| Abstract: |
| 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. |
| Key words: Credibility theory, Distributed energy resource (DER), Scheduling strategy, Uncertain factors, Virtual powerplant (VPP) |
| DOI：10.1186/s41601-016-0017-x |
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| Fund: |
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