Thermochemical energy storage: bridging the gap between solar energy and long-term energy storage

Large-scale deployment of renewable energy systems is central to global decarbonisation strategies, yet integration at high penetration levels remains constrained by interacting technical, economic, infrastructural, and socio-regulatory barriers. Existing review studies typically examine these challenges in isolation or within single-technology silos, limiting system-level prioritisation across renewable technologies. This study presents a semi-systematic integrative review of recent literature (2020–2025) to develop a unified classification framework that links integration barriers with corresponding solution pathways across solar, wind, and hydropower systems. The proposed framework explicitly captures interactions between technical constraints (e.g., intermittency, grid stability, power quality), economic limitations (e.g., capital intensity, financing risk, market design), transportation and storage bottlenecks, and social–regulatory factors. A comparative severity-weighted heat-map is introduced to assess the relative impact of these barriers across technologies, enabling cross-sector prioritisation rather than technology-specific diagnosis. The review synthesises system-level solution pathways, including hybrid renewable configurations, sector-coupled integrated energy systems, advanced storage portfolios, Power-to-X routes, and green hydrogen as a long-duration flexibility vector. Techno-economic optimisation tools such as HOMER are critically assessed as screening-level instruments for hybrid system design, with explicit discussion of their applicability limits under high-renewable, network-constrained conditions. The findings suggest that effective renewable integration is increasingly dependent on the coordinated deployment of flexibility, cross-sector coupling, and coherent policy and market frameworks, rather than incremental technology-specific improvements. By aligning barrier severity with solution pathways across multiple renewable technologies, this review provides practical guidance for policymakers, system planners, and industry stakeholders seeking reliable and cost-effective pathways toward net-zero energy systems.

Interseasonal solar thermal energy storage in abandoned mine shaft: A study based on TRNSYS

Current trends and challenges in solar PV-integrated battery energy storage technology: Key components, methods, and future prospects

Application of deep learning in wind, solar, and ocean energy: An analysis of prediction, optimization, and operation & maintenance

Sustainable hybrid solar drying technologies with auxiliary heating systems: A comprehensive review of design, performance, and deployment approaches

Density functional theory analysis of Na3AgO: Assessing its viability as a sustainable material for solar energy applications

Experimental investigation and analysis of a direct expansion photovoltaic-thermal heat pump system with optimized solar energy harvesting

Mata Vaishno Devi Shrine in Jammu and Kashmir is the best visited religious site in India with millions of pilgrims every year thronging this site. Although its religious and economic importance is beyond measure, the sheer number of pilgrimage tourism traffic has already presented a lot of environmental pressure on the location. Among the serious issues are challenges of waste production, water preservation, land degradation and quality of air. The research will look at the effects of pilgrimage tourism on the environment of the shrine environment and suggest a competency model of sustainable tourism growth towards introduction of technological advancements and community integration consideration. The study uses a qualitative method to examine both environmental tasks, the fieldwork, and the interviews conducted with the stakeholders. It singles out practices of proper waste management, water recycling, and energy efficiency such as the adoption of smart waste system, solar energy solution, and control with RFID features. The paper is applicable to the United Nations Sustainable Development Goals (SDGs), especially SDG 12 (Responsible Consumption and Production) and SDG 13 (Climate Action) and it can be used to provide a transferable construct on sustainable pilgrimage tourism. In the paper policy recommendations are offered that can come into place by the local authorities and they are mainly concerned with controlling the number of pilgrims, the management of waste products as well as fully capitalising on water and energy consumption. This study will make a contribution to the overall discussion regarding sustainable tourism practices in pilgrimage destinations by providing practical remedies to the reduction of any environmental impact without compromising on culture and spiritual heritage.

In this work, first-principles calculations based on density functional theory (DFT) are employed to investigate the structural, mechanical, and optoelectronic properties of a series of penta-graphene-like monolayers. Structural, dynamical, and mechanical stability are confirmed by the absence of imaginary phonon modes and by compliance with the Born–Huang criteria for two-dimensional systems. The investigated monolayers exhibit indirect band gaps as calculated using the hybrid HSE06 functional, with values of 2.68, 1.91, 2.42, 1.79, 2.57, 1.91, 2.46, and 1.82 eV for AgAlS 4 , AgAlSe 4 , AgInS 4 , AgInSe 4 , CuAlS 4 , CuAlSe 4 , CuInS 4 , and CuInSe 4 , respectively. The optical absorption spectra indicate strong optical activity spanning the visible to ultraviolet regions. Excitonic effects are also significant, with binding energies ranging from 421 to 488 meV, indicating robust Coulomb interactions in these 2D materials. The theoretical Shockley–Queisser and maximum SLME limits predict upper-bound power conversion efficiencies up to 28.47%. In contrast, the directly computed SLME efficiencies are below 0.27% due to the ultrathin character and limited optical absorbance of the monolayers. Overall, the results demonstrate that penta-structured monolayers are promising candidates for next-generation optoelectronic and solar energy harvesting devices.

