scholarly journals The Vulnerability of the Power Sector to Climate Variability and Change: Evidence from Indonesia

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3640 ◽  
Author(s):  
Kamia Handayani ◽  
Tatiana Filatova ◽  
Yoram Krozer
Keyword(s):  
Power Plants ◽  
Distribution Networks ◽  
Climate Impacts ◽  
Severe Weather ◽  
Electricity Supply ◽  
Power Sector ◽  
Power Outages ◽  
Lightning Strikes ◽  
Vulnerability To Climate Change ◽  
Weather Events

The power sector is a key target for reducing CO2 emissions. However, little attention has been paid to the sector’s vulnerability to climate change. This paper investigates the impacts of severe weather events and changes in climate variables on the power sector in developing countries, focusing on Indonesia as a country with growing electricity infrastructure, yet being vulnerable to natural hazards. We obtain empirical evidence concerning weather and climate impacts through interviews and focus group discussions with electric utilities along the electricity supply chain. These data are supplemented with reviews of utilities’ reports and published energy sector information. Our results indicate that severe weather events often cause disruptions in electricity supply—in the worst cases, even power outages. Weather-related power outages mainly occur due to failures in distribution networks. While severe weather events infrequently cause shutdowns of power plants, their impact magnitude is significant if it does occur. Meanwhile, transmission networks are susceptible to lightning strikes, which are the leading cause of the networks’ weather-related failures. We also present estimates of financial losses suffered by utilities due to weather-related power disruptions and highlights their adaptation responses to those disruptions.

The role of gap analyses in energy assurance planning

2017 ◽  
Vol 11 (3) ◽  
pp. 181
Author(s):  
Katherine Shea, JD
Keyword(s):  
Local Governments ◽  
Power Loss ◽  
Gap Analysis ◽  
Hurricane Sandy ◽  
Severe Weather ◽  
Power Outages ◽  
Weather Events ◽  
State And Local ◽  
The Impact

Energy-related emergencies, such as power outages or interruptions to other energy supplies, can arise from a number of factors. Common causes include severe weather events—such as snowstorms, hurricanes, or summer storms with strong winds—as well as energy infrastructure that is overburdened, aging, or in need of repair. As past experience indicates, jurisdictions will continue to experience severe weather events, as well as confront infrastructure issues that make future power outages likely. As a result, state and local governments have turned to energy assurance planning, an energy-specific form of planning that helps jurisdictions prepare for and recover from energy emergencies. Energy assurance recognizes that power loss/disruption cannot be eradicated completely, but jurisdictions can mitigate the impact of power loss through effective planning. This article discusses the role of energy assurance planning and provides a description of what energy assurance means and why developing such plans at the state and local levels is important. In addition, this article discusses the role of statutory gap analyses in energy assurance planning and discusses how a gap analysis can be used by planners to identify trends and gaps in energy assurance. To provide context, a recently conducted statutory gap analysis analyzing national emergency backup power trends is provided as a case study. A summary of this project and key findings is included. Finally, this article briefly touches on legislation as an alternative to energy assurance planning, and provides summaries of recent legislative proposals introduced in the aftermath of Hurricane Sandy.

scholarly journals Power sector investment implications of climate impacts on renewable resources in Latin America and the Caribbean

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Silvia R. Santos da Silva ◽  
Mohamad I. Hejazi ◽  
Gokul Iyer ◽  
Thomas B. Wild ◽  
Matthew Binsted ◽  
...  
Keyword(s):  
Climate Change ◽  
Latin American ◽  
Climate Impacts ◽  
Integrated Assessment Model ◽  
Assessment Model ◽  
Climate Mitigation ◽  
Power Sector ◽  
Vulnerability To Climate Change ◽  
Financial Infrastructure ◽  
Primary Focus

AbstractClimate change mitigation will require substantial investments in renewables. In addition, climate change will affect future renewable supply and hence, power sector investment requirements. We study the implications of climate impacts on renewables for power sector investments under deep decarbonization using a global integrated assessment model. We focus on Latin American and Caribbean, an under-studied region but of great interest due to its strong role in international climate mitigation and vulnerability to climate change. We find that accounting for climate impacts on renewables results in significant additional investments ($12–114 billion by 2100 across Latin American countries) for a region with weak financial infrastructure. We also demonstrate that accounting for climate impacts only on hydropower—a primary focus of previous studies—significantly underestimates cumulative investments, particularly in scenarios with high intermittent renewable deployment. Our study underscores the importance of comprehensive analyses of climate impacts on renewables for improved energy planning.

