Search Results (17)

The large-scale integration of renewable energy has significantly improved the low-carbon performance of power systems, but has also increased operational uncertainty. Under extreme weather conditions, wind and solar power may experience consecutive days of simultaneous output shortfalls—referred to as “renewable energy drought”—leading to persistently high net load and severe challenges to supply guarantee. To address this issue, this paper proposes a multi-source coordinated supply-guarantee dispatch strategy for consecutive-day renewable energy drought scenarios. First, net load is defined as the total system load minus the available wind and solar output. Based on magnitude and duration thresholds, renewable energy drought events are extracted from historical data to generate representative scarcity scenarios. Second, a multi-source coordinated optimization dispatch model is constructed, incorporating wind power, solar power, thermal units, battery energy storage, and pumped-storage hydro. The objective is to minimize the total system operating cost, which includes thermal fuel cost, start-up/shut-down costs, storage cycling cost, wind/solar curtailment penalty cost, and load shedding penalty cost. The load shedding penalty coefficient is set to a magnitude much higher than conventional costs to highlight the priority of supply guarantee. The model accounts for operational constraints such as minimum up/down times, deep regulation capability, ramping limits of thermal units, and charge/discharge power limits of storage. Taking a provincial power system in China for the year 2030 as a case study, a dispatch case covering four consecutive days (96 time periods) is designed. Based on a baseline scenario, eight groups of sensitivity analyses are conducted to comprehensively investigate the impacts of key factors on the supply-guarantee strategy, including: the minimum up/down time of thermal units, deep regulation capability, load shedding penalty cost, load level, rated energy capacity and charge/discharge efficiency of battery energy storage, rated energy capacity and pumping/generating efficiency of pumped-storage hydro, thermal fuel cost coefficient, and renewable energy capacity. Simulation results show that the proposed strategy can effectively coordinate multiple resources under consecutive-day drought conditions; reducing the minimum up/down time of thermal units improves supply flexibility but increases start-up/shut-down costs; enhancing deep regulation capability optimizes storage utilization and reduces total system cost; the load shedding penalty cost directly determines the trade-off between supply guarantee and economic efficiency; and as load level decreases by 5%, 10%, and 15%, the total system operating cost reduces by approximately 6.3%, 12.5%, and 18.8%, respectively. This study provides a quantitative method and technical support for supply-guarantee dispatch decisions and resource allocation in high-renewable power systems under persistent drought conditions. Full article

This research investigates novel polymeric composite materials made from recycled polyolefin and waste plant biomass (poplar seeds and vegetable peels), which have potential applications in the relatively unexplored field of electrical insulation. For composites made from poplar seeds with low density polyethylene matrix, the structure appears more uniform, even with increased biomass content, in contrast to those utilizing high density polyethylene matrix, which displays notable heterogeneous areas where the polymer appears separated from the fibrous network at higher biomass levels. Concerning the composites of vegetable peels with high density polyethylene matrix, the fragments of vegetable peels are clearly recognizable, and their bond to the polymer matrix appears weaker. When incorporating vegetable peels into the polypropylene matrix, it results in a better distribution of the vegetable peel fragments within the polymer matrix, as well as enhanced structural homogeneity. Overall, the incorporation of biomass reduces the Shore hardness measurement for every polymer matrix. Regarding tear resistance, the inclusion of biomass reduces the values only for low density polyethylene with poplar seeds. For both high density polyethylene and polypropylene, regardless of the biomass type, the property seems to enhance marginally with the addition of biomass. The primary advantage of utilizing these composites is that their water absorption rate is at least twice as low as that of transformer board, while still offering a similar capacity for absorbing transformer oil. All composite types exceeded the minimum required threshold of 70 °C for service exposure, and adhered to insulation class A, similar to cellulose-based insulations. The addition of cellulose to polyolefin composites appears to slightly improve their breakdown strength. The conductivity for this type of composite is at least three times lower than that of cellulose insulation materials, rendering them beneficial for applications in electrical engineering as potential substitutes for cellulose-based materials in multiple electrical insulation uses, e.g., for insulating low voltage electrical machines, as well as serving as a substitute for pressboard in transformers. Additionally, their thermoplastic properties offer enhanced processing versatility, opening up new opportunities for electrical engineering technology, especially with regard to electrical insulation recyclability in the context of a circular economy. Full article

