LEE- Enerji Bilim ve Teknoloji-Doktora
Bu koleksiyon için kalıcı URI
Gözat
Son Başvurular
1 - 5 / 15
-
ÖgeFarklı tip metro istasyon modülleri için konfor ve acil durum şartlarının deneysel ve sayısal olarak incelenmesi(Lisansüstü Eğitim Enstitüsü, 2025-06-18)İstanbul, Avrupa ve Asya kıtalarının birleştiği, yüksek nüfus yoğunluğu ve trafik sıkışıklığı ile bilinen büyük bir metropoldür. Şehirde özel araç sayısının ve trafiğin günden güne artması merkezi konumlarda ulaşım sürelerinin uzamasına ve emisyon kaynaklı hava kirliliğine sebep olmaktadır. Karbon emisyonlarının azaltılması, küresel ısınmayla mücadele ve gelecek nesiller için daha yaşanabilir bir dünya sağlamak adına temel hedeflerden biridir. Bu bağlamda, şehir merkezlerinde özel araçlardan kaynaklanan emisyonların azaltılması büyük önem taşımaktadır. Şehrin yaşam standardını yükseltmek ve çevreyi korumak için toplu taşımanın, özellikle raylı sistemlerin geliştirilmesi ve kullanımının artırılması gerekmektedir. Raylı sistem hatlarının kullanımını teşvik etmek için; bu hatların erişimi kolay, hızlı, konforlu, güvenilir, emniyetli ve diğer ulaşım modlarıyla iyi entegre olacak şekilde planlanması gerekmektedir. Şehrin topografik yapısından dolayı İstanbul'daki metro istasyonları çoğunlukla derin olmaktadır. Bu durum, hem yürüme mesafelerini hem de yolcuların istasyonda geçirdikleri süreyi artırmaktadır. Yolcuların istasyonda kalma süresi uzadıkça, istasyon içinde yeterli düzeyde ısıl konfor ve emniyet şartlarının sağlanması yolcu memnuniyeti ve sağlığı açısından daha önemli hale gelmektedir. Bu tez çalışması kapsamında, İstanbul'un en yoğun metro hattı olan M2 Yenikapı-Hacıosman metro hattında bulunan Şişli-Mecidiyeköy ve Gayrettepe istasyonlarında saha ölçümleri ve Bağıl Sıcaklık İndeksi (RWI) hesaplamalarıyla ısıl konfor, Hesaplamalı Akışkanlar Dinamiği (HAD) analizleriyle acil durum yangın konuları incelenmiştir. Şişli-Mecidiyeköy ve Gayrettepe istasyonları M2 metro hattı üzerinde art arda gelmektedir ve peron katları farklı yapım teknikleri kullanılarak inşa edilmiştir. Şişli-Mecidiyeköy istasyonunun peron katı delme tünel, konkors katı ise aç-kapa yöntemiyle inşa edilmiştir. Gayrettepe istasyonunun tamamı aç-kapa yöntemiyle inşa edilmiştir. HAD analizleri için istasyonların ve hatta kullanılan trenin 3 boyutlu katı modeli oluşturulmuştur. Isıl konfor incelemelerinde, Şişli-Mecidiyeköy ve Gayrettepe istasyonları peron ve konkors katlarından ilkbahar, yaz ve sonbahar mevsimleri boyunca her gün sıcaklık ve bağıl nem verileri toplanmıştır. Sıcaklık ve bağıl nem ölçümleri istasyonlarda 2,5 m yükseklikte eşzamanlı olarak gerçekleştirilmiştir. Şişli-Mecidiyeköy istasyonunda peron katında 15, kuzey ve güney konkors katlarında 2'şer olmak üzere toplam 19 noktada, Gayrettepe istasyonunda ise peron katında 13, konkors katında 4 olmak üzere toplam 17 noktada ölçümler yapılmıştır. Hava hızı verileri RWI hesaplamalarında kullanılmak üzere istasyonlarda farklı zamanlarda gerçekleştirilmiştir. Isıl konfor incelemelerinde, istasyonların peron ve konkors katlarında ölçülen sıcaklık ve bağıl nem değerlerinin yüksek olduğu ve genel itibariyle literatürde bulunan ısıl konfor şartlarının istasyonlarda sağlanmadığı belirlenmiştir. Ortalama RWI değerleri, ilkbahar mevsiminde Şişli-Mecidiyeköy istasyonu hariç incelenen tüm mevsimlerde 2 istasyonda da ASHRAE konfor sınıflandırması açısından ısıl konfor şartlarının sağlanmadığını göstermiştir. Ortalama RWI değerleri karşılaştırıldığında ilkbahar, yaz ve sonbahar mevsimlerinin tamamında aç-kapa tip Gayrettepe istasyonunda