Affiliation:
1. K.Ramakrishnan College of Engineering, Samayapuram, Tiruchirappalli, India
2. Sona College of Technology, Salem, India
Abstract
This study proposes a hybrid AC/DC microgrid with plugin EVs, leveraging PSO-tuned ANFIS for voltage and power control. With the existing control, which faced challenges such as instability and complexity, the proposed approach is aimed at simplifying control through PSO, efficient power sharing, and reduced sample requirements. This innovative method contributes to improved energy management in hybrid microgrids, bridging existing research gaps. This approach streamlines neural transmission in microgrid control, addressing challenges in distributed generation power, load demand, energy storage system SOC, and AC grid power integration. Notably, the proposed PSO-ANFIS simplifies electric vehicle power references using distinct inputs for each mode, trained through PSO. This methodology is tailored for microgrids with varying power profiles, presenting a promising solution for efficient energy management. The proposed EMS was experimentally verified using MATLAB simulations of a small-scale hybrid AC/DC microgrid for every operating mode. The financial dynamics of a microgrid’s power exchange with the main grid are examined through three distinct methodologies: fuzzy logic, ANFIS (adaptive neurofuzzy inference system), and PSO-ANFIS (ANFIS optimized using particle swarm optimization). In case 1, the PSO-ANFIS approach demonstrates its superiority by achieving the lowest grid purchase power cost of 1995.24 Rs/day compared to fuzzy (2243.63 Rs/day) and ANFIS (2150.45 Rs/day), while also yielding the highest revenue from power selling to the microgrid: PSO-ANFIS (668.84 Rs/day) surpassing fuzzy (536.12 Rs/day) and ANFIS (575.35 Rs/day). Similarly, in case 2, PSO-ANFIS proves its efficiency with the lowest net price of 8619.192 Rs/day, showcasing its effectiveness in optimizing financial dynamics. Furthermore, in case 3, the revenue aligns precisely with net prices, indicating the PSO-ANFIS method’s financial advantage, generating the highest revenue of 6544.0224 Rs/day compared to fuzzy (6025.36 Rs/day) and ANFIS (6153.214 Rs/day). These findings underscore the potential utility of the PSO-ANFIS approach in optimizing microgrid operations and enhancing cost-effectiveness across various scenarios.
Subject
General Materials Science,Renewable Energy, Sustainability and the Environment,Atomic and Molecular Physics, and Optics,General Chemistry
Cited by
2 articles.
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1. A review of control strategies for optimized microgrid operations;IET Renewable Power Generation;2024-07-19
2. Fuzzy Logic-Based Control Algorithm for Smart Microgrid Energy Management;2024 4th International Conference on Innovative Practices in Technology and Management (ICIPTM);2024-02-21