Typical Weather Conditions Research Articles

Exploring and Quantifying River Thermal Response to Heatwaves

Most of the existing literature on river water temperature focuseds on river thermal sensitivity to long-term trends of climate variables, whereas how river water temperature responds to extreme weather events, such as heatwaves, still requires in-depth analysis. Research in this direction is particularly relevant in that heatwaves are expected to increase in intensity, frequency, and duration in the coming decades, with likely consequences on river thermal regimes and ecology. In this study we analyzed the long-term temperature and streamflow series of 19 Swiss rivers with different hydrological regime (regulated, low-land, and snow-fed), and characterized how concurrent changes in air temperature and streamflow concurred to affect their thermal dynamics. We focused on quantifying the thermal response to the three most significant heatwave events that occurred in Central Europe since 1950 (July–August 2003, July 2006, and July 2015). We found that the thermal response of the analyzed rivers contrasted strongly depending on the river hydrological regime, confirming the behavior observed under typical weather conditions. Low-land rivers were extremely sensitive to heatwaves. In sharp contrast, high-altitude snow-fed rivers and regulated rivers receiving cold water from higher altitude hydropower reservoirs or diversions showed a damped thermal response. The results presented in this study suggest that water resource managers should be aware of the multiple consequences of heatwave events on river water temperature and incorporate expected thermal responses in adaptive management policy. In this respect, additional efforts and dedicated studies are required to deepen our knowledge on how extreme heatwave events can affect river ecosystems.

Study on Performance of Solar Water Heating System using TRNSYS Software

Based on the basic principles of thermodynamics and heat and mass transfer, this paper establishes the simulation model of solar hot water system to investigate its performance. The annual thermal performance of solar hot water system is simulated with TRNSYS software as simulation platform. At the same time, under typical weather conditions, the variation of water temperature in the storage tank, the temperature of the inlet and outlet of the collector, the total solar radiation and the change of the heat collection efficiency are analyzed. The establishment of the simulation model of solar hot water system is of guiding significance for setting operating parameters of components and improving the comprehensive performance of solar hot water system. The present study provides theoretical guidance for the operation of the solar hot water system,

Experimental Design of a Prescribed Burn Instrumentation

Observational data collected during experiments, such as the planned Fire and Smoke Model Evaluation Experiment (FASMEE), are critical for evaluating and transitioning coupled fire-atmosphere models like WRF-SFIRE and WRF-SFIRE-CHEM into operational use. Historical meteorological data, representing typical weather conditions for the anticipated burn locations and times, have been processed to initialize and run a set of simulations representing the planned experimental burns. Based on an analysis of these numerical simulations, this paper provides recommendations on the experimental setup such as size and duration of the burns, and optimal sensor placement. New techniques are developed to initialize coupled fire-atmosphere simulations with weather conditions typical of the planned burn locations and times. The variation and sensitivity analysis of the simulation design to model parameters performed by repeated Latin Hypercube Sampling is used to assess the locations of the sensors. The simulations provide the locations for the measurements that maximize the expected variation of the sensor outputs with varying the model parameters.

Rainfall effects on the erodibility of sediment and microphytobenthos in the intertidal flat

The frequent rainfall during the low tide would erode and transport the surface sediment and microphytobenthos (MPB) in the intertidal flat. In order to quantify the rainfall effects on the erodibility of sediment and MPB at the salt marsh and mixed flat, a series of erosion experiments have been conducted with a Gust erosion microcosm system. Surface sediments were sampled for analyzing algal biomass (Chl-a) and primary production (PP) during three typical weather (without rain, rain, and post-rain) conditions. The results of erosion experiment, in both salt marsh and mixed flat, showed that the sediment erodibility under rain condition was higher than that under without rain condition, with increased total eroded mass by 37–86%. It indicated that the rainfall effects caused to significantly disturb the surface sediment. After the rainfall events, the removal of highly-erodible sediments resulted in the reduction in eroded mass. The MPB erodibility under rain condition was lower than that under without rain condition, with decreased total eroded Chl-a by 29%. At the mixed flat, the rainfall effects caused to significantly decrease biological activities of MPB (biomass and PP) associated with surface sediment. The surface Chl-a concentration under post-rain condition decreased by 73%, compared to that under rain condition. At the salt marsh, in contrast, the rainfall effects were barely shown when the biological activities of MPB were rather stable. This implied that the eroded MPB induced by rainfall was retained within the marsh system due to vegetation canopy.

