Real Solutions for Power Systems, Not Just Theories
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Algorithm for Pareto optimal reconfiguration of power distribution systems
• The first Pareto optimal approach for distribution systems reconfiguration
• Based on the best genetic algorithm for multi-criteria problems - NSGA II
• Supports distributed generators and microgrids
• Obtaines the Pareto front with active power losses and SAIFI index

•  "Far better an approximate answer to the right question than the exact answer to the wrong question." (John Tukey)

The optimization of power distribution systems through reconfiguration, as a single objective problem with constraints, was the most investigated. Typically, active power losses were adopted as the objective function. Also, usually, bounds for currents flowing through lines, bounds for voltages in each node and radial configuration were imposed as constraints. Nevertheless, in 1993, Tsai demonstrated the effectiveness of reconfiguration for improving the reliability of distribution systems.

On the other hand, some researchers have introduced, at the same time, active power losses and the interruptions in the objective function, using aggregation functions. They converted the multi-objective problem into a single objective one that assumes a sum of the selected criteria. In such approaches, the major difficulty consists in the incompatibility between criteria. In order to create an aggregation function, the criteria must be converted into the same measurement unit. In this case, the solution consists in the conversion of the criteria into costs, often, a disputable and an inaccurate solution for practical applications.

Consequently, the existence of a tool which gives the possibility to take into account more criteria in the objective function is of great interest. In order to eliminate the rigidity caused by the aggregation functions, in 2008 ( Balkan Power Coneference ), we have proposed the first approach based on Pareto optimality for problem formulation of reconfiguration, with active power losses and reliability indices as objectives.

Pareto optimality is based on a non-dominated solution as central concept. A non-dominated solution must satisfy two conditions:
• there is no other solution that is superior at least in one objective function;
• it is equal or superior with respect to other objective function values.

• In such approaches, typically, the result consists of a set of acceptable optimal solutions named Pareto optimal. The set of Pareto solutions forms the Pareto front associated with the problem. The Pareto front allows an informed decision to be made by visualizing a wide range of options; it contains the solutions that are optimal from an overall standpoint.

How it works?

The algorithm is based on several innovative ideas which make it unique, fast and effective:
• The criteria for optimization are evaluated on active power distribution systems (containing distributed generators connected directly to the main distribution system and microgrids operated in grid-connected mode)
• The original formulation of the optimization problem, as a Pareto optimal one, with two objective functions (active power losses and system average interruption frequency index)
• The original genetic algorithm is based on NSGA-II and solves the problem (as a Pareto optimal one) in a non-prohibitive execution time

For more, please read the main ideas on this Energies journal article. Also, a comparative study of existing Pareto optimal approaches for distribution system reconfiguration can be consulted here.