An Optimal Dispatch Framework of Electric and Heating Networks Based on Controllable Electric and Thermostatically Controlled Loads

With the increasing capacity of wind power generators (WTGs), the volatility of wind power could significantly challenge the stability and economy of electric and heating networks. To tackle this challenge, this paper proposes an optimal dispatch framework based on controllable load (including controllable electric load and controllable thermostatically load) to reduce wind power curtailment. A forecasting model is developed for the controllable load, which comprehensively considers autocorrelation, weather factor, and consumers’ behavior characteristics. With adjusting controllable load, an optimal dispatch model of power system is then established and resolved by Sequential Least Squares Programming (SLSQP) method. Our method is verified through numerous simulations. The results show that, compared with the state-of-the-art techniques of support vector machine and recurrent neural networks, the root mean square error with the proposed long short-term memory can be reduced by 0.069 and 0.044, respectively. Compared with conventional method, the peak wind power curtailment with dispatching controllable load is reduced by nearly 10% and 5% in two cases, respectively.

A Link between Atmospheric Pressure and Fertility of Drosophila Laboratory Strains

Standardization of conditions under which insects are kept is of great importance when studying their physiology and researchers do their best to maintain it. Nevertheless, sometimes an obvious side effect of some unaccounted factor affecting insects’ reproduction can be revealed even under thoroughly controlled laboratory conditions. We faced such a phenomenon when studying the fertility level in two wild type Drosophila melanogaster strains. For fertility analysis, 50 newly emerged females and 50 males of each strain under study were transferred to fresh medium daily within 10 days. We found out that fertility of both strains was stable on days 2–10 after the oviposition onset in one experiment, while in another one it was significantly decreased during days 5–10. When compared to publicly available meteorological data, these changes in the fertility level demonstrated a strong association with one weather factor: barometric pressure. Thus, we conclude that changes in atmospheric pressure can be considered a factor affecting insects reproduction and discuss a possible mechanism of their influence on fertility.

March, September and December months with the greatest influence of atmospheric pressure on blood pressure in patients with hypertension

Objectives For a long time, science has searched for the relationship between weather and human health. Atmospheric pressure is the most objective weather factor because, regardless of whether the objects are outdoors or indoors, it affects all objects in the same way. In cardiology, we often look for factors that worsen blood pressure control. Could atmospheric pressure be one of them? The main objective of our research was to assess the relationship between atmospheric pressure and blood pressure in patients with treated hypertension in different months in the moderate climate of Central Poland. Material and methods The study group consisted of 4191 patients with arterial hypertension, divided into 2 near equal groups due to a lower or higher average value of atmospheric pressure when blood pressure was recorded. Blood pressure was monitored by a means of 24-h ABPM. Atmospheric pressure was recorded with the frequency of 1 measurement per minute using a meteorological station. The observations were conducted in the years 2009–2019. Comparisons between blood pressure values in the 2 groups were performed using the Mann-Whitney U test. Results We observed a significant difference in blood pressure recorded during the periods of lower and higher atmospheric pressure: for systolic blood pressure during the days of September (125.01±14.99 vs 120.14±12.83, p<0.001) and December (124.22±15.45 vs 127.50±14.35, p<0.05), for diastolic pressure during the days of March (72.24±10.92 vs 69.81±9.13, p<0.02) and for diastolic pressure during the nights of March (61.53±8.96 vs 59.58±9.17, p<0.04). Conclusions A significant inverse relationship between atmospheric pressure and blood pressure was observed; during March days and nights for diastolic blood pressure and during September and December days for systolic blood pressure. This finding may be important for the understanding of why during some months the pharmacological control of blood pressure is poor, and of the consequences of this fact. FUNDunding Acknowledgement Type of funding sources: Public hospital(s). Main funding source(s): own resources

Comparison of the Spatial Wind Erosion Patterns of Erosion Risk Mapping and Quantitative Modeling in Eastern Austria

