The most important aspect of the planning of power generation dispatch is its complementary relationship with the power flows on the interconnectors of the transmission network. A plan could become invalid if the power flow created violates the transfer limit of any interconnectors. The long-term dispatch planning is more affected by this because of the relative difficulty in predicting the state of the transmission network in advance. It is generally planned in a trade-based manner, without a means to explicitly compute the power flows. Deviations in the plans are then corrected near the time of dispatch, in the expense of opportunity costs. In Europe, the flow-based market coupling is proposed in the Central Western Europe, which is an effective means for modeling the inter-zonal power flows and transfer capacity allocations. However, its usefulness for long-term planning is still limited. Especially, the Power Transfer Distribution Factors (PTDFs) of its model (key parameter for integrating power flow in dispatch planning) is stochastic and unpredictable. This paper introduces a data-driven approach to construct a zonal model for closing the gap between the long-term and the actual dispatch plan. It is able to reconstruct all zonal PTDFs existed in the system, by inverse modeling the ex-post power flow data. The paper as well presented the validity of decomposing a large zonal model into substantially smaller sub-problems, and the existence of clusters of ex-post power flow cases which share the same zonal PTDFs. These features have greatly simplified the implementation of the method.
Data-driven Tracing Method of Overload of Transmission Network Equipment
