Journal of Alternative and Renewable Energy Sources

Green Hydrogen as an Alternative Renewable Energy towards attainment of Sustainable Development Goals (SDGs): A Review

2026-08-13T06:26:11+00:00

Hydrogen can be produced from fossil fuels, like natural gas, and renewable energy sources. But green hydrogen from renewable energies like solar and wind is emerging as a key player in the energy transition towards achieving global SDGs. The study analyses the recent advancements in green hydrogen production technologies, while evaluating green hydrogen against hydrogen from fossil fuels and natural gas. Even though green hydrogen is more advantageous than hydrogen from other methods, green hydrogen has to face challenges in terms of high costs in production, processes, and infrastructure for storage, along with transportation. Global investments and policy initiatives are factors influencing a reduction in the cost of production to below $2/kg by 2030. Europe, Asia, and Australia are taking the initiative to support large-scale green hydrogen production, with enhanced electrolyser capacity. They are also trying to integrate green hydrogen into industrial, transportation, and power generation sectors to meet the energy crisis due to developmental activities. The advancements in electrolyser efficiency, material innovations, and renewable energy integration are expected to achieve commercial viability of green hydrogen. This review article elaborates key strategies, policy frameworks, and technological improvements for green hydrogen adoption, as it is a crucial component for carbon neutrality and energy security to accomplish the SDGs mission.

Agrivoltaics: A Review of Sustainable Integration Between Solar Energy and Agriculture

2026-08-10T05:56:58+00:00

The combination of agriculture and solar photovoltaic systems, referred to as agrivoltaics, has gained importance as an efficient strategy for meeting the increasing energy needs and addressing global food security concerns. Given the current competition in terms of land resource utilization, agrivoltaics presents a promising solution for enhancing land productivity and generating renewable energy. The objective of this review paper is to evaluate the latest advances in agrivoltaics in terms of design optimization, partial shading effects, environmental benefits, and socio-economic considerations. This research follows the systematic review method by considering scientific literature published from 2022 to 2025 in reputable academic databases. Selected papers are examined with respect to different aspects like land use efficiency, crop productivity, energy production, water use efficiency, and economic feasibility. Special focus is given to novel technologies in the field of solar PVs, such as semi-transparent, bifacial, and intelligent tracking PV panels. It is found that agrivoltaics can lead to higher overall productivity of land by up to 60-70% compared to single land use systems. The partial shading effect provided by solar PV modules results in the creation of favorable microclimate conditions, resulting in lower soil temperatures, reduced evapotranspiration rates, and enhanced soil moisture content. Moreover, agrivoltaic farming provides farmers with double earning potential, thus boosting their financial sustainability. To conclude, agrivoltaic systems can be considered a viable and scalable solution for land use practices. Yet, several issues, including high upfront costs and policy restrictions, should be tackled to implement these technologies on a larger scale.

A Smart Pedestrian Motion-based Energy Harvesting Model with Efficient Power Conversion and Storage Integration

2026-07-21T11:23:50+00:00

The increasing demand for sustainable and eco-friendly energy solutions has led to the exploration of unconventional energy sources. This project proposes a smart footstep power generation system that converts mechanical energy from human walking into electrical energy using the Piezoelectric Effect. When pressure is applied on piezoelectric sensors embedded beneath walking surfaces such as floors, roads, or staircases, electrical energy is generated due to the deformation of the material.

The generated energy is collected, stored in batteries, and can be used for low-power applications such as LED lighting, mobile charging, and sensor-based systems. This system is particularly suitable for high-footfall areas like railway stations, shopping malls, and educational institutions. Additionally, the project can be enhanced with smart monitoring using microcontrollers to track energy generation in real time. This innovative approach not only promotes renewable energy usage but also contributes to energy conservation and sustainability by utilizing otherwise wasted human kinetic energy. The system is cost-effective, environmentally friendly, and has potential for future smart city applications.

A Systematic Review of Artificial Intelligence Applications in Renewable Energy Systems

2026-08-10T12:06:49+00:00

The rapid Progress toward sustainable energy development has advanced the implementation of Artificial Intelligence (AI) to address the operational, technical, and economic challenges associated with renewable energy integration. This systematic review provides a comprehensive analysis of recent advances in the application of artificial intelligence to renewable energy systems, with a focus on machine learning, deep learning, reinforcement learning, explainable AI, and hybrid optimization approaches. The review follows a structured systematic methodology based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, covering peer-reviewed studies published between 2020 and 2026 from major scientific databases. The findings reported across the reviewed studies highlight that AI now serves as a transformative technology across multiple renewable energy domains. AI-driven models significantly enhance renewable energy forecasting, predictive maintenance, fault diagnosis, energy management, load prediction, demand response, and system optimization, resulting in improved operational efficiency, reliability, and cost-effectiveness. Deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) networks, have demonstrated remarkable accuracy in forecasting renewable energy generation. Additionally, reinforcement learning and metaheuristic optimization techniques facilitate adaptive energy management and improve resource allocation efficiency. Emerging technologies, including digital twins, federated learning, edge AI, generative AI, and explainable AI, are further expanding the capabilities of intelligent renewable energy systems. Despite notable advancements, several issues continue to hinder progress, such as the scarcity of reliable datasets, concerns related to cybersecurity and data privacy, limited transparency of predictive models, high computational requirements, difficulties in integrating with existing infrastructure, and the absence of universally accepted benchmarking standards. This review highlights major research gaps and outlines potential directions for future investigations, with a particular emphasis on trustworthy AI, physics-informed machine learning, multimodal data fusion, autonomous energy management systems, and AI-enabled carbon-neutral energy infrastructures. The results indicate that artificial intelligence can significantly contribute to the development of resilient, intelligent, and sustainable renewable energy systems. This review provides researchers, engineers, policymakers, and industry practitioners with a comprehensive understanding of current developments and opportunities at the intersection of artificial intelligence and energy technologies.

Using the Z Catalytic Technique, Conversion of Different Renewable Energy Resources, Like Vegetable Oil into Biodiesel for Sustainable Development

2026-07-21T11:32:51+00:00

In an era marked by rapidly rising energy demands and the continued use of fossil fuels, the need for and search for sustainable fuels have become a global priority. However, the ongoing decline in fossil fuel reserves has raised serious concerns about energy shortages and environmental pollution. This has encouraged scientists to explore renewable fuel options that are safer for nature. Biodiesel is one such fuel that can be produced from natural sources such as plant oils, animal fats, and recycled cooking oil. This study explains how biodiesel production has developed over time, starting from early uses of natural oils to today's advanced technological methods. It also describes the reasons for its growing importance, the materials required, the production steps, the cost factors, and the environmental advantages. In addition, the paper highlights India's efforts, government initiatives, and the role of modern technologies, such as artificial intelligence, in improving efficiency and reducing waste, as well as the history and need for Biodiesel. The study shows that Biodiesel has strong potential to become an important and eco-friendly fuel in the future as conventional diesel resources continue to decline.