Increasing renewable penetration in distribution grids calls for improved monitoring and
control, where power flow (PF) model is the basis for many advanced functionalities …

In this work we design and compare different supervised learning algorithms to compute the
cost of Alternating Current Optimal Power Flow (ACOPF). The motivation for quick …

Wind energy has generally intermittent and stochastic nature. In this regard, it is more
desirable for both system and wind units' owners to operate in coordination with an energy …

Different optimization techniques are used for the training and fine‐tuning of feed forward
neural networks, for the estimation of STATCOM voltages and reactive powers. In the first …

The need to improve the performance of electrical power systems involves solving the
Optimal Power Flow (OPF) problem by determining the optimal controllable setpoints, which …

Towards decarbonisation of geographical islands in the Mediterranean, PRISMI proposes
the use of a methodology toolkit which includes a Load-Flow (LF) analysis tool. This tool is …

Artificial neural networks (ANN) have significantly improved speed and frequency of solving
optimal power flow (OPF) problems. It also proved its ability to capture generation outputs …

The optimal power flow (OPF) is a non-linear and non-convex problem that seeks the
optimization of a power system operation point to minimize the total generation cost or …

The smart grid represents a paradigm shift in energy management, aiming to optimize
energy storage and distribution while accommodating the growing demand for renewable …

The increased electrification of society and calls for improvements in electrical grid reliability
lend renewed attention to the domain of power systems optimization. For the future smart …