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(1+PD)-PID cascade controller design for performance betterment of load frequency control in diverse electric power systems
(Springer London Ltd, 2021) Celik, Emre; Ozturk, Nihat; Arya, Yogendra; Ocak, Cemil
In our world of today developing incredibly fast, load frequency control (LFC) is an indispensable and vital element in increasing the standard of living of a country by providing a good quality of electric power. To this end, rapid and notable development has been recorded in LFC area. However, researchers worldwide need for the existence of not only effective but also computationally inexpensive control algorithm considering the limitations and difficulties in practice. Hence, this paper deals with the introduction of (1 + PD)-PID cascade controller to the relevant field. The controller is simple to implement and it connects the output of 1 + PD controller with the input of PID controller where the frequency and tie-line power deviation are applied to the latter controller as feedback signals also, which is the first attempt made in the literature. To discover the most optimistic results, controller gains are tuned concurrently by dragonfly search algorithm (DSA). For the certification purpose of the advocated approach, two-area thermal system with/without governor dead band nonlinearity is considered as test systems initially. Then single/multi-area multi-source power systems with/without a HVDC link are employed for the enriched validation purpose. The results of our proposal are analyzed in comparison with those of other prevalent works, which unveil that despite its simplicity, DSA optimized (1 + PD)-PID cascade strategy delivers better performance than others in terms of smaller values of the chosen objective function and settling time/undershoot/overshoot of the frequency and tie-line power deviations following a step load perturbation.
AGC performance amelioration in multi-area interconnected thermal and thermal-hydro-gas power systems using a novel controller
(Elsevier - Division Reed Elsevier India Pvt Ltd, 2021) Arya, Yogendra; Dahiya, Pankaj; Celik, Emre; Sharma, Gulshan; Gozde, Haluk; Nasiruddin, Ibraheem
Due to varying structure, random load demands, nonlinearities, parameters ambiguity, steadily escalating size and intricacy of the interconnected power system (IPS), automatic generation control (AGC) is treated as one of the biggest crucial issues in IPS. Hence, expert, intelligent and robust control scheme is indispensable for stable operation of IPS and supply of electricity under sudden load demand disturbances. In vision of this, in this work, a novel cascade fuzzy-proportional integral derivative incorporating filter (PIDN)-fractional order PIDN (FPIDN-FOPIDN) controller is offered as an expert control strategy to deal effectively with AGC issue of IPS. Imperialist competitive algorithm is prolifically utilized for optimizing the controller parameters. Initially, a two area non-reheat thermal IPS is studied in detail and next to attest the efficacy of the technique, the study is extended to realistic two-area multi-source thermal-hydro-gas and reheat thermal three-area systems. The prominent benefit of cascade FPIDN-FOPIDN strategy comprises its great lethargy to large load demands and its supremacy over various latest intelligent classical/fuzzy controllers. The control strategy beats several techniques concerning significant lesser settling time, oscillations, over/under shoots and different performance index values. Finally, a robustness investigation is performed in order to validate the robustness of the controller. (C) 2020 Karabuk University. Publishing services by Elsevier B.V.
Commutation current ripple minimization of brushless DC motor drive based on programmed phase current references
(Springer, 2021) Celik, Emre; Ozturk, Nihat
Although direct phase current control of brushless DC motor prevents commutation current ripple at low speed, it occurs at high speed which has not received the deserved attention in the literature. Dealing with this current ripple is of practical significance because commutation becomes more influential for high speeds as its duration and the current ripple's amplitude increase with speed. This paper concerns with the successful application of a fuzzy logic estimator (FLE) as an expert control technique to minimize the so-called current ripple profitably. Phase current reference waveforms are programmed as a function of commanded current, angular position, and commutation angle which is adjusted online by the developed FLE as per the motor working condition. The presented approach renders the current references with changing but equal slopes during commutation to keep the other phase current constant at all times. A genetic algorithm is also deployed to optimize the FLE's rule table. Unlike the reported researches, this study does not require calculating commutation time, and use of torque observer and/or commutation detection circuits. The acceptability of our proposal is widely illustrated by simulated and experimental results using DSP TMS320F28335, which signifies that prolific performance toward commutation current ripple minimization is achieved.
