Towards Stable and Efficient Microgrids: Integrating Centralized and Droop Control Techniques
DOI:
https://doi.org/10.51646/jsesd.v15iMME.371Abstract
This study proposes an enhanced control strategy to address critical challenges in microgrids with distributed energy sources, particularly voltage stability and power-sharing issues. The approach utilizes a Microgrid Central Controller (MGCC) in conjunction with droop control techniques. Evaluations using real-world meteorological data and MATLAB/Simulink demonstrate significant improvements in microgrid performance. The effectiveness of this strategy highlights the importance of advanced control in optimizing renewable energy microgrid performance, paving the way for advancements in sustainable energy management.
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Wang Y, Liu Y, Sun H, Li F. 2023. Distributed secondary control for frequency restoration and power sharing in islanded AC microgrids. IEEE Transactions on Smart Grid. 14(1):321–332.
Zhang L, Alammari RA, Guerrero JM. 2022. Robust hierarchical control of grid-connected microgrids with renewable energy sources. International Journal of Electrical Power & Energy Systems. 138:107903.
Zranzese P, Ribera M, Cervone A, Iannuzzi D. 2023. Optimized control strategy for single-phase multilevel cascaded converter in a distributed PV-BESS system. Electric Power Systems Research. 214:108818.
Zhao J, Wang Z, Ma K. 2022. Real-time decentralized energy scheduling in multi-microgrid systems under uncertainty. Applied Energy. 314:118983
Rezaei M, Ghassemi A. 2023. Coordinated secondary control of low-voltage DC microgrids based on adaptive sliding mode techniques. IEEE Access. 11:43478–43489.
Shukla RR, Garg MM, Panda AK. 2024. Driving grid stability: Integrating electric vehicles and energy storage devices for eficient load frequency control in isolated hybrid microgrids. Journal of Energy Storage. 89:111654.
Liu T, Li X, Han Y. 2022. Stability-oriented distributed control of DC microgrids with electric springs. Renewable Energy. 194:936–949.
Jha SK, Kumar D, Lehtonen M. 2021. Modified V-I droop based adaptive vector control scheme for demand side management in a stand-alone microgrid. International Journal of Electrical Power & Energy Systems. 130:106950.
Bayat M, Farahani M, Ghadimi AA, Tostado‐Véliz M, Miveh MR, Jurado F. 2023. Optimal siting, sizing and setting of droop-controlled DERs in autonomous microgrids: A new paradigm in microgrid planning. Electric Power Systems Research. 225:109850.
Rajasekar N, Bilakanti N, Miyatake M, Thirunavukkarasu GS, Seyedmahmoudian M, Jamei E, Horan B, Mekhilef S, Stojcevski A. 2022. Role of optimization techniques in microgrid energy management systems—A review. Energy Strategy Reviews. 43:100899.
Choudhury S, Varghese GT, Mohanty S, Kolluru VR, Bajaj M, Blažek V, Prokop L, Mišák S. 2023. Energy management and power quality improvement of microgrid system through modified water wave optimization. Energy Reports. 9:6020–6041.
Liu J, Wang H. 2023. Hierarchical centralized control of smart microgrids under communication latency. IEEETransactions on Industrial Informatics. 19(1):345–356.
Al-Ghussain L, Guerrero JM. 2022. Centralized energy scheduling for islanded microgrids:Challenges and solutions. Energies. 15(6):2120.
Bukhsh WA, Qureshi R. 2023. Enhanced droop control for resilient microgrid operation in high-R/X ratio systems. Electric Power Systems Research. 213:108918.
Ramos-Paja CA, Peña RA. 2022. Decentralized secondary voltage regulation using consensus- based control. Renewable Energy. 195:875–884.
Zhang X, Sun Y. 2023. Multi-level coordinated control of MGCC and local agents in hybrid microgrids. International Journal of Electrical Power & Energy Systems. 146:108775.
Shahnia F, Ghosh A. 2022. Real-time hybrid control of inverter-based microgrids using predictive droop schemes. IEEE Access. 10:53324–53338.
Ranjbar AM, Taheri S. 2023. Energy optimization in hybrid microgrids using genetic algorithm- based EMS. Applied Soft Computing. 132:109953.
