Resilient power network structure for stable operation of energy systems: A transfer learning approach

Huang, Wanjun; Zhang, Xinran; Zheng, Weiye

doi:10.1016/j.apenergy.2021.117065

Cited by 20 publications

(4 citation statements)

References 33 publications

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“…The location and sizing of components in electrical energy systems are also determined by various approaches such as data-driven models [116,120,123]. The influence of EVs and parking lots is analysed in [122,124] and eventually, References [118,119,121] present modification strategies or transmission line expansion to enhance resiliency versus extreme events.…”

Section: Optimal Location and Sizing Of Sourcesmentioning

confidence: 99%

Electrical energy systems resilience: A comprehensive review on definitions, challenges, enhancements and future proceedings

Amini

Zadeh

Rostami

et al. 2023

IET Renewable Power Gen

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Secure energy providing is a critical feature of sustainable societies, where this subject requires reliable operation of generation, transmission and distribution infrastructures. In order to achieve the mentioned goal, the influence of uncertainties should be analyzed using appropriate methods, criteria and tools. The high‐impact low‐probability (HILP) events are special uncertainties that can affect the safe operation and lead to irreparable damages. This paper presents a comprehensive review of resilience in electrical energy systems consisting of fundamental concepts and definitions, challenges, enhancements and future proceedings. In this regard, a resilience evaluation framework is designed first in which all the necessary actions for a resilience study are defined. In the next step, various HILP events are introduced and then the resilience concept is defined accurately and related curves are investigated. Afterwards, the resilience assessment indices and quantitative measures are described and their details and applications are precisely explained. As well, the resilience enhancement strategies are discussed from short‐term and long‐term perspectives and eventually, resilience‐based objective functions and optimization approaches are classified in the last part. It is noteworthy that the main research gaps are also clarified according to the reviewed papers and further suggestions are expressed to cope with the declared problems.

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Section: Optimal Location and Sizing Of Sourcesmentioning

confidence: 99%

Electrical energy systems resilience: A comprehensive review on definitions, challenges, enhancements and future proceedings

Amini

Zadeh

Rostami

et al. 2023

IET Renewable Power Gen

View full text Add to dashboard Cite

show abstract

“…Voltage stability [175]- [178] Security and cascading failure assessment [179]- [182] Transient stability [183]- [186] Building-level event detection Occupancy and activity [187]- [190] Fault diagnosis in appliances [191]- [194] Optimal power flow End-to-end learning [195]- [198] Learning-augmented [199]- [202] Energy management & control Demand side management Heating/Cooling loads [203]- [206] Demand-response [207]- [210] Buildings [211]- [214] Communities [215]- [218] Microgrids [219]- [222] Load frequency control [223]- [226] Voltage control [227]- [230] Grid variables estimation/ identification Phase [231]- [234] Topology and lines parameters [235]- [238] State estimation [239]- [242] Voltage calculation [243]- [246] FIGURE 9: Further decomposition of analytics services (II). Four indicative references are given for each analytics category.…”

Section: Analytics Cybersecuritymentioning

confidence: 99%

“…• Stability analysis: Data-driven methods that assess the ability of the distribution grid to maintain steady-state operation under various operating conditions. We split the literature into three services: voltage stability un-der various operating conditions [175]- [178], security and cascading failure assessment under fault conditions [179]- [182], and stability under transient conditions [183]- [186]. • Building-level event detection: Data-driven methods to detect and identify significant events or anomalies in the energy consumption patterns of individual buildings.…”

Section: Analytics Cybersecuritymentioning

confidence: 99%

Data-Driven Analytics for Reliability in the Buildings-to-Grid Integrated System Framework: A Systematic Text-Mining-Assisted Literature Review and Trend Analysis

Bachoumis,

Mylonas,

Plakas

et al. 2023

IEEE Access

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Data-driven machine learning-based methods have provided immense capabilities, revolutionizing sectors like the Buildings-to-grid (B2G) integrated system. Since the penetration rate of distributed energy resources increases towards a net-zero emissions power system, so does the need for advanced services that ensure B2G-integrated system reliability. The convergence of advancements in machine learning, computational resources at the entire cloud-edge continuum, and large datasets from sensing devices enable the development of these data-driven energy analytics services. This work conducts a systematic text-mining-based literature review to examine the diverse range and trends of machine learning methods used to enhance reliability in B2G-integrated systems. While traditional manual sampling and analysis approaches have limited the effectiveness of previous literature review papers in this field, this systematic literature review work aims to synthesize and summarize the existing body of research more efficiently and effectively. To achieve this, this study collected almost 10,500 papers from Scholar and Scopus databases. It employed text-mining-assisted BERTopic-based topic modelling and statistical trend analysis techniques to uncover semantic patterns and explore the temporal evolution of research themes. A two-dimensional taxonomy was derived to analyze the technical papers from a business and machine learning-related perspective. By quantifying the temporal trends within these topics, the study unveiled insights about the state-of-the-art analytics that ensure reliability in the B2G-integrated system domain while proposing future research directions.

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“…These disturbances include, for instance, load changes or network interruptions (transients). Fast and frequent fluctuations in load are difficult for the generator to handle, which can jeopardize the dynamic stability of the system [7]. As a result, frequency oscillations occur in the generator.…”

Section: Multy Systemmentioning

confidence: 99%

Stability Simulation of 150 kV Malang Power Grid

Fujita

2022

FESPE

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This research describes the oscillation control based on a power system that takes the place of the traditional automatic voltage regulators for excitation control in addition to a multimachine power system. The design is built on equilibrium and a potent adaptive critic technique called decreasing time oscillation for each generator. The generators' local measurements serve as the sole basis for the feedback variables. For enhancing the dynamic performance and stability of the power grid under significant shocks that affected oscillation power stations, simulations on multi-machine power systems were shown to be effective.

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Resilient power network structure for stable operation of energy systems: A transfer learning approach

Cited by 20 publications

References 33 publications

Electrical energy systems resilience: A comprehensive review on definitions, challenges, enhancements and future proceedings

Electrical energy systems resilience: A comprehensive review on definitions, challenges, enhancements and future proceedings

Data-Driven Analytics for Reliability in the Buildings-to-Grid Integrated System Framework: A Systematic Text-Mining-Assisted Literature Review and Trend Analysis

Stability Simulation of 150 kV Malang Power Grid

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