delme tünel tip Şişli-Mecidiyeköy istasyonuna kıyasla ısıl konfor şartlarının daha kötü olduğu sonucuna varılmıştır. Şişli-Mecidiyeköy istasyonunda yolcuların çoğunluğunun ve Gayrettepe istasyonunda da hemen hemen tamamının özellikle yaz ayında daha serin bir ortam istediği ortaya çıkmıştır. İstasyonlarda ölçülen sıcaklık ve hesaplanan RWI değerlerinin, yakın konumdaki meteorolojik hava ölçüm istasyonundan temin edilen dış hava sıcaklığı verileri ile mevsimsel bazda benzer değişim trendleri gösterdiği belirlenmiştir. Acil durum yangın incelemelerinde, istasyonda tren yangını olayı için farklı senaryolar oluşturularak acil durum havalandırması ve yolcu tahliyesi konuları araştırılmıştır. Şişli-Mecidiyeköy istasyonunda yolcuların peron katını 5,36 dakikada (322 s), istasyonu ise 8,53 dakikada (512 s), Gayrettepe istasyonunda yolcuların peron katını 4,21 dakikada (253 s), istasyonu ise 7,22 dakikada (433 s) tahliye ettiği hesaplanmıştır. Şişli-Mecidiyeköy istasyonunda HAD analizleri sonucunda 6 MW yangın yükü için 4 adet 50 m3/s ve 25 MW yangın yükü için 4 adet 90 m3/s debili tünel havalandırma fanlarının en az tahliye süresi boyunca NFPA 130 standardında belirtilen hava hızı, sıcaklık ve görüş mesafesi kriterlerini sağladığı belirlenmiştir. Şişli-Mecidiyeköy istasyonunda 25 MW yangın yükü orta hızda yangın büyüme eğrisi için uygun sonuç alınan senaryo, aynı tünel havalandırma fan debisi (4 adet 90 m3/s) kullanılarak çok hızlı yangın büyüme eğrisine sahip 25 MW yangın yükü senaryosu için tekrarlanmıştır. Analiz sonucunda sıcak hava ve dumanın daha fanlar devreye girmeden kısa sürede peronu kapladığı ve yolcu tahliyesi açısından risk oluştuğu görülmüştür. Bu sonuç işletmede kullanılacak tren ile HAD analizlerinde kullanılan trenin yangın özellikleri açısından aynı veya benzer olmasının önemini göstermiştir. Şişli-Mecidiyeköy istasyonunda 25 MW yangın yükü için tüm tünel havalandırma fanları egzoz modunda çalıştırıldığında uygun sonuç alınan senaryo (4 adet 90 m3/s), kuzey yönde olan fanlar basma (2 adet 90 m3/s) ve güney yönde olan fanlar egzoz (2 adet 90 m3/s) modunda çalıştırılarak tekrarlanmıştır. Analiz sonucunda sıcak hava ve dumanın yolcu tahliye güzergahında ilerleyerek merdiven bölgesine ve akabinde konkors katına ulaştığı görülmüştür. Analiz edilen egzoz-basma senaryosunun yolcu tahliyesi açısından risk oluşturduğu belirlenmiştir. Gayrettepe istasyonunda HAD analizleri sonucunda 6 MW yangın yükü için 4 adet 120 m3/s debili tünel havalandırma fanlarının tahliye süresi boyunca NFPA 130 standardında belirtilen hava hızı, sıcaklık ve görüş mesafesi kriterlerini sağladığı belirlenmiştir. 25 MW yangın yükü için sadece tünel havalandırma fanlarının çalıştığı senaryolarda başarılı sonuçlar alınamadığı için senaryolara peron altı egzoz fanları da dahil edilmiştir. İlave fanlarla yapılan analizlerin sonuçlarında iyileşme olmakla birlikte dumanın konkors katına ulaşması engellenememiştir. Bu sonuçlar mimari tasarımda bazı iyileştirmeler yapılmasını gerekli kılmıştır. Mimari tasarımda yapılan revizyonla, konkors katının uç noktalarına ve ortadaki merdivenlerin etrafına duvar örülmüştür. İlave olarak merdiven üzerindeki bölümlere tavan kotundan 1 m aşağısına kadar duvar eklenmiştir. Revize edilen mimari tasarım kullanılarak yapılan HAD analizi sonucunda 25 MW yangın yükü için 4 adet 120 m3/s debili tünel havalandırma ve 2 adet 55 m3/s debili peron altı egzoz fanlarının en az tahliye süresi boyunca NFPA 130 standardında belirtilen hava hızı, sıcaklık ve görüş mesafesi kriterlerini sağladığı belirlenmiştir.
