Vol. 4 No. 3 (2026): In progress

Published: 2026-04-24

Article

  • Open Access

    Article ID: 798

    The impact of technological innovation on sustainable energy in solar microgrids: The moderate role of green supply chain management practices

    by Firas Tayseer Ayasrah, Mahmoud Allahham, Wasef Almajali, Ahmad Bani Ahmad, Ahmad Marei, Nawwaf Hamid Salman Alfawerh
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    0 Views
    DOI: https://doi.org/10.18686/cest798

    This research paper analyzes how technological innovation affects sustainable energy in solar microgrids and the moderating role of green supply chain management (GSCM) practices. The study examines technological innovation across three dimensions—process innovation, organizational innovation, and marketing innovation—and their effects on sustainable energy performance in solar microgrid systems. A quantitative research design is adopted using a conceptual framework that links technological innovation, green supply chain management, and sustainable energy performance. Data is gathered from professionals working in renewable energy firms and solar infrastructure organizations. Structural equation modeling with Partial Least Squares (PLS-SEM) is applied to test the proposed relationships and the moderating role of GSCM practices. The results indicate that technological innovation significantly improves sustainable energy outcomes in solar microgrid systems. In addition, green supply chain management practices moderate the relationship between technological innovation and sustainable energy by strengthening environmental practices and resource efficiency. The findings are informative for renewable energy firms, energy planners, and policymakers seeking to enhance the sustainability of solar microgrids. The integration of technological innovation with green supply chain management can improve operational efficiency and environmental performance in decentralized energy systems. The study contributes to the renewable energy management literature by incorporating both technological innovation and GSCM into the solar microgrid context, offering fresh insight into how technology and sustainable supply chain activities collaborate to advance sustainable energy.

  • Open Access

    Article ID: 797

    Advanced control-oriented modeling of two-stage anaerobic digesters for resilient and energy-efficient biogas production

    by Jasim Al Shehihi, Nitin Raut
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    0 Views
    DOI: https://doi.org/10.18686/cest797

    Anaerobic Digestion (AD) is a key technology in the circular bioeconomy due to increasing demand for sustainable energy and efficient organic waste management. Advanced configurations, such as the Two-Stage Anaerobic Digestion (TSAD) systems, yield higher methane production and allow for superior operational flexibility. But tight biochemical couplings between stages cause extreme dynamic instability in the face of real-world disturbances. In this study, a reduced-order dynamic model based on Anaerobic Digestion Model No. 1 (ADM1) was employed to study stability behavior and assess advanced control strategies for resilient and energy-efficient biogas generation. Five real disturbance scenarios were simulated: organic loading shock (3–7 kg VS·m⁻3·d⁻1), acidification (pH 6.2 → 5.5), thermal shock (35 → 25 °C), Volatile Fatty Acids (VFA)/ammonia inhibition and feed interruption (48 h). Three control strategies, Proportional Integral Derivative (PID), Fuzzy Logic Control (FLC) and Model Predictive Control (MPC), were examined comparatively under open- and closed-loop operation. Uncontrolled disturbances caused methane yield losses of 40–60% and recovery times >72 h. PID reduced loss to 20–35%, FLC to 10–25%, whereas MPC restricted methane loss to <10% with up to 60% reduction in recovery time. MPC also achieved an improvement in pH compared to PID. The results show that the use of MPC significantly improves the energy recovery efficiency and operational resilience. The proposed reduced-order ADM1 is innovative in that it establishes a computationally efficient framework for modeling TSAD systems, integrating predictive control with energy performance metrics, thus providing stability and scalability attributes.

  • Open Access

    Article ID: 760

    Comparative design and economic analysis of dry-type power transformers: Comparative study of copper and aluminum windings

    by Kamran Dawood, Muhammed Alperen Çakir, Güven Kömürgöz Kırış, Semih Tursun
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    58 Views
    DOI: https://doi.org/10.18686/cest760

