Gradient-based methods are optimization algorithms that use the gradient (or derivative) of a function to find its minimum or maximum values. These methods are particularly effective for solving problems in linear and nonlinear programming, as they iteratively update decision variables based on the direction of the steepest descent or ascent, leading to efficient solutions for optimal power flow (OPF) in energy systems.
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