Search Results (210)

As a cultural corridor connecting the Central Plains and Northeast China, the Liaoxi Corridor has a special position in the transmission of traditional Chinese culture. Traditional villages in the region have preserved rich intangible cultural heritage and traditional architectural features, which highlight the historical heritage of multicultural intermingling. This study fills the gap in the spatial distribution of traditional villages in the Liaoxi Corridor and reveals their spatial distribution pattern, which is of great theoretical significance. Using Geographic Information System (GIS) spatial analysis and quantitative geography, this study analyzes the spatial pattern of traditional villages and the influencing factors. The results show that traditional villages in the Liaoxi Corridor are clustered, forming high-density settlement areas in Chaoyang County and Beizhen City. Most villages are located in hilly and mountainous areas and river valleys and are affected by the natural geographic environment (topography and water sources) and historical and human factors (immigration and settlement, border defense, ethnic integration, etc.). In conclusion, this study provides a scientific basis and practical reference for rural revitalization, cultural heritage protection, and regional coordinated development, aiming at revealing the geographical and cultural mechanisms behind the spatial distribution of traditional villages. Full article

Battery-swapping stations (BSSs) are pivotal for supplying energy to electric heavy-duty trucks. However, their operations face challenges in accurate demand forecasting for battery-swapping and fair revenue allocation. This study proposes an optimization strategy for the economic operation of BSSs that optimizes revenue allocation and load balancing to enhance financial viability and grid stability. First, factors including geographical environment, traffic conditions, and truck characteristics are incorporated to simulate swapping behaviors, supporting the construction of an accurate demand-forecasting model. Second, an optimization problem is formulated to maximize the weighted difference between BSS revenue and squared load deviations. An economic operations strategy is proposed based on an adaptive Shapley value. It enables precise evaluation of differentiated member contributions through dynamic adjustment of bias weights in revenue allocation for a strategy that aligns with the interests of multiple stakeholders and market dynamics. Simulation results validate the superior performance of the proposed algorithm in revenue maximization, peak shaving, and valley filling. Full article

The Quaternary saw numerous reorganizations of the hydrographic network, greatly modifying the hydrological network of these rivers. Eastern France is well known for many stream captures, described as early as the late 19th century. The oldest of these have been dated to the Middle Pleistocene. It is interesting to note, however, that these sites, located in the heart of vast limestone plateaus, have systematically become peatland zones, and understanding their functioning is fundamental to wetland restoration and renaturation programs. In addition to serving as biodiversity reservoirs, these peatlands also represent substantial carbon storage potential in the context of global climate change. Using two examples—the Marais de Saint-Gond and the Bar peatland—we propose to provide the key to understanding the origin of their sedimentary filling and the consequences of their current hydrogeological functioning. Full article

This paper proposes a ladder carbon trading-based low-carbon economic dispatch model for integrated energy systems (IESs), incorporating flexible load optimization and hybrid energy storage systems consisting of battery and thermal energy storage. First, a ladder-type carbon trading mechanism is introduced, in which the carbon trading cost increases progressively with emission levels, thereby providing stronger incentives for emission reduction. Second, flexible loads are categorized and modeled as shiftable, transferable, and reducible types, each with distinct operational constraints and compensation mechanisms. Third, both battery and thermal energy storage systems are considered to improve system flexibility by storing excess energy and supplying it when needed. Finally, a unified optimization framework is developed to coordinate the dispatch of renewable generation, gas turbines, waste heat recovery units, and multi-energy storage devices while integrating flexible load flexibility. The objective is to minimize the total system cost, which includes energy procurement, carbon trading expenditures, and demand response compensation. Three comparative case studies are conducted to evaluate system performance under different operational configurations: the proposed comprehensive model, a carbon trading-only approach, and a conventional baseline scenario. Results demonstrate that the proposed framework effectively balances economic and environmental objectives through coordinated demand-side management, hybrid storage utilization, and the ladder-type carbon trading market mechanism. It reshapes the system load profile via peak shaving and valley filling, improves renewable energy integration, and enhances overall system efficiency. Full article

