i-manager Publications

i-manager's Journal on Power Systems Engineering (JPS)

Current Issue Vol. 11 Issue 3

Voltage Stability and Power Loss Minimization with STATCOM using Particle Swarm Optimization and Hybrid Firefly Particle Swarm Optimization Algorithms
Load Frequency Control of Multi Area Power System Network with Soft Computing Algorithm Based Controller and Coordinated Strategy of TCSC and Battery Energy Storage
Performance Analysis of Distribution System under Different Loading Conditions using Test Bench
Simulation of Solar PV with Different Control System of Boost Converter for Composite Climate
Enhancement of System Performance using PeSche Scheduling Algorithm on Multiprocessors

Most Cited

Volume 11 Issue 3 October - December 2023

Research Paper

Voltage Stability and Power Loss Minimization with STATCOM using Particle Swarm Optimization and Hybrid Firefly Particle Swarm Optimization Algorithms

R. Siva Subramanyam Reddy*

Srikalahasteeswara Institute of Technology (SKIT), Andhra Pradesh, India.

Reddy, R. S. S. (2023). Voltage Stability and Power Loss Minimization with STATCOM using Particle Swarm Optimization and Hybrid Firefly Particle Swarm Optimization Algorithms. i-manager’s Journal on Power Systems Engineering, 11(3), 1-10. https://doi.org/10.26634/jps.11.3.20045

Abstract

This paper presents a hybrid algorithm using a hybrid firefly and particle swarm optimization (HFPSO) algorithm to determine the optimal placement of STATCOM devices. A multi-objective function is used to increase voltage stability, voltage profile and minimize overall power losses of the transmission system. At first, PSO algorithm is used to find the optimal STATCOM location and further more to reduce the power losses and voltage profile enhancement to overcome the sub-optimal operation of existing algorithms, the HFPSO algorithm is used to determine the optimal placement of STATCOM FACTS device and verification of the proposed algorithm was achieved on standard IEEE 14-bus and 30-bus transmission systems in the MATLAB environment. Comprehensive simulation results of two different cases show that the proposed HFPSO demonstrates significant improvements over other existing algorithms to enhance voltage stability and reducing active and reactive power losses in an electrical power transmission systems.

References

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[11]. Gerbex, S., Cherkaoui, R., & Germond, A. J. (2003, June). Optimal location of FACTS devices to enhance power system security. In 2003 IEEE Bologna Power Tech Conference Proceedings, 3, 7. IEEE.

[12]. Grigsby, L. L. (2007). Power System Stability and Control. CRC press, New York.

[13]. Hingorani, N. G., & Gyugi, L. (1999). Understanding FACTS – Concepts and Technology of Flexible AC Transmission Systems. Wiley-IEEE Press.

[14]. Jeong, H. M., Lee, H. S., & Park, J. H. (2009, October). Application of parallel particle swarm optimization on power system state estimation. In 2009 Transmission & Distribution Conference & Exposition: Asia and Pacific (pp. 1-4). IEEE.

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[16]. Li, N., Xu, Y., & Chen, H. (2000). FACTS-based power flow control in interconnected power system. IEEE Transactions on Power Systems, 15(1), 257-262.

[17]. Murali, D., & Rajaram, M. (2010). Active and reactive power flow control using FACTS devices. International Journal of Computer Applications, 9(8), 45-50.

[18]. Murali, D., Rajaram, M., & Reka, N. (2010). Comparison of FACTS devices for power system stability enhancement. International Journal of Computer Applications, 8(4), 30-35.

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[21]. Rao, S. S. (2019). Engineering Optimization: Theory and Practice. John Wiley & Sons.

[22]. Reddy, R. S. S. (2020). Optimal placement of UPFC using Heuristic Techniques. i-manager's Journal on Electrical Engineering, 14(2), 26-33.

[23]. Samy, M. M., & Barakat, S. (2019, December). Hybrid invasive weed optimization-particle swarm optimization algorithm for biomass/PV micro-grid power system. In 2019 21st international Middle East power systems conference (MEPCON) (pp. 377-382). IEEE.

