Energy Transition Framework for Nearly Zero-Energy Ports: HRES Planning, Storage Integration, and Implementation Roadmap

Abstract

Ports are vital nodes in global trade networks but are also significant contributors to greenhouse gas emissions. Their transition toward sustainable, nearly zero-energy operations require comprehensive and structured strategies. This study proposes a practical and scalable framework to support the energy decarbonization of ports through the phased integration of hybrid renewable energy systems (HRES) and energy storage systems (ESS). Emphasizing a systems-level approach, the framework addresses key aspects such as energy demand assessment, resource potential evaluation, HRES configuration, and ESS sizing, while incorporating load characterization protocols and decision-making thresholds for technology deployment. Special consideration is given to economic performance, particularly the minimization of the Levelized Cost of Energy (LCOE), alongside efforts to meet energy autonomy and operational resilience targets. In parallel, the framework integrates digital tools, including smart grid infrastructure and digital shadow technologies, to enable real-time system monitoring, simulation, and long-term optimization. It also embeds mechanisms for regulatory compliance and continuous adaptation to evolving standards. To validate its applicability, the framework is demonstrated using a representative case study based on a generic port profile. The example illustrates the transition process from conventional energy models to a sustainable port ecosystem, confirming the framework’s potential as a decision-making tool for port authorities, engineers, and policymakers aiming to achieve effective, compliant, and future-proof energy transitions in maritime infrastructure.

1. Introduction

The escalating urgency of climate change and environmental degradation has compelled humanity to reconsider conventional methods of energy production [1,2]. The increased reliance on fossil fuels due to transport significantly contributes to global warming, resulting in the loss of biodiversity and the destabilization of ecosystems [3,4,5]. As the worldwide community increases efforts to transition toward sustainable development, establishing resilient, low-carbon energy systems becomes a priority and an environmental necessity [6,7].

Recent energy crises across the western parts of Europe, including major power disruptions in Portugal, Spain, and France, highlight the vulnerability of power grids and the urgent need to diversify energy production sources. These events are reminders that the current infrastructure may not be sufficient to manage ever-growing energy demands, climate-induced stresses, and geopolitical instabilities [8]. In this context, HRES, which integrate multiple renewable sources with energy storage solutions, offer a promising pathway toward energy sustainability, emissions reduction, and enhanced energy security [9,10,11,12]. At the same time, sufficient ESS can have a crucial role in avoiding these types of shutdowns by providing backup power, stabilizing the supply, and managing fluctuations in energy generation [13].

In alignment with these goals, green energy, derived from inherently renewable and non-polluting sources, has emerged as a cornerstone of sustainable development strategies worldwide. Unlike conventional technologies that may still rely on carbon-based inputs, green energy solutions such as solar, wind, and hydroelectric power present clean alternatives that drastically reduce greenhouse gas emissions (GHGs) throughout their lifecycle [14]. Promoting the large-scale deployment of green energy is essential for meeting climate targets, while at the same time fostering energy independence, stimulating green economies, and safeguarding public health through reduced air and water pollution [15].

Beyond the need for reliable power production, there lies a broader responsibility to design energy systems that uphold long-term environmental stewardship. This includes reducing ecological footprints, conserving natural resources, and advancing technologies that operate within planetary boundaries. The integration of battery storage with renewable sources such as solar and wind energy can further increase system flexibility. Such implementation enables effective load balancing, demand-side management, and minimizes dependence on fossil-fuel-based backup generation.

Within this broader context, ports represent important infrastructures that are both energy-intensive and uniquely positioned to lead the sustainability transition [16]. As major logistical hubs supporting international trade, they operate around the clock and have substantial energy needs, making them ideal testbeds for innovative, sustainable energy solutions. Implementing HRES and battery storage in port settings mitigates the risks of power interruptions and exemplifies how critical sectors can drive decarbonization efforts, serving as influential models for society [17].

In pursuit of this transformation, the concept of nearly zero-energy ports (nZEPs) has emerged as a forward-looking framework that combines local renewable energy production, advanced storage systems, and optimized grid interaction to achieve minimal net energy consumption [18]. These ports aim to balance their operational energy needs with clean, on-site generation while improving energy autonomy and resilience. Although the vision of nZEPs aligns closely with climate and energy policy objectives, practical implementation remains limited and underexplored [19].

To address critical challenges and emerging opportunities in port decarbonization, this paper proposes a comprehensive framework for systematically integrating HRES and battery storage within port infrastructures. The ultimate goal is facilitating the transition toward nearly zero-energy, sustainable port operations. Anchored in interdisciplinary principles, the framework consolidates essential design parameters, operational strategies, and energy management practices that collectively support environmental, economic, and technical sustainability [20]. By prioritizing adaptability, efficiency, and long-term scalability, the proposed model contributes to global sustainable development objectives and offers both a conceptual foundation and a practical roadmap for real-world implementation. This work fills a significant gap in the current literature and supports the broader systemic transformation required for achieving low-carbon, resilient maritime infrastructures [21].

The structure of this paper follows a clear and systematic approach to the development of the proposed framework. The second section provides a critical overview of the existing literature, identifying current limitations and research gaps related to sustainable energy integration in port infrastructures. The third section outlines the methodology, detailing the conceptual foundation, design principles, and key components that inform the construction of the framework. The final section discusses the framework’s potential applications, emphasizing its relevance, adaptability, and contribution to future developments in the field of sustainable port energy systems.

2. State of the Art

This section provides a comprehensive overview of the state of the art in key areas relevant to achieving sustainable and energy-efficient port operations. This section delves into state-of-the-art principles and advancements in green energy technologies, strategies for carbon neutralization, the benefits and challenges of hybrid renewable energy systems, and the crucial role of energy storage. Finally, we integrate these concepts by discussing their specific application within port infrastructure, culminating in the concept of nearly zero-energy ports (nZEPs), which serve as a foundational framework for our proposed approach, and expand into the current literature gaps.

2.1. Green Energy

Green energy consists of energy sources that are renewable and naturally replenished, such as solar radiation, wind, hydropower, geothermal heat, and biomass. These alternatives offer a means to reduce GHG emissions and decrease dependency on fossil fuels. While advancements in technology have accelerated the deployment of green energy solutions worldwide, questions remain about their scalability and adaptability in diverse regional contexts, especially in low-resource environments [22].

At the intersection of environmental sustainability and energy production lies the challenge of creating systems that are not only clean but also socially and economically inclusive. True sustainability involves more than just reducing carbon emissions. It also calls for fair energy access, long-term economic viability, and minimal ecological disruption. However, many green energy projects overlook local community impacts or contribute to land use conflicts and resource extraction issues. These concerns point to a need for more holistic sustainability frameworks that integrate social and environmental equity into energy planning [23].

Technological innovations have enhanced the efficiency and cost-effectiveness of renewable energy systems, particularly in solar photovoltaics, wind turbines, and energy conversion technologies. Yet, the complex nature of many of those renewable resources continues to challenge the reliability and stability of power grids in which they are incorporated, especially in regions with outdated infrastructure. The development of robust energy storage solutions and smart grid technologies seems essential to fully leverage the potential of green energy, but current research often falls short in addressing how these innovations can be deployed [24].

Decentralized green energy systems are increasingly seen as a promising approach to enhancing the resilience, accessibility, and sustainability of energy supply. Unlike centralized grids that rely on large-scale infrastructure and long transmission distances, decentralized systems distribute energy generation closer to the point of consumption rather than overproducing. This model can support rural electrification, reduce transmission losses, and allow communities greater control over their energy resources. Technologies such as rooftop solar panels, small-scale wind turbines, and microgrids are enabling such initiatives. However, despite their potential, decentralized systems often face regulatory, technical, and financial barriers, particularly in integrating with national grids and ensuring long-term reliability. Research remains limited on scalable frameworks that can support the widespread deployment and governance of decentralized energy systems across diverse socioeconomic contexts [25,26].

Frameworks supporting the integration of renewable energy technologies into distributed systems have gained attention as a means to enhance the adaptability and resilience of green energy applications. These approaches often incorporate multiple energy sources and emphasize system coordination, control, and performance evaluation to optimize energy delivery in diverse contexts. Such frameworks contribute to the broader effort of enabling sustainable, decentralized energy solutions that are both technically viable and responsive to local energy needs [27].

While these challenges persist, the principles of decentralized green energy systems, with their focus on resilience and local control, are particularly relevant for port environments, offering a pathway to reduce reliance on conventional energy sources and enhance energy independence within this critical infrastructure.

2.2. Carbon Neutralization

Carbon neutralization has become a necessity in the context of conventional energy production, particularly where fossil fuels remain integral to electricity generation. Technologies such as carbon capture and storage and the use of low-carbon fuels are being developed to reduce or offset emissions from coal- and gas-fired power plants. These approaches allow for a reduction in net carbon output without requiring the immediate decommissioning of existing infrastructure. Such solutions are vital for transitional periods. However, they often involve high costs, complex implementation, and uncertain long-term effectiveness, especially in large-scale applications. As a result, there remains a research need to assess their role in decarbonizing conventional power systems in a way that aligns with goals [28].

With the increasing shift toward renewable energy sources, the reliance on carbon neutralization mechanisms in energy production is expected to diminish. Solar, wind, and hydroelectric systems generate power with minimal direct emissions, thereby reducing the need for carbon removal techniques. However, renewable energy systems (RES) are not entirely without carbon impact. Emissions can arise from manufacturing, transport, and maintenance processes, as well as the variability of renewables, which may lead to continued reliance on backup fossil-based generation. Additionally, the integration of renewables into existing grids can pose operational and regulatory challenges. These factors underline the importance of ongoing research both in improving the efficiency and resilience of renewable systems and in developing clear criteria for when carbon neutralization remains necessary within sustainable energy frameworks [29,30].