-
ÖgeEvidence-based analysis of Türkiye's energy efficiency obligation scheme: sectoral applications, energy poverty, flexibility options and policy implications(Graduate School, 2025-05-05)Energy efficiency is a fundamental pillar of energy transition. It plays a crucial role in enhancing energy security, reducing greenhouse gas emissions, and driving the transition to a low-carbon economy. Among the various policy instruments developed to promote energy efficiency, market-based mechanisms, particularly Energy Efficiency Obligation Schemes (EEOS), stand out for their flexibility, cost-effectiveness, and potential to mobilize private sector participation. With the 2012/27/EU Energy Efficiency Directive (EED), EEOS has become a key policy tool across European Union (EU), where its importance has grown in parallel with rising climate ambition and increasing focus on energy poverty. Following the adoption of the 2007 Energy Efficiency Law, Türkiye introduced a series of legislations and strategic documents aimed at enhancing energy efficiency across all sectors. In alignment with EU EED, Türkiye published its first National Energy Efficiency Action Plan (NEEAP) for the 2017–2023 period, which included the implementation of an EEOS action. However, despite this clear intent, the EEOS was not implemented during the plan period, primarily due to institutional, regulatory, and technical challenges. In 2024, Energy Efficiency 2030 strategy and the second NEEAP reaffirms Türkiye's commitment and schedules the implementation of the scheme by 2027. This Ph.D. thesis aims to contribute to the successful realization of a EEOS in Türkiye through analytical groundwork, policy-oriented modeling, and applied research. Beyond academic contribution, this Ph.D. thesis seeks to offer practical insights for policymakers, support better understanding among potential scheme participants, and serve as a reference for the institutionalization and internalization of the EEOS within Türkiye's energy policy landscape. The primary purpose of this thesis is to provide a comprehensive, evidence-based foundation for the potential implementation of an EEOS in Türkiye. Based on existing international experience and lessons learned, this Ph.D. thesis aims to address the multidimensional requirements of such a scheme, including its sectoral applications, economic feasibility, social equity implications, internal flexibility mechanisms, institutional design, and policy integration. These objectives are pursued through applied, data-oriented and evidence-based research, policy-relevant modeling, and strategic recommendations. The ultimate goal is to support Türkiye in developing a cost-effective, socially inclusive, and institutionally viable EEOS tailored to its national circumstances. The thesis is structured into ten chapters. Chapter 1 introduces the background, motivation, and structure of the thesis. It begins by establishing the critical role of energy efficiency, explains how EEOS emerged, traces its development within the EU framework, and discusses Türkiye's evolving policy landscape. The chapter also outlines the motivation, contribution, and purpose of the thesis. Chapter 2 introduces the EEOS by examining its conceptual foundations, core components, and global evolution as a policy tool. The chapter provides a structured review of international implementation experiences, with particular focus on European countries, and evaluates the academic literature to identify key design considerations, operational challenges, and success factors. By synthesizing lessons learned from both practice and research, the chapter lays the groundwork for understanding how EEOS can be adapted to Türkiye's context, offering early insights into the opportunities and constraints shaping its potential adoption. Chapter 3 presents an ex-ante cost-benefit assessment of a possible EEOS structure for Türkiye, focusing on the industrial sub-sectors and commercial buildings. Within this framework, incumbent electricity suppliers are designated as obligated parties. A two-level distributed optimization model is employed, allowing obligated parties and end-users to independently pursue their economic objectives while preserving market realism. By evaluating various policy scenarios such as different obligation structures, EEOS fee rates, and penalty levels, the chapter offers insights into the financial feasibility, cost distribution, and policy effectiveness of a basic EEOS model. The findings support the conclusion that a self-financing, balanced scheme can be established in Türkiye, provided that design parameters are carefully calibrated. Chapter 4 explores the intersection of energy poverty and EEOS. It begins by distinguishing between fuel poverty and energy poverty, making the case for adopting the energy poverty terminology in the Turkish context. The chapter then traces the historical