Projects that integrate circular economy principles, such as recycling, waste reduction, and sustainable material use, contribute to long-term resource sustainability.	E
Regional Development Contribution	Projects that address specific regional needs, such as energy access in rural areas or resilience against climate impacts, contribute to balanced regional development.	S, E

Source: Developed by the authors.

).

The recommended framework provides mandatory criteria that ensure baseline compliance with sustainability standards, environmental protection, transparency, energy efficiency, and community benefits. Additional criteria enhance project attractiveness by aligning with climate goals, enabling access to green financing, supporting circular economy practices, and addressing regional needs. Together, these criteria help structure energy projects that are both compliant and appealing to sustainable investors.

4.3. Incorporating Local Regulatory Requirements for Energy Project Assessment in Ukraine

To ensure the assessment model is tailored to the specific regulatory and strategic needs of Ukraine’s energy sector, we need to outline key local requirements that must be integrated. In Ukraine, essential requirements include the Environmental Impact Assessment and Corporate Governance Reporting. Additionally, Ukraine’s Energy Strategy 2050 sets critical long-term goals for the sector, which must be considered to align project assessments with national priorities for sustainability, efficiency, and energy independence.

In Ukraine, the Environmental Impact Assessment (EIA) process mandates that project developers submit an EIA report if their activities are likely to have significant environmental impacts. This requirement applies to projects in sectors such as energy, infrastructure, mining, agriculture, and industrial production. Typically, the EIA is essential for large-scale construction, expansions of existing facilities, or any project with potential ecological risks, especially those near environmentally sensitive areas. The EIA is generally submitted once per project, usually during the planning or pre-approval phase, before any physical development begins [32,33].

An EIA report includes comprehensive sections detailing the project’s scope, potential impacts, and proposed mitigation measures. The project description provides a thorough outline of the project’s scale and activities. Environmental baseline data offers insights into the current state of the project area, covering aspects such as local ecosystems, water bodies, soil, and air quality. The impact assessment analyzes potential environmental effects, including emissions, waste production, and biodiversity implications. To address these impacts, the report must specify mitigation measures: proposed actions to minimize or manage the identified environmental risks.

Some industry experts have outlined significant challenges with EIA in Ukraine [34]:

• The Ukrainian EIA framework includes a wider range of activities than EU standards, requiring assessments for projects not deemed significant in the EU. This overloads the system with minor cases, potentially diverting attention from truly impactful projects;
• There are no clearly defined requirements regarding the issues that must be addressed in an EIA report. This allows officials to request additional, sometimes irrelevant, information, adding to bureaucratic delays and inconsistency in evaluations;
• Officials have broad discretion in EIA approvals, and the qualifications of designated experts are often questioned. This flexibility can lead to biased or inconsistent assessments, impacting the objectivity of the process;
• Although public participation is intended, there are complaints that the process often favors authorities and businesses, reducing public confidence in the EIA’s effectiveness.

The Corporate Governance Report in Ukraine is a mandatory document for certain companies that outlines their governance structure, policies, and practices. This report includes information on the board of directors, shareholder rights, risk management practices, and corporate ethics. It aims to ensure transparency and accountability by providing stakeholders with insight into the company’s leadership and decision-making processes [35]. In practice, the document often serves as a formal requirement rather than a practical tool for stakeholders to gain insight into the company’s corporate strategy, goals, and values.

The Energy Strategy of Ukraine 2050 is a comprehensive document approved by the Cabinet of Ministers of Ukraine, outlining the country’s long-term vision for the energy sector [36]. It addresses key issues like energy security, resilience, climate neutrality, and modernization of the energy infrastructure. The strategy is influenced by the aftermath of the Russian invasion, Ukraine’s ambitions to integrate with the European Union, and global sustainability goals. Based on Ukraine’s Energy Strategy 2050, here are three critical criteria that new energy projects should meet to align with the strategic goals outlined:

• Energy Security and Resilience: Projects must enhance Ukraine’s energy independence by diversifying energy sources, increasing domestic production, or strengthening infrastructure resilience against physical and cyber threats.
• Climate Neutrality and Emission Reduction: Projects should prioritize low-carbon or zero-carbon technologies (e.g., renewables, hydrogen production) to actively reduce greenhouse gas emissions, with clear plans for carbon footprint monitoring.
• Modernization and Technological Innovation: Projects must integrate advanced technologies, such as smart grids and energy storage, to modernize infrastructure, improve efficiency, and support the green transition in alignment with Ukraine’s Energy Strategy 2050.

In the context of Ukraine, it is crucial to tailor the ESG criteria to address the specific social and economic needs arising from the country’s unique challenges. The Social (S) component should incorporate factors that support the involvement of veterans in the workforce, promote regional development, and prioritize projects in areas most affected by the war. This focus aligns with Ukraine’s broader goals of social recovery and economic resilience, ensuring that energy projects contribute not only to sustainable growth but also to social stability and cohesion. By emphasizing these aspects within the ESG framework, the model can help direct investments towards initiatives that not only fulfill sustainability requirements but also aid in the rebuilding and revitalization of communities most impacted by the conflict.