Frameworks addressing carbon neutralization have expanded beyond technical emissions reduction strategies to encompass systemic and ecological approaches. Recent studies have highlighted the need for integrated models that consider environmental thresholds, carbon cycling, and long-term sustainability goals. These frameworks emphasize the balance between anthropogenic emissions and ecosystem capacities, offering broader perspectives on achieving net-zero targets through both technological and natural solutions [31].

For port infrastructures, which often rely on a mix of energy sources and face significant emissions from both stationary operations and vessel activity, these broader frameworks for carbon neutralization are crucial in developing comprehensive strategies to achieve net-zero targets.

2.3. Hybrid Renewable Energy Systems

HRES’s ability to combine multiple energy production sources allows for a more stable and efficient energy supply, making them key to both off-grid applications and grid support in low-carbon energy transitions. However, to fully leverage their potential, intelligent management and control strategies are essential. The use of advanced methods and algorithms, such as genetic algorithms (GAs) and other evolutionary or heuristic methods, has become increasingly important in managing energy flow, predicting demand, and dynamically adjusting system behavior [32]. Such approaches contribute to greater operational efficiency and reliability but require further development to handle real-time variability and large-scale implementation challenges effectively [33].

Beyond operational controls, the correct sizing and configuration of HRES components, such as photovoltaic arrays, wind turbines, and auxiliary generators, is critical to achieving economic sustainability and technical viability. Oversizing leads to unnecessary capital costs, while undersizing can compromise system reliability and energy security. Multi-objective optimization techniques are commonly applied to balance trade-offs between cost, performance, and environmental impact. Such models often rely on idealized input data or simplified assumptions. Improving sizing methodologies to incorporate uncertainty, load forecasting, and location-specific resource profiles remains an open research area. A more comprehensive optimization approach could significantly enhance the long-term sustainability and resilience of hybrid renewable energy systems [34].

As renewable energy systems evolve, growing attention is being directed toward frameworks that account for both external and internal operational influences. These include regulatory conditions, environmental pressures, technological innovation, as well as organizational processes and workforce capacity. Research has highlighted the importance of integrating these multifaceted factors into structured models that guide the production and management of renewable energy. Such frameworks aim to enhance performance stability, ensure operational resilience, and support decision-making in complex energy environments [35].

This increasing emphasis on holistic planning and advanced management strategies is directly reflected in the growing number of HRES implementations within diverse industrial settings, including the maritime sector. These real-world applications demonstrate how ports are actively exploring and deploying tailored HRES solutions, combining various renewable sources with sophisticated energy management systems to meet their unique energy demands and accelerate decarbonization efforts [33].

Applying these advanced optimization and management frameworks to hybrid renewable energy systems within ports is paramount for optimizing energy flows, ensuring reliability, and adapting to the unique operational demands and spatial constraints of maritime environments.

An examination into the feasibility of HRES further delves into these considerations, specifically looking at systems combining solar, wind, hydrogen, and biofuel energy in remote, off-grid locations. This investigation highlights the critical role of hydrogen energy for backup supply and the significant environmental advantages of such configurations, including zero CO₂ and SO₂ emissions [36].

2.4. Energy Storage Systems

ESS are essential for improving the stability and reliability of renewable energy production. This can be achieved particularly in hybrid systems where intermittent sources like solar and wind must be balanced against fluctuating demand. They enable time-shifting of energy use, provide grid services like frequency regulation, and reduce reliance on fossil-based peaking units. However, the performance, lifespan, and environmental impact of various storage technologies differ significantly. Many ongoing research studies seek to optimize storage selection and configuration based on application context, cost, and long-term sustainability [37].

Effective integration of ESS into energy systems relies heavily on advanced energy management systems (EMS), which coordinate generation, storage, and consumption in real time. Modern EMS architecture increasingly incorporates predictive algorithms, demand forecasting, and machine learning models to manage distributed resources efficiently [38,39]. In hybrid renewable energy systems, EMS must dynamically respond to varying resource availability, user load patterns, and market signals while ensuring system reliability and economic performance. Despite these advances, many EMS models still struggle with scalability, interoperability, and adaptability to complex, multi-source systems [40,41]. Future research must address these limitations by developing modular, intelligent, and decentralized EMS solutions that can adapt to different operational scenarios and facilitate the transition to more autonomous and resilient energy networks [42].

The development of ESS has become increasingly vital to addressing the intermittency and variability associated with renewable energy sources. Emerging frameworks focus on evaluating storage technologies across a range of performance, cost, and environmental criteria to guide their integration into sustainable energy systems. These approaches aim to support informed decision-making by assessing the suitability of various storage solutions under different operational conditions, ultimately contributing to the reliability and flexibility of low-carbon energy infrastructures [43].

For port infrastructures seeking to integrate intermittent renewable sources and provide shore power, the intelligent deployment of ESS through advanced EMS is fundamental to ensuring a stable, reliable, and sustainable energy supply, thereby facilitating their decarbonization efforts.

2.5. Port Infrastructure

Ports, as hubs of industrial activity and high-energy consumption, face significant pressure to reduce GHG emissions, both from stationary operations and from vessels during docking. Integrating renewable energy sources, such as solar and wind generation, shore energy (cold ironing), and energy storage systems, into port infrastructure is a growing focus. These efforts aim to reduce reliance on diesel generators and other conventional energy uses, improve air quality, and align with international maritime emission regulations. However, the deployment of green technologies in port environments poses challenges related to space constraints, fluctuating energy demand, and the need for robust grid integration. Further research is required to develop scalable, cost-effective solutions tailored to the operational complexity of ports and to establish standard frameworks for green port design and energy management [44,45].

The development of climate-resilient port infrastructure frameworks has become increasingly critical in addressing the vulnerabilities posed by climate change to maritime operations. Emerging methodologies focus on evaluating infrastructural resilience across a range of environmental, operational, and economic criteria to guide their adaptation within sustainable maritime systems. These approaches aim to support informed decision-making by assessing the suitability of various adaptation strategies under different climatic scenarios, ultimately contributing to the robustness and sustainability of global port infrastructures [46].

A case study along the Caspian Sea evaluated hybrid photovoltaic and wave energy systems in three Iranian ports, revealing promising energy output levels and identifying cost-effectiveness as achievable under reduced energy subsidies. Broader frameworks, such as decision guidance systems and flexible optimization models, although not exclusive to ports, have been developed to design cost-optimal, resilient HRES configurations adaptable to complex, high-demand environments like maritime terminals [47,48,49]. Additionally, advanced monitoring systems leveraging IoT and SCADA platforms are being developed to ensure the reliable operation and integration of these hybrid systems, underscoring the growing maturity of HRES technologies for port applications [50].

2.6. Nearly Zero-Energy Ports

nZEPs represent an advanced model for transforming port infrastructure into highly efficient, low-to-zero emission energy ecosystems. These systems aim to minimize net energy consumption through the on-site generation of renewable energy and the implementation of intelligent energy distribution strategies. Central to this approach is the integration of hybrid RES, including solar-, wind-, and hydrogen-based technologies, alongside energy storage and shore-side electrification. These technologies work together to significantly reduce fossil fuel dependency and emissions from both port operations and berthed vessels. The nZEP concept aligns with broader decarbonization goals, encapsulating many of the challenges and solutions discussed in previous sections, such as energy variability, carbon neutralization, and grid integration, into a single, application-focused framework [51].

Beyond energy production, nZEPs emphasize the importance of advanced energy management systems for real-time monitoring, demand forecasting, and load balancing. Accurate component sizing, lifecycle optimization, and flexible operational control are all crucial to ensuring the reliability and cost-effectiveness of such systems. Intelligent algorithms, such as evolutionary and machine learning-based methods, are increasingly applied to optimize energy flows and adapt to changing conditions, supporting resilient and autonomous operation. By addressing environmental, technical, and operational dimensions simultaneously, the nZEP framework demonstrates how ports can serve as practical testbeds for comprehensive, sustainable energy transition strategies. This integrative approach not only decarbonizes a high-impact sector but also provides a replicable model for other complex, energy-intensive infrastructures [52].

Despite the compelling conceptual advantages and growing global interest, the widespread realization of nZEPs across the maritime sector remains largely in its nascent stages, with most initiatives focused on pilot projects and strategic planning rather than comprehensive, full-scale deployment. While early efforts demonstrate technical feasibility and the potential for significant decarbonization, their broader implementation faces a range of complex, interconnected barriers [41]. These prominently include substantial financial hurdles due to high capital expenditure and long return on investment periods. Overcoming stakeholder resistance and achieving effective coordination among diverse port entities and users is another significant challenge. Furthermore, technical complexities related to integrating intermittent renewable energy sources with existing port and national grid infrastructure, particularly concerning grid stability and capacity, often require innovative solutions. Other common impediments involve spatial constraints within often-congested port areas for large-scale renewable generation, and the absence of fully developed, harmonized regulatory and policy frameworks. Addressing these multifaceted practical challenges is essential for translating nZEP concepts from promising demonstrations into widely adopted, scalable solutions, thereby underscoring the necessity of robust frameworks designed to navigate these complexities and facilitate their practical implementation [52].