Design of new fractional order PI-fractional order PD cascade controller through dragonfly search algorithm for advanced load frequency control of power systems
(Springer, 2021) Celik, Emre
Owing to integrating the dense range of distinct electric power sources, high volume of power generation units, abrupt and continuous changes in load demand, and rising utilization of power electronics, the electric power system (EPS) is striving for high-performance control schemes to counterwork the concerns depicted above. Additionally, it is highly creditable to have the controller structure as simple as possible from a viewpoint of practical implementation. Thus, this paper describes a virgin application of fractional order proportional integral-fractional order proportional derivative (FOPI-FOPD) cascade controller for load frequency control (LFC) of electric power generating systems. The proposed controller includes fractional order PI and fractional order PD controllers connected in cascade wherein orders of integrator (lambda) and differentiator (mu) may be fractional. The gains and fractional order parameters of the controller are concurrently tuned using recently proposed dragonfly search algorithm (DSA) by minimizing the integral time absolute error (ITAE) of frequency and tie-line power deviations. DSA is the mathematical model and computer simulation of static and dynamic swarming behaviors of dragonflies in nature, and its implementation in LFC studies is very rare, unveiling additional research gap to be bridged. Performance of the advocated approach is first explored on popular two-area thermal PS with/without governor dead band (GDB) nonlinearity and then on three-area hydrothermal PS with suitable generation rate constraints. To highlight the prominence and universality of our proposal, the work is extended to single-/multi-area multi-source EPSs. Several comparisons with DSA optimized FOPID controller and the relevant recent works for each test system indicate the contribution of proposed DSA optimized FOPI-FOPD cascade controller in alleviating settling time/undershoot/overshoot of frequency and tie-line power oscillations.
Effective speed control of brushless DC motor using cascade 1PDf-PI controller tuned by snake optimizer
(Springer London Ltd, 2024) Celik, Emre; Karayel, Mehmet
This paper introduces a cascade one proportional derivative incorporating filter (1PDf)-proportional integral (PI) controller abbreviated as c-1PDf-PI to deal effectively with the speed control issue of brushless DC (BLDC) motors. Two problems exist with implementing this controller such as iterated integral overflow and derivation-based chattering owing to the noise. The former is resolved by using an equivalent expression for the integral operation, while the latter is addressed by putting a first-order filter on the derivative term. To achieve the best performance from the controller, snake optimizer (SO) is fruitfully employed for optimizing the controller parameters without need for expert knowledge/interpretation. Here, a more reasonable cost function to assess the candidate solutions is also described. Simulations and laboratory experiments using DSP of TI TMS320F28335 are performed and the results are presented which show that the reference tracking performance, torque disturbance capability and robustness of the c-1PDf-PI controller have potential. These results are also contrasted by those offered by PI and 1PDf speed control schemes individually, affirming the superior performance of our proposal. As per the results, discussion and observation of this research, we stress that good performance and simplicity are salient advantages of the c-1PDf-PI controller, rendering it a good alternative over the complicated controller designs.
