Renewable Energy Sources Research Articles

The contribution of green technological innovation, clean energy, and oil rents in improving the load capacity factor and achieving SDG13 in Saudi Arabia

This research aims to assess the effects of green technological innovation, renewable energy sources, and oil rents on the load capacity factor in Saudi Arabia from 1988 to 2021. The primary conclusions can be outlined as follows. The combined cointegration and Saikkonen-Lütkepohl cointegration tests reveal long-run relationships between the load capacity factor and the explanatory variables at the 1% significance level. In comparison, the Phillips-Ouliaris test shows evidence of cointegration only at 10%. Moreover, the quantile regression indicates that oil rents adversely impact environmental quality; however, they remain contingent upon environmental conditions. A 1% increase in oil rents results in a decline in environmental quality by 0.025% under poor conditions, 0.036% under moderate/normal conditions, and 0.108% under good conditions. On the contrary, renewable energy consumption and green technological innovation improve environmental quality, irrespective of the prevailing environmental conditions. However, the environmental impacts of renewable energy consumption exceed those of green technological innovation. Results show that a 1% increase in renewable energy consumption leads to a 0.052-0.253% improvement in environmental quality, whereas a 1% increase in green technological innovation results only in a 0.017-0.047% improvement. Finally, population and GDP per capita exert negative and positive implications on the load capacity factor, respectively, while energy intensity has no significant environmental effects. The research findings provide significant insights and suggest policy recommendations to address climate change and meet the targets set out in SDG13.

Strategy towards sustainable energy transition: The effect of policy uncertainty, environmental technology and natural resources rent in the OECD nations

The stupendous increase in environmental pollutants alongside climate alterations are calling for integrated tasks at the global level to meet the Paris Agreements. Energy conversion from fossil fuel to renewable energy sources is an important step to address the adverse effects of extreme climatic conditions. This study explores the key contributors of energy transition in the context of the OECD countries during the period 1991 to 2019. To this end the major determinants chosen include natural resources rents, policy uncertainty, environmental technologies, environmental policies, income and globalization. The quantile regression technique is used to explore heterogeneous role of the contributory factors of energy transition across its different levels. This study applies method of moments quantile regression (hereafter MM-QR) by Machado and Silva (2019) that provides evidence on how the covariates affect the integral conditional distributions of energy transition. The study documents interesting findings. (i) Natural resources rents reduce the pace of the progress of sustainable energy transition in OECD economies. (ii) An escalation in the world uncertainty index leads to an improvement in energy transition index. (iii) Environmental technologies support the transition concerning cleaner and more efficient energy sources. (iv) Finally, as natural resources, uncertainty, environmental technologies, and globalization impacts energy transition differently, their effects need to be rationalized with varying environmental policy instruments. The study concludes that energy transition process requires the task of upgrading the quality of implementation of policies related to energy technology.

Analysis of air-to-water converter frame using ANSYS simulation

According to projections made by the Indonesian Institute of Sciences (LIPI), by 2040 every region along Java's northern coast—from Banten to Surabaya and Iswara—will be an urban area vulnerable to water scarcity. As a result, more careful consideration is required. Since air is an endless supply, turning it into water is one way to address the clean water shortage. A good design's structure is one of its essential components. This is because the device's structure must sustain both the renewable energy source and the complete system. By utilizing ANSYS Workbench and theoretical calculations to analyze the maximum stress results, the research aims to ascertain whether the machine frame is safe for usage. In this investigation, the ANSYS 2021 R1 software was used to apply the finite element method to ASTM A36 material under vertical loading. The air-to-water converter mechanism is still safe after simulations were run on its shaft and frame. This is demonstrated by the biggest maximum stress on the shaft (6.2194 MPa) from the ANSYS numerical simulation and the largest maximum stress (0.349 MPa) on the frame, both of which are still below the allowable stress. Furthermore, a 0.9694 difference in safety factor was found between theoretical calculations and shaft simulation, and a 0.1573 difference was found for the frame. The safety factor acquired from the shaft was 1.6043, while the safety factor gained from the frame was 1.6073

Analysis of the effect of a spring constant of 980 N/m on a wave energy converter device due to heaving