Uncoordinated electric vehicle (EV) charging can significantly complicate power system operations. In this paper, we develop a hybrid EV charging method that seamlessly integrates centralized EV charging and distributed control schemes to address EV energy demand challenges. The proposed method includes (1) a centralized day-ahead optimal scheduling mechanism and EV shifting process based on mixed-integer linear programming (MILP) and (2) a distributed control strategy based on a genetic algorithm (GA) that dynamically adjusts the charging rate in real-time grid scenarios. The MILP minimizes energy imbalance at overloaded slots by reallocating EVs based on supply–demand mismatch. By combining full and minimum charging strategies with MILP-based shifting, the method significantly reduces network stress due to EV charging. The centralized model schedules time slots using valley-filling and EV-specific constraints, and the local GA-based distributed control adjusts charging currents based on minimum energy, system availability, waiting time, and a priority index (PI). This PI enables user prioritization in both the EV shifting process and power allocation decisions. The method is validated using demand data on a radial feeder with residential and commercial load profiles. Simulation results demonstrate that the proposed hybrid EV charging framework significantly improves grid-level efficiency and user satisfaction. Compared to the baseline without EV integration, the average-to-peak demand ratio is improved from 61% to 74% at Station-A, from 64% to 80% at Station-B, and from 51% to 63% at Station-C, highlighting enhanced load balancing. The framework also ensures that all EVs receive energy above their minimum needs, achieving user satisfaction scores of 88.0% at Stations A and B and 81.6% at Station C. This study underscores the potential of hybrid charging schemes in optimizing energy utilization while maintaining system reliability and user convenience. Full article

LED lighting plays a pivotal role in the illumination landscape owing to its substantial energy efficiency, prolonged operational lifespan, environmental advantages, superior light quality, and its capacity for advanced lighting control. Flicker in led lighting systems has emerged as a substantial concern and is appropriate to its potential opposing impacts on human health and visual comfort. Hence, this paper presents a comprehensive analysis, design, and mitigation strategy for flicker in a DC-DC led driver that incorporates a valley fill circuit. The initial stage of this investigation involves an analysis of a conventional cuk converter. However, it is noted that this converter produces an inverting output and experiences high current stress on the semiconductor switch. Consequently, to address these limitations, a non-inverting cuk converter (NICC) is introduced, resulting in a positive output, reduced voltage and current ripple and increased efficiency. To surmount these challenges, the implementation of a valley fill circuit is proposed. This addition facilitates the rapid attainment of a steady state, increases efficiency, and substantially reduces the output voltage and current ripple. An in-depth analysis of the stress imposed on the switch is conducted, leading to the development of a circuit designed to extend the operational life of the LED driver. Therefore, this paper compares the topologies of three different DC-DC cuk power converters. These converters include conventional cuk, non-inverting cuk (NICC), and non-inverting cuk with valley-fill. The performance metrics are examined and compared for all three topologies. The findings of this study affirm that the proposed driver circuit is highly effective in mitigating flicker, thereby enhancing the user experience and elevating the quality of led lighting, all while maintaining energy efficiency. The MATLAB simulations of these converters are performed to validate the theoretical results. Full article

The disordered nature of electric vehicle (EV) charging and user electricity consumption behaviors has intensified the strain on the grid. Meanwhile, energy storage technologies and microgrid interconnections still lack effective supply–consumption regulations and cost–benefit optimization mechanisms. Therefore, the system’s operational efficiency holds significant potential for improvement. This paper proposes hierarchical optimization strategies for the multi-microgrid system to address these issues. In the lower layer, for the charging states of EVs in a single microgrid, an improved simulation method to enhance accuracy and a recursion mechanism of an energy storage margin band to facilitate intelligent EV-to-grid interaction are proposed. Additionally, in conjunction with demand management, an adaptive optimization method and a Pareto decision method are proposed to achieve optimal peak shaving and valley filling for both the EVs and load, yielding a 38.5% reduction in the total electricity procurement costs. The upper layer is built upon the EV–load management strategies of microgrids in the lower layers and evolves into a distributed interconnection structure. Furthermore, a dynamic optimization mechanism based on state mapping and a collaborative optimization method are proposed to improve storage benefits and energy synergies, achieving a 22.1% reduction in the total operating cost. The results provided demonstrate that the proposed strategy optimizes the operation of the multi-microgrid system, effectively enhancing the overall operational efficiency and economic performance. Full article

The planned construction of a steam–gas unit at the Adamów Power Plant raises questions about the potential hydrological impact on the neighboring Natura 2000 protected areas, particularly the Middle Warta Valley (PLB300002) and the Jeziorsko Reservoir (PLB100002). These ecosystems play a key role in protecting bird habitats and biodiversity, and any changes in water management can affect their condition. This paper presents a detailed hydrological analysis of the Warta River and Jeziorsko Reservoir for 2018–2022, with a focus on low-flow periods. The Peak Over Threshold (POT) method and Q_70% threshold were used to identify the frequency, length, and seasonality of low-flow periods in three water gauge profiles: Uniejów, Koło, and Sławsk. The longest recorded low-flow episode lasted 167 days. The permissible water intake for the investment (up to 0.8 m³∙s^–1) is in accordance with the applicable permits and is used mainly for cooling purposes. Calculations indicate that under maximum intake conditions, the water level reduction in the Jeziorsko Reservoir would be between 1.7 and 2.0 mm∙day^–1, depending on the current level of filling. Such changes do not disrupt the natural functions of the reservoir under typical conditions, although during prolonged droughts, they can pose a threat to protected areas. An analysis of the impact of periodic water overflow into the Kiełbaska Duża River indicates its negligible effect on water levels in the reservoir and flows in the Warta River. The results underscore the need for the integrated management of water and power resources, considering the increasing variability in hydrological conditions. Ensuring a balance between industrial needs and environmental protection is key to minimizing the potential impact of investments and implementing sustainable development principles. Full article

