Search Results (10,043)

Accurate wind speed forecasting plays a crucial role in the safe and stable operation of wind farms and the efficient integration of renewable energy into modern power systems. However, wind speed exhibits complex spatiotemporal variations affected by diverse meteorological conditions, making high-precision prediction a long-standing bottleneck in wind power scheduling. This paper develops a U-shaped spatiotemporal feature fusion network named U-STNet, which realizes joint modeling of inter-turbine spatial correlations and multi-period long-range temporal dependencies. The model maps raw wind speed series to high-dimensional embeddings and adopts an encoder–decoder U-shaped architecture to complete feature encoding, reconstruction and multi-scale feature extraction, which effectively captures the inherent periodic and seasonal patterns of wind speed. Experiments on the SDWPF wind farm dataset show that U-STNet obtains competitive prediction accuracy across all multi-step forecasting horizons. Compared with traditional statistical models, recurrent neural networks and state-of-the-art Transformer baselines, the proposed method exhibits more stable error accumulation characteristics and superior long-step prediction performance. This verifies the effectiveness of jointly modeling turbine spatial topology and multi-scale temporal dependencies for wind speed forecasting. Full article

This paper examines how the body of research and innovation on electric cooking for low- and middle-income countries has evolved to the extent that electric cooking can now be argued to have the potential to influence energy system performance. Methods: The paper synthesises recent evidence on electric cooking from pilots, market developments, and system-level analysis across Africa and Asia, focusing on demand patterns, utility economics, carbon finance mechanisms, and emerging digital and financing models. Results: Electric cooking is increasingly argued to be acting as a system-strengthening source of demand, rather than a system stressor. Two reinforcing mechanisms are identified: (i) an electricity revenue loop, in which increased consumption can improve utility and mini-grid viability and support further investment, and (ii) a carbon finance loop, enabled by metered methodologies and measurable emissions reductions, which can improve household affordability and accelerate adoption. The analysis also highlights the importance of diversified demand (household, commercial, and institutional), which has great potential to improve load factors and align demand with generation. However, a persistent planning blind spot remains, with growth in electric cooking demand largely excluded from energy models. Conclusions: Electric cooking is moving from proof of concept toward tangible system integration, but scale is constrained by affordability, reliability, tariff design, fuel stacking, institutional fragmentation, and carbon market uncertainty. The findings suggest that electric cooking should increasingly be treated as a core component of energy system design, requiring coordinated policy, planning, and financing to realise its full potential. Full article

Teacher leadership has gained increasing attention since the 1980s. With the various operationalizations of teacher leadership in research and practice as well as mixed results of effects of teacher leadership, we sought to investigate the difference in teacher leadership under the school reform and renewal approaches. We delineated nuanced differences in teacher leadership under the two approaches and provided empirical illustrations, including (a) boundary spanning vs. embedded co-construction, (b) compliant sense-making vs. holistic, generative sense-making, (c) episodic, task-based engagement vs. sustained, identity-based stewardship, (d) initiative-driven activation vs. developmental capacity building, and (e) parallel leadership vs. integrated leadership. The illustrations were based on three large school leadership projects conducted from 2017 to the present. The article creates a nuanced understanding of teacher leadership by situating its construct and practice in a larger school improvement context. Full article

The integration of photovoltaic generation, battery storage, electric vehicles, smart appliances, and dynamic electricity pricing has made residential energy management a challenging real-time optimization problem. Conventional demand-side management methods often depend on fixed rules and are less effective under uncertain solar generation, changing tariffs, and variable user demand. To address this issue, this paper proposes a Proximal Policy Optimization-based deep reinforcement learning framework for smart home energy management. The proposed PPO controller learns adaptive scheduling decisions using real-time PV output, electricity price, battery state of charge, EV charging status, and appliance operating conditions. The controller coordinates shiftable, controllable, and non-shiftable loads while reducing electricity cost and maintaining user comfort. The proposed method is compared with DDPG and TRPO. Simulation results show that PPO reduces the average daily energy cost by 4.7% compared with TRPO and 8.3% compared with DDPG. The results confirm that PPO is an effective and stable approach for real-time residential demand-side management. Full article

