Search Results (295)

An increasing penetration of distributed energy resources and electrification-driven peak demand pose significant challenges to distribution networks, often resulting in voltage violations and congestion. This paper presents a multi-stage optimization framework that enables battery storage unit (BSU) to act as a flexible non-wire alternative to traditional grid expansions conducted by Distribution System Operators (DSO), but also helpful for Transmission System Operators (TSO). The proposed method integrates a mixed-integer planning model with a quadratically constrained, second-order-cone–relaxed, AC optimal power flow to determine the optimal siting and sizing of battery storage. Representative operating days are obtained through clustering, while the operational optimization model evaluates battery participation in energy and reserve markets under network constraints. The value of flexibility the DSO procures from an independently-owned battery storage unit is determined as the opportunity cost of providing this flexibility as opposed to taking part in the fast reserves and day-ahead energy markets. The results obtained offer valuable information when weighing the decision between network expansion and alternative strategies and determine the price of flexibility that the DSO can offer to an independently owned storage unit. The results confirm that battery storage can defer network investments while providing transparent and economically justified flexibility remuneration. The proposed framework is implemented sequentially, with strong coupling between planning and operational stages through physical constraints and economic signals. Full article

This paper presents an Internet of Things-oriented intelligent supervisory system and high-level control for a small wind turbine powering a residential building. The proposed approach integrates wind generation, battery storage, grid interaction, technical condition analysis, and initial operating mode selection within a single cyber–physical framework. A nonlinear discrete–time hybrid mathematical model was developed for the study, describing the interdependent operating processes of the turbine, storage, and power converter, along with a control algorithm that accounts for constraint flows. A series of experiments are presented for steady-state and dynamic operating scenarios, including wind-speed variations, evening energy shortages, stochastic disturbances, and a developing converter unit fault. As a result, the proposed Internet of Things-oriented supervisory algorithm ensures more efficient utilization of the available wind resource, reduced grid-import dependency, improved battery reserve preservation, and lower thermal loading of the power electronics. Under developing fault conditions and stochastic operating disturbances, the proposed framework maintains more stable residential energy-management behavior and improved operational robustness. The obtained results confirm the potential of the proposed control design for autonomous and semi-autonomous low-power wind energy systems for residential and distributed use. Full article

The transition toward modern power systems with high renewable penetration has significantly increased the demand for system flexibility. However, existing reserve capacity assessment methods often overestimate the actual deliverable flexibility by neglecting network topology constraints. This paper proposes a topology-constrained flexibility assessment framework based on the Regional Security-Constrained Economic Dispatch (R-SCED) model to quantify the true deliverable reserve of adjustable resources in electricity spot markets. Unlike conventional approaches, the proposed framework explicitly captures the spatial distribution of load increments and their interactions with transmission constraints. Through multi-scenario analysis, we reveal a critical “capacity restriction effect”, where network bottlenecks drastically reduce the theoretically available reserve. Case studies on an 88-node multi-area system show that the actual upward flexibility is reduced from a theoretical level of 67,000 MW to a constrained range of 5200–19,000 MW. The results demonstrate that flexibility in modern power systems is fundamentally limited by network topology rather than generation capacity, highlighting the necessity of topology-aware reserve assessment for real-time market operation. This work provides important insights for improving dispatch strategies and enhancing system flexibility under high renewable penetration. Full article

Reservoir simulation of unconventional resources has become increasingly important due to advancing technologies and the growing demand for efficient hydrocarbon recovery. These reservoirs present distinct challenges related to characterization, multiphase flow behavior, and production forecasting. Reservoir simulation workflows integrate geological, petrophysical, and fluid-property data to better represent subsurface behavior. As hydraulic fractures provide the primary pathways for fluid flow in unconventional reservoirs, accurately modeling fracture geometry and conductivity is essential for reliable reserves estimation, production forecasting, and field development planning. Fracture conductivity is controlled by several coupled processes, including fracture propagation, proppant transport, proppant placement, and stress-dependent permeability, which makes its accurate estimation challenging. Although commercial hydraulic fracturing software incorporates geomechanical and particle-transport models to predict conductivity, their outputs are not always directly compatible with reservoir simulation models and often fail to reproduce observed production trends. This study implements various conductivity models in commercial software and evaluates their performance within reservoir simulation. A fracture model built from publicly available data is integrated into a mechanistic reservoir simulation framework to assess the impact of different conductivity models on pressure distribution, depletion behavior, and production profiles. The results provide practical insights into conductivity modeling approaches that balance realism with applicability in reservoir simulation workflows. Different conductivity models, including constant, expanded conductive zone, linear, and multiple exponential forms, were evaluated. It was found that conductivity variation directly impacts well profiles, ultimate recoveries and well spacing in unconventional reservoir development. Full article

