A Semi-Markov Stochastic Model for Operational Reliability Assessment of Hybrid AC and LCC-VSC-Based DC System With Remote Wind Farms

By combining the advantages of line commutated converter (LCC) and voltage source converter (VSC), the hybrid AC and LCC-VSC-based DC system (HALVDS) has broad application prospects to deliver remote wind power to the load center. Faced with the increasing uncertainties, the reliability issues of HALVDS with remote wind farms can be significantly serious, especially in the operational phase. In previous studies, the traditional reliability models are usually developed based on Markov stochastic process (MSP) where the duration times of different states are supposed to follow exponential distributions. However, in intricate operational environments, several components may not obey the above assumptions, e.g., the state duration times of wind turbines and electronic components following arbitrary distributions. Hence, the traditional method cannot be suitable for evaluating the operational reliability of HALVDS with complicated structures of various components whose state duration times follow different distributions. To address this, a semi-Markov stochastic process (SMSP) model is innovatively proposed in this paper for evaluating the operational reliability of HALVDS. By solving the integral equations of the SMSP, the operational reliability of components following arbitrary distributions can be determined. On this basis, the Lz-transform technique is applied to develop the generalized reliability models of different components, whose time-varying characteristics can be described in a unified way. The optimal AC/DC power flow (OADPF) operator is then defined to aggregate the reliability models of components to determine the operational reliability of HALVDS with complex structures. Furthermore, time-varying reliability indices of nodes and systems are defined to evaluate the spatial-temporal reliability of HALVDS. Case studies validate the effectiveness of the proposed technique.