2.7. Research Gaps

In light of the technological, environmental, and regulatory challenges identified throughout this review, it becomes clear that there is a pressing need for a unified, adaptable framework tailored to the energy transition of port infrastructure. Notably, there is limited literature that focuses on the development of a comprehensive, step-by-step framework guiding the transformation of ports into nZEPs across all stages of the process. This paper seeks to address and fill these research gaps, ranging from hybrid system optimization and energy storage integration to intelligent energy management and policy alignment, by translating these insights into a scalable, actionable solution (

Table 1. Summary of the most relevant articles containing HRES frameworks in comparison with our study’s novel contribution (full table included in Appendix A).

Ref.	Focus Area	Summary	Our Novel Contribution
[22]	Green Energy	Evaluates seven green energy strategies using novel impact and sustainability ratios.	Applies theoretical metrics to real port infrastructure, integrating simulation, IoT monitoring, and transition pathways for nZEP.
[23]	Green Energy	Reviews energy sources and technologies for sustainable building energy use.	Bridges sustainability principles with port-specific implementation (digital shadows, smart systems, real-time energy management).
[24]	Green Energy	Explores challenges and advancements in microgrid control architectures (inverter-based systems).	Extends microgrid control to a medium-scale port with real-time EMS, digital shadows, and RES/ESS integration.
[25]	Green Energy	Explores decentralized renewable energy systems for mitigating geopolitical conflicts and environmental degradation.	Translates decentralized green energy benefits to port operations via integrated RES, smart tech, digital monitoring, and stakeholder engagement.
[26]	Green Energy	Empirical evidence on fiscal decentralization’s influence on carbon emissions via renewable energy transition.	Demonstrates on-ground application of renewable transitions in port operations through localized assessment, coordination, and digital monitoring.
[27]	Green Energy	Proposes an integrated framework for hydrogen-assisted, fuel cell-based renewable energy applications.	Applies integrated design/simulation to a Mediterranean port with digital shadowing, real-time EMS, and stakeholder planning.
[28]	Carbon Neutralization	Explores carbon capture and storage (CCS) for CO2 emission mitigation.	Advances emission prevention at the source through integrated renewable generation, electrification, and smart load management in ports.
[29]	Carbon Neutralization	Quantifies renewable energy development’s impact on carbon emission intensity.	Applies renewables’ emissions-reducing potential to port microenvironments via real-time energy management, digital twins, and hybrid systems.
[30]	Carbon Neutralization	Evaluates cost-efficiency and emissions reduction potential of electricity generation technologies.	Extends comparative analysis to practical port context with integrated solar, wind, ESS, EMS, and digital shadowing.
[31]	Carbon Neutralization	Highlights MOF-based materials for effective carbon dioxide capture.	Explores MOF-based carbon capture within HRES, emphasizing impact on system efficiency and sustainability.
[41]	HRES	Optimizes hybrid renewable energy systems in seaports for cost efficiency, autonomy, and sustainability.	Combines HRES with smart EMS and ESS for real-time operational efficiency and carbon mitigation in smart port design.
[34]	HRES	Reviews advancements in hybrid renewable energy systems focusing on sizing, optimization, and control.	Introduces an empirically validated optimization framework for real-time port operations, demonstrating applied benefits of HRES, ESS, and EMS.
[35]	HRES	Presents a framework for identifying factors influencing renewable energy production using the SCOR model.	Expands operational focus by embedding advanced control and real-time optimization in a live hybrid renewable energy system for ports.
[37]	ESS	Reviews historical evolution and operating principles of energy storage systems for renewable energy integration.	Implements and evaluates ESS in a real-time hybrid renewable energy setup, demonstrating practical performance in port applications.
[42]	ESS	Reviews optimization techniques for energy management in microgrids (forecasting, scheduling, control).	Demonstrates real-world implementation of a unified EMS combining renewable integration, storage optimization, and dispatch in a port.
[43]	ESS	Proposes a game-theoretic energy storage sharing framework for prosumers.	Implements an integrated EMS-ESS framework managing storage for cost optimization and system-wide stability in a port.
[44]	Port Infrastructure	Reviews modern seaport electrification: RES integration, digitalization, energy-efficient infrastructure.	Applies a real-time optimization framework uniting HRES, ESS, and EMS to quantify techno-economic benefits in port operations.
[45]	Port Infrastructure	Analyzes energy efficiency practices in European ports through green port principles.	Quantifies impact of integrated HRES, ESS, and EMS on reducing energy costs and emissions, offering a scalable framework for green ports.
[53]	Port Infrastructure	Techno-economic analysis of hydrogen-based HRES and cold ironing for port decarbonization.	Implements a broader HRES optimization framework with real-time EMS and ESS, demonstrating flexibility in managing energy flows.
[46]	Port Infrastructure	Develops a climate risk assessment framework for port infrastructure adaptation.	Complements climate adaptation by integrating HRES, ESS, and EMS to create resilient, low-emission port energy systems.
[51]	nZEP	Reviews renewable energy solutions and smart systems for nearly zero-energy ports.	Operationalizes nZEP via GA-based optimization of HRES, ESS, and EMS for real port conditions, achieving cost/emission reductions.
[54]	nZEP	Evaluates cold ironing and hydrogen-based renewable systems for zero-emission, energy-autonomous ports.	Extends hydrogen-based autonomy by incorporating HRES-ESS-EMS optimization for flexible, cost-effective, real-time energy management.
[55]	nZEP	Compares HRES and storage configurations in grid-connected ports, analyzing dispatch strategies.	Enhances dispatch strategy evaluation via GA-driven framework dynamically optimizing HRES, ESS, and EMS under real constraints.
[52]	nZEP	Methodological framework for transforming Rethymno port into an nZEP.	Expands discussion by applying real-time HRES and EMS to optimize operational efficiency under dynamic demand, going beyond static modeling.

). By embodying the principles of an nZEP, this framework prioritizes sustainability, operational autonomy, and replicability, serving both the specific port in which it is deployed and acting as a reference model for broader global adoption. In doing so, it contributes to international decarbonization efforts and the promotion of green energy practices across maritime and industrial sectors. This paper represents an initial step toward developing and validating such a framework, aiming to bridge current knowledge gaps and support the transition of ports into resilient, future-proof energy ecosystems.

2.8. Novel Contribution of Our Work

The novel contribution of this research lies in the practical application and integration of theoretical green energy principles within the complex, real-world context of port operations. This study moves beyond abstract sustainability metrics and high-level frameworks by developing and implementing a holistic system combining HRES, ESS, and advanced EMS. Utilizing a methodology grounded in simulation-based design, IoT-driven monitoring, digital shadowing, and stakeholder-informed planning, this research demonstrates a tangible pathway towards achieving nZEP operations. This work effectively operationalizes sustainability ratios into concrete design, implementation, and real-time optimization strategies specifically tailored for decentralized energy systems and maritime electrification.

This study bridges the critical gap between conceptual sustainability goals and domain-specific, on-ground implementation. By tailoring energy-efficient and renewable integration strategies to the unique operational and infrastructural demands of a medium-scale port, general conservation and emission-reduction ideas are transformed into targeted, functional solutions. The presented approach uniquely incorporates advanced, real-time EMS and digital shadows, driven by a genetic algorithm-based optimization, to manage HRES and ESS effectively. This methodology ensures not only significant reductions in emissions and energy costs but also enhances operational resilience, autonomy, and efficiency, thereby providing a validated, data-driven framework.

Ultimately, this research extends the existing body of knowledge by demonstrating a replicable and scalable model for decarbonizing critical maritime infrastructure. It showcases how the integration of smart technologies, renewable resources, and optimized control strategies can achieve measurable environmental and operational benefits. By translating theoretical advantages into a functioning, techno-economically modeled system, this study offers a practical blueprint for implementing national and international energy goals at vital logistical nodes, establishing that sustainable, resilient, and nearly zero-energy port operations represent an attainable reality.

3. Methodology

A structured framework is outlined to support the transition of port facilities toward nearly zero-energy operations and the broader idea of green energy decarbonization. Such a framework does not limit its focus to integrating hybrid renewable energy systems. Instead, it adopts a holistic approach that attempts to transform the studied port into a more sustainable and resilient infrastructure. The initial stage of the framework involves a detailed assessment of the port’s current situation, including a comprehensive analysis of energy consumption patterns and a technical evaluation of the existing electrical systems. Establishing this baseline is essential for identifying key problems and inefficiencies while determining the readiness of the current infrastructure for future energy system upgrades.

Following this, the framework assesses the renewable energy potential of the port area by analyzing the availability of local natural resources such as solar, wind, and marine energy. This analysis is based on datasets and site-specific conditions [56,57]. A technology prioritization process is then employed to determine the most suitable renewable energy solutions, taking into account multiple criteria, including resource availability, technical feasibility, and environmental impact [58,59].

The next phase involves the design and optimization of integrated energy systems that combine multiple renewable energy sources with storage and management capabilities [60,61]. Energy simulations are conducted using specialized software to model energy flows, optimize configurations, and evaluate performance under various operational scenarios. In parallel, digital shadow technologies are introduced to mirror the port’s energy systems by collecting and analyzing real-time data. In the next stage, a digital shadow provides a unidirectional, real-time data replica of physical systems [62,63]. This allows for enhanced monitoring, operational insights, and data-driven decision-making, without actively controlling the system. A smart grid infrastructure is also developed to enhance communication between energy production and consumption while enabling flexible, demand-driven energy distribution [64].