[24]. Sharma, D., Gaur, P., & Mittal, A. P. (2014). Comparative analysis of hybrid GAPSO optimization technique with GA and PSO methods for cost optimization of an off-grid hybrid energy system. Energy Technology & Policy, 1(1), 106-114.

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Research Paper

Load Frequency Control of Multi Area Power System Network with Soft Computing Algorithm Based Controller and Coordinated Strategy of TCSC and Battery Energy Storage

Ch. Naga Sai Kalyan*

Vasireddy Venkatadri Institute of Technology, Andhra Pradesh, India.

Kalyan, Ch. N. S. (2023). Load Frequency Control of Multi Area Power System Network with Soft Computing Algorithm Based Controller and Coordinated Strategy of TCSC and Battery Energy Storage. i-manager’s Journal on Power Systems Engineering, 11(3), 11-21. https://doi.org/10.26634/jps.11.3.20241

Abstract

This work proposes the possible implementation of a water cycle algorithm (WCA) optimized controller of tilt-integral derivative plus filter (TIDF) for the load frequency control (LFC) of a multi-area multi-fuel (MAMF) interconnected power system network (IPSN). The MAMF network has two areas, and the dynamic analysis of the IPSN is assessed pertaining to the step load perturbation (SLP) of 10% in area 1. However, the performance efficacy of the TIDF is demonstrated and validated with other recent control techniques reported in the literature. The IPSN is considered with the communication time delays (CTDs) as the realistic constraint, and their subsequent impact on the LFC performance is demonstrated and vindicated. Further, the IPSN model of the MAMF system is enacted with the battery energy storage (BES) in areas 1 and 2, and the thyristor-controlled series compensator (TCSC) with the tie-line as the territory regulator. Simulation results showcased that there will be an improvement in the LFC of MAMF system performance with the employment of a territory control scheme.

References

[1]. Abdelaziz, A. Y., & Ali, E. S. (2015). Cuckoo search algorithm based load frequency controller design for nonlinear interconnected power system. International Journal of Electrical Power & Energy Systems, 73, 632-643.

[2]. Alhelou, H. H., Nagpal, N., Kassarwani, N., & Siano, P. (2023). Decentralized optimized integral sliding modebased load frequency control for interconnected multiarea power systems. IEEE Access, 11, 32296-32307.

[3]. Ali, M., Kotb, H., AboRas, M. K., & Abbasy, H. N. (2022). Frequency regulation of hybrid multi-area power system using wild horse optimizer based new combined Fuzzy Fractional-Order PI and TID controllers. Alexandria Engineering Journal, 61(12), 12187-12210.

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[7]. Fernández-Guillamón, A., Muljadi, E., & Molina-García, A. (2022). Frequency control studies: A review of power system, conventional and renewable generation unit modeling. Electric Power Systems Research, 211, 108191.

[8]. Guha, D., Roy, P. K., & Banerjee, S. (2016). Quasioppositional differential search algorithm applied to load frequency control. Engineering Science and Technology, an International Journal, 19(4), 1635-1654.

[9]. Jalendra, M., Reddy, K. S. G., Lavanya, M., Jaideep, N. V., Kalyan, C. N. S., & Suresh, C. V. (2022, December). Fruit fly optimization algorithm based TIDF controller for LFC of traditional hydro thermal system with SSSC and ultra-capacitors. In 2022 International Conference on Knowledge Engineering and Communication Systems (ICKES), (pp. 1-6). IEEE.

[10]. Kalyan, C. H., & Rao, G. S. (2020). Coordinated SMES and TCSC damping controller for load frequency control of multi area power system with diverse sources. International Journal on Electrical Engineering & Informatics, 12(4). 747-769.

[11]. Kalyan, C. N. S., Goud, B. S., Kishan, H., Ramineni, P., Kumar, B. P., & Kumar, T. A. (2022, December). Donkey and smuggler optimization algorithm-based degree of freedom controller for stability of two area power system with AC-DC links. In 2022 IEEE 7th International Conference on Recent Advances and Innovations in Engineering (ICRAIE), 7, 461-466. IEEE.

