scholarly journals Novel Optimal Perennial Calendar Systems vs Gregorian Calendar and Their Impact on the Energy Demand and the Environment

2021 ◽  
Vol 1 (3) ◽  
Author(s):  
Claude Ziad El-Bayeh ◽  
Mohamed Zellagui ◽  
Brahim Brahmi
Keyword(s):  
Climate Change ◽  
Optimization Model ◽  
Energy Demand ◽  
Optimization Method ◽  
Gregorian Calendar ◽  
Mathematical Formula

Have you ever missed an event because you were confused about days and dates? Do you remember the date of any specific day without looking at the calendar? Is the current Gregorian Calendar efficient enough for usage, and does it facilitate our life or make it more complicated? Have you ever thought about a simpler way to calculate days and dates in a year without using a calendar? All these questions are answered in this paper, in which authors propose two contributions, (a) a new mathematical formula that calculates the number of days in any month in the Gregorian calendar for any year, including the leap years, (b) an original optimization method that creates optimal perennial calendars. Results show that there is more than one way to create a perennial calendar using the proposed optimization model, in which the number of days in each month does not change, neither the dates. Hence, all months have the same sequence of days and dates. In other meaning, Monday becomes the first day of every month, and Sunday becomes the last day. Consequently, the calendars become much easier to memorize, and it becomes simpler to predict the days and dates in any year. In addition, the proposed optimal perennial calendar system reduces the energy demand and pollution worldwide, in which it has less impact on the environment and climate change compared to the Gregorian calendar. This is due to the fact that less printed-out calendars are produced, and less time is spent on the digital calendars to check the dates and days.

scholarly journals Overheating Risk and Energy Demand of Nordic Old and New Apartment Buildings during Average and Extreme Weather Conditions under a Changing Climate

2021 ◽  
Vol 11 (9) ◽  
pp. 3972
Author(s):  
Azin Velashjerdi Farahani ◽  
Juha Jokisalo ◽  
Natalia Korhonen ◽  
Kirsti Jylhä ◽  
Kimmo Ruosteenoja ◽  
...  
Keyword(s):  
Climate Change ◽  
Energy Demand ◽  
Energy Use ◽  
Residential Buildings ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Living Room ◽  
Extra Energy ◽  
Cooling Unit ◽  
Indoor Conditions

The global average air temperature is increasing as a manifestation of climate change and more intense and frequent heatwaves are expected to be associated with this rise worldwide, including northern Europe. Summertime indoor conditions in residential buildings and the health of occupants are influenced by climate change, particularly if no mechanical cooling is used. The energy use of buildings contributes to climate change through greenhouse gas emissions. It is, therefore, necessary to analyze the effects of climate change on the overheating risk and energy demand of residential buildings and to assess the efficiency of various measures to alleviate the overheating. In this study, simulations of dynamic energy and indoor conditions in a new and an old apartment building are performed using two climate scenarios for southern Finland, one for average and the other for extreme weather conditions in 2050. The evaluated measures against overheating included orientations, blinds, site shading, window properties, openable windows, the split cooling unit, and the ventilation cooling and ventilation boost. In both buildings, the overheating risk is high in the current and projected future average climate and, in particular, during exceptionally hot summers. The indoor conditions are occasionally even injurious for the health of occupants. The openable windows and ventilation cooling with ventilation boost were effective in improving the indoor conditions, during both current and future average and extreme weather conditions. However, the split cooling unit installed in the living room was the only studied solution able to completely prevent overheating in all the spaces with a fairly small amount of extra energy usage.

scholarly journals Efficient Design of Energy Disaggregation Model with BERT-NILM Trained by AdaX Optimization Method for Smart Grid

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4649
Author(s):  
İsmail Hakkı ÇAVDAR ◽  
Vahit FERYAD
Keyword(s):  
Smart Grids ◽  
Energy Demand ◽  
Optimization Technique ◽  
Cost Effective ◽  
Optimization Method ◽  
Long Term Memory ◽  
Successful Implementation ◽  
Efficient Design ◽  
Energy Disaggregation ◽  
Load Monitoring

One of the basic conditions for the successful implementation of energy demand-side management (EDM) in smart grids is the monitoring of different loads with an electrical load monitoring system. Energy and sustainability concerns present a multitude of issues that can be addressed using approaches of data mining and machine learning. However, resolving such problems due to the lack of publicly available datasets is cumbersome. In this study, we first designed an efficient energy disaggregation (ED) model and evaluated it on the basis of publicly available benchmark data from the Residential Energy Disaggregation Dataset (REDD), and then we aimed to advance ED research in smart grids using the Turkey Electrical Appliances Dataset (TEAD) containing household electricity usage data. In addition, the TEAD was evaluated using the proposed ED model tested with benchmark REDD data. The Internet of things (IoT) architecture with sensors and Node-Red software installations were established to collect data in the research. In the context of smart metering, a nonintrusive load monitoring (NILM) model was designed to classify household appliances according to TEAD data. A highly accurate supervised ED is introduced, which was designed to raise awareness to customers and generate feedback by demand without the need for smart sensors. It is also cost-effective, maintainable, and easy to install, it does not require much space, and it can be trained to monitor multiple devices. We propose an efficient BERT-NILM tuned by new adaptive gradient descent with exponential long-term memory (Adax), using a deep learning (DL) architecture based on bidirectional encoder representations from transformers (BERT). In this paper, an improved training function was designed specifically for tuning of NILM neural networks. We adapted the Adax optimization technique to the ED field and learned the sequence-to-sequence patterns. With the updated training function, BERT-NILM outperformed state-of-the-art adaptive moment estimation (Adam) optimization across various metrics on REDD datasets; lastly, we evaluated the TEAD dataset using BERT-NILM training.

