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Flexible AC Transmission Systems (FACTS) play an important role in minimizing power losses and voltage deviations while increasing the real power transfer capacity of transmission lines. The extent to which these devices can provide benefits to the transmission network depend on their optimal location and sizing. However, finding appropriate locations and sizes of these devices in an electrical network is difficult since it is a nonlinear problem. This paper proposes a technique for the optimal placement and sizing of FACTS, namely the Thyristor-Controlled Series Compensators (TCSCs), Shunt VARs Compensators (SVCs), and Unified Power Flows Controllers (UPFCs). To find the optimal locations of these devices in a network, weak buses and lines are determined by constructing PV curves of load buses, and through the line stability index. Then, the whale optimization algorithm (WOA) is employed not only to find an ideal ratings for these devices but also the optimal coordination of SVC, TCSC, and UPFC with the reactive power sources already present in the network (tap settings of transformers and reactive power from generators). The objective here is the minimization of the operating cost of the system that consists of active power losses and FACTS devices cost. The proposed method is applied to the IEEE 14 and 30 bus systems. The presented technique is also compared with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The findings showed that total system operating costs and transmission line losses were considerably reduced by WOA as compared to existing metaheuristic optimization techniques.

Voltage stability improvement is a challenging issue in planning and security assessment of power systems. As modern systems are being operated under heavily stressed conditions with reduced stability margins, incorporation of voltage stability criteria in the operation of power systems began receiving great attention. This study presents a novel voltage stability constrained optimal power flow (VSC-OPF) approach based on static line voltage stability indices to simultaneously improve voltage stability and minimise power system losses under stressed and contingency conditions. The proposed methodology uses a voltage collapse proximity indicator (VCPI) to provide important information about the proximity of the system to voltage instability. The VCPI index is incorporated into the optimal power flow (OPF) formulation in two ways; first it can be added as a new voltage stability constraint in the OPF constraints, or used as a voltage stability objective function. The proposed approach has been evaluated on the standard IEEE 30-bus and 57-bus test systems under different cases and compared with two well proved VSC-OPF approaches based on the bus voltage indicator L-index and the minimum singular value. The simulation results are promising and demonstrate the effectiveness of the proposed VSC-OPF based on the line voltage stability index.

A large amount of underground cavities nowadays exists throughout the Apulian region (south-eastern Italy) as a result of mining processes of soft calcarenite, which frequently followed the “room and pillar” technique. In these cave systems, pillars and septa are critical structures, whose failure can lead to a significant increment of the sinkhole hazard. The behaviour of these rocky structures in the dynamic field is poorly studied in literature, and the present study aims to investigate their dynamic stability, according to regional seismicity data. For this purpose, ideal pillar geometries were considered, for which the evolution of the stress–strain field under dynamic inputs was observed in both 2D and 3- configurations by means of parametrical finite element analysis. For shallow cavities, slender septa were found to be the most affected by the influence of seismic loading. For deep cavities, dynamic instability is observed only for rather squat septa, with the cavity width also influencing the dynamic behaviour. To quantitatively assess the septum stability, a stability index was also proposed in 2D models. Moreover, three-dimensional analyses showed a stabilizing effect in the pillar exerted by the stress component perpendicular to the earthquake.

Flexible AC Transmission Systems (FACTS) are essential devices used for the efficient performance of modern power systems and many developing countries lack these devices. Due to the non-existence of these advanced technologies, the national grid remains weak and vulnerable to power stability issues that can jeopardize system stability. This study proposes novel research to solve issues of an evolving national grid through the installation of FACTS devices. FACTS devices play a crucial role in minimizing active power losses while managing reactive power flows to keep the voltages within their respective limits. Due to the high costs of FACTS, optimization must be done to discover optimal locations as well as ratings of these devices. However, due to the nonlinearity, it is a challenging task to find the optimal locations and appropriate sizes of these devices. Shunt VARs Compensators (SVCs) and Thyristor-Controlled Series Compensators (TCSCs) are the two FACTS devices considered for the study. Optimal locations for SVCs and TCSCs are determined by Voltage Collapse Proximity Index (VCPI) and Line Stability Index (Lmn), respectively. Particle Swarm Optimization (PSO) is employed to find the ideal rating for FACTS devices to minimize the system operating cost (cost due to active power loss and capital cost of FACTS devices). This technique is applied to IEEE (14 and 30) bus systems. Moreover, reliable operation of the electricity grid through the placement of FACTS for developing countries has also been analysed; Pakistan being a developing country has been selected as a case study. The planning problem has been solved for the present as well as for the forecasted power system. Consequently, in the current national network, 6.21% and 6.71% reduction in active and reactive power losses have been observed, respectively. Moreover, voltage profiles have been improved significantly. A detailed financial analysis covering the calculation of Operation Cost (OC) of the national grid before and after the placement of FACTS devices is carried out.