Against the backdrop of the dual-carbon goals, a new power system is undergoing rapid construction, and distributed renewable energy is being connected at high density to regional ring networks. This study deeply explores the impact of photovoltaic (PV) power station connection positions on energy distribution and flow, as well as the voltage and energy loss of ring networks. Firstly, it takes the actual 220 kV/500 kV ring network in a certain city in Yunnan Province as the research object, and constructs a high-precision ETAP simulation model. It then systematically explores the mechanism of how PV power connection positions and grid connection penetration rates affect node voltage and line loss and derives the energy loss calculation formula. On this basis, two differentiated operation scenes corresponding to renewable energy output peaks and valleys are established. Through comparative analysis of multiple sets of simulation data, this study reveals the coupling laws among PV output fluctuation, bidirectional reverse power flow, system energy loss, and voltage over-limit. Finally, combined with the operational pain points of existing ring network and distribution network connection modes, this study proposes diversified loss reduction optimization strategies, including coordinated optimization of active and reactive power, and coordinated regulation of PV power and energy storage. The relevant research conclusions and optimization methods can improve the line loss analysis theory for ring networks integrated with PV power, and provide important engineering references for renewable energy planning and design, operation regulation, and loss management for similar mountain power grids. Full article

Solar tracking can increase photovoltaic (PV) energy yield, but its contribution to sustainable electricity depends on more than geometric gain. This structured narrative review evaluates flat-plate and low-concentration PV trackers using an integrated three-layer taxonomy covering mechanical architecture, actuation and drivetrain, and control strategy. Tracker classes are compared in terms of annual energy gain, life-cycle cost, parasitic consumption, land-use efficiency, structural resilience, reliability, maintainability, and deployment maturity. Utility-scale horizontal single-axis trackers using astronomical control, backtracking, supervisory monitoring, and weather-dependent stow provide the most mature balance of energy yield, cost, and operational robustness. Dual-axis systems can offer higher output under high-direct-normal-irradiance conditions but impose greater structural and O&M burdens, while passive fluid-based and shape-memory-alloy concepts remain mainly experimental. The review also examines bifacial and terrain-aware tracking, agrivoltaic dual land use, extreme-weather resilience, tracker-specific availability, artificial intelligence, digital twins, predictive maintenance, and end-of-life considerations. A plant-level decision framework and reporting checklist are proposed to support transparent, project-specific choices that maximize lifetime renewable-energy value while limiting material use, land-use conflict, operational risk, and avoidable life-cycle impacts. Full article

The European Union’s REPowerEU Plan (2022) targets 10 million tonnes of renewable hydrogen imports by 2030, catalyzing an unprecedented cascade of bilateral green hydrogen partnerships with countries across the Middle East and North Africa (MENA) and Sub-Saharan Africa (SSA). Despite the strategic and developmental significance of these partnerships, the literature has treated hydrogen largely as a techno-economic or single-country problem, leaving the diplomatic architecture and equity dimensions of EU–MENA–SSA hydrogen diplomacy under-theorized and unmeasured. This study addresses these gaps by integrating energy-security realism, regime-complex theory, and critical political ecology into a synthetic framework, and by introducing two novel empirical instruments: a hand-coded dataset of 26 in-scope bilateral hydrogen agreements (2020–2024) and a fully specified protocol for a Green Hydrogen Diplomacy Equity Index (GHD-EI). A longitudinal dyad-year panel skeleton (27 EU importers × 36 MENA/SSA exporters, 2015–2026, 11,664 dyad-year cells) has been constructed to host a planned multi-method quantitative sequence, structural gravity PPML, staggered difference-in-differences, synthetic control, exponential random graph models, and causal forests whose execution against fully populated covariates is reserved for a subsequent paper. This paper is accordingly framed as a data descriptor and specified analytical protocol, reporting descriptive and structural findings from the 26 in-scope agreements: a 2022 inflection synchronized with REPowerEU and COP27; importer-side concentration on Germany (34.6% of agreements) and EU-level framework partnerships (34.6%)—two distinct actors jointly accounting for 69.2%—and a small, statistically non-significant difference in mean partnership depth between MENA (n = 18, M = 3.22) and SSA (n = 8, M = 3.25) exporters (Welch t = −0.08, p = 0.94; Cohen’s d = −0.04). The comparison is likely under-powered (power ≈ 0.20–0.44) given the small SSA cell and reported here as a tentative pattern. At this stage, the study contributes a cross-regional agreement dataset, a fully specified equity-indicator protocol, and a theoretical framework for subsequently evaluating whether the green hydrogen transition advances just internationalism or reproduces green-extractivist patterns. Full article

