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Öğe 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, IbraheemDue 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.Öğe Cascade-(IDN)-D-lambda-N-mu controller design for AGC of thermal and hydro-thermal power systems integrated with renewable energy sources(Inst Engineering Technology-Iet, 2021) Arya, Yogendra; Kumar, Nishant; Dahiya, Pankaj; Sharma, Gulshan; celik, Emre; Dhundhara, Sandeep; Sharma, MandeepExpert, intelligent and robust automatic generation control (AGC) scheme is requisite for stable operation and control of power system (PS) integrated with renewable energy sources (RES) under sudden/random small load disturbances. Large frequency deviations appear if AGC capacity is inept to compensate for the imbalances of generation and demand. In this paper, a cascade-fractional order ID with filter (C-(IDN)-D-lambda-N-mu) controller is proposed as an expert supplementary controller to promote AGC recital adequately in electric power systems incorporated with RES like solar, wind and fuel cells. The imperialist competitive algorithm is fruitfully exploited for optimizing the controller parameters. First, a 2-area reheat thermal system is examined critically and then to authorize the worth of the proposed controller, the study is protracted to a 2-area multi-source hydro-thermal system. The prominent benefits of C-(IDN)-D-lambda-N-mu controller with/without renewable energy sources consist of its great indolence to large load disturbances and superiority over various optimized classical/fuzzy controllers published recently. The sensitivity study validates the robustness of the recommended controller against +/- 20% deviations in the system parameters and random step load perturbations.Öğe Design and Robustness Analysis of Multiple Extended State Observer Based Controller (MESOBC) for AVR of the Power System(Hindawi Limited, 2023) Gandhi, Ravi; Masikana, S.B.; Sharma, Gulshan; Çelik, EmreAutomatic voltage regulator (AVR) is installed on the synchronous generators in the power system and plays a very important role in maintaining the generator output voltage besides changes in load demand, parametric uncertainties, and operating temperature. As the load is continuously varying in the system, the AVR needs controllers to track and regulate the voltage of the synchronous generator much faster. This paper shows an initial attempt to design a robust multiple extended state observer (MESO) to estimate the variation in lump disturbances (i.e., load demand and parametric uncertainties) from all the components of the AVR. MESO-based controller (MESOBC) can track such matching and mismatching of both types of irregularities and regulate the terminal voltage of the generator accordingly. MESOBC performance is matched with strong published AVR designs for a standard condition, ±30% load voltage variation and for simultaneous changes in AVR parameters with ±30% load voltage variations. Integrated square error (ISE) is chosen as an objective function to compare the output of MESOBC with other published AVR designs in view of graphical AVR responses and by calculating various numerical values for AVR responses. At last, the robustness of MESOBC is also checked through sensitivity analysis, and it is seen that MESOBC guaranteed robust performance for the AVR of the power system under diverse operating conditions. © 2023 Ravi Gandhi et al.Öğe 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, EmreThe 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.Öğe 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, EmreThe 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.Öğe 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, NihatThe 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.Öğe 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, GulshanThis 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.Öğe 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, ErdalThe 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.Öğe 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, EmreLoad 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.Öğe 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 FarazDue 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.Öğe 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, EmreIn 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.Öğe 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, EmreVoltage 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.Öğe 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, ErdalPower 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.Öğe Reliability Assessment of Demand Response Strategies for Profit Maximization(Taylor & Francis Inc, 2023) Sivasankari, G. S.; Narayanan, K.; Sharma, Gulshan; Celik, Emre; Bekiroglu, ErdalThe idea of renewable resource integration influences the demand-supply balance significantly. The effort taken to diminish the deviation in demand-supply balance is greatly influenced by demand response (DR) strategy. In this analysis, the concept of DR is incorporated via the approach of load management. The optimal scheduling of the load considering the available energy helps to avoid unessential load shedding. The DR strategy of load shifting is suggested at different levels in accordance with the nature of load and real-time price. The profit of the utility is enhanced by providing the customer the flexibility to schedule their load. The curtailment of load can be avoided by increased customer participation in the suggested DR programs. The operating system is designed to be both efficient and effective by utilizing the real-time tariff profile of electricity to plan the generation of renewable energy, energy storage systems that include electric vehicles, and the utilization of grid power. The scalability and generalization of the proposed DR approach make it suitable for large-scale power systems that integrate renewable energy sources. The validation of the proposed method using reliability analysis ensures the effectiveness of the formulated DR. The proposed method is tested under two different scenarios and topologies on the IEEE-33 bus system and the results accomplished are promising.Öğe Sensitivity Factor-Based Congestion Mitigation in DPS Applying Novel Hybrid GWPSO(Taylor & Francis Inc, 2023) Gautam, Anubha; Sharma, Parshram; Kumar, Yogendra; Sharma, Gulshan; Gautam, Anurag; Çelik, Emre; Öztürk, NihatIn a deregulated power system, with a limited power system framework, alleviation in power transfer has been one of the most crucial problems. This alleviation of bulk power transmission came with congestion, where a transmission line transmits power very near the constrained thermal limits. Congestion has to be mitigated for reliable, economical, and stable operation of the power system. Congestion can be mitigated by applying several methods which may be cost-free or non-cost-free. This article presents a cost-free method employing TCSC as a FACTS device. FACTS devices are very costly. To make the TCSC operation economic, LUF and DLUF are used here to optimally locate the device. TCSC is used here as a variable impedance device. A novel hybrid heuristic optimization technique where Grey Wolf optimizer is merged with Particle Swarm Optimizer to optimize the size of TCSC. The proposed method is implemented to regulate the line reactance for congestion mitigation. The power loss and voltage deviation of the system are reduced by the proposed method to relieve the system congestion. The system security margin is enhanced significantly to make the system more reliable. The proposed algorithm is validated on IEEE 30 bus system and is also validated by comparing the results with parent algorithms. The results reveal that the proposed methodology successfully minimized the objectives for mitigating congestion.Öğe Squirrel search algorithm applied to effective estimation of solar PV model parameters: a real-world practice(Springer Science and Business Media Deutschland GmbH, 2023) Maden, Dinçer; Çelik, Emre; Houssein, Essam H.; Sharma, GulshanModel parameters estimation of solar photovoltaic (PV) cells/modules using real current–voltage (I–V) data is a critical task for the performance of PV systems. Therefore, there is a necessity to procure optimal parameters of PV models using proper optimization techniques. For this aim, squirrel search algorithm (SSA) as the recent and powerful tool is employed to accomplish the mentioned task in the single-diode model (SDM) and double-diode model (DDM) of a PV unit. Of course, better parameter values can be obtained by reducing the error between the experimental and model-based estimated data. Analyses are performed under two case studies. The former considers a standard dataset of R.T.C. France silicon solar cell, whereas the latter uses an experimental dataset of a polycrystalline CS6P-220P solar module. The I-V data of this PV module were acquired when it worked under 30 °C and solar radiance of 1000W/m2 at the Engineering Faculty Campus of Düzce University, Turkey. The results of the first case study are compared with those of other prevalent approaches, which demonstrate the superiority of SSA over its competing peers. Moreover, SSA is found to handle the model parameters definition of an industrial PV module located at the university campus. Thus, the new method offers a practical tool beneficial to boost the effectiveness of PV systems. © 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.
