Accurate estimation of modern power system harmonics using a novel LSA hybridized recursive least square technique

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ashok Bhoi ◽  
Ranjan Kumar Mallick ◽  
Gayadhar Panda ◽  
Pravati Nayak
Keyword(s):  
Power System ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Least Square ◽  
Computational Time ◽  
Natural Phenomenon ◽  
Accurate Estimation ◽  
Hybrid Technique ◽  
Recursive Least Square ◽  
Time Data

Abstract This paper purposes a new type of hybrid technique depends on lightning search algorithm (LSA) and recursive least square (RLS) named as LSA-RLS to overcome the harmonic estimation issues in time varying modern power system signals buried with noises. LSA is based on a natural phenomenon of lightning. It consists of three types of projectiles: transition, space and lead projectiles. Transition projectiles create population, space projectiles do the exploration and the lead projectiles do the work of exploitation and find the optimal solution. The basic LSA algorithm is mixed with RLS algorithm in an adaptive way to estimate the states of the harmonic signals. Simulation and validation are made with real time data obtained from a converter fed D.C motor drive. The efficacy of the proposed algorithm is verified by comparing the simulation results of recently reported algorithms such as particle swarm optimization (PSO), differential evolution (DE), bacteria foraging optimization (BFO), gravity search algorithm hybridized recursive least square method (GSA-RLS). It is verified that proposed (LSA-RLS) technique is the best in terms of computational time, convergence, accuracy.

Kernel Recursive Least Square Approach for Power System Harmonic Estimation

2021 ◽  
pp. 1-16
Author(s):  
Omar Avalos ◽  
Erik Cuevas ◽  
Héctor G. Becerra ◽  
Jorge Gálvez ◽  
Salvador Hinojosa ◽  
...  
Keyword(s):  
Power System ◽  
Least Square ◽  
Recursive Least Square ◽  
Least Square Approach

Optimal Design of Power System Stabilizer Using a Novel Evolutionary Algorithm

2018 ◽  
Vol 7 (3) ◽  
pp. 24-46
Author(s):  
Sourav Paul ◽  
Provas Roy
Keyword(s):  
Optimal Design ◽  
Power System ◽  
Search Algorithm ◽  
Low Frequency ◽  
Optimal Solution ◽  
Power System Stabilizer ◽  
Low Frequency Oscillation ◽  
Large Power ◽  
Wide Range ◽  
System Stabilizer

In this article, an Oppositional Differential search algorithm (ODSA) is comprehensively developed and successfully applied for the optimal design of power system stabilizer (PSS) parameters which are added to the excitation system to dampen low frequency oscillation as it pertains to large power system. The effectiveness of the proposed method is examined and validated on a single machine infinite bus (SMIB) using the Heffron-Phillips model. The most important advantage of the proposed method is as it reaches toward the optimal solution without the optimal tuning of input parameters of the ODSA algorithm. In order to verify the effectiveness, the simulation was made for a wide range of loading conditions. The simulation results of the proposed ODSA are compared with those obtained by other techniques available in the recent literature to demonstrate the feasibility of the proposed algorithm.

scholarly journals Optimal economic dispatch of power generation solution using lightning search algorithm

2020 ◽  
Vol 9 (3) ◽  
pp. 371
Author(s):  
Murad Yahya Nassar ◽  
Mohd Noor Abdullah ◽  
Asif Ahmed Rahimoon
Keyword(s):  
Power Generation ◽  
Power System ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Thermal Power ◽  
Economic Dispatch ◽  
Optimal Solution ◽  
Fuel Price ◽  
Solution Quality ◽  
Generation Cost

Economic dispatch (ED) is the power demand allocating process for the committed units at minimum generation cost while satisfying system and operational constraints. Increasing cost of fuel price and electricity demand can increase the cost of thermal power generation. Therefore, robust and efficient optimization algorithm is required to determine the optimal solution for ED problem in power system operation and planning. In this paper the lightning search algorithm (LSA) is proposed to solve the ED problem. The system constraints such as power balance, generator limits, system transmission losses and valve-points effects (VPE) are considered in this paper. To verify the effectiveness of LSA in terms of convergence characteristic, robustness, simulation time and solution quality, the two case studies consists of 6 and 13 units have been tested. The simulation results show that the LSA can provide optimal cost than many methods reported in literature. Therefore, it has potential to solve many optimization problems in power dispatch and power system applications.