    This paper explores the effect of winding material selection on the design and performance of dry-type distribution transformers with power ratings from 400 kVA to 3,000 kVA. Each transformer is manufactured with specific limits for electromagnetic and heat conditions: leakage impedance kept at 6% with a ±10% allowance, a magnetic flux density of 1.7 T, and winding temperature rise kept under 100 K, in accordance with IEC 60076-11 guidelines. The number of turns, core dimensions, conductor cross-sectional area, and the space between windings were adjusted to satisfy these conditions across varying power levels. The study is structured in two stages. First, losses, cost, and weight are individually evaluated for both materials (copper and aluminum) across different power ratings. Second, a comparison between copper and aluminum windings is performed to highlight trade-offs in efficiency, material usage, and design impact. Experimental results reveal that although copper offers improved conductivity and compactness, aluminum remains a viable alternative, especially where cost and weight are priority concerns. The outcomes provide practical insights for transformer designers aiming to optimize material usage in medium-voltage dry-type applications. These findings contribute to the development of energy-efficient and sustainable transformer designs, which are critical for the advancement of clean energy systems. Implementing optimized material selection can support reduced environmental impact and promote sustainable power distribution solutions in modern electrical networks.

  • Open Access

    Article ID: 738

    Influence of solar radiation reflected from the earth’s surface on the formation of the global flux

    by Makhmud Mamarasulovich Sobirov, Jurabek Yuldashboy Roziqov, Valijon Umarali Ruziboev, Muhabbat Muhiddin Kamolova
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    46 Views
    DOI: https://doi.org/10.18686/cest738

    A method was developed to quantify the effect of the solar radiation flux reflected from the Earth’s surface on the atmospheric radiation field. The reflected flux was accounted for within a Lambertian model of isotropic diffuse reflection. The influence of surface-reflected radiation on the formation of the global flux power incident on a unit horizontal area at the Earth’s surface, as well as on the power of the flux reflected by the atmosphere back toward space, was demonstrated. Variations in the direct and diffuse components of radiation emerging through the lower and upper atmospheric boundaries were calculated as functions of the underlying surface albedo and the illumination angle. A relationship between the Earth’s surface albedo and the effective atmospheric albedo was established. The results enable more accurate theoretical assessments of the performance of bifacial (double-sided) solar panels, whose rear side receives energy from radiation reflected by the Earth’s surface.

  • Open Access

    Article ID: 735

    Enhanced generator scheduling through the lambda iteration method with clone-based optimization and Lévy flight integration

    by Rifki Rahman Nur Ikhsan, Jangkung Raharjo, Ardiansyah Ramadhan, Lindiasari Martha Yustika
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    118 Views
    DOI: https://doi.org/10.18686/cest735

    One of the hardest parts of running a power system is economic dispatch (ED), which means finding the cheapest way to meet demand and operational limits. To alleviate these limitations, this study presents a hybrid methodology known as Vectorized Lambda Iteration Method–Clone-Based Optimization with Lévy flight (VLIM-CBO-LF). The contribution comprises the synchronized amalgamation of three complementary strategies. The VLIM-CBO-LF improves the accuracy of dispatch calculations, clone-based optimization improves local search by using adaptive cloning, selection, and Lévy flight improves global exploration by letting movements happen over long distances from time to time. The suggested method was tested on a 42-unit economic dispatch system over a 24-h period, running it 30 times to make sure it worked each time. The results show that VLIM-CBO-LF has the lowest average daily fuel cost of IDR 3.9096 × 1010. This is better than the artificial bee colony, particle swarm optimization, grey wolf optimization, and whale optimization algorithm. The cost goes down from IDR 1.050 × 10⁹ to 3.666 × 10⁹ per day, but the performance stays the same, with a standard deviation of 6.50 × 10⁷ IDR. The ANOVA test (F = 19.004, p = 1.820 × 10⁻⁷) and the Friedman test (χ2 = 60, p = 9.358 × 10⁻14) both show that the results are statistically significant. The Wilcoxon signed-rank test (W⁺ = 0) shows that the results are strictly better than all other benchmark methods. Future research may investigate the applicability of the VLIM-CBO-LF model to more complex electrical market mechanisms.

