*8.1. Data, Agents and Scenarios*

The following sources of data are considered: (i) hourly prices and quantities of the day-ahead and intra-day Iberian markets (data published by the Spanish electricity market operator, OMIE [38]), (ii) hourly prices and quantities submitted to the Portuguese balancing market (data reported by the Portuguese system operator, REN [41]), and (iii) hourly deviations and prices of the imbalances for producers and retailers (data reported by REN [41]). Also, the study makes use of real wind power data from a set of wind parks located in the central region of Portugal, which is available from 1 January 2009 to 31 December 2010.

The (software) agents are 12 producers (with several production units), representing the supply-side of Portugal, five retailers, representing the demand-side of Portugal and Spain, and one aggregated wind power producer, with 249 MW of installed capacity (representing 10% of the Portuguese installed capacity in 2010). To get expressive results, the data was upscaled to 2490 MW of installed capacity, by multiplying all values by a constant factor.

Table 4 presents several key features of the producer agents. As noted earlier, the forecasts for the day-ahead and intra-day markets (time horizon ranging from 18 h to 42 h, in case of the day-ahead market, and from 2 to 7 h, for the intra-day market), were obtained by considering a numerical weather prediction model coupled with an artificial neuronal networks approach. Both the numerical prediction model and the artificial neuronal approach were calibrated for the region under consideration. The normalized root mean square error of the day-ahead forecast is around 13.5%. For the new products, the wind power forecasts were obtained using the historical time series and the ANN approach.



The study involves the following seven scenarios:


For all scenarios, we consider that the agents assume their balance responsibility, including the wind power producers, meaning that all agents pay penalties for their imbalances. To quantify the relevance of both the new contract and the new marketplaces, several important parameters are simulated, notably:

