Search Results (90)

We present a transdisciplinary Teaching–Learning Sequence (TLS) for lower secondary school students that integrates climate change education with the promotion of gender equality in science. The TLS connects theoretical understanding with practical engagement through laboratory demonstrations, simulations, and accessible experiments. The sequence addresses key topics in sustainability education, including incoming and outgoing radiation, the greenhouse effect, energy transformations, and energy sources, through activities involving the electromagnetic spectrum, infrared imaging, selective transparency, absorption, and albedo. It also includes inquiry-based explorations of electromagnetic induction, miniature hydroelectric and wind power systems, Stirling engines, photovoltaic and concentrated solar technologies, and combustion-related CO₂ acidification. A distinctive feature of the TLS is the explicit integration of the social dimension of sustainability through discussion of the Matilda Effect and the historical case of Eunice Newton Foote, with the aim of challenging persistent gender stereotypes in STEM. The intervention was implemented with 12–13-year-old students and evaluated through pre- and post-tests, written explanations, closed-ended questions, drawings, and the Draw-A-Scientist Test. The results indicate a significant improvement in students’ understanding of climate-related scientific concepts and in their critical awareness of misinformation and climate denial strategies. While the sequence did not significantly increase students’ engagement in climate action, the gender-focused activities promoted strong critical reflection on stereotypes and on the role of women in science. Full article

Renewable energy curtailment has emerged as a growing challenge on the Korean mainland grid as photovoltaic (PV) and wind power capacity continues to expand toward national carbon neutrality targets. Plus demand response (Plus DR), in which electricity consumers increase consumption during curtailment periods, has been introduced as a demand-side mitigation measure. Buildings represent a potential resource for Plus DR participation. However, existing studies have primarily focused on load-reduction DR, and Plus DR availability by building use type under curtailment conditions has not been systematically quantified. This study estimates Plus DR availability of building loads by use type—department store, hotel, general commercial, public facility, apartment, and school—based on representative building load profiles, PV generation data, and 2025 curtailment occurrence data from the Korean mainland grid. Curtailment events were concentrated in the 10:00–16:00 window with peak frequency at 12:00 (80 events). The combined Plus DR availability across the six use types averaged 290.3 kW during curtailment hours, peaking at 300.9 kW at 14:00. The estimated Plus DR availability operated primarily through the load-increase pathway (additional grid consumption) rather than the surplus absorption pathway (reduced PV export). Surplus generation was observed only in the school at 13:00 (0.77 kW). These results provide a quantitative basis for identifying suitable building types and curtailment-responsive time windows for building-based Plus DR program design on the Korean mainland, and may serve as a reference for mainland DR market development. Full article

Integrating renewable energy into modern grids while reducing carbon emissions represents a critical challenge for achieving “dual carbon” objectives. This paper proposes a two-stage stochastic optimization scheduling model for integrated energy systems (IES) that accounts for dynamic carbon emission factors and spatiotemporal uncertainty in wind power. First, a dynamic carbon emission factor model is developed to reflect real-time grid operational status and marginal power generation characteristics, replacing the conventional fixed-factor approach and enabling precise guidance for low-carbon electricity procurement strategies. Second, a Copula-based joint probability distribution model is established to capture complex temporal and spatial correlations in multi-wind-farm clusters, from which representative scenarios are generated and reduced through advanced pruning techniques. The scheduling model minimizes total operating costs and tiered carbon trading costs via mixed-integer quadratic programming (MIQP) and Benders decomposition. Case studies demonstrate that the proposed approach reduces daily operating costs by 6.4% (from 2.069 to 1.936 million yuan) and total carbon emissions by 8.4% (from 1051.8 to 963.2 tonnes) compared to conventional static-factor methods. Further, by accurately characterizing wind power uncertainty, the model achieves wind power absorption rates exceeding 90%, reducing curtailment from 272 kWh to 75 kWh and improving renewable energy utilization from 57.5% to 92%. The results validate that dynamic carbon factors and spatiotemporal correlation modelling effectively enhance both low-carbon performance and economic efficiency in IES dispatch, offering theoretical and practical guidance for achieving carbon-neutral energy system operations. Full article