An enhanced sea-horse optimizer for solving global problems and cluster head selection in wireless sensor networks
(Springer, 2024) Houssein, Essam H.; Saad, Mohammed R.; Celik, Emre; Hu, Gang; Ali, Abdelmgeid A.; Shaban, Hassan
An efficient variant of the recent sea horse optimizer (SHO) called SHO-OBL is presented, which incorporates the opposition-based learning (OBL) approach into the predation behavior of SHO and uses the greedy selection (GS) technique at the end of each optimization cycle. This enhancement was created to avoid being trapped by local optima and to improve the quality and variety of solutions obtained. However, the SHO can occasionally be vulnerable to stagnation in local optima, which is a problem of concern given the low diversity of sea horses. In this paper, an SHO-OBL is suggested for the tackling of genuine and global optimization systems. To investigate the validity of the suggested SHO-OBL, it is compared with nine robust optimizers, including differential evolution (DE), grey wolf optimizer (GWO), moth-flame optimization algorithm (MFO), sine cosine algorithm (SCA), fitness dependent optimizer (FDO), Harris hawks optimization (HHO), chimp optimization algorithm (ChOA), Fox optimizer (FOX), and the basic SHO in ten unconstrained test routines belonging to the IEEE congress on evolutionary computation 2020 (CEC'20). Furthermore, three different design engineering issues, including the welded beam, the tension/compression spring, and the pressure vessel, are solved using the proposed SHO-OBL to test its applicability. In addition, one of the most successful approaches to data transmission in a wireless sensor network that uses little energy is clustering. In this paper, SHO-OBL is suggested to assist in the process of choosing the optimal power-aware cluster heads based on a predefined objective function that takes into account the residual power of the node, as well as the sum of the powers of surrounding nodes. Similarly, the performance of SHO-OBL is compared to that of its competitors. Thorough simulations demonstrate that the suggested SHO-OBL algorithm outperforms in terms of residual power, network lifespan, and extended stability duration.
Frequency regulation in solar PV-powered thermal power system using FPA-PID controller through UPFC and RFB
(Springer, 2024) Masikana, S. B.; Sharma, Gulshan; Sharma, Sachin; Celik, Emre
The integration of additional renewable energy sources, such as solar PV, into the current power grid is a global priority due to the depletion of traditional supplies and rising power demand. In order to achieve load frequency control (LFC) of the power system with integration of solar PV, this study employs the construction of a proportional integral derivative (PID) scheme that has been fine-tuned via the flower pollination algorithm (FPA). When evaluating the performance of FPA-PID on an interconnected thermal power system, three distinct error values-integral time absolute error (ITAE), integral time multiplied by square error (ITSE), and integral of absolute error (IAE)-are taken into consideration. The results are compared with those of genetic algorithm, particle swarm optimization, and hybrid bacteria foraging optimization based PID. It can be observed that the error values achieved with FPA-PID are substantially lower than those obtained with other PID designs, which are ITSE of 2.07e-05, ITAE of 0.01839, and IAE of 0.008889. Furthermore, the PV integration has further decreased the ITSE to 7.872e-06, the ITAE to 0.008953, and the IAE to 0.005376. All error levels have been further reduced because of the integration of unified power flow control (UPFC) in series with the tie-line and redox flow battery (RFB) separately, utilizing the FPA-PID scheme with solar PV. Finally, it is seen that FPA-PID with solar PV and with UPFC outperforms other LFC designs. The graphical LFC plots verify that FPA-PID with solar PV and with UPFC has capability to reduce the frequency, tie-line power, and area control error excursions in comparison to other LFC designs.
Frequency Support Studies of a Diesel-Wind Generation System Using Snake Optimizer-Oriented PID with UC and RFB
(Mdpi, 2023) Rameshar, Vikash; Sharma, Gulshan; Bokoro, Pitshou N.; Celik, Emre
The present paper discusses the modeling and analysis of a diesel-wind generating system capable enough to cater to the electrical power requirements of a small consumer group or society. Due to high variations of the load demand or due to changes in the wind speed, the frequency of the diesel-wind system will be highly disturbed, and hence to regulate the frequency and power deviations of the wind turbine system, an effective controller design is a necessary requirement, and therefore this paper proposes a novel controller design based on PID scheme. The parameters of this controller is effectively optimized through a new snake optimizer (SO) in an offline manner to minimize frequency and power deviations of an isolated diesel-wind system. The performance of SO-PID for the diesel-wind system is evaluated by considering the integral of time multiplied absolute error (ITAE), integral absolute error (IAE), and integral of time multiplied square error (ITSE). The results were calculated for a step change in load, step change in wind speed, load change at different instants of time with diverse magnitude, and for random load patterns, and they were compared with some of the recently published results under similar working conditions. In addition, the effect of an ultracapacitor (UC) and redox flow battery (RFB) on SO-PID was investigated for the considered system, and the application results demonstrated the advantages of our proposal over other studied designs.