With the advancement of technology, increasing attention has been focused on the development of encryption techniques. Visual secret sharing (VSS), also known as visual cryptography (VC), is used to encrypt a secret image into multiple share images, which can be stacked together to visually reconstruct the secret without complex computations. Decryption in traditional VSS schemes is equivalent to performing logical OR operations. In 2023, a novel (k,n)-threshold VSS based on polarization (P-VSS) scheme was proposed. This scheme utilizes the physical property that two orthogonal polarizers block light transmission to simulate a better VSS. A minimum of k shares is required to successfully reveal the original secret. In this study, we further propose a (f,k,n) dual-threshold P-VSS scheme. The proposed polarization-based scheme introduces two distinct reconstruction thresholds. When f or more shares are stacked, a fake secret image is revealed to mislead potential attackers. Only when k or more shares are combined can the true secret image be successfully recovered. This dual-threshold design significantly enhances the security of visual secret sharing by increasing the confusion for potential attackers and improving resistance against information leakage. Full article

Aedes aegypti is the primary urban vector for several important arboviruses, including dengue, chikungunya, yellow fever, and Zika viruses. Traditional dengue virus (DENV) surveillance relies on passive reporting of human cases, which often underestimates transmission due to asymptomatic or unreported infections. This study evaluated the utility of monitoring DENV in Ae. aegypti mosquitoes to improve detection of local dengue transmission and inform vector control strategies during the 2024 dengue epidemic in Puerto Rico. Mosquito surveillance was conducted in 15 neighborhoods within the San Juan metropolitan area where confirmed dengue cases had been recently reported. Adult female Ae. aegypti were collected weekly using Autocidal Gravid Ovitraps (AGO traps) placed within a 200 m radius of index cases. Pools of 1–20 mosquitoes were tested for DENV RNA and serotype using RT-PCR. Surveillance continued for up to 91 days in study areas, depending on virus detection. A total of 29,354 female Ae. aegypti were collected, of which 29,211 females were pooled (1–20 specimens per pool) into 3878 pools and analyzed. DENV was detected in 49 pools across 11 neighborhoods, with serotypes DENV-1, DENV-2, and DENV-3 identified. Multiple serotypes were sometimes detected in mosquitoes from the same neighborhood. Minimum infection rates and vector indices were higher during the epidemic than in previous inter-epidemic periods, and mosquito densities exceeded thresholds considered protective against outbreaks. Entomo-virological surveillance detected a greater variety and evenness of serotypes than passive human surveillance. These findings suggest that entomo-virological surveillance can complement passive case surveillance, providing a more comprehensive detection of DENV circulation. Integrating mosquito-based and human surveillance can improve outbreak detection, guide vector control, and aid in reducing dengue burden in affected communities. Full article

To address the key issues in cooperative collision avoidance of multiple aircraft, such as unknown dynamics, external disturbances, and limited communication resources, this paper proposes a reference correction method based on the Artificial Potential Field-Control Barrier Function (APF-CBF) and combines it with a dynamic event-triggered mechanism to achieve efficient cooperative control. This paper adopts a Fuzzy Wavelet Neural Network (FWNN) to design a finite-time disturbance observer. By leveraging the advantages of FWNN, which integrates fuzzy logic reasoning and the time-frequency locality of wavelet basis functions, this observer can synchronously estimate system states and unknown disturbances, to ensure the finite-time uniformly ultimate boundedness of errors and break through the limitation of insufficient robustness in traditional observers. Meanwhile, the APF is embedded in the CBF framework. On the one hand, APF is utilized to intuitively describe spatial interaction relationships, thereby reducing reliance on prior knowledge of obstacles; on the other hand, CBF is used to strictly construct safety constraints to overcome the local minimum problem existing in APF. Additionally, the reference correction mechanism is combined to optimize trajectory tracking performance. In addition, this paper introduces a dynamic event-triggered mechanism, which adjusts the triggering threshold by real-time adaptation to error trends and mission phases, realizing “communication on demand”. This mechanism can reduce communication resource consumption by 49.8% to 69.8% while avoiding Zeno behavior. Theoretical analysis and simulation experiments show that the proposed method can ensure the uniformly ultimate boundedness of system states and effectively achieve safe collision avoidance and efficient formation tracking of multiple aircraft. Full article

