Resilience in an Evolving Electrical Grid

Cicilio, Phylicia; Glennon, David; Máté, Ádám; Barnes, Arthur K.; Chalishazar, Vishvas; Cotilla‐Sanchez, Eduardo; Vaagensmith, Bjorn; Gentle, Jake P.; Rieger, Craig; Wies, Richard; Kapourchali, Mohammad Heidari

doi:10.3390/en14030694

Cited by 24 publications

(21 citation statements)

References 136 publications

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“…The reliability of a self-healing building depends on the successful operation of each involved component, because it influences the strategy of market participation and consequently affects the economic and resiliency aspects. Furthermore, the uncertainty associated with natural and human-made disruptions should be integrated with optimal energy management to reduce the risks and probable losses [25].…”

Section: A Resiliency-based Energy Managementmentioning

confidence: 99%

Optimal Scheduling of a Self-Healing Building Using Hybrid Stochastic-Robust Optimization Approach

Dibavar

Mohammadi‐Ivatloo

Zare

et al. 2022

IEEE Trans. on Ind. Applicat.

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This article provides a two-stage robust energy management method for a self-healing smart building that can handle contingencies that occur during real-time operation. Aside from an electrical link with the distribution network, the smart building is equipped with a diesel generator and photovoltaic solar power generating systems. The energy management system should be smart enough to plan different resources based on the situation. At first, bi-level programming identifies critical faults for affected components based on mean-time-to-repair. After identifying major failures, the faults are described in operational scenarios, and two-stage hybrid robust-stochastic programming technique is used to determine the bid/offer in day-ahead and real-time energy markets, in which stochastic programming is responsible for considering the uncertainty of faults, and the robust optimization approach is used to cope with the uncertainty of real-time market prices. After linearization, the final optimization is modeled as mixed-integer linear programming in GAMS optimization package. For the studied smart building, the daily operational cost is expected to increase from $ 25.794 (for the deterministic case) to $ 28.097 (for the most conservative case) due to the uncertainty of real-time market prices. Due to power shortages caused by the failure of components, the total expected not-supplied load is 6.72 kW (2.53%). A comparison between a naive, and self-healing scheduling indicated that a naive energy management will charge additional $ 2.75 without considering the probability of components failures under the deterministic case.

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Section: A Resiliency-based Energy Managementmentioning

confidence: 99%

Optimal Scheduling of a Self-Healing Building Using Hybrid Stochastic-Robust Optimization Approach

Dibavar

Mohammadi‐Ivatloo

Zare

et al. 2022

IEEE Trans. on Ind. Applicat.

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“…The installation of more complicated and networked devices for monitoring, communication, and control characterizes the digitalization trend. Adequate planning, flexible operations, and technology concerning controls, protection, cyber-physical dependencies, black start, resilience frameworks, markets, forecasting, and capacity expansion models are some significant gaps in areas of research that will aid in addressing these developments in an interlinked manner [59].…”

Section: Literature Review On Components Of Hpsmentioning

confidence: 99%

“…From all renewable energy sources, solar thermal power is exceptionally facilitating and commonly deployed. Parabolic trough solar collector (PTC) is one of the most mature and tested solar thermal technologies with a substantial contribution possibility in the energy sector [59]. Spain is leading the way in combined solar thermal power with an installed capacity of 2370 MW, surpassed by the USA with a capacity of 1836 MW.…”

Section: Solar Thermal Renewable Generating Units In Hpsmentioning

confidence: 99%

Isolated and Interconnected Multi-Area Hybrid Power Systems: A Review on Control Strategies

et al. 2021

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Concerned with the increasing greenhouse gases in the atmosphere due to fossil fuels, the entire world is focusing on electricity generation through renewable energy resources. The most advantageous aspect of the distributed renewable sources is to provide the electricity to remote, scattered and the deprived rural areas by developing the hybrid power system at the smaller scale where power transmission through grid extension is not viable due to some economical, technical or environmental constraints for building new transmission lines. An accurate and adequate control strategy becomes inevitable to uphold the smooth operation by restraining the frequency and voltage deviation within its limit ensuring the highest degree of reliability of hybrid power system to provide an adequate power quality. In this paper, a comprehensive review of different control strategies adopted in isolated and interconnected multi-area hybrid power systems is presented.

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“…Fundamental changes in generation structure and profiles alongside increased demands for robustness and resilience have created the need for new operational and planning practices for modern networks. Cicilio et al [18] reviewed research that explores the changing generation profile, cutting-edge practices to address resilience and the combination of both topics. Other scholars have offered integrated decision-making analyses to characterise resilience, robustness, restoration agility and load criticality [19,20].…”

Section: Introductionmentioning

confidence: 99%

Integrated Risk Assessment for Robustness Evaluation and Resilience Optimisation of Power Systems after Cascading Failures

Beyza

Yusta

2021

Energies

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Power systems face failures, attacks and natural disasters on a daily basis, making robustness and resilience an important topic. In an electrical network, robustness is a network’s ability to withstand and fully operate under the effects of failures, while resilience is the ability to rapidly recover from such disruptive events and adapt its structure to mitigate the impact of similar events in the future. This paper presents an integrated framework for jointly assessing these concepts using two complementary algorithms. The robustness model, which is based on a cascading failure algorithm, quantifies the degradation of the power network due to a cascading event, incorporating the circuit breaker protection mechanisms of the power lines. The resilience model is posed as a mixed-integer optimisation problem and uses the previous disintegration state to determine both the optimal dispatch and topology at each restoration stage. To demonstrate the applicability of the proposed framework, the IEEE 118-bus test network is used as a case study. Analyses of the impact of variations in both generation and load are provided for 10 simulation scenarios to illustrate different network operating conditions. The results indicate that a network’s recovery could be related to the overload capacity of the power lines. In other words, a power system with high overload capacity can withstand higher operational stresses, which is related to increased robustness and a faster recovery process.

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Resilience in an Evolving Electrical Grid

Cited by 24 publications

References 136 publications

Optimal Scheduling of a Self-Healing Building Using Hybrid Stochastic-Robust Optimization Approach

Optimal Scheduling of a Self-Healing Building Using Hybrid Stochastic-Robust Optimization Approach

Isolated and Interconnected Multi-Area Hybrid Power Systems: A Review on Control Strategies

Integrated Risk Assessment for Robustness Evaluation and Resilience Optimisation of Power Systems after Cascading Failures

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