Interconnected multi-machine power system stabilizer design using whale optimization algorithm

Butti, Dasu; Mangipudi, Sivakumar; Rayapudi, Srinivasarao

doi:10.1186/s41601-019-0116-6

Cited by 77 publications

(42 citation statements)

References 38 publications

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“…The central location of box plot [43] represents the median value and the middle box contains 50% of the samples. The upper and lower edges of the box are the upper and lower quartiles of sample.…”

Section: Case Study and Discussionmentioning

confidence: 99%

Optimum Location and Parameter Setting of STATCOM Based on Improved Differential Evolution Harmony Search Algorithm

Zhang

et al. 2020

IEEE Access

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Identification of the optimum location and capacity of Static Synchronous Compensator (STAT-COM) in power grids has been given much attention to maximize its technical performance while minimizing operational cost. In this regard, a new multi-objective optimization model that minimizes power loss, enhances system stability and reduces operational cost of STATCOMs is presented in this paper. To overcome the issue of the harmony search (HS) optimization algorithm in solving high-dimensional multi-objective optimization problem, an improved differential evolution harmony search (DEHS) algorithm is proposed. In this algorithm, mutation and crossover operations are adopted instead of the original pitch adjustment operation adopted in the HS optimization algorithm, which enhances the algorithm global search ability. Moreover, opposition-based learning technique is incorporated to the process to broaden the diversity of variables and hence improving the search efficiency of the algorithm. The proposed algorithm is employed to identify the optimal allocation and sizing of multiple STATCOMs within the IEEE 30-bus system. Results reveal the superiority of the proposed optimization algorithm over the conventional multi-objectives adaptive harmony search algorithm. INDEX TERMS Flexible ac transmission systems, static synchronous compensator, system optimization, harmony search algorithm.

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Section: Case Study and Discussionmentioning

confidence: 99%

Optimum Location and Parameter Setting of STATCOM Based on Improved Differential Evolution Harmony Search Algorithm

Zhang

et al. 2020

IEEE Access

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“…These algorithms require a minimum time to optimize the design parameters of any complex engineering problem when compared with the conventional optimization techniques. Simulated annealing, tabu search, genetic algorithm, PSO, ant‐directed hybrid differential evolution, bacteria foraging algorithm, honey‐bee colony algorithm, harmony search algorithm, cuckoo algorithm, chaotic–teaching‐learning methods, grey wolf algorithm, bat algorithm, water cycle algorithm, backtracking search algorithm, gradient‐based metaheuristic algorithm, whale optimization algorithm, gravitational search agorithm, and minimax polynomial approximation using PSO‐based PSS design techniques are developed by many researchers from the last few years. Though several methods are developed, optimal design of PSS for the highly nonlinear multi‐machine interconnected power system operating at different loading conditions is still essential for robust operation.…”

Section: Introductionmentioning

confidence: 99%

An improved whale optimization algorithm for the design of multi‐machine power system stabilizer

Butti¹,

Mangipudi²,

Rayapudi

2020

Int Trans Electr Energ Syst

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Summary An improved whale optimization algorithm (IWOA) for the design of a robust power system stabilizer (PSS) for the multi‐machine power system is developed in this paper. Tuning of PSS parameters using the proposed IWOA is carried out by minimizing a multi‐objective function comprising the damping ratio and damping factor of lightly damped oscillating modes of all the generators. The advantage of considering the objective function is that the lightly damped and undamped oscillating modes of all the generators can shift to a prespecified zone of the s‐plane. The performance of the proposed IWOA is tested on standard benchmark test functions and compared with familiar optimization algorithms. The efficacy of the proposed design technique is tested on three benchmark test systems: three‐generator nine‐bus system, two‐area four‐machine interconnected system, and the New England 10‐generator 39‐bus system working on various operating conditions under several typical disturbances. The potential of the proposed method is demonstrated through eigenvalue analysis. The proposed IWOA‐based PSS is compared with the other stabilizers to show its efficacy.

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“…In [42], two controllers, one for excitation and the other for the governor, are proposed to enhance system stability in the case of controller failure. The PSS design for a multi-machine system is developed using a whale optimization technique [43], while the effect of penetration of wind farms on small signal stability is studied in [44]. To cater for the multiple requirements of power systems, a wide area damping controller is designed in [45].…”

Section: Introductionmentioning

confidence: 99%

Design of a robust PID-PSS for an uncertain power system with simplified stability conditions

Vijaya

Manyala

Mangipudi³

2020

Prot Control Mod Power Syst

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In a deregulated power system uncertainty exists and lack of sufficient damping can lead to Low Frequency Oscillations (LFO). The problem can be addressed using robust Power System Stabilizers (PSS). In this paper, an optimal procedure to design a robust PID-PSS using interval arithmetic for the Single Machine Infinite Bus (SMIB) power system is proposed. The interval modelling captures the wide variations of operating conditions in bounds of system coefficients. In the proposed design procedure, simple and new closed loop stability conditions for an SMIB interval system are developed and are used to design an optimum PID-PSS for improving the performance of an SMIB system. The optimum PID-PSS is attained by tuning the parameters using the FMINCON tool provided in MATLAB. The robustness of the proposed PID-PSS design is validated and compared to other notable methods in the literature when the system is subjected to different uncertainties. The simulation results and performance error values show the effectiveness of the proposed robust PID-PSS controller.

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Interconnected multi-machine power system stabilizer design using whale optimization algorithm

Cited by 77 publications

References 38 publications

Optimum Location and Parameter Setting of STATCOM Based on Improved Differential Evolution Harmony Search Algorithm

Optimum Location and Parameter Setting of STATCOM Based on Improved Differential Evolution Harmony Search Algorithm

An improved whale optimization algorithm for the design of multi‐machine power system stabilizer

Design of a robust PID-PSS for an uncertain power system with simplified stability conditions

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