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Efficient energy management in microgrid

Figure 2. Flowchart of ZoA algorithm

the acquired findings and those from the moth-flame Table 1. Selected parameters for the ZOA,
optimization algorithm (MFOA) and stochastic fractal MFOA, and SFSN algorithms
search network (SFSN) to verify the effectiveness of the Algorithm Parameters
proposed method. The proposed approach is tested in ZOA T max=150, R 1=10, R 2=20,
the IEEE 13 bus system. Table 1 shows parameters for R 3=30 and R 4=50
the different algorithms to observe the initial flow of the MFOA T max=150, search agents=20,
initial load. Grid specifications are given in Table 2. a 1=2, a 2=2, G.p=0.5
SFSN T max=150, search agents=50
4.1. REEM in deterministic conditions
The ZOA solves the REEM problem under Abbreviations: MFOA: Moth-flame optimization algorithm;
SFSN: Stochastic fractal search network; ZOA: Zebra
deterministic conditions while accounting for input, optimization algorithm.
output, and constraints. An analysis of time-varying
market prices, solar irradiance load profile, and the percentage of load, solar irradiance, wind speed,
wind speed are evaluated for the performance of the and market price over a 24-h period, are shown in
proposed algorithm. The various profiles, including Figure 3A-D, respectively.

Volume 22 Issue 1 (2025) 127 doi: 10.36922/AJWEP025050030