An Optimization Method for Local Consumption of Photovoltaic Power in a Facility Agriculture Micro Energy Network

In order to solve the problem of optimal dispatching of photovoltaic power for local consumption to the greatest degree in a photovoltaic greenhouse, this paper proposes a multiform energy optimal dispatching model and a solution algorithm. First, an input-output power model is established for energy storages which are reservoir, biogas digester, and block wall with phase-change thermal storage. Based on it, multiform energy storages play a bridging role of energy transfer in optimal energy dispatching. Subsequently, an optimal energy dispatching model is proposed with the objective of minimizing the sum of the squares of the difference between the loads and the photovoltaic generation in dispatching periods. Control variables are working state quantities of the time-shiftable loads and input-output state quantities of energy storages in dispatching periods. Finally, a genetic algorithm with matrix binary coding is used to solve the energy optimal dispatching model. Simulation results of a practical photovoltaic greenhouse facility agricultural micro energy network system in three typical weather conditions showed that the method could fully utilize the energy transfer function of the multiform energy storage and the time-shiftable characteristics of the agricultural load to achieve the maximum effect of increasing the local consumption of the photovoltaic power.

Experimental performance analysis of a direct-expansion solar-assisted heat pump water heater with R134a in summer

A direct-expansion solar-assisted heat pump (DX-SAHP) system for domestic hot water supply was built and tested, which mainly consisted of a bare flat-plate collector/evaporator with a surface area of 2.1 m2, a variable-frequency rotary-type hermetic compressor, a hot water tank with the volume of 0.2 m3 surrounded by a micro-channel condenser, and an electronic expansion valve. A series of experiments were carried out to test the system performance under typical summer weather conditions in Qingdao, China. The effects of various parameters, including solar radiation intensity of 258–634 W·m−2, ambient temperature of 28–34 °C, compressor speed of 2500–6000 rpm and final water temperature of 50–60.3 °C, on the system performance are analyzed. Experimental results show that the system coefficient of performance(COP) could be enhanced with the increase of the solar radiation intensity or the ambient temperature, and with the decrease of the compressor speed or the final water temperature.

Defining Photovoltaic Mission Profile for the Pre-Design of Static Converters

A methodology is presented for accurately defining the mission profile and relevant operating conditions of photovoltaic systems. The proposed method works as a tool for obtaining useful information for designing high-efficiency and reliable photovoltaic power converters. This methodology enables modern design techniques of pre-sizing and optimizing power converters according to its mission profile and relevant operating conditions. Two cities in different climate zones were analyzed and compared, wherein a large dataset of solar irradiance and ambient temperature from each location was used. Meteorological measurements from ten years were used to obtain an average typical year of weather conditions for both cities. In-plane irradiance on photovoltaic panels for an annual operation was estimated. A mathematical model was used to analyze solar incidence on modules in fix mounting and with the use of mechanical trackers. A photovoltaic system's operating current, voltage, and temperature levels were estimated in relationship to in-plane irradiance and ambient temperature. Energy yield throughout one year was obtained based on the average typical weather condition. An analysis is presented regarding how climate affects photovoltaic operation and what are the most relevant current and voltage levels for each mission profile; these levels are the starting point for an accurate converter design. Validation results of photovoltaic modeling are presented for a fourteen-panel system of 3.29 kW installed capacity. The impact of using mechanical trackers on power processing is also presented. A discussion is made on the importance of previous knowledge of an accurate photovoltaic mission profile on the design of power converters and on maximizing energy processing.

