This paper derives a novel direct model predictive based power controller (DMPPC) for renewable energy systems (RES) to address voltage fluctuations caused by varying power demands and renewable source outputs. This method utilizes the bi-directional DC-DC converter in the Battery Energy Storage (BES) System to level the renewable energy output, also maintain DC bus voltage stability, with the assistance of fuzzy decision making. Based upon grid necessities and the BES system’s state of charge, the controller controls an AC/DC interlinking converter to ensure consistent AC potential and appropriate power exchange with the utility grid. This paper presents an enhanced model predictive controller with an objective function based on fuzzy objectives and limitations that dynamically adapts to external circumstances, instead of utilizing a layered control structural design for BES planning and grid control. With the aid of simulation models created with Matlab Simulink, the suggested controller's operability is confirmed. This approach demonstrates excellent reference tracking performance with minimal Total Harmonic Distortion (THD) with both non-linear as well as linear loads. This article presents the development of a basic hybrid microgrid prototype.
Moghadasi A, Sargolzaei A, Anzalchi A, Moghaddami M, Khalilnejad A, Sarwat A. A model predictive power control approach for a three-phase single-stage grid-tied PV module-integrated converter. IEEE Transactions on Industry Applications. 2017;54(2):1823–31.
2.
Mohankumar M, Balamurugan K, Singaravel G, Menaka SR. A Dynamic Workflow Scheduling Method based on MCDM Optimization that Manages Priority Tasks for Fault Tolerance. International Academic Journal of Science and Engineering. 2024;11(1):9–14.
3.
Dong H, Xu Z, Song P, Tang G, Xu Q, Sun L. Optimized power redistribution of offshore wind farms integrated VSC-MTDC transmissions after onshore converter outage. IEEE Transactions on Industrial Electronics. 2016;64(11):8948–58.
4.
Dinesh R, Myilraj R, Ragul G, Kumar TR, Singaravel G. Energy Efficient Task Allocation Algorithm for Fog Computing Networks. International Journal of Advances in Engineering and Emerging Technology. 2023;14(1):46–51.
5.
Han Y, Li H, Shen P, Coelho EAA, Guerrero JM. Review of active and reactive power sharing strategies in hierarchical controlled microgrids. IEEE Transactions on Power Electronics. 2016;32(3):2427–51.
6.
Ikechukwu O, Aniekan E, Paul S. Design of a Beam Structure for Failure Prevention at Critical Loading Conditions. International Academic Journal of Innovative Research. 2019;6(1):53–65.
7.
Shadmand MB, Li X, Balog RS, Abu Rub H. Constrained decoupled power predictive controller for a single‐phase grid‐tied inverter. IET Renewable Power Generation. 2017;11(5):659–68.
8.
Boopathy EV, Niranjana MI, Prasath S, Sivabalvigneshan P, Sanjesh R, Sanjay S, et al. : IOT-Enabled Robotic Firefighter for Advanced Fire Detection and Suppression. . Archives for Technical Sciences/Arhiv za Tehnicke Nauke. 2025;1(32).
9.
Kumar PS, Lenine D, Kiran PS, Tummala SK, Al-Jawahry HM, Singh S. Energy management system for small scale hybrid wind solar battery based microgrid. InE3S Web of Conferences EDP Sciences. 2023;391:01138.
10.
Kang J, Kim J, Sohn MM. Supervised learning-based Lifetime Extension of Wireless Sensor Network Nodes. J Internet Serv Inf Secur. 2019;9(4):59–67.
11.
Chaiyatham T, Ngamroo I. Improvement of power system transient stability by PV farm with fuzzy gain scheduling of PID controller. IEEE Systems Journal. 2014;11(3):1684–91.
12.
Lee JH, Teraoka F. Guest editorial: Advances in wireless mobile and sensor technologies. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications. 2010;1(2–3):1–2.
13.
Benadli R, Bjaoui M, Khiari B, Sellami A. Sliding mode control of hybrid renewable energy system operating in grid connected and stand-alone mode. Power Electronics and Drives. 2021;6.
14.