[12]. Kalyan, C. N. S., Goud, B. S., Kumar, M. K., Thakur, P., Bajaj, M., & Bansal, R. C. (2023). Squirrel search algorithm based intelligent controller for interconnected power system. International Journal of Modelling and Simulation, 1-21.

[13]. Kalyan, C. N. S. (2021, January). UPFC and SMES based coordinated control strategy for simultaneous frequency and voltage stability of an interconnected power system. In 2021 1st International Conference on Power Electronics and Energy (ICPEE), (pp. 1-6). IEEE.

[14]. Kalyan, C. N. S., & Rao, G. S. (2020). Performance comparison of various energy storage devices in combined LFC and AVR of multi area system with renewable energy integration. International Journal of Renewable Energy Research (IJRER), 10(2), 933-944.

[15]. Kalyan, C. N. S., & Rao, G. S. (2022). Coordinated control strategy for simultaneous frequency and voltage stabilisation of the multi-area interconnected system considering communication time delays. International Journal of Ambient Energy, 43(1), 5512-5524.

[16]. Kalyan, N. S., & Rao, G. S. (2020). Frequency and voltage stabilisation in combined load frequency control and automatic voltage regulation of multiarea system with hybrid generation utilities by AC/DC links. International Journal of Sustainable Energy, 39(10), 1009-1029.

[17]. Kumar, A., & Pan, S. (2022). Design of fractional order PID controller for load frequency control system with communication delay. ISA Transactions, 129, 138-149.

[18]. Mishra, S., Prusty, R. C., & Panda, S. (2021). Performance analysis of modified sine cosine optimized multistage FOPD PI controller for load frequency control of an islanded microgrid system. International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, 34(6), e2923.

[19]. Mohapatra, G., Debnath, M. K., & Mohapatra, K. K. (2020). IMO-based novel adaptive dual-mode controller design for AGC investigation in different types of systems. Cogent Engineering, 7(1), 1711675.

[20]. Morsali, J., Zare, K., & Hagh, M. T. (2017). Modified group search optimisation based comparative performance evaluation of thyristor controlled series capacitor based fractional order damping controllers to improve load frequency control performance in restructured environment. IET Generation, Transmission & Distribution, 11(18), 4654-4669.

[21]. Padhy, S., & Panda, S. (2017). A hybrid stochastic fractal search and pattern search technique based cascade PI-PD controller for automatic generation control of multi-source power systems in presence of plug in electric vehicles. CAAI Transactions on Intelligence Technology, 2(1), 12-25.

[22]. Prakash, S., & Sinha, S. K. (2018). Automatic load frequency control of six areas' hybrid multi-generation power systems using neuro-fuzzy intelligent controller. IETE Journal of Research, 64(4), 471-481.

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Research Paper

Performance Analysis of Distribution System under Different Loading Conditions using Test Bench

Shekhappa G. Ankaliki * , Sanjeeth P. Aminabhavi, Manjula Sureban*, Pradeep Vibhuti****

*-**** Department of Electrical & Electronics Engineering, Shri Dharmasthala Manjunatheshwara College of Engineering and Technology, Karnataka, India.

Ankaliki, S. G., Aminabhavi, S. P., Sureban, M., and Vibhuti, P. (2023). Performance Analysis of Distribution System under Different Loading Conditions using Test Bench. i-manager’s Journal on Power Systems Engineering, 11(3), 22-29. https://doi.org/10.26634/jps.11.3.20399

Abstract

This paper presents performance analysis of power distribution system using distribution test bench. Distribution system is the part of power system in which significant portion of the power is utilized in it. The losses occur in distribution system mainly due to inherent characteristics of the number of components in the system. In this wok, we analyse the performance of distribution system having 4 feeders having different lengths supplying resistive and combination of resistive and inductive loads. The analysis includes the voltage regulation, power loss, efficiency for different loading conditions. Also shown are the improvement of terminal voltage of the feeders and receiving end power with compensation. Finally the inferences are drawn and suggestions are proposed to improve the performance.

References

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Research Paper

Simulation of Solar PV with Different Control System of Boost Converter for Composite Climate

Roshni Rahangdale* , Deeksha Sahare**

*-** Department of Electrical & Electronics Engineering, Shri Shankaracharya Group of Institution, Durg, Chhattisgarh, India.

