The virtual power plant (VPP) is a new and efficient solution to manage the integration of distributed energy resources (DERs) into the power system. Considering the unpredictable output of stochastic DERs

conventional scheduling strategies always set plenty of reserve aside in order to guarantee the reliability of operation

which is too conservative to gain more benefits. Thus

it is significant to research the scheduling strategies of VPPs

which can coordinate the risks and benefits of VPP operation. This paper presents a fuzzy chance-constrained scheduling model which utilizes fuzzy variables to describe uncertain features of distributed generators (DGs). Based on credibility theory

the concept of the confidence level is introduced to quantify the feasibility of the conditions

which reflects the risk tolerance of VPP operation. By transforming the fuzzy chance constraints into their equivalent forms

traditional optimization algorithms can be used to solve the optimal scheduling problem. An IEEE 6-node system is employed to prove the feasibility of the proposed scheduling model. Case studies demonstrate that the fuzzy chance strategy is superior to conservative scheduling strategies in realizing the right balance between risks and benefits.