Optimal methodology for distribution systems reconfiguration based on OPF and solved by decomposition technique

Abstract

SUMMARYThis paper presents a new and efficient methodology for distribution network reconfiguration integrated with optimal power flow (OPF) based on a Benders decomposition approach. The objective minimizes power losses, balancing load among feeders and subject to constraints: capacity limit of branches, minimum and maximum power limits of substations or distributed generators, minimum deviation of bus voltages and radial optimal operation of networks. The Generalized Benders decomposition algorithm is applied to solve the problem. The formulation can be embedded under two stages; the first one is the Master problem and is formulated as a mixed integer non-linear programming problem. This stage determines the radial topology of the distribution network. The second stage is the Slave problem and is formulated as a non-linear programming problem. This stage is used to determine the feasibility of the Master problem solution by means of an OPF and provides information to formulate the linear Benders cuts that connect both problems. The model is programmed in GAMS. The effectiveness of the proposal is demonstrated through two examples extracted from the literature.Supporting information may be found in the online version of this article.

Optimal allocation of distributed generation using a two-stage multi-objective mixed-integer-nonlinear programming

“…When we try to optimize several objectives at the same time, the search space also becomes partially ordered. To obtain the optimal solution, there will be a set of optimal trade-offs between the conflicting objectives [12,13]. However, multiobjective programming encounters difficulties in dealing with both qualitative and quantitative objectives in a decision problem.…”

Flexibility evaluation and flexible comprehensive optimization in power systems

“…"N-1" and "N-2" laws in transmission network safety and reliability evaluation and reconfiguration in distribution network operation state optimization [29] are actual examples of structure flexibility. In normal cases, there are usually some margins in the design, construction and operation of power networks.…”

“…The structure flexibility of power networks is also flexibility of system operation mode. "N-1" and "N-2" laws in transmission network safety and reliability evaluation and reconfiguration in distribution network operation state optimization [29] are actual examples of structure flexibility.…”

Annual energy loss reduction of distribution network through reconfiguration and renewable energy sources

“…However, both the studies 52,53 did not consider renewable DG and reconfiguration. Researchers have also used other optimization techniques such as simulated annealing, 54 artificial immune algorithm, 55,56 vaccine-enhanced artificial immune system, 57 modified plant growth simulation algorithm, 58 PSO, 59,60 GA 61-63 , runner root algorithm, 64 harmony search algorithm, 65 artificial bee colony algorithm, 66,67 hybrid Harmony search and particle artificial bee colony algorithm, 68 interval analysis, 69 stochastic MILP, 70 Ant Colony Optimization, 71 hybrid receding horizon control and scenario analysis, 72 nondominated sorting GA, 73 fuzzy mutated GA, 74 tabu search, 75 Benders decomposition approach, 76 and evolutionary programming. 77 Summary of the reviewed literature is presented in Tables 1 and 2. From the above literature survey, it is seen that most of the researchers have studied either DG installation or network reconfiguration for power loss minimization.…”