Traditional high-utility itemset (HUI) mining methods tend to overestimate utility for long itemsets, leading to biased results. High average-utility itemset (HAUI) mining addresses this problem by normalizing utility with itemset length. However, uniform utility thresholds fail to account for varying item importance. Recently, HAUI mining with multiple minimum utility thresholds (MMU) has been used for flexible utility evaluation. While the generalized HAUIM (GHAUIM) algorithm performs well, it requires two database scans and is limited to static datasets. Therefore, we developed a novel tree-based method that scans the database only once to improve efficiency by reducing storage and eliminating costly join operations. Additionally, pruning strategies and incremental updates were introduced to enhance scalability. The developed method outperformed GHAIM in efficiency. Full article

This paper addresses the challenge of fostering cooperation among virtual power plant (VPP) operators in competitive electricity markets, focusing on the application of evolutionary game theory (EGT) and static reward–punishment mechanisms. This investigation resolves four critical questions: the minimum reward–punishment thresholds triggering stable cooperation, the influence of initial market composition on equilibrium selection, the sufficiency of static versus dynamic mechanisms, and the quantitative mapping between regulatory parameters and market outcomes. The study establishes the mathematical conditions under which static reward–punishment mechanisms transform competitive VPP markets into stable cooperative systems, quantifying efficiency improvements of 15–23% and renewable integration gains of 18–31%. Through rigorous evolutionary game-theoretic analysis, we identify critical parameter thresholds that guarantee cooperation emergence, resolving longstanding market coordination failures documented across multiple jurisdictions. Numerical simulations and sensitivity analysis demonstrate that static reward–punishment systems enhance cooperation, optimize resources, and increase renewable energy utilization. Key findings include: (1) Reward–punishment mechanisms effectively promote cooperation and system performance; (2) A critical region exists where cooperation dominates, enhancing market outcomes; and (3) Parameter adjustments significantly impact VPP performance and market behavior. The theoretical contributions of this research address documented market failures observed across operational VPP implementations. Our findings provide quantitative foundations for regulatory frameworks currently under development in seven national energy markets, including the European Union’s proposed Digital Single Market for Energy and Japan’s emerging VPP aggregation standards. The model’s predictions align with successful cooperation rates achieved by established VPP operators, suggesting practical applicability for scaled implementations. Overall, through evolutionary game-theoretic analysis of 156 VPP implementations, we establish precise conditions under which static mechanisms achieve 85%+ cooperation rates. Based on this, future work could explore dynamic adjustments, uncertainty modeling, and technologies like blockchain to further improve VPP resilience. Full article

With the rapid development of wireless communication networks and Internet of Things technology (IoT), higher requirements have been put forward for spectrum resource utilization and system performance. In order to further improve the utilization of spectrum resources and system performance, this paper proposes an intelligent reflecting surface (IRS)-assisted fair energy allocation algorithm for cognitive multiple-input single-output (MISO) wireless-powered networks. The goal of this paper is to maximize the minimum energy receiving power in the energy receiver, which is constrained by the signal-to-interference-plus-noise ratio (SINR) threshold of the information receiver in the secondary network, the maximum transmission power at the cognitive base station (CBS), and the interference power threshold of the secondary network on the main network. Due to the coupling between variables, this paper uses iterative optimization algorithms to optimize and solve different variables. That is, when solving the active beamforming variables, the passive beamforming variables are fixed; then, the obtained active beamforming variables are fixed, and the passive beamforming variables are solved. Through continuous iterative optimization, the system converges. The simulation results have verified the effectiveness of the proposed algorithm. Full article

In the realm of building demolition, ensuring the uniform distribution of energy from multiple sources is of paramount significance for the systematic deconstruction of large structures. This study presents an integrated methodology that combines genetic optimization and potential energy balance to determine the most suitable locations for multiple energy release points, thereby enhancing the efficiency and reliability of the demolition process. We initiate our approach by randomly selecting energy release points within a building model and subsequently simulate energy dispersion utilizing a potential function until reaching stable boundaries. In instances where the discrepancy in the area between the regions with maximum and minimum energy dispersion exceeds a predefined threshold, we instigate an optimization process employing genetic algorithms. This optimization process involves genetic crossover and mutation operations, followed by subsequent energy balance calculations. The result is not only an improvement in demolition efficiency but also an assurance of even energy coverage throughout the target area. Full article

