Development of a Toolbox for Short-term Hydro Power Scheduling with a Detailed Transmission Network Representation. The hydro power model is based on successive linear programming, and the network model is based on DC Optimal Power Flow.
Development of a Toolbox for DC Optimal Power Flow. It includes a preventive secure dispatch but can also include the post-contingency rescheduling after outages. It is based on the use of Power Transfer Distribution Factors (PTDF) and only transmission lines with violations are included in the optimization.
Continuation Power Flow is a valuable tool for quasi-static simulation. It is based on a predictor-corrector scheme and is also helpful to detect and find the cause for infeasible power flow conditions.
The Newton method is a widely used algorithm for solving the Optimal Power Flow (OPF) problem. Its main strength is its quadratic convergence rate. The core idea is to solve the Karush-Kuhn-Tucker (KKT) conditions for optimality of the OPF problem by using a Newton-Raphson approach to find the zeros of the Lagrangian's first-order derivatives.
Empirical Mode Decomposition (EMD) is a data-driven method for decomposing a signal into intrinsic mode functions (IMFs) plus a residual. It has its challenges in separating frequencies close to each other (within the same octave), and in this case, mode-mixing may occur. The work has been related to how we with proper use of masking signal can improve the separtion process.