4.4. Comprehensive ESG Criteria for Sustainable Energy Project Evaluation

To ensure energy projects meet the standards of sustainable development, it is essential to assess them through a comprehensive Environmental, Social, and Governance (ESG) framework. Key ESG criteria that projects must fulfill to align with both international sustainability goals and the specific objectives of Ukraine’s energy strategy have been outlined. Through these criteria, energy projects can demonstrate their commitment to reducing environmental harm, fostering community benefits, and upholding ethical and transparent governance practices.

Based on the analysis of ESG component weights across different sectors, it is evident that Environmental (E) and Social (S) factors hold greater importance in the energy sector compared to Governance (G). This trend reflects the specific priorities and challenges within energy projects, particularly those related to renewable energy and electric utilities, where environmental impact and social responsibility are critical concerns. This analysis is well covered in the literature [21]. By prioritizing E and S components, the assessment framework can more effectively address the unique operational and sustainability demands of the energy industry (

Table 4. Consolidated ESG criteria for sustainable energy projects in Ukraine.

№	Criteria	Description
1	Environmental (E)
	Mandatory Requirements
1.1	Carbon Emission Reduction	Projects must meet specific emissions reduction thresholds, aligning with national and EU climate goals.
1.2	Environmental Impact Assessment (EIA)	A comprehensive EIA is required to protect biodiversity and natural resources, as per Ukrainian law.
1.3	Energy Efficiency	Projects should demonstrate efficient energy usage, minimizing energy waste through advanced technology.
	Additional Criteria
1.4	Renewable Energy Integration	Projects should prioritize renewable sources to support Ukraine’s low-carbon transition.
1.5	Resource Efficiency and Circular Economy	Emphasize resource efficiency, waste reduction, and recycling to align with circular economy practices.
1.6	Alignment with Fit for 55 Targets	Proactively support EU-aligned emissions reduction and renewable energy adoption targets.
2	Social (S)
	Mandatory Requirements
2.1	Community Impact and Benefits	Projects must provide benefits to local communities, including job creation and regional support.
2.2	Public Participation	Stakeholders and communities must be involved in project planning for transparency and social acceptance.
	Additional Criteria
2.3	Veteran Involvement	Projects should include opportunities for veterans’ employment and skill development to support social recovery.
2.4	Regional Development Focus	Prioritize areas heavily affected by the war to support regional rebuilding and economic development.
2.5	Social Inclusivity	Ensure equitable access to project benefits for underserved communities, promoting social equity.
3	Governance (G)
	Mandatory Requirements
3.1	Transparent Governance	Projects must ensure clear reporting, ethical management, and accountability aligned with national and EU standards.
3.2	Regulatory Compliance	Adherence to both Ukrainian and EU regulatory requirements for transparency and governance practices.
	Additional Criteria
3.3	Green Financing Eligibility	Projects should be designed to qualify for sustainable financing, such as green bonds, to attract investors.
3.4	Risk Management and Resilience Planning	Demonstrate risk management, including resilience to climate risks and external threats.
3.5	Alignment with Regional Development Goals	Address specific regional needs, like energy access in underserved areas, to support balanced development.

Source: Developed by the authors.

).

To create a scalable and practical model that ranks energy projects based on their adherence to ESG standards and potential for contributing to long-term sustainability and energy transition, we propose the use of the Fuzzy DEMATEL method [37,38] to rank additional criteria within each group of factors. The structure of the proposed approach is presented below (Figure 1).

In the first stage, an expert group is created, considering the interests of the main stakeholders and specialists with relevant competencies in the subject area. Since the evaluation criteria must reflect the interests of key stakeholders (owners, managers, employees, creditors, consumers, and society at large), representatives from these groups should participate in the process.

Then, the group undertakes the formulation of a list of evaluation criteria. At this stage, it is advisable to group the formulated criteria based on specific dimensions (e.g., by stakeholder group, area of activity, or functional domain). The following notations are introduced: M—the number of such groups; K1, K2, …—the number of experts participating in the formulation and subsequent evaluation of criteria in the specified groups; and n1, n2, …—the number of preliminarily formulated criteria in the specified groups.

The Fuzzy DEMATEL method is applied to determine the weights of criteria by analyzing their interdependence and influence relationships. The application sequence of this method is as follows:

2.1. Evaluation of the interdependence of criteria within each identified group using pairwise comparisons. For this, the fuzzy linguistic scale (as shown in

Table 5. Fuzzy linguistic scale.

Linguistic Term	Notation	Triangular Fuzzy Number
No impact	NN	(0.0; 0.0; 1.0)
Very Low impact	VLVL	(0.0; 1.0; 2.0)
Low impact	LL	(1.0; 2.0; 3.0)
Moderate impact	MM	(2.0; 3.0; 4.0)
High impact	HH	(3.0; 4.0; 5.0)
Very High Impact	VHVH	(4.0; 5.0; 5.0)

Source: Developed by the authors based on [33].

) is applied, which is a modified version of the scale proposed in the source [39].

Experts in each identified group are asked to evaluate the interdependence of criteria pairwise using the linguistic terms from Table 1, which correspond to triangular fuzzy numbers. A geometric representation of the membership functions of the terms is shown in Figure 2.

