Prognosis of after spot volumes at the Scandinavian electricity market

The Thesis is dedicated to development of an operative tool to support decision making in after spot trading on the Nordic electricity market. The basics of the Nordic electricity market, trading mechanisms on the spot and after spot markets are presented in the Thesis. Mathematical equations that describe electricity balance condition in the power system are offered. The main driving factors that impact deviation of actual electricity balance from the scheduled one (object) in the power system have been explored and mathematically defined. The behavioral model of the object and principal trends in change of state of the object under an impact of the driving factors are determined with the help of regression analysis made in Microsoft Office Excel. The behavioral model gives an indication for the total regulation volume (Elbas trades volume, volume of regulation market, balance power) for a certain hour that serves as the base input in estimating prices on the after spot markets. Proposals for development of methodologies of forecasting the after spot electricity prices are offered.

Stress testing and risk evaluation of new capacity payment algorithm proposed by Market Council

In the Russian Wholesale Market, electricity and capacity are traded separately. Capacity is a special good, the sale of which obliges suppliers to keep their generating equipment ready to produce the quantity of electricity indicated by the System Operator. The purpose of the formation of capacity trading was the maintenance of reliable and uninterrupted delivery of electricity in the wholesale market. The price of capacity reflects constant investments in construction, modernization and maintenance of power plants. So, the capacity sale creates favorable conditions to attract investments in the energy sector because it guarantees the investor that his investments will be returned.

Design of marine generators for alternative diesel-electric power systems

This study compares different electric propulsion systems. Results of the analysis of all the advantages and disadvantages of the different propulsion systems are given. This thesis estimates possibilities to apply different diesel-electric propulsion concepts for different vessel types. Small and medium size vessel’s power ranges are studied. The optimal delivery system is chosen. This choice is made on the base of detailed study of the concepts, electrical equipment market and comparison of mass, volume and efficiency parameters. In this thesis three marine generators are designed. They are: salient pole synchronous generator and two permanent magnet synchronous generators. Their electrical, dimensional, cost and efficiency parameters are compared. To understand all the benefits diagrams with these parameters are prepared. Possible benefits and money savings are estimated. As the result the advantages, disadvantages and boundary conditions for the permanent magnet synchronous generator application in marine electric-power systems are found out.

Economics of combined power plant and pyrolysis bio-oil production

There are reasons of necessity in bio-fuel use and bio-energy fast development. It includes the material about bio-energy technologies, applications and methods. There are basic thermodynamics and economic theories. The economic calculation presents the comparison between two combinations. There are boiler plant below 20 MW in combination with ablative pyrolysis plant for bio-oil production and CHP plant below 100 MW in combination with the RTP pyrolysis bio-oil production technology. It provides a material about wood chips and bio-oil characteristics and explains it nature, presents the situation around the bio-fuel market or bio-fuel trade. There is a description of pyrolysis technologies such as ablative and RTP. The liquid product of the pyrolysis processes is bio-oil. The bio-oil could be different even of the same production process, because of the raw material nature and characteristics. The calculation shows advantages and weaknesses of combinations and obtained a proof of suppositions. The next thing, proven by this work is the fact that to get more efficiency from energy project it is good possibility to built plants in combinations.

Performance characteristic of moving average trading rules in the Finnish stock market

The thesis examines the profitability of DMAC trading rules in the Finnish stock market over the 1996-2012 period. It contributes to the existing technical analysis literature by comparing for the first time the performance of DMAC strategies based on individual stock trading portfolios to the performance of index trading strategies based on the trading on the index (OMX Helsinki 25) that consists of the same stocks. Besides, the market frictions including transaction costs and taxes are taken into account, and the results are reported from both institutional and individual investor’s perspective. Performance characteristic of DMAC rules are evaluated by simulating 19,900 different trading strategies in total for two non- overlapping 8-year sub-periods, and decomposing the full-sample-period performance of DMAC trading strategies into distinct bullish- and bearish-period performances. The results show that the best DMAC rules have predictive power on future price trends, and these rules are able to outperform buy-and-hold strategy. Although the performance of the DMAC strategies is highly dependent on the combination of moving average lengths, the best DMAC rules of the first sub-period have also performed well during the latter sub-period in the case of individual stock trading strategies. According to the results, the outperformance of DMAC trading rules over buy-and-hold strategy is mostly attributed to their superiority during the bearish periods, and particularly, during stock market crashes.

The Anchoring Bias of Investors and the 52-Week High Momentum Strategy in the OMX Helsinki Stock Exchange: Psychological Approach to Market Efficiency

The behavioural finance literature expects systematic and significant deviations from efficiency to persist in securities markets due to behavioural and cognitive biases of investors. These behavioural models attempt to explain the coexistence of intermediate-term momentum and long-term reversals in stock returns based on the systematic violations of rational behaviour of investors. The study investigates the anchoring bias of investors and the profitability of the 52-week momentum strategy (GH henceforward). The relatively highly volatile OMX Helsinki stock exchange is a suitable market for examining the momentum effect, since international investors tend to realise their positions first from the furthest security markets by the time of market turbulence. Empirical data is collected from Thomson Reuters Datastream and the OMX Nordic website. The objective of the study is to provide a throughout research by formulating a self-financing GH momentum portfolio. First, the seasonality of the strategy is examined by taking the January effect into account and researching abnormal returns in long-term. The results indicate that the GH strategy is subject to significantly negative revenues in January, but the strategy is not prone to reversals in long-term. Then the predictive proxies of momentum returns are investigated in terms of acquisition prices and 52-week high statistics as anchors. The results show that the acquisition prices do not have explanatory power over the GH strategy’s abnormal returns. Finally, the efficacy of the GH strategy is examined after taking transaction costs into account, finding that the robust abnormal returns remain statistically significant despite the transaction costs. As a conclusion, the relative distance between a stock’s current price and its 52-week high statistic explains the profits of momentum investing to a high degree. The results indicate that intermediateterm momentum and long-term reversals are separate phenomena. This presents a challenge to current behavioural theories, which model these aspects of stock returns as subsequent components of how securities markets respond to relevant information.

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.

Insiders´ views as a predictor of stock performance : can insider trading be used to predict stock performance on the United States stock market?

This thesis studies the possibility of using information on insiders’ transactions to forecast future stock returns after the implementation of Sarbanes Oxley Act in July 2003. Insider transactions between July 2003 and August 2009 are analysed with regression tests to identify the relationships between insiders’ transactions and future stock returns. This analysis is complemented with rudimentary bootstrapping procedures to verify the robustness of the findings. The underlying assumption of the thesis is that insiders constantly receive pieces of information that indicate future performance of the company. They may not be allowed to trade on large and tangible pieces of information but they can trade on accumulation of smaller, intangible pieces of information. Based on the analysis in the