Resilience of Finnish electricity distribution networks against extreme weather conditions

2016 ◽  
Author(s):  
K. Forssen ◽  
K. Maki
Keyword(s):  
Weather Conditions ◽  
Distribution Networks ◽  
Extreme Weather ◽  
Electricity Distribution

Resilience of Electricity Distribution Networks Against Extreme Weather Conditions

2017 ◽  
Vol 3 (2) ◽  
Author(s):  
Kim Forssén ◽  
Kari Mäki ◽  
Minna Räikkönen ◽  
Riitta Molarius
Keyword(s):  
Distribution System ◽  
Situational Awareness ◽  
Weather Conditions ◽  
Distribution Networks ◽  
Extreme Weather ◽  
Electricity Supply ◽  
Electricity Distribution ◽  
Overhead Lines ◽  
Electrical Grid ◽  
Adverse Weather

Extreme weather forms a major threat to electricity distribution networks and has caused many severe power outages in the past. A reliable electrical grid is something most of us take for granted, but storms, heavy snowfall, and other effects of extreme weather continue to cause disruptions in electricity supply. This paper contributes to ensuring the continuity of electricity supply under adverse weather events. The aim is to describe and to analyze how the continuity of electricity supply can be ensured in the case of extreme weather. Based on the research, the energy sector is highly dependent on the existing locations and structures of the current infrastructure. Aging infrastructure is commonly seen as a main vulnerability factor. The most vulnerable parts of the electricity distribution system to extreme weather conditions are the networks built as overhead lines. However, the resilience of the networks against extreme weather can be increased significantly in all phases of a disaster management cycle. Methods and technological solutions proposed in this paper to alleviate such problems include adjacent forest management and periodic aerial inspections, situational awareness, distributed generation and microgrids, placement of overhead lines, underground cabling, and unmanned air vehicles. However, it must be noticed that the methods and their value for stakeholders are context-dependent. Thus, their applicability and appropriateness may change over time.

scholarly journals Precipitation Modeling for Extreme Weather Based on Sparse Hybrid Machine Learning and Markov Chain Random Field in a Multi-Scale Subspace

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1241
Author(s):  
Ming-Hsi Lee ◽  
Yenming J. Chen
Keyword(s):  
Machine Learning ◽  
Markov Chain ◽  
Random Field ◽  
Long Range ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Prediction Algorithm ◽  
Learning Method ◽  
Multi Scale ◽  
Hybrid Machine

This paper proposes to apply a Markov chain random field conditioning method with a hybrid machine learning method to provide long-range precipitation predictions under increasingly extreme weather conditions. Existing precipitation models are limited in time-span, and long-range simulations cannot predict rainfall distribution for a specific year. This paper proposes a hybrid (ensemble) learning method to perform forecasting on a multi-scaled, conditioned functional time series over a sparse l1 space. Therefore, on the basis of this method, a long-range prediction algorithm is developed for applications, such as agriculture or construction works. Our findings show that the conditioning method and multi-scale decomposition in the parse space l1 are proved useful in resisting statistical variation due to increasingly extreme weather conditions. Because the predictions are year-specific, we verify our prediction accuracy for the year we are interested in, but not for other years.

Multi-objective resilience enhancement program in smart grids during extreme weather conditions

2021 ◽  
Vol 129 ◽  
pp. 106824
Author(s):  
Rahman Ashrafi ◽  
Meysam Amirahmadi ◽  
Mohammad Tolou-Askari ◽  
Vahid Ghods
Keyword(s):  
Smart Grids ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Multi Objective

scholarly journals Extreme weather conditions and dengue outbreak in Guangdong, China: spatial heterogeneity based on climate variability

2021 ◽  
pp. 110900
Author(s):  
Jian Cheng ◽  
Hilary Bambrick ◽  
Laith Yakob ◽  
Gregor Devine ◽  
Francesca D. Frentiu ◽  
...  
Keyword(s):  
Climate Variability ◽  
Spatial Heterogeneity ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Dengue Outbreak

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.

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