scholarly journals Heating and Cooling Degree-Days Climate Change Projections for Portugal

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 715
Author(s):  
Cristina Andrade ◽  
Sandra Mourato ◽  
João Ramos
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Thermal Comfort ◽  
Energy Demand ◽  
Residential Buildings ◽  
Degree Days ◽  
Climate Change Projections ◽  
Heating And Cooling ◽  
Cooling Degree Days ◽  
Heating Energy Demand

Climate change is expected to influence cooling and heating energy demand of residential buildings and affect overall thermal comfort. Towards this end, the heating (HDD) and cooling (CDD) degree-days along with HDD + CDD were computed from an ensemble of seven high-resolution bias-corrected simulations attained from EURO-CORDEX under two Representative Concentration Pathways (RCP4.5 and RCP8.5). These three indicators were analyzed for 1971–2000 (from E-OBS) and 2011–2040, and 2041–2070, under both RCPs. Results predict a decrease in HDDs most significant under RCP8.5. Conversely, it is projected an increase of CDD values for both scenarios. The decrease in HDDs is projected to be higher than the increase in CDDs hinting to an increase in the energy demand to cool internal environments in Portugal. Statistically significant linear CDD trends were only found for 2041–2070 under RCP4.5. Towards 2070, higher(lower) CDD (HDD and HDD + CDD) anomaly amplitudes are depicted, mainly under RCP8.5. Within the five NUTS II

scholarly journals Urban Geometry Optimization to Mitigate Climate Change: Towards Energy-Efficient Buildings

2020 ◽  
Vol 13 (1) ◽  
pp. 27
Author(s):  
Hatem Mahmoud ◽  
Ayman Ragab
Keyword(s):  
Climate Change ◽  
Heat Stress ◽  
Thermal Efficiency ◽  
Energy Demand ◽  
Building Blocks ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Urban Geometry ◽  
Outdoor Spaces ◽  
The Impact

The density of building blocks and insufficient greenery in cities tend to contribute dramatically not only to increased heat stress in the built environment but also to higher energy demand for cooling. Urban planners should, therefore, be conscious of their responsibility to reduce energy usage of buildings along with improving outdoor thermal efficiency. This study examines the impact of numerous proposed urban geometry cases on the thermal efficiency of outer spaces as well as the energy consumption of adjacent buildings under various climate change scenarios as representative concentration pathways (RCP) 4.5 and 8.5 climate projections for New Aswan city in 2035. The investigation was performed at one of the most underutilized outdoor spaces on the new campus of Aswan University in New Aswan city. The potential reduction of heat stress was investigated so as to improve the thermal comfort of the investigated outdoor spaces, as well as energy savings based on the proposed strategies. Accordingly, the most appropriate scenario to be adopted to cope with the inevitable climate change was identified. The proposed scenarios were divided into four categories of parameters. In the first category, shelters partially (25–50% and 75%) covering the streets were used. The second category proposed dividing the space parallel or perpendicular to the existing buildings. The third category was a hybrid scenario of the first and second categories. In the fourth category, a green cover of grass was added. A coupling evaluation was applied utilizing ENVI-met v4.2 and Design-Builder v4.5 to measure and improve the thermal efficiency of the outdoor space and reduce the cooling energy. The results demonstrated that it is better to cover outdoor spaces with 50% of the overall area than transform outdoor spaces into canyons.

The Discussion on the Construction of City Waterfront Landscape Based on the Visual Angle of Ecology Restoration

2011 ◽  
Vol 243-249 ◽  
pp. 6827-6833 ◽  
Author(s):  
Gui Yuan Li ◽  
Zhong Yuan Duan ◽  
Yang Xu
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Visual Angle ◽  
Global Climate ◽  
Optimization Method ◽  
Water Shortage ◽  
Practical Significance ◽  
Living Standard ◽  
Design Technique ◽  
The Sustainable Development

In recent years, with the increase of population, the development of urbanization, and the improvement of people’s living standard, people have got an increasingly strong consciousness of environment landscape. While, the global climate change, water shortage and pollution problems which are resulted in the development of social economy.In this article, according to the different traits of waterfront landscape environment, we will analyze the problems of waterfront landscape environment construction, and discuss the design technique of waterfront landscape and the optimization method of landscape environment based on the visual angle of ecology restoration. This can prompt the development of waterfront landscape environment towards the harmony and intergrowth of nature ,ecology and human culture, and this has practical significance for the sustainable development of human and water.