Evaluation on the Performance of Photovoltaic–Thermal Hybrid System Using CO2 as a Working Fluid

In this study, the CO2-based photovoltaic–thermal hybrid system has been investigated with an objective to increase the power generation efficiency in photovoltaic solar panel and to improve the performance of supercritical CO2 solar Rankine cycle system (SRCS). From a previous study, an improvement of 2% of power generation efficiency was confirmed via experimental investigation. In this study, the temperature distribution on the CO2-based photovoltaic–thermal hybrid system has been numerically and experimentally investigated and confirmed with referenced experimental results. Particularly, in this study, the one-dimensional (1D) calculation of CO2 flow in the cooling tube and three-dimensional (3D) calculation of temperature distribution on the surface of the photovoltaic solar panel are conducted. The typical summer and winter weather conditions are used as the calculation references to investigate the effect of temperature distribution of the photovoltaic solar panel. The results show that the trend of temperature distribution from calculation was confirmed with the experimental data both in summer and winter conditions. Furthermore, in summer condition, the CO2 temperature was increased to a maximum of 28 °C.

Experimental Study on the Effect of Solar Radiation on Heat Transfer Performance of Flat panel Solar Water Heater

The development status of flat panel solar water heater and the composition of water heater are described. The solar radiation in three typical weather conditions of sunny, cloudy and rainy days is studied. The hot water temperature, heat and heat collector efficiency are studied. The results show that the influence of the weather on the solar irradiance is large, and the irradiance has a great influence on the water temperature.

Analysis and assessment of an off-grid services building through the usage of a DC photovoltaic microgrid

The main motivation for carrying out this research is to collaborate in developing new less aggressive energy consumption mechanisms to take care of the environment and reduce greenhouse emissions. This paper is focused on the development of a DC photovoltaic building in off-grid operation mode. The modelized PV system satisfies the energy demand of a large residential building using only DC electricity to keep it powered on without any shortage or cut-off. A comprehensive study has been carried out using real consumption data, local solar irradiance, and local temperature measures, all gathered in the last 30 years, to create five different scenarios. These scenarios test the installation under typical weather and usage pattern conditions as well as under the lowest irradiance levels, all the while maintaining: the comfort in all areas without any energy cut-offs and keeping the output rated voltage inside the tolerance values (the voltage fluctuation average represented a 9.70%). Finally, the mean performance of the system is higher than 75% while the losses due to the low voltage used are three times lower than the transmission losses of the AC network.

A New Security Warning Model about Power Grid

In recent years, lots of power grid blackouts at home and abroad indicates that the meteorological disasters caused by external meteorological conditions has gradually rose to major contradiction of power grid security. Basing on release information of meteorology, lightning monitoring information and power transmission equipment monitoring information, it established a weather warning model about power grid security, combined with real-time security analysis. Firstly, mathematical models of various types of weather conditions and weather risk assessment model grid were built, then actual operating conditions of a certain regional power grid and model results were compared, the comparison result prove the accuracy of the warning model, and provides a strong recommendation for decision-making.

Impact of Reference Years on the Outcome of Multi-Objective Optimization for Building Energy Refurbishment

There are several methods in the literature for the definition of weather data for building energy simulation and the most popular ones, such as typical meteorological years and European test reference years, are based on Finkelstein–Schafer statistics. However, even starting from the same multi-year weather data series, the developed reference years can present different levels of representativeness, which can affect the simulation outcome. In this work, we investigated to which extent the uncertainty in the determination of typical weather conditions can affect the results of building energy refurbishment when cost-optimal approach is implemented for the selection of energy efficiency measures by means of the NSGA-II genetic algorithm coupled with TRNSYS simulations. Six different reference years were determined for two north Italy climates, Trento and Monza, respectively in the Alpine and in the continental temperate regions. Four types of energy efficiency measures, related to both building envelope and HVAC system, were applied to six existing building typologies. Results showed how the choice of reference year can alter the shape of the Pareto fronts, the number of solutions included and the selection among the alternatives of the energy efficiency measures, for the entire front and, in particular, for energy and economic optima.

