article · Mathematics
A gorilla troops optimization technique provides an algorithmic approach to resolving optimal power flow problems within electrical power systems. The method mirrors collective gorilla behaviours, including migrating to unfamiliar or specific spots, travelling towards peers, following the silverback, and competing for females. It targets multiple objectives simultaneously, specifically lowering fuel expenditure, cutting power losses, and decreasing harmful emissions, while consistently satisfying transmission requirements and consumer power demand. Testing of the developed technique was conducted across an IEEE standard 30-bus system and a practical electrical power network in Egypt. Statistical assessments and comparisons against several modern algorithms, including CST, GWT, ISHT, NBT, and SST, demonstrate that this computational tool offers robust and efficient problem-solving capabilities when managing electrical power flow operations.
Managing electrical grids requires balancing operational expenses, energy losses, and environmental impacts while reliably supplying electricity. Optimization algorithms that efficiently handle these competing demands help grid operators cut operating costs and curb harmful emissions. Establishing robust computational techniques ensures that modern power systems function dependably under complex constraints, supporting cleaner and more economical energy distribution.
The method could be integrated into energy management software used by electrical grid operators and power utility planners to optimize dispatch schedules. Validated through simulations on standard benchmarks and an operational Egyptian power system, the research represents an applied algorithm tested in simulation, placing it at a stage prior to live grid integration and operational deployment.
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This paper presents a developed solution based on gorilla troops optimization technique for OPFP in EPSs. The GTOT is motivated by gorillas’ group behaviors in which several methods are replicated, such as migration to an unfamiliar location, traveling to other gorillas, migration toward a specific spot, accompanying the silverback, and competing for adult females. The multi-dimension OPFP in EPSs is examined in this article with numerous optimizing objectives of fuel cost, power losses, and harmful pollutants. The system’s power demand and transmission losses must be met as well. The developed GTOT’s evaluation is conducted using an IEEE standard 30-bus EPS and practical EPS from Egypt. The created GTOT is employed in numerous evaluations and statistical analyses using many modern methods such as CST, GWT, ISHT, NBT, and SST. When compared to other similar approaches in the literature, the simulated results demonstrate the GTOT’s solution efficiency and robustness.
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DOI: 10.3390/math10101636
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