Real-Time Resilience Optimization Combining an AI Agent With Online Hard Optimization

Yang, Zejun; Martí, José

doi:10.1109/tpwrs.2021.3088376

Cited by 15 publications

(3 citation statements)

References 28 publications

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“…Figure 1 [3] shows the various stages involved in recovering a system damaged by a disaster, from preparation to recovery. The post-disaster period can be divided into immediately after a disaster, days after, weeks after, and months after.…”

Section: System Resiliencementioning

confidence: 99%

Introductory Chapter: Critical Infrastructure – Modern Approach and New Developments

Di Pietro,

Martì

2024

Critical Infrastructure - Modern Approach and New Developments

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Section: System Resiliencementioning

confidence: 99%

Introductory Chapter: Critical Infrastructure – Modern Approach and New Developments

Di Pietro,

Martì

2024

Critical Infrastructure - Modern Approach and New Developments

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“…To enhance the precision of assessing customer welfare, we introduce the concept of the Human Readable Table (HRT) to gauge consumer satisfaction regarding energy consumption while considering the quality of services (QoS). This concept draws inspiration from the Infrastructure Interdependencies Simulator (i2SIM) [10]- [14], a system simulator developed at the University of British Columbia's Complex Systems Integration Laboratory, which models the interdependencies of diverse systems. We have several reasons for proposing the HRT for welfare calculation:…”

Section: Human Readable Tablementioning

confidence: 99%

Home Energy Management combining a welfare calculation and Vehicle-to-house technique for grid stability

2024

ACE

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The increasing adoption of electric vehicles (EVs) poses grid stability challenges. This study explores Home Energy Management (HEM) systems, facilitating bidirectional communication between users and energy providers to address these issues. We review HEM methods, including ZigBee, PLC control, and reinforcement learning, optimizing household energy usage. We investigate the incorporation of welfare calculation, accounting for occupants' well-being, and introduce the potential of Vehicle-to-Home (V2H) technology for enhancing energy resilience. Combining welfare calculation and V2H offers optimized HEM, prioritizing user comfort and decision-making efficiency. This report identifies research gaps and emphasizes the significance of delay-intolerant and delay-tolerant demand considerations. Battery charge-discharge conditions and utility welfare calculation are also discussed as critical facets of HEM. To solve the delay intolerant demand issue, EVs are used as storage devices to mitigate the peak load impacts using vehicle-to-house (V2H) technology. A scaled-down version (1:10^6) of the real UK electricity consumption system is used in the test. Simulation results verify that the proposed V2H system considering the welfare calculation can optimize the welfare level when one 60-kWh Tesla EV is involved in this scaled-down system.

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“…The authors demonstrate that their method ensures system observability pre-and post-reconfiguration, even under varying load levels and topologies. Reference [116] presents a novel Soft-Hard Optimal Convergence (SHOC) strategy that combines AI and algorithmic optimization to enhance the resilience of electrical distribution systems in large cities. The SHOC strategy, which uses machine learning to train an AI agent with offline scenarios, enables rapid calculation of optimal reconfiguration and recovery paths post-disaster.…”

Section: System Reconfigurationmentioning

confidence: 99%

AI Applications to Enhance Resilience in Power Systems and Microgrids—A Review

Zahraoui,

Korõtko,

Rosin

et al. 2024

Sustainability

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This paper presents an in-depth exploration of the application of Artificial Intelligence (AI) in enhancing the resilience of microgrids. It begins with an overview of the impact of natural events on power systems and provides data and insights related to power outages and blackouts caused by natural events in Estonia, setting the context for the need for resilient power systems. Then, the paper delves into the concept of resilience and the role of microgrids in maintaining power stability. The paper reviews various AI techniques and methods, and their application in power systems and microgrids. It further investigates how AI can be leveraged to improve the resilience of microgrids, particularly during different phases of an event occurrence time (pre-event, during event, and post-event). A comparative analysis of the performance of various AI models is presented, highlighting their ability to maintain stability and ensure a reliable power supply. This comprehensive review contributes significantly to the existing body of knowledge and sets the stage for future research in this field. The paper concludes with a discussion of future work and directions, emphasizing the potential of AI in revolutionizing power system monitoring and control.

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Real-Time Resilience Optimization Combining an AI Agent With Online Hard Optimization

Cited by 15 publications

References 28 publications

Introductory Chapter: Critical Infrastructure – Modern Approach and New Developments

Introductory Chapter: Critical Infrastructure – Modern Approach and New Developments

Home Energy Management combining a welfare calculation and Vehicle-to-house technique for grid stability

AI Applications to Enhance Resilience in Power Systems and Microgrids—A Review

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