development of the concept in academic and policy literature, examining key definitions and measurement methods. It continues with a review of international experiences where social concerns have been integrated into EEOS design, highlighting various targeting strategies and associated risks. The chapter also assesses Türkiye's current policy framework and research efforts related to energy poverty, identifying existing gaps and opportunities. By providing a comprehensive understanding of the conceptual, policy, and practical dimensions of energy poverty, this chapter lays a critical foundation for the analyses presented in Chapters 5 and 6. Chapter 5 conducts a comparative assessment of income- and energy expenditure-based definitions of energy poverty to determine their effectiveness in identifying vulnerable households in Türkiye. Drawing on microdata from the Turkish statistical Institute's (TurkStat) 2022 Household Budget Survey, the chapter examines key energy poverty drivers to evaluate how each definition reflects actual deprivation. Furthermore, a simulation of an EEOS-related cost increase in households' energy bills is performed to analyse its potential impact on energy poverty rates under these definitions, incorporating updated energy price dynamics and macroeconomic trends for 2024. The results provide evidence-based insights into the strengths and limitations of each definition and offer critical implications for the equitable integration of energy poverty concerns into a future EEOS framework. Chapter 6 builds upon the previous chapter's findings by proposing a more comprehensive and context-sensitive approach to identifying and targeting energy-poor households within the EEOS framework in Türkiye. Recognizing the limitations of conventional income- and expenditure-based definitions, this chapter develops a custom statistically robust eligibility index using detailed housing and socio-economic data from the TurkStat Survey on Income and Living Conditions. By combining indicators of physical inefficiency, financial difficulty, and regional differences the study categorizes households into three groups (priority energy-poor, at-risk, and regular) using clustering techniques. Finally, the spatial distribution of these groups and their corresponding energy efficiency needs are mapped across Türkiye, offering policymakers a data-driven and geographically informed strategy for equitable EEOS implementation. Chapter 7 expands the discussion by focusing on design elements that can enhance the adaptability, cost-effectiveness, and policy coherence of a potential EEOS of Türkiye. Building on earlier findings, the chapter examines key flexibility mechanisms for compliance (buy-out, banking, borrowing, and saving trading) that allow obligated parties to meet their targets with greater efficiency. In addition to reviewing international practices, the chapter evaluates the applicability and implications of these flexibility options within the context of Türkiye. It then turns to the market-based feature of EEOS, the white certificate schemes, exploring their evolution, institutional typologies, and implementation experiences across Europe. Drawing from these international insights, the chapter proposes a reference framework for Türkiye, outlining how a well-structured white certificate scheme could be integrated into national energy efficiency policy. The framework is designed to reflect Türkiye's institutional capacity and policy context, supporting the launch of a pilot program that is both technically sound and socially equitable. Chapter 8 focuses on the strategic positioning of a potential EEOS within Türkiye's broader energy efficiency policy mix. The interactions between EEOS and other existing policy instruments are discussed through a review of relevant literature, aiming to establish connections with the current policy frameworks in Türkiye. Based on the existing energy efficiency mechanisms and the targets set in Türkiye's Energy Efficiency 2030 Strategy and 2nd NEEAP, an attempt will be made to forecast the future role of the EEOS within the country's broader energy efficiency strategy. Chapter 9 synthesizes the key findings of the thesis and presents forward-looking policy recommendations to inform the design and implementation of an EEOS in Türkiye, building on the analytical results and insights developed throughout the thesis study. Chapter 10 presents the conclusion of the thesis by offering an overall evaluation of the findings, synthesizing insights from previous chapters. The chapter also revisits the main policy recommendations and reflects on their potential to shape Türkiye's energy efficiency agenda. Finally, it outlines possible directions for future research, emphasizing the need for continued empirical work, institutional learning, and policy innovation to ensure the long-term success of EEOS in the national context.