Sounding rockets constitute a class of rocket with a generally simple layout, being composed of a cylindrical center-body, a nosecone, a number of fins placed symmetrically around the longitudinal axis (usually three or four), and possibly a boat-tail. This type of flying craft is typically not actively controlled; instead, a passive stabilization effect is obtained through suitable positioning and sizing of the fins. Therefore, in the context of dynamic performance analysis, the margin of static stability is an index of primary interest. However, the classical approach to static stability analysis, which consists in splitting computations in two decoupled domains, namely, around the pitch and yaw axis, provides a very limited insight to the missile performance for this type of vehicle due to the violation of the classical assumptions of planar symmetry and symmetric flight conditions commonly adopted for winged aircraft. To tackle this issue, this paper introduces a method for analyzing static stability through a novel index, capable of more generally assessing the level of static stability for sounding rockets, exploiting the same information on aerodynamic coefficients typically required for more usual (i.e., decoupled) static stability analyses, and suggests a way to assess the validity and shortcoming of the method in each case at hand.

In agricultural areas, soil physical quality controls critical properites for plant growth, such as aeration, soil water, and strength. This study investigated the impacts of different long-term land use types (LUTs) (natural pasture (control), kiwi fruit, cherry laurel, forage crops, soybean, and maize) on soil physical properties, such as structure stability index (SSI), bulk density (ρ b ), aeration capacity (AC), and Dexter’s index (S-index). The long-term LUTs significantly affected all the examined soil properties ( p  < 0.01 or p  < 0.001). Other soil physical properties, except for plant available water content, macroporosity, clay content, and silt content, changed statistically depending on soil sampling depths. The S-index values (≥ 0.050) obtained for all LUTs indicate very good physical quality or structural quality in the study area, but the S-index values decreased with the effect of LUTs compared to the natural pasture (control) land use. Different LUTs, such as cherry laurel, soybean, and maize land uses, have caused different structural degradation due to tillage practices. While the natural pasture (control) land use type revealed the best results regarding primarily soil organic carbon (SOC) and SSI, these values were lower in LUTs, where soil tillage is the most common, such as cherry laurel, soybean, and maize land use types. The results regarding S-index reveal that the soils in the study area will continue to be degraded as the impacts of the current LUTs continue. Therefore, for these soils in the future, there is a need for sustainable soil management practices that will protect the physical or structural quality and increase soil organic matter content.

Forecasting thunderstorms, along with their intensity and phenomenon, is still one of the most challenging tasks in modern weather forecasting. One of the methods for this prediction is based on the indices of convective instability in the atmosphere. For the first time, we analysed the values and trends of 23 stability indices on days when hail occurred. From 2005 to 2020, the most frequently observed hailstones had a diameter between 13 and 20 mm, which accounted for 35.8% of all hail days, which was 826. Huge hailstones with a greater than 50 mm diameter were observed on only two days. Eight of the 23 stability indices show a monotonically decreasing (Showalter Index, Lifted Index, Lifted Index using the virtual temperature, and Humidity Index) or increasing trend (K Index, Convective Available Potential Energy for the most unstable air parcel and for mixing layer, and Convective Available Potential Energy in the layer between air temperatures −10 and −30 °C). These trends indicate that the environment is becoming increasingly favourable for the formation of thunderstorms. However, this potential does not appear to be fully realised, as the frequency of severe and large hail (with diameters of 21 mm or more) has not increased during the period studied.

