Handling inequalities and discrete variables in newton optimal power flow using optimal multiplier and fuzzy based limit enforcement and relaxation technique

This paper makes contributions in the Newton’s optimal power flow in two ways, in the handling of inequalities and the discrete variables. The problem of identification of binding inequalities is handled by controlled correction of the variables during iterations through the use of separate optimum multipliers for active and reactive variables. Convergence of the OPF is improved by enforcing the limit on the inequalities that oscillate around their limiting values. A fuzzy based limit enforcement and relaxation technique is used for this purpose. The problem of handling discrete variables with large step sizes is also solved using the optimum multipliers. Optimal multipliers are selected in such a way that corrections of the discrete variables automatically correspond to their available tap values. Numerical test results for standard IEEE test systems and a real power system are produced in support of the claims of the authors.

► Identification of binding inequalities is done by controlled correction of variables.
► A fuzzy based limit enforcement and relaxation technique is used.
► The problem of handling discrete variables with large step sizes is also solved.