Search Results (409)

This study investigates the asymmetric trade-off between cost and reliability in the optimal sizing of stand-alone Hybrid Renewable Energy Systems (HRESs) composed of photovoltaic panels (PV), wind turbines (WT), battery storage, a diesel generator (DG), and an inverter. The optimization is formulated as a multi-objective problem with Cost of Energy (CoE) and Loss of Power Supply Probability (LPSP) as conflicting objectives, highlighting that those small gains in reliability often require disproportionately higher costs. To ensure practical feasibility, the installation roof area limits both the number of PV panels, wind turbines, and batteries. Two metaheuristic algorithms—NSGA-II and MOPSO—are implemented in a Python-based framework with an Energy Management Strategy (EMS) to simulate operation under real-world load and resource profiles. Results show that MOPSO achieves the lowest CoE (0.159 USD/kWh) with moderate reliability (LPSP = 0.06), while NSGA-II attains a near-perfect reliability (LPSP = 0.0008) at a slightly higher cost (0.179 USD/kWh). Hypervolume (HV) analysis reveals that NSGA-II offers a more diverse Pareto front (HV = 0.04350 vs. 0.04336), demonstrating that explicitly accounting for asymmetric sensitivity between cost and reliability enhances the HRES design and that advanced optimization methods—particularly NSGA-II—can improve decision-making by revealing a wider range of viable trade-offs in complex energy systems. Full article

Exploring the effects and mechanisms of spatial agglomeration of construction land resources on economic resilience across Chinese provinces will provide theoretical support for governments to optimize the allocation of productive forces and enhance economic resilience through rational distribution of construction land quotas. Based on the “Structure-Conduct-Performance (SCP)” analytical framework, this paper identifies spatial agglomeration through the share of the largest city and draws on the microeconomic concept of “elasticity” that reflects the relationships between variables to construct economic resilience with spatial relationship attributes. On this basis, it utilizes China’s provincial panel data gathered since 2000 and employs fixed-effects models, mediation models, moderation models, quantile regression, and subsample regression to examine the impact mechanisms of the spatial agglomeration of construction land on economic resilience. The research finds the following: the spatial agglomeration of construction land has a positive empowering effect on economic resilience; innovation and technical efficiency are important transmission paths for the spatial agglomeration of construction land to empower economic resilience; and further research shows that the empowering effect has an inverted U-shaped process, with the promoting effect being predominant. The empowering effect increases with rising quantiles and exhibits regional heterogeneity, showing an ascending gradient from eastern to western regions. The basic law in the western region is consistent with that of the whole country, and the scale of provincial construction land will strengthen the empowering effect. The research findings can provide decision-making references for the implementation and deepening of the main functional area strategy, as well as for strengthening the concentrated allocation of construction land quotas to advantageous regions. Full article

This study introduces YOLOv13-Cone-Lite, an enhanced algorithm based on YOLOv13s, designed to meet the stringent accuracy and real-time performance demands for traffic cone detection in autonomous formula racing cars on enclosed tracks. We improved detection accuracy by refining the network architecture. Specifically, the DS-C3k2_UIB module, an advanced iteration of the Universal Inverted Bottleneck (UIB), was integrated into the backbone to boost small object feature extraction. Additionally, the Non-Maximum Suppression (NMS)-free ConeDetect head was engineered to eliminate post-processing delays. To accommodate resource-limited onboard terminals, we minimized superfluous parameters through structural reparameterization pruning and performed 8-bit integer (INT8) quantization using the TensorRT toolkit, resulting in a lightweight model. Experimental findings show that YOLOv13-Cone-Lite achieves a mAP₅₀ of 92.9% (a 4.5% enhancement over the original YOLOv13s), a frame rate of 68 Hz (double the original model’s speed), and a parameter size of 8.7 MB (a 52.5% reduction). The proposed algorithm effectively addresses challenges like intricate lighting and long-range detection of small objects and offers the automotive industry a framework to develop more efficient onboard perception systems, while informing object detection in other closed autonomous environments like factory campuses. Notably, the model is optimized for enclosed tracks, with open traffic generalization needing further validation. Full article