After converting linguistic evaluations of experts into fuzzy numbers using the scale shown in Table 1, we obtain fuzzy pairwise comparison matrices $\widetilde{X^{𝚤𝚥}}=|\widetilde{x_{pq}^{𝚤𝚥}}{|}_{n_i\times n_i}$, where $\widetilde{X^{𝚤𝚥}}$ is the fuzzy matrix of pairwise comparisons for the interdependence of evaluation criteria provided by the j-th expert for the i-th group (direction). Each element is represented as $\widetilde{x_{pq}^{𝚤𝚥}}=\left(a_{pq}^{ij};b_{pq}^{ij};c_{pq}^{ij}\right); p=1,2,\dots ,n_i; q=1,2,\dots ,n_i.$

The calculation of the aggregated fuzzy pairwise comparison matrices of evaluation criteria is performed as follows: $\widetilde{Y^{𝚤}}=|\widetilde{y_{pq}^{𝚤}}{|}_{n_i\times n_i},$ where $\widetilde{y_{pq}^{𝚤}}=\left(a_{pq}^i; b_{pq}^i;c_{pq}^i\right), \mathrm{a}\mathrm{n}\mathrm{d} a_{pq}^i=\underset{j}{\min } a_{pq}^{ij};$ $b_{pq}^i={\displaystyle \frac{1}{K_i}}{\sum }_{j=1}^{K_i}{b}_{pq}^{jj}; c_{pq}^i=\max c_{pq}^{ij}.$ These relationships allow us to “defuzzify” the evaluations into aggregated fuzzy values. For further precision, the following formulas can also be used:

$$\begin{array}{c}{a}_{pq}^i={\displaystyle \frac{1}{K_i}}{\displaystyle \sum _{j=1}^{K_i}}{a}_{pq}^{ij};b_{pq}^i={\displaystyle \frac{1}{K_i}}{\displaystyle \sum _{j=1}^{K_i}}{b}_{pq}^{ij};c_{pq}^i={\displaystyle \frac{1}{K_i}}{\displaystyle \sum _{j=1}^{K_i}}{c}_{pq}^{ij}\end{array}$$

Normalization of the aggregated fuzzy pairwise comparison matrices is performed as follows. $\widetilde{Y^{𝚤}}=|\widetilde{y_{pq}^{𝚤}}{|}_{n_i\times n_i}\to \widetilde{Z^{𝚤}}=|\widetilde{z_{pq}^{𝚤}}{|}_{n_i\times n_i}$, where $\begin{array}{c}{\tilde{Z}}^i=s^i\times {\tilde{Y}}^i,i=1,2,\dots ,M\end{array}$, and s is the normalization coefficient:

$$\begin{array}{c}{s}^i=min[1/\underset{1\le p\le n_i}{max}{\displaystyle \sum _{q=1}^{n_i}}{c}_{pq}^i;1/\underset{1\le q\le n_i}{max}{\displaystyle \sum _{p=1}^{n_i}}{c}_{pq}^i].\end{array}$$

Thus, we obtain the fuzzy matrix: $\widetilde{Z^{𝚤}}=|\widetilde{z_{pq}^{𝚤}}{|}_{n_i\times n_i},\mathrm{w}\mathrm{h}\mathrm{e}\mathrm{r}\mathrm{e} \widetilde{z_{pq}^{𝚤}}$—are fuzzy numbers represented in triangular form as $\widetilde{z_{pq}^{𝚤}}=\left({\mathsf{\alpha }}_{pq}^i;{\mathsf{\beta }}_{pq}^i;{\mathsf{\gamma }}_{pq}^i\right).$ Accordingly, the fuzzy matrix $\widetilde{Z^{𝚤}}$ can be represented as a superposition of three matrices with crisp (non-fuzzy) values:

$$\begin{array}{c}{Z}_{\alpha }^i=\left[\begin{array}{cccc}{\alpha }_{11}^i& {\alpha }_{12}^i& \cdots & {\alpha }_{1n_i}^i\\ {\alpha }_{21}^i& {\alpha }_{22}^i& \cdots & {\alpha }_{2n_k}^i\\ ⋮& ⋮& \cdots & ⋮\\ {\alpha }_{n_{i}1}^i& {\alpha }_{n_{i}2}^i& \cdots & {\alpha }_{n,n_i}^i\end{array}\right];Z_{\beta }^i=\left[\begin{array}{cccc}{\beta }_{11}^i& {\beta }_{12}^i& \cdots & {\beta }_{1n_i}^i\\ {\beta }_{21}^i& {\beta }_{22}^i& \cdots & {\beta }_{2n_k}^i\\ ⋮& ⋮& \cdots & ⋮\\ {\beta }_{n_{i}1}^i& {\beta }_{n_{i}2}^i& \cdots & {\beta }_{n_i{n}_l}^i\end{array}\right];\\ Z_{\gamma }^i=\left[\begin{array}{cccc}{\gamma }_{11}^i& {\gamma }_{12}^i& \cdots & {\gamma }_{1n_i}^i\\ {\gamma }_{21}^i& {\gamma }_{22}^i& \cdots & {\gamma }_{2n_k}^i\\ ⋮& ⋮& \cdots & ⋮\\ {\gamma }_{n_{1}1}^i& {\gamma }_{n_{i}2}^i& \cdots & {\gamma }_{n_i{n}_i}^i\end{array}\right]\end{array}$$