To address fault-period DC-link overvoltage, the reduction in grid-side active-power regulation margin caused by reactive-current-priority operation, and the double-frequency current fluctuation induced by negative-sequence components under asymmetrical grid faults in a flywheel-assisted permanent-magnet direct-drive wind power system, this paper proposes a coordinated low-voltage ride-through (LVRT) strategy based on DC-link-voltage-threshold partitioning. According to the DC-link voltage level, the operating process is divided into a normal regulation region, a grid-side saturation region, and a flywheel activation region, thereby enabling coordinated regulation between grid-side reactive-current support and flywheel-side active-power absorption. To improve transient smoothness, an anti-windup mechanism together with a bumpless transfer scheme is incorporated into the coordinated control process to suppress integrator saturation and mitigate mode-transition disturbances. In addition, a grid-side proportional–integral–vector resonant controller (PI-VRC) is introduced to improve the suppression of double-frequency current fluctuation under asymmetrical faults and enhance converter capacity utilization. Simulation results show that the proposed strategy can effectively restrain fault-period DC-link voltage rise, improve three-phase current symmetry and grid power quality, and strengthen transient reactive-power support, thereby enhancing the asymmetrical-fault LVRT capability of the system. Full article

Offshore wind and wave energy have emerged as promising alternatives due to their abundant availability and substantial energy potential. This research explores a V-shaped semi-submersible platform designed to support both wind turbines and wave energy converters (WECs). The V-shaped configuration is selected for its ability to enhance hydrodynamic performance by reducing wave-induced loads and improving motion characteristics, while also providing increased structural stability through a wider effective footprint. In addition, the geometry creates a favourable layout for integrating WECs between the pontoons, enabling efficient wave energy capture without significantly interfering with the aerodynamic performance of the wind turbine. The study assesses the performance of different V-shaped platform configurations, ensuring their motion responses meet the operational limits required for wind turbines. It also examines whether interactions between the platform and coexisting WECs can lead to an improvement in wave energy absorption efficiency. Numerical hydrodynamic diffraction was conducted using the boundary element method in ANSYS AQWA, based on 3D potential flow theory and considering viscous damping effects, to calculate platform motion and the wave power output of WECs with a linear power take-off system. Preliminary analyses revealed that optimising the placement of WECs on a V-shaped semi-submersible can significantly improve energy generation while maintaining acceptable platform motion. This research demonstrates the additional potential of integrated wind-wave energy systems in delivering efficient and sustainable offshore energy solutions. The study also highlights the advantages of a turret mooring system for passive alignment with environmental forces, prolonging platform structure longevity and enhancing energy efficiency. Full article

An approximate analytical model for the variation of A-weighted broadband sound levels with distance over flat acoustically soft ground from a source of known sound power depends on the reduction in low frequency content in noise spectra due to A-weighting. Also, it assumes a weak linear sound speed gradient and a frequency independent attenuation coefficient for air absorption. The model introduces adjustable frequency independent parameters for ground effect, turbulence and atmospheric refraction. An additional parameter allows for the source being located over acoustically hard ground. Predictions of the model are compared with measurements over several ground surfaces. The approximate model predicts a more rapid reduction in sound attenuation due to ground effect with increasing mean propagation path height than the simplified method in a widely used international standard. Moreover, predictions of A-weighted sound levels from onshore wind turbines using the approximate analytical method compare with data and numerical simulations better than the simplified and octave band methods in the international standard and the Swedish standard method. Full article

Industrial activities represent the primary source of anthropogenic carbon dioxide (CO₂) emissions, and accurate monitoring of industrial CO₂ emissions is critical to mitigating greenhouse gas emissions. Due to the lack of quantifiable and direct measurement technologies, industrial CO₂ emissions are typically calculated based on fuel combustion consumption and emission factors. However, the calculation method is not applicable to the quantification of fugitive emissions of CO₂. This work demonstrates the capability of remotely measuring industrial CO₂ emissions by mobile Differential Absorption Lidar (DIAL) system. The two-dimensional concentration distributions of the CO₂ plume were remotely measured using DIAL system, and the CO₂ emission rate was obtained with wind field information. The DIAL measurements were cross-validated using in-stack CEMS data and emission-factor calculations. Results show that the relative deviations of CO₂ emission rates between DIAL and CEMS range from −5.83% to +2.57% across four tests, all within ±6%, and the coefficient of variation (CV) of 27 valid datasets is 7.24%. In contrast, the emission factor method yields consistently higher estimates, with relative deviations of +4.61% compared to DIAL measurements. Furthermore, the mobile DIAL system was deployed in three industrial scenarios with different emission intensities: a natural gas-fired industrial park, a photovoltaic glass manufacturing plant (low-emission steady-state), and a coal-fired power plant (high-emission dynamic), demonstrating its preliminary adaptability under different operating conditions. This study indicates the feasibility and potential reliability of the mobile DIAL system for high spatio-temporal resolution remote measurement of industrial CO₂ emissions. Full article