The development of fluvial systems over long time scales is a complex interplay of tectonic, climatic, and lithological factors. The initiation and location of fluvial channels in the landscape is less well understood. Recently exposed surfaces provide opportunities to determine factors controlling fluvial channel initiation. During the Würm Last Glacial Maximum (c. 20 ka), the Ain valley in eastern France transformed into a large proglacial lake. Following deglaciation, new drainage channels initiated on the drained lake floor. Extensive morphological and sedimentological mapping and lithogenetic interpretation of the valley fill enable to determine the forcing factors of fluvial channel initiation. The location of the postglacial channels is determined by the initial topography of the lake floor and lithological variability of the sediments. Tributary channels of the Ain preferentially initiated in depressions of gently sloping former delta bottomsets, which prograded from different directions. In addition, the location of channels is determined by the presence of low-permeability, glacio-lacustrine deposits, that favored overland flow and erosion, compared to the highly permeable terrace deposits on the former lake floor. The differences in erodibility of the fine-grained and coarse-grained deposits resulted in relief inversion. Full article

With the expansion of the scale of high-proportion wind and solar power grid connections, the problems of abandoned wind and solar power and insufficient peak shaving have become increasingly prominent. The electric–hydrogen coupling system has greater potential in flexible regulation, providing a new technological approach for the consumption of new energy. This paper proposes a two-layer optimization model for an electricity–hydrogen coupled distributed power generation system. The model is based on the collaborative regulation of flexible loads by electrolytic cells and fuel cells. Through the collaborative optimization of capacity configuration and operation scheduling, it breaks through the strong dependence of traditional systems on the distribution network and enhances the autonomous consumption capacity of new energy. The upper-level optimization model aims to minimize the total life-cycle cost of the system, and the lower-level optimization model aims to minimize the system’s operating cost. The capacity configuration of each module before and after the integration of flexible loads is compared. The simulation results show that the integration of flexible loads can not only effectively reduce the level of wind and solar power consumption in distributed power generation systems, but also play a role in load peak shaving and valley filling. At the same time, it can effectively reduce the system’s peak electricity purchase and sale cost and reduce the system’s dependence on the distribution network. Based on this, with the premise of meeting the load demand, the capacity configuration results of each module were compared when connecting electrolytic cells of different capacities. The results show that the simulated area has the best economic benefits when connected to a 4 MW electrolytic cell. This optimization model can increase the high wind and solar power consumption rate by 23%, reduce the peak purchase and sale cost of electricity by 40%, and achieve an economic benefit coefficient of up to 0.097. Full article

The issue of sulfate (SO₄²⁻) pollution in groundwater has already attracted widespread attention from scientists. However, at the large-scale regional level, especially in areas with groundwater overexploitation, the pollution mechanisms and sources of sulfate remain unclear. This study innovatively investigates the spatial distribution characteristics and sources of SO₄²⁻ in the groundwater of the Hutuo River alluvial fan area, an understudied region facing significant environmental challenges due to overexploitation. Utilizing a combination of hydrochemical analysis, multivariate statistical methods, and geostatistical techniques, we reveal that the mean concentration of SO₄²⁻ is significantly higher (127 mg/L) in overexploited areas, with an exceedance rate of 5.1%. Our findings uncover substantial spatial heterogeneity in SO₄²⁻ concentrations, with particularly high levels in the river valley plain (RVP) (175 mg/L) and the upper area of the alluvial fan (UAF) (169 mg/L), which we attribute to distinct human activities. A novel contribution of our study is the identification of groundwater depth as a critical factor influencing SO₄²⁻ distribution (p < 0.001). We also demonstrate that the higher proportion of sulfate-type waters in overexploited areas is primarily due to the accelerated oxidation of sulfide minerals caused by overexploitation. Principal component analysis (PCA) and correlation analysis further identify the main sources of SO₄²⁻ as industrial wastewater, domestic sewage, the dissolution of evaporites, and the oxidation of sulfide minerals. By integrating geostatistical techniques, we present the spatial distribution of sulfate pollution sources at a fine scale, providing a comprehensive and spatially explicit understanding of the pollution dynamics. These results offer a novel scientific basis for developing targeted strategies to control sulfate pollution and protect the sustainable use of regional groundwater resources. Our study thus fills a critical knowledge gap and provides actionable insights for groundwater management in similar regions facing overexploitation challenges. Full article