Performance of different photovoltaic-thermal (PVT) configurations integrated on prototype test cells: An experimental approach

Analytical model for temperature dependent electrical and thermal efficiency for four different photovoltaic-thermal configurations integrated on identical prototype test cells namely; Case 1: glass to glass photovoltaic with duct integrated on a test cell, Case 2: glass to glass photovoltaic without duct integrated on a test cell, Case 3: glass to tedlar photovoltaic with duct integrated on a test cell and, Case 4: glass to tedlar photovoltaic without duct integrated on a test cell is developed in absence of ambient air exchange and experimentally validated in New Delhi’s winter and summer seasonal conditions. The glass to glass photovoltaic module gives better performance in both electrical as well as thermal aspects, and gives daily average ηm 11.91% and 11.96% in summer whereas in winter, it gives 12.65% and 12.70% for case 1 and 2 respectively. Similarly, daily average ηith was 32.77% and 25.44% for case 1 and 2 respectively in winter. Ducted cases 1 and 3 have higher ηm and ηith due to the large heat dissipation capacity. Constant temperature mode operations inside test cells were attained, and we also discuss the effect of varying mass flow rate on electrical efficiency for ducted cases. Further, the yearly-round electrical, thermal, overall thermal, and overall exergy efficiencies for case 1 were found respectively 10.41%, 34.35%, 61.52% and 13.72% under typical New Delhi weather condition. The characteristic equations for all four cases were also been developed.

Pengaruh Cuaca Terhadap Perilaku Pengendara Sepeda Motor di Daerah Istimewa Yogyakarta

Indonesia as a developing country has a considerable growth in motor vehicles. Unlike other countries, the growth of motor vehicles is quite large motorcycle. In the last few years, the study of the relationship between weather and transportation is mostly done in the region or country with four seasons different in climate condition or in developed countries with good public transport conditions. It is still few to do research in developing countries, with poor public transport conditions and other problems. Yogyakarta is a city with tropical climate that it only has two types of weather conditions, namely dry and rainy seasons, which the both will affect motorcyclists in Yogyakarta becoming the majority. In this study, the author used a qualitative and quantitative approach to find the impact of weather changes on motorcyclists' travel behavior. From the results of the study, it was found that the number of motor users was reduced by more than 30% when the weather changed. Broadly speaking, there are three behaviors of motorcyclists when the weather changes namely, wait until the weather back to normal, cancel the trip and continue the journey however in the conditions due to some reasons.

Development of robust meteorological year weather data

Abstract Building energy performance simulations are limited to typical meteorological weather conditions available in simulation software. Such simulations are insufficient for analysing energy performance sensitivity to a range of probable weather conditions. This research presents a method for developing robust meteorological weather data that can be used for energy performance sensitivity analysis without the need to access historical weather data. The method decomposes dry bulb temperature (DBT) and global horizontal solar radiation (H) into deterministic and stochastic components. For the typical weather data of the City of Adelaide, the deterministic component for each of DBT and H consists of a single frequency Fourier series. The stochastic components consist of 1-lag and 2-lags autoregressive models for DBT and H respectively. The stochastic components also include randomly selected values from the residuals of the autoregressive models. Based on this method, the coldest and hottest weather conditions were selected to simulate the energy performance of a single space. The results revealed 39% more cooling and 15% less heating in the hottest year, and 14% more heating and 64% less cooling in the coldest year. The results indicate that simulations based on typical weather conditions only are insufficient for assessing buildings' energy performance.

Performance analysis of static ice refrigeration air conditioning system driven by household distributed photovoltaic energy system

The static ice refrigeration air conditioning system (SIRACS) driven by household distributed photovoltaic energy system (HDPES) was proposed and the energy conversion as well as the transmission performance were investigated by combining the theoretical calculation with experimental test. Results revealed that the system could be operated stably and continuously during three typical weather conditions (sunny, cloudy and light rainy) with an average photoelectric conversion efficiency of 11.76% and an average ice production of 52.56kg. This system could continuously and stably serve user for 4h during night. The models were verified to be reasonable and the simulated results were reliable. Meanwhile, the system average energy efficiency η was 7.65%. The performance analysis results showed that the ice making efficiency of the refrigerator was 50.19%, which was mainly responsible for the low energy efficiency. Therefore, to improve the refrigeration performance some optimization strategies were recommended and proposed in this paper.

