Vulnerability Assessment of Electric Power Supply under Extreme Weather Conditions

This thesis analyses and models the vulnerability of the electricity power supply under extreme weather conditions. The system under study is the electric supply system that includes major power plants to main load centers. Extreme weather conditions can cause common mode contingencies (CMCs) of overhead power lines, which endanger the security of electricity supply. Planning and operation of transmission systems are subject to N-1 criterion, which requires that all single failures of network elements do not cause a breach of safety limits. This criterion does not guarantee the security of electricity supply at the time of extreme weather conditions. The objective of this research is to identify critical and plausible CMCs, taking into account space-time correlations of extreme weather conditions and possible states of the network. The most vulnerable zones are focused on to determine appropriate countermeasures for reducing vulnerability. In the past, extreme weather events have caused major disruptions. For example, the blackout in New York in 1977 was initiated by three impacts of lightning on high voltage lines. In 1999, hurricane Lothar caused damage to power grids in several countries, leaving hundreds of thousands of people in darkness. These examples demonstrate the vulnerability of power systems to CMCs. Current transmission networks are expected to undergo significant changes in response to developments such as increases in consumption and newly installed capacity. These changes provide an opportunity to strengthen the security of electricity supply in the perspective of extreme weather conditions and even improve the resilience of electric supply systems. The use of the proposed methodology allows reducing the level of vulnerability by reinforcing only few points or change of the topology of the network. Faced with uncertainties about the evolution of networks and plausible extreme weather conditions, a methodology based on scenarios has been selected. The methodology allows the modeler to reproduce the complexity of the problem while still encouraging the learning process. The core of the methodology is founded on a scenario of electric supply systems and a scenario of extreme weather events. The first scenario includes three models: electric, geographic, and reliability. The electric model comprises components of the network compatible with load flow calculations. The geographic model contains a representation of each power line in a geographic information system, and each of these lines is divided into segments that are associated with a reliability model. The reliability model evaluates failure rates related to exposure to extreme weather conditions. Scenarios of extreme weather events are built on data from weather stations or by numerical simulations implemented in a geographic information system. A vulnerability level index is calculated on the basis of probability and severity indices of a priori possible CMCs. These probabilities are evaluated by a simulation of the interaction between the scenario of transmission network and scenario of extreme weather event. They are a subjective and temporal measure of plausibility of CMCs stemming from interactions in space and time of the two systems previously mentioned. The severity index of CMCs is calculated by a contingency analysis that involves the evaluation of security limit violations. A matrix of vulnerability is constructed as a projection of the vulnerability level in two dimensions, including the lines involved in overload and those being overloaded. This matrix allows the identification of the infrastructures involved in the vulnerability and the determination of major zones of vulnerability. Countermeasures are then proposed to reduce the vulnerability of these zones, and these measures may include additions or retirement of lines or other network topology changes. This methodology is applied to the Swiss transmission network in 2018 subject to summer thunderstorms. A reference case from 2006 is compared in terms of vulnerability to a plausible scenario of transmission network 2018. The latter includes an increased consumption of 20%, around 3 GW of pumped-storage power plants, and network changes proposed by the electricity sector plan supported by the Swiss Federal Office of Energy. On another level, two scenarios of extreme weather events were constructed. The first is an intense thunderstorm occurring in the past, where lightning strikes were recorded by a tracking system. The second case stems from a simulation of a thunderstorm event composed of six cells passing over the Swiss territory. The vulnerability of both scenarios of electric supply system impacted by both scenarios of extreme weather events was evaluated. Two major zones of vulnerability were detected both in the reference case 2006 and the plausible scenario 2018. They are in mountainous regions near major centers of production. The network changes between 2006 and 2018 did not decrease the vulnerability. This is due to the installation of large generation capacity and the difficulty of building lines as a result of the topography in these regions. To reduce vulnerability, the addition of a 380 kV overhead line is proposed for the plausible scenario 2018. This line allows draining off the new hydro generation by offering a new route to major consumption centers and drastically reduces the vulnerability of the two zones mentioned. This measure illustrates the methodology's ability to identify areas of vulnerability and propose actions to increase network resilience. One of the major contributions and innovative points of this research is the consideration of the spatiotemporal correlations of extreme weather conditions for the geographical distribution and structural resistance of transmission lines. In the application of the Swiss 2018 scenario of transmission network, the concept of major zones of vulnerability was useful in identifying the weakest zones and in finding a measure capable of increasing network resilience.

