Design and implementation of a multipurpose reactor for scale-up studies

In the theoretical part, the different polymerisation catalysts are introduced and the phenomena related to mixing in the stirred tank reactor are presented. Also the advantages and challenges related to scale-up are discussed. The aim of the applied part was to design and implement an intermediate-sized reactor useful for scale-up studies. The reactor setting was tested making one batch of Ziegler–Natta polypropylene catalyst. The catalyst preparation with a designed equipment setting succeeded and the catalyst was analysed. The analyses of the catalyst were done, because the properties of the catalyst were compared to the normal properties of Ziegler–Natta polypropylene catalyst. The total titanium content of the catalyst was slightly higher than in normal Ziegler–Natta polypropylene catalyst, but the magnesium and aluminium content of the catalyst were in the normal level. By adjusting the siphonation tube and adding one washing step the titanium content of the catalyst could be decreased. The particle size of the catalyst was small, but the activity was in a normal range. The size of the catalyst particles could be increased by decreasing the stirring speed. During the test run, it was noticed that some improvements for the designed equipment setting could be done. For example more valves for the chemical feed line need to be added to ensure inert conditions during the catalyst preparation. Also nitrogen for the reactor needs to separate from other nitrogen line. With this change the pressure in the reactor can be kept as desired during the catalyst preparation. The proposals for improvements are presented in the applied part. After these improvements are done, the equipment setting is ready for start-up. The computational fluid dynamics model for the designed reactor was provided by cooperation with Lappeenranta University of Technology. The experiments showed that for adequate mixing with one impeller, stirring speed of 600 rpm is needed. The computational fluid dynamics model with two impellers showed that there was no difference in the mixing efficiency if the upper impeller were pumping downwards or upwards.

Price spike forecasting in a competitive day-ahead energy market

Electricity price forecasting has become an important area of research in the aftermath of the worldwide deregulation of the power industry that launched competitive electricity markets now embracing all market participants including generation and retail companies, transmission network providers, and market managers. Based on the needs of the market, a variety of approaches forecasting day-ahead electricity prices have been proposed over the last decades. However, most of the existing approaches are reasonably effective for normal range prices but disregard price spike events, which are caused by a number of complex factors and occur during periods of market stress. In the early research, price spikes were truncated before application of the forecasting model to reduce the influence of such observations on the estimation of the model parameters; otherwise, a very large forecast error would be generated on price spike occasions. Electricity price spikes, however, are significant for energy market participants to stay competitive in a market. Accurate price spike forecasting is important for generation companies to strategically bid into the market and to optimally manage their assets; for retailer companies, since they cannot pass the spikes onto final customers, and finally, for market managers to provide better management and planning for the energy market. This doctoral thesis aims at deriving a methodology able to accurately predict not only the day-ahead electricity prices within the normal range but also the price spikes. The Finnish day-ahead energy market of Nord Pool Spot is selected as the case market, and its structure is studied in detail. It is almost universally agreed in the forecasting literature that no single method is best in every situation. Since the real-world problems are often complex in nature, no single model is able to capture different patterns equally well. Therefore, a hybrid methodology that enhances the modeling capabilities appears to be a possibly productive strategy for practical use when electricity prices are predicted. The price forecasting methodology is proposed through a hybrid model applied to the price forecasting in the Finnish day-ahead energy market. The iterative search procedure employed within the methodology is developed to tune the model parameters and select the optimal input set of the explanatory variables. The numerical studies show that the proposed methodology has more accurate behavior than all other examined methods most recently applied to case studies of energy markets in different countries. The obtained results can be considered as providing extensive and useful information for participants of the day-ahead energy market, who have limited and uncertain information for price prediction to set up an optimal short-term operation portfolio. Although the focus of this work is primarily on the Finnish price area of Nord Pool Spot, given the result of this work, it is very likely that the same methodology will give good results when forecasting the prices on energy markets of other countries.