Finally, the methodology includes a thorough economic and environmental assessment to evaluate financial viability and quantify reductions in GHG emissions for both the current and upgraded port infrastructure. It also ensures compliance with relevant policies and regulations and incorporates mechanisms for continuous monitoring, adaptation, and long-term improvement. These steps, demonstrated in Figure 1, rely on a clear understanding of the port’s existing operational and energy conditions, which serve as the critical reference point for shaping appropriate interventions and guiding the progression of the overall framework.

3.1. Baseline Assessment: Energy Demand and Infrastructure

A comprehensive baseline assessment forms the foundational phase of the proposed framework, serving as the reference point for all stages of the analysis and design. Figure 2 begins by establishing the port’s current energy profile. This involves a thorough examination of existing energy demand patterns, consumption trends, and associated operational characteristics [20]. The goal is a precise understanding of energy utilization across various port zones, such as container terminals, administrative buildings, cold storage units, lighting systems, and cargo handling equipment. Historical energy consumption data, including peak demand periods, seasonal variability, and dependency on fossil fuels, are all considered to construct a clear and accurate energy baseline [65].

In parallel, an in-depth assessment of the port’s existing electrical infrastructure is conducted. This technical evaluation covers key components such as transformers, substations, electrical wiring networks, energy distribution systems, and control units. Analysis of their reliability, capacity, age, and current condition identifies inefficiencies, limitations, and modernization needs. Understanding these technical constraints and the potential of the current infrastructure is essential for determining the feasibility of integrating renewable energy technologies and upgrading the port toward nearly zero-energy operations [66].

A structured engagement process with port authorities and relevant stakeholders is initiated to collect necessary datasets and technical documentation (Figure 3). This involves formal requests, participation in organized seminars and workshops addressing energy transition, and technical consultations with port engineers, energy managers, and infrastructure planners. These interactions facilitate access to crucial data, including load profiles, utility bills, infrastructure schematics, and maintenance records. Concurrently, secondary sources such as academic research, government publications, and institutional reports are reviewed to complement and verify direct findings. When needed, access to sensitive or unpublished material is negotiated through formal agreements or confidentiality arrangements. This combined approach of formal communication, technical consultation, and targeted research ensures both data availability and analytical accuracy throughout the baseline assessment phase.

Following data acquisition, a systematic and organized data storage strategy is implemented. All collected information is categorized into well-structured datasets corresponding to specific energy usage or infrastructure components. Furthermore, data is segmented by defined time periods, such as daily, monthly, or seasonal intervals, to detect trends, fluctuations, and recurring patterns. This temporal organization is critical for understanding the port’s operational behavior and identifying any inefficiencies or anomalies. Proper data labeling and classification facilitate comparative analysis across different functional zones or timeframes, ensuring information is ready for in-depth analysis and interpretation, and supporting evidence-based decision-making on the port’s current energy performance and potential intervention areas [67].

By establishing a clear and comprehensive understanding of the port’s current energy demand and infrastructure status, this baseline assessment provides the necessary foundation for all subsequent stages of the framework. It enables the identification of technical constraints, operational inefficiencies, and opportunities for energy optimization or integration of renewable technologies. With the data properly structured and insights derived, the next phase, focusing on energy resources analysis and the collection of renewable energy potential data, can proceed with confidence.

If Internet of Things (IoT) technologies are employed effectively during the baseline assessment phase, they can provide continuous, real-time data collection on energy consumption, equipment performance, and infrastructure status [68]. This streamlines the monitoring process, reduces dependency on manual data gathering, and enhances the precision of operational insights. While traditional data acquisition methods and stakeholder consultations remain valuable, particularly for historical context, infrastructure evaluation, and strategic alignment, they may become supplementary rather than essential [69]. However, these conventional methods can still serve as useful validation tools, supporting the accuracy of IoT-derived data and enriching the overall robustness of the baseline assessment [70].

3.2. Renewable Energy Potential Assessment

The second phase of the framework focuses on assessing the renewable energy potential of the port, forming a critical component in designing a low-carbon and nearly zero-energy system (Figure 4). This begins with systematic identification and preliminary assessment of all viable renewable energy sources available within or around the port area. These may include solar, wind, biomass, marine energy, or geothermal options, depending on the port’s geographical and environmental context. This step aims to establish a clear understanding of the types of renewable resources that can be realistically harnessed based on their local availability [71].

Following the initial identification, a comprehensive data collection process is initiated to evaluate the performance and potential of each energy source (Figure 5). This process combines both live field testing and the analysis of historical data to ensure reliability and accuracy. Field measurements may include solar irradiance monitoring, wind speed and direction logging, or temperature and humidity tracking, depending on the energy source in question [72]. Where field testing is not feasible due to technical, legal, or financial constraints, the assessment relies on data from secondary sources. These include publicly accessible databases, institutional repositories, reports from relevant organizations, and datasets provided by stakeholders or research institutions. Reputable sources such as European Union energy data portals and national environmental agencies offer valuable live and long-term datasets that enhance the robustness of the analysis.

The integration of real-time and historical data allows for cross-verification, reducing the risk of relying on incomplete or biased datasets. Once sufficient data has been collected and validated, the next step involves evaluating the feasibility and suitability of each energy source. This is achieved through a structured assessment process that identifies the most promising technologies in terms of availability, scalability, operational efficiency, and economic viability within the port environment [73].

To support evidence-based decision-making, a multicriteria analysis is applied to compare and rank the identified renewable energy technologies [74]. This analysis incorporates both quantitative and qualitative factors, focusing specifically on the technical constraints, environmental impact, cost-effectiveness, policy support, and compatibility with existing infrastructure of the proposed renewable devices and systems [75]. Following the multicriteria analysis, the most promising energy sources are subjected to a second layer of validation through targeted literature review. This step ensures that the selected technologies are cross-checked for economic viability, long-term sustainability, and real-world applicability. Past research, regional case studies, and documented port transition projects are examined to reinforce the credibility of the selected options [76]. Specialized software tools, ranging from dedicated multicriteria analysis (MCA) platforms to advanced optimization algorithms like genetic algorithms (GAs), support this process by enabling scenario simulations and sensitivity analyses, while benchmarking against similar geographic and operational contexts helps verify the suitability of the recommended technologies and strengthens the overall strategic foundation.

3.3. System Design and Optimization

Following the assessment of the renewable energy potential, this phase involves the detailed design of a HRES according to the port’s energy requirements (Figure 6). The process begins with the selection of specific renewable energy generation technologies corresponding to the sources identified in the previous phase. This selection follows a structured multi-step approach. First, for each viable energy source, a pool of commercially available technologies is identified, including technical specifications such as efficiency, rated power, lifetime, and operational constraints (Figure 7). Then, compatibility with the port’s environmental and spatial conditions is assessed. The third step involves benchmarking the shortlisted technologies against similar case studies from ports or industrial facilities with comparable demand profiles and climatic conditions. Past device choices, their performance, and lessons learned are critically examined to identify best practices and avoid design inefficiencies. This step-by-step filtering process ensures that the chosen RES technologies are context-appropriate, scalable, and practically deployable [77].

In parallel, the selection of ESS technologies is carried out through a similarly structured methodology (Figure 8). The process starts with an analysis of the expected generation patterns from the selected RES devices and the energy demand profiles of the port based on historical consumption data gathered during the baseline assessment. Key parameters such as daily load curves, seasonal consumption trends, and critical load periods are examined to determine the storage needs in terms of capacity, power output, and response time. Based on this analysis, candidate storage technologies, such as lithium-ion batteries, flow batteries, or hybrid storage systems, are evaluated against criteria including efficiency, degradation rate, round-trip energy losses, depth of discharge, cost per kilowatt-hour, and lifetime. Additionally, the suitability of each storage technology is tested against the port’s operational needs, such as peak shaving, backup capability, or grid services like frequency regulation. Case studies are once again consulted to review which ESS technologies have proven effective in similar applications. This ensures that the final selection is not only technically sound but also supported by practical evidence from real-world implementations [78].

Once the system components have been selected, the next step involves the simulation of the integrated HRES and ESS using specialized software tools. Software such as HOMER Pro, or alternatively custom-developed simulation codes, are employed to model the performance of the system under varying conditions [79]. These simulations provide insights into energy generation, storage behavior, system efficiency, and overall feasibility, taking into account weather variability, load fluctuations, and system degradation. To further enhance system design, optimization algorithms, such as GA or other heuristic methods, are applied to determine the ideal number and configuration of components. These algorithms aim to minimize cost, maximize efficiency, and ensure that energy production and storage are optimally aligned with the port’s energy demand profile [80].

The result of this phase is a fully defined, optimized system design that integrates renewable energy generation and storage in a balanced and technically sound configuration. This design serves as the foundation for technical planning, and eventual implementation, and ensures that the proposed solution is both practical and performance-driven within the context of the selected port case study [81].

3.4. Digital Shadow and Smart Technologies

Following the design and simulation of integrated energy systems, the framework progresses to the implementation of physical and operational upgrades aligned with long-term sustainability objectives (Figure 9). This phase focuses on the transformation of the port’s infrastructure through the deployment of technologies and systems that reduce environmental impact, enhance energy efficiency, and enable cleaner operations.

Key interventions include the introduction of cold ironing facilities [82], allowing for docked vessels to shut down onboard fossil-fuel engines and draw electricity directly from the port’s renewable-powered grid [83,84]. Additionally, a gradual transition of port machinery and transport fleets, such as cranes, container movers, and service vehicles, towards electric or hybrid alternatives is initiated. This shift is supported by the installation of electric charging stations strategically located throughout the port to accommodate the increased energy demand and ensure operational continuity [85,86].

