1,721,066 research outputs found
Microgrids reliability analysis in case of HILP events
No full textLAUREA MAGISTRALEDato il costante aumento di infrastrutture elettriche, il crescente fenomeno del
riscaldamento globale e la sempre più difficoltosa estrazione delle attuali fonti energetiche
si è costretti a trovare nuovi ed efficienti metodi di produzione di energia elettrica avendo
cura dell’impatto ambientale associato ad ogni possibile soluzione.
Attualmente, la rete elettrica è dimensionata tenendo in considerazione guasti sulle linee
provocati da fenomeni con alta probabilità di accadimento ma con basso impatto di rischio
che riescono ad essere risolti in pochi istanti. Nel prossimo futuro è invece dato in aumento
la possibilità che avvengano eventi che potranno avere un impatto catastrofico sulle linee
ma che si presenteranno con bassa probabilità di accadimento.
Questi Eventi, noti sotto il nome di HILP, sono catastrofi climatiche come tsunami,
inondazioni e incendi su grossa scala che possono causare disagi su sistemi elettrici di
trasmissione e di distribuzione con danni che possono richiedere giorni, se non settimane,
prima di essere risolti.
Risulta quindi fondamentale lo studio della rete elettrica in presenza di HILP e di
conseguenza i concetti di affidabilità e resilienza di rete stanno diventato sempre più
attuali.
Lo scopo della tesi è di analizzare, grazie a un processo di ottimizzazione matematica, la
fattibilità energetica ed economica di due differenti microgrid, funzionanti in off-grid, nel
momento in cui eventi HILP provochino guasti sulla rete.
Nella prima parte dell’elaborato verranno messe a confronto due microgrid; una
funzionante grazie a un sistema ibrido PV+BESS+DG ed una comandata da un impianto
CHP. Grazie a tecniche di ottimizzazione matematica, valori come costo totale di
installazione e di manutenzione verranno calcolati e confrontati.
Nella seconda parte dell’elaborato, le due micorgrid (separatamente) verranno collegate ad
una rete test funzionante in off-grid in maniera tale da studiarne l’affidabilità grazie al
modello RBTS introdotto da Roy Billinton nel 1997.
Conseguentemente, dei guasti casuali verranno generati sulla rete utilizzando una
simulazione Monte Carlo e, utilizzando in concetto di CVaR, sarà possibile studiare
l’andamento del sistema in caso di HILP.
Data l’immediatezza del controllo e dell’immissione in rete di energia, al termine delle
simulazioni è stato possibile concludere che la migliore microgrid da utilizzare in caso di
HILP è quella comandata dal sistema CHP.Due to increasing demand for electricity, climate change and scarcity of energy resources
the earth population is forced to find new approaches towards powering electrical systems
with less use of fossil fuels with more care on the environment.
Moreover, the climate change that we’re facing is altering the classic climate patterns
increasing the ‘catastrophic’ with low probability events forcing us to be more aware of the
concept of Resilience and Reliabilty of the Power systems.
When power electrical systems are designed in an efficient way, they may not only have
smaller impact on the environment, they can also be less costly compared to other classic
technologies and can also reduce the outage time created by phenomena such as floods,
hurricanes, earthquakes and fires.
The scope of this research is to analyze by multi objective optimization process the
economic and the energetic feasibility of microgrids in area where climatic events might
create blackouts on the network.
The importance of the research is given by the fact that generally, the reliability
considerations on the electrical network are made using average probability values of
outage occurrence and they do not consider the effect of High Impact Low Probability
Events (HILP).
The first part of the thesis is a comparison between a CHP based microgrid and a
PV+BESS+DG microgrid where Optimizations Minimization Techniques are applied in
order to obtain results about Total Costs and Total Capacity.
In the second part of the work, the two off-grid microgrids are connencted to a test network
in order to study the reliability of the network in case of presence of only one of the two
power production microgrid at a time.
The optimization is performed considering the bus 2 of the Reliability Test System (RBTS)
firstly introduced by Roy Billinton in 1997 and, consequently, a Monte Carlo Simulation is
used in order to generate random faults on the branches of the network under analysis.
