Download to read offline
More Related Content
Similar to SIntelligent Optimization Techniques for Controlling Load Frequency of Interconnected Multiple Source Power Systems including Renewable Energy Sources
SIntelligent Optimization Techniques for Controlling Load Frequency of Interconnected Multiple Source Power Systems including Renewable Energy Sources
- 1. 1 PAPER ID :40 Intelligent Optimization Techniques for Controlling Load Frequency of Interconnected Multiple Source Power Systems including Renewable Energy Sources Bijaya Kumar Mohapatra, Deepak Kumar Gupta, Chinmoy Kumar Panigrahi School of Electrical Engineering, KIIT, DU
- 2. STPGE 2022 12th-13th Feb2022 Outlines Introduction Literature Survey Objective of Proposed Work The Proposed System and PID Controller Simulation Model Intelligent Optimization Techniques Discussion of the Finding Results Conclusion & Future work References 2
- 3. STPGE 2022 12th-13th Feb2022 Introduction • Controlling the system frequency under load variation of multiple source power systems (MSPS), including renewable energy sources (RES), is a very difficult task for power system engineers. • The paper presents a performance investigation of a two-area system that includes RES. Hydro, thermal, wind and diesel power stations have been modeled and used in the test system. • The algorithms set the constraints of a PID controller to provide controlling load frequency in an automatic manner of MSPS with RES. • Intelligent optimization techniques are used to fine-tune the controller's parameters with constraints. The ITAE is used as an objective function. The PID Controller kept the deviation of frequency and tie-line power of the MSPS within acceptable limits 3
- 4. STPGE 2022 12th-13th Feb2022 Objective of Proposed Work • A two-area power system with multiple sources is considered in this work. By minimizing ITAE, the proposed methodology was used to modify the parameters of the PID controller. • For optimally tuning the parameter of PID controller and problems on LFC, two well-known optimization techniques such as GSA and Firefly Algorithm (FA) have been used. • Comparative analysis for the dynamic behavior of frequency and tie-line power of the system for both the techniques has been done. • The performance of the system was evaluated in both domains while considering the perturbation step load change. 4
- 5. STPGE 2022 12th-13th Feb2022 The Proposed System and PID Controller • The output of the PID controller can be denoted by Equation (1) …………………(1) • The PID controller parameters were tuned by minimizing this objective function. The objective function can be described by Equation (2) ………………..(2) • ITAE as an objective function in our current research. ……….………(3) 5 ( ) ( ) ( ) ( ) P I D de t u t K e t K e t dt K dt 0 ( ) sim t ITAE t e t dt 1 2 0 ( ). . sim t tie J ITAE F F P t dt
- 6. STPGE 2022 12th-13th Feb2022 Simulation Model 6
- 7. STPGE 2022 12th-13th Feb2022 Intelligent Optimization Techniques Gravitational Search Algorithm (GSA) Firefly Algorithm (FA) 7
- 8. STPGE 2022 12th-13th Feb2022 Discussion of the Finding Results Case Study-I 8 Case Study-II
- 9. STPGE 2022 12th-13th Feb2022 Discussion of the Finding Results Case Study-I Case Study-II 9
- 10. STPGE 2022 12th-13th Feb2022 Discussion of the Finding Results Case Study-I Case Study-II 10
- 11. STPGE 2022 12th-13th Feb2022 Discussion of the Finding Results Case Study-I Case Study-II 11
- 12. STPGE 2022 12th-13th Feb2022 Discussion of the Finding Results Case Study-I Case Study-II 12
- 13. STPGE 2022 12th-13th Feb2022 Conclusion & Future work • The work looked at the difficulties of using the LFC in MAPS with various sources. We explored a multi-source, two-area power system. • By minimizing ITAE performance indices, the optimization methodologies were used to optimize the parameters of PID controller. • Finally, it was found that the FA outperformed the GSA. • Furthermore, the authors want to know how the system performs in a restructured deregulated power system with several generation stations and consumers having power contracts. 13
- 14. STPGE 2022 12th-13th Feb2022 14 References 1. Kumari, Sandhya, and Gauri Shankar. "Maiden application of cascade tilt-integral–tilt- derivative controller for performance analysis of load frequency control of interconnected multi-source power system." IET Generation, Transmission & Distribution 13.23 (2019): 5326-5338. 2. Topno, Pretty Neelam, and Saurabh Chanana. "Load frequency control of a two-area multi- source power system using a tilt integral derivative controller." Journal of Vibration and Control 24.1 (2018): 110-125. 3. Tavakoli, Mehdi, et al. "Load-frequency control in a multi-source power system connected to wind farms through multi terminal HVDC systems." Computers & Operations Research 96 (2018): 305-315. 4. Lu, Kangdi, et al. "Constrained population extremal optimization-based robust load frequency control of multi-area interconnected power system." International Journal of Electrical Power & Energy Systems 105 (2019): 249-271. 5. Sahoo, Prafulla Kumar, et al. "Multi-Verse Optimized Fractional Order PDPI Controller for Load Frequency Control." IETE Journal of Research (2020): 1-14. 6. Guha, Dipayan, Provas Kumar Roy, and Subrata Banerjee. "Whale optimization algorithm applied to load frequency control of a mixed power system considering nonlinearities and PLL dynamics." Energy Systems 11.3 (2020): 699-728. 7. KOM, Charles Hubert. "Understanding Interphase Power Controller: A Description." Journal of Electrical Engineering, Electronics, Control and Computer Science 6.3 (2020): 19-24. 8. Ahmed, Shazly Abdo Mohamed. "Performance Analysis of Power Quality Improvement for Standard IEEE 14-Bus Power System based on FACTS Controller." Journal of Electrical Engineering, Electronics, Control and Computer Science 5.4 (2019): 11-18.
- 15.