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This paper proposes and compares three iterative approaches for handling discrete variables in optimal power flow (OPF) computations. The first two approaches rely on the sensitivities of the objective and inequality constraints with respect to discrete variables. They set the discrete variables values either by solving a mixed-integer linear programming (MILP) problem or by using a simple procedure...
As a useful tool for combinatorial optimisation over continuous and discrete variables, the mixed-integer linear programming (MILP) approach can address complex control and planning models providing high computational efficiency as well as robust behavior. On power system planning, previous work using MILP employed conventional dc load flow model neglecting reactive power, power loss and transformer...
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