  The widespread uncertainties have made the interaction between wind power and
power grid more complicated and difficult to model and handle. This paper
proposes an approach for the solution of unit commitment (UC) problem
incorporating multiple uncertainties that exist in both wind power and power
grid inherently, consisting of probability, possibility, and interval measures.
To handle the manifold uncertainties in a comprehensive and efficient manner,
the evidence theory (ET) is applied to fuse these uncertain variables into
Dempster-Shafer structure. Moreover, the power loss is introduced into power
balance constraints, and the extended affine arithmetic (EAA) is employed to
evaluate the uncertainty of power loss caused by the propagation of the
aforementioned uncertainties. Regarding the mix-discrete nonlinear
characteristics of the established optimization model, an enhanced grey wolf
optimizer (GWO) algorithm is developed to solve the proposed model.
Specifically, the corresponding commitment schedule is determined by a kind of
binary grey wolf optimizer (BGWO), and the economic dispatch (ED) is settled by
GWO. Finally, the IEEE 30-bus test system and a real-sized 183-bus China power
system are studied to demonstrate the validity and scalability of the proposed
model and method.