Nasiri M, Golkar MA. 2024. Real-time adaptive EMS in microgrids using deep reinforcement learning. Journal of Cleaner Production. 438:140499.
Yilmaz A, Ceylan I. 2023. Predictive energy management with uncertainty modeling for renewable-based microgrids. Renewable Energy. 207:1088–1102.
Khalid M, Rehman S. 2023. Review of EMS techniques in microgrids: Classification, comparison, and challenges. Energy Reports. 9:502–519.
Da Silva CA, Torres L. 2022. Comparative analysis of centralized, decentralized, and distributed energy management approaches. Sustainable Energy Technologies and Assessments. 53:102517.
Rezaei M, Ghassemi A. 2023. Coordinated secondary control of low-voltage DC microgrids based on adaptive sliding mode techniques. IEEE Access. 11:43478–43489.
Shukla RR, Garg MM, Panda AK. 2024. Driving grid stability: Integrating electric vehicles and energy storage devices for eficient load frequency control in isolated hybrid microgrids. Journal of Energy Storage. 89:111654.
Liu T, Li X, Han Y. 2022. Stability-oriented distributed control of DC microgrids with electric springs. Renewable Energy. 194:936–949.
Jha SK, Kumar D, Lehtonen M. 2021. Modified V-I droop based adaptive vector control scheme for demand side management in a stand-alone microgrid. International Journal of Electrical Power & Energy Systems. 130:106950.
Bayat M, Farahani M, Ghadimi AA, Tostado‐Véliz M, Miveh MR, Jurado F. 2023. Optimal siting, sizing and setting of droop-controlled DERs in autonomous microgrids: A new paradigm in microgrid planning. Electric Power Systems Research. 225:109850.
Rajasekar N, Bilakanti N, Miyatake M, Thirunavukkarasu GS, Seyedmahmoudian M, Jamei E, Horan B, Mekhilef S, Stojcevski A. 2022. Role of optimization techniques in microgrid energy management systems—A review. Energy Strategy Reviews. 43:100899.
Choudhury S, Varghese GT, Mohanty S, Kolluru VR, Bajaj M, Blažek V, Prokop L, Mišák S. 2023. Energy management and power quality improvement of microgrid system through modified water wave optimization. Energy Reports. 9:6020–6041.
Liu J, Wang H. 2023. Hierarchical centralized control of smart microgrids under communication latency. IEEETransactions on Industrial Informatics. 19(1):345–356.
Al-Ghussain L, Guerrero JM. 2022. Centralized energy scheduling for islanded microgrids:Challenges and solutions. Energies. 15(6):2120.
Bukhsh WA, Qureshi R. 2023. Enhanced droop control for resilient microgrid operation in high-R/X ratio systems. Electric Power Systems Research. 213:108918.
Ramos-Paja CA, Peña RA. 2022. Decentralized secondary voltage regulation using consensus- based control. Renewable Energy. 195:875–884.
Zhang X, Sun Y. 2023. Multi-level coordinated control of MGCC and local agents in hybrid microgrids. International Journal of Electrical Power & Energy Systems. 146:108775.
Shahnia F, Ghosh A. 2022. Real-time hybrid control of inverter-based microgrids using predictive droop schemes. IEEE Access. 10:53324–53338.
Ranjbar AM, Taheri S. 2023. Energy optimization in hybrid microgrids using genetic algorithm- based EMS. Applied Soft Computing. 132:109953.
Nasiri M, Golkar MA. 2024. Real-time adaptive EMS in microgrids using deep reinforcement learning. Journal of Cleaner Production. 438:140499.
Yilmaz A, Ceylan I. 2023. Predictive energy management with uncertainty modeling for renewable-based microgrids. Renewable Energy. 207:1088–1102.
Khalid M, Rehman S. 2023. Review of EMS techniques in microgrids: Classification, comparison, and challenges. Energy Reports. 9:502–519.
Da Silva CA, Torres L. 2022. Comparative analysis of centralized, decentralized, and distributed energy management approaches. Sustainable Energy Technologies and Assessments. 53:102517.
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