Frequency Support Studies of a Microgrid Having DG-WTG Using ANFIS and with the Application of HAE-FC and RFB
(Taylor & Francis Inc, 2023) Rameshar, Vikash; Sharma, Gulshan; Bokoro, Pitshou N.; Celik, Emre; Öztürk, Nihat
The micro-grid (mu-grid) has picked up momentum worldwide with the ability to supply cost-effective, clean, and reliable electrical power to the present-day demand. The practical mu-grids are comprised of non-conventional and conventional sources such as wind turbine generators (WTG) and diesel generators (DG). Due to the encouragement of wind power which is exceedingly sporadic in nature and thus the frequency of the mu-grid is exceedingly vulnerable due to the erratic nature of wind speed. Variations in the load demand have also added to the vulnerability of the mu-grid at distinctive moments of time. Consequently, this paper appears to be a novel plan that utilizes artificial neuro-fuzzy inference system (ANFIS) within the built frequency regulation of the mu-grid. The proposed research has been employed within the mu-grid, and the application outcomes have taken all possibilities, such as load variety at the distinctive moment of time, modification of the load demand on the mu-grid, and step alteration of the wind input. The achieved results are coordinated with a few of the most recent results, which presents the ANFIS ahead over other strategies. Although there is a probable scope for improvement which subsequently involves the fuel cell (FC) with a hydrogen aqua electrolyzer (HAE) unit, as well as a redox flow battery (RFB), that is introduced one at a time in the mu-grid and the results of mu-grid are calculated for various working conditions to show the impact that the ANFIS technology has upon storage devices with regards to the mu-grid architecture.
An improved honey badger algorithm for global optimization and multilevel thresholding segmentation: real case with brain tumor images
(Springer, 2024) Houssein, Essam H.; Emam, Marwa M.; Singh, Narinder; Samee, Nagwan Abdel; Alabdulhafith, Maali; Celik, Emre
Global optimization and biomedical image segmentation are crucial in diverse scientific and medical fields. The Honey Badger Algorithm (HBA) is a newly developed metaheuristic that draws inspiration from the foraging behavior of honey badgers. Similar to other metaheuristic algorithms, HBA encounters difficulties associated with exploitation, being trapped in local optima, and the pace at which it converges. This study aims to improve the performance of the original HBA by implementing the Enhanced Solution Quality (ESQ) method. This strategy helps to prevent becoming stuck in local optima and speeds up the convergence process. We conducted an assessment of the enhanced algorithm, mHBA, by utilizing a comprehensive collection of benchmark functions from IEEE CEC'2020. In this evaluation, we compared mHBA with well-established metaheuristic algorithms. mHBA demonstrates exceptional performance, as shown by both qualitative and quantitative assessments. Our study not only focuses on global optimization but also investigates the field of biomedical image segmentation, which is a crucial process in numerous applications involving digital image analysis and comprehension. We specifically focus on the problem of multi-level thresholding (MT) for medical image segmentation, which is a difficult process that becomes more challenging as the number of thresholds needed increases. In order to tackle this issue, we suggest a revised edition of the standard HBA, known as mHBA, which utilizes the ESQ approach. We utilized this methodology for the segmentation of Magnetic Resonance Images (MRI). The evaluation of mHBA utilizes existing metrics to gauge the quality and performance of its segmentation. This evaluation showcases the resilience of mHBA in comparison to many established optimization algorithms, emphasizing the effectiveness of the suggested technique.