Climate change and its influence on the planning and operation of electric power systems

Raphaël Barben, Edgard Gnansounou

The IPCC Report (Intergovernmental Panel on Climate Change 2007) raises serious concerns about the increase of extreme weather events (storms, rains, snowfalls). Over the past 100 years the average global temperature has risen by around 0.75°C and the sea level increases by 3 millimetres a year. There is a consensus on the impact of this climate change phenomena on the planning and operation of the electric power systems: winds are growing in strength, resulting in a greater frequency of operations interruption (falling trees, avalanches, etc.). Furthermore, due to the increasing incidence of heavy precipitation, lines and substations are often flooded, damaged or destroyed. Repairing the resultant damage is often very time-consuming. And also the temperature of permafrost layers is rising. As a result the bedrock is becoming loose. This in turn increases the risk of landslides, which also damage and destroy lines and substations. There are many cases of extreme weather which have caused enormous damage to electric power systems, e.g. the ice storm in Canada (1998) or the hurricane "Lothar" in Western Europe (1999). Considering the climate change at the planning of electric power systems is therefore highly relevant. In order to plan the power system we need to evaluate the risk of outages due to extreme weather. The vulnerability is assessed, based on historic meteorological data. It results in geographic and seasonal exposure maps. E.g. in Switzerland, alpine regions are more prone to extreme conditions which can vary from one valley to the other. In this paper, the planning methodology uses scenarios to assess the uncertainty related to the vulnerability of the power system under extreme weather conditions. These scenarios are based on weather-related contingencies and reference cases of the Swiss transmission system. The climate change has also to be considered at the operation of electric power systems. At the control centres new operating tools have to be introduced which take into account the impact of the climate change, e.g. an early warning weather system, or a Geographic Information System (GIS) which pinpoints (together with information of protection systems), the location of a damaged line so that the repair staff can be on the spot very quickly, thereby minimising downtime. Furthermore the dispatchers must be trained on how to manage their electric power system during extreme weather conditions. Finally experienced crisis organisations must be established.

2008

Model Predictive Control Strategies for Polygeneration systems and microgrids

Ramanunni Parakkal Menon

Increasing electricity and thermal demand in all sectors, an increasing focus on the reduction in carbon emissions and use of nuclear power, advent of distributed generation and greater use of renewable technologies on an aging electrical and thermal grid system has necessitated the need for modern control and management systems. These new control and management systems need to be able to integrate new technologies, stochasticities and maximise the utilisation of the existing infrastructure while satisfying demands, without requiring complete overhaul of the pre-existing centralised grid system and the transmission and distribution systems. A model predictive control system has been proposed and demonstrated here which is able to create strategies for thermal and electrical systems such that the grid efficiency and security is maintained while minimising resource usage and emissions, while, simultaneously reducing the operating costs in the grid. The model predictive control(MPC) utilises a fully energetic approach for low-voltage microgrids and houses in the residential and commercial sector which comprises of CHP units, heat pumps, storage systems(electric and thermal) and stochastic renewable resources, while accounting for the varying dynamics of the electrical and thermal systems. Finally, validation of the MPC is performed on a testbed with physical units and building emulators which have access to meteorological and resource market data. The capability of the MPC to provide strategies for systems with photovoltaics (PV), heat pumps and CHP units is demonstrated. The MPC implementation developed is input into an optimal system design algorithm based on a multi-objective optimisation genetic algorithm developed for microgrids and urban systems/grids with end-users and polygeneration systems and storage devices. The optimal design of the system is so that the optimal sizes of the polygeneration systems can be identified. This will help in maximising the utilisation of heat pumps, storage devices and other systems in a LV microgrid equipped with an MPC-based thermo-electric energy management system. The work also aims to compare the cost effectiveness versus ability of thermal storage devices compared to electrical storage devices for the same grid in question.

EPFL2017

Signatures of selection and environmental adaptation across the goat genome post-domestication

Stéphane Joost, Estelle Rochat

Background: Since goat was domesticated 10,000 years ago, many factors have contributed to the differentiation of goat breeds and these are classified mainly into two types: (i) adaptation to different breeding systems and/or purposes and (ii) adaptation to different environments. As a result, approximately 600 goat breeds have developed worldwide; they differ considerably from one another in terms of phenotypic characteristics and are adapted to a wide range of climatic conditions. In this work, we analyzed the AdaptMap goat dataset, which is composed of data from more than 3000 animals collected worldwide and genotyped with the CaprineSNP50 BeadChip. These animals were partitioned into groups based on geographical area, production uses, available records on solid coat color and environmental variables including the sampling geographical coordinates, to investigate the role of natural and/or artificial selection in shaping the genome of goat breeds. Results: Several signatures of selection on different chromosomal regions were detected across the different breeds, sub-geographical clusters, phenotypic and climatic groups. These regions contain genes that are involved in important biological processes, such as milk-, meat- or fiber-related production, coat color, glucose pathway, oxidative stress response, size, and circadian clock differences. Our results confirm previous findings in other species on adaptation to extreme environments and human purposes and provide new genes that could explain some of the differences between goat breeds according to their geographical distribution and adaptation to different environments. Conclusions: These analyses of signatures of selection provide a comprehensive first picture of the global domestication process and adaptation of goat breeds and highlight possible genes that may have contributed to the differentiation of this species worldwide.

BMC2018