  • Open Access

    Article ID: 783

    Predictive modeling of terrestrial radiation for optimizing solar-powered irrigation under limited data in Adrar region (Algeria)

    by Assia Meziani, Nabil Mega, Abdelmonen Miloudi, António Canatário Duarte
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    210 Views
    DOI: https://doi.org/10.18686/cest783

    An accurate estimation of the radiation is a prerequisite for the net radiation balance, evapotranspiration modeling, and optimal scheduling of water extraction by solar-powered irrigation, especially in the water-scarce Saharan zone. In this study, we developed a predictive model to estimate daily terrestrial radiation at the surface of the Adrar region in Algeria. We used a training set of 25 years of data (2000–2025) from 10 stations (Adrar, Tamantit, Sidi Ahmed Timmi, Fenoughil, Zaouiet Kounta, Reggane, Gharmianou, Tittaf, Ikiss, Kassbet Lahrar) with only three features: soil temperature (0–7 cm), air temperature (2 m), and vapor pressure deficit. The robustness of the models was ensured by a time-based split. The random forest (RF), gradient boosting (GB), and extra trees (ET) tree-based models were evaluated on the generalization set. RF and ET exhibited the best performance (R = 0.92, rootean square error—RMSE = 31.85 W/m2, Nash–Sutcliffe efficiency—NSE = 0.84 for RF; R = 0.92, RMSE = 32.33 W/m2, NSE = 0.84 for ET), whereas GB exhibited poor performance (R = 0.90, RMSE = 36.67 W/m2, NSE = 0.79). Finally, we proposed a map for solar-powered irrigation optimization. In particular, we demonstrated that the southern part of the Adrar region (Reggane, Zaouiet Kounta) has high potential for solar-powered irrigation (more than 350 W/m2). This study contributes to hyper-arid agricultural regions in Algeria through water conservation and the utilization of renewable energy.

  • Open Access

    Article ID: 752

    Sputtering yield calculation of tritium plasma interacting with beryllium by using atomic simulation environment

    by Alper Pahsa
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    106 Views
    DOI: https://doi.org/10.18686/cest752

    Designing buildings for magnetic fusion devices mostly aims to replicate the interactions between structural material surfaces and plasma. The sputtering effects of plasma ions on the surface structures of various materials are unique. It is essential to take structural deformations into account when constructing structures for Tokamak-type fusion reactors. Tokamak nuclear fusion reactors require a significant amount of research on the ways in which plasma interacts with materials and the structures of these materials. Surfaces can be altered by plasma ions with high energy. It is absolutely necessary to have a solid understanding of the processes that include material surface modification, such as chemical or physical sputtering and retention events. Fusion reactions, which generate heat and energy, can modify the walls of reactors. As a result, reactors produce energy with reduced efficiency. For example, beryllium is the most frequently employed material in the Tokamak reactor divertor. In this study, the positions of beryllium atoms are shown on a flat graph, and calculations for how much material is ejected due to molecular dynamics are done. The simulation employed tritium bombarding energies at a steady electromagnetic force of 3 T, ranging from 5 to 35 keV. The molecular dynamics of the tritium plasma on the beryllium crystal significantly illuminated the plasma material interaction process.

  • Open Access

    Article ID: 749

    Implementation of advanced turbulence models for aerodynamic performance prediction of S818-NR airfoil in wind turbine applications

    by Ismatulla Khujaev, Muzaffar Hamdamov, Sardorbek Muzaffarov, Khushvaqt Maratov
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    126 Views
    DOI: https://doi.org/10.18686/cest749

    This research presents a comprehensive numerical analysis of the airflow around the S818-NR (subsonic) airfoil, designed for use as wind turbine blades. Numerical simulations were produced using the Finite Element Analysis (FEA) method with the COMSOL Multiphysics simulation software package to determine how subsonic airflow behaves around the S818-NR airfoil. To accurately simulate the turbulence in the airflow around wind turbines, the two-equation Shear Stress Transport (SST) k-omega (k-ω) model was used, it provides a good representation of near-wall and free-stream turbulent flow conditions. The analysis of aerodynamic characteristics enables the evaluation of key parameters, including pressure distribution along the airfoil surface, flow-field velocity components, and lift force coefficients, at different angles of attack. Furthermore, the aerodynamic performance and turbulence structure development of the S818-NR airfoil blade were compared across various Reynolds numbers to determine the influence of flow conditions on these parameters. The aerodynamic validation of the S818-NR airfoil using both FEA simulations and experimental data was within acceptable error limits. Additionally, another focus was on improving our method for determining the various numerical simulation parameters, including mesh refinement level, boundary condition formulation, solver configuration settings, and post-processing methods, to ultimately provide good, stable numerical results with low error throughout the entire numerical process. Ultimately, these findings provide essential insights for accurately predicting turbulent flow around airfoils. This enables developers to create blade designs that maximize aerodynamic performance, significantly improving the energy efficiency and overall reliability of the global renewable energy sector.