Improved stochastic fractal search algorithm and modified cost function for automatic generation control of interconnected electric power systems
(Pergamon-Elsevier Science Ltd, 2020) Celik, Emre
y An improved stochastic fractal search algorithm (ISFS) and a modified cost function are proposed in this paper to skillfully handle the issue of automatic generation control (AGC) of power systems. Most employed power system models namely two-area non-reheat thermal power system with and without governor dead band nonlinearity, and three-area hydro-thermal power plant with generation rate constraints are considered to be controlled by a PID controller. Then the gains of this controller are optimized with SFS and ISFS individually by minimizing the value of cost function proposed. This function consists in minimizing the integral time absolute error (ITAE) and also the time rates of frequency and tie-line power deviations. After recognizing the supremacy of SFS tuned PID controller over some existing methods in improving settling time and oscillations of frequency and tie-line power deviations, ISFS tuned PID controller is shown to promote the system performance further to compete with some other control schemes of higher degree and complexity available in the literature. This outcome has unveiled the superior tuning ability of ISFS over the original version of SFS. Also, convergence curves of the algorithms are analyzed from which it is observed that the speed of convergence for ISFS is remarkable.
Improving speed control characteristics of PMDC motor drives using nonlinear PI control
(Springer London Ltd, 2024) Celik, Emre; Bal, Gungor; Ozturk, Nihat; Bekiroglu, Erdal; Houssein, Essam H.; Ocak, Cemil; Sharma, Gulshan
This paper introduces a nonlinear PI controller for improved speed regulation in permanent magnet direct current (PMDC) motor drive systems. The nonlinearity comes from the exponential (Exp) block placed in front of the classical PI controller, which uses a tunable exponential function to map the speed error nonlinearly. Such a configuration has not been studied till now, thus meriting further investigation. We consider an exponential PI (EXP-PI) controller and to attain the best performance from this controller, its parameters are optimized offline using salp swarm algorithm (SSA), which borrows its inspiration from the way of forage and navigation of salps living in deep oceans. To indicate the credibility of SSA tuned EXP-PI controller convincingly, numerous experiments on speed regulation in PMDC motor have been implemented using DSP of TMS320F28335. The results obtained are also compared to similar results in the literature. It is shown that the proposed approach performs well in practice by ensuring tight tracking of the speed reference and superb torque disturbance rejection for the closed loop control. Furthermore, superior performance is achieved by the proposed nonlinear PI controller with respect to a fixed-gain PI controller.
Investigating the Effectiveness of Wind Turbine and Salp Swarm Optimization in Alleviating Transmission Congestion of Power System
(Taylor & Francis Inc, 2024) Gautam, Anurag; Nasiruddin, Ibraheem; Sharma, Gulshan; Ahmer, Mohammad F.; Celik, Emre; Bekiroglu, Erdal
The current power system grapples with congestion challenges arising from technological advancements and deregulation. Conversely, renewable energy sources like wind offer an inexhaustible, cost-effective, and environmentally friendly solution, potentially alleviating congestion in the modern transmission network by reducing the need for conventional generators to reschedule. This article conducts a thorough analysis of how the penetration of wind power impacts congestion costs in conventional energy systems. To address this, a novel approach utilizing the bus sensitivity factor is introduced for precise wind turbine placement. To efficiently mitigate congestion costs, a pioneering Salp Swarm Optimization Algorithm is proposed and validated on a modified IEEE 30 Bus system, demonstrating superior performance compared to other algorithms. The findings underscore the effectiveness of the proposed algorithm and highlight wind turbines, coupled with generator rescheduling, as a potent and cost-effective solution for alleviating transmission network congestion.
Load Frequency Control of Hydro-Hydro Power System using Fuzzy-PSO-PID with Application of UC and RFB
(Taylor & Francis Inc, 2023) Joshi, Milan; Sharma, Gulshan; Celik, Emre
Load frequency control (LFC) plays a crucial rule in matching the power generation with variable power demand, and hence, maintains the system frequency and tie-line power to its esteemed value. Further, most of the countries are dependent on thermal power plants to meet the electrical energy requirement, and hence, LFC strategies are available for these types of power plants only. As the world is moving to generate electrical energy via cleaner sources to reduce harmful environmental pollutants, and hence, hydro power are one of the well-developed and cleanest sources of electrical energy. Subsequently, this article shows up a novel LFC design for hydro-hydro system based on joint endeavors of fuzzy logic with PID viably optimized through particle swarm optimization (PSO) coming into a new and robust Fuzzy-PSO-PID for LFC. At to beginning with, the result of Fuzzy-PSO-PID is evaluated for step load alteration, and the outcomes of Fuzzy-PSO-PID are matched with recently published outcomes of LFC with regards to values of PID, error minimization, and graphical results. In any case, still, there may be a scope of LFC upgrade in Fuzzy-PSO-PID due to higher responding time of turbines used in hydro-hydro plants and subsequently, the combinations of storage devices such as ultra-capacitor (UC) in each zone and UC with redox flow battery combination are used to improve the LFC and the application outcomes are analyzed again and uncover considering the step load alteration, non-linearity, load pattern, and parametric modification to see the benefits of the proposed work for hydro-hydro LFC.