Panel data from 30 provinces in China spanning the years from 2007 to 2022 were selected. Regional virtual water flows were calculated based on the principle of social equity, and agricultural production efficiency was measured using the Super-SBM model, which overcomes the issue of being unable to measure efficiency values when they exceed 1 for decision-making units. Based on the aforementioned estimation results, methods such as ArcGis and kernel density estimation were employed to illustrate the changing trends of virtual water flows and agricultural production efficiency in key years. Additionally, a fixed-effects model was used to explore the relationship between the two. The following conclusions are drawn: (1) The overall pattern of virtual water trade in grain exhibits a “north-to-south grain transportation” flow, with the volume of transfers increasing annually, which is contrary to the spatial distribution of water resources. Regions with a net outflow of virtual water in grain are mostly concentrated in major grain-producing areas such as the northeast, while provinces with a net inflow are mainly concentrated in economically developed regions such as South China, Southeast China, and the middle and lower reaches of the Yangtze River. (2) The average agricultural production efficiency shows a fluctuating upward trend, with an overall “S”-shaped pattern in a horizontal view, and the overall differences in production efficiency among provinces have widened. (3) Agricultural production efficiency exhibits an inverted “U”-shaped trend with the increase in virtual water flows, a conclusion that remains valid after a series of robustness tests. Therefore, corresponding suggestions are proposed based on the above conclusions, including formulating a scientific virtual water trade strategy and improving agricultural production efficiency. Full article

Land use efficiency (LUE) serves as a crucial nexus between economic development and sustainable resource management, directly influencing urban production–consumption systems. While economic development stages (EDSs) reflect a region’s environmental carrying capacity and profoundly affect LUE, the specific mechanisms governing this relationship remain unclear. In this study, we combined multi-source data to portray the spatiotemporal patterns of EDSs and LUE in 276 Chinese cities from 1995 to 2020, and we identified the nonlinear effects of EDSs on LUE. Based on the fine-scale LUE, it is confirmed that the older the age of urban land generation, the higher the LUE, laying a theoretical foundation for subsequent research. Simultaneously, the EDS continues to be upgraded, with approximately 70% of cities reaching the post-industrialization stage or higher by 2020. The results of partial dependency plots (PDPs) revealed that the EDS has a positive impact on LUE. From the perspective of different urban scales, the higher the EDSs of supercities, type I large cities, type II large cities, and type II small cities, the greater the positive impact on LUE, whereas the impact patterns at other urban scales follow an inverted U-shape. These findings carry important implications for sustainable spatial development, particularly in optimizing land resource allocation to assist the shift to more efficient production systems and responsible consumption patterns. Full article

Harmonic distortion from non-linear loads poses a significant challenge to power quality in residential nanogrids, often requiring complex control strategies and communication between distributed resources. This paper presents a parallel hybrid inverter system for an AC nanogrid that enhances power quality using only decentralized droop-based primary control, without the need for secondary control or communication links. The system features two inverters with strategic placement: one maintains voltage stability at the point of common coupling, while the other directly supplies the harmonic and reactive current demanded by non-linear loads. A compensation mechanism allows the second inverter to dynamically switch from supplying sinusoidal current to injecting targeted harmonic components, effectively isolating distortion from the main grid. Simulation results confirm that this approach significantly reduces voltage distortion at the PCC and ensures balanced power sharing, all while simplifying the control architecture. The proposed method offers a scalable, cost-effective solution for residential nanogrids seeking to integrate diverse loads and distributed energy resources while maintaining high power quality. Full article

China’s healthcare expenditure tripled during 2010–2019, prompting the nationwide implementation of centralized volume-based procurement (CVBP). While effective in reducing drug prices, CVBP introduces sustainability challenges including supply chain vulnerabilities and welfare trade-offs. This study develops a pharmaceutical sector-embedded computable general equilibrium (CGE) model to quantify CVBP’s multidimensional sustainability impacts. Using China’s 2020 Social Accounting Matrix (SAM) with simulated 10–50% price reductions, key findings reveal that (1) >40% price reductions trigger sectoral output reversal; (2) GDP exhibits an inverted U-shape; (3) household income declines despite corporate/government gains; and (4) industrial contraction impairs innovation capacity and employment stability. Our analysis identifies potential sustainability risks, emphasizing the need for rigorous empirical validation prior to implementing aggressive price reduction policies, and underscores the importance of integrating supply chain considerations into procurement policy design. This approach maximizes resource allocation efficiency while advancing socioeconomic resilience in healthcare systems. Full article

Although digitalization offers new pathways for carbon reduction, its underlying mechanisms have not been fully explored. Unlike previous studies, this research investigates the impact of digitalization on corporate carbon performance through both technological and structural effects while also revealing the boundary conditions under which digitalization contributes to carbon reduction in the context of corporate financing constraints. We conducted an empirical analysis using a fixed-effects model and a partially linear functional-coefficient model based on data from A-share listed companyies in China from 2008 to 2023. The results show that digitalization is significantly and positively associated with corporate carbon performance, confirming its potential for emission reduction. Mechanism tests indicated that digitalization improves corporate carbon performance by enhancing technological absorptive capacity, promoting factor substitution, and optimizing resource allocation. Further analysis revealed that, under financing constraints, the marginal effect of digitalization on corporate carbon performance follows an “inverted U-shaped” curve. Our study enriches the literature on the digital economy and carbon emissions and provides both theoretical and practical insights for promoting the coordinated transformation of enterprises toward digitalization and low-carbon development. Full article