Kayalvizhi S, Kumar DV. Load frequency control of an isolated micro grid using fuzzy adaptive model predictive control. IEEE Access. IEEE Access. 2017;5:16241–51.
15.
Liu X, Wang D, Peng Z. Cascade-free fuzzy finite-control-set model predictive control for nested neutral point-clamped converters with low switching frequency. IEEE Transactions on Control Systems Technology. 2018;27(5):2237–44.
16.
Wang B, Yang L, Wu F, Chen D. Fuzzy predictive functional control of a class of non‐linear systems. IET Control Theory & Applications. 2019;13(14):2281–8.
17.
Liu X, Wang D, Peng Z. Cascade-free fuzzy finite-control-set model predictive control for nested neutral point-clamped converters with low switching frequency. IEEE Transactions on Control Systems Technology. 2018;27(5):2237–44.
18.
Hu J, Xu Y, Cheng KW, Guerrero JM. A model predictive control strategy of PV-Battery microgrid under variable power generations and load conditions. Applied Energy. 2018;221:195–203.
19.
Suresh P, Lenine D. Design and Investigation of Sliding Mode Control Based DC-link Converter of Hybrid Microgrid System. International Journal of Integrated Engineering. 16(3):346–57.
20.
Priyanka G, Kumari JS, Lenine D, Tummala SK, Al-Jawahry HM, Gupta H. Reduced Common Mode Multilevel Inverter Strategy in Photovoltaic Systems. InE3S Web of Conferences. 2023;391:01136.
21.
Bozorgi AM, Gholami-Khesht H, Farasat M, Mehraeen S, Monfared M. Model predictive direct power control of three-phase grid-connected converters with fuzzy-based duty cycle modulation. IEEE Transactions on Industry Applications. 2018;54(5):4875–85.
22.
Ma T, Cintuglu MH, Mohammed OA. Control of a hybrid AC/DC microgrid involving energy storage and pulsed loads. IEEE Transactions on industry applications. IEEE Transactions on Industry Applications. 2016;53(1):567–75.
23.
Kumar PS, Suresh P, Lenine D. Performance improvement of predictive voltage control for interlinking converters of integrated microgrid. Measurement: Sensors. 2024;33:101196.
24.
Kumari JS, Babu CS, Lenine D, Lakshman J. Improvement of static performance of multilevel inverter for single-phase grid connected photovoltaic modules. . In2009 Second International Conference on Emerging Trends in Engineering & Technology. 2009;691–7.
25.
Shan Y, Hu J, Chan KW, Fu Q, Guerrero JM. Model predictive control of bidirectional DC–DC converters and AC/DC interlinking converters—A new control method for PV-wind-battery microgrids. IEEE Transactions on Sustainable Energy. 2018;10(4):1823–33.
26.
Xing X, Zhang C, He J, Chen A, Zhang Z. Model predictive control for parallel three‐level T‐type grid‐connected inverters in renewable power generations. IET Renewable Power Generation. 2017;11(11):1353–63.
27.
Dharmasena S, Choi S. Model predictive control of five-phase permanent magnet assisted synchronous reluctance motor. In2019 IEEE Applied Power Electronics Conference and Exposition . 2019;1885–90.
28.
Dong H, Xu Z, Song P, Tang G, Xu Q, Sun L. Optimized power redistribution of offshore wind farms integrated VSC-MTDC transmissions after onshore converter outage. . IEEE Transactions on Industrial Electronics. 2016;64(11):8948–58.
29.
Han H, Hou X, Yang J, Wu J, Su M, Guerrero JM. Review of power sharing control strategies for islanding operation of AC microgrids. IEEE Transactions on Smart Grid. 2015;7(1):200–15.
30.
Liu Z, Miao W, Wang W, Sun D. Comprehensive control scheme of the interlinking converter in hybrid AC/DC microgrid. CSEE Journal of Power and Energy Systems. 2020;7(4):719–29.
31.
Kayalvizhi S, Kumar DV. Load frequency control of an isolated micro grid using fuzzy adaptive model predictive control. IEEE Access. 2017;5:16241–51.
The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.