Protection of Nuclear Power Plants Against Severe Winds: Impact of the Local Building Configuration on the Wind Speed to Consider

2020 ◽  
Author(s):  
Arièle Défossez ◽  
Eric Dupont ◽  
Laurence Grammosenis ◽  
Hervé Cordier ◽  
Tiphaine Le Morvan
Keyword(s):  
Wind Speed ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Power Plants ◽  
Flow Behavior ◽  
Severe Weather ◽  
Wind Rose ◽  
Pressurized Water ◽  
Weather Events

Abstract Over the years, power plants have been hit by numerous severe weather events (storm, flood, heat wave...). EDF (Electricity of France) and ASN (Nuclear Safety Authority) want to assess the future impact of severe weather events on the power plants. Furthermore, recent research on storms estimates more accurate wind speed return values than before. For this reason, the severe wind value is an important parameter to quantify on a NPP (Nuclear Power Plant) site, in order to verify if the protection measures are sufficient or, if necessary, to design adequate protection. To cope with those objectives, wind flow behavior around a PWR (Pressurized Water Reactor) nuclear power plant is studied. The goal of this work is to check that there is no exceeding local wind speed relative to the wind entering the site. The severe winds are characterized locally near the buildings in terms of location and amplitude. Different kind of topology for the nuclear power plant sites are studied in the project: near a cliff, in a plain or in a basin. In our study, the CFD (Computational Fluid Dynamics) open source tool Code_Saturne developed at EDF-R&D is used to simulate the wind over a French PWR site located in nearly flat terrain in a plain. The 3D mesh includes buildings of the site. Several wind directions corresponding to the prevailing winds are studied. Two wind speeds corresponding to wind speed return values are studied (eg: the inlet wind speed is 25 m/s at 10 meter high for a return period of 50 years). Furthermore, several locations selected near buildings are studied carefully. Swirling flows have been viewed between buildings. Analysis of the results shows that the wind speed near the buildings does not exceed the wind speed at the entrance of the domain for the three directions studied except near the cooling towers and above buildings. However, this result should not be generalized to other PWR sites due to the specificities of each site such as relief, buildings position, buildings size, roughness, wind rose... This methodology could be applied at other nuclear power plant sites.

scholarly journals Modeling of Lightning Strike Events, and it’s Correlational with Power Outages in South-West Coast, Nigeria

2017 ◽  
Vol 7 (6) ◽  
pp. 3262 ◽  
Author(s):  
Melodi A. O. A. O. ◽  
Olayinka Matthew Oyeleye
Keyword(s):  
Power Systems ◽  
Power Distribution ◽  
Distribution System ◽  
Distribution Network ◽  
Distribution Networks ◽  
Lightning Strike ◽  
Power Outages ◽  
Lightning Strikes ◽  
Power Distribution System ◽  
Review Management

This paper aimed to model lightning strike events and evaluate its correlation with power outages in a Nigerian power distribution system. A specified coastal distribution network of southwest Nigeria was selected as a case study. Zone-specific records of cloud-to-ground lightning strikes for 84 months were obtained from the Nigerian Meteorological Agency (NiMet); records of power outage frequencies and durations for 36 months were obtained at the substations of the selected distribution network. Using numerical statistical analysis techniques, lightning activity in the system area were characterized in relative frequency terms, and correlation statistics were evaluated and analyzed for power outages and lightning events on the 11kV, 33kV, and 132kV voltage levels. An analysis of the results shows that the modelled lightning strike events patterns are closely related but the expected frequencies vary from one zone to another; and there is correlation between lightning strike and power outages in the distribution networks, which is strong and positive at the 33 kV and 132 kV circuits. In essence, the results provided salient information, useful for power systems lightning protection review, management and planning in the area.

scholarly journals Spatial variations in the warming trend and the transition to more severe weather in midlatitudes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Francisco Estrada ◽  
Dukpa Kim ◽  
Pierre Perron
Keyword(s):  
Radiative Forcing ◽  
Warming Trend ◽  
Severe Weather ◽  
Montreal Protocol ◽  
The Arctic ◽  
Extreme Weather Events ◽  
Jet Stream ◽  
Atmospheric Blocking ◽  
Regional Warming ◽  
Weather Events

