## 5 Analysis and Discussion of the Results Obtained from the Redispatch Model in Real-Time Operation  
The most relevant results of the redispatch model using the real-time extreme scenario are shown below. The advantages and shortcomings of the proposed model are compared  
Figure 14: Economic dispatch of business as usual versus economic dispatch of generation redispatch for extreme scenarios in real time. with the unit commitment model and the operation of the system using the economic merit list. Table 5 shows the comparison of the marginal costs of the economic merit list versus the extreme real-time scenarios from number 1 to number 6, showing, in most of the periods of high, medium, and low demand, the optimal value that represents the lowest marginal cost for each simulation scenario. However, the redispatch model delivers non-optimal values of the marginal cost, causing the marginal costs of the merit list to be optimal over the redispatch model in some periods in the simulation horizon. Additionally, the redispatch model indicates the lowest operating costs in all simulation scenarios compared to the merit list, thus validating its implementation. However, the weakness in using the economic merit list is due to the fact that it does not adapt to the immediacy of the system operator to simulate extreme power system conditions with mathematical background support and timely response times. In summary, Table 5 and Figure 15 show the economic results of the redispatch model, such as operating costs (OpC) and marginal cost (MgC) in different demand periods, with a three-day simulation horizon. However, the real scenarios with the best marginal cost  
are the RTES1, RTES2, and RTES4 scenarios (70 to 89 USD/MWh), which can compete with the unit commitment and economic merit list models. It is also evident from the redispatch model that the overall operating cost of the real-time extreme scenario ranges from 23,739,307 to 25,524,673 USD. Therefore, it is shown that for these scenarios, the overall cost of operation is competitive, as opposed to the overall cost of operation of the actual scenarios using the economic merit list (40,898,179 USD). However, the most critical real scenarios of RTES3, RTES5, and RTES6 represent a true reflection of the use of coal-diesel thermal generation, where the overall operating costs range from 33,341,278 to 40,592,628 USD, close to the operating cost of the economic merit list (40,898,179 USD) which is evaluated through a base scenario with no variation in the system. From these results, we can deduce that, if we submit the redispatch using the economic merit list for RTES3, RTES5, and RTES6, the overall cost of operation could double. On the other hand, the lower operating cost of the proposed model (23,739,307 USD) is higher than the unit commitment model due to the fact that the network parameters are adapted to the reality of real-time operation. This shows that the operating cost of a unit commitment model is cheaper (15,804,718 USD). However, the unit commitment model has not been fitted with the actual variable cost functions of the plants, because its modeling is a linear cost function. Instead, the proposed work runs a redispatch model that integrates polynomial functions of the variable costs, which depend on the specific net consumption and the maximum dispatch power. In the real-time extreme scenario, a maximum dispatch power of 1050 MW is recorded without the need to limit generation. As for the convergence times of the redispatch model, it can be stated that they are acceptable (2-5 min) and meet the expectations for decision making in real-time operation, surpassing on a large scale the pre-dispatch model (1 h) and the economic merit list (3 h).