Indonesia is a country with a larger sea area compared to its land area. Therefore, utilizing ocean current or wave energy as a renewable energy source, specifically for generating electricity through Wave Energy Converters (WEC), is a suitable solution. Wave Energy Converters (WEC) work on the basic principle of converting wave energy into linear motion or rotation to drive a generator and then convert it into electricity. The rotation is generated by the up-and-down movement of the pontoon affected by the pontoon's spring constant, which originates from sea waves. Hence, this study aims to analyze the effect of the spring constant on the pontoon due to heaving motion in response to sea waves. The study uses a spring constant of 980 N/m and is conducted with and without a planetary gear system. The highest voltage and current were achieved at a wave height of 0.35 m, producing a voltage of 84.5 V with a current of 8.26 A and a power of 698 Watts for the generator with the planetary system. For the generator without the planetary system, it produced a voltage of 1.73 V with a current of 0.046 A and a power of 0.0795 Watts with a gearbox shaft rotation of 37.32 RPM. The lowest voltage and current were observed at a wave height of 0.15 m, producing a voltage of 39.6 V with a current of 3.58 A and a power of 141.8 Watts for the generator with the planetary system. For the generator without the planetary system, it produced a voltage of 0.53 V with a current of 0.021 A and a power of 0.0111 Watts with a gearbox shaft rotation of 21.62 RPM

Investigating the Impact of Cloud Computing on Environmental Sustainability

Abstract: It discusses the effects of cloud computing on the environmental aspect of sustainability by focusing specifically on carbon emission reduction, cost-cutting, and exploiting renewable sources of energy. Using only hypothetical data obtained from TechCorp Solutions, Global Data Inc., InnovaTech Ltd., and NextGen Systems, this paper reveals strong decreases in energy usage - between 38.89 percent to 45 percent in cost savings following the implementation of cloud computing. The study also records remarkable carbon emission reductions. The cuts in drops range between 42.86% and 45%. Not only this, but on implementation, every firm asserted a flat rate cut of 40% in operating costs. The second investment area the research probes is the commitment of the major cloud providers to renewable energy sources. It finds some using up to 100% from renewable sources. Cloud data centers are much more efficient than traditional data centers, as the PUE comparison indicates, and hence produce maximum energy efficiency with the least negative impact on the environment. The results represent important implications regarding cloud computing in light of sustainability goals and revenue generation. This implies that cloud technology will be used much more widely within various industries going forward.

Exploring the potential of biohydrogen as a sustainable energy solution for Pakistan: A review of production processes and policy challenges

Due to growing carbon dioxide emissions and the depletion of fossil-based energy sources, international studies have been focusing more intensely on developing hydrogen as a source of renewable energy. Biohydrogen is an exciting and green alternative energy source with various different benefits. Unlike traditional energy sources, biohydrogen production does not emit pollutants, making it a more environmentally friendly option. Biohydrogen generation, particularly from microalgae and other low-cost biomass feedstocks, so offers the dual benefit of delivering clean electricity while absorbing Carbon Dioxide. This research investigates the possibility of biohydrogen as a sustainable energy solution for Pakistan's climate issue. We examine the current state of biohydrogen generation technologies, such as dark fermentation, photo fermentation, bio photolysis, with a focus on their potential application in Pakistan. The study investigates global advances in biohydrogen research and their significance in Pakistan, demonstrating biohydrogen's potential contribution to Pakistan's energy independence and environmental targets, as well as the practical and policy-related challenges that must be addressed to advance biohydrogen energy generation and wider adoption.

Global renewable energy transition in fossil fuel dependent regions

The worldwide shift towards renewable energy, as defined by the United Nations' Sustainable Development Goals (SDGs) in 2015, is a crucial milestone in achieving a sustainable future. The core focus of SDG 7 is to advance the accessibility, dependability, and environmentally-friendly nature of energy, aiming to substantially enhance the proportion of renewable energy sources and enhance energy efficiency. Although there have been significant developments in renewable energy, notably in solar and wind technologies, the rate of transition is still inadequate to achieve climate objectives. This study examines the imperative of implementing policy changes and integrated strategies to align global and local goals, while tackling the issues of resource allocation and the pressing need to transition away from fossil fuels in order to mitigate global temperature increase. Case studies showcase effective national endeavors, such as Brazil's Proalcool, Germany's Energiewende, and India's ambitious renewable energy objectives, illustrating diverse strategies for bolstering renewable energy capability. The report also analyzes the economic consequences for emerging nations that heavily rely on fossil fuels and the expected effects of reduced fossil fuel consumption. This article offers a detailed analysis of the current advancements, difficulties, and variations across different regions in the field of renewable energy. It gives valuable information on the future of global renewable energy plans, highlighting the importance of unified worldwide endeavors to attain a sustainable energy future.