The integration of non-orthogonal multiple access (NOMA) technology and cognitive radio networks (CRNs) promises to enhance the spectrum utilization efficiency of 5G and beyond-5G (B5G) mobile communication systems. In this article, a NOMA-based spectrum-sharing scheme is proposed for dual-hop CRNs in which a primary transmitter separated by a long distance from the primary receiver communicates via NOMA-based CRN. In this scenario, we mathematically formulate a constrained optimization problem to maximize the sum rate of all secondary users (SUs) while maintaining the total transmit power of the system. Inspired by the effectiveness of computational intelligence (CI) tools in solving non-linear optimization problems, this article proposes three CI-based solutions to the given problem aiming to guarantee quality of service (QoS) for all users. In addition, an enhanced version of the classic artificial bee colony (ABC) algorithm, referred to here as the enhanced-artificial-bee-colony (EABC)-based power allocation scheme, is proposed to overcome the limitations of classic ABC. The comparison of different CI approaches illustrates that the minimum power required by the secondary NOMA relay to satisfy the primary rate threshold of 5 bit/s/Hz is 20 mW for EABC, while ABC, PSO and GA achieve the same target at 23 mW, 27 mW and 32 mW, respectively. Thus, EABC reduces power consumption by 13.95% compared to ABC, while 29.78% and 46.15% power-saving is achieved compared to PSO and GA, respectively. Full article

Cured-in-place pipe (CIPP) is one of the most popular in situ rehabilitation techniques to repair sewer and water pipes. While there are multiple approaches to curing CIPP, steam-curing of styrene-based resins has been found to be associated with air-borne chemical emissions. Health officials, utilities and industry representatives have recognized the need to know more about these emissions, especially styrene. Such concern has led to multiple studies investigating the concentrations of volatile organic compounds on CIPP installation sites. This study expands upon previous effort by modeling worst-case, steam-cured CIPP emissions over a 5-year weather record. The effort also includes calibration of the model to emissions averages over the work day rather than instantaneous field measurements. Dispersion modelling software, AERMOD, was utilized to model the styrene component of CIPP emissions on two CIPP installation sites in the US. Based on the analysis results, it was found that the styrene emitted from stacks dissipates rapidly with styrene concentrations only exceeding minimum health and safety threshold levels at distances close to the stack (2 m or less). The values predicted by the model analysis are comparable with the field measured styrene concentrations from other studies. Current safety guidelines in the US recommend a 4.6-m (15-ft) safety perimeter for stack emission points. The results of this study indicate that significant and lasting health impacts are unlikely outside recommended safety perimeter. The results also validate the importance of enforcing recommended safety guidance on steam-cured CIPP sites. Full article

Grassland species diversity monitoring is essential to grassland resource protection and utilization. “Spectral variation hypothesis” (SVH) provides a remote sensing method for monitoring grassland species diversity at pixel scale by calculating spectral heterogeneity. However, the pixel spectrum is easily affected by soil and other background factors in natural grassland. Unmanned aerial vehicle (UAV)-based imaging spectroscopy provides the possibility of soil information removal by virtue of its high spatial and spectral resolution. In this study, UAV-imaging spectroscopy data with a spatial resolution of 0.2 m obtained in two sites of typical alpine steppe within the Sanjiangyuan National Nature Reserve were used to analyze the relationships between four spectral diversity metrics (coefficient of variation based on NDVI (CV_NDVI), coefficient of variation based on multiple bands (CV_Multi), minimum convex hull volume (CHV) and minimum convex hull area (CHA)) and two species diversity indices (species richness and the Shannon–Wiener index). Meanwhile, two soil removal methods (based on NDVI threshold and the linear spectral unmixing model) were used to investigate the impact of soil on species diversity estimation. The results showed that the Shannon–Wiener index had a better response to spectral diversity than species richness, and CV_Multi showed the best correlation with the Shannon–Wiener index between the four spectral diversity metrics after removing soil information using the linear spectral unmixing model. It indicated that the estimation ability of spectral diversity to species diversity was significantly improved after removing the soil information. Our findings demonstrated the applicability of the spectral variation hypothesis in natural grassland, and illustrated the impact of soil on species diversity estimation. Full article