Complementary EMS are deployed to oversee and coordinate the generation, storage, and distribution of energy across all port operations [87,88]. These systems leverage real-time data to balance loads, forecast demand, and optimize the use of renewable sources and storage assets. Other sustainable solutions may include advanced water and waste management systems, green building initiatives, and low-carbon logistics strategies that further reinforce the port’s environmental performance [89].

To ensure a secure, efficient, and adaptable implementation of these solutions, a comprehensive digital shadow of the upgraded port infrastructure is developed (Figure 10). This digital shadow replicates the operational behavior of the physical systems through continuous real-time data collection and analysis. Enabled by IoT, this digital layer provides the necessary connectivity and data acquisition capabilities to monitor a wide range of operational assets and conditions. While it does not control physical assets directly, it enables simulation of potential events, predictive analytics, and evaluation of various transition scenarios [67]. This capacity allows for stakeholders to test the effects of system changes, maintenance strategies, and emergency responses in a virtual environment before deploying them in the real world, thereby mitigating risk and supporting smoother, safer transitions [90,91].

This phase establishes the physical and digital backbone for a future-proof, low-carbon port. It also lays the groundwork for continuous innovation and improvement through the integration of advanced analytics, stakeholder feedback, and adaptive policy mechanisms [70,92,93].

3.5. Techno-Economic and Environmental Impact Analysis

This phase of the framework provides a detailed evaluation of the economic and environmental implications of transitioning the port’s infrastructure and operations toward sustainability. It involves a dual-layered analysis: first, a comparison of the current port configuration with the proposed HRES and associated infrastructure upgrades; second, a projection of the resulting environmental benefits, particularly in terms of GHG emission reductions.

3.5.1. Cost Simulation and Economic Comparison

The economic assessment begins with a detailed simulation of the current operational costs of the port, taking into account energy consumption patterns, fuel usage, maintenance, and infrastructure depreciation over a defined time horizon. Using data gathered in earlier simulation phases, the Levelized Cost of Energy (LCOE) is calculated for the current energy mix, which predominantly relies on conventional fossil-fuel sources (Figure 11).

Parallel to this, a cost model of the optimized port configuration, integrating HRES, ESS, electrified machinery, and supporting infrastructure, is developed [94]. This model includes capital expenditures for technology acquisition and infrastructure retrofitting, operational expenditures, and projected maintenance costs. It also reflects energy production forecasts derived from HRES simulations from previous steps, adjusted according to local resource availability, seasonal variability, and system efficiency [95].

A comparative analysis is conducted between the two configurations, evaluating LCOEs, total lifecycle costs, and payback periods. The analysis also quantifies cost optimization percentages, offering insights into the long-term economic benefits of decarbonization despite potentially higher upfront investment [96]. This cost/benefit analysis is essential for stakeholders evaluating the financial viability of the transition [97,98].

To evaluate the HRES, the energy payback period (PP), the internal rate of return (IRR), net present value (NPV), and the return on investment (ROI) are used. The PP quantifies the time required for the cumulative annual cash inflows to recover the initial investment. The IRR represents the discount rate at which the net present value of all cash flows from a project equals zero, indicating the project’s profitability. Lastly, the ROI measures the gain or loss generated on an investment relative to the amount of money invested. These metrics are calculated by considering the initial investment (C_init), the annual cash inflow (C_af), the nominal annual cash flow for the baseline (C_af,ref), and the project lifetime (n_pro). Additionally, the capital cost (C_cap) of the initial/current system and the baseline’s capital cost (C_cap,ref) are factored into the assessment [99,100].

$$PP={\displaystyle \frac{C_{init}}{C_{af}}}$$

(1)

$$NPV=0={{\displaystyle \sum }}_{t=1}^T{\displaystyle \frac{C_t}{{\left(1+IRR\right)}^t}}-C_0$$

(2)

$$ROI={\displaystyle \frac{{{\displaystyle \sum }}_{I=0}^{n_{pro}}{C}_{af,ref}-C_{af}}{n_{pro}\left(C_{cap}-C_{cap,ref}\right)}}$$

(3)

3.5.2. Greenhouse Gas Emissions Assessment

In parallel, the framework performs a GHG emissions assessment for both the existing and optimized port systems (Figure 12). The current port accounts for emissions from direct fuel combustion, energy imports, and equipment operation. Emissions intensity is calculated based on the carbon footprint of the energy sources used and the efficiency of current systems.

For the optimized scenario, emissions are projected based on the energy produced from renewable sources, accounting for the embedded emissions in the manufacturing, installation, and lifecycle of HRES and ESS technologies. Additionally, emissions associated with electrified machinery, port vehicles, and auxiliary services, powered by clean electricity, are evaluated. Infrastructure-level changes such as cold ironing, which reduce emissions from berthed vessels, are also incorporated into the analysis.

The assessment includes a lifecycle emissions comparison for both configurations and highlights the expected percentage reduction in GHG emissions. This reduction is linked directly to the decarbonization of energy supply, improved energy efficiency, and reduced reliance on fossil fuels [101].

This step provides an integrated view of the port’s financial and environmental performance, demonstrating how strategic investment in renewable energy and electrification can lead to cost savings and significant reductions in GHG emissions over time. It supports evidence-based decision-making for stakeholders while ensuring alignment with broader sustainability and climate goals.

The environmental impact of the HRES is quantified using the CO₂ equivalent (CO₂,eq) index, which accounts for GHG emissions. This index is calculated using the most recent Global Warming Potential (GWP) factors provided by the Intergovernmental Panel on Climate Change (IPCC) for a hundred-year timeframe. The carbon footprint (CF) for each suggested technology, specifically photovoltaic panels (PVs), wind turbines (WTs), and ESS, and for the electricity grid, is determined (

Table 2. Carbon footprint factors and installed capacity emissions for various technologies.

Technologies	Electricity Grid	PV	WT	LAB ESS
CF factor 2	2250	37.3	40	24,250 1

Per kw of systems installed capacity ¹; [gCO₂, eq/kWh] ².

). This calculation considers the emissions of various pollutants along with their respective GWP factors. These emissions, both direct and indirect, correspond to the technology’s lifecycle [102]. The CF is measured in gCO₂, eq/kWh, representing the amount of CO₂ equivalent emitted per kilowatt-hour of energy produced [103,104]. The calculation also incorporates the electricity grid’s carbon footprint, which is based on factors related to primary energy conversion, the characteristics of diesel consumption, and the mix of fossil fuels versus renewable energy sources [99,105,106].

$$Emissions\left({\displaystyle \frac{tn}{y}}\right)={\displaystyle \frac{E_{grid}\left(\frac{kWh}{y}\right)\times PollutantIndex\left(g\frac{C{O}_{2eq}}{kWh}\right)}{{10}^6}}$$

(4)

$$C{F}_S={\displaystyle \frac{{{\displaystyle \sum }}_{y\in GHG}\times GW{P}_y\times E{M}_y}{E_P}}$$

(5)

$$C{F}_{DS}=F_{PE}\times F_D\times F_{FF}=0.989\times 0.785=0.776kg{\displaystyle \frac{C{O}_{2,eq}}{kWh}}$$

(6)

$$NetEnergy=E_{grid}-E_{PV}-E_{WT}$$

(7)

3.6. Policy and Regulatory Compliance

Ensuring alignment with national and international policy frameworks is a critical component of the port’s transition toward an nZEP (Figure 13). This phase of the methodology evaluates the extent to which the proposed upgrades and operational changes comply with existing environmental regulations, energy transition strategies, and sector-specific sustainability mandates. It also outlines the mechanisms necessary to maintain compliance throughout the transition process and beyond [107].

The framework is benchmarked against relevant climate action policies, including national decarbonization roadmaps, maritime and transport sector emission reduction targets (e.g., IMO MARPOL Annex VI), renewable energy integration guidelines, and international agreements and regulations (e.g., policies stemming from the EU Green Deal and its ‘Fit for 55’ package) [108,109].

To achieve full regulatory compliance, the methodology incorporates early-stage policy analysis and stakeholder consultation during the planning and simulation phases. This ensures that all proposed interventions are not only technologically feasible but also legally viable. During implementation, continuous engagement with regulatory bodies supports real-time alignment with evolving standards and facilitates permitting, reporting, and certification procedures.

A key enabler of compliance in this framework is the integration of IoT technologies, which allow for real-time data collection across a wide range of infrastructure elements. IoT-connected sensors and devices enable continuous environmental and operational monitoring, supporting dynamic compliance tracking and responsive system adjustments. These technologies feed directly into the port’s energy management systems and contribute to the automated generation of reports aligned with regulatory metrics.

Furthermore, the framework embeds a system of ongoing monitoring and adaptive management to ensure that compliance is maintained over time. The synergy between IoT infrastructure and the digital shadow environment enables simulation of policy impacts, stress testing of regulatory scenarios, and proactive adjustments based on predictive insights. This digital–physical integration supports a more resilient and responsive regulatory posture [110].

By systematically addressing regulatory compliance, the framework ensures that the nZEP transition is not only technically and economically viable but also institutionally robust. This enhances the credibility of the port’s decarbonization strategy, reduces legal and operational risks, and positions the port as a leader in sustainable and regulation-aligned maritime infrastructure development.