Artificial Intelligence in Climate Change Mitigation: A Review of Predictive Modeling and Data-Driven Solutions for Reducing Greenhouse Gas Emissions

Artificial Intelligence (AI) is increasingly recognized as a powerful tool for addressing the challenges of climate change. Its ability to process vast amounts of data and generate advanced predictive models positions AI as a key player in efforts to reduce greenhouse gas (GHG) emissions and develop sustainable solutions. This review delves into the multifaceted role of AI in climate change mitigation, highlighting its potential in several critical areas. Firstly, AI is revolutionizing predictive climate modeling by providing more accurate forecasts and simulations, enabling better-informed policy and decision-making. Secondly, it is optimizing energy systems through smart grid management, demand forecasting, and the integration of renewable energy sources, thereby enhancing energy efficiency and reducing reliance on fossil fuels. Furthermore, AI is advancing carbon capture and storage technologies by improving the identification of optimal sites and enhancing process efficiency. In environmental monitoring, AI-driven solutions are enabling real-time detection and analysis of environmental data, contributing to more effective conservation efforts. This review also presents case studies and data that demonstrate the tangible impact of AI applications in driving progress towards global emission reduction targets. However, the adoption of AI in this domain is not without challenges. Issues such as data privacy, algorithmic transparency, and the ethical implications of AI deployment need to be carefully addressed. The paper concludes by outlining future research directions and emphasizing the need for interdisciplinary collaboration to fully harness the potential of AI in combating climate change.

AI-driven decarbonization of buildings: Leveraging predictive analytics and automation for sustainable energy management

The decarbonization of buildings is a pivotal strategy in addressing global climate change, and artificial intelligence (AI) is increasingly recognized as a powerful tool in this process. This paper explores the application of AI in optimizing building energy consumption, focusing on predictive analytics, real-time energy monitoring, and smart energy systems. By leveraging machine learning algorithms, AI enhances energy efficiency through precise automation, particularly in heating, ventilation, and air conditioning (HVAC) systems. AI-powered demand response solutions dynamically adjust energy use based on factors like occupancy, weather patterns, and energy prices, further minimizing carbon footprints. Additionally, the integration of renewable energy sources such as solar and wind with AI-driven energy management systems enables smarter utilization of clean energy. The paper examines both new construction projects and the retrofitting of existing infrastructures, offering insights into AI’s role in reducing carbon emissions and improving energy sustainability. Case studies highlight successful implementations, underscoring AI’s ability to drive significant energy savings and carbon reduction. The study also discusses challenges such as data privacy, the high cost of AI technology, and the regulatory framework required for widespread adoption. The findings present AI as an essential component of the future of sustainable, carbon-neutral buildings.

Analyzing the lifecycle of solar panels including raw material sourcing, manufacturing, and end-of-life disposal

The lifecycle of photovoltaic systems, encompassing the procurement of raw materials, manufacturing processes, and eventual disposal at the end of their operational lifespan, presents considerable ecological challenges notwithstanding their contribution to the enhancement of renewable energy sources. This research offers an exhaustive examination of the ecological ramifications associated with each phase of the lifecycle of photovoltaic systems. The extraction of essential materials, including silicon, silver, and rare earth metals, necessitates energy-demanding processes and leads to resource depletion, while the manufacturing phase is associated with the emission of greenhouse gases and resource consumption, particularly in the fabrication of crystalline silicon panels. The disposal at the end of life is becoming increasingly significant, as retired panels accumulate, and existing recycling technologies provide minimal recovery of valuable materials. Despite the substantial reduction in greenhouse gas emissions attributable to solar panels throughout their operational lifespan, there is a pressing need for enhancements in material efficiency, manufacturing methodologies, and recycling frameworks to mitigate their lifecycle repercussions. The investigation underscores the imperative for sustainable methodologies, circular economy paradigms, and policy measures to guarantee the enduring environmental sustainability of solar energy.

Economic evaluation of kinetic energy storage systems as key technology of reliable power grids.