Noise Removal from EMG Signal Using Adaptive Enhanced Squirrel Search Algorithm

2020 ◽  
Vol 19 (04) ◽  
pp. 2050039
Author(s):  
B. Nagasirisha ◽  
V. V. K. D. V. Prasad
Keyword(s):  
Adaptive Filters ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Maximum Error ◽  
Noise Removal ◽  
Least Square ◽  
Mean Square ◽  
Least Mean Square ◽  
Recursive Least Square ◽  
Emg Signal

Electromyogram (EMG) signals are mostly affected by a large number of artifacts. Most commonly affecting artifacts are power line interference (PLW), baseline noise and ECG noise. This work focuses on a novel attenuation noise removal strategy which is concentrated on adaptive filtering concepts. In this paper, an enhanced squirrel search (ESS) algorithm is applied to remove noise using adaptive filters. The noise eliminating filters namely adaptive least mean square (LMS) filter and adaptive recursive least square (RLS) filters are designed, which is correlated with an ESS. This novel algorithm yields better performance than other existing algorithms. Here the performances are measured in terms of signal-to-noise ratio (SNR) in decibel, maximum error (ME), mean square error (MSE), standard deviation, simulation time and mean value difference. The proposed work has been implemented at the MATLAB simulation platform. Testing of their noise attenuation capability is also validated with different evolutionary algorithms namely squirrel search, particle swarm optimization (PSO), artificial bee colony (ABC), firefly, ant colony optimization (ACO) and cuckoo search (CS). The proposed work eliminates the noises and provides noise-free EMG signal at the output which is highly efficient when compared with existing methodologies. Our proposed work achieves 4%, 40%, 4%, 7%, 9% and 70% better performance than the literature mentioned in the results.

scholarly journals Online Parameter Identification of Lithium-Ion Batteries Using a Novel Multiple Forgetting Factor Recursive Least Square Algorithm

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3180 ◽  
Author(s):  
Bizhong Xia ◽  
Rui Huang ◽  
Zizhou Lao ◽  
Ruifeng Zhang ◽  
Yongzhi Lai ◽  
...  
Keyword(s):  
Parameter Identification ◽  
Lithium Ion ◽  
Least Square ◽  
Estimation Methods ◽  
Accurate Estimation ◽  
Model Parameters ◽  
Identification Algorithm ◽  
Recursive Least Square ◽  
Forgetting Factor ◽  
Temperature State

The model parameters of the lithium-ion battery are of great importance to model-based battery state estimation methods. The fact that parameters change in different rates with operation temperature, state of charge (SOC), state of health (SOH) and other factors calls for an online parameter identification algorithm that can track different dynamic characters of the parameters. In this paper, a novel multiple forgetting factor recursive least square (MFFRLS) algorithm was proposed. Forgetting factors were assigned to each parameter, allowing the algorithm to capture the different dynamics of the parameters. Particle swarm optimization (PSO) was utilized to determine the optimal forgetting factors. A state of the art SOC estimator, known as the unscented Kalman filter (UKF), was combined with the online parameter identification to create an accurate estimation of SOC. The effectiveness of the proposed method was verified through a driving cycle under constant temperature and three different driving cycles under varied temperature. The single forgetting factor recursive least square (SFFRLS)-UKF and UKF with fixed parameter were also tested for comparison. The proposed MFFRLS-UKF method obtained an accurate estimation of SOC especially when the battery was running in an environment of changing temperature.

scholarly journals A Novel Hybrid GWO-LS Estimator for Harmonic Estimation Problem in Time Varying Noisy Environment