The large-scale integration of photovoltaic generation into distribution grids has introduced significant operational challenges, including voltage excursions, reverse power flows, and increased variability. Battery energy storage systems (BESSs) offer a versatile solution by providing coordinated active- and reactive-power support. However, their scheduling in active distribution networks is challenging because of the non-convex alternating-current (AC) power-flow equations, the nondifferentiability of battery-degradation modeling, and uncertainty in renewable generation and demand. This paper proposes a two-stage methodology for the day-ahead operation of BESSs in ADNs. In the first stage, parallel particle swarm optimization (PPSO) determines the hourly active- and reactive-power schedules of the BESS units. In the second stage, a matrix-based multi-period AC power flow based on successive approximations evaluates the schedules and verifies voltage, thermal, converter-capability, and state-of-charge (SoC) constraints. A rainflow-counting degradation model is incorporated into the objective function to account for cycling and calendar aging costs. The methodology is assessed through ablation analyses comparing active-power-only and coordinated P–Q dispatches, degradation-unaware and degradation-aware scheduling, and serial and parallel PSO implementations. It is validated on modified 33-, 69-, and 136-node systems under deterministic and uncertainty-based operating conditions, including 100 demand and PV-generation scenarios. PPSO is compared with parallel versions of the adaptive Jaya algorithm (AJAYA), genetic algorithm (GA), multi-verse optimizer (MVO), salp swarm algorithm (SSA), grey wolf optimizer (GWO), and vortex search algorithm (VSA), using operating-cost reduction, computational time, solution variability, feasibility indicators, BESS lifetime, and weekly cost analysis. Additionally, exact one-sided Wilcoxon signed-rank tests with Holm adjustment are used to assess the statistical significance of the economic differences between PPSO and the benchmark methods. Results show that PPSO provides the lowest or most competitive operating costs and the shortest computational time in the evaluated cases, while all network and storage constraints remain satisfied. Full article

Recently, microgrid (MG) structures include a mix of renewable energy sources (RES) and conventional sources. At high levels of RES penetration, reduced inertia and frequency stability have been confirmed in several studies. Properly designed and structured load frequency control (LFC) and virtual inertia control (VIC) are feasible solutions to these problems. In this paper, a new hybridized two-degree-of-freedom (2DOF) non-integer controller is proposed for multi-generation, multi-area MGs’ frequency regulation. The proposed new LFC is based on a 2DOF tilt-integral/tilt-derivative-double-derivative controller with a filter (TI-TD²F²). Meanwhile, the proposed design process considers coordinating capacitive energy storage (CES) to help regulate frequency deviation, as well as the high penetration of RESs (wind and PV). The incorporation of CES participation in frequency regulation helps provide fast VIC for the studied multi-MG system. Furthermore, an Enhanced Escape Algorithm (EESC) optimization algorithm is proposed to simultaneously optimize the control parameter set of the two-area MG system. The proposed EESC optimization algorithm identifies appropriate parameters for controller design, yielding better overall dynamic performance. An enhanced Escape Algorithm (EESC) is based on boosting the searching mechanism of the conventional Escape Algorithm by the integration of three modifications, including the Chaos map logistic mutation mechanism, the Fitness distance balance mechanism, and the Sorted Quasi-oppositional based learning (SQOBL). The proposed 2DOF TI-TD²F² controller demonstrates improved frequency stability and sustainable operation under load changes, variation in RESs, and other uncertainties of system parameters. The obtained results showed that the proposed EESC optimization algorithm adjusts the parameters of the TI-TD²F² controller, which significantly improves the dynamic performance in load frequency and tie-line power control. Compared to traditional TID and FOPID controllers, TI-TD²F² achieves up to a 70–80% reduction in tie-line power deviation and up to 60% faster settling time in many scenarios, demonstrating better robustness, faster response, and better overall system stability. Full article