In recent years, energy-storage systems have become increasingly important, particularly in the context of increasing efforts to mitigate the impacts of climate change associated with the use of conventional energy sources. Renewable energy sources are an environmentally friendly source of energy, but by their very nature, they are not able to supply the required amount of energy in a uniform distribution. This study evaluated the economic efficiency of short-term electrical energy storage technology based on the principle of high-speed flywheel mechanism using vacuum with the help of an innovative approach based on life cycle cost analysis (LCC). The innovative potential of high-speed flywheel energy storage systems (FESS) can be seen in increasing the reliability of the electricity transmission system with the possibility of providing control power to compensate for residual loads caused by volatile renewable power sources and power sinks. Based on the research conducted, the LCC method was selected in this study as the most appropriate method to evaluate the economic efficiency of a high-speed FESS used to compensate for short-term fluctuations in an upgraded electric transmission system. As a result, the adjusted LCC per MWh values were compared with the average intra-hour margin realisable in the Intra-Day OTE Market, while the margin calculation also considered the efficiency of the inertial storage. Under the modelled technical and economic conditions, it was found that a high-speed FESS project that can compensate for short-term fluctuations in the electricity transmission system can be economically efficient in the Czech Republic.

Survey of Reliability Challenges and Assessment in Power Grids with High Penetration of Inverter-Based Resources

Decarbonization is driving power systems toward more decentralized, self-governing models. While these technologies improve efficiency, planning, operations, and reduce the carbon footprint, they also introduce new challenges. In modern grids, particularly with the integration of power electronic devices and high penetration of Renewable Energy Sources (RES) and Inverter-Based Resources (IBRs), traditional reliability concepts may no longer ensure adequate performance due to systemic restructuring. This shift necessitates new or significantly modified reliability indices to capture the characteristics of the evolving power system. Ensuring converter reliability is essential for effective planning, which requires precise, component-to-system-level modeling, as different converters impact system performance indicators. However, the existing literature in this field faces a significant limitation, as most studies focus on a singular perspective. Some examine reliability at the device-level, others at the component-level, while broader reviews in power systems often emphasize system-level analysis. In this paper, we aim to bridge these gaps by comprehensively reviewing the interconnections between these levels and analyzing the mutual influence of power converter and system reliability. A key point to highlight is that, with the rapid evolution of modern power grids, decision-makers must adopt a multi-level approach that incorporates insights from all levels to enable more accurate and realistic planning and operational strategies. Our ultimate goal is to provide an in-depth investigation of studies addressing the unique challenges posed by modern power grids. Finally, we will highlight the gaps in the literature and suggest directions for future research.

Taming CO2•- via Synergistic Triple Catalysis in Anti-Markovnikov Hydrocarboxylation of Alkenes.

The direct utilization of carbon dioxide as an ideal one-carbon source in value-added chemical synthesis has garnered significant attention from the standpoint of global sustainability. In this regard, the photo/electrochemical reduction of CO2 into useful fuels and chemical feedstocks could offer a great promise for the transition to a carbon-neutral economy. However, challenges in product selectivity continue to limit the practical application of these systems. A robust and general method for the conversion of CO2 to the polarity-reversed carbon dioxide radical anion, a C1 synthon, is critical for the successful valorization of CO2 to selective carboxylation reactions. We demonstrate herein a hydride and hydrogen atom transfer synergy driven general catalytic platform involving CO2•- for highly selective anti-Markovnikov hydrocarboxylation of alkenes via triple photoredox, hydride, and hydrogen atom transfer catalysis. Mechanistic studies suggest that the synergistic operation of the triple catalytic cycle ensures a low-steady-state concentration of CO2•- in the reaction medium. This method using a renewable light energy source is mild, robust, selective, and capable of accommodating a wide range of activated and unactivated alkenes. The highly selective nature of the transformation has been revealed through the synthesis of hydrocarboxylic acids from the substrates bearing a hydrogen atom available for intramolecular 1,n-HAT process as well as diastereoselective synthesis. This technology represents a general strategy for the merger of in situ formate generation with a synergistic photoredox and HAA catalytic cycle to provide CO2•- for selective chemical transformations.

