Dynamic stochastic fractional programming for sustainable management of electric power systems
A dynamic fractional programming (DSFP) method is developed for energy management. Ratio objectives, capacity expansion issues and random inputs can be dealt with. A case study of power generation system planning demonstrates its advantages. DSFP can reflect system efficiency and achieve better resources sustainability. This study explores system tradeoffs and supports policy analysis under uncertainty.
fractional programming sustainability generation expansion planning chance-constrained programming renewable energy stochastic uncertainty