Trajectory Optimization Applied to Space Rendezvous

2013 ◽  
Vol 756-759 ◽  
pp. 3466-3470
Author(s):  
Xu Min Song ◽  
Qi Lin
Keyword(s):  
Simulated Annealing ◽  
Optimization Model ◽  
Trajectory Optimization ◽  
Optimization Problem ◽  
Optimization Method ◽  
Nonlinear Constraints ◽  
Design Variables ◽  
Adaptive Simulated Annealing ◽  
Simulation Results

The trajcetory plan problem of spece reandezvous mission was studied in this paper using nolinear optimization method. The optimization model was built based on the Hills equations. And by analysis property of the design variables, a transform was put forward , which eliminated the equation and nonlinear constraints as well as decreaseing the problem dimensions. The optimization problem was solved using Adaptive Simulated Annealing (ASA) method, and the rendezvous trajectory was designed.The method was validated by simulation results.

scholarly journals Spatial-temporal variation of CO2 emissions from private vehicle use in Japan

2021 ◽  
Author(s):  
Yin Long ◽  
Yoshikuni Yoshida ◽  
Yuan Li ◽  
Alexandros Gasparatos
Keyword(s):  
Climate Change ◽  
Energy Demand ◽  
Vehicle Emissions ◽  
City Size ◽  
Transport Sector ◽  
Large Variability ◽  
Factors Affecting ◽  
Clear Cut ◽  
Private Vehicle ◽  
Nationally Representative

Abstract The transport sector is a major contributor to anthropogenic climate change through the emissions of large amounts of greenhouse gases (GHGs) from fossil fuel combustion. Private vehicles account for almost half of the transport energy demand, and are thus a major target of climate change mitigation efforts. However, emissions from private vehicles can have large variability due to various geographic, demographic and socioeconomic factors. This study aims to understand how such factors affect private vehicle emissions in Japan using a nationally representative survey of household energy consumption (n=7,370) for 2017. The results indicate a large temporal and spatial variability in private vehicle emissions. Annual emissions show three peaks associated with major holiday seasons in winter and summer. Some of the more noteworthy spatial patterns are the higher emissions in prefectures characterized by low population density and mountainous terrain. Income, city size and the fuel-saving driving behavior all have a significant effect on emissions. The results indicate the need for sub-regional and socioeconomically-sensitive mitigation efforts that reflect the very different emission patterns, and the factors affecting them. The strong effect of city size, which is often much more clear-cut than between prefectures, suggests that it is more appropriate to approach transport decarbonization in Japan at the city level.

scholarly journals Risks and opportunities for a Swiss hydropower company in a changing climate

2019 ◽  
Author(s):  
Kirsti Hakala ◽  
Nans Addor ◽  
Thibault Gobbe ◽  
Johann Ruffieux ◽  
Jan Seibert
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Energy Demand ◽  
Climate Change Impacts ◽  
Climate Impacts ◽  
Water Volume ◽  
Volume Distribution ◽  
Impact Studies ◽  
Changing Climate ◽  
Low Flows

Abstract. Anticipating and adapting to climate change impacts on water resources requires a detailed understanding of future hydroclimatic changes and of stakeholders' vulnerability to these changes. However, climate change impact studies are often conducted at a spatial scale that is too coarse to capture the specificity of individual catchments, and more importantly, the changes they focus on are not necessarily the changes most critical to stakeholders. While recent studies have combined hydrological and electricity market modeling, they tend to aggregate all climate impacts by focusing solely on reservoir profitability, and thereby provide limited insights into climate change adaptation. Here, we collaborated with Groupe E, a hydropower company operating several reservoirs in the Swiss pre-Alps and worked with them to produce hydroclimatic projections tailored to support their upcoming water concession negotiations. We started by identifying the vulnerabilities of their activities to climate change and then together chose streamflow and energy indices to characterize the associated risks. We provided Groupe E with figures showing the projected climate change impacts, which were refined over several meetings. The selected indices enabled us to simultaneously assess a variety of impacts induced by changes on i) the seasonal water volume distribution, ii) low flows, iii) high flows, and iv) energy demand. We were hence able to identify key opportunities (e.g., the future increase of reservoir inflow in winter, when electricity prices are historically high) and risks (e.g., the expected increase of consecutive days of low flows in summer and fall, which is likely to make it more difficult to meet residual flow requirements). This study highlights that the hydrological opportunities and risks associated with reservoir management in a changing climate depend on a range of factors beyond those covered by traditional impact studies. We also illustrate the importance of identifying stakeholder needs and using them to inform the production of climate impact projections. Our user-centered approach is transferable to other impact modeling studies, in the field of water resources and beyond.

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