AbstractDue to various feedback processes called Arctic amplification, the high-latitudes’ response to increases in radiative forcing is much larger than elsewhere in the world, with a warming more than twice the global average. Since the 1990’s, this rapid warming of the Arctic was accompanied by no-warming or cooling over midlatitudes in the Northern Hemisphere in winter (the hiatus). The decrease in the thermal contrast between Arctic and midlatitudes has been connected to extreme weather events in midlatitudes via, e.g., shifts in the jet stream towards the equator and increases in the probability of high-latitude atmospheric blocking. Here we present an observational attribution study showing the spatial structure of the response to changes in radiative forcing. The results also connect the hiatus with diminished contrast between temperatures over regions in the Arctic and midlatitudes. Recent changes in these regional warming trends are linked to international actions such as the Montreal Protocol, and illustrate how changes in radiative forcing can trigger unexpected responses from the climate system. The lesson for climate policy is that human intervention with the climate is already large enough that even if stabilization was attained, impacts from an adjusting climate are to be expected.

scholarly journals Machine Learning and GIS Approach for Electrical Load Assessment to Increase Distribution Networks Resilience

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4133
Author(s):  
Alessandro Bosisio ◽  
Matteo Moncecchi ◽  
Andrea Morotti ◽  
Marco Merlo
Keyword(s):  
Machine Learning ◽  
Distribution System ◽  
Low Voltage ◽  
Regression Tree ◽  
Distribution Networks ◽  
Machine Learning Algorithms ◽  
Extreme Weather Events ◽  
Medium Voltage ◽  
Weather Events ◽  
Building Area

Currently, distribution system operators (DSOs) are asked to operate distribution grids, managing the rise of the distributed generators (DGs), the rise of the load correlated to heat pump and e-mobility, etc. Nevertheless, they are asked to minimize investments in new sensors and telecommunication links and, consequently, several nodes of the grid are still not monitored and tele-controlled. At the same time, DSOs are asked to improve the network’s resilience, looking for a reduction in the frequency and impact of power outages caused by extreme weather events. The paper presents a machine learning GIS-based approach to estimate a secondary substation’s load profiles, even in those cases where monitoring sensors are not deployed. For this purpose, a large amount of data from different sources has been collected and integrated to describe secondary substation load profiles adequately. Based on real measurements of some secondary substations (medium-voltage to low-voltage interface) given by Unareti, the DSO of Milan, and georeferenced data gathered from open-source databases, unknown secondary substations load profiles are estimated. Three types of machine learning algorithms, regression tree, boosting, and random forest, as well as geographic information system (GIS) information, such as secondary substation locations, building area, types of occupants, etc., are considered to find the most effective approach.

Understanding Severe Weather Events at Airport Spatial Scale

2020 ◽  
Author(s):  
Enrico Solazzo ◽  
Pierre-Yves Tournigand ◽  
Stefano Barindelli ◽  
Valerio Guglieri ◽  
Eugenio Realini ◽  
...  
Keyword(s):  
Spatial Scale ◽  
Severe Weather ◽  
Weather Events

scholarly journals A Total Lightning Trending Algorithm to Identify Severe Thunderstorms

2010 ◽  
Vol 27 (1) ◽  
pp. 3-22 ◽  
Author(s):  
Patrick N. Gatlin ◽  
Steven J. Goodman
Keyword(s):  
Severe Weather ◽  
Lightning Flash ◽  
Severe Thunderstorm ◽  
Critical Success ◽  
Severe Thunderstorms ◽  
Weather Events ◽  
Total Lightning ◽  
Jump Algorithm ◽  
Early Indication ◽  
Critical Success Index

Abstract An algorithm that provides an early indication of impending severe weather from observed trends in thunderstorm total lightning flash rates has been developed. The algorithm framework has been tested on 20 thunderstorms, including 1 nonsevere storm, which occurred over the course of six separate days during the spring months of 2002 and 2003. The identified surges in lightning rate (or jumps) are compared against 110 documented severe weather events produced by these thunderstorms as they moved across portions of northern Alabama and southern Tennessee. Lightning jumps precede 90% of these severe weather events, with as much as a 27-min advance notification of impending severe weather on the ground. However, 37% of lightning jumps are not followed by severe weather reports. Various configurations of the algorithm are tested, and the highest critical success index attained is 0.49. Results suggest that this lightning jump algorithm may be a useful operational diagnostic tool for severe thunderstorm potential.

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