As the power system develops towards a high proportion of renewable energy sources and power electronic devices, the power system suffers from poor frequency stability due to the lack of synthetic inertia. The grid-forming energy storage can not only improve the frequency dynamic response of the generator and enhance inertia support capability but can also realize the peak regulation and valley filling of the power system. But its relatively high configuration cost restricts its development and construction. Therefore, how to rationally configure the grid-forming energy storage and grid-following energy storage within the power system by means of corresponding technical approaches has become the focal point of academic research. This study proposes a method for evaluating the inertia distribution characteristics of the power system based on the network equations of the power system. Furthermore, the demand for grid-forming energy storage at each node of the power system under different operation scenarios can be quantified according to this method. Finally, an optimization configuration method for an energy storage system that can improve the inertia distribution characteristics of the power system is proposed, and its effectiveness is verified through the 39-bus system. Full article

Alcalá de Ebro is located 35 km northwest of the city of Zaragoza, on the right bank of the Ebro River at the outlet of a ravine (Juan Gastón) towards the river, with a catchment area of more than 230 km². Over time, urbanisation and agricultural development have eliminated the last stretch of the drainage channel, and these water inputs have been channelled underground, filtering through the ground. This section of the Ebro Valley rests on a marly tertiary substratum, which promotes dissolution-subbing processes that can lead to sinkholes. The ground tends to sink gradually or suddenly collapse. Many studies have been carried out to understand not only the origin of the phenomenon but also its geometry and the area affected by it in the town of Alcalá de Ebro. In this sense, it has been possible to model an area around the main access road, where numerous collapsing sinkholes have been found, blocking the road and affecting houses. It also affects the embankment that protects the town from the floods of the river Ebro. These studies have provided specific knowledge, enabling us to evaluate and implement underground consolidation measures, which have shown apparent success. Several injection campaigns have been carried out, initially with expansion resins and finally with columnar development, using special low-mobility mortars to fill and consolidate the undermined areas and prevent new subsidence. These technical solutions propose a method of ground treatment that we believe is novel for this type of geological process. The results have been satisfactory, but it is considered necessary to continue monitoring the situation and to extend attention to a wider area to prevent, as far as possible, new problems of subsidence and collapse. In this sense, the objective is to continue the control and monitoring of possible phenomena related to subsidence problems in the affected area and its immediate surroundings, to detect and, if necessary, anticipate subsidence or collapse phenomena that could affect the body of the embankment. Full article

The fluctuating uncertainty of load demand as an influencing factor for day-ahead scheduling of an integrated energy system with photovoltaic (PV) power generation may cause an imbalance between supply and demand, and to solve this problem, this paper proposes a day-ahead optimal scheduling model considering uncertain loads and electric heating appliance (EH)–PV energy storage. The model fuses the multi-interval uncertainty set with the CNN-MI-BILSTM neural network prediction technique, which significantly improves the accuracy and reliability of load prediction and overcomes the limitations of traditional methods in dealing with load volatility. By integrating the EH–photothermal storage module, the model achieves efficient coupled power generation and thermal storage operation, aiming to optimize economic targets while enhancing the grid’s peak-shaving and valley-filling capabilities and utilization of renewable energy. The validity of the proposed model is verified by algorithm prediction simulation and day-ahead scheduling experiments under different configurations. Full article

The energy router (ER) is a crucial component in smart distribution networks, and its optimal configuration is essential for enhancing the operational efficiency, economy, and security of the grid. However, existing research rarely considers both the location and sizing costs of the ER in conjunction with flexible load demand response. Therefore, this paper proposes an optimal configuration method for the energy router in active distribution networks, incorporating demand response. First, to balance the comprehensive operational characteristics of the active distribution network throughout the year with computational efficiency, an improved K-means clustering algorithm is employed to construct multiple representative scenarios. Then, a bi-level programming model is established for ER location and sizing, considering demand response. The upper level optimizes the location and capacity configuration of the ER to minimize the overall cost of the distribution network. The lower level focuses on multi-objective optimization, including peak shaving, valley filling, network losses, and voltage deviations, to achieve energy scheduling within the distribution network. Finally, an improved bi-level particle swarm optimization algorithm is employed to solve the model. Simulation results based on the IEEE 33-node system demonstrate that the peak shaving and valley filling optimization rate after ER integration into the active distribution network is at least 9.19%, and it is improved to 14.35% when combined with demand response. Concurrently, the integration of the ER enhances the distribution network’s ability to absorb renewable energy, reduces network losses, and improves power quality. Full article