Impact of grid reduction on modelling accuracy of line usage rates
Grid constraints have a strong influence on the results of energy system optimization models. Since energy system optimization is a problem of high complexity and data e.g. power production potential is not necessarily available for all grid nodes grid reduction is one method to overcome both. It reduces the computational burden and it may fit grid structure to given data.. This paper addresses the influence of grid reduction on line usage rates. Line usage rates are indicators to determine necessary investments for grid reinforcement. Three reduction methodologies, preserving original grid parameters, hence allowing to calculate which line of the original grid needs to be upgraded, are tested. Statistical error measures show that those reduction methodologies lead to high errors for usage rate calculation, due to the influence of the intra-zonal network. The high error rates could be reasoned and approaches were identified which might overcome them.