The secondary users (SUs) in cognitive radio networks (CRNs) can obtain reliable spectrum sensing information of the primary user (PU) channel using cooperative spectrum sensing (CSS). Multiple SUs share their sensing observations in the CSS system to tackle fading and shadowing conditions. The presence of malicious users (MUs) may pose threats to the performance of CSS due to the reporting of falsified sensing data to the fusion center (FC). Different categories of MUs, such as always yes, always no, always opposite, and random opposite, are widely investigated by researchers. To this end, this paper proposes a hybrid boosted tree algorithm (HBTA)-based solution that combines the differential evolution (DE) and boosted tree algorithm (BTA) to mitigate the effects of MUs in the CSS systems, leading to reliable sensing results. An optimized threshold and coefficient vector, determined against the SUs employing DE, is utilized to train the BTA. The BTA is a robust ensembling machine learning (ML) technique gaining attention in spectrum sensing operations. To show the effectiveness of the proposed scheme, extensive simulations are performed at different levels of signal-to-noise-ratios (SNRs) and with different sensing samples, iteration levels, and population sizes. The simulation results show that more reliable spectrum decisions can be achieved compared to the individual utilization of DE and BTA schemes. Furthermore, the obtained results show the minimum sensing error to be exhibited by the proposed HBTA employing a DE-based solution to train the BTA. Additionally, the proposed scheme is compared with several other CSS schemes such as simple DE, simple BTA, maximum gain combination (MGC), particle swarm optimization (PSO), genetic algorithm (GA), and K-nearest neighbor (KNN) algorithm-based soft decision fusion (SDF) schemes to validate its effectiveness. Full article

Since electronic components are constantly getting smaller and smaller, sensors and logic boards can be fitted into smaller enclosures. This miniaturization lead to the development of smart rings containing motion sensors. These sensors of smart rings can be used to recognize hand/finger gestures enabling natural interaction. Unlike vision-based systems, wearable systems do not require a special infrastructure to operate in. Smart rings are highly mobile and are able to communicate wirelessly with various devices. They could potentially be used as a touchless user interface for countless applications, possibly leading to new developments in many areas of computer science and human–computer interaction. Specifically, the accelerometer and gyroscope sensors of a custom-built smart ring and of a smartwatch are used to train multiple machine learning models. The accuracy of the models is compared to evaluate whether smart rings or smartwatches are better suited for gesture recognition tasks. All the real-time data processing to predict 12 different gesture classes is done on a smartphone, which communicates wirelessly with the smart ring and the smartwatch. The system achieves accuracy scores of up to 98.8%, utilizing different machine learning models. Each machine learning model is trained with multiple different feature vectors in order to find optimal features for the gesture recognition task. A minimum accuracy threshold of 92% was derived from related research, to prove that the proposed system is able to compete with state-of-the-art solutions. Full article

Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) proves to be a better choice for high speed underwater acoustic (UWA) communication as it increases the data rate and solves the bandwidth limitation issue; however, at the same time, it increases the design challenges and complexity of the receivers. Inter-Symbol Interference (ISI) and Inter-Carrier Interference (ICI) are introduced in the received signal by the extended multipath and Doppler shifts along with different types of noises due to the noisy acoustic channel. Here we propose two iterative receivers: one is ICI unaware iterative MIMO-OFDM receiver, which uses a novel cost function threshold based soft information decision feedback method. The second one is ICI aware progressive iterative MIMO-OFDM receiver, which adapts and increases the progressions according to the level of ICI present in the received signal, while fully utilizing the soft information from the previous iterations, therefore reducing the complexity. Orthogonal Matching pursuit (OMP) channel estimation, low density parity check (LDPC) decoding and minimum mean square error (MMSE) equalization schemes are exploited by both the receivers. The proposed receivers are analyzed and compared with the standard Alamouti MIMO receiver as a reference and also compared with the non-iterative, basic turbo iterative and non-progressive iterative MIMO receivers. Simulations and experimental results prove the efficiency and effectiveness of the proposed receivers. Full article