Synergistic water-electricity cogeneration enabled by topology engineering hierarchical MoS2 decorated hollow carbon heterostructures for enhanced solar energy utilization

Investigating the performance-cost of different system configurations for green hydrogen production utilizing dual solar energy conversion forms to power the electrolyzer

AI-driven bandgap engineering of Mg–Ca Co-doped HgS semiconductors: A hybrid ML–DL–DFT+U framework for next-generation solar energy materials

Efficient photoelectrocatalytic ammonia synthesis over graphene oxide-modified Fe-based metal-organic frameworks with high conductivity and photoresponsivity.

Bio-based shape-stabilized composite phase change materials (ss-PCMs) are emerging as sustainable solutions for thermal and solar energy harvesting. However, typical shape-stability issues, poor thermal/optical properties, and complex synthesis methods hinder the use of such materials at large scale. This study reports the design of nanofiller-loaded bio-based composite PCMs with enhanced thermo-optical and mechanical properties (shape-stability). Incorporating a 25 wt% biomass-derived porous matrix (coffee/turmeric powder) significantly enhanced the material's structural integrity by effectively controlling PCM leakage while achieving a high latent thermal energy storage (TES) capacity of ∼130 J/g. Graphene-loaded ss-composite PCMs demonstrated a significant photothermal conversion efficiency enhancement (106 %) and effective thermal management (TM) potential (superheat degree reduced by ∼ 10 °C) compared to pristine PCM, due to the improved photo-thermal properties and power density. Thermal cycling (up to 500 cycles) and load-bearing capacity tests (∼212,566 and ∼31,242 N/m 2 across the phase transition zone) confirm the high reliability of the proposed novel ss-composite PCMs in terms of thermal and shape stability. These results highlight their strong potential for long-term TES applications, with stable performance even under adverse environmental conditions such as humidity and wetting. This research contributes to the design of bio-compatible (possibly edible) substance-based strategies for creating cost-effective composite PCMs with enhanced thermo-optical and shape stability characteristics, offering significant advancement for latent TES systems and TM technologies. Highlights • Coffee and turmeric bio-based porous framework improves structural integrity. • Sustainable PCM composites with superior power density and stability for TES. • PCM composite with superior PTC and thermal management capacity. • Newly designed cost-effective and environmentally friendly shape stabilized PCMs.

This project focuses on designing an agrivoltaic system integrated with smart irrigation to promote sustainable agriculture and efficient resource management. The system combines solar photovoltaic (PV) panels with agricultural land to generate renewable energy while cultivating crops, thereby achieving dual land utilization. The solar panels provide electricity for powering irrigation pumps and IoT based sensors, which monitor soil moisture, weather data, and crop conditions in real time. A smart irrigation mechanism uses this data to automate water distribution, ensuring crops receive the right amount of water at the right time, minimizing waste and reducing water consumption. Additionally, the shading effect of solar panels reduces soil evaporation and heat stress on crops, leading to improved crop yield and resilience against climate variability. Surplus solar energy can be stored or sold back to the grid, creating an extra source of income for farmers. This project aims to demonstrate an energy efficient, water saving, and climate smart agricultural model that is scalable for both small and large farming operations, addressing the pressing challenges of food security, water scarcity, and sustainable energy production.

The radiative nanofluids have versatile implications in modern industrial and technological applications, including heat exchangers, solar energy devices, chemical reactors, lubricants, missile technology, renewable solar energy equipment, air conditioners, food processing, etc. Having all these modern appliances in view, this research emphasized the 3D (three-dimensional) bidirectionally stretched radiative flow of Maxwell nanofluid flowing over the chemically reactive stretched surface. The energy and solutal transmission analysis is conducted using the utilization of non-Fourier energy and non-Fick’s mass flux models. Waste-discharge solute aspects are considered in the mass species relationship. The thermally radiative and chemically reactive Robin’s conditions are imposed at the boundaries of the chemically reactive stretched surface. The assumptions of the boundary layer (BL) are taken into account for the formulation of the problem. The resulting nonlinear dimensional model is converted into a dimensionless system of equations by the implication of feasible similarity variables. This non-dimensional model is treated numerically with the help of the RKF-45 (Runge–Kutta–Fehlberg) method along with the shooting scheme. The comparative analysis is executed to assess the appropriateness of the current methodology. The results are reported in the form of sketches and tabular data. The thermal field is declined against the higher Prandtl number. Sherwood number is enhanced for larger Schmidt numbers because of reduced mass diffusivity, while solutal relaxation and chemical reaction parameters significantly regulate the surface mass transfer rate.