3.7. Continuous Monitoring and Improvement

Although not strictly mandatory for the successful completion of the port’s transition to an nZEP, continuous monitoring and improvement represents a critical enabler for long-term sustainability, resilience, and operational excellence. This phase focuses on establishing systems and practices that ensure the port remains adaptable, data-driven, and aligned with evolving technological, environmental, and regulatory conditions (Figure 14).

Following the implementation of sustainable infrastructure and systems, a structured monitoring framework is deployed. This framework leverages data generated from sensors, smart meters, and energy management systems across the port to track key performance indicators related to energy efficiency, emissions, operational performance, and system reliability. These metrics provide real-time feedback and support evidence-based decision-making for optimization and future upgrades [111,112].

To provide concrete examples, key performance indicators (KPIs) monitored in this framework include (1) energy consumption per ton of cargo handled, (2) CO₂ emissions per TEU (twenty-foot equivalent unit), (3) the percentage of energy derived from renewable sources, (4) equipment availability rate, and (5) vessel turnaround time. System evaluations are proposed to be conducted quarterly, using performance dashboards that visualize these KPIs, alongside detailed reports that summarize trends and deviations from targets. Annual audits are also performed to ensure long-term compliance and identify areas for strategic improvement.

A core component of this phase is the synthesis and interpretation of operational data to identify patterns, inefficiencies, and emerging risks. By continuously analyzing this data, port operators and stakeholders can implement targeted interventions, such as fine-tuning equipment operation, reallocating resources, or updating energy distribution strategies, to maintain high performance and minimize resource waste [113,114].

Furthermore, the use of the digital shadow plays a significant role in ongoing optimization. It allows for virtual testing of proposed adjustments, technology integrations, or policy changes before they are introduced physically, thereby reducing risk and enhancing system agility. This digital layer supports proactive improvement rather than reactive correction.

To sustain progress, the port also establishes periodic review cycles where environmental, economic, and technical performance is assessed against predefined benchmarks. These reviews can inform the recalibration of objectives, the introduction of emerging technologies, and the adoption of revised best practices.

Ultimately, while this step is not required for the initial transition, it is essential for maintaining relevance, ensuring future-proof operations, and reinforcing the port’s role as a dynamic, sustainable, and forward-looking node within the global maritime network [115].

3.8. Summary of Methodological Framework

In summary, this study’s Methodology Section presents a structured, multi-phase framework designed to guide the transition of port infrastructure toward nearly zero-energy operations (Figure 15). Beginning with a thorough assessment of existing energy conditions and progressing through renewable potential analysis, system design, and the integration of digital tools and smart infrastructure, each step has been methodically developed to build a comprehensive and adaptable roadmap. The framework emphasizes not only technical and economic viability but also policy compliance and long-term environmental impact.

By concluding with an optional yet impactful phase of continuous monitoring and improvement, the framework ensures that sustainability does not end with implementation but evolves through informed, data-driven decision-making. Together, these interconnected steps form a coherent foundation for decarbonizing port operations and support the broader goal of establishing resilient, future-ready maritime infrastructure.

While the proposed framework offers a structured technical and economic roadmap, its successful application assumes a minimum level of stakeholder cooperation. Conflicts such as space use competition or resistance to reallocation of financial resources may limit implementation unless mitigated through prior consensus-building. The framework allows for methodological flexibility (e.g., using secondary data where direct access is constrained) but it does not resolve institutional unwillingness or define governance models, which remain context-dependent.

4. Discussion and Results

To evaluate the practical use of the proposed framework, a representative case study is conducted using the Port of Souda, located in Chania, Greece (Figure 16). These maps show actually the Greek area and the actual port’s area. The Greek words are the names of the cities accompanied with their English names. This port has been selected due to its mid to small-sized operational scale; its diverse range of activities, including passenger, commercial, and other naval and maritime operations; as well as its geographic suitability for renewable energy implementation. The case study applies the structured framework outlined in the Methodology Section to assess the potential for transitioning the port toward an nZEP, using realistic energy demand estimates, infrastructure characteristics, and environmental conditions derived from the literature.

It is important to note that the use of literature-based data and assumptions means that the results do not represent an exact analysis of the existing Port of Chania. Actual figures, particularly cost estimates and energy consumption patterns, may vary due to differences in market conditions, infrastructure specifics, and operational practices. The purpose of using literature values is to demonstrate how the proposed framework can be applied in a practical setting, especially in cases where direct access to real-time data from stakeholders or local authorities is limited or unavailable. This approach ensures that the methodology remains accessible and replicable for future research applications.

By implementing each step of the framework, from baseline assessment and renewable potential evaluation to integrated system design, infrastructure upgrades, and digital modeling, the transformation pathway for the Port of Souda is systematically demonstrated. This allows for a holistic examination of the port’s decarbonization potential, considering technical, economic, and regulatory factors. The outcomes not only validate the framework’s practical applicability but also provide insights into the feasibility, benefits, and challenges of enabling such an energy transition in maritime infrastructure.

4.1. Baseline Assessment

The initial step following the port’s selection involves the identification of its current energy profile and infrastructure. The port’s energy demand is utilized to determine consumption patterns and trends, which can be obtained either through stakeholder engagement with port authorities and leveraging IoT, or through a review of the existing literature. In the case study presented, the latter approach is adopted to ensure that future researchers applying the proposed framework can access reliable data without the need for extensive fieldwork and communication with stakeholders and port authorities. Accordingly, the energy demand data for the Port of Souda was assessed using available literature sources, allowing for the construction of a representative energy profile.

Hourly demand data analysis reveals variability in consumption patterns throughout the year. Visualization of the dataset through graphs indicates that energy usage is not evenly distributed (Figure 17 and Figure 18). Higher energy consumption is observed during nighttime hours, while overall consumption decreases during the summer months and increases in winter. This fluctuation in energy consumption occurs due to extended nighttime durations in winter, leading to higher usage of lighting infrastructure and especially port lamps.

For the evaluation of the port’s existing electrical infrastructure, IoT technologies can again offer valuable insights. However, in smaller or non-centralized ports, limitations in IoT deployment may dictate supplementary communication with local authorities to gain a comprehensive understanding of infrastructure conditions. In this case study, infrastructure data for the Port of Souda was gathered through a combination of IoT-derived insights, literature review, and verification through direct communication with local port authorities.

Souda’s infrastructure primarily consists of basic operational elements such as ticketing stations, lighting systems, and administrative facilities. As a medium-to-small-scale port, its infrastructure remains limited. There is minimal to no integration of renewable energy sources, aside from isolated pilot programs that do not constitute systematic RES deployment. Furthermore, advanced sustainability-oriented technologies, such as cold ironing systems or EMS, are currently absent. This indicates potential for future upgrades and energy transition interventions.

Upon completion of this initial assessment, the collected data are systematically archived in categorized folders to ensure efficient access and future usability. Key features of each dataset are highlighted, and the emerging patterns and trends stated are clearly documented, forming the foundation for the following stages of analysis and design

4.2. Renewable Energy Potential Assessment

Following the initial phase of the baseline assessment, the next step in the framework involves the evaluation of renewable energy potential. This phase focuses on identifying and analyzing the locally available RES that can be harnessed to support the port’s infrastructure and administrative energy needs. For the island of Crete, and specifically the Port of Souda, several renewable alternatives can be considered. Among them, solar, wind, and wave energy present the most promising options. At the same time, tidal energy potential in the Mediterranean region is generally low, except for specific locations, and thus is not a viable solution for this case. Additionally, wave energy, while attractive, remains largely unexplored in Crete and lacks the necessary technological maturity and data availability to be practically assessed at this stage.

Given these limitations, the focus of this case study is placed on solar and wind energy, both of which are extensively deployed and well-documented in Greece, particularly on the island of Crete [116,117,118]. Once these RES options are identified, the next task involves data collection to assess their viability for deployment in the port area. As with the energy demand analysis, the data for solar and wind resources are gathered from the existing literature and reputable European Union websites known for providing accurate data (Figure 19 and Figure 20). This approach is taken to facilitate reproducibility and ease of access for future research efforts, as field testing and field implementation of sensors may not be a viable solution in data collection for every research approach [119,120,121].

Following data collection, a validation process is conducted to ensure both the reliability of the sources, assumed credible due to their inclusion in the academic literature, and the technical potential of the selected RES in meeting the port’s energy demands. This validation is carried out using simulation tools such as HOMER Pro, where the collected data are input to evaluate energy generation performance against the port’s demand profile. Additionally, a custom Python 3.12 is developed to verify the outputs and provide further insight into the technical feasibility of the results. This dual approach strengthens the robustness of the analysis.

While multicriteria decision analysis methods, such as ELECTRE or more advanced techniques, can be employed for RES selection when multiple alternatives are under consideration, in this case the options are limited to solar and wind. Therefore, a simplified evaluation approach is sufficient. However, in future studies that include more diverse technologies, such as wave or tidal energy, the implementation of multicriteria decision analysis frameworks may prove valuable for selecting the optimal mix based on technical, economic, and environmental factors.

The final stage of the renewable energy potential assessment involves benchmarking the selected RES against similar applications in other ports. Wind and solar are among the most widely used RES in port decarbonization projects, offering a rich body of literature for comparative analysis. When compared with analogous implementations, it becomes evident that the wind and solar potential in Crete, and the broader Mediterranean region, is among the most favorable, particularly when these sources are integrated into hybrid systems. Although, on occasion, their standalone performance may fall short in comparison to that observed in other global regions, the combined use of wind and solar in Crete demonstrates strong viability for sustainable energy transition.