-
ÖgeSiting and sizing of renewable energy supported electric vehicle charging stations along highways with a novel interoperable smart energy management system(Graduate School, 2025-04-14)Electric vehicles (EVs) have experienced rapid growth in recent years, driven by advancements in battery technology and mass production. With global EV sales surging, the demand for electric vehicle charging stations (EVCSs) has risen accordingly. However, the majority of these developments are concentrated in economically developed countries due to the significant costs associated with installing EVCS infrastructure. Economic disparities have also influenced EV and EVCS distribution, with metropolitan areas typically being better served compared to regions with smaller populations. On intercity roads, where drivers prefer time-efficient charging stops, the strategic placement of EVCSs along highways becomes crucial. The increasing adoption of EVs has also brought challenges in meeting rising energy demands. EV batteries, typically ranging from 50 to 80 kWh, place substantial stress on the grid, particularly when multiple vehicles need fast charging simultaneously. Coordinated management of EVCSs is essential to prevent grid overload and ensure efficient resource allocation. Properly sizing charging infrastructure based on traffic patterns and charging behaviors, combined with coordinated energy management, can prevent both undersized and oversized EVCS systems, optimizing both operational efficiency and investment costs. Another major concern is the environmental impact of the growing energy demand for EVs. While EVs are promoted as a greener alternative to internal combustion engine vehicles, their reliance on grids still powered largely by fossil fuels creates a paradox. Integrating renewable energy sources into EVCSs is seen as a solution, but hybrid systems must balance environmental benefits with economic viability. Therefore, multi-objective approaches are needed to create sustainable and practical solutions for EVCS infrastructure. This thesis emphasizes the strategic importance of siting and sizing of EVCSs along highways to facilitate the widespread adoption of EVs and promote sustainable transportation.
-
ÖgeMulti-objective optimization of generation expansion planning considering the diffusion of renewable energy(Graduate School, 2024-12-30)In today's world, energy planning plays a critical role in ensuring sustainable and efficient use of energy. The planning process is essential for maximizing the effective use of limited national resources and reducing the dependence on energy imports. It contributes to the energy security and economic stability. It is also a key factor in reducing the environmental impacts and mitigating the climate change, which has led to a notable increase in renewable energy investments over the past few years. However, as investments in renewable energy increase, the additional electricity costs are inevitably passed on to end users due to the feed-in tariffs required to support these investments. This doctoral study aims to create a roadmap for Turkey for the year 2030 by representing and simultaneously optimizing investors, central decision-makers, as and end user views in objective functions. This approach not only addresses the need for a robust energy infrastructure capable of managing the variability inherent in renewable energy production and demand fluctuations but also emphasizes the necessity of strategic investments in renewable technologies to achieve both stability and feasibility in our energy systems. This doctoral study begins by exploring financial scenario based renewable energy investment trends in Turkey for the year 2030. To address this, an optimization model was developed that minimizes the initial investment cost and the levelized cost of energy plan, while examining the annual distribution of investments. The analysis included a baseline scenario tracking investment trends from past years, an optimistic scenario with annual expenditure values 20% higher than the baseline, and a pessimistic scenario with values 20% lower. According to the results, by 2023, all scenarios indicate that the installed capacity targets for solar photovoltaic renewable energy plants will be met. For wind energy, targets will only be achieved in the optimistic scenario, while for biomass and hydroelectric power plants, targets will not be met under any scenario. Furthermore, it has been observed that in all scenarios, at least 30% of the electricity generated was from renewable sources, achieving this particular target as well. With this study, a new method has been developed to select a solution adapted from multi-criteria decision-making (MCDM) techniques upon obtaining a nondominated set of solutions which allows for the evaluation and scoring of solutions under several criteria grouped into