Micro-scale counter-rotating wind turbines (CRWTs) offer enhanced potential for wake energy recovery. This study proposes an integrated cascade–coupling design framework for high-solidity CRWTs, in which rear rotor geometry and rotor coupling are co-designed based on stereoscopic particle image velocimetry measurements of the front rotor wake. Experiments are conducted at a tip-speed ratio of $\lambda =1.0$, solidity $\sigma =1.25$, spacing ratios of $d=0.6R_T$, $1.0R_T$, and $3.0R_T$, and a tip radius of $R_T=70$ mm. At the physical limit spacing of $d=0.6R_T$, the integrated design increases the system power coefficient by 24.1% while limiting front rotor power reduction to 17.2%, compared to a 10.3% system gain and 34.5% front rotor suppression for the baseline mirrored configuration. Wake measurements confirm near-complete absorption of rotational kinetic energy from the front rotor wake without exacerbating upstream interference. These results demonstrate that cascade-based energy extraction and coupling-based interference mitigation can operate synergistically, enabling compact, high-performance micro-scale CRWTs suitable for space-constrained and urban energy applications. Full article

With the advancement of the dual carbon goals and the rapid increase in the proportion of new energy installations, the power system faces multiple challenges including insufficient flexibility resources, intensified fluctuations in generation and load, and reduced operational safety. Integrated energy systems (IESs), serving as key platforms for integrating diverse energy sources and flexible resources, possess complex internal structures and limited individual regulation capabilities, making direct participation in grid dispatch and market interactions challenging. To achieve large-scale resource coordination and efficient utilization, this paper investigates external characteristic modeling and cluster aggregation optimization methods for IES, proposing a comprehensive technical framework spanning from individual external characteristic identification to cluster-level coordinated control. First, addressing the challenge of unified dispatch for heterogeneous resources within IES, this study proposes an external characteristic modeling method based on operational feasible region projection. It constructs models for the active power output boundary, marginal cost characteristics, and ramping rate of virtual power plants (VPPs), enabling quantitative representation of their overall regulation potential. Second, a cluster aggregation optimization model for integrated energy systems is established, incorporating regional autonomy. This model pursues multiple objectives: cost–benefit matching, maximizing renewable energy absorption rates, and minimizing peak external power purchases. The Gini coefficient and Shapley value method are introduced to ensure fairness and participation willingness among cluster members. Furthermore, an optimization mechanism incorporating key constraints such as cluster scale, grid interaction, and regulation complementarity is designed. The NSGA-II multi-objective genetic algorithm is employed to efficiently solve this high-dimensional nonlinear problem. Finally, simulation validation is conducted on a typical regional energy scenario based on the IEEE-57 node system. Results demonstrate that the proposed method achieves average daily cost savings of approximately 3955 CNY under the optimal aggregation scheme, reduces wind and solar curtailment rates to 5.38%, controls peak external power purchases within 2292 kW, and effectively incentivizes all entities to participate in coordinated regulation through a rational benefit distribution mechanism. Full article

The current study examines the innovative use of rubber–concrete composites as structural solutions that provide significantly higher noise absorption properties compared to traditional concrete. Focusing on their potential for sound insulation in challenging environments such as wind energy infrastructure, the study examines the effect of varying contents of ground tyre rubber (GTR) content (20%, 40%, and 60% by volume) and acetone treatment duration (0, 1, 6, and 24 h) on the characteristics of the composite. The results demonstrate that these rubber–concrete composites significantly improve both sound absorption and sound insulation. An increase in sound absorption coefficients to approximately 0.18 was observed, representing an average improvement of 43.4% compared to the average coefficient of the reference mixture, 0.043. This improvement is particularly effective in the 100–1250 Hz frequency range and maintains stable properties from 50 to 1600 Hz. Sound transmission losses also showed a clear improvement in the mid-frequency ranges. Despite their excellent acoustic characteristics, these structural composites demonstrate a compromise in mechanical properties. Compressive strength decreased from approximately 43–46 MPa (control) to 25–38 MPa at 60% rubber content after 28 days, representing a 40–46% reduction. The reduction in flexural strength was even more pronounced, decreasing by approximately 60% at a rubber content of 35%. However, treatment of GTR with acetone significantly improved interfacial bonding, increasing mechanical integrity at moderate rubber doses (20–40%). The optimal range of rubber content, providing a balance between acoustic benefits and structural integrity, appears to be 15–25%. Full article