  • Open Access

    Article ID: 733

    Wavelets to detect trends and variability of mini hydropower generations—Insights from Sri Lanka

    by Dilmi Amarakoon, Panchali Fonseka, Madhawa Herath, Upaka Rathnayake
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    131 Views
    DOI: https://doi.org/10.18686/cest733

    Mini hydropower generation is strongly seasonal and can exhibit non-stationary variability that complicates planning in run-of-river systems. This study investigates monthly electricity generation (kWh) from three grid-connected mini hydropower plants in Sri Lanka, namely Erathna, Denawaka Ganga, and Kiriwaneliya, using records spanning from Jan 2015 to Oct 2025. The analysis was conducted at both overall and seasonal scales based on four climate seasons of Sri Lanka: Northeast Monsoon, Southwest Monsoon, and two inter-monsoon periods. Long-term monotonic trends were assessed using the Mann-Kendall test and Sen’s slope, with robustness checks for commissioning-year effects and multiplicity across seasonal subsets. Time-frequency structure was examined using the continuous wavelet transform (CWT) with a Morlet mother wavelet (), an AR (1) red noise background, 95% pointwise significance contours, and a cone of influence (COI) to delineate regions affected by finite-length edge effects. Across all sites, wavelet power indicates a persistent annual band consistent with monsoon-driven seasonality. The Denawaka Ganga shows an increasing trend (Sen slope = 7,215 kWh/month; p = 0.0019), although significance weakens when the first two operational years are excluded (p = 0.063), suggesting possible commissioning-related effects. After false discovery rate control, seasonal subset trends do not remain statistically significant and are treated as exploratory. These results highlight that robust inference about multi-year periodicities from decade-scale monthly records requires careful interpretation outside the COI, together with red noise significance testing.

  • Open Access

    Article ID: 774

    Intelligent hybrid control of a five-level shunt active power filter for power quality enhancement in renewable-rich power systems

    by Akharakit Chaithanakulwat, Teeeawut Savangboon, Nuttee Thungsuk, Thaweesak Tanaram, Sakdawut Boontua
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    171 Views
    DOI: https://doi.org/10.18686/cest774

    The increasing penetration of renewable energy sources and power electronic converters in modern distribution networks has introduced significant harmonic distortion and power-quality challenges, particularly in converter-dominated systems. These distortions degrade the system efficiency, reduce the equipment lifespan, and compromise the stability of sensitive loads. This study proposes an intelligent hybrid control strategy for a five-level shunt active power filter (SAPF) to enhance the power quality under nonlinear load conditions. The proposed framework integrates fuzzy logic-based DC-link voltage regulation, adaptive hysteresis current control with quasi-constant switching frequency, and space vector pulse width modulation (SVPWM) for optimized switching vector generation. The control algorithm was implemented on a digital signal processor (DSP), specifically the Texas Instruments TMS320F28335, and validated through both MATLAB/Simulink simulations and real-time experiments. The results demonstrate that the total harmonic distortion (THDi) of the source current was reduced from 18.67% to 5.04%, achieving compliance with the IEEE Std. 519. In addition, the proposed method exhibits a fast dynamic response, stable DC-link voltage regulation, and reduced switching frequency variation. Comparative evaluation confirms that the hybrid control approach outperforms the conventional proportional–integral and fixed-band hysteresis controllers in terms of harmonic mitigation and system stability. These findings highlight the effectiveness and practical applicability of the proposed SAPF in renewable-rich, converter-dominated power systems.

  • Open Access

    Article ID: 795

    Generation of green hydrogen from wind energy in Huanchaco—La Libertad, Peru

    by Santos-Andrés Castillo-Vargas, Alexander-Manuel Villoslada-Chilón, Jorge-Luis Leiva-Piedra, Emilio Ramirez-Juidias
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    210 Views
    DOI: https://doi.org/10.18686/cest795