Lastly, using the concept of the Conditional Value at Risk (CVaR), the risk associated to
the Energy not Supplied on each load point is studied and, thanks to the results, it will be
possible to conclude that the CHP microgrid is more favorable in case of HILP events due
to his immediate and affordable control
Modeling and evaluating the resilience of critical electrical power infrastructure to extreme weather events
No full textElectrical power systems have been traditionally designed to be reliable during normal conditions and abnormal but foreseeable contingencies. However, withstanding unexpected and less frequent severe situations still remains a significant challenge. As a critical infrastructure and in the face of climate change, power systems are more and more expected to be resilient to highimpact low-probability events determined by extreme weather phenomena. However, resilience is an emerging concept, and, as such, it has not yet been adequately explored in spite of its growing interest. On these bases, this paper provides a conceptual framework for gaining insights into the resilience of power systems, with focus on the impact of severe weather events. As quantifying the effect of weather requires a stochastic approach for capturing its random nature and impact on the different system components, a novel sequential Monte-Carlo-based time-series simulation model is introduced to assess power system resilience. The concept of fragility curves is used for applying weather-and time-dependent failure probabilities to system's components. The resilience of the critical power infrastructure is modeled and assessed within a context of system-of-systems that also include human response as a key dimension. This is illustrated using the IEEE 6-bus test system.</p
Correlations of Shocks and Stresses with Distribution Network Outages
No full textDistribution network outages have significant socioeconomic impacts, and potentially pose a threat to life when critical infrastructures are affected. Shocks and stresses, such as climate change, extreme weather or intentional attacks, in combination with an expected rise in electricity demand, pose an increasing risk to power network reliability. Detailed data on distribution network outages can be used for further research in prevention and mitigation of such outages. This paper presents and describes a unique and comprehensive dataset of UK distribution network outages. The dataset for 2020 is analyzed to identify correlations with shocks and stresses, such as demand, extreme weather, and COVID-19 lockdown. The results justifyfurther research in prevention and mitigation of distribution network outages, support the industry in future planning of distribution networks, and can feed into models for operational planning in face of upcoming shocks and stresses
Influence of Extreme Weather and Climate Change on the Resilience of Power Systems: Impacts and Possible Mitigation Strategies
Full text linkA key driver for developing more sustainable energy systems is to decrease the effects of climate change, which could include an increase in the frequency, intensity and duration of severe weather events. Amongst others, extreme weather has a significant impact on critical infrastructures, and is considered one of the main causes of wide-area electrical disturbances worldwide. In fact, weather-related power interruptions often tend to be of high impact and sustained duration, ranging from hours to days, because of the large damage on transmission and distribution facilities. Hence, enhancing the grid resilience to such events is becoming of increasing interest. In this outlook, this paper first discusses the influence of weather and climate change on the reliability and operation of power system components. Since modeling the impact of weather is a difficult task because of its stochastic and unpredicted nature, a review of existing methodologies is provided in order to get an understanding of the key modeling approaches, challenges and requirements for assessing the effect of extreme weather on the frequency and duration of power system blackouts. Then, the emerging concept of resilience is discussed in the context of power systems as critical infrastructure, including several defense plans for boosting the resilience of power systems to extreme weather events. A comprehensive research framework is finally outlined, which can help understand and model the impact of extreme weather on power systems and how this can be prevented or mitigated in the future
The Grid: Stronger, Bigger, Smarter? Presenting a conceptual framework of power system resilience
Full text linkIncreasing the resilience of critical power infrastructures to high-impact low-probability events, such as extreme weather phenomena driven by climate change, is of key importance for keeping the lights on. However, what does resilience really mean? Should we build a stronger and bigger grid, or a smarter one? This article discusses a conceptual framework of power system resilience, its key features, and potential enhancement measures
Correlations of Shocks and Stresses with Distribution Network Outages
No full textDistribution network outages have significant socioeconomic impacts, and potentially pose a threat to life when critical infrastructures are affected. Shocks and stresses, such as climate change, extreme weather or intentional attacks, in combination with an expected rise in electricity demand, pose an increasing risk to power network reliability. Detailed data on distribution network outages can be used for further research in prevention and mitigation of such outages. This paper presents and describes a unique and comprehensive dataset of UK distribution network outages. The dataset for 2020 is analyzed to identify correlations with shocks and stresses, such as demand, extreme weather, and COVID-19 lockdown. The results justifyfurther research in prevention and mitigation of distribution network outages, support the industry in future planning of distribution networks, and can feed into models for operational planning in face of upcoming shocks and stresses
Influence of Extreme Weather and Climate Change on the Resilience of Power Systems: Impacts and Possible Mitigation Strategies
Full text linkA key driver for developing more sustainable energy systems is to decrease the effects of climate change, which could include an increase in the frequency, intensity and duration of severe weather events. Amongst others, extreme weather has a significant impact on critical infrastructures, and is considered one of the main causes of wide-area electrical disturbances worldwide. In fact, weather-related power interruptions often tend to be of high impact and sustained duration, ranging from hours to days, because of the large damage on transmission and distribution facilities. Hence, enhancing the grid resilience to such events is becoming of increasing interest. In this outlook, this paper first discusses the influence of weather and climate change on the reliability and operation of power system components. Since modeling the impact of weather is a difficult task because of its stochastic and unpredicted nature, a review of existing methodologies is provided in order to get an understanding of the key modeling approaches, challenges and requirements for assessing the effect of extreme weather on the frequency and duration of power system blackouts. Then, the emerging concept of resilience is discussed in the context of power systems as critical infrastructure, including several defense plans for boosting the resilience of power systems to extreme weather events. A comprehensive research framework is finally outlined, which can help understand and model the impact of extreme weather on power systems and how this can be prevented or mitigated in the future
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