Sustainable energy management in grid-connected AC microgrids is investigated through a comparative assessment of centralized, distributed, and decentralized multi-agent-system-based load management control architectures integrating photovoltaic (PV) generation and battery energy storage system. A sustainability-oriented rule-based load scheduling strategy is implemented to efficiently utilize available renewable energy while maintaining grid power consumption within the prescribed demand limits and ensuring priority support for critical loads. Multi-agent-system (MAS)-based load agents coordinate centralized, distributed, and decentralized load management operations. The control architectures are evaluated under identical load profiles, PV generation patterns, and demand-limit constraints to ensure a fair comparison of sustainability-oriented energy management performance. Their resilience is further assessed under agent failures, communication losses, and delays. The comparative analysis employs sustainability-oriented performance metrics, including load served percentage, load curtailment percentage, demand-limit violation duration, and PV utilisation, to assess reliable energy delivery, demand-side efficiency, grid compliance, and effective renewable-energy utilisation. The results reveal distinct architectural trade-offs in sustainable energy management: decentralized control offers greater resilience to agent failures and achieves the highest average load-served percentage (64.83%) and lowest demand-limit violation duration (40.61 ms). Distributed control provides enhanced coordination and priority-based load management, with intermediate performance (64.10%, 41.17 ms), whereas centralized control is constrained by single-point failures and scalability, exhibiting the lowest performance (58.52%, 43.33 ms). PV utilisation remains approximately 99% across all architectures, indicating near-complete utilisation of available solar generation for load supply and battery charging with minimal curtailment. Full article

Railway idle land offers a large and underused space for solar power, yet its economic value has not been evaluated. Revenue depends on the volatile System Marginal Price (SMP) and Renewable Energy Certificate (REC) markets, whose uncertainty cannot be fully captured by static discounted cash flow (DCF) analysis. This study asks whether solar development on Korea’s railway idle land is worthwhile over the long term, and at what scale it should proceed. It applies an integrated DCF and real options analysis (ROA) framework to a proposed 438 MW project on the Honam Line in southern Korea. Price volatility is estimated from monthly SMP and REC data with a geometric Brownian motion model, and the options to expand and to contract are valued on a binomial lattice. The DCF yields a marginal net present value of USD 3.2 million. The expansion option adds USD 172.5 million and is exercised in 67% of states, raising the total project value to USD 175.7 million. Rising panel efficiency and falling capital costs move the project firmly into feasibility. Therefore, scale flexibility turns a marginal project into a strongly positive one, supporting the large-scale deployment of solar on railway idle land. Full article

The potato production process in Konya, Türkiye, was evaluated through a cumulative and system-oriented approach. A functional unit of one ton of potatoes produced was used for all analyses, using region-specific agricultural input data. In this study, the cumulative energy consumption (CEnC), exergy consumption (CExC), and CO₂ emissions (CCO₂E) of the agricultural production process were determined. Specifically, the sustainability performance of the potato production process was examined through thermodynamic indicators. The results indicate that nitrogen fertilizer accounts for the highest CEnC, reaching 368.94 MJ per ton of potato produced, followed by diesel fuel at 179.64 MJ/ton and electricity at 91.79 MJ/ton. However, the CExC assessment revealed a different pattern, with electricity emerging as the dominant source of exergy depletion. Electricity consumption accounted for 382.75 MJ/ton, representing the largest exergy burden among all inputs, while diesel (166.21 MJ/ton) and nitrogen (154.28 MJ/ton) followed as secondary contributors. A similar trend was observed in the carbon emission analysis. Electricity use resulted in the highest CCO₂E value at 12.85 kg CO₂/ton, whereas diesel contributed 2.94 kg CO₂/ton. Emissions from chemical fertilizers remained notably low, with nitrogen, phosphorus and potassium generating only 0.42, 0.22 and 0.75 kg CO₂/ton, respectively. The sustainability indicators further highlighted the system’s performance. The cumulative degree of perfection (CDP) was calculated as 7.34, while the renewability indicator (RI) reached 0.86, suggesting that potato production in Konya demonstrates relatively high thermodynamic efficiency and a strong potential for renewable energy integration. Under a scenario in which agrivoltaic systems (AVS) and fully electric agricultural machinery replace conventional energy inputs, the CDP increased markedly to 21.61 and the RI to 0.95. To the authors’ knowledge, this study is the first thermodynamic analysis of potato production in Türkiye that integrates sustainability indicators with an AVS integration scenario. The proposed framework provides a practical decision support approach for evaluating the integration of renewable energy into agricultural production systems. Full article