Near Real-Time Load Forecasting of Power System Using Fuzzy Time Series, Artificial Neural Networks, and Wavelet Transform Models
(Taylor & Francis Inc, 2024) Khatoon, Shahida; Ibraheem, Mohammad; Shahid, Mohammad; Sharma, Gulshan; Celik, Emre; Bekiroglu, Erdal; Ahmer, Mohammad Faraz
Due to the increasing usage of electrical power, the size of electrical power system has increased manifold over the years. There is no inventory or buffer from generation to customer; therefore, to provide a reliable and quality electrical energy whenever demanded, power utility engineers require an adequate, efficient, and precise load forecast to meet continuously varying load demands. This article presents the design and analysis of demand forecasting over shorter interval for power system. The fuzzy time series (FTS), artificial neural network (ANN), and wavelet transform (WT) based forecasting is presented and analyzed in this article. The real-time data from Indian utility is collected for forecasting the demand and to check the effectiveness of FTS, ANN, and WT. The various error definitions are used to calculate the accuracy of the proposed techniques, and the application results verify the superiority of WT and ANN over FTS by showing reduced error value with greater accuracy. Additionally, it is watched that wavelet db3, level 3 is discovered to be the most accurate Daubechies wavelet-oriented technique for predicting the demand in comparison to other dbs, and it highly aligns in reducing the error between actual and predicted demand.
A new objective function design for optimization of secondary controllers in load frequency control
(Gazi Univ, Fac Engineering Architecture, 2021) Yilmaz, Zumre Yenen; Bal, Gungor; Celik, Emre; Ozturk, Nihat; Guvenc, Ugur; Arya, Yogendra
In this study, load frequency control (LFC) of two-area non-reheat thermal power system and multi-source power systems is addressed. A simple PID-structured controller is used as a secondary controller in these systems. To raise the performance of PID controller, a new multi-objective function is designed and PID controller parameters are acquired by minimizing the value of this function with symbiotic organisms search (SOS) algorithm. All electrical power systems simulated are modeled in MATLAB/Simulink environment and the optimizer is coded in MATLAB/M-file platform. In order to affirm the contribution of the work, results collected from each power system are compared with popular results published in prestigious journals. As per the comparative results, despite its simplicity, SOS:PID controller tuned via the proposed objective function is observed to result in better performance than other approaches in terms of oscillations, settling time, maximum overshoot and maximum undershoot time domain indicators of the frequency and tie-line power change curves.
A novel congestion mitigation key of power system via generator rescheduling using Jaya algorithm
(Taylor & Francis Inc, 2024) Gautam, Anurag; Nasiruddin, Ibraheem; Sharma, Gulshan; Krishnan, Narayanan; Ahmer, Mohd Faraz; Celik, Emre
In the contemporary power system, congestion is a big hazard to system security. Congestion reduces the capability of the power system to work under secure limits of thermal and voltage profiles. Implementing FACTS devices or rescheduling the generator's active power output are the most prevalent ways to mitigate congestion in the current scenario and hence this paper presents generator rescheduling for congestion management under the N-1 contingency condition. The generator sensitivity factor (GSF) is used to select the generators' participation in the rescheduling process. The minimization of active power rescheduled by the selected generators is the key to success. JAYA algorithm is used first time in this work to reduce the congestion cost of the system. Furthermore, the JAYA algorithm is applied to a modified IEEE 30 bus system and the results obtained are validated by comparing them with other popular heuristic algorithms as available in the literature for diverse case studies.
