MATLAB Implementation of Interior Point Method for Optimal Power Flow

The Interior Point Method is a numerical approach for solving nonlinear programming problems. Its fundamental principle involves searching for optimal solutions within the feasible region, thereby avoiding infeasible solutions during the optimization process. In MATLAB, the Interior Point Method algorithm can be implemented to solve Optimal Power Flow (OPF) problems. Optimal Power Flow using Interior Point Method refers to determining the power flow distribution that minimizes grid losses while satisfying various constraints of the power system. Through the implementation of the Interior Point Method algorithm, power flow distributions can be calculated more accurately, thereby enhancing the stability and efficiency of power systems. Key implementation aspects in MATLAB typically involve: - Formulating the OPF problem as a nonlinear optimization problem with equality and inequality constraints - Using MATLAB's Optimization Toolbox functions like fmincon with interior-point algorithm options - Implementing constraint handling for power balance equations, generator limits, and voltage boundaries - Designing appropriate barrier functions and step size controls for convergence - Incorporating gradient calculations and Hessian approximations for efficient optimization The algorithm generally follows these steps: initialization within feasible region, barrier parameter update, search direction computation, and step size determination. Proper implementation ensures robust convergence to optimal solutions while maintaining constraint satisfaction throughout the iterative process.