Fragility analysis of nuclear power plant structure under real and spectrum-compatible seismic waves considering soil-structure interaction effect

Cheng, Feng; Li, Jianbo; Zhou, Lei; Gao, Lin

doi:10.1016/j.engstruct.2023.115684

Cited by 30 publications

(6 citation statements)

References 34 publications

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“…We also noticed the sudden OLR increase prior to both the EQs. This was due to the sudden EQ energy release along with the various outward flowing radiations [59][60][61][62][63]. Shahzad et al [48] recommended that the OLR can be used as an efficient tool for short term anomalies of the impending EQs.…”

Section: Discussionmentioning

confidence: 99%

Machine-Learning-Based Lithosphere-Atmosphere-Ionosphere Coupling Associated with Mw > 6 Earthquakes in America

et al. 2023

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The identification of atmospheric and ionospheric variations through multiple remote sensing and global navigation satellite systems (GNSSs) has contributed substantially to the development of the lithosphere-atmosphere-ionosphere coupling (LAIC) phenomenon over earthquake (EQ) epicenters. This study presents an approach for investigating the Petrolia EQ (Mw 6.2; dated 20 December 2021) and the Monte Cristo Range EQ (Mw 6.5; dated 15 May 2020) through several parameters to observe the precursory signals of various natures. These parameters include Land Surface Temperature (LST), Air Temperature (AT), Relative Humidity (RH), Air Pressure (AP), Outgoing Longwave Radiations (OLRs), and vertical Total Electron Content (TEC), and these are used to contribute to the development of LAIC in the temporal window of 30 days before and 15 days after the main shock. We observed a sharp increase in the LST in both the daytime and nighttime of the Petrolia EQ, but only an enhancement in the daytime LST for the Monte Cristo Range EQ within 3–7 days before the main shock. Similarly, a negative peak was observed in RH along with an increment in the OLR 5–7 days prior to both impending EQs. Furthermore, the Monte Cristo Range EQ also exhibited synchronized ionospheric variation with other atmospheric parameters, but no such co-located and synchronized anomalies were observed for the Petrolia EQ. We also applied machine learning (ML) methods to confirm these abrupt variations as anomalies to further aid certain efforts in the development of the LAIC in order to forecast EQs in the future. The ML methods also make prominent the variation in the different data.

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Section: Discussionmentioning

confidence: 99%

Machine-Learning-Based Lithosphere-Atmosphere-Ionosphere Coupling Associated with Mw > 6 Earthquakes in America

et al. 2023

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“…It expresses as single or multi-objective function [72][73]. Optimization problem includes the different constraints [74][75][76][77][78][79][80]. Constraints are as equality and inequality formulation [81][82][83][84][85][86][87].…”

Section: Vpp Constraintsmentioning

confidence: 99%

Network‐constrained unit commitment‐based virtual power plant model in the day‐ahead market according to energy management strategy

Pirouzi

2023

IET Generation Trans & Dist

105

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Energy management of a virtual power plant (VPP) that consists of wind farm (WF), energy storage systems and a demand response program is discussed in the present study. The introduced strategy is realized at the electrical power transmission level and takes into account the collaboration between VPPs in day‐ahead energy and reserve markets. One notable feature of the proposed strategy is attempting to make the revenue of VPPs close to the operating cost of generating units as much as possible. The objective function is subjected to the network‐constrained unit commitment model, up and down reserve requirements and the proposed VPP constraints. This method is taking into account the uncertainty in system and VPP loads, day‐ahead market energy and reserve price and WF power generation. This strategy is applied as hybrid stochastic‐robust scheduling to the VPP at the electrical power transmission level, where the scenario‐based stochastic programming models the uncertainty of day‐ahead market prices, and the bounded uncertainty‐based robust optimization has been adopted to model the uncertainties related to the load and WF power. Scheme has been tested on IEEE systems. According to the obtained results, the proposed coordination of VPPs in the mentioned markets demonstrates capability of suggested strategy.

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“…It expresses as single or multi-objective formulation [59]. Optimization problem includes the different constraints [60][61][62][63][64][65]. Constraints are as equality or inequality formulation [66][67][68][69][70][71].…”

Section: Lower-level Problemmentioning

confidence: 99%

Resilience‐oriented expansion planning of multi‐carrier microgrid utilizing bi‐level technique

Dehshiri Badi,

Amir,

Shariatmadar

2023

IET Renewable Power Gen

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This paper presents the generation and transmission expansion planning (GTEP) in electricity and gas networks by considering their resilience against floods and earthquakes. These networks supply electricity, heat, and gas consumption energies as a multi‐carrier microgrid. The scheme is expressed in the form of bi‐level optimization, the upper level of which is the minimization of generation and transmission planning cost (total investment cost and expected operating cost) in the mentioned networks constrained to the investment budget and the planning model of the mentioned elements. Lower‐level formulation minimizes the total expected annual operating cost of these networks and the expected outage cost of electricity, heat, and gas consumers in the event of floods and earthquakes. This formulation is bound by the power flow equations of electricity and gas networks, the operation and resilience constraints of the networks, and the limitation on generation capability. In this problem, the expected energy not‐supplied and the outage cost during natural disasters are considered resilience indicators. Next, a single‐level model for the proposed design is extracted from the Karush–Kuhn–Tucker (KKT) method. The basic requirement of this method is the convexity of the lower‐level constraints. For this purpose, first, a linear approximation model is obtained for the lower‐level constraints of the problem. Furthermore, stochastic optimization is adopted to model the uncertainty of load, renewable power, and network equipment availability during floods and earthquakes. Finally, the extracted numerical results confirm the capability of the proposed scheme in improving the operation and resilience of the mentioned networks using optimal generation and transmission planning.

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Fragility analysis of nuclear power plant structure under real and spectrum-compatible seismic waves considering soil-structure interaction effect

Cited by 30 publications

References 34 publications

Machine-Learning-Based Lithosphere-Atmosphere-Ionosphere Coupling Associated with Mw > 6 Earthquakes in America

Machine-Learning-Based Lithosphere-Atmosphere-Ionosphere Coupling Associated with Mw > 6 Earthquakes in America

Network‐constrained unit commitment‐based virtual power plant model in the day‐ahead market according to energy management strategy

Resilience‐oriented expansion planning of multi‐carrier microgrid utilizing bi‐level technique

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