A Study On Risk Assessment Model Of Composite Generation And Transmission Systems Considering Multiple-Circuit Transmission Lines On The Same Tower

Multiple-circuit transmission lines setting on the same tower(MTLST) not only can effectively solve the contradiction between the transmission corridor and the transmission capacity, but also can save a lot of power grid construction funds. So it is paid more and more attention to by the power supply company in the days of rapidly growing demand for electricity. Especially, it is very important to the areas where are lack of transmission corridors, such as densely populated cities and remote mountainous areas with complex terrain. However, the characteristics of the architecture itself have resulted it can easily lead to common cause outages. From the perspective of power grid’s security, these could have engendered greater impact than other failures on the stability of power system during its operation.In this thesis, the risk assessment model of MTLST will pay attention to four components:wires, tower, overhead grounding wires and insulators. The model considers randomness and fuzziness of system components’outages, as well as weather conditions and load rate of wires. Incorporating this model into a composite generation and transmission system, risk indices are calculated by a system state transition sampling method based on optimal load curtailment of AC power flow model. These results are4to7.5%larger than the risk indices from traditional model. The following four cases are assumed.Case1:Without weather conditions.Case2:Neglect the MTLST model.Case3:Excluding the fuzzy factors.Case4:Load rate of wires are not related to the failure.Under other identical conditions, risk indices of the four cases demonstrate that the system subject to weather conditions and the MTLST model is even more severe. At the same time, deviations of EENS under these two conditions are5.12%and4.22%, respectively. In a bulk power system risk assessment, if it is exposed to complex meteorological conditions, or there is a large proportion of MTLST, the risk indices will be too optimistic and unacceptable without considering the MTLST model.