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An artificial gorilla troops optimizer for stochastic unit commitment problem solution incorporating solar, wind, and

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The Artificial Gorilla Troops Optimizer (GTO) effectively solves the unit commitment (UC) problem, reducing costs in deterministic and uncertain power system states. Integrating renewable energy (RE) further enhances cost savings and system reliability.

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Area of Science:

  • Power Systems Engineering
  • Optimization Algorithms
  • Renewable Energy Integration

Background:

  • The unit commitment (UC) problem is crucial for power system operation and management.
  • Increasing renewable energy (RE) sources introduces significant uncertainty, complicating UC problem-solving.
  • Traditional UC methods struggle with the dynamic and uncertain nature of modern power grids.

Purpose of the Study:

  • To address the complex UC problem using the Artificial Gorilla Troops Optimizer (GTO).
  • To evaluate GTO's performance in deterministic and uncertain power system scenarios, including with and without RE.
  • To quantify the cost savings and reliability improvements offered by GTO and RE integration.

Main Methods:

  • The Artificial Gorilla Troops Optimizer (GTO) was employed for UC problem-solving.
  • Uncertainty modeling utilized probability density functions (PDFs) for load and RE sources.
  • Monte Carlo Simulation (MCS) and backward reduction algorithm (BRA) were used for scenario generation and reduction.

Main Results:

  • GTO demonstrated effectiveness in solving the deterministic UC problem, achieving cost reductions of 0.2181% to 3.7528%.
  • Integration of RE resources led to a significant daily cost reduction of 19.23%.
  • GTO showed a powerful optimization capability with faster convergence for deterministic UC problems.

Conclusions:

  • GTO is a robust optimizer for deterministic UC problems, offering cost benefits and faster convergence.
  • Renewable energy integration significantly reduces operational costs.
  • Considering uncertainty in power systems enhances their reliability and realism, making GTO a valuable tool for such challenges.