Generalized linear‐constrained optimal power flow for distribution networks

Abstract Optimal power flow (OPF) plays an important role in the secure and economical operation of distribution network. This paper proposes a novel generalized linear‐constrained optimal (GLOPF) model for both radial mesh networks, which iteratively approaches solution to original OPF problem. The first‐order Taylor series approximation method is applied linearize non‐linear non‐convex constraints given expansion point (TEP). In addition, objective function GLOPF only added with easy‐compute second‐order penalty on state variables, at least positive semi‐definite guarantees convexity quadratic optimization. Then TEP‐based iterative (TEP‐I) proposed construct convex optimizations, avoids complex calculation quasi‐Hessian or Hessian matrices traditional sequential programming methods. converged proved satisfy Karush–Kuhn–Tucker conditions Furthermore, first second iterations can be implemented as ‘cold‐start’ ‘warm‐start’ LOPF models, respectively. Case studies verify super‐linear convergence high accuracy model.