    This study evaluates the technical potential for green hydrogen production from wind energy in the coastal district of Huanchaco, located in the La Libertad region of northern Peru. A long-term dataset of hourly wind speed records from 2010 to 2024, obtained from the NASA POWER (MERRA-2) database, was used to characterize the wind resource. Wind speeds measured at 50 m were extrapolated to the turbine hub height (80 m) using the power law. The statistical behavior of wind speed was modeled using a two-parameter Weibull distribution, with parameters estimated through the Maximum Likelihood Method (MLM), achieving an excellent fit (R2 > 0.99; RMSE < 0.01). The results indicate a moderate but seasonally stable wind regime, with monthly wind power density values ranging from 71 to 216 W/m2 and capacity factors between 0.17 and 0.32 for a Siemens Gamesa SG 2.1-114 wind turbine. The estimated annual electricity generation reaches approximately 4.65 GWh, enabling a hydrogen production of about 77.6 t per year through proton exchange membrane (PEM) electrolysis, assuming a specific energy consumption of 54 kWh/kg and a rectifier efficiency of 90%. A preliminary economic analysis yields a levelized cost of hydrogen (LCOH) of approximately 7.1 USD/kg under current investment conditions. These findings demonstrate that coastal regions, characterized by moderate but temporally stable wind regimes, can support technically viable configurations for decentralized green hydrogen production. The study provides region-specific quantitative evidence that contributes to energy planning and highlights the importance of considering both wind resource magnitude and temporal stability in wind-to-hydrogen system assessments.

  • Open Access

    Article ID: 790

    International cooperation, energy transition and green growth in the MENA region: A panel data analysis

    by Sahbi Gabsi, Mohamed Neffati
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    182 Views
    DOI: https://doi.org/10.18686/cest790

    This paper examines the effects of international cooperation and energy transition on green growth in 15 Middle East and North Africa (MENA) countries over the period 1990–2023. Green growth is proxied by production-based CO2 emissions, where higher emissions indicate lower green growth performance; consequently, a positive coefficient on any explanatory variable indicates an increase in emissions, whereas a negative coefficient indicates the opposite. The panel Autoregressive Distributed Lag (ARDL) framework is employed, using Mean Group (MG), Pooled Mean Group (PMG), and Dynamic Fixed Effects (DFE) estimators to capture both short- and long-run dynamics. The Hausman test favors the PMG estimator as the most appropriate specification. The empirical results confirm a long-run cointegrating relationship between green growth, political globalization (international cooperation), renewable energy consumption (energy transition), Gross Domestic Product (GDP) per capita, Foreign Direct Investment (FDI) and population growth. In the long-run, both international cooperation and energy transition make significant positive contributions to green growth. economic growth and population growth similarly contribute to emissions reduction, suggesting that structural change and technological advancement have improved environmental performance. FDI, by contrast, does not exhibit a significant long-run effect. Short-run responses are largely insignificant, confirming that environmental improvements materialize gradually through structural and institutional changes. Overall, the findings underscore that advancing green growth in MENA countries requires sustained international cooperation, accelerated renewable energy deployment, and long-term economic structure reform. The results carry important policy implications for sustainable development and low-carbon transitions across the region.

  • Open Access

    Article ID: 713

    Development and implementation of a hybrid renewable energy system in a pilot cheese production facility in Beja, Portugal

    by João Garcia, Arian Semedo, Francisco Calvo, João Dias
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    149 Views
    DOI: https://doi.org/10.18686/cest713

    The increasing demand for renewable energies, encouraged by the European Union (EU), aims to position Europe as a leader in clean energy production while reducing its carbon footprint. The application of renewable energy in industry is crucial, given the high energy consumption associated with it, particularly in the production and preservation of food. This article presents the development and implementation of an integrated energy system applied to the production and ripening of traditional Alentejo cheese. During the production phase, which includes pasteurization and coagulation processes that rely on hot water, heating is provided by a pellet boiler, capable of using alternative biofuels, and by solar thermal collectors. For the curing of cheese, conducted in a refrigerated chamber with humidity control, a refrigeration system using R744 (carbon dioxide) was considered, complemented by a heat exchanger to assist in water heating. The electrical supply is ensured by photovoltaic (PV) panels, a wind turbine, and batteries, allowing for storage and energy autonomy during periods without production. The electrical supply is ensured by PV panels, a wind turbine, and batteries, allowing for storage and energy autonomy during periods without production. Monthly analysis indicates that photovoltaic energy is the dominant source, supplying 3,391 kWh annually and covering, on average, 87% of the monthly demand. The system also integrates passive heating technologies and phase change materials (PCM) with the aim of optimizing performance and reducing equipment operating hours. Upon completion of the installation, it will be possible to evaluate cheese production under real conditions and collect data on thermal and electrical consumption, allowing for future system optimization.