Centralized reactive orchestration in Low Earth Orbit (LEO) networks struggles with heavy-tailed traffic surges that trigger signaling storms and topology instability. To address this challenge, we develop a LEO-specific predictive resource allocation framework that integrates spectral-aware distributional forecasting with risk-aware allocation. The forecasting module pairs cascaded dual-scale Exponential Moving Average (EMA) decomposition with a direct multi-step decoder to suppress autoregressive error accumulation. A Spectral Penalty operating in the frequency domain enhances sensitivity to orbital harmonics, while nonuniform quantization yields calibrated probabilistic bounds that preserve heavy-tailed characteristics. On the allocation side, the predictive standard deviation serves as an endogenous risk index amplified by service priority to form a capacity bound that is explicitly aware of risk. A companion demand model structurally reserves a fixed control plane bandwidth floor, insulating signaling from data plane congestion. Simulation results show that the forecasting module reduces the Continuous Ranked Probability Score (CRPS) by up to 5.9% relative to the strongest compared distributional baseline across prediction horizons of 30–105 min. Under a 300% traffic shock, the distributed allocation mechanism maintains 99.99% satisfaction for the highest priority service class and keeps control plane overflow below 0.05%. Lower-priority traffic is curtailed through compression governed by priority, and the per-node memory consumption is sufficiently low for deployment on current onboard satellite processors. Full article

China hosts a large number of closed coal mines containing abundant residual resources. Driven by resource recycling, mine safety, environmental protection, and the dual-carbon goals, research on gas resources in closed coal mines has expanded rapidly. In some closed mines, substantial unmined coal resources remain with high gas content, making in situ gas resources a key focus of investigation. Given the Xinzhuangzi closed coal mine as a case study, this study analyzed the distribution of coal resources based on the monitoring results of coal extraction and remaining reserves, and the distribution of gas content based on regression equation. Furthermore, it applied a volumetric calculation method to estimate the gas resources of any a certain unit, all units, and summarize the gas resources across different coal seams, structural divisions, mining levels and the entire coal mine, thereby characterizing the in situ gas resources. The results indicated that the area below −412 m in the closed Xinzhuangzi coal mine was favorable for in situ gas resource development, containing 20,061.1 × 10⁴ t of coal resource and 2250.32 × 10⁶ m³ of gas resources, with a gas resource abundance of 1.96 × 10⁸ m³/km². C13, B11b, B4, B7a, B6, and B8 were favorable targets for in situ gas resources, each containing over 100 × 10⁶ m³ of gas resources, and these seams were thick and stable. Levels 6 and 7 were favorable zones for in situ gas resources, each containing abundant coal resources with high gas content, holding 644.94 × 10⁶ and 1407.77 × 10⁶ m³ of gas resources, respectively. These findings provided not only a scientific basis for the future evaluation and development of gas resources in this coal mine, but also important references for the study of in situ gas resources in other abandoned mines. And, several suggestions were given about the development prospects of gas resources. Full article

In future active distribution networks with high penetrations of renewable energy, flexible loads are expected to play an increasingly important role as reserve resources to support the sustainable and reliable operation of power grids. Accurate evaluation of flexible load reserve capacity is therefore essential for reliable reserve scheduling. Existing research mainly focuses on the operational characteristics and physical constraints of flexible loads, while insufficiently accounting for user response willingness and the uncertainty of user decision-making behavior, which may lead to biased reserve capacity assessments and impair the sustainability of reserve supply in actual grid operation. To address this issue, this paper proposes a results-oriented reserve capacity evaluation method for flexible loads that explicitly incorporates user response willingness. Specifically, a fuzzy logic system is developed to quantitatively characterize the response willingness of electric vehicle (EV) and air-conditioning (AC) users under multiple influencing factors. Then, a probabilistic modeling approach for user decision-making behavior is established using the theory of planned behavior, enabling explicit representation of behavioral uncertainty. Furthermore, a comprehensive reserve capacity evaluation framework for flexible loads is constructed by integrating user willingness states, sustainable response duration, and operational power constraints. Finally, the case studies demonstrate that the proposed method can effectively improve the objectivity of flexible load reserve capacity assessments while maintaining high user participation willingness, thus supporting the long-term sustainable application of flexible loads as grid reserve resources. Full article