4.3. System Design and Optimization

Following the assessment of renewable energy potential, the next critical phase of the proposed framework involves the design of the HRES. The initial step in this process is the selection of appropriate RES and ESS technologies, tailored to the specific characteristics and operational profile of the selected port.

Beginning with the RES component, a comprehensive technology review is conducted to evaluate available market options for both PV panels and WT. Approximately ten commercially available technologies are initially shortlisted for each RES category. These technologies are assessed based on technical specifications, such as efficiency, rated capacity, operational thresholds, and cost per kilowatt-hour (kWh). A comparison of their advantages and limitations is then performed to ensure compatibility with the port’s environmental and operational conditions.

For instance, deployment of small wind turbines in a region with consistently high wind speeds may pose mechanical and safety challenges, while selecting PV panels that are not optimized for the local solar irradiance profile could lead to suboptimal performance. Therefore, matching the technologies to the renewable energy potential identified in the previous assessment stage of the port is essential for ensuring system effectiveness and long-term reliability.

In the context of the Souda Port case study, the final RES technologies selected were the Longi Solar LR-60PH PV panel (LONGI Solar Technology Co., Xi’an, China) for the solar component and the EW16 Thetis wind turbine (Eunice Group, Maroussi, Greece) for wind energy generation (Table 3 and Table 4). These technologies were deemed most compatible with the site’s conditions and offered a favorable performance-to-cost ratio. However, the costs used in the case study will differ from the original figures, as they are based on the literature values for the technologies. This approach ensures that future research can be conducted using solely literature-based data in cases where direct engagement with market stakeholders proves challenging [122].

A parallel process is followed for selecting the ESS technology. The first step involves estimating the port’s storage requirements by analyzing the energy consumption data obtained in the baseline assessment. Specifically, the desired autonomy period, defined as the duration the port must operate independently in the absence of RES or grid support, is set at 8 h. To determine the necessary storage capacity, an 8 h rolling sum is calculated across the full hourly energy demand dataset collected. This value represents the total energy that must be available to ensure uninterrupted port operation during power outages.

To enhance system resilience and battery health, only 50% of the total storage capacity is allocated for regular day-to-day operation. The remaining 50% serves as a reserve, activated during unexpected shortfalls in RES output or grid power availability. This design approach ensures longer battery life, accommodates safe charge/discharge cycles, and avoids energy wastage or undersupply during high-demand periods.

Further, the ESS’s charge and discharge power capacities are selected to exceed both the hourly RES generation and port demand. This guarantees that the system avoids curtailment during energy surpluses and meets consumption needs during supply deficits. After defining the required storage characteristics, the available literature and commercial technologies are reviewed for technical alignment and operational reliability. Existing case studies using similar specifications are also used to validate the feasibility of the selected configuration.

For the Souda Port case study, the chosen ESS technology is the Galaxy 3420 ESS (FFD Power, Brescia, Italy), offering a total storage capacity of 3421 kWh (Table 5). This solution meets the defined autonomy, power, and operational safety requirements.

To ensure the replicability and transparency of the proposed framework, the cost values associated with the selected PV, WT, and ESS technologies are sourced from the existing literature. This approach allows for other stakeholders and researchers to adapt the framework for similar applications. Specifically, the cost for solar PV systems is considered to range between EUR 650 and EUR 930 per installed kilowatt, wind turbines are estimated at approximately EUR 2790 per kilowatt, and the energy storage systems are evaluated at around EUR 200 per kilowatt-hour. These standardized references support fair benchmarking and facilitate comparative analysis across different implementation scenarios.

It is important to note that while specific technologies were selected for this case study, the associated costs and simulation parameters are based on literature-derived data rather than direct market quotations. This intentional approach enhances the transparency, replicability, and adaptability of the proposed framework, making it applicable for broader research and feasibility assessments in similar contexts.

Once the RES and ESS technologies are selected, the next step involves simulating the integrated HRES to evaluate its performance and viability. Tools such as HOMER Pro and custom-developed Python algorithms are employed for this purpose. These simulations help analyze the dynamic interactions between energy generation, storage, and consumption, while also identifying potential operational challenges.

Additionally, a GA-based optimization process is implemented to determine the most efficient configuration of RES components. This ensures that the system design not only meets energy demand reliably but also does so with optimized cost-effectiveness and resource allocation.

Through this integrated simulation and optimization phase, the final HRES design for the Port of Souda is validated, demonstrating its potential to support the port’s transition toward a more sustainable and autonomous energy model [123,124].

Table 3. Longi Solar LR-60PH PV specifications [125].

Parameter	Value
Power per module (kW)	0.31
Optimal operating temperature (°C)	40
Efficiency (%)	19
Lifetime (y)	25
Temperature power coefficient (%/°C)	−0.038

Table 3. Longi Solar LR-60PH PV specifications [125].

Parameter	Value
Power per module (kW)	0.31
Optimal operating temperature (°C)	40
Efficiency (%)	19
Lifetime (y)	25
Temperature power coefficient (%/°C)	−0.038

Table 4. EW16 Thetis WT specifications [126].

Parameter	Value
Rated power (kW)	54
Rated wind speed (m/s)	12
Minimum sufficient wind speed (m/s)	3
Maximum wind speed (m/s)	20
Hub height (m)	22.03
Lifetime (y)	25
Efficiency (%)	90

Table 4. EW16 Thetis WT specifications [126].

Parameter	Value
Rated power (kW)	54
Rated wind speed (m/s)	12
Minimum sufficient wind speed (m/s)	3
Maximum wind speed (m/s)	20
Hub height (m)	22.03
Lifetime (y)	25
Efficiency (%)	90

Table 5. Galaxy 3420 ESS specifications [127].

Parameter	Value
System capacity per unit (kwh)	3421
Efficiency (%)	86
Cycles	≥8000
Rated voltage (V)	3.2
Charging current (A)	150
Discharging current (A)	150

Table 5. Galaxy 3420 ESS specifications [127].

Parameter	Value
System capacity per unit (kwh)	3421
Efficiency (%)	86
Cycles	≥8000
Rated voltage (V)	3.2
Charging current (A)	150
Discharging current (A)	150

The energy output of the selected RES, along with the charge and discharge profiles and the state of charge (SoC) of the ESS, is illustrated in Figure 21, Figure 22 and Figure 23. These visualizations provide a comprehensive overview of the hybrid system’s operational behavior under real or simulated conditions. They reveal how renewable generation fluctuates over time, how the ESS responds to these variations by storing excess energy or supplying it when needed, and how the overall system maintains a balance between supply and demand. This dynamic interaction underscores the system’s effectiveness in enhancing energy reliability, optimizing resource utilization, and reducing dependence on conventional power sources. The figures also help identify periods of surplus or deficit energy, offering valuable insights for future optimization and control strategies.

In parallel, the simulation and optimization processes deriving from the HOMER PRO software v3.16 and custom Python-based GA code, the results of which are shown in Figure 24, propose an ideal configuration comprising approximately 396 kW of PV capacity and 60 kW of WT capacity (

Table 6. HRES optimal configuration based on the GA optimization.

Technology	Installed Capacity
PV (kW)	396
WT (kW)	60

). This configuration ensures optimal resource utilization while maintaining the required energy security and autonomy for port operations.

Additionally, a series of monthly boxplots, each aligning with RES monthly energy production, illustrate how the HRES has been optimized to meet the port’s energy demand profile (Figure 25 and Figure 26). These plots highlight the system’s capacity to maintain stable operation, particularly in providing up to 8 h of autonomous functionality in the absence of renewable generation or grid support. The results underscore the effectiveness of the implemented HRES in ensuring reliability, resilience, and sustainability in port energy management.

4.4. Digital Shadow and Smart Technologies

Following the design and simulation of the HRES, the next step in the port’s transition toward sustainability involves the implementation of sustainable infrastructure and smart electrified technologies. This phase extends beyond simply covering energy demand through renewable sources and focuses on the practical modernization of the port’s facilities to reduce its overall environmental footprint and improve operational efficiency.

It is important to note that the electrification of port equipment and mobility systems leads to an increase in overall energy demand. This shift not only raises the baseline load but also makes modifications in the distribution of energy consumption throughout the day. To address this anticipated escalation in demand, adjustments were made during the earlier stages of system modeling and forecasting. Specifically, the energy demand dataset used for simulation purposes was deliberately oversized in selected intervals to reflect the probable impact of full-scale decarbonization measures. This proactive approach ensured that the HRES design and capacity planning can accommodate future operational loads, maintaining both performance reliability and long-term scalability.

One of the primary objectives in this phase is the decarbonization of port operations by replacing conventional fuel-based machinery and vehicles with electric alternatives. This includes the electrification of port cranes, cargo-handling trucks, and administrative vehicles, as well as smaller maritime machinery and personal transport systems such as electric scooters and bicycles. The incorporation of bike-sharing stations, designated bike lanes, and electric vehicle charging stations throughout the port enhances both accessibility and sustainability in daily operations.

A critical element in reducing the carbon footprint of maritime traffic is the implementation of cold ironing, or shore power, for both transport and cruise ships. This technology enables ships to shut down their engines while docked and draw power directly from the port’s electrical grid, significantly reducing emissions and noise pollution during berthing. These interventions are not purely theoretical but are aligned with practices observed in other leading case studies and sustainable port initiatives globally and are actively proposed within the scope of this research for the Port of Souda.