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2587
Author(s):  
Muhammad Abdullah ◽  
Tahir N. Malik ◽  
Ali Ahmed ◽  
Muhammad F. Nadeem ◽  
Irfan A. Khan ◽  
...  
Keyword(s):  
Power Quality ◽  
Minimum Mean Square Error ◽  
Linear Part ◽  
Electrical Power ◽  
Least Square ◽  
Computational Time ◽  
Grey Wolf Optimizer ◽  
Hybrid Technique ◽  
Electrical Power System

The power quality of the Electrical Power System (EPS) is greatly affected by electrical harmonics. Hence, accurate and proper estimation of electrical harmonics is essential to design appropriate filters for mitigation of harmonics and their associated effects on the power quality of EPS. This paper presents a novel statistical (Least Square) and meta-heuristic (Grey wolf optimizer) based hybrid technique for accurate detection and estimation of electrical harmonics with minimum computational time. The non-linear part (phase and frequency) of harmonics is estimated using GWO, while the linear part (amplitude) is estimated using the LS method. Furthermore, harmonics having transients are also estimated using proposed harmonic estimators. The effectiveness of the proposed harmonic estimator is evaluated using various case studies. Comparing the proposed approach with other harmonic estimation techniques demonstrates that it has a minimum mean square error with less complexity and better computational efficiency.

scholarly journals Edible Gelatin Diagnosis Using Laser-Induced Breakdown Spectroscopy and Partial Least Square Assisted Support Vector Machine

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4225 ◽  
Author(s):  
Hao Zhang ◽  
Shun Wang ◽  
Dongxian Li ◽  
Yanyan Zhang ◽  
Jiandong Hu ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Partial Least Square ◽  
Least Square ◽  
Computational Time ◽  
Laser Induced Breakdown Spectroscopy ◽  
Accurate Estimation ◽  
Support Vector ◽  
Breakdown Spectroscopy ◽  
Svm Model ◽  
Laser Induced Breakdown

Edible gelatin has been widely used as a food additive in the food industry, and illegal adulteration with industrial gelatin will cause serious harm to human health. The present work used laser-induced breakdown spectroscopy (LIBS) coupled with the partial least square–support vector machine (PLS-SVM) method for the fast and accurate estimation of edible gelatin adulteration. Gelatin samples with 11 different adulteration ratios were prepared by mixing pure edible gelatin with industrial gelatin, and the LIBS spectra were recorded to analyze their elemental composition differences. The PLS, SVM, and PLS-SVM models were separately built for the prediction of gelatin adulteration ratios, and the hybrid PLS-SVM model yielded a better performance than only the PLS and SVM models. Besides, four different variable selection methods, including competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variable elimination (MC-UVE), random frog (RF), and principal component analysis (PCA), were adopted to combine with the SVM model for comparative study; the results further demonstrated that the PLS-SVM model was superior to the other SVM models. This study reveals that the hybrid PLS-SVM model, with the advantages of low computational time and high prediction accuracy, can be employed as a preferred method for the accurate estimation of edible gelatin adulteration.

Harmony Search Algorithm

2018 ◽  
pp. 1-30 ◽  
Author(s):  
Alireza Askarzadeh ◽  
Esmat Rashedi
Keyword(s):  
Optimization Problems ◽  
Search Algorithm ◽  
Harmony Search ◽  
Optimal Solution ◽  
Harmony Search Algorithm ◽  
Computational Time ◽  
Engineering Applications ◽  
Heuristic Search Algorithm ◽  
And Performance ◽  
Significant Attention

Harmony search (HS) is a meta-heuristic search algorithm which tries to mimic the improvisation process of musicians in finding a pleasing harmony. In recent years, due to some advantages, HS has received a significant attention. HS is easy to implement, converges quickly to the optimal solution and finds a good enough solution in a reasonable amount of computational time. The merits of HS algorithm have led to its application to optimization problems of different engineering areas. In this chapter, the concepts and performance of HS algorithm are shown and some engineering applications are reviewed. It is observed that HS has shown promising performance in solving difficult optimization problems and different versions of this algorithm have been developed. In the next years, it is expected that HS is applied to more real optimization problems.

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