Evaluation of the Accuracy of Different PV Estimation Models and the Effect of Dust Cleaning: Case Study a 103 MW PV Plant in Jordan

The estimation of PV production has been widely investigated previously, where many empirical models have been proposed to account for wind and soiling effects for specific locations. However, the performance of these models varies among the investigated sites. Hence, it is vital to assess and evaluate the performance of these models and benchmark them against the common PV estimation model that accounts only for the ambient temperature. Therefore, this study aims to evaluate the accuracy and performance of four empirical wind models considering the soiling effect, and compare them to the standard model for a 103 MW PV plant in Jordan. Moreover, the study investigates the effect of cleaning frequency on the annual energy production and the plant’s levelized cost of electricity (LCOE). The results indicate almost identical performance for the adopted models when comparing the actual energy production with R2 and RMSE (root mean square error) ranges of 0.93–0.98 and 0.93–1.56 MWh for both sub-plants, with a slight superiority of the models that incorporate wind effect. Finally, it is recommended in this study to clean the PV panels every two weeks instead of every three months, which would increase annual energy production by 4%, and decrease the LCOE by 5% of the two PV sub-plants.

Structural optimization of concrete plane frames considering the static and dynamic wind effect

abstract: This study has as its main purpose the structural optimization of plane frames in concrete, having as the objective function the minimum total weight of the structure. For this purpose, external actions, considered within the optimization process, are intended to represent accurately all effects observed in a real situation. In such manner, loads are dependent on the cross-section obtained in each optimization step, as well as the static and dynamic effects of the wind are considered for a more realistic representation. The optimization method adopted is the Teaching-Learning Based Optimization (TLBO). Thus, all proper design constraints were considered in accordance with Brazilian standards for concrete structures. From the results obtained in both situations (static and dynamic effects), it is possible to notice the difference regarding external actions, in which higher loads were obtained in higher floors, using the simplified dynamic model proposed in standards. Regarding the analysis of the structure optimization, the weight was higher when the applied forces were the result of the dynamic wind model, in which the larger cross-sections were found at the bottom of the structure. Even though this may be a well-known issue, the present work shows a quantitative study in which both effects are discussed in detail, as well as it features a methodology, based on a novel optimization method and with a straightforward implementation, that could be adapted for the analysis of more complex structures.

A Review on the Building Wind Impact through On-site Monitoring in Haeundae Marine City: 2021 12th Typhoon OMAIS Case Study

Overcrowding of high-rise buildings in urban zones change the airflow pattern in the surrounding areas. This causes building wind, which adversely affects the wind environment. Building wind can generate more serious social damage under extreme weather conditions such as typhoons. In this study, to analyze the wind speed and wind speed ratio quantitatively, we installed five anemometers in Haeundae, where high-rise buildings are dense, and conducted on-site monitoring in the event of typhoon OMAIS to determine the characteristics of wind over skyscraper towers surround the other buildings. At point M-2, where the strongest wind speed was measured, the maximum average wind speed in 1 min was observed to be 28.99 m/s, which was 1.7 times stronger than that at the ocean observatory, of 17.0 m/s, at the same time. Furthermore, when the wind speed at the ocean observatory was 8.2 m/s, a strong wind speed of 24 m/s was blowing at point M-2, and the wind speed ratio compared to that at the ocean observatory was 2.92. It is judged that winds 2–3 times stronger than those at the surrounding areas can be induced under certain conditions due to the building wind effect. To verify the degree of wind speed, we introduced the Beaufort wind scale. The Beaufort numbers of wind speed data for the ocean observatory were mostly distributed from 2 to 6, and the maximum value was 8; however, for the observation point, values from 9 to 11 were observed. Through this study, it was possible to determine the characteristics of the wind environment in the area around high-rise buildings due to the building wind effect.

Methodology for mapping the probability of fire occurrence in the Brazilian cerrado biome based on the danger of fire propagation variables

The area covered by the Brazilian cerrado biome has been greatly reduced in recent years due to the expansion of agricultural land and the increased number of fire outbreaks. The objective of this paper is to propose a methodology based on geospatial analysis and logistic regression analysis (LRA) for mapping the probability of fire occurrence in Brazilian cerrado conservation units. This model was applied in the Serra da Canastra National Park (SCNP) in the Southeast of Brazil. The methodology uses the maps of the following environmental variables, which are related to the danger of fire propagation: wind effect (WIN), terrain convexity (CVX), slope (SLO), drainage density (DRD), altitude (ELV), vegetation index (NDVI), and road density (ROD). The results of the LRA showed that the variables SLO, ELV, NDVI, ROD (p<0.0001), DRD (p=0.0005) and WIN (p=0.0007) contributed significantly to the occurrence of fire outbreaks. The model correctly classified 94.26% of cases. We conclude that this methodology can be used to inform the planning of firefighting actions in the Brazilian cerrado biome.