The coordinated development of tourism and industrialization is essential for achieving sustainable and inclusive growth in the tourism sector, as well as for ensuring long-term regional economic sustainability. This study is motivated by the observation that land is a key factor influencing the coordination between tourism and industrialization, yet the specific role of land use remains underexplored. Therefore, the objective of this paper is to investigate the nonlinear relationship and underlying mechanisms through which tourism development impacts industrialization, with a particular focus on land transfers. To achieve this, the study employs an empirical approach using multi-source data—including data on China’s A-level scenic areas and land transfers—combined with an econometric method. The results indicate a U-shaped relationship between both the quantity and quality of tourism resources and the growth of industrial enterprises, as well as an inverted U-shaped relationship between the concentration of tourism resources and industrial development. The research finds that tourism development influences industrialization through two primary land-related mechanisms: the factor competition effect and the resource conservation effect. This study also investigates the potential for synergistic development between the tourism and industrial sectors, providing valuable insights for the sustainable economic advancement of land-based tourism and industrialization. Full article

Grid-forming (GFM) inverters have recently seen wider adoption in microgrids and inverter-based-resource (IBR)-penetrated grids, and are primarily used to establish grid voltage under a wide array of conditions. In the existing literature, GFM control is almost exclusively applied using voltage-source inverters (VSIs). However, due to the inherent limitations of available semiconductor devices’ current ratings, inverter-side current must be limited in VSIs, particularly during grid-fault conditions. These limitations complicate the real-world application of GFM functionality in VSIs, and complex control methodologies and tuning parameters are required as a result. In the following study, GFM control is instead applied to a buck-type current-source inverter (CSI) using a combination of linear droop-control and finite-control-set (FCS) mode-predictive control (MPC) that will be referred to herein as hybrid model-predictive control (HMPC). The resulting inverter features a simple topology, inherent current limiting capabilities, and a relatively simple and intuitive control structure. Verification was performed on a 1MVA/630V system via MATLAB/Simulink, and the simulation results demonstrate strong performance in voltage establishment, power regulation, and low-voltage ride through under-grid-fault conditions, highlighting its potential as a competent alternative to VSIs in GFM applications, and lacking the inherent limitations and/or complexity of existing GFM control methodologies. Full article

Power distribution systems are witnessing a growing deployment of distributed, inverter-based renewable resources such as solar generation. This poses certain challenges such as rapid voltage fluctuations due to the intermittent nature of renewables. Volt-Var control (VVC) methods have been proposed to utilize the ability of inverters to supply or consume reactive power to mitigate fast voltage fluctuations. These methods usually require a detailed power network model including topology and impedance data. However, network models may be difficult to obtain. Thus, it is desirable to develop a model-free method that obviates the need for the network model. This paper proposes a novel model-free cooperative control method to perform voltage regulation and reduce inverter aging in power distribution systems. This method assumes the existence of time-series voltage and load data, from which the relationship between voltage and nodal power injection is derived using a feedforward artificial neural network (ANN). The node voltage sensitivity versus reactive power injection can then be calculated, based on which a cooperative control approach is proposed for mitigating voltage fluctuation. The results obtained for a modified IEEE 13-bus system using the proposed method have shown its effectiveness in mitigating fast voltage variation due to PV intermittency. Moreover, a comparative analysis between model-free and model-based methods is provided to demonstrate the feasibility of the proposed method. Full article

Cross-validation and open research on future electric grids, particularly in their stability modeling and dynamic performance, can greatly benefit from high-fidelity, publicly available test cases, since access to dynamic response models of actual grid models is often limited due to legitimate security concerns. This paper presents a methodology for designing and validating the dynamic performance of large, IBR-heavy synthetic grids, that is, realistic but fictitious test cases. The methodology offers a comprehensive framework for creating dynamic models for both synchronous generators (SGs) and inverter-based resources (IBRs), focusing on realism, controllability, and flexibility. For realistic dynamic performance, the parameters in each dynamic model are sampled based on statistical data from benchmark actual grids, considering power system dynamics such as frequency and voltage control, as well as oscillation response. The paper introduces system-wide governor design, which improves the controllability of parameters in dynamic models, resulting in a more realistic frequency response. As an example, multiple case studies on a 2000-bus Texas synthetic grid are shown; these represent realistic dynamic performance under different transmission conditions in terms of frequency, voltage control, and oscillation response. Full article