technological, economic, environmental, and socio-political categories. Within the set of optimal solutions, the solution with the highest score is recommended to decision makers as the preferred outcome. Furthermore, the model predicts the optimal timing for future investments in offshore wind farms in Turkey, which are currently not under operation. While offering a solution from a non-dominated set of solutions using multi-criteria decision-making techniques, popular distance-based methods such as VIKOR, TOPSIS, and CODAS were applied in the study. During the application of these methods, a weakness was identified in the distance-based MCDM techniques. These methods assume that the similarity of an intuitionistic fuzzy set to the reference point increases as its distance from it decreases. However, the validity of this assumption was found to be debatable, prompting an innovative shift in the doctoral study towards developing a Hypervolume-based approach as an alternative to the traditional distance-based (geometric) MCDM methods. This method was demonstrated to be effective both as a metric for ranking intuitionistic fuzzy sets and as a robust MCDM technique, laying the groundwork for a novel approach in this domain of multi-criteria assessment of energy resources research. Subsequently, it was recognized that the issues identified with the distance-based MCDM techniques were not limited to intuitionistic fuzzy sets alone; similar challenges arise with other sets when ranking according to the distance from a negative or positive ideal solution. Instead of questioning the robustness and reliability of the methods, we prefer to interpret that different rankings can be obtained depending on whether we view the problem from a positive or negative perspective. Indeed, isn't this akin to how we often make choices or address problems in everyday life, by considering situations from various positive or negative angles which affects our decisions? Next, the research further delves into the energy market by introducing a day-ahead market model that incorporates hourly dispatch to adeptly handle the uncertainties in renewable energy production and energy demand. The initial deterministic model, accounting for hourly dispatch, integrates the perspectives of investors, end-users, and central decision-makers, with objective functions focused on investment payback period, average electricity generation cost, and total investment costs. In addressing the deterministic problem, renewable energy production and demand projections for 2030 are modeled using generative adversarial network structures, with each season distinctly represented by representative weeks. The decision variables have been selected as the investment amounts for renewable energy sources and the appropriate feed-in tariff values. The capacities of conventional resources are calculated within the day-ahead market model and are not treated as decision variables. When the calculated capacity for conventional resources surpasses the existing capacity, it is evaluated as new investment; conversely, if it is less, no new investment is deemed necessary. As a result of these methodological decisions, the complexity of the problem and, consequently, the solution time have been significantly reduced. Furthermore, a scenario-based robust optimization model is created by using the scenarios generated by generative adversarial neural networks. This model employs a robust approach to optimization, seeking to make decisions that perform well under the most adverse conditions anticipated within the defined scenarios, to calculate objective functions including the minimization of the payback period of investments, average electricity generation cost, and total investment costs. A notable distinction between the deterministic and robust results was that decisions on wind energy investments in the robust model were more conservative compared to the deterministic outcomes, while investments in solar photovoltaic facilities increased relative to the deterministic model. If installation costs for solar PV panels reach to the price levels in the Energy Information Administration's new policies scenarios by 2030, considering that the remaining power plants are already near their economically feasible limits, it appears that solar PV will be the predominantly installed power plant compared to wind. As variability in wind energy production increases with additional scenarios, the ability of thermal sources to adapt to the remaining demand becomes more challenging, which in turn impacts the unit electricity price for end-users. Consequently, in the robust model, new investments in wind energy are less favored due to this increased variability. This underscores the variability and risk management inherent in robust approaches, highlighting their potential to adapt to uncertainties in renewable energy frameworks.