Urban and peri-urban regions increasingly face climate-related pressures, competing land-use demands, and the need to expand renewable-energy infrastructure while maintaining agricultural land and landscape functions. Agrivoltaics, which combines photovoltaic energy generation with agricultural production, represents a potentially multifunctional approach to land use; however, regional GIS assessments often stop at environmental suitability surfaces without translating those results into planning-relevant cadastral inventories. This study develops and applies a planning-oriented Geographic Information System (GIS) framework for preliminary statewide agrivoltaic screening in Connecticut. Annual global solar radiation and terrain slope were integrated through a weighted suitability model, while incompatible land-cover classes were treated as hard exclusions through a binary land-cover mask. The workflow subsequently excluded protected and open-space lands, associated suitable areas with cadastral parcels, normalized and dissolved parcel identifiers using ParcelKey, and a recalculated suitable area from the resulting unique parcel geometries and then applied a minimum requirement of 1 ha of cumulative suitable area per retained parcel. The final baseline inventory contained 3497 normalized unique cadastral parcels encompassing 16,366.49 ha of GIS-identified suitable area, with suitable land representing an average of 42.46% of total parcel area. Peri-urban contexts accounted for the largest share of the final suitable area, containing 2497 parcels and 73.16% of the total, compared with 476 urban and 524 rural parcels. Sensitivity analysis indicated strong stability under alternative weighting schemes, with spatial overlap exceeding 99% relative to the baseline. Reducing the suitability-score threshold from 3.0 to 2.5 produced only minor changes, whereas increasing it to 3.5 reduced the inventory to 3095 parcels and 13,712.89 ha. From a sustainability perspective, the framework provides a spatial decision-support approach for coordinating renewable-energy planning with agricultural land stewardship, conservation constraints, and more efficient use of already fragmented land resources. By making the effects of exclusions, parcel thresholds, and analytical assumptions explicit, the approach supports more transparent and reproducible evaluation of land-use trade-offs relevant to sustainable development. The resulting inventory is intended as a first-stage planning resource rather than a determination of project feasibility or site-level sustainability performance. Full article

Background/Objectives: Basic sciences form the conceptual foundation of dentistry, yet their delivery in dental curricula varies worldwide. As demographic shifts, growing healthcare complexity and scientific advances continue to reshape the dental profession, renewed attention to how these subjects are taught has become essential. This comparative narrative review aims to examine different approaches to basic science education in dentistry, exploring variation in curricular structure, depth, timing and pedagogical strategies across diverse dental schools. Particular emphasis is placed on models of vertical, horizontal and spiral integration, the alignment of basic sciences with clinical training and the implications of instructional design for long-term knowledge retention and professional competence. Methods: PubMed and Google Scholar were searched from November 2025 to June 2026 using terms related to dental education, curriculum integration and geographic regions. Sources were selected based on predefined relevance criteria rather than through systematic screening. Published literature was supplemented by structured outreach to faculty representatives using a standardised set of questions. Of the 25 dental schools contacted, nine responded, and five were included. Results: Across the programs examined, a structure of approximately two preclinical years followed by clinical training remained the most common. Early clinical exposure appeared to strengthen student confidence and professional identity. Heavy workload and curricular overload were recurring challenges in the dental curricula examined. Conclusions: The findings suggest that although curriculum integration is widely recognised as essential, no single model appears to be universally superior. Its effectiveness likely depends on the quality of implementation and faculty coordination. However, the lack of independent evaluation studies limits the ability to draw conclusions about the long-term effectiveness of different educational approaches. The review highlights the need for independent and systematic evaluation of dental curricula. Full article

This research presents a comprehensive diagnosis of Ecuador’s electricity generation (2003–2024), focusing on structural vulnerabilities, fuel dependence, and Greenhouse Gas (GHG) emissions from electricity generation. The technological composition of the grid, including installed and effective capacity, as well as the share of fossil and organic fuels, is analyzed to construct a coherent analytical framework. GHGs (i.e., CO₂, CH₄, and N₂O) are estimated from fuel consumption in Non-Conventional Renewable Energy (NCRE) and Non-Renewable Energy (NRE), in accordance with the 2006 IPCC Guidelines. Conversion to CO₂ equivalent utilizes the AR5 GWP factors, in agreement with AR6. The results present annual series for each gas and their corresponding CO₂ equivalents, showing that NREs dominate the CO₂ profile, while NCREs contribute significantly to CH₄ and N₂O. Despite the expansion of installed capacity, a gap persists with effective capacity, reflecting the structural vulnerabilities of Ecuador’s electricity generation system, including exposure to hydrological variability (Kraftnōt, referring in this research to electricity shortages caused by reduced hydropower generation under adverse hydrological conditions), insufficient thermal backup, a high concentration of hydropower plants, fluctuating fossil fuel subsidies, and limited diversification. This manuscript provides a technical and quantitative basis using annual CO₂, CH₄, and N₂O values and their CO₂ equivalents to inform future decarbonization scenarios that strengthen NCRE integration within international climate commitments and a sustainable electricity transition. Full article