Abstract

Addressing climate change and advancing the SDGs necessitate a rapid and equitable global energy transition. Within this transition, electrification is pivotal for enhancing energy accessibility, stimulating economic growth, and reducing carbon emissions. Yet, existing disparities in technological capabilities, policy frameworks, and socio-economic conditions risk exacerbating inequalities and vulnerabilities. This study develops a novel and comprehensive indicator system to assess ES and EE. Utilizing K-means clustering across 123 countries, we identify distinct patterns of electrification, ES, and EE, revealing significant cross-national disparities in energy transition outcomes. Four distinct clusters emerge: “advanced,” “balanced development,” “transition-challenged,” and “lagging.” By dissecting the unique characteristics and challenges of each cluster, this study provides a scientific foundation for designing differentiated energy transition strategies. It offers targeted policy recommendations and optimized transition pathways to improve resource allocation, advance global energy equity, and promote sustainable development. This research aims to provide empirical evidence and theoretical insights for policymakers, offering practical pathways toward energy justice and sustainable development globally.

Abstract

Agrivoltaic systems (AVSs) provide a promising strategy to reconcile Japan’s competing land demands for renewable energy and food production. Yet the spatial distribution of AVS designs that reflect the country’s pronounced climatic diversity remains poorly quantified. This study performed a nation‑wide optimization of fixed‑tilt, elevated AVS designs for lowland rice cultivation by coupling 1‑km MONSOLA‑20 monthly radiation data with a computationally efficient crop‑light model. For every one of 376,871 grid cells we identified the projected ground coverage ratio (pGCR) that balances power production and agricultural environmental impacts. The resulting optimal pGCR averaged 20.33%, yielded an average land‑equivalent ratio (LER) of 1.64, demonstrating significantly higher land productivity compared to conventional separate production systems. The resulting AVS design map offers location‑specific guidance for growers, developers, and policy‑makers, thereby facilitating the responsible expansion of AVSs and the formation of resilient urban‑rural food‑energy partnerships in Japan.

Abstract

As urban expansion drives escalating building energy consumption, responsible for a third of global energy-related COâ‚‚ emissions, building-integrated photovoltaics (BIPV) present a multifunctional renewable energy solution. Addressing the limitations of previous single-city evaluations, this study establishes a spatial assessment framework integrating both rooftop photovoltaic (RPV) and facade photovoltaic (FPV) systems across prefecture-level 360 Chinese cities, encompassing 7.7×10⁴ km² of installation areas. Our analysis demonstrates that the total BIPV generation potential reaches 10,023 TWh annually, equivalent to 126% of China’s current electricity demand, in addition to a carbon mitigation potential of 8.32 Gt. Spatial cluster analysis reveals four distinct city typologies: high-density metropolises (Cluster 1), emerging industrial hubs (Cluster 2), developing inland cities (Cluster 3), and the cities in the western region (Cluster 4). Particularly, Cluster 1 cities exhibit 3.8 times greater photovoltaic potential per unit area than the national average, suggesting that these cities are strategic priorities for the energy transition. This spatially explicit evaluation methodology provides decision-support tools for optimizing photovoltaic urban planning and formulating regionalized renewable energy policies, offering practical insights for achieving carbon neutrality targets.

Abstract

To achieve carbon neutrality in the building sector, advanced low-carbon designs such as Zero Energy Buildings (ZEBs) are increasingly being adopted globally. However, ZEBs often requires significantly higher investment compared to general low-carbon methodologies in buildings. In urban settings, these advanced solutions tend to be implemented primarily by large corporations with sufficient capital, technical expertise, and human resources. In Japan, over 98% of enterprises are classified as small and medium-sized enterprises (SMEs), SMEs often face significant challenges in adopting similar approaches.
Aiming whole carbon neutrality, there is a growing need to develop cost-effective and operationally feasible low-carbon methodologies tailored specifically for SMEs. Such strategies must accommodate both limited financial and ease of daily operation, especially in urban business districts predominantly occupied by SMEs.
This study explores the feasibility of developing an Area Energy Management System (AEMS) to support carbon neutral transitions among SMEs in a test site of “Kanda and Nihonbashi” area in central Tokyo where is known business district for its traditional character and concentration of long-established SMEs.
The methodology includes the following steps;1) Characterization of the Urban Context by GIS, 2) Estimation of Energy Consumption, 3) Development of tailored low-carbon strategies.
This research demonstrates the potential for a localized, collaborative approach to carbon neutrality, emphasizing the development of pragmatic and scalable solutions for SMEs.

Abstract

Numerical studies were conducted to investigate the conjugate heat transfer characteristics of a mist/steam-cooled high-pressure turbine vane in a hydrogen gas turbine, which was proposed for a hydrogen fuel pure oxygen combustion gas turbine combined cycle with flow bypass and recompression. A double-wall cooling vane operating in a real turbine environment was considered. The effect of mist injections on the overall cooling effectiveness of the steam-cooled double-wall vane of a hydrogen gas turbine was investigated by varying the mist concentration (5% ≤ ms ≤ 20%) and droplet size (5 μm ≤ dp ≤ 20 μm). The ms and dp have a synergistic effect on the overall cooling effectiveness, and it tends to increase with increasing ms, especially at the suction side. The highest averaged overall cooling effectiveness of the steam-cooled vane at the mid-span of the vane was obtained at ms = 20% with a relatively small particle size of 10 μm, which was approximately 11% higher than that without mist, corresponding to an 88.6K drop in the vane’s wall temperature.