Industrial isolated power systems are highly sensitive to load disturbances due to their limited inertia and absence of large-grid support. This article analyzes the dynamic stability of an isolated system with a current available generation contribution of approximately 24 MW, evaluating the integration of a new production plant planned to be integrated in two construction phases of 2 MW each (total 4 MW). The system operates with local generation at 13.8 kV and distribution at 34.5 kV; therefore, demand expansion requires a detailed assessment to maintain safe operating conditions. In addition, the study verifies compliance with spinning reserve requirements for Phase 1 and Phase 2 in accordance with applicable industrial power system criteria, including IEEE 3007.1 and IEEE C37.106, as part of the N−1 security assessment. The developed stability analysis is based on time-domain dynamic simulations using IEEE AC8C excitation models and a UG-8 governor. The results show that, under severe contingencies, the frequency nadir can reach deviations close to 1.5 Hz and RoCoF values above 4 Hz/s. The results indicate that Phase 1 (2 MW) can be incorporated while maintaining acceptable spinning reserve margins, whereas the additional 2 MW corresponding to Phase 2 cannot be integrated under the current operating conditions without violating reserve criteria. However, the system remains stable when generators operate under automatic voltage control, while fixed power factor mode produces less robust responses. Based on this result, the dynamic analysis is focused on the Phase 1 condition under critical contingencies, particularly the sudden outage of the 5 MW and 8 MW generating units, with special emphasis on the outage of the largest generator, mitigated through spinning reserve support and a RoCoF-based load shedding scheme of approximately 4.4 MW. Likewise, the energization of the new plant through the 8 km line requires the evaluation of the available reactive compensation resources, including the use of capacitor banks/reactive support, to prevent underexcitation and maintain acceptable voltage conditions. Full article

The Northeast Black Soil Region is an important commercial grain production base in China. However, ecological issues such as black soil degradation and soil erosion pose direct threats to food security. Previous studies have mainly examined individual factors of black soil degradation. Few have integrated spatial thickness distribution with multi-dimensional ecological sensitivity. To address this gap, this study establishes an ecological sensitivity evaluation index system for Bayan County, located in the eastern Songnen High Plain. Based on a review of relevant literature, the system includes four dimensions: topography, climate, natural resources, and human activities. A combined Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM) was used to determine indicator weights. Compared with single-weighting methods, this approach balances expert judgment with data-driven variation. The results are as follows. (1) The thickness of the black soil layer in Bayan County ranges from 18 to 77 cm. Medium, thin, and thick layers account for 78.81%, 16.32%, and 4.87% of the area, respectively. The total black soil reserve is estimated at about 1.267 billion m³. (2) Among the primary indicators, natural resources have the highest weight (0.53). The five most important secondary indicators are the river buffer zone (0.14), NDVI (0.13), soil type (0.12), land use type (0.12), and road buffer zone (0.09). (3) The overall ecological sensitivity of the county is moderate, with a composite index ranging from 1.45 to 4.45. The proportions of extremely sensitive, highly sensitive, moderately sensitive, mildly sensitive, and insensitive areas are 10.79%, 25.51%, 28.95%, 24.23%, and 10.52%, respectively. These findings provide a scientific basis for ecological protection and black soil conservation. They also support the development of targeted, zone-specific management strategies in Bayan County. Full article

The daily activity patterns of wild animal species are driven by environmental conditions and plant productivity although the degree of dependence varies according to their ecological niche. Bear ecology is intrinsically linked to seasonal vegetative availability. As omnivores with high metabolic demands, these species rely heavily on botanical resources including fruits, seeds, and roots. Consequently, differences in primary productivity across the landscape influence how individuals distribute their circadian activity patterns. The Enhanced Vegetation Index (EVI) is a tool that quantifies the quality and vigor of vegetation. Relating the EVI to activity patterns allows us to understand how vegetation dynamics and conditions influence the use of time at different times of the day. This study analyzes the daily activity pattern of the American black bear (Ursus americanus) in the El Cielo Biosphere Reserve (ECBR) using camera traps and its association with spatial variations in the Enhanced Vegetation Index (EVI). The results show that the daily activity pattern of the American black bear in the ECBR exhibits a diurnal–crepuscular tendency. In areas with high primary productivity and higher temperatures, activity occurs before sunrise and at sunset, with low activity during the rest of the day. In contrast, in areas with less vegetation and lower temperatures, activity occurs throughout the day. This suggests that, in the ECBR, the activity pattern of black bears could be modulated by temperature variations related to changes in vegetation productivity. Full article

The depletion of global reserves of high-quality sulfide nickel deposits, coupled with the steady growth of nickel demand, has led to increased interest in the processing of oxidized (lateritic) nickel ores, including deposits with significant resource potential in the Republic of Kazakhstan. This paper provides an overview of global nickel ore reserves and their distribution, as well as the major nickel deposits in Kazakhstan, which are primarily located in the Aktobe, East Kazakhstan, Kostanay, and Pavlodar regions. Pyrometallurgical processing routes for lateritic nickel ores are also considered. Conventional production technologies, including the Rotary Kiln–Electric Furnace (RKEF), Krupp–Renn process, blast furnace smelting, Vaniukov process, and ISASMELT process, are reviewed, and their process flow diagrams are presented. These methods typically process lateritic nickel ores containing more than 1.2% Ni, whereas Kazakhstan ores are characterized by lower nickel grades, generally in the range of 0.75–1.1%. The advantages and limitations of conventional processing routes are analyzed, and the factors limiting the effective beneficiation of lateritic nickel ores using traditional methods are identified. The present study substantiates the feasibility of producing nickel-containing alloys from lateritic nickel ores using a metallothermic reduction approach. This method is based on the reduction of nickel and iron oxides using metallic reductants, which enables more selective extraction of target components and the formation of alloys with controlled composition. Metallothermic reduction is of particular interest for the processing of low-grade lateritic ores, as it allows the production of nickel-containing alloys without prior beneficiation, at lower energy consumption, and with reduced sensitivity to variations in the chemical and mineralogical composition of the raw materials. Therefore, this approach is considered a promising direction for the processing of lateritic nickel ores in Kazakhstan. Full article