According to the Fuzzy DEMATEL method, we modify the fuzzy integral matrices of interrelations for each group (direction). For this purpose, each of the matrices $Z_{\mathsf{\alpha }}^i,Z_{\mathsf{\alpha }}^i,Z_{\mathsf{\alpha }}^i$ is transformed as follows: $T_{\mathsf{\alpha }}^i=Z_{\mathsf{\alpha }}^i\times {\left(E-Z_{\mathsf{\alpha }}^i\right)}^{-1};T_{\mathsf{\beta }}^i=Z_{\mathsf{\beta }}^i\times {\left(E-Z_{\mathsf{\beta }}^i\right)}^{-1};T_{\mathsf{\gamma }}^i=Z_{\mathsf{\gamma }}^i\times {\left(E-Z_{\mathsf{\gamma }}^i\right)}^{-1}$. As a result, we obtain the fuzzy matrix:

$$\begin{array}{c}{\tilde{T}}^i={\tilde{Z}}^i\times {\left(E-{\tilde{Z}}^i\right)}^{-1}=\left[\begin{array}{cccc}{\tilde{t}}_{11}^i& {\tilde{t}}_{12}^i& \cdots & {\tilde{t}}_{1n_i}^i\\ {\tilde{t}}_{21}^i& {\tilde{t}}_{22}^i& \cdots & {\tilde{t}}_{2n_i}^i\\ ⋮& ⋮& \cdots & ⋮\\ {\tilde{t}}_{n_{i}1}^i& {\tilde{t}}_{n_{i}2}^i& \cdots & {\tilde{t}}_{n_i{n}_i}^i\end{array}\right].\end{array}$$

The next step is to calculate the sum of fuzzy numbers in rows $\widetilde{R_p^{𝚤}}={\sum }_{q=1}^{n_i}\widetilde{t_{pq}^{𝚤}} \mathrm{a}\mathrm{n}\mathrm{d} \mathrm{c}\mathrm{o}\mathrm{l}\mathrm{u}\mathrm{m}\mathrm{n}\mathrm{s} \widetilde{P_q^{𝚤}}={\sum }_{p=1}^{n_i}\widetilde{t_{pq}^{𝚤}}$ of the fuzzy matrix ${\tilde{T}}^i$, which represent the levels of integral interrelations and dependencies of the defined criteria for each ii-th group (direction) as the sum of direct and indirect influences and dependencies among them.

Next, we calculate the fuzzy sums and differences and perform defuzzification of these fuzzy numbers using the BNP method. To simplify the obtained results, we can construct a chart where the horizontal axis ${\left(\widetilde{R_{𝚤}}\left(+\right)\widetilde{P_{𝚤}}\right)}^{\mathrm{def}}$ (showing the strength of influence for both incoming and outgoing interrelations) represents the level (rank) of this criterion in the overall interaction, and the vertical axis shows ${\left(\widetilde{R_{𝚤}}\left(-\right)\widetilde{P_{𝚤}}\right)}^{\mathrm{def}},\mathrm{w}\mathrm{h}\mathrm{e}\mathrm{r}\mathrm{e}\mathrm{if}{\left(\widetilde{R_{𝚤}}\left(-\right)\widetilde{P_{𝚤}}\right)}^{\mathrm{def}}>0$, then the ii-th criterion influences other criteria; if ${\left(\widetilde{R_{𝚤}}\left(-\right)\widetilde{P_{𝚤}}\right)}^{\det }<0,$ then it depends on them.

At the fifth stage, the ranking of criteria is conducted. To assess the importance of criteria at the fifth stage, apart from considering the values ${\left(\widetilde{R_{𝚤}}\left(+\right)\widetilde{P_{𝚤}}\right)}^{\mathrm{def}}$, the priority can also be determined using the following relationship:

$$\begin{array}{c}{w}_i=\sqrt{{({({\tilde{R}}_j^i(+){\tilde{P}}_j^i)}^{def})}^2+{({({\tilde{R}}_j^i(-){\tilde{P}}_j^i)}^{def})}^2}\end{array}$$

We now illustrate the application of the developed methodology with an example. For this purpose, we will use a procedure and case where a general list of criteria is formed.

Table 6. Evaluation criteria grouping.

№	Criteria Group	Description
C1	Renewable Energy Integration (E)	Projects should prioritize renewable sources to support Ukraine’s low-carbon transition.
C2	Resource Efficiency and Circular Economy (E)	Emphasize resource efficiency, waste reduction, and recycling to align with circular economy practices.
C3	Alignment with Fit for 55 Targets (E)	Proactive support EU-aligned emissions reduction and renewable energy adoption targets.
C4	Veteran Involvement (S)	Projects should include opportunities for veterans’ employment and skill development to support social recovery.
C5	Regional Development Focus (S)	Prioritize areas heavily affected by the war to support regional rebuilding and economic development.
C6	Social Inclusivity (S)	Ensure equitable access to project benefits for underserved communities, promoting social equity.
C7	Green Financing Eligibility (G)	Projects should be designed to qualify for sustainable financing, such as green bonds, to attract investors.
C8	Risk Management and Resilience Planning (G)	Demonstrate risk management, including resilience to climate risks and external threats.
C9	Alignment with Regional Development Goals (G)	Address specific regional needs, like energy access in underserved areas, to support balanced development.