A Novel Salp Swarm Optimization Oriented 3-DOF-PIDA Controller Design for Automatic Voltage Regulator System
(Ieee-Inst Electrical Electronics Engineers Inc, 2024) Chetty, Nelson Dhanpal; Sharma, Gulshan; Gandhi, Ravi; Celik, Emre
Voltage stability is critical in electrical power systems, and automatic voltage regulators play a crucial role in maintaining voltage levels within permissible limits. Due to their simplicity and effectiveness, traditional Proportional-Integral-Derivative (PID) controllers have been widely used in automatic voltage regulation. However, they may not always perform optimally in complex power systems with varying operating conditions and external disturbances. This research introduces an integrated approach of employing a 3-degrees of freedom-PID-Acceleration (3-DOF-PIDA) controller coupled with a disturbance observer-based control strategy. This combination is embedded with a simple but effective salp swarm optimisation algorithm. This novel control approach of the combined 3-DOF-PIDA, disturbance observer and salp swarm optimisation will enhance the voltage regulation of the system. The proposed novel control strategy incorporates an acceleration component to continuously adjust its parameters based on system dynamics. Simultaneously, the disturbance observer is responsible for estimating and compensating for external disturbances, further improving the system's performance. The salp swarm optimization is applied to optimize both the PIDA control parameters and the disturbance observer's parameters in the automatic voltage regulation system to find optimal solutions that improve voltage regulation and disturbance rejection capabilities. The results are established by performing statistical and graphical analyses with time-varying step load fluctuations, and under various system parameter variations. The results are validated by comparisons to five popular optimization algorithms found in the reviewed literature. The investigations demonstrate that this new proposed approach provides outstanding performance, in the presence of substantial system parameter fluctuations and uncertainties.
Power Loss Minimization through Reconfiguration Using BPSO-Based Technique
(Taylor & Francis Inc, 2023) Kirithikaa, S.; Narayanan, K.; Sharma, Gulshan; Bokoro, Pitshou N.; Celik, Emre; Bekiroglu, Erdal
Power loss is influenced by uncertain and ever increasing loads in the system but can be minimized by network reconfiguration where the topological structure of the system is changed by altering the switching operation. In this work, a multi-objective framework through reconfiguration is formulated with loss minimization as primary objective and reliability and voltage profile improvement as secondary objectives. A binary particle swarm optimization (BPSO) base method is developed to reconfigure the network by fulfilling all distribution network constraints. The influence of the BPSO parameters to obtain the optimal switches with minimized power loss, reliability indices, and voltage deviations are studied by a faster convergence. The results have been compared for different weights of the objective to give a comprehensive understanding of the nature of the objective attempted in this work. IEEE 33 bus and radial IEEE 69 bus systems were considered for testing the proposed method.
A powerful variant of symbiotic organisms search algorithm for global optimization
(Pergamon-Elsevier Science Ltd, 2020) Celik, Emre
This paper suggests a new variation to the existing symbiotic organisms search (SOS) algorithm developed by simulating three symbiotic strategies of mutualism, commensalism and parasitism used by the organisms. In the revised version called improved SOS (ISOS), the theory of quasi-oppositional based learning is employed during generation of initial population and in the parasitism phase to raise the possibility of getting closer to high-quality solutions. An efficient alternative for parasitism phase is also presented. The two upgraded parasitism strategies avoid the over exploration issue of original parasitism phase that causes unwanted longtime search in the inferior search space as the solution is already refined. To guide the algorithm perform an exhaustive search around the best solution in attempting to further improve the search model of ISOS, a chaotic local search based on the piecewise linear chaotic map is coupled into the proposed algorithm. Twentysix benchmark functions and three engineering design problems are tested and a contrast with other popular metaheuristics is widely established. Comparative results substantiate the great contribution of proposed ISOS algorithm in solving various optimization problems with superior global search capability and convergence characteristics which render it useful in handling global optimization problems.

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