Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
The effective control and management strategies are crucial for ensuring the best performance of hybrid systems based on renewable energies and ensuring a dependable energy system with high efficiency. The energy flow management problem of a system with several sources can be addressed in one of three ways: through the use of control strategies, strategies based on predetermined rules, or optimization-based strategies. The main purpose of this work is to developpe a Stateflow-based energy management strategy for a 6-kilowatt photovoltaic array and battery hybrid source to supply an alternative load which also relies on grid power. Indirect control, also known as the voltage-based maximum power point tracking, is used to get the most energy out of a solar array. A fuzzy logic-based control technique is then applied to regulate direct current link voltage, and a Model Predictive Control is developed to fine-tune of the bidirectional converter. To show how efficient the proposed energy management strategy is when implemented using the Stateflow simulator in Matlab/Simulink software. The simulation results demonstrated the effectiveness of stateflow based energy management and its ability to adapt to weather conditions (irradiation) and load variations in different modes of operations of hybrid system include grid-connected and grid-non connected modes. The suggested Stateflow-based energy management is efficient in performance, easy to implement, and enables simulations of the switching between operating modes. Consequently, it is deemed highly suitable for managing the hybrid system under optimal operation mode settings.
The effective control and management strategies are crucial for ensuring the best performance of hybrid systems based on renewable energies and ensuring a dependable energy system with high efficiency. The energy flow management problem of a system with several sources can be addressed in one of three ways: through the use of control strategies, strategies based on predetermined rules, or optimization-based strategies. The main purpose of this work is to developpe a Stateflow-based energy management strategy for a 6-kilowatt photovoltaic array and battery hybrid source to supply an alternative load which also relies on grid power. Indirect control, also known as the voltage-based maximum power point tracking, is used to get the most energy out of a solar array. A fuzzy logic-based control technique is then applied to regulate direct current link voltage, and a Model Predictive Control is developed to fine-tune of the bidirectional converter. To show how efficient the proposed energy management strategy is when implemented using the Stateflow simulator in Matlab/Simulink software. The simulation results demonstrated the effectiveness of stateflow based energy management and its ability to adapt to weather conditions (irradiation) and load variations in different modes of operations of hybrid system include grid-connected and grid-non connected modes. The suggested Stateflow-based energy management is efficient in performance, easy to implement, and enables simulations of the switching between operating modes. Consequently, it is deemed highly suitable for managing the hybrid system under optimal operation mode settings.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.