Source: Developed by the authors.

shows the initial list of criteria, which includes proposals from a working group of four experts and specialists.

Table 7. Evaluation by experts.

E1

G1

G2

G3

G4

G5

G6

G7

G8

G9

E2

G1

G2

G3

G4

G5

G6

G7

G8

G9

G1

N

H

M

L

VL

L

M

H

VL

G1

N

M

L

VL

L

M

H

VH

L

G2

M

N

L

M

H

M

L

VL

M

G2

H

N

M

L

VL

H

M

H

M

G3

H

VL

N

L

VL

M

H

M

VL

G3

M

L

N

VL

VL

L

H

H

VL

G4

L

M

L

N

VL

VL

M

H

VL

G4

L

H

VL

N

L

L

M

VL

L

G5

VH

H

M

L

N

L

M

H

VL

G5

M

M

M

L

N

L

M

VH

L

G6

L

VL

L

VL

L

N

H

M

VL

G6

L

VL

H

VL

L

N

M

M

L

G7

M

M

H

M

M

L

N

H

L

G7

VH

M

H

M

M

L

N

M

M

G8

H

VL

M

H

VH

M

M

N

L

G8

H

L

M

M

M

M

H

N

L

G9

VL

M

L

VL

L

VL

M

H

N

G9

L

VL

VL

VL

L

L

M

H

N

E3

G1

G2

G3

G4

G5

G6

G7

G8

G9

E4

G1

G2

G3

G4

G5

G6

G7

G8

G9

G1

N

L

M

H

VH

M

L

L

VL

G1

N

H

H

VL

VL

L

M

VH

M

G2

VL

N

L

H

L

M

L

VL

L

G2

L

N

L

L

M

M

L

H

L

G3

H

L

N

M

H

VH

H

VL

L

G3

M

M

N

M

L

M

H

M

M

G4

VL

H

M

N

M

H

M

VL

L

G4

VL

VL

VL

N

VL

L

VL

L

VL

G5

M

L

H

M

N

L

M

VH

L

G5

H

H

VH

L

N

M

M

VH

H

G6

L

VL

L

VL

L

N

H

VL

VL

G6

M

VL

M

L

L

N

M

H

VL

G7

H

VL

H

VL

M

H

N

M

L

G7

H

M

M

M

H

M

N

H

M

G8

VH

H

VH

L

H

M

L

N

L

G8

VH

H

VH

H

VH

M

M

N

L

G9

L

M

VL

L

VL

VL

VL

L

N

G9

L

VL

VL

L

VL

VL

M

M

N

Source: Developed by the authors.

presents the linguistic evaluations by experts of the interdependence of criteria during pairwise comparisons according to the fuzzy linguistic scale (Table 5).

Using the fuzzy numbers presented in triangular form in Table 5, corresponding to the defined linguistic terms, we can obtain fuzzy evaluations of the interdependence of criteria (

Table 8. Fuzzy evaluations of the first expert on the interdependence of strategic goals.

Expert 1	G1	G2	G3	G4	G5	G6	G7	G8	G9
G1		(3; 4; 5)	(2; 3; 4)	(1; 2; 3)	(0; 1; 2)	(1; 2; 3)	(2; 3; 4)	(3; 4; 5)	(0; 1; 2)
G2	(2; 3; 4)		(1; 1; 3)	(2; 3; 4)	(3; 4; 5)	(2; 3; 4)	(1; 2; 3)	(0; 1; 2)	(2; 3; 4)
G3	(3; 4; 5)	(0; 1; 2)		(1; 2; 3)	(0; 1; 2)	(2; 3; 4)	(3; 4; 5)	(2; 3; 4)	(0; 1; 2)
G4	(1; 2; 3)	(2; 3; 4)	(1; 2; 3)		(0; 1; 2)	(0; 1; 2)	(2; 3; 4)	(3; 4; 5)	(0; 1; 2)
G5	(4; 5; 6)	(3; 4; 5)	(2; 3; 4)	(1; 2; 3)		(1; 2; 3)	(2; 3; 4)	(3; 4; 5)	(0; 1; 2)
G6	(1; 2; 3)	(0; 1; 2)	(1; 2; 3)	(0; 1; 2)	(1; 2; 3)		(3; 4; 5)	(2; 3; 4)	(0; 1; 2)
G7	(2; 3; 4)	(2; 3; 4)	(3; 4; 5)	(2; 3; 4)	(2; 3; 4)	(1; 2; 3)		(3; 4; 5)	(1; 2; 3)
G8	(3; 4; 5)	(0; 1; 2)	(2; 3; 4)	(3; 4; 5)	(4; 5; 6)	(2; 3; 4)	(2; 3; 4)		(1; 2; 3)
G9	(0; 1; 2)	(2; 3; 4)	(1; 2; 3)	(0; 1; 2)	(1; 2; 3)	(0; 1; 2)	(2; 3; 4)	(3; 4; 5)

Source: Developed by the authors.