  • Open Access

    Article ID: 670

    From pollution to prosperity:Quantifying the impact of cleaner production on triple-bottom-line sustainability in Algerian industrial start-ups

    by Ismail Bengana, Khaled Mili, Mekimah Sabri, Zighed Rahma
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    156 Views
    DOI: https://doi.org/10.18686/cest670

    This empirical study examines the causal link between cleaner production strategies and comprehensive sustainability outcomes in Algerian industrial start-ups, thereby addressing a notable research gap in emerging economies. These enterprises operate under intensifying global sustainability pressures, requiring them to integrate environmentally responsible practices without compromising economic viability. Using Confirmatory Composite Analysis (CCA) with SMART-PLS on data from 300 innovative Algerian start-ups, the research evaluates the differentiated impact of three cleaner production dimensions: renewable resource utilization, clean technology adoption, and zero-pollution initiatives. The results reveal a hierarchical influence pattern: clean technology exerts the strongest effect on sustainability (50.2%), followed by renewable resources (10.3%) and zero-pollution practices (8.2%), highlighting a strategic reliance on technological solutions as cost-effective sustainability drivers under resource constraints. The study offers a validated measurement model for assessing cleaner production implementation in developing economies and delivers actionable implications, indicating that technology-led approaches provide the most efficient short-term pathway to sustainability improvement. It recommends that industrial start-ups prioritize investment in clean technology infrastructure while simultaneously expanding renewable resource use and pollution reduction efforts. Furthermore, it advocates structured collaboration among start-ups, government agencies, and universities to design targeted training on cleaner production methodologies. Future research directions include longitudinal assessment of financial performance, exploration of institutional enablers and barriers to green practice adoption, and cross-cultural comparative studies to situate these findings within global sustainability discourses, particularly in support of SDG 9, SDG 12, and SDG 13 under the 2030 Agenda.

  • Open Access

    Article ID: 709

    Electric energy and decarbonized power plant capacity requirements to support battery electric vehicle penetration in Morocco by 2050

    by Amin Bennouna
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    150 Views
    DOI: https://doi.org/10.18686/cest709

    This paper aims to present an estimate of the of electricity needs until 2050 in a "business-as-usual" Moroccan economy (2.48% annual Gross Domestic Product (GDP) growth in constant value per capita), first without, then with a massive but gradual introduction of battery electric vehicles (BEV) following three scenarios simulated by three logistic curves respectively centered on 2051, 2054, and 2057. The study does not require the evolution number of vehicles since it deals only with their total energy requirements. The idea is based on conserving the energy supplied today "to the wheel" of current internal combustion engine vehicles (ICEVs) in the battery electric vehicles (BEVs) of the future and, consequently, on a universal model of two conversion chains for current ICEVs, on the one hand, and future BEVs, on the other. A so-called "universal model" of the two conversion chains is proposed to allow jumping from land fuels (diesel and gasoline) to electricity requirements. A forecast of the evolution of national needs for land fuels then makes it possible to calculate electricity needs for each scenario of penetration of BEVs. The results show that powering the 2050 BEV in the slowest scenario would need the equivalent of all the 2020 net electric demand and the equivalent of the 2025 annual maximum power. At the end, the paper shows that, in 2050, around 28 GWp of solar photovoltaic (PV), or 14 GW of wind or 7 GW of nuclear plants should be needed to operate the BEVs penetration of the fastest scenario considered.

  • Open Access

    Article ID: 652

    Unlocking green power:How do institutional quality,innovative technologies and foreign aid drive clean energy in Pakistan?

    by Saima Sajid, Shareen Qayyum, Sania Ahmad, Syed Saqlain Ul Hassan, Hamid Waqas
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    253 Views
    DOI: https://doi.org/10.18686/cest652

