Abstract
In this study, a state feedback controller is designed for a linearized model of a diesel generator-based generation plant and a battery storage-based inverter model plant. The diesel generator plant and inverter-based battery storage system constitute as a microgrid. The microgrid is a localized power system network and minimized the mismatch between the generation and loads in a specific region. Thus, to achieve better performance and stability, a proposed controller is designed for microgrid. The stability convergence of the control law is analyzed through Lyapunov stability theorem as well as the Nyquist diagram stability criteria. The proposed controller improves the overall system performance in the presence of initial parameter variation and mechanical shaft power random step variations by reducing over/under shoots, settling time and oscillations. In addition, the proposed controller regulated both diesel generator model and inverter-based DG independently. The performance, stability and ability to keep in synchronism of the proposed control scheme are validated on a diesel generator and inverter-based battery storage model simulated in MATLABĀ©.
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References
Kundur P (1994) Power system stability and control. McGraw Hill, New York, pp 780ā808
Olivares DE, Mehrizi-Sani A, Etemadi AH, CaƱizares CA, Kazerani RIM, Hajimiragha AH, Gomis-Bellmunt O, Saeedifard M, Palma-Behnke R, JimĆ©nez-EstĆ©vez GA, Hatziargyriou ND (2014) Trends in microgrid control. IEEE Trans Smart Grid 5(4):1905ā1919
Singh M, Singh O, Kumar A (2019) Renewable energy sources integration in micro-grid including load patterns: In: 2019 3rd international conference on recent developments in control, automation and power engineering (RDCAPE), pp 1ā6
Gupta P, Ansari MA (2019) Analysis and control of AC and hybrid AC-DC microgrid: a review. In: 2019 2nd international conference on power energy, environment and intelligent control (PEEIC), pp 1ā6
Lu W, Zhao Y, Li W, Du H (2014) Design and application of microgrid operation control system based on IEC 61850. J Mod Power Syst Clean Energy 2(3):256ā263
Han Y, Ning X, Yang P, Xu L (2019) Review of power sharing, voltage restoration and stabilization techniques in hierarchical controlled DC microgrids. IEEE Access 7:149202ā149223
Zhang W, Xu Y (2019) Distributed optimal control for multiple microgrids in a distribution network. IEEE Trans Smart Grid 10(4):3765ā3779
Kaviri SM, Pahlevani M, Jain P, Bakhshai A (2017) A review of AC microgrid control methods. In: 2017 IEEE 8th international symposium on power electronics for distributed generation systems (PEDG), pp 1ā6
Qingdong H, Bin X, Wei W, Yueliang C (2019) Operation control strategy of microgrid based on energy storage system. In: IEEE 4th advanced information technology, electronic and automation control conference (IAEAC), pp 1ā6
Parisio A, Rikos E, Glielmo L (2014) A model predictive control approach to microgrid operation optimization. IEEE Trans Control Syst Technol 22(5):1813ā1827
de Andrade F, Castilla M, Bonatto BD (2020) Microgrids: operation and control methods. In: Basic tutorial on simulation of microgrids control using MATLABĀ® and SimulinkĀ® software. Springer briefs in energy. Springer, Cham. https://doi.org/10.1007/978-3-030-43013-9_1
Xuefeng L, Kaiju L, Weiqiang L, Chaoxu M, Dan W (2018) A brief analysis of distributed generation connected to distribution network. In: 2018 33rd youth academic annual conference of Chinese Association of Automation (YAC), pp 1ā6
John N, Janamala V, Rodrigues J (2019) Impact of variable distributed generation on distribution system voltage stability. In: 2019 international conference on data science and communication (IconDSC), pp 1ā6
Rahmanov NR, Karimov OZ (2020) AC and DC combined microgrid, modeling and operation. In: Mahdavi Tabatabaei N, Kabalci E, Bizon N (eds) Microgrid architectures, control and protection methods. Power systems. Springer, Cham. https://doi.org/10.1007/978-3-030-23723-3_3
Yazdanian M, Mehrizi-Sani A (2014) Distributed control techniques in microgrids. IEEE Trans Smart Grid 5(6):2901ā2909
Bordons C, Garcia-Torres F, Ridao MA (2020) Microgrid control issues. In: Model predictive control of microgrids. Advances in industrial control. Springer, Cham. https://doi.org/10.1007/978-3-030-24570-2_1
Chowdhury MKI (2016) Pre and post controller based MVC architecture for web application. In: 2016 5th international conference on informatics, electronics and vision (ICIEV), pp 1ā6
Prainetr S, Phurahong T, Janprom K, Prainetr N (2019) Design tuning PID controller for temperature control using ant colony optimization. In: 2019 IEEE 2nd international conference on power and energy applications (ICPEA), pp 1ā6
Taher SA, Zolfaghari M, Cho C, Abedi M, Shahidehpou M (2017) A new approach for soft synchronization of microgrid using robust control theory. IEEE Trans Power Deliv 32(3):13701381
Taher SA, Zolfaghari M (2014) Designing robust controller to improve current-sharing for parallel-connected inverter-based DGs considering line impedance impact in microgrid networks. Electr Power Energy Syst 63:625ā644
Gopal et al (2021) Digital transformation through advances in artificial intelligence and machine learning. J Intell Fuzzy Syst (Pre-press) 1ā8. https://doi.org/10.3233/JIFS-189787
Fatema N et al (2021) Intelligent data-analytics for condition monitoring: smart grid applications. Elsevier, 268 pp. ISBN 978-0-323-85511-2. https://www.sciencedirect.com/book/9780323855105/intelligent-data-analytics-for-condition-monitoring
Smriti S et al (2018) Special issue on intelligent tools and techniques for signals, machines and automation. J Intell Fuzzy Syst 35(5):4895ā4899. https://doi.org/10.3233/JIFS-169773
Jafar A et al (2021) AI and machine learning paradigms for health monitoring system: intelligent data analytics. Springer Nature, Berlin, 496 pp. https://doi.org/10.1007/978-981-33-4412-9. ISBN 978-981-33-4412-9
Sood YR et al (2019) Applications of artificial intelligence techniques in engineering, vol 1. Springer Nature, 643 pp. https://doi.org/10.1007/978-981-13-1819-1. ISBN 978-981-13-1819-1
Yadav AK et al (2020) Soft computing in condition monitoring and diagnostics of electrical and mechanical systems. Springer Nature, Berlin, 496 pp. https://doi.org/10.1007/978-981-15-1532-3. ISBN 978-981-15-1532-3
Aggarwal S et al (2020) Meta heuristic and evolutionary computation: algorithms and applications. Springer Nature, Berlin, 949 pp. https://doi.org/10.1007/978-981-15-7571-6. ISBN 978-981-15-7571-6
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Khan, S., Iqubal, N., Prasad, S. (2022). Design of a Controller for the Microgrid to Enhance Stability and Synchronization Capability. In: Tomar, A., Malik, H., Kumar, P., Iqbal, A. (eds) Machine Learning, Advances in Computing, Renewable Energy and Communication. Lecture Notes in Electrical Engineering, vol 768. Springer, Singapore. https://doi.org/10.1007/978-981-16-2354-7_39
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