Power loss minimization load flow studies using Artificial Bee Colony swarm intelligence technique

This paper presents the capability of an emerging swarm intelligence technique for power loss minimization known as the Artificial Bee Colony (ABC) used in the context of an Alternative Load Flow Analysis (LFA) technique (ABC-LFA) for the solution of a power systems network. Studies are performed considering the effect of an important parameter of the ABC, the “maxcycle” on the LFA process; experiments are conducted by applying the ABC-LFA to the Western System Coordinated Council (WSCC) 3-machine 9- bus power system and a section of the Nigerian 132-kV power transmission network Port-Harcourt Region (NPHC-132), and the results reported. The results indicate that increasing the value of the ABC “maxcycle” parameter has a pronounced effect on the results obtained by the ABC-LFA. The results also indicate the sensitivity of the ABC to low values of maxcycle parameter.

A Hierarchical Control Approach for Power Loss Minimization and Optimal Power Flow within a Meshed DC Microgrid

This work considers the DC part of a hybrid AC/DC microgrid with a meshed topology. We address cost minimization, battery scheduling and the power loss minimization within the power distribution network through constrained optimization. The novelty comes from applying differential flatness properties to the microgrid components and formulating the cost and constraints in terms of the associated B-splines parametrization of the flat outputs (the voltages and currents of the system). This allows us to obtain optimal power profiles to minimize the power dissipation and the cost of the electricity purchase from the external grid. These profiles are tracked by a model predictive controller at the higher level, while at a a lower level a controller deals with the operation of the switches within the DC/DC converters. Extensive simulations under nominal and fault-affected scenarios using realistic data validate the proposed approach.