,

Table 9. Fuzzy evaluations of the second expert on the interdependence of strategic goals.

Expert 2	G1	G2	G3	G4	G5	G6	G7	G8	G9
G1		(2; 3; 4)	(1; 2; 3)	(0; 1; 2)	(1; 2; 3)	(2; 3; 4)	(3; 4; 5)	(4; 5; 6)	(1; 2; 3)
G2	(3; 4; 5)		(2; 3; 4)	(1; 2; 3)	(0; 1; 2)	(3; 4; 5)	(2; 3; 4)	(3; 4; 5)	(2; 3; 4)
G3	(2; 3; 4)	(1; 2; 3)		(0; 1; 2)	(0; 1; 2)	(1; 2; 3)	(3; 4; 5)	(3; 4; 5)	(0; 1; 2)
G4	(1; 2; 3)	(3; 4; 5)	(0; 1; 2)		(1; 2; 3)	(1; 2; 3)	(2; 3; 4)	(0; 1; 2)	(1; 2; 3)
G5	(2; 3; 4)	(2; 3; 4)	(2; 3; 4)	(1; 2; 3)		(1; 2; 3)	(2; 3; 4)	(4; 5; 6)	(1; 2; 3)
G6	(1; 2; 3)	(0; 1; 2)	(3; 4; 5)	(0; 1; 2)	(1; 2; 3)		(2; 3; 4)	(2; 3; 4)	(1; 2; 3)
G7	(4; 5; 6)	(2; 3; 4)	(3; 4; 5)	(2; 3; 4)	(2; 3; 4)	(1; 2; 3)		(2; 3; 4)	(2; 3; 4)
G8	(3; 4; 5)	(1; 2; 3)	(2; 3; 4)	(2; 3; 4)	(2; 3; 4)	(2; 3; 4)	(3; 4; 5)		(1; 2; 3)
G9	(1; 2; 3)	(0; 1; 2)	(0; 1; 2)	(0; 1; 2)	(1; 2; 3)	(1; 2; 3)	(2; 3; 4)	(3; 4; 5)

Source: Developed by the authors.

,

Table 10. Fuzzy evaluations of the third expert on the interdependence of strategic goals.

Expert 3	G1	G2	G3	G4	G5	G6	G7	G8	G9
G1		(1; 2; 3)	(2; 3; 4)	(3; 4; 5)	(4; 5; 6)	(2; 3; 4)	(1; 2; 3)	(1; 2; 3)	(0; 1; 2)
G2	(0; 1; 2)		(1; 2; 3)	(3; 4; 5)	(1; 2; 3)	(2; 3; 4)	(1; 2; 3)	(0; 1; 2)	(1; 2; 3)
G3	(3; 4; 5)	(1; 2; 3)		(2; 3; 4)	(3; 4; 5)	(4; 5; 6)	(3; 4; 5)	(0; 1; 2)	(1; 2; 3)
G4	(0; 1; 2)	(3; 4; 5)	(2; 3; 4)		(2; 3; 4)	(3; 4; 5)	(2; 3; 4)	(0; 1; 2)	(1; 2; 3)
G5	(2; 3; 4)	(1; 2; 3)	(3; 4; 5)	(2; 3; 4)		(1; 2; 3)	(2; 3; 4)	(4; 5; 6)	(1; 2; 3)
G6	(1; 2; 3)	(0; 1; 2)	(1; 2; 3)	(0; 1; 2)	(1; 2; 3)		(3; 4; 5)	(0; 1; 2)	(0; 1; 2)
G7	(3; 4; 5)	(0; 1; 2)	(3; 4; 5)	(0; 1; 2)	(2; 3; 4)	(3; 4; 5)		(2; 3; 4)	(1; 2; 3)
G8	(4; 5; 6)	(3; 4; 5)	(4; 5; 6)	(1; 2; 3)	(3; 4; 5)	(2; 3; 4)	(1; 2; 3)		(1; 2; 3)
G9	(1; 2; 3)	(2; 3; 4)	(0; 1; 2)	(1; 2; 3)	(0; 1; 2)	(0; 1; 2)	(0; 1; 2)	(1; 2; 3)

Source: Developed by the authors.

and

Table 11. Fuzzy evaluations of the fourth expert on the interdependence of strategic goals.