Ocean Wave Energy Conversion: A Review

The globally increasing demand for energy has encouraged many countries to search for alternative renewable sources of energy. To this end, the use of energy from ocean waves is of great interest to coastal countries. Hence, an assessment of the available resources is required to determine the appropriate locations where the higher amount of wave energy can be generated. The current paper presents a review of the resource characterizations for wave energy deployment. The paper gives, at first, a brief introduction and background to wave energy. Afterward, a detailed description of formulations and metrics used for resource characterization is introduced. Then, a classification of WECs (wave energy converters) according to their working principle, as well as PTO (power take off) mechanisms used for these WECs are introduced. Moreover, different sources for the long-term characterization of wave climate conditions are reviewed, including in situ measurements, satellite altimeters, and data reanalysis on one hand, and numerical simulations based on spectral wave models on the other hand. Finally, the review concludes by illustrating the economic feasibility of wave farms based on the use of the levelized cost of the energy index.

Research on the Possibilities of Expanding the Photovoltaic Installation in the Microgrid Structure of Kielce University of Technology Using Digital Twin Technology

Global challenges related to sustainable development are increasingly focusing on the use of digital twin technology as a universal tool for optimizing and monitoring renewable energy installations. This article discusses digital twin technology as a support for sustainable development based on the analysis of microgrid structures. Digital twins allow the creation of virtual models of physical systems. This capability facilitated the accurate replication of the microgrid model at Kielce University of Technology using ETAP (Electrical Transient Analyzer Program) software (version 22.5). The operational parameters of the microgrid structure were analyzed for the examined power range of the photovoltaic installation to determine the possibilities of expanding the existing installation. The impact of the photovoltaic installation’s power on the operational parameters of the microgrid structure was visualized, and final conclusions were formulated. Moreover, the integration of digital twin technology into renewable energy systems not only enhances operational efficiency but also plays a pivotal role in advancing sustainability objectives. Through real-time monitoring and predictive maintenance, digital twin technology facilitates the optimization of energy production and distribution, thereby reducing waste and contributing to the overall sustainability of energy systems. This technology enables the simulation of various scenarios, such as fluctuations in energy demand or the integration of new renewable sources, which can inform more sustainable decision-making processes. In the context of microgrids, digital twin technology ensures that energy production is closely aligned with consumption patterns, minimizing energy losses and enhancing grid resilience. Furthermore, digital twin technology supports the sustainable expansion of renewable installations by providing detailed insights into potential environmental impacts and the long-term sustainability of various energy configurations. As the demand for clean energy continues to grow, digital twin technology will be indispensable in achieving a balance between energy needs and environmental stewardship, ensuring that the expansion of renewable energy sources contributes positively to global sustainability objectives.

An extendable switched‐capacitor based three‐phase multilevel inverter with boosting capability

AbstractThe increasing demand for integrating renewable energy sources necessitates inverter topologies with boosting capabilities. Using inverters with boosting capability and a low number of components to integrate renewable energy sources can reduce costs. This study describes a three‐phase multilevel inverter based on extendable switching capacitors. The use of voltage‐doubling modules permits the development of the inverter's capability. By increasing the number of doubling modules, the number of output voltage levels and boost factor are increased. Furthermore, the study introduces and implements a line voltage‐based pulse width modulation approach developed for the proposed inverter. The operation of the proposed multilevel inverter, along with the pulse width modulation scheme, common mode voltage, and power loss analysis are thoroughly discussed. Additionally, a comparative analysis is provided; highlighting the advantage of reducing the number of power switches in the proposed three‐phase inverter compared to other existing topologies. Finally, a laboratory prototype is developed, operating at a 4 kHz switching frequency and with a 120 V DC‐link voltage. The experimental results corroborate the efficiency and performance of the proposed multilevel inverter, thereby validating its practical applicability.

Weather as Fuel — The Wicked Problem of Renewable Energy

Abstract A key component of mitigating climate change is reducing society’s dependence on fossil fuels, which will require replacing them with clean energy sources. The key strategy being pursued in the United States (and most other countries) is to rapidly scale up our use of renewable energy sources. Electricity generation provided by wind turbines and solar photovoltaic panels, in particular, has been growing rapidly, and most energy experts expect them to be the dominant forms of electricity generation in the future. Given the dependence these energy sources have on weather conditions (windiness and cloudiness, respectively), it is useful to view weather as the “fuel” for these renewables in the same way that coal or natural gas serves as the fuel in generating electricity in a fossil-fuel power plant. This paper uses a novel thought experiment to drive home this concept, while also exploring the complexity of providing reliable power on a grid dominated by renewable generation. The paper then shows how the transition to renewable energy falls into the class of problems known as “wicked problems,” and discusses approaches that will be needed to make progress. The current status of addressing these complex issues is reviewed through the lens of the wicked problem paradigm.