Sensitivity Analysis of the Levelized Cost of Electricity for a Particle-Based CSP System

This study presents a sensitivity analysis of the LCOE for a particle-based system with the costs of the most current components. New models for the primary heat exchanger, thermal energy storage and tower are presented and used to establish lower and upper bounds for these three components. The rest of component costs such as particle cost, cavity cost and lift cost are set to lower and upper bounds estimating an uncertainty between 25% and 50%. Other relevant parameters related to lift and storage performance are also included in the analysis with the same uncertainty. This study also includes an upgrade to the receiver model by including the wind effect in the efficiency, which was not included in previous publications and may have a big impact in the system design. A parametric analysis shows the optimum values of solar multiple, storage hours, tower height and concentration ratio, and a probabilistic analysis provides a cumulative distribution function for a range of LCOE values. The results show that the LCOE could be below $0.06/kWh with a probability of between 80% and 90%, where the costs of primary heat exchanger, particles and lifts have largest contribution to the variance of the LCOE.

Sea-level prediction for early warning information of coastal inundation in Belawan coastal area using Delft3D model

Coastal inundation has a great impact on the environment, such as damage to infrastructure and pollution of land and water. One of the efforts to prevent coastal inundation is to predict the water level. Delft3D is a hydrodynamic model that's able to simulate the water level. Coastal inundation research using the Delft3D model is still rarely done in Indonesia, especially on the east coast of Sumatra. This research is conducted in Belawan coastal area by simulating the water level that caused the coastal inundation using the Delft3D model. The best bathymetry for the prediction of water level and the magnitude of the wind effect was obtained from the simulation. The final step is to predict the water level in Belawan coastal area. The result of this research shows that the Delft3D model can simulate the water level which causes the coastal inundation in the Belawan coastal area. The correlation of the Delft3D model is 0.9, and the RMSE of GEBCO bathymetry is 0.39 meters and the RMSE of NOAA bathymetry is 0.46 meters. The GEBCO bathymetry is better than NOAA bathymetry in describing the water level in the Belawan coastal area. The wind effect on the water level simulations is not significant because the coefficient of determination is 0.47%. Besides, the Delft3D model with GEBCO bathymetry input can predict the water level which causes the coastal inundation with correlation reaches 0.92 and RMSE is 0.39 meters.

Diurnal Dynamics of the Umov Kinetic Energy Density Vector in the Atmospheric Boundary Layer from Minisodar Measurements

The diurnal hourly dynamics of the kinetic energy flux density vector, called the Umov vector, and the mean and turbulent components of the kinetic energy are estimated from minisodar measurements of wind vector components and their variances in the lower 200-meter layer of the atmosphere. During a 24-hour period of continuous minisodar observations, it was established that the mean kinetic energy density dominated in the surface atmospheric layer at altitudes below ~50 m. At altitudes from 50 to 100 m, the relative contributions of the mean and turbulent wind kinetic energy densities depended on the time of the day and the sounding altitude. At altitudes below 100 m, the contribution of the turbulent kinetic energy component is small, and the ratio of the turbulent to mean wind kinetic energy components was in the range 0.01–10. At altitudes above 100 m, the turbulent kinetic energy density sharply increased, and the ratio reached its maximum equal to 100–1000 at altitudes of 150–200 m. A particular importance of the direction and magnitude of the wind effect, that is, of the direction and magnitude of the Umov vector at different altitudes was established. The diurnal behavior of the Umov vector depended both on the time of the day and the sounding altitude. Three layers were clearly distinguished: a near-surface layer at altitudes of 5–15 m, an intermediate layer at altitudes from 15 m to 150 m, and the layer of enhanced turbulence above. The feasibility is illustrated of detecting times and altitudes of maximal and minimal wing kinetic energy flux densities, that is, time periods and altitude ranges most and least favorable for flights of unmanned aerial vehicles. The proposed novel method of determining the spatiotemporal dynamics of the Umov vector from minisodar measurements can also be used to estimate the effect of wind on high-rise buildings and the energy potential of wind turbines.

Flutter Analysis of Long-Span Suspension Bridges Considering Yaw Wind and Aerostatic Effects

Based on the aerostatic and self-excited aerodynamic force models, a computational approach of three-dimensional (3D) refined flutter analysis for long-span bridges under skew winds is established, in which the structural nonlinearity, aerostatic effect and full-mode coupling effect, etc., are fully considered, and the computational procedure ([Formula: see text] flutter-sw) is developed accordingly. By taking the Runyang Suspension Bridge over the Yangtze river as an example, under the wind attack with initial angles of 0∘ and [Formula: see text] and yaw angles between 0∘ and 25∘, the flutter stability of the bridge in completion under skew winds is analyzed, and the influences of skew wind and aerostatic effect on the flutter stability of suspension bridges are assessed. The results show that the aerostatic effect has a significant influence on the flutter stability of long-span suspension bridge, and it may worsen its flutter stability, with an average decrease of 6.0%. However, it does not change the evolution of flutter stability of suspension bridge with increasing wind yaw angle. The critical flutter wind speed fluctuates with the increase of wind yaw angle, and it reaches the lowest value mostly under the skew wind, with an average reduction of 8.0%. The combined influence of the aerostatic effect and skew wind further reduces the flutter critical wind speed by 11.5% on average, and therefore, the aerostatic effect, skew wind effect and their adverse influences need to be comprehensively considered in the flutter analysis of long-span suspension bridges.