Investigation of Different Configurations of a Ventilated Window to Optimize Both Energy Efficiency and Thermal Comfort

The study in this article investigates 15 ventilated window typologies with different pane configurations and glazing types in climates of four European countries (United Kingdom, Denmark, France and Germany) in order to identify the optimum typology with regard to their energy balance and impact on thermal comfort. Hourly simulations of the heat balances of the windows are conducted on four days representing different typical weather conditions according to the method described in EN ISO 13790. U and g values used in the calculation method are calculated in European software tool (WIS) for the calculation of the thermal and solar properties of commercial and innovative window systems. Additionally, comfort performance is evaluated by inlet air temperature and internal surface temperature of the windows calculated by WIS software.The results of the study show the energy and comfort performance of different ventilated window typologies and provide optimally ventilated window typologies for climates of these four European climates. The typologies with solar control or Low-emissivity (Low-e) coatings and typologies with double glazing on the outside have better performance in terms of either minimizing the energy consumption or optimizing the thermal comfort. The provided optimal window typologies can be used in residential and commercial buildings for both new constructions and renovations.

Thermal comfort and energy performance of public rental housing under typical and near-extreme weather conditions in Hong Kong

Building performance evaluation is crucial for sustainable urban developments. In high-density cities, occupants suffer from poor living conditions due to building overheating, especially during increasingly frequent near-extreme summer conditions caused by climate change. To represent this situation, the summer reference year weather data was employed for building simulations using DesignBuilder. This study aims to evaluate the thermal comfort and energy consumption of four typical public rental housing (PRH) building types in Hong Kong. For free-running flats, results show generally higher air temperatures in the oldest PRH type (Slab) with a compact linear building form and the most sensitive response to outdoor temperature changes for another older PRH type (Trident) with a Y-shaped design, possibly owing to its high wall conductivity. Occupants in all building types experience a ∼10% increase in the proportion of discomfort hours when compared to results for typical summer conditions, but overheating is the most severe in Slab type PRH. Following an initial assessment of the cooling energy usage, a simple sensitivity test was conducted to explore the potential energy savings by various passive design strategies, including shading and reducing the exposed cooled space. A cross-shaped building form also appears to be more energy efficient. These findings, complemented by further parametric analyses, may prove useful when designing buildings for climate change.

Haze Removal Using Radial Basis Function Networks for Visibility Restoration Applications.

Restoration of visibility in hazy images is the first relevant step of information analysis in many outdoor computer vision applications. To this aim, the restored image must feature clear visibility with sufficient brightness and visible edges, while avoiding the production of noticeable artifacts. In this paper, we propose a haze removal approach based on the radial basis function (RBF) through artificial neural networks dedicated to effectively removing haze formation while retaining not only the visible edges but also the brightness of restored images. Unlike traditional haze-removal methods that consist of single atmospheric veils, the multiatmospheric veil is generated and then dynamically learned by the neurons of the proposed RBF networks according to the scene complexity. Through this process, more visible edges are retained in the restored images. Subsequently, the activation function during the testing process is employed to represent the brightness of the restored image. We compare the proposed method with the other state-of-the-art haze-removal methods and report experimental results in terms of qualitative and quantitative evaluations for benchmark color images captured in typical hazy weather conditions. The experimental results demonstrate that the proposed method is able to produce brighter and more vivid haze-free images with more visible edges than can the other state-of-the-art methods.

Investigation on capacity matching in a heat pump and hollow fiber membrane-based two-stage liquid desiccant hybrid air dehumidification system

The heat pump and hollow fiber membrane-based two-stage liquid desiccant hybrid air dehumidification system is promising recently because solution droplets can be prevented from crossing over into the process air. The quasi-isothermal processes are realized by two-stage dehumidification processes and the system performance is improved. In this study, a novel capacity matching index (CMI) is introduced to evaluate the energy capacity matching of the system through modeling study. It is found that CMI is usually lower than 1 under the typical hot and humid weather condition like South China and the demand and supply of energy in the system is mismatching. As inlet air temperature rises, the dehumidification rates, CMI, EER and COP all decrease. But CMI is almost constant with different inlet air humidity. The influence of air inlet temperature to dehumidifiers and regenerators on the system performance is also investigated. The higher the inlet temperature of dehumidifiers is, the larger the CMI, EER and COP are. The dehumidification rates and CMI both grow with an increase in the inlet temperature of regenerators. It is beneficial for energy balance of the system and high moisture loads, but the side effect is that the EER and COP both decrease.