Rahangdale, R., and Sahare, D. (2023). Simulation of Solar PV with Different Control System of Boost Converter for Composite Climate. i-manager’s Journal on Power Systems Engineering, 11(3), 30-36. https://doi.org/10.26634/jps.11.3.20409

Abstract

This paper works on the modelling of solar PV with series parallel connection of the strings for the composite climate location and the detailed study has been done on the gate signal of the chopper used for boosting with three different conditions. As the climate conditions are very important factor for the installation of the project to fulfill the captive requirements, a study has also been done with the help of climate consultant software so that the radiations capacity and potential to develop the energy is with in its maximum output capacity. In the next phase an inverter has also been connected for the conversion into single phase AC output for the testing of the model for the usage in the load or grid. Various methods for the control of the booster has been analyzed and considered. Simulation is done on a Matlab software and the result is analyzed.

References

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[2]. Agorreta, J. L., Reinaldos, L., Gonzalez, R., Borrega, M., Balda, J., & Marroyo, L. (2009). Fuzzy switching technique applied to PWM boost converter operating in mixed conduction mode for PV systems. IEEE Transactions on Industrial Electronics, 56(11), 4363-4373.

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Research Paper

Enhancement of System Performance using PeSche Scheduling Algorithm on Multiprocessors

M. Sreenath* , P. A. Vijaya**

* Infosys Ltd., Bengaluru, India.

** Department of ECE., BNMIT, Bengaluru, Karnataka, India.

Sreenath, M., and Vijaya, P. A. (2023). Enhancement of System Performance using PeSche Scheduling Algorithm on Multiprocessors. i-manager’s Journal on Power Systems Engineering, 11(3), 37-54. https://doi.org/10.26634/jps.11.3.20277

Abstract

The scheduling techniques have been investigated by the job execution process in a system to maximize multiprocessor utilization. Dynamic Power Management (DPM) and Dynamic Voltage and Frequency Scaling (DVFS) represent two general strategies for lowering energy use. Performance enhanced Scheduling (PeSche) is a proposed scheduling algorithm designed for an optimal solution. CodeBlocks were utilized to run extensive simulations. In terms of computing performance (average waiting time and average turnaround time), the PeSche scheduling algorithm outperformed recently reported scheduling algorithms such as SJF, RR, FCFS, Priority, and SJF-LJF. The PeSche scheduling algorithm yielded better results by assigning priority in terms of energy-time ratio, programming running time, total energy, and total time than existing algorithms. In comparison to Minimum Energy Schedule (MES) and Slack Utilization for Reduced Energy (SURE), PeSche consumed less energy.

References

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i-manager's Journal on Power Systems Engineering (JPS)

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Volume 11 Issue 3 October - December 2023

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Srikalahasteeswara Institute of Technology (SKIT), Andhra Pradesh, India.

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Load Frequency Control of Multi Area Power System Network with Soft Computing Algorithm Based Controller and Coordinated Strategy of TCSC and Battery Energy Storage

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Vasireddy Venkatadri Institute of Technology, Andhra Pradesh, India.

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Shekhappa G. Ankaliki * , Sanjeeth P. Aminabhavi**, Manjula Sureban***, Pradeep Vibhuti****

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Simulation of Solar PV with Different Control System of Boost Converter for Composite Climate

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Enhancement of System Performance using PeSche Scheduling Algorithm on Multiprocessors

M. Sreenath* , P. A. Vijaya**

* Infosys Ltd., Bengaluru, India. ** Department of ECE., BNMIT, Bengaluru, Karnataka, India.

Sreenath, M., and Vijaya, P. A. (2023). Enhancement of System Performance using PeSche Scheduling Algorithm on Multiprocessors. i-manager’s Journal on Power Systems Engineering, 11(3), 37-54. https://doi.org/10.26634/jps.11.3.20277

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Shekhappa G. Ankaliki * , Sanjeeth P. Aminabhavi, Manjula Sureban*, Pradeep Vibhuti****

* Infosys Ltd., Bengaluru, India.

** Department of ECE., BNMIT, Bengaluru, Karnataka, India.