Enhanced long-run incremental cost pricing considering the impact of network contingencies
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This paper improves the existing long-run incremental cost (LRIC) pricing which forms the basis for one of the two common charging methodologies that are to be adopted by the U.K.'s seven distribution network operators for charging customers connected at extra-high voltage (EHV) distribution networks from April 2012. The original model is expected to respect network security while evaluating charges based on the extent of the use of the network, which it achieves by reshaping components' capacity with their contingency factors into maximum available capacity. It then identifies the impact of a nodal injection on each component under normal conditions within the threshold of the maximum available capacity. The problem with the LRIC is that it assumes that the impact from a nodal injection is the same under both normal and contingent states, thus underestimating its impact under contingencies. In this paper, the original LRIC model is improved by considering the respective impacts from users under both normal and contingent conditions. The improved model runs incremental contingency flow analysis to determine how they affect components' flows under contingencies. In order to illustrate the differences in the reinforcement horizons, a comparison of the original and enhanced approaches is carried out on three basic distribution networks: single-branch, parallel-branch, and meshed. The new approach chooses the smaller horizons between those from normal and contingent situations to derive charges. Sensitivity analysis is introduced to reduce the calculation burden in determining components' flowincrements due to injections. The improved approach is finally testified and compared with the original model on a threebusbar system and a practical system.
|Creators||Gu, C., Li, F. and He, Y.|
|Uncontrolled Keywords||long-run increment cost, network contingency, security, network pricing|
|Departments||Faculty of Engineering & Design > Electronic & Electrical Engineering|
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