Expert 4	G1	G2	G3	G4	G5	G6	G7	G8	G9
G1		(3; 4; 5)	(3; 4; 5)	(0; 1; 2)	(0; 1; 2)	(1; 2; 3)	(2; 3; 4)	(4; 5; 6)	(2; 3; 4)
G2	(1; 2; 3)		(1; 2; 3)	(1; 2; 3)	(2; 3; 4)	(2; 3; 4)	(1; 2; 3)	(3; 4; 5)	(1; 2; 3)
G3	(2; 3; 4)	(2; 3; 4)		(2; 3; 4)	(1; 2; 3)	(2; 3; 4)	(3; 4; 5)	(2; 3; 4)	(2; 3; 4)
G4	(0; 1; 2)	(0; 1; 2)	(0; 1; 2)		(0; 1; 2)	(1; 2; 3)	(0; 1; 2)	(1; 2; 3)	(0; 1; 2)
G5	(3; 4; 5)	(3; 4; 5)	(4; 5; 6)	(1; 2; 3)		(2; 3; 4)	(2; 3; 4)	(4; 5; 6)	(3; 4; 5)
G6	(2; 3; 4)	(0; 1; 2)	(2; 3; 4)	(1; 2; 3)	(1; 2; 3)		(2; 3; 4)	(3; 4; 5)	(0; 1; 2)
G7	(3; 4; 5)	(2; 3; 4)	(2; 3; 4)	(2; 3; 4)	(3; 4; 5)	(2; 3; 4)		(3; 4; 5)	(2; 3; 4)
G8	(4; 5; 6)	(3; 4; 5)	(4; 5; 6)	(3; 4; 5)	(4; 5; 6)	(2; 3; 4)	(2; 3; 4)		(1; 2; 3)
G9	(1; 2; 3)	(0; 1; 2)	(0; 1; 2)	(1; 2; 3)	(0; 1; 2)	(0; 1; 2)	(2; 3; 4)	(2; 3; 4)

Source: Developed by the authors.

).

Next, it is necessary to calculate the aggregated fuzzy pairwise comparison matrix of criteria. We present the final results of fuzzy values $\widetilde{R_{𝚤}},\widetilde{P_{𝚤}},\widetilde{R_{𝚤}}\left(+\right)\widetilde{P_{𝚤}} \mathrm{a}\mathrm{n}\mathrm{d} \widetilde{R_{𝚤}}\left(-\right)\widetilde{P_{𝚤}}.$ (

Table 12. Fuzzy values $\widetilde{R_{𝚤}},\widetilde{P_{𝚤}},\widetilde{R_{𝚤}}\left(+\right)\widetilde{P_{𝚤}} \mathrm{a}\mathrm{n}\mathrm{d} \widetilde{R_{𝚤}}\left(-\right)\widetilde{P_{𝚤}}.$

C	R	P	R+P	R−P
C1	(0.66; 1.63; 5.41)	(0.75; 1.77; 5.76)	(1.41; 3.4; 11.17)	(−5.1; −0.15; 4.66)
C2	(0.58; 1.49; 5.12)	(0.55; 1.47; 5.03)	(1.13; 2.95; 10.15)	(−4.46; 0.02; 4.56)
C3	(0.64; 1.6; 5.34)	(0.69; 1.67; 5.55)	(1.33; 3.27; 10.89)	(−4.91; −0.07; 4.65)
C4	(0.39; 1.22; 4.44)	(0.47; 1.34; 4.72)	(0.86; 2.56; 9.16)	(−4.33; −0.12; 3.97)
C5	(0.82; 1.88; 6)	(0.56; 1.47; 5.05)	(1.37; 3.35; 11.05)	(−4.23; 0.4; 5.44)
C6	(0.44; 1.29; 4.6)	(0.6; 1.53; 5.19)	(1.03; 2.82; 9.79)	(−4.75; −0.25; 4.01)
C7	(0.78; 1.82; 5.88)	(0.73; 1.75; 5.7)	(1.52; 3.57; 11.57)	(−4.91; 0.08; 5.15)
C8	(0.87; 1.96; 6.2)	(0.81; 1.86; 5.97)	(1.68; 3.82; 12.17)	(−5.09; 0.1; 5.4)
C9	(0.35; 1.15; 4.28)	(0.36; 1.17; 4.31)	(0.7; 2.32; 8.59)	(−3.97; −0.02; 3.92)

Source: Developed by the authors.

).

The results presented in

Table 13. Defuzzified values of the priority of strategic goals.

C	(R + P)def	(R − P)def	w	Rank
C1	5.33	−0.20	5.33	3
C2	4.74	0.04	4.74	6
C3	5.16	−0.11	5.17	5
C4	4.19	−0.16	4.20	8
C5	5.26	0.54	5.29	4
C6	4.55	−0.33	4.56	7
C7	5.55	0.10	5.55	2
C8	5.89	0.13	5.89	1
C9	3.87	−0.02	3.87	9

Source: Developed by the authors.

and illustrated in Figure 3 reveal the relative importance and interdependencies of the proposed ESG criteria. Criterion C8 (Risk Management and Resilience Planning) ranks highest in priority with a weight of w = 5.89, indicating its critical influence on the entire evaluation framework. This underscores the strategic relevance of incorporating long-term risk mitigation and system adaptability as core principles for energy investment decisions, particularly in high-uncertainty environments like post-war recovery.

The second most influential criterion is C7 (Green Financing Eligibility), with a weight of w = 5.55, reflecting its significance in aligning projects with sustainable financing instruments such as green bonds and climate-related funding mechanisms. This confirms that financial access and alignment with ESG-compliant capital flows are essential enablers of project viability.