    Affordable and clean energy (Sustainable Development Goals, SDG 7) is taking center stage in Pakistan, where the country is experiencing increasing energy deficits, electricity demand and serious environmental degradation. Thus, it will be essential to identify the factors that will push towards the use of clean energy to realize long-term sustainability. Therefore, this study explored the long-term relationship between clean energy (SE) as dependent variable and Economic growth, Institutional Quality (IQ), Innovative Technology (IT), Foreign Aid (FA) as independent variables and internation of IQ and Gross Domestic Product (GDP) in Pakistan. For empirical results, this study employed Autoregressive Distributed Lag (ARDL) Bond test approach from 1996 to 2024. The findings from this study validate the long-term relationship between the variables; however, the results reveal that GDP, IQ and FA have significant negative impact on SE in Pakistan, indicating that current macroeconomic and institutional framework of Pakistan is ineffective in transforming economic expansion into clean energy, along with external funds allocation directed towards more general projects instead of energy-specific ones. In contrast, IT poses a significant positive impact on SE, underscoring the importance of technological advancements in supporting clean energy. Although IT has positive effects on adoption of clean energy, inconsistency in regulation because of poor institutional quality sabotages all these relations and leads to fragmentation and inconsistent policies that will perpetuate subsidies on fossil production and hence, curtails the adoption of mass adoption of clean energy resources. This study highlights the urgent need for governance reforms, sector-specific foreign aid allocation, and investment in innovative technologies to strengthen institutional capacity and transparent foreign aid allocation to strengthen clean energy infrastructure.

  • Open Access

    Article ID: 474

    The evolution of power market structures: Strategic approaches for the Indian electricity market

    by Anusree Thattiyot, Rashmi Mogenahalli Ranganath, Ila Rai, Hoong Pin Lee
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    192 Views
    DOI: https://doi.org/10.18686/cest474

    This paper explores strategies for India’s evolving power market, focusing on the renewable energy integration and competitive dynamics introduced by the Electricity Act 2023. With India targeting 450 GW of renewable energy by 2030, it identifies a critical gap in short-term power market models vital for optimizing portfolios and managing fluctuations. The study evaluates five major investment strategies: conventional flexible Power Purchase Agreement (PPA), tariff pass-through approach, contract for difference, physical hedge, and renewable energy generator flexible PPA, using mean and standard deviation for present value and net present value. Findings reveal significant variability in flexible PPAs, underscoring the importance of short-term trading models to enhance adaptability. To address market power, the study evaluates the Herfindahl-Hirschman Index and implements improvement strategies, including adding distributed generation, regulatory oversight, and regional expansion. These approaches aim to enhance competition and diversification in the energy market. The paper proposes a hybrid approach combining long-term PPAs for base loads with short-term markets, leveraging transactive energy facilitated by blockchain-enabled smart contracts for efficient procurement and management. By reviewing policies, power exchanges, and literature, the study provides actionable insights into regulatory reforms, advanced trading mechanisms, and decentralized market architectures, emphasizing short-term markets as crucial for India’s sustainable power transition and enhanced competition.

  • Open Access

    Article ID: 791

    Environmental sustainability in Asian economies: The role of ICT trade, energy transition, and sustainable development

    by Pham Van Phong, Pham My Dung, Luong Van Lieu, Nguyen Cong Tay
    Clean Energy Science and Technology, Vol.4, No.3, 2026;
    181 Views
    DOI: https://doi.org/10.18686/cest791

    This study examines the determinants of environmental pressure in selected Asian economies, with a focus on the roles of Information and Communication Technology (ICT) trade openness, energy intensity, renewable energy consumption, access to clean cooking fuels, and sustainable development. Using a balanced panel dataset and estimation techniques robust to cross-sectional dependence and heterogeneity, namely Panel Corrected Standard Errors and Feasible Generalized Least Squares, CO₂ emissions per capita are employed as a proxy for environmental pressure. The empirical results indicate a differentiated pattern of environmental dynamics. The ICT trade is found to be negatively associated with emissions, suggesting that technological diffusion improves production efficiency and reduces environmental pressure. In contrast, energy intensity exhibits a strong positive relationship with emissions, confirming that inefficient energy use remains a central driver of environmental degradation. Renewable energy consumption shows a positive association with emissions, reflecting the dominance of scale effects and the limited substitution away from fossil fuels in the early stages of energy transition. Access to clean cooking fuels contributes to lower emissions, highlighting the importance of household-level energy transition. Sustainable development is also associated with reduced environmental pressure, although its effect appears gradual and context-dependent. The findings suggest that environmental sustainability in Asian economies depends on the interaction between technological openness, energy structure, and structural transformation. Policies should prioritize improving energy efficiency, ensuring effective substitution toward clean energy, strengthening absorptive capacity for technological adoption, and promoting inclusive access to modern energy services.