Multi-energy systems are one of the main solutions to facilitate the integration of renewable energy resources in the smart energy system. To this end, this paper presents a comprehensive structure for the energy system that integrates the electrical, hydrogen, and water sections for sustainable management of modern energy systems. The presented model offers cooperative scheduling for neighbor multi-energy systems that provides the opportunity of local energy trading among them. Also, it focuses on the water system and seeks to supply potable water for the energy systems by a water well, desalination unit, and water storage tank. Besides, compressed air energy storage is developed to utilize the surplus generation of renewable energy to provide an efficient operation for the system. To control the uncertain nature of renewable generation, the energy systems can take part in the electrical and thermal demand-side programs to manage their consumption in response to the signal prices. The proposed model is tested on a standard case study, and the numerical results show that the cooperation among energy systems reduces their operating cost and unserved energy by $ 23.91 and 64.317 kWh compared to autonomous operation.

The inexorable rise in global energy demand, coupled with the pressing imperative to mitigate anthropogenic climate change, has catalyzed unprecedented research effort into renewable energy sources. Photochemistry, the study of chemical reactions initiated by light, is fundamentally shaping this landscape, particularly in solar energy conversion. This review provides a comprehensive and critical analysis of current trends in photochemistry that are directly enabling the development of next-generation renewable energy technologies. We delve into the operational principles, recent advances in materials, and persistent challenges across three pivotal photochemical systems: photoelectrochemical (PEC) devices, artificial photosynthetic systems for solar fuel production, and dye-sensitized solar cells (DSSCs). The discourse highlights the strategic shift from scarce, noble-metal-based components towards earth-abundant alternatives, the integration of molecular and solid-state systems in hybrid architectures, and the critical pursuit of long-term operational stability. While significant progress has been made in understanding charge transfer dynamics and tailoring material properties at the nanoscale, the path to widespread commercialization necessitates continued interdisciplinary innovation to overcome efficiency, durability, and scalability hurdles. This critical evaluation of the current state of the art aims to illuminate both the remarkable achievements and the fundamental scientific questions that remain at the forefront of photochemical energy research.

In the current landscape, the world is grappling with mounting environmental crises and a persistent fossil fuel crunch. Thus, a bold shift toward sustainable, carbon-neutral renewable energy systems with advanced storage and conversion capabilities is crucial to tackle these urgent challenges head-on. In this context, hydrogen (H), with its unmatched gravimetric energy density, stands out as the ultimate clean energy carrier, leaving minimal ecological footprint due to its zero harmful emissions. However, the practical realization of H technologies is hindered by the lack of rational guidelines for designing catalysts that are simultaneously highly active, durable, and cost-effective at industrial scales. It is thus of paramount importance to design materials that combine high activity, long-term durability, and cost-effectiveness to drive the successful adoption of hydrogen-based energy technologies. This review delves into the core-principles of overall water splitting, unravelling its kinetics, the influence of reaction conditions and analysis of metrics involved in performance assessment together with the pivotal role of density functional theory (DFT) and enthalpic contributions in pushing the boundaries of theoretical modelling and tuning of surface energetics, which thereby optimize the H adsorption-desorption dynamics. We also offer actionable, application-focused strategies for designing and selecting industrial-grade HER catalysts and spotlight the fabrication strategies fuelling material innovation, alongside the performance and sustainability of cutting-edge functional materials aimed at sparking further research in this transformative field and advancing the collective mission of safeguarding our planet and its pulse.

Electrochemical water splitting driven by renewable energy provides a sustainable route for generating high-purity hydrogen, yet its efficiency is hampered by the sluggish and economically unfavorable oxygen evolution reaction (OER) at the anode. Replacing OER with the urea oxidation reaction (UOR) has emerged as an attractive strategy to reduce energy input and simultaneously achieve wastewater remediation. Nevertheless, the six-electron transfer process of UOR still suffers from kinetic limitations, highlighting the urgent need for robust and cost-effective electrocatalysts. Recent progress has demonstrated that nanostructure-engineered catalysts enable precise regulation of surface electronic structures, optimization of intermediate adsorption energies, and enhancement of catalytic activity. In this review, we systematically summarize the recent advancements of nanostructural catalysts for UOR-assisted hydrogen evolution, highlighting how rational nanostructuring and compositional engineering contribute to improved intrinsic performance and energy efficiency. The underlying reaction mechanisms are critically discussed based on both experimental and theoretical perspectives. In addition, the practical application of the Zn-urea battery system is introduced, encompassing its electrochemical performance and potential for integrated energy storage and hydrogen production. Finally, we present the current challenges and propose future research directions aimed at bridging the gap between laboratory-scale studies and practical implementation.