Finally, some hope. Communicating systemic aspects of climate‐change mitigation

AbstractClimate communication, including from museums, often advocates individual lifestyle changes, and while these are necessary, the biggest emissions reductions will come from the systemic transition to renewable energy sources. The importance of this systemic change and its attainability has been under‐communicated in the public discourse, although bodies like the Intergovernmental Panel on Climate Change have increased their focus on it. We tested a message focusing on systemic aspects and actions that individuals can do to accelerate the renewable energy transition against a message advocating lifestyle change and a neutral message on the science of climate change. The neutral message elicited the highest levels of negative emotions, whereas the systemic message elicited higher levels of hope. These higher hope levels mediated increased behavioral intentions for doing the suggested system‐aimed actions and for making lifestyle changes. Our results suggest that museums and climate communicators should prominently feature systemic aspects of climate change mitigation.

Greenhouse Gas Emission Estimation Using Extended Input–Output Tables for Thailand’s Biomass Pellet Industry

Greenhouse gas (GHG) emissions from Thailand’s biomass pellet production were comprehensively assessed, with a specific focus on wood and corn pellets. Employing the extended input and output tables, the anticipated economic and environmental effects of the rising demand for biomass pellets within the Asia–Pacific Economic Cooperation region, which is projected to see an increase exceeding 33% by the year 2050, were investigated. The estimations of CO2, CH4, and N2O emissions, which were conducted utilizing an open Leontief model based on the 2015 National Input–Output Tables, covered each stage of the production process. The results show that emissions from the production of corn pellets are expected to rise steadily, from 52.91 MtCO2e in 2022 to 75.77 MtCO2e by 2030, whereas emissions from wood pellet production are set to increase more substantially, from 210.30 to 301.18 MtCO2e within the same timeframe. Data derived from surveys and interviews with corn farmers and wood pellet manufacturers informed the lifecycle data for the biomass pellet supply chain from cradle to gate. The findings suggest that Thailand’s power sector could benefit significantly from the biomass potential in the northern part of Thailand, which boasts an estimated energy content of corncob at 39 ktoe (0.0016 TJ). Market demand scenarios were explored in two forms: one where it was assumed that all biomass pellets are to be exported to Japan and South Korea, expecting a combined demand of approximately 560,262 tons by 2030, and another positing that 10% of production will be reserved for the domestic market, with a forecasted annual increase of 10% from 2020 to 2050. This paper highlights the need to prioritize low-emission renewable energy sources, expand technologies with lower lifecycle emissions, optimize the biomass supply chain to enhance efficiency, and introduce sustainable energy practices. The detailed GHG emissions analysis provides critical insights for policy formulation, underscoring the importance of sustainable transitions in the context of increasing biomass demand.

Design and performance evaluation of a multi-load and multi-source DC-DC converter for efficient electric vehicle power systems

This paper introduces the design and comprehensive performance evaluation of a novel Multi-Load and Multi-Source DC-DC converter tailored for electric vehicle (EV) power systems. The proposed converter integrates a primary battery power source with a secondary renewable energy source—specifically, solar energy—to enhance overall energy efficiency and reliability in EV applications. Unlike conventional multi-port converters that often suffer from cross-regulation issues and limited scalability, this converter ensures stable power distribution to various EV subsystems, including the motor, air conditioning unit, audio systems, and lighting. A key feature of the design is its ability to independently manage multiple power loads while maintaining isolated outputs, thus eliminating the inductor current imbalance that is common in traditional systems. Experimental validation using a 100 W prototype demonstrated the converter’s ability to deliver stable 24 V and 48 V outputs from a 12 V input, with output voltage deviations kept within ± 1%, significantly improving upon the ± 5% deviations typically seen in existing converters. Furthermore, the system achieved an impressive 93% efficiency under variable load conditions. The modular nature of the converter makes it not only suitable for EV applications but also for a broader range of industries, including renewable energy systems and industrial power supplies. This paper concludes by discussing optimization strategies for future improvements and potential scaling of the technology for commercial use in sustainable energy applications.