Wind-resistant optimal design of tall buildings based on improved genetic algorithm

Li, Yi; Duan, Ru-Biao; Li, Qiusheng; Li, Yonggui; Huang, Xuan

doi:10.1016/j.istruc.2020.08.036

Cited by 19 publications

(7 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In these few decades, buildings become taller and many skyscrapers are constructed, and not only the seismic loads but also wind loads are important for building designing. Recently, many wind-resistant design methods are studied such as [1], [2], [3], and some devices are devised to suppress responses of wind loads [4], [5]. Moreover, some studies consider both seismic and wind loads to design a building [6], [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Wind-load estimation with equivalent-input-disturbance approach

Miyamoto

She

Chen

et al. 2022

2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)

View full text Add to dashboard Cite

This paper presents a new method to estimate an along-wind load that contains a mean component using an equivalent-input-disturbance approach. An along-wind force contains both mean and fluctuating components. However, most studies estimate only fluctuating components. Moreover, these studies assume that the damping matrix is a Rayleigh one. In contrast, this paper presents a method that estimates both the mean and fluctuating components using velocity response. Furthermore, this method does not require that the damping coefficient is Rayleigh damping. The numerical verification verifies using an 11 degree-of-freedom(DOF) model of a seismicisolated building. The results presented that the presented method accurately estimates an along-wind load.

show abstract

Section: Introductionmentioning

confidence: 99%

Wind-load estimation with equivalent-input-disturbance approach

Miyamoto

She

Chen

et al. 2022

2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)

View full text Add to dashboard Cite

show abstract

“…In this paper, GA is utilized for parameter optimization. The GA has been successfully applied to a variety of problems including, wind power forecast error, 14 hybrid solar wind battery system, 15 optimal power exchange facilitating in GENCO's bidding strategy, 16 optimal design for wind‐resistant tall buildings, 17 respectively. In Reference 18, the auxiliary controller is designed for the wind power system to enhance system damping under various wind speeds and its parameter are tuned by using GA.…”

Section: Introductionmentioning

confidence: 99%

“…These optimization techniques have proven efficient for many applications in the optimal tuning of control gain parameters. The GA and PSO are considered the most established algorithm for optimization and taken into consideration as the benchmark for optimization techniques 6,8,11,14‐17 . In this work, GA is used to design and optimize the damping controller parameters because of their capability, versatility, faster convergence, and efficient complex problems.…”

Section: Introductionmentioning

confidence: 99%

Parameter tuning of PSS and STATCOM controllers using genetic algorithm for improvement of small‐signal and transient stability of power systems with wind power

Bhukya

Mahajan

2021

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary This work demonstrates the impact and robust coordination control among the Doubly Induction Generator (DFIG) and Synchronous Generators (SGs) with Power Oscillation Damping (POD), Power System Stabilizer (PSS),and STATic synchronous COMpensator (STATCOM) on the critical Low‐Frequency Oscillations (LFOs). These modes occurred due to system uncertainty, which leads to power flow interruption and experiences instability. It is mitigated by the proposed location and optimal coordinated optimized gain parameters of the controller. The locations are determined using the deterministic method and power flow sensitivity analysis (PSS and STATCOM). The objective function for the Genetic Algorithm (GA) is chosen as the real part and damping ratio of eigenvalue deviation of rotor speed. The small‐signal stability is assessed by using eigenvalue analysis via linearization of a nonlinear system. The transient stability is performed through time‐domain simulation by creating a three‐phase fault. Both analyses are examined with and without POD, PSS, and STATCOM and their combination by substituting SG with the same capacity of Wind Farm (WF). It is also indicated that a combination of POD, PSS, and STATCOM enhances system stability. It is also observed that the WF could not significantly involve in the modes of oscillation alike to the SG but provides the damping and beneficial toward the stability. GA and optimal location improve the system damping characteristics over a wide range of system uncertainty. The effectiveness and robustness of the proposed approaches are verified by considering a two‐area modified test system. Highlights This work demonstrates the impact and robust coordination control among the DFIG and SGs with POD, PSS and STATCOM on the critical LFOs caused by the intermittent nature of wind power. The locations are determined using the deterministic method and power flow sensitivity analysis (PSS and STATCOM). The objective function for the GA is chosen as the real part and damping ratio of eigenvalue and rotor speed deviation. The obtained results show enhancement in system stability.

show abstract

“…33,34 However, as a gradient-based optimization algorithm, the OC algorithm may become trapped in a local optimum and cannot solve the optimization problem with discrete design variables. 34,35 Furthermore, it is challenging to apply OC in solving multi-objective optimization problems (IMOPs). With the development of computer technology, metaheuristic algorithms such as GA, [35][36][37] particle swarm optimization (PSO), 38,39 and firefly algorithm 40 have been applied in structural optimization.…”

mentioning

confidence: 99%

“…34,35 Furthermore, it is challenging to apply OC in solving multi-objective optimization problems (IMOPs). With the development of computer technology, metaheuristic algorithms such as GA, [35][36][37] particle swarm optimization (PSO), 38,39 and firefly algorithm 40 have been applied in structural optimization. A nondominated sorting genetic algorithm II (NSGA-II) was developed by Deb et al, 41 which is acknowledged to be one of the most classic multi-objective optimization methods.…”

mentioning

confidence: 99%

A multi‐objective structural optimization method for serviceability design of tall buildings

Huang,

Wang,

Lin

et al. 2023

Structural Design Tall Build

View full text Add to dashboard Cite

SummaryStructural optimization design aims to identify optimal design variables corresponding to a minimum objective function with constraints on performance requirements. To this end, many optimization frameworks have been proposed to determine optimal structural systems that are subjected to seismic and wind hazards in isolation. However, some modern tall buildings are sensitive to seismic and wind excitation owing to their complex structural systems and geographic regions. Therefore, a proper structural optimization method for such buildings is required to ensure that the expected performance is achieved in a multi‐hazard scenario. This study proposes a multi‐objective serviceability design optimization methodology for buildings in multi‐hazard seismic and wind environments by combining optimality criteria and the nondominated sorting genetic algorithm II (NSGA‐II). Seismic and wind effects can be instantaneously updated due to changes in the structural dynamic properties during the optimal design process. A neural‐network‐based surrogate model with self‐updating is proposed to predict the structural natural frequency so that the overall computation time of the optimization process can be reduced. The proposed method was used to optimize a 50‐story frame‐tube building and was compared against the general genetic algorithm and general NSGA‐II to verify the feasibility and effectiveness.

show abstract

Wind-resistant optimal design of tall buildings based on improved genetic algorithm

Cited by 19 publications

References 35 publications

Wind-load estimation with equivalent-input-disturbance approach

Wind-load estimation with equivalent-input-disturbance approach

Parameter tuning of PSS and STATCOM controllers using genetic algorithm for improvement of small‐signal and transient stability of power systems with wind power

A multi‐objective structural optimization method for serviceability design of tall buildings

Contact Info

Product

Resources

About