This article investigates a wind–solar–biogas complementary integrated energy system (IES) for achieving combined cooling, heating, and power (CCHP) supply in agricultural parks. The system consists of wind power, photovoltaic power, biogas-based combined heat and power (CHP), waste heat boilers, electric heating/cooling units, absorption chillers, and energy storage devices. Using Changma Village, Baiwu Town, Yanyuan County, Sichuan Province as a case study, a multi-objective optimization model was established with the objectives of minimizing operating costs and carbon emissions. An improved multi-objective grey wolf optimizer (MOGWO) was applied to solve the model. The results show that the proposed method yielded a well-distributed Pareto front. In the optimal compromise solution, the total operating cost decreased from CNY 6461.77 to CNY 2070.51, a reduction of 67.96%, and the carbon emissions decreased from 13,740.72 kg to 2370.45 kg, a reduction of 82.75%. The proposed wind–solar–biogas complementary IES can enhance both the overall economic performance and low-carbon sustainability of the agricultural park energy systems. Full article

The randomness and volatility of wind power increase peak regulation pressure, leading to wind curtailment despite the deep peak regulation efforts of thermal power units. By integrating conventional power source dispatch and high-energy-consuming load configuration, a two-layer optimization model is developed to maximize wind curtailment absorption and minimize thermal power deep peak regulation costs. The model first analyzes the fused magnesium load’s operating characteristics and its dispatch-participation model, then combines with the thermal power deep peak regulation model for hierarchical joint peak regulation. Applying the method to an actual regional system via CPLEX shows that it reduces wind curtailment, optimizes thermal power deep peak regulation, and improves power generation economic efficiency. Full article

With the rapid integration of high-penetration renewable energy, its inherent uncertainty complicates power system day-ahead/intra-day scheduling, leading to challenges like wind curtailment and high operational costs. Existing methods either rely on inflexible physical models or use deep reinforcement learning (DRL) without prioritizing critical variables or synergizing multi-source energy storage and demand response (DR). This study develops a multi-time scale coordination scheduling framework to balance cost minimization and renewable energy utilization, with strong adaptability to real-time uncertainties. The framework integrates a day-ahead optimization model and an intra-day rolling model powered by an attention-enhanced DRL Actor–Critic network—where the attention mechanism dynamically focuses on critical variables to correct real-time deviations. Validated on an East China regional grid, the framework significantly enhances renewable energy absorption and system flexibility, providing a robust technical solution for the economical and stable operation of high-renewable power systems. Full article

Traditional pumped storage capacity configuration uses static, year-targeted approaches, leading under-capacity in the early planning stages—wasting renewable energy—and over-capacity in later stages, thus wasting resources. In order to solve the above problems, this article innovatively proposes a dynamic, time-sequenced construction timeline and annual capacity configuration strategy, synchronized with new energy and load development, enhancing sustainability through optimized investment allocation and efficient resource utilization. It presents a two-layer model that considers multiple scenario operational dispatch. The upper layer aims to minimize the curtailment of wind and solar energy, providing a planning scheme to the lower layer, which focuses on multi-scenario economic dispatch, taking into account the peak-valley difference indicators. The models co-iterate: lower-layer operational outcomes feed back to refine the upper-layer’s capacity plan. This process continues until the predicted curtailment calculated by the upper layer aligns closely with that observed in the lower-layer operational simulations, or until capacity changes stabilize, ultimately determining the optimal time-phased capacity configuration. Simulations on a provincial power grid during three typical scenarios in winter, transitional seasons, and summer, as well as extreme weather scenarios, confirm that timely, dynamic configuration strategy significantly enhances renewable absorption, proving the model’s effectiveness. Full article

With the widespread integration of renewable energy sources such as wind and solar power into power systems, their inherent unpredictability and fluctuations present significant challenges to grid stability and security. To address these issues, Battery Energy Storage Systems (BESSs) offer an effective means of enhancing renewable energy absorption and improving the overall system efficiency. This study proposes a coordinated planning method based on the improved bat algorithm (IBA) to tackle the challenges associated with integrating renewable energy into distribution networks. A bi-level optimization framework is introduced to coordinate the planning and operation of the distributed generation (DG) and BESS. The upper-level model focuses on selecting optimal sites and determining the capacity of wind turbines, photovoltaic arrays, and storage systems from an economic perspective. The lower-level model optimizes the curtailment of wind and solar energy and minimizes network losses based on the upper-level planning outcomes. Additionally, the lower-level model also coordinates the dispatch between renewable energy generation and storage systems to ensure the reliable operation of the system. To effectively solve this bi-level optimization model, we have improved the conventional bat algorithm. Simulation results show that the improved bat algorithm not only significantly enhances the convergence speed but also improves the voltage stability, with the photovoltaic utilization rate reaching 90.27% and the wind energy utilization rate reaching 92.18%. These results highlight the practical advantages and success of the proposed method in optimizing renewable energy configurations. Full article