Lowering the overpotential of oxygen evolution reaction with electrocatalysts is essential for efficient renewable-electricity-driven electrolysis. Active noble-metal catalysts suffer from leaching and scarcity, while non-noble alternatives face limited intrinsic activity. Here we combine computational guidance with experimental validation to identify atomically dispersed tungsten within NiFe oxyhydroxide, namely W-NiFeOOH, as a promising noble-metal-free oxygen evolution reaction catalyst. An equivariant transformer-based machine-learning interatomic potential accelerates out-of-domain adsorption energy predictions and nominates W-NiFeOOH from 3,976 single-atom-incorporated metal oxyhydroxide configurations. Cyclic-electrodeposited W-NiFeOOH achieves a high current density of 13.1 A cm at 2.0 V and remains stable for 500 hours in alkaline exchange-membrane water electrolysis with commercial membranes. In situ spectroscopy and density functional theory calculations suggest that subsurface W promoter induces synergistic electron redistribution at neighboring Ni-O-Fe edge active sites, thereby lowering the proton-coupled electron-transfer barrier for the deprotonation step and facilitating transformation into the active γ-phase. This integrated computational-experimental workflow provides a blueprint for cost-effective catalyst design for sustainable energy systems.

Wind power forecasting (WPF), as a significant research topic within renewable energy, plays a crucial role in enhancing the security, stability, and economic operation of power grids. However, mid-term forecasting faces a persistent dilemma: achieving high predictive accuracy often comes at the cost of computational efficiency. Existing Transformer-based architectures struggle with this trade-off: traditional temporal attention mechanisms suffer from computational redundancy and weak inter-variable coupling, while recent transposed architectures, despite improving speed, inherently compromise the capture of local temporal dynamics and domain-specific periodic characteristics. To overcome these limitations, this paper proposes Fast-Powerformer. Built upon the Reformer backbone, the model reconstructs the feature extraction paradigm through three complementary strategies: (1) an Input Transposition Mechanism that optimizes multivariate coupling modeling while reducing sequence complexity; (2) a lightweight temporal embedding module that compensates for the intrinsic deficiency of transposed architectures in capturing local sequential features; and (3) a Frequency Enhanced Channel Attention Mechanism (FECAM) that exploits spectral information to characterize the physical periodic patterns of wind power. Experimental results on multiple real-world wind farm datasets demonstrate that Fast-Powerformer achieves the best overall performance among compared methods. The model successfully balances superior accuracy with reduced resource consumption, highlighting its significant practical potential for resource-constrained scenarios.

For industrial water electrolysis, the development of active and stable catalysts for the oxygen evolution reaction remains a challenge. Here, we report a heterostructure catalyst composed of NiFe layered double hydroxide nanosheets anchored on pyramidal Fe(MoO) to activate lattice oxygen for efficient and durable oxygen evolution. Our investigation reveals that oxygen vacancies within the NiFe layered double hydroxide and the internal electrical field at the material interface optimize the electronic states, allowing oxygen atoms within the crystal lattice to participate directly in the reaction. The resulting heterostructured NiFe LDH/FeMoO catalysts possess high oxygen evolution reaction activity in 1 M KOH electrolyte with a low overpotential of 316 mV at 2 A cm and maintain long-term stability over 3,000 h. Furthermore, integrating this anode into a solar-powered electrolyzer yields a high solar-to-hydrogen efficiency of 20.15%. This work provides a promising strategy for designing stable catalysts and advancing the integration of renewable energy with water electrolysis to produce clean hydrogen at scale.

Electromobility can contribute to a reduction in greenhouse gas emissions if usage behavior is aligned with the increasing availability of renewable energy. To achieve this, smart navigation systems can be used to inform drivers of optimal charging times and locations. Yet, required flexibility may impart time penalties. We investigate the impact of financial and symbolic incentive schemes to counteract these additional costs. In a laboratory experiment with real-life time costs, we find that monetary and symbolic incentives are both effective in changing behavior towards 'greener' charging choices, while we find no significant statistical difference between them.

This case study presents an analysis and quantification of the impact of the lack of co-optimization of energy and reserve in the presence of high penetration of wind energy. The methodology is developed in a companion paper, Part I. Two models, with and without co-optimization are confronted. The modeling of reserve and the incentive to renewable as well as the calibration of the model are inspired by the Spanish market. A sensitivity analysis is performed on configurations that differ by generation capacity, ramping capability, and market parameters (available wind, Feed in Premium to wind, generators risk aversion, and reserve requirement). The models and the case study are purely illustrative but the methodology is general.

The Synthesis Report (SYR) distils and integrates the findings of the three Working Group contributions to the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), the most comprehensive assessment of climate change undertaken thus far by the IPCC: Climate Change 2013: The Physical Science Basis; Climate Change 2014: Impacts, Adaptation, and Vulnerability; and Climate Change 2014: Mitigation of Climate Change. The SYR also incorporates the findings of two Special Reports on Renewable Energy Sources and Climate Change Mitigation (2011) and on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (2011).