Various large-scale risk maps show that the eastern part of Austria, in particular the Pannonian Basin, is one of the regions in Europe most vulnerable to wind erosion. However, comprehensive assessments of the severity and the extent of wind erosion risk are still lacking for this region. This study aimed to prove the results of large-scale maps by developing high-resolution maps of wind erosion risk for the target area. For this, we applied a qualitative soil erosion assessment (DIN 19706) with lower data requirements and a more data-demanding revised wind erosion equation (RWEQ) within a GIS application to evaluate the process of assessing wind erosion risk. Both models defined similar risk areas, although the assignment of severity classes differed. Most agricultural fields in the study area were classified as not at risk to wind erosion (DIN 19706), whereas the mean annual soil loss rate modeled by RWEQ was 3.7 t ha−1 yr−1. August was the month with the highest modeled soil loss (average of 0.49 t ha−1 month−1), due to a low percentage of vegetation cover and a relatively high weather factor combining wind speed and soil moisture effects. Based on the results, DIN 19706 is suitable for a general classification of wind erosion-prone areas, while RWEQ can derive additional information such as seasonal distribution and soil loss rates besides the spatial extents of wind erosion.

Effects of weather conditions on concrete work task productivity – a questionnaire survey

Purpose This paper aims to study the effects of different weather conditions on typical concrete work tasks’ productivity. Weather is one important factor that has a negative impact on construction productivity. Knowledge about how weather affects construction works is therefore important for the construction industry, e.g. during planning and execution of construction projects. Design/methodology/approach A questionnaire survey method is used involving means to perform pairwise comparisons of different weather factors according to the analytical hierarchical process (AHP). The survey also contains means to enable assessment of the loss in productivity for typical work tasks exposed to different weather types. The survey targets practitioners involved in Swedish concrete construction projects, and the results are compared with previous research findings. Findings The survey covers responses from 232 practitioners with long experience of concrete construction. The pairwise comparisons reveal that practitioners rank precipitation as the most important followed by wind and temperature. The loss in productivity varies significantly (from 0 to 100%) depending on the type of work and the type of weather factor considered. The results partly confirm findings reported in previous research but also reveal a more complex relationship between weather and productivity indicating several underlying influencing factors such as type of work, type of weather (e.g. rain or snow) and the intensity of each weather factor. Originality/value This paper presents new data about how 232 practitioners assess the effects of weather on construction productivity involving novel means to perform objective rankings such as the AHP methodology.

A Study on Characteristics and Comparison of Evaporation Estimation Methods in Bandung

This study aims to understand the characteristic of evaporation and to evaluate the evaporation estimation methods to be employed in Bandung by using observation data at three different land cover characteristics sites, namely, densely vegetated area (Baleendah), densely built-up area (Ujung Berung), and mix of buildings and vegetation area (ITB). Observation data used are hourly evaporation, vapour pressure deficit, temperature, relative humidity, wind speed, and radiation. The analysis was done mostly by using statistical methods such as regression analysis and error comparison. The result shows the dominant weather factor affecting the evaporation in ITB and Ujung Berung is vapour pressure deficit, and in Baleendah is solar radiation. The methods of evaporation estimations used in this study are Trabert, Schendel, Turc, and CIMIS-Penman methods. The result shows that the original constant values of those methods are significantly correlated. However, the Schendel is found the most overestimated, and the second is Turc. The best estimated evaporation in Baleendah, ITB, and Ujung Berung is calculated using CIMIS-Penman with one hour lag of radiation, Trabert, and Calibrated Schendel, respectively. The improvement of constant value was applied to Schendel and the result is better than the original constants.

A Study on Characteristics and Comparison of Evaporation Estimation Methods in Bandung

This study aims to understand the characteristic of evaporation and to evaluate the evaporation estimation methods to be employed in Bandung by using observation data at three different land cover characteristics sites, namely, densely vegetated area (Baleendah), densely built-up area (Ujung Berung), and mix of buildings and vegetation area (ITB). Observation data used are hourly evaporation, vapour pressure deficit, temperature, relative humidity, wind speed, and radiation. The analysis was done mostly by using statistical methods such as regression analysis and error comparison. The result shows the dominant weather factor affecting the evaporation in ITB and Ujung Berung is vapour pressure deficit, and in Baleendah is solar radiation. The methods of evaporation estimations used in this study are Trabert, Schendel, Turc, and CIMIS-Penman methods. The result shows that the original constant values of those methods are significantly correlated. However, the Schendel is found the most overestimated, and the second is Turc. The best estimated evaporation in Baleendah, ITB, and Ujung Berung is calculated using CIMIS-Penman with one hour lag of radiation, Trabert, and Calibrated Schendel, respectively. The improvement of constant value was applied to Schendel and the result is better than the original constants.

