# Forecasting Irregular Seasonal Power Consumption.
## 2 Materials and Methods  
### Study Area  
The study has been applied to the consumption node of a hot-dip galvanizing company. The process is carried out by coating extruded steel strips with a zinc foil that forms an alloy with the steel and gives the desired properties. This process is continuous and produces high-quality products [40]. Figure 1 shows a general scheme for the galvanizing process, where the greatest consumption is in the zinc bath. In the annealing furnace, the steel strip is preheated, and then it is immersed in a bath of molten zinc at 460 \({}^{\circ}\)C. Subsequently, the galvanized steel strip goes through the skin-pass process [41; 42; 43] after it has cooled down. The zinc bath consists of a molten alloy of Zn in a bath, which is kept at 460 \({}^{\circ}\)C by the action of two heating inductors located at the bottom of the bath. Figure 2 schematically shows the operation of the zinc bath. The bath temperature is measured as an average of the local temperatures provided by the thermocouples Ta, Tb and Tc. The inductors heat from the bottom of the bath and a natural flow inside the bath is produced so that the bath achieves the targeted temperature. Figure 1: Representation of a hot dip galvanizing process. The electrical consumption associated with the process can be seen in Figure 3. This graph shows the consumption for eight working days, measured every six minutes. It begins on 14 th November, 2009 at 00:00 am and ends on 22 nd November, 2009 at 08:00 am. There are in total 2000 measurements. The oscillations shown in the time series are produced by the action of induction heaters that keep the bath at the targeted temperature. The big peaks in consumption are produced when the bath needs to be recharged, and new Zn (dropped in ingots) is added into the bath. At this moment, the heaters must be put into full operation. From this dataset, the first 1800 observed values are used for training purposes, and the last 200 ones are used for validation. Figure 3: Electricity demand for the hot-dip galvanizing. The ticks represent the beginning of each day. The blue dataset designates the data used for training, whereas the red one represents the data used for testing and validation. Figure 2: Galvanizing section (hot dip zinc bath). Pretreated steel goes into the zinc pot, which is filled with an Al–Zn solution at 460 \({}^{\circ}\)C. thermocouples Ta, Tb and Tc measure the local temperatures in the bath. Induction heaters located at the base of the bath keep the temperature as targeted. After the bath, the steel is coated with Zn. A series of cyclical patterns can be observed (oscillations) that are repeated throughout the series, with a short-length pattern that is repeated continuously throughout the series clearly standing out. There are other patterns that are repeated irregularly, with differentiated behaviors. A closer view of the series is shown in Figure 4. In graph (a) and graph (b), a common underlying pattern can be identified, with a length of around ten time units (which means an hour, as the temperature is measured every six minutes). This first pattern is repeated regularly over the whole time period, and it is considered as a seasonality. Figure 4, graph (c) and (d) show the time series after removing the first seasonal pattern. It can also be seen that other patterns develop throughout the series in such a way that the time of their appearance or their length are not constant. Technically, this non-regular behavior cannot be considered as a seasonality, since it is not possible to predict the fluctuation pattern that will develop in the future. To make consumption  
Figure 4: Close-up version of Figure 3, where different seasonal patterns can be located: a first pattern along the whole series, with sort oscillations as shown in (**a,b**); and a second pattern covering the consumption peaks, as shown in (**c,d**). This second pattern has a different length on every appearance. predictions, it is necessary to take into account this seasonal behavior, even though it is not regular.