Abstract

With the expansion of urban electric vehicle (EV) fleets, utilizing EVs as distributed energy storage has become a key approach to enhancing energy system resilience, particularly in power shortage scenarios. This study proposes a proactive heuristic dispatch method for EVs, which integrates dynamic resource partitioning and user willingness modeling. The method enables intra-zone discharging of available EVs prior to outages, based on priority rules, to alleviate power shortages. In addition, it incorporates outage detection and EV behavior simulation modules base on real-world data, that provides reliable spatiotemporal data to support dispatch decisions. Simulation results indicate that the proposed method has the potential to alleviate power outages through EV dispatch, but its current effectiveness remains limited due to practical constraints—particularly the restricted availability of discharging locations at electric vehicle charging station (EVCS). Nevertheless, it provides preliminary validation and practical insights into the potential of EV dispatch for enhancing urban energy resilience.

Abstract

The objective of this paper was to define and demonstrate a model that simulates electricity consumption on pasture-based beef farms. The Beef Farm Electricity Model (BFEM) was designed to simulate electricity consumption across beef farm operations, including water pumping, electric fencing, lighting, and other electrically powered infrastructure. BFEM employed grey box modelling techniques that utilised empirical data for tuning model parameters and was trained using empirical data from 12 pasture-based Irish beef farms. The results showed strong agreement between simulated and actual electricity use, with moderate predictive accuracy for water pumps (RMSE = 12.79 kWh, MAPE = 8.13%) and lighting systems (RMSE = 9.53 kWh, MAPE = 11.00%). Prediction accuracy for electric fence electricity use was lower (RMSE = 9.85 kWh, MAPE = 58.46%). These findings demonstrated BFEM’s potential as a decision-support resource for energy auditing, infrastructure planning, and facilitating the integration of renewable energy systems on beef farms.

Abstract

Rural-residence-converted guesthouses often suffer from high energy consumption and a lack of effective energy-saving measures, indicating a significant potential for efficiency improvements. This study proposes a practical and rapid calibration method for energy simulation models tailored to such buildings, where guestroom occupancy status is treated as an optimization variable. By minimizing the monthly deviation between simulated and actual energy consumption, efficient initial calibration is achieved. Using a typical guesthouse in Zhejiang Province as a case study, the optimization results show monthly energy deviations ranging from 0.05 to 23.75 kWh, with corresponding occupancy rates between 20% and 80%. The calibrated model achieved a Normalized Mean Bias Error (NMBE) of 0.067% and a Coefficient of Variation of the Root Mean Square Error (CV(RMSE)) of 0.947%, both satisfying the accuracy criteria of ASHRAE Guideline 14. The proposed method provides an efficient and practical approach for calibrating energy models in guesthouse buildings, serving as a foundation for subsequent energy retrofit planning.

Abstract

With accelerating climate change and policy-driven mandates for carbon neutrality, cities are prioritizing low-carbon transitions in energy systems. In response to this urgent need, this paper proposes a low-carbon-oriented planning framework for urban multi-operator integrated energy system (UMIES), integrating multi-operator coordination, carbon emission cost and system feasibility. Firstly, a novel low-carbon/economic feasible region model is developed to harmonize multi-operator resource allocation with carbon reduction goals, and the low-carbon-oriented optimal allocation model is further developed. Then, the coordinated planning approach based on feasible region projection is proposed, which enables the multi-operator optimal allocation realized in a privacy-protected, iteration-free and calculation-distributed fashion. Case studies validate the method’s efficacy in balancing economic viability, carbon mitigation, and privacy protection, offering a practical pathway for sustainable urban energy planning.

Abstract

Vertical farming enables high-yield crop production with minimal land use in urban areas, supporting sustainable food systems, but its large energy demand presents a significant challenge. This study employs the vertical farming model developed by the German Aerospace Center to evaluate the impact of integrating passive building design, photovoltaic power systems, and energy storage systems on energy consumption, carbon emissions, and economic performance. By developing a parameter optimization model, the energy system of the vertical farming building can be systematically optimized. Using Shuangliu District in Chengdu, China as the case area, simulation results show that the annual energy consumption of the building is reduced by 84.7 million kWh, and carbon emissions decrease from 82.96 to 36.37 million kg COâ‚‚ per year. The return on investment of the photovoltaic and energy storage systems in vertical farming reaches 11.07, indicating high economic viability alongside significant environmental benefits. These findings confirm the technical and economic feasibility of integrating renewable energy systems and energy storage into vertical farming, advancing its potential as a scalable model for low-carbon, resilient, and sustainable urban agriculture.