Seasonal variation and its impacts in rice-growing regions of the Mekong Delta

Purpose In recent years, agricultural activities in the Mekong Delta have frequently faced the potential risks of drought, saline intrusion and unusually heavy rainfall because of climate change, leading to a decline in crop yield. Therefore, this study aimed to establish rice planting seasons in An Giang, an upper-located province in the Mekong Delta. Design/methodology/approach The impacts of seasonal variation on the key rice seasons were simulated using the Food and Agriculture Organization-crop model for the OM6976 rice variety grown in the study area. For the simulation, the model combined crop, soil, weather and crop management data. Findings The results show that seasonal variation because of changes in weather factors leads to alternation in crop yields across the study area. Specifically, the spring and summer rice planting seasons are advanced by one to two weeks compared with the baseline, and crop yield increased by 5.9% and 4.2%, respectively. Additionally, planting for the autumn–winter rice season on 3 August increased crop yield by up to 8.1%. Originality/value In general, rice planting seasons that account for weather factor changes effectively reduce production costs and optimise production.

Prediction and Analysis of Train Passenger Load Factor of High-Speed Railway Based on LightGBM Algorithm

In order to improve the prediction accuracy of train passenger load factor of high-speed railway and meet the demand of different levels of passenger load factor prediction and analysis, the influence factor of the train passenger load factor is analyzed in depth. Taking into account the weather factor, train attribute, and passenger flow time sequence, this paper proposed a forecasting method of train passenger load factor of high-speed railway based on LightGBM algorithm of machine learning. Considering the difference of the influence factor of the passenger load factor of a single train and group trains, a single train passenger load factor prediction model based on the weather factor and passenger flow time sequence and a group of trains’ passenger load factor prediction model based on the weather factor, the train attribute, and passenger flow time sequence factor were constructed, respectively. Taking the train passenger load factor data of high-speed railway in a certain area as an example, the feasibility and effectiveness of the proposed method were verified and compared. It is verified that LightGBM algorithm of machine learning proposed in this paper has higher prediction accuracy than the traditional models, and its scientific and accurate prediction can provide an important reference for the calculation of passenger ticket revenue, operation benefit analysis, etc.

Changes in wind erosion climatic erosivity in northern China from 1981-2016: a comparison of two climate/weather factors of wind erosion models

Wind erosion is largely determined by wind erosion climatic erosivity. In this study, we examined changes in wind erosion climatic erosivity during 4 seasons across northern China from 1981-2016 using 2 models: the wind erosion climatic erosivity of the Wind Erosion Equation (WEQ) model and the weather factor from the Revised Wind Erosion Equation (RWEQ) model. Results showed that wind erosion climatic erosivity derived from the 2 models was highest in spring and lowest in winter with high values over the Kumtag Desert, the Qaidam Basin, the boundary between Mongolia and China, and the Hulunbuir Sandy Land. In spring and summer, wind erosion climatic erosivity showed decreasing trends in whole of northern China from 1981-2016, whereas there was an increasing trend in wind erosion climatic erosivity over the Gobi Desert from 1992-2011. For the weather factor of the RWEQ model, the difference between northern Northwest China and the Gobi Desert and eastern-northern China was much larger than that of the wind erosion climatic erosivity of the WEQ model. In addition, in contrast to a decreasing trend in the weather factor of the RWEQ model over southern Northwest China during spring and summer from 1981-2016, the wind erosion climatic erosivity of the WEQ model showed a decreasing trend for 1981-1992 and an increasing trend for 1992-2011 over southern Northwest China. According to a comparison between dust emission and wind erosion climatic erosivity, the 2 models have the ability to project changes in future wind erosion in northern China.