The cumulative number of historical and recent power system outages substantiates the fact that further studies are necessary for an improved solution to the issue of voltage instability on the grid and the subsequent system collapse. Voltage collapse is a serious reliability issue which inhibits the objective of running a reliable and secure power system network. In this study, a new line stability index (NLSI_1) for predicting voltage collapse is presented.  The new index considers a switching logic which is derived from the difference of voltage angle between the two load buses. The index is deployed for performance analysis using the 28-bus, 330-kV Nigeria National Grid (NNG).  The simulation implemented in MATLAB shows that the index gives the same results as Line stability index (Lmn) and Fast Voltage Stability Index (FVSI) indices. The base case and the contingency scenarios were considered during the simulation. The base case analysis using the NNG values of all the three indices FVSI, Lmn, and NLSI_1 for simulation generates a value less than one for the entire lines which implies that the NNG is stable in this mode. The values of the three indices are almost the same, which confirms the accuracy of the novel index developed. The analysis for the contingency case reveals that the load bus 16 (Gombe) which has the lowest, maximum permissible reactive load of 139.5MVAR is the weakest; also power line 16-19 is identified as the critical line. The result of the simulation confirms that the accuracy was improved by using NLSI_1.

We use the maps elaborated within the Mexican Mangrove Monitoring System (MMMS) project of the National Commission for Knowledge and Use of Biodiversity (CONABIO) to analyze the changes in mangrove area distribution during the last 45 years, within the framework of the coastal regional characteristics in Mexico. We found that 19% of the primary mangrove area identified in 1970/1980 was lost and that 9.4% was gained as secondary mangrove forests due to the colonization of new or disturbed areas. Using location and residence stability indexes, we identified two main change dynamics within three periods (1970/1980–2005, 2005–2010 and 2010–2015): (1) the dominant effect of climate change, especially in northwest Mexico and (2) the dominant effect of anthropic activities, mainly in the Gulf of Mexico. Significant differences in changes in the area of mangroves between regions over time highlight the relevance of more detailed and local studies to understand the processes leading to the degradation or conservation of mangroves.

The present study delineates the relative performance of 3D‐Var and 4D‐Var data assimilation (DA) techniques in the regional NCUM‐R model to simulate three heavy rainfall events (HREs) over the Indian region. Four numerical experiments for three extreme rainfall cases were conducted by assimilating different combinations of observations from surface, aircraft, upper‐air and satellite‐derived Atmospheric Motion Vectors (AMVs) using 3D‐Var and 4D‐Var techniques. These experiments generated initial conditions (ICs) for the NCUM‐R forecast model to simulate HREs. Key atmospheric variables, such as wind speed and direction, vertically integrated moisture transport (VIMT: kg.m−1.s−1), vertical profiles of relative humidity and temperature as well as various stability indices are analysed during the HREs. Forecast verification was performed using statistical skill scores and object‐based methods from the METplus tool, comparing NCUM‐R output against GPM rainfall data. The results demonstrate that the 4D‐Var technique improves simulation accuracy compared to 3D‐Var, particularly when assimilating satellite wind data. Incorporating satellite‐derived AMVs improved the representation of rainfall intensity and spatial patterns, as well as other atmospheric variables. It is found that rainfall for Case‐01, the VIMT was notably high along the eastern coast of India and southwest of BoB, with the 4DVS simulation better capturing moisture transport patterns compared to 3DVS and 3DV. The SWEAT index ranged from 205 to 250 J·kg−1 in the morning, rising to 250–300 J·kg−1 by noon, indicating increasing convective instability. On 18 March 2023 (Day‐1), the K‐index exceeded 30, signalling scattered thunderstorms, consistent with the IMD's reports of isolated to scattered rainfall on 19th and 20th March 2023. Similarly, it is found that satellite wind assimilation improved the statistical skill scores in predicting heavy precipitation in all three cases. Overall, the study suggested that the performance of the NCUM‐R model integrated with the 4D‐Var technique improved the model's forecast skill in the simulation of HREs. This study evaluates the 3D‐Var and 4D‐Var data assimilation using high resolution model (NCUM‐R). The surface, upper‐air and satellite wind data are assimilated to simulate three heavy rainfall cases with different experiments carried out over Indian region. The 3D‐Var technique reduced the event intensity and energy in all forecast days as well as in analysis. But 4D‐Var gives better simulation as compared to 3D‐Var and 3D‐Var with satellite wind data. The 4D‐Var with satellite wind data have better simulated the dynamics and thermodynamics variables of atmosphere, and enhance the predictability of model also.