ABSTRACT Photovoltaic (PV) systems are an invaluable green power solution to the energy requirements in the world yet as they are placed outside, they are subject to numerous issues and environmental challenges that may lead to loss of efficiency in the systems and even system failures. Thus, early and accurate fault diagnosis is necessary to minimize downtime and costs of maintenance. This paper proposes an automated PV-based fault diagnosis system with the aid of a pre-trained image-based InceptionV3 convolutional neural network, which can find faults in panels. The model was trained and tested on a diverse dataset of 885 images to classify six categories of conditions, including physical degradation, electrical degradation, bird droppings, dust, snow coverage, and fault-free panels. Using transfer learning and extensive data augmentation, the model achieved a good overall test-based accuracy of 85.71%. The comprehensive analysis of the performance showed that it was highly suitable for detecting Dusty, Clean, and Bird-drop classes with high F1-scores. However, the model struggled with the lower recall Physical-Damage class, indicating that it was not fully reliable in detecting subtle physical defects such as cracks. The results, complemented by ROC curves and confusion matrices, determine the extent to which the InceptionV3 architecture is appropriate for this task and highlight some diagnostic limitations. This article is important in providing more reliable and cost-effective solar energy production by creating a clear and methodologically rigorous standard for automated PV fault detection.

This paper proposes an integrated and optimally tuned photovoltaic water pumping system (PVWPS) with high performance and operational stability under variable climatic conditions. The pumping process starts with PV arrays that transform solar energy into electricity to drive the centrifugal pump through an induction motor and an inverter. To evaluate and optimize system performance, three control strategies have been implemented and compared: Direct torque control (DTC), Predictive torque control (PTC), and the proposed Gorilla Troop Optimization-PTC (GTO-PTC) with an optimized PI speed controller. In this improved method, the GTO is applied to optimally tune the proportional integral (PI) controller parameters and address the limitations of conventional controllers. The Incremental Conductance algorithm has also been adopted for the maximum power point tracking (MPPT) to achieve maximum energy extraction from photovoltaic panels, due to its high accuracy and excellent stability. The presented system was developed and tested in MATLAB/Simulink to assess its performance across various operating scenarios. The comparative results show that PTC outperforms DTC by reducing torque and flux ripples, improving current quality, and achieving faster dynamic response. Moreover, the integration of PI-GTO-PTC significantly enhances control accuracy, reduces oscillations, and improves the system's overall efficiency.

Quantum dot (QD)-organic hybrid materials offer promising spectral conversion platforms for applications such as photoredox catalysis, solar energy conversion, 3D printing, and bioimaging. In spectral upconversion, the overall triplet energy transfer (TET) efficiency remains limited due to inefficient secondary TET that occurs beyond the QD core, i.e., from triplet mediators to annihilators (TET2). Here, we reveal that the hydrocarbon ligands on nanoparticles can remotely govern this external TET2 that occurs entirely outside the core. By shrinking the native oleate ligand shell on PbSe QD sensitizers before attaching triplet mediator ligands, the NIR-to-visible upconversion performance can be significantly improved. Transient absorption spectroscopy confirms that the more compact ligand shell substantially accelerates TET2, boosting the highest transfer efficiency from 59.4% to 93.5%. We propose that the enhanced TET2 stems from shortened mediator-annihilator distances induced by reduced steric hindrance from the shorter, proximal hydrocarbon ligands, as confirmed by molecular dynamics simulations. The strategy proves versatile across multiple upconversion systems, including solid-state films, CdSe QD-based green-to-blue systems, and lanthanide-doped nanoparticle-sensitized hybrids. Furthermore, the same principle remains applicable to molecular singlet fission-based downconversion using QD as photon emitters, raising the highest photon-multiplication efficiency from 132% to 163%. Our work demonstrates that ligand shell proximity can remotely tune TET beyond the nanoparticle core, providing a general route to optimize inorganic-organic hybrid spectral up- and downconverters.