Research Of Spatial And Temporal Distribution Of Transmission Network Reliability

The reliability assessment of transmission network can evaluate the degree of reliability of the transmission system quantitatively,the result is an important tool for the planning decision of transmission network.In particular the spatial and temporal distribution of transmission network can describe the reliability of the various aspects in the whole system.In this paper, system states are simulated by Sequential Monte Carlo Method(SMCM) while clocks are imitated by the Next Event Propulsion Principle(NEPP)after fully taking the operating character of Power Grid into consideration.Considering the single and double system faults, the power flow of system fault states are calculated by DC-flow method. In order to reduce the unnecessary outage cost(power interruption cost) and obtain more reliability, the Optimal Load Reduction Model(OLRM) is adopted to adjust the generator outputs and henceforth reduce loads. Several typical criteria are also given to evaluate the degree of reliability. Meanwhile some equivalent treatments for the outrage rate and repair rate of power transmission line, breaker and disconnector are done for the simplification of analysis and calculation. On the premise that guaranteeing the largest similarity between simplification model and the actual model, we further do some operation on load character to reduce calculating Memories and time. And bearing the non-determinacy of initial data in mind, outrage rate model is built by Blind Number Theory(BNT) which is combined with Sequential Monte Carlo Method(SMCM) to calculated the Blind Number index of reliability estimation.With the above models and methods, assess for spatial and temporal distribution characteristics of grid reliability, get the panel point reliability indices of the system, N-1 checksum, sort the panel point reliability, draw reliability spatial distribution, obtain temporal distribution of reliablity according to load curve and inclement weather conditions in different seasons.And using 500 k V level transmission grid network in province X as example. The results indicates the feasibility of this model and algorithm which can provide us more comprehensive information for the Reliability optimization and the power grid planning, which also can help operating crew make better decision.