*4.2. Regression Analysis*

Table 2 presents the parameter estimates from the regression analysis as described in the previous sections. Three different regressions were applied and the comparison between real and calculated values are presented in Figures 8–11.


**Table 2.** Model parameter estimation results.

**Figure 8.** Seasonal variation: Comparison between real (grey lines) and model calculated (black lines) values. D = demand, R = renewables, SMP = system marginal price, MOE = merit order e ffect.

**Figure 9.** Daily variation: Comparison between real (points) and model calculated (lines) values. D = demand, DR = demand renewables, R = renewables, VSMP = virtual system marginal price, SMP = system marginal price, MOE = merit order effect.

**Figure 10.** Merit order curve: Comparison between real and model calculated values.

Parameters in Table 2 express either (a) the market characteristics (weather, demand, generation technologies, etc) which remain constant long term or (b) the market size (demand, conventional and renewable installed power, etc) which follow the growth of economy.

The four parameters which express the market size are:


S*max* is analogous to the installed power of conventional electricity generated systems that are dispatchable, meaning that they determine SMP through hourly price bidding in the day-ahead market. Similarly, *WT* and *PVT* are analogous to the renewable installed power, non-photovoltaics and photovoltaics, respectively. Finally, *DT* expresses the society activities and is analogous to the economic growth.

**Figure 11.** Merit order curve: Comparison between real and model calculated values. Monthly averaged values.

Thus, it is useful to compare the estimated values of these parameters with the recorded values:

