Data clustering based probabilistic optimal power flow in power systems
Data clustering based probabilistic optimal power flow in power systems is a scholarly work, published in 2018 in ''IET Generation, Transmission and Distribution''. The main subjects of the publication include power, probabilistic logic, Cholesky decomposition, data mining, wind power, Monte Carlo method, electricity market, mathematical optimization, distributed generation, electric power system, genetic algorithm, cluster analysis, and computer science. Ever increasing use of renewable energies beside other uncertain parameters in power systems makes it necessary to evaluate power system issues, probabilistically.