To ensure optimal operation and coordination of energy production, storage, and consumption, the deployment of an advanced EMS is essential. The EMS has a vital role in balancing the load demands of the port with the variable output of renewable energy sources, ensuring efficiency, reliability, and system resilience. The framework was demonstrated using a medium-scale port to ensure methodological clarity and data accessibility. However, its structure is modular and parameter-driven, allowing for adaptation to larger and more complex port systems. In such contexts, additional modeling layers—such as multi-terminal load profiling, logistics subsystem coordination, and multi-nodal grid integration—can be appended without altering the core methodology.

In the context of this case study, a custom-developed Python-based EMS was created, incorporating a GA for dynamic optimization. This system specifically addresses nighttime energy management, a critical challenge given the absence of solar generation during these hours. The EMS allows for the battery storage system to strategically charge from the grid during off-peak hours, when electricity prices are significantly lower (e.g., LCOE: EUR 0.20/kWh at night versus EUR 0.36/kWh during the day). Simultaneously, it enables the use of stored energy during peak demand periods, enhancing the port’s energy autonomy and minimizing energy wastage.

Furthermore, a digital shadow of the port’s energy infrastructure was established using simulation tools such as HOMER Pro and the custom Python code mentioned. This digital shadow serves as a real-time testing and monitoring platform, allowing for researchers and engineers to simulate system modifications and evaluate their outcomes before physical implementation. The digital shadow continuously monitors changes in both energy demand and renewable output, enabling predictive modeling and proactive system adjustments. The combined use of GA optimization and EMS integration within this digital environment supports robust decision-making and system stability.

The integration of these sustainable technologies and smart systems forms a comprehensive operational portfolio that supports the Port of Souda’s transformation into an nZEP. Through the electrification of equipment, implementation of cold ironing, adoption of EMS tools, and the development of a digital simulation framework, this case study demonstrates a clear path toward sustainability. These measures provide a solid foundation for future expansions, scalability across other Mediterranean ports, and long-term strategic planning aligned with international climate and energy objectives.

4.5. Techno-Economic and Environmental Impact Analysis

The techno-economic and environmental impact analysis builds upon the actions undertaken in the system design and optimization phase, where the primary objectives of the optimization process were to minimize the LCOE and reduce carbon emissions. This chapter presents and analyzes the results of that process, offering a comprehensive assessment of both the economic and environmental outcomes.

4.5.1. Cost Simulation and Economic Comparison

The first part of this analysis focuses on the economic aspects, beginning with an evaluation of the current operational costs and the existing LCOE of the port. Subsequently, the cost model applied during the optimization stage is assessed in detail. This includes the projected costs of HRES production, as well as the capital and operational expenditures associated with both the RES and the ESS. These components are critical in determining the financial feasibility of the port’s transition to a sustainable energy model.

As a result of the optimization process, the port’s LCOE was recalculated to reflect the expected performance of the newly designed HRES. The updated LCOE is demonstrably lower than the current value justifying the transformation from an economic perspective. Using the custom-developed Python-based GA, several key economic indicators were extracted, including the new LCOE, payback period, initial capital investment, and operational cost savings.

Finally, a detailed comparative analysis is conducted between the existing and the optimized LCOE values. This comparison quantifies the improvement achieved through the optimization process, providing a clear demonstration of the economic progress associated with the port’s transformation. The resulting insights serve to validate the proposed system configuration and underline the financial viability of implementing a hybrid renewable energy system at the Port of Souda. In

Table 7. Key economic indicators for the current port.

NPC (EUR)	4,070,367
LCOE (EUR/kWh)	0.360
Total grid supplied energy (kWh/year)	874,623.636

and

Table 8. Key economic indicators for the nZEP.

NPC (EUR)	1,867,930
Initial capital (EUR)	1,407,888
LCOE (EUR/kWh)	0.1424
Total grid supplied energy (kWh/year)	98,850
Total RES supplied energy (kWh/year)	774,713
Payback period (years)	5.041

, the key economic indicators of the optimized port configuration are presented alongside those of the current port setup, enabling a direct comparison of the financial performance before and after the implementation of the HRES.

4.5.2. Greenhouse Gas Emissions Assessment

The second part of this section focuses on the assessment of GHG emissions. In this analysis, the emissions associated with both the current port operations and the optimized system are calculated to enable a thorough comparison. For the current port, total annual CO₂ emissions were 1967 tn/year, which were reduced to 325 tn/year in the optimized nZEP configuration. This clearly illustrates the significant reduction achieved through the transition to an nZEP, highlighting the environmental benefits of the proposed system and its contribution to cleaner, more sustainable port operations. All emission calculations were conducted using the custom-developed GA-based Python code, ensuring consistency with the optimization methodology employed throughout the study. Notably, the optimized configuration results in a GHG emissions reduction of approximately 83.48% compared to the baseline scenario, equating to an absolute decrease of 1642 tn per year. This quantifiable improvement underscores the effectiveness of the implemented measures in advancing the port’s decarbonization objectives.

4.6. Policy and Regulatory Compliance

The transition of the Port of Souda into an nZEP was designed in alignment with key national and international policy frameworks. At the national level, the project supports the goals outlined in Greece’s National Energy and Climate Plan (NECP), particularly regarding emissions reduction, renewable energy integration, and energy efficiency.

At the European level, the project complies with the European Green Deal, the Energy Efficiency Directive (EED), and the Renewable Energy Directive (RED II). The inclusion of cold ironing infrastructure aligns with EU Directive 2014/94/EU, which promotes alternative fuels and shore power for ports, and anticipates requirements under EU Regulation 2023/1804 [128,129,130,131].

In the maritime sector, the port’s upgrades support compliance with IMO MARPOL Annex VI by reducing air pollution from ships through electrification. Regular consultation with Greek authorities such as the Regulatory Authority for Energy (RAE) and the Ministry of Environment and Energy ensures all components meet legal and environmental standards.

Finally, the integration of IoT technologies and a digital simulation environment enables continuous monitoring and reporting, helping maintain long-term compliance with both national and EU regulations, including upcoming maritime carbon regulations [132].

4.7. Continuous Monitoring and Improvement

By leveraging the digital shadow developed during the simulation phase, along with sensor-based data collection, stakeholder collaboration, and the integrated use of previously deployed technologies (RES, ESS, and EMS), the Port of Souda can establish a robust digital and operational framework. This framework serves as both a protective and adaptive layer, enabling real-time oversight, efficient resource management, and predictive maintenance.

The ongoing analysis of operational data collected from sensors supports continuous optimization throughout the port’s years of operation. This allows for timely adjustments, performance improvements, and the incorporation of emerging technologies or strategies. In doing so, the port remains not only energy-efficient and sustainable but also resilient and up to date, securing its role as a modern and environmentally responsible maritime hub.

5. Conclusions

In response to the growing environmental, technological, and energy-related challenges outlined throughout this study, the transition toward sustainable and resilient port infrastructures has become both a necessity and an opportunity. The critical role of ports in global logistics, combined with their high energy demands, positions them as key actors in the shift toward low-carbon systems. However, as the literature reveals, there is a notable absence of holistic, adaptable frameworks that address the full spectrum of requirements for transforming ports into nZEPs. This research begins to fill that gap by proposing an integrated approach that aligns renewable energy deployment, storage solutions, and intelligent energy management within a unified, scalable model.

This study successfully developed and validated a comprehensive, step-by-step framework for transforming conventional ports into nearly zero-energy ports (nZEPs). Its key contribution lies in providing an integrated approach that systematically guides the assessment of current energy profiles, evaluation of renewable potential, optimized system design (integrating renewables with storage), real-time monitoring via digital shadow, smart grid development, and comprehensive environmental and economic impact evaluation.

The framework’s application to a case study port demonstrated substantial improvements in both economic and environmental performance. Specifically, the transition to an nZEP configuration resulted in a significant reduction in the LCOE by approximately 60.44% compared to the current port’s operational costs. Concurrently, the environmental benefits were marked by a decrease in the overall carbon footprint by 83.48% relative to the existing baseline. These quantitative outcomes underscore the framework’s efficacy in achieving tangible sustainability gains for high-energy-demand infrastructures.

Beyond these quantifiable benefits, this framework offers a practical roadmap for port authorities and stakeholders seeking to initiate or accelerate their decarbonization journeys. It provides a structured methodology to navigate the complexities of integrating diverse renewable energy technologies and smart management systems within existing port infrastructure. The emphasis on a digital shadow, for instance, provides a robust mechanism for risk reduction and agile adaptation in complex energy environments, fostering more resilient and future-proof operations.

Despite its demonstrated efficacy, this study acknowledges certain limitations. The validation of the framework primarily relied on literature-based data and site-relevant benchmarks for simulation, given the absence of direct operational datasets for the chosen case study. While this approach enabled a realistic representation, future research should aim to validate the framework using real-time, empirical data from live port operations to further refine its applicability and accuracy. Additionally, while practical challenges and context-specific considerations were highlighted, future work could delve deeper into the specific regulatory, financial, and sociotechnical barriers encountered during actual nZEP implementations.

Future research directions include expanding the framework to incorporate dynamic market pricing mechanisms for energy trading within a smart port environment, exploring the integration of emerging green fuels like ammonia or methanol production, and developing more advanced AI-driven predictive maintenance modules for renewable energy assets. Future work should explicitly incorporate governance configurations and stakeholder conflict resolution protocols to support the framework’s real-world deployment under non-cooperative conditions. Further validation across diverse port types and geographical locations, utilizing empirical operational data, would also strengthen the framework’s generalizability and practical impact. Actually, further validation on large-scale, high-density port infrastructures could refine its scalability across diverse maritime contexts.