Virtual power plants (VPPs) aggregate flexible resources, such as distributed photovoltaics (PV), energy storage, and flexible loads, to provide substantial reserve capacity for grid operation. However, the combined effects of renewable energy output uncertainty, load forecast errors, and user-bounded rationality responses lead to significant errors in traditional deterministic VPP reserve assessment methods, severely affecting the balance between system supply and demand. To address this challenge, this paper proposes a credible reserve assessment method that accounts for user-bounded rationality. First, thermodynamic models with on–off constraints for air conditioning loads, energy feasible region, and power constraint models for electric vehicles (EVs) and energy storage systems (ESSs), as well as PV forecast error models are established to characterize physical reserve boundaries. Second, prospect theory is introduced to describe user-bounded rationality and a logit-based response probability model is developed. Monte Carlo sampling and kernel density estimation are employed to derive credible reserve sets under different confidence levels, achieving a probabilistic quantification of VPP reserve capacity distribution. Case studies demonstrate that the proposed method accurately characterizes the probabilistic distribution characteristics of VPP reserve provision under multiple uncertainties, providing comprehensive and reliable assessment information for power dispatching agencies. Full article

Multi-regional electricity markets increasingly struggle to balance data privacy requirements with the computational burden of centralized clearing. To address this issue, this study proposes a distributed joint-clearing framework based on the Alternating Direction Method of Multipliers (ADMM) to co-optimize pumped storage hydropower (PSH) and battery energy storage systems (BESS) across energy, frequency regulation, and reserve markets. A mixed-integer programming model is formulated to maximize social welfare, explicitly capturing the time-coupled, energy-oriented characteristics of PSH and the fast-response, power-oriented capabilities of BESS. The global problem is decomposed into regional subproblems that can be solved in parallel. An adaptive penalty parameter strategy is further introduced to dynamically balance primal and dual residuals, thereby improving convergence and robustness in the mixed-integer setting. To address the limited economic interpretability of dual variables in mixed-integer programming (MIP) models, an approximate marginal pricing mechanism based on subproblem sensitivity analysis is proposed. A two-region, 24 h case study shows that the proposed method converges in around 65 iterations and achieves a social welfare outcome within 0.61% of the centralized optimum. By minimizing information exchange, the framework offers a scalable and privacy-aware solution for future multi-regional market operations involving heterogeneous energy storage resources. Full article

Nature-based tourism (NBT) is increasingly promoted as a means to contribute to conservation efforts. However, there is limited understanding of the relationship between environmental education and awareness and conservation attitudes and practices in this form of tourism that centers on green spaces. This study, therefore, aimed to explore this relationship using data from tourism operators and local communities in the Mexican Caribbean and provide useful insights for environmental sustainability in tourism destinations that depend on nature as a critical resource. The study employed a triangulation approach, which involved examination of two sets of data: firstly, household-level survey information from local communities participating in nature-based tourism; and secondly, data from semi-structured in-depth interviews with tour companies operating within the Mexican Caribbean, as well as focus group discussions with key informants including academicians, public-sector stakeholders and other opinion leaders in the tourism industry. Household surveys determined associations between potential predictor variables (environmental education and awareness, local community involvement, costs and benefits distribution) and conservation perspectives and practices in nature-based tourism. Semi-structured interviews and focus group discussions explored participants’ attitudes, experiences and views on environmental education and awareness, nature-based tourism, attitudes and practices towards conservation. Findings demonstrated that direct benefits from nature-based tourism are significant, but do not guarantee positive conservation attitudes and practices among the local communities. Other factors (indirect benefits), such as environmental education and awareness, could be more effective in achieving environmental sustainability and quality in nature-based tourism. It was also found that several tourism operators lack formal environmental education and awareness programs. The study recommends that the entire cycle of using natural resources for tourism purposes and tourists’ interaction with nature be anchored in adequate environmental education and awareness. This research contributes to valuable insights into debates, practices and policy developments related to nature-based tourism as a mechanism for environmental sustainability in biosphere reserves and tourism destinations. Full article