Probabilistic generation and transmission planning with renewable energy integration

Abstract

Renewable energy sources are playing a vital role with increasing influences in modern power grid. Among various forms of renewables, wind turbine generators and solar photovoltaic (PV) systems have drawn much attention because of their relatively mature technologies and large-scale deployment worldwide. However, wind and solar power is intermittent in nature, which poses significant uncertainties to power grid operation. Excessive curtailments have occurred for wind power in the field and caused financial losses. Facing such challenges, the conventional power system planning methods must be changed in order to accommodate grid-connected renewable energy sources reliably and economically. Traditionally, deterministic approaches for power system planning have been used, but with increasing penetration of renewable energy sources, probabilistic methods appear to be more suitable to address stochastic features and uncertainties associated with the overall system. In this paper, an extensive literature review is conducted on probabilistic methods for generation and transmission planning incorporating wind power. The state-of-art techniques in the field are summarized, and future research directions are recommended.