The transition towards a power system characterized by a reduced presence of synchronous generators (SGs) and an increased reliance on inverter-based resources (IBRs), including wind, solar photovoltaics (PV), and battery storage, presents new operational challenges, particularly when these sources exceed 50–60% of the system’s demand. While current grid-following (GFL) IBRs, which are equipped with fast and rigid control systems, continue to dominate the inverter landscape, there has been a notable surge in research focused on grid-forming (GFM) inverters in recent years. This study conducts a comparative analysis of the practicality and control methodologies of GFM inverters relative to traditional GFL inverters from a system planning perspective. A comprehensive framework aimed at assisting system developers and consulting engineers in the grid-integration of wide-scale renewable energy sources (RESs), incorporating strategies for the deployment of inverters, capacitor banks, and harmonic filters, is proposed in this paper. The discussion includes an examination of the reactive power capabilities of the plant’s inverters and the provision of additional reactive power to ensure compliance with grid interconnection standards. Furthermore, the paper outlines a practical approach to assess the necessity for enhanced filtering measures to mitigate potential resonant conditions and achieve harmonic compliance at the installation site. The objective of this work is to offer useful guidelines and insights for the effective addition of RES into contemporary power systems. Full article

To address the modeling complexity and multi-objective collaborative optimization challenges in multi-depot and multiple unmanned aerial vehicle (UAV) delivery task planning, this paper proposes a bi-layer planning framework, which comprehensively considers resource constraints, multi-depot coordination, and the coupling characteristics of path execution. The novelty of this work lies in the seamless integration of an enhanced genetic algorithm and tailored swarm optimization within a unified two-tier architecture. The upper layer tackles the task assignment problem by formulating a multi-objective optimization model aimed at minimizing economic costs, delivery delays, and the number of UAVs deployed. The Enhanced Non-Dominated Sorting Genetic Algorithm II (ENSGA-II) is developed, incorporating heuristic initialization, goal-oriented search operators, an adaptive mutation mechanism, and a staged evolution control strategy to improve solution feasibility and distribution quality. The main contributions are threefold: (1) a novel ENSGA-II design for efficient and well-distributed task allocation; (2) an improved PSO-based path planner with chaotic initialization and adaptive parameters; and (3) comprehensive validation demonstrating substantial gains over baseline methods. The lower layer addresses the path planning problem by establishing a multi-objective model that considers path length, flight risk, and altitude variation. An improved particle swarm optimization (PSO) algorithm is proposed by integrating chaotic initialization, linearly adjusted acceleration coefficients and maximum velocity, a stochastic disturbance-based position update mechanism, and an adaptively tuned inertia weight to enhance algorithmic performance and path generation quality. Simulation results under typical task scenarios demonstrate that the proposed model achieves an average reduction of 47.8% in economic costs and 71.4% in UAV deployment quantity while significantly reducing delivery window violations. The framework exhibits excellent capability in multi-objective collaborative optimization. The ENSGA-II algorithm outperforms baseline algorithms significantly across performance metrics, achieving a hypervolume (HV) value of 1.0771 (improving by 72.35% to 109.82%) and an average inverted generational distance (IGD) of 0.0295, markedly better than those of comparison algorithms (ranging from 0.0893 to 0.2714). The algorithm also demonstrates overwhelming superiority in the C-metric, indicating outstanding global optimization capability in terms of distribution, convergence, and the diversity of the solution set. Moreover, the proposed framework and algorithm are both effective and feasible, offering a novel approach to low-altitude urban logistics delivery problems. Full article

Looking toward the future, governments around the world have started to change their energy mix due to climate change. The new energy mix will consist mainly of Inverter-Based Resources (IBRs), such as wind and solar power. This transition from a synchronous to a non-synchronous grid introduces new challenges in stability, resilience, and synchronization, necessitating advanced control strategies. Among these, Grid-Forming (GFM) control techniques have emerged as an effective solution for ensuring stable operations in microgrids and large-scale power systems with high IBRs integration. This paper presents a systematic review of GFM control techniques, focusing on their principles and applications. Using the PRISMA 2020 methodology, 75 studies published between 2015 and 2025 were synthesized to evaluate the characteristics of GFM control strategies. The review organizes GFM strategies, evaluates their performance under varying operational scenarios, and emphasizes persistent challenges like grid stability, inertia emulation, and fault ride-through capabilities. Furthermore, this study examines real-world implementations of GFM technology in modern power grids. Notable projects include the UK’s National Grid Pathfinder Program, which integrates GFM inverters to enhance stability, and Australia’s Hornsdale Power Reserve, where battery energy storage with GFM capabilities supports grid frequency regulation. Full article