Mid-ranked criteria, including C3 (Environmental Compliance) and C6 (Use of Renewable Energy Sources), hold moderate weights, suggesting their necessary but supportive role in ESG integration. These criteria contribute to regulatory alignment and sustainability but are less central than C7 and C8 in driving the system.

Conversely, lower-ranked criteria such as C9 (Alignment with Regional Development Goals) and C4 (Veteran Involvement), with weights of w = 3.87 and w = 4.20, respectively, are positioned more as dependent variables within the framework. While they reflect important socio-political considerations—especially in the Ukrainian context—they exert less direct influence over the system dynamics compared to the primary drivers.

The cause-and-effect diagram (Figure 3) further clarifies the structure of relationships. C8 and C7 emerge as key causal criteria, meaning they have strong influence over other components in the system. In contrast, C9 and C4 are identified as effect-oriented elements, which are more responsive to changes elsewhere in the framework.

These results validate the strength of the model in differentiating strategic drivers from dependent indicators. In practice, this suggests that decision-makers should focus on maximizing performance in risk management and green financing readiness, while ensuring that supportive social and regional criteria are not neglected, especially in the context of national recovery and just energy transition.

5. Discussions

While ESG integration is widely recognized as essential in project evaluation, our literature review revealed an ongoing lack of consensus in how ESG factors are defined, grouped, and measured. Financial institutions, national governments, and regulatory bodies apply varying standards—many of which overlap, conflict, or fail to account for local realities. For example, global taxonomies tend to emphasize green financing and climate-related metrics but often neglect context-specific priorities such as war-affected region recovery, or social reintegration—which are crucial for Ukraine. This highlights a deeper tension between universal ESG frameworks and national-level sustainability needs.

The proposed groupings of ESG criteria to evaluate energy projects combine different approaches to the sustainable development assessment in an attempt to create a comprehensive model including the maximum number of criteria available. This result is in line with previous studies that revealed the important role of factors other than economic feasibility, as was pointed out in [1].

The idea proposed by [2] to create an index of environmental sustainability of energy projects was further developed to include multiple aspects of ESG criteria to achieve integral assessment of energy projects.

Our findings show that the proposed algorithm, structured around nine clearly defined groups, enables a comprehensive assessment of the energy projects and their rankings according to the economic, environmental, and social components. It confirms the conclusions of [4], as they selected a hybrid decision-making framework from environmental, economic, technical, and social aspects.

The methodology developed in this study helps bridge that gap, but comes with important limitations. The Fuzzy DEMATEL method is well-suited for expert-based analysis under uncertainty; however, it presumes a fixed understanding of which criteria are most influential, which may shift over time as local policies, geopolitical conditions, and institutional priorities evolve. The model also assumes that national or sector-specific ESG factors can be treated independently, but in practice, new or updated regulations may lead to overlaps between criteria or shifts in their systemic influence. Therefore, future versions of the model should include mechanisms to periodically review, update, and realign ESG indicators to ensure continued relevance and avoid redundancy.

6. Conclusions

This study has achieved its objectives by developing a comprehensive ESG-based framework tailored for evaluating energy projects, particularly in Ukraine’s post-war context. The primary goal was to create a scalable and practical model that aligns with both global sustainability standards and Ukraine’s specific recovery and development needs.

Firstly, the relevant ESG criteria applicable to energy sector projects were defined and structured. By integrating international standards with localized requirements, such as social inclusivity for war-affected regions and veteran involvement, this model addresses the unique economic and infrastructural challenges Ukraine faces. This provides stakeholders with a structured approach to assess project sustainability while supporting the country’s rebuilding efforts.

Secondly, a scalable model was created to rank energy projects based on their adherence to ESG standards and potential contribution to long-term sustainability and energy transition. This model allows projects to be evaluated not only on their environmental and social impact but also on governance aspects, enabling a holistic approach to sustainable energy development. The ranking system helps investors and policymakers prioritize projects that align with Ukraine’s strategic goals in energy security, climate action, and socio-economic recovery.

Lastly, the model was adapted to address the specific needs and constraints of Ukraine’s energy sector, reflecting the impact of the war and the country’s rebuilding goals in line with global climate and sustainability objectives. By embedding ESG factors that cater to local socio-economic recovery and regional development, the model ensures relevance to both domestic and international stakeholders, supporting Ukraine’s integration with EU standards.

Regarding the lack of sensitivity analysis, we acknowledge this as a limitation, and provide the following rationale for its exclusion in the current stage:

• The primary objective of this study was to develop and structure the ESG evaluation framework, focusing on criteria definition and causal analysis rather than scenario testing.
• The method already incorporates expert consensus and fuzzy ranges, which serve to buffer uncertainty and variability across judgments.
• Introducing a sensitivity analysis at this stage would require assumptions about real project data or dynamic scenarios, which are more appropriate for future validation studies using actual case applications.

In summary, while the model offers a scalable and context-aware approach to ESG assessment, its long-term effectiveness depends on continuous adaptation to evolving policy, regulatory, and sectoral realities. Future research should focus on validating the model with real investment cases, integrating financial metrics, and exploring the robustness of rankings under variable conditions.