-
ÖgeSimulation and life cycle assessment of combined bioheat and biopower plant using hungary oak (Quercus frainetto L.) coppices as a feedstoc(Graduate School, 2024-02-16)Almost zero-emission woody biomass resources are vital for the decarbonization of energy while effectively using them as a product of sustainable forest management in energy production, especially in facilities such as for instance cogeneration plants. In cogeneration facilities, which aim to obtain thermal and mechanical energy simultaneously during the energy production process while producing electrical energy using woody biomass, heat energy is also produced by using some of the heat that emerges as a result of the process. This integrated energy production approach aims to minimize environmental impacts by increasing resource efficiency, thus providing a sustainable energy production model. Cogeneration facilities that use biomass as raw material are collectively called bioheat and biopower facilities. In Turkey's energy sector, the use of woody biomass, especially resources such as oak coppices, which have a significant share in forest assets, is essential in terms of Turkey's 2053 Net Zero Emission Target and sustainable energy production. In this context, the use of woody biomass in Turkey's energy policies will contribute to energy security by increasing diversity among renewables. Obtaining energy from woody biomass promotes sustainable management of biomass resources and enables the formation of a strategy to protect forest ecosystems. Turkey's focus on woody biomass resources such as oak coppices both supports local energy production and demonstrates the ability to lower carbon footprint of energy production processes from biomass. Sustainable management of forest and biomass production's energy intensity make life cycle assessment (LCA) environmentally necessary. LCA in energy production represents a holistic analytical approach that covers all stages of an energy source, namely feedstock extraction, energy production, energy use and waste management processes. Thus, it contributes to minimizing environmental impacts and developing a sustainable energy production model. This methodology provides a perspective on sustainability by assessing environmental, economic and social effects of an energy source from start to finish. First, during the extraction or production of the energy source, factors for instance the use of natural resources and harvesting of biomass are taken into account. Environmental impacts that occur at this stage include elements such as soil erosion, water pollution or biodiversity loss. During the production phase, the processes of processing, refining or transforming the energy source are evaluated. In these processes, factors such as use of energy, greenhouse gas emissions (GHGs) and waste production are examined. Environmental impacts during the production phase generally differ based on the kind of energy source and the technology used. In the usage phase, the consuming of energy resources and the operation of the facilities where energy production takes place are evaluated. Environmental aspects including the energy source's carbon emissions and its impact on the quality of the air and water are included at this stage. In addition, the economic impacts of the energy source, energy costs and employment creation potential are also evaluated. In the waste stage, the processes where the energy production process ends and waste products are managed are examined. It includes environmental and economic factors such as disposal processes, recycling possibilities, waste storage or disposal methods. In this thesis study, the simulation and LCA of a combined heat and power (CHP) plant burning woody biomass was carried out. The study is essential in terms of energy sustainability and covers the three basic dimensions of energy sustainability: energy security, energy equality and energy systems' sustainability in terms of the environment. Turkey's energy outlook, energy production from wood, woody biomass supply chain (BSC), modeling of combined bioheat and biopower (CBHBP) power plants burning woody biomass and analysis of life cycle scenarios of generation of energy from biomass constitute the subheadings of the literature research of the thesis study. As part of the theoretical analysis of this thesis, process simulations were created for four different case studies using Aspen Plus V12.1 software, and together, SimaPro V9.5 software was used in the LCA of nine various scenarios to examine the effects on the environment of the related bioheat and biopower plant process parameters. To characterize the production of bioheat and biopower together, process simulations of cases with 1, 2, 5 and 10-megawatt electricity (MWe) installed power using the technique for producing steam using direct combustion technology and the classical Rankine cycle were created using an eco-design methodology by Aspen Plus V12.1 software. Oak coppice forests, which have a significant share in Turkey's Forest Assets, were chosen as the raw material source of the relevant cases. A raw material sample of Hungarian Oak (Quercus Frainetto L.) was taken from the Oak Coppice forests in Kırklareli, Vize district of the Marmara Region, turned into oak chips and characterized. Bioheat and biopower process simulation outputs were used together in the LCA study. The purpose and the study's scope were determined, inventory analysis was made, and then the life cycle inventory (LCI) with the created scenarios was prepared using SimaPro V9.5 software. The life cycle system boundary that is subject to the thesis begins with the oak coppices harvesting in the forest and ends with the transmission of electricity and heat to the grid. Nine different scenarios were created according to production capacity, supply chain management and waste management system criteria to evaluate how different alternatives for the system would affect the environment and to help with decision-making. In the study, 1 kilowatt-hour (kWh) of biopower and 1 kWh of bioheat were taken for comparisons of functional unit production capacities, carbon footprint and water footprint. For supply chain management comparisons, functional unit was taken as 1 ton of oak chip and 1 kg of oak ash and in the waste management system comparison. To determine environmental impact "ReCiPe 2016 Endpoint (H)/World 2010 (H)" impact assessment method was chosen as the midpoint method, and "ReCiPe 2016 Endpoint (H)/World 2010 (H/A)" impact assessment method was selected as the endpoint method. "IPCC GWP100" method was chosen as the method for carbon footprint calculation and "AWARE" technique was chosen for water footprint calculation. Life cycle comparisons of the scenarios include carbon and water footprint results of all scenarios with midpoint characterization, midpoint normalization, damage assessment, damage assessment by impact category, weighting, single score, and single score results by impact category. The selection of the best scenarios was made by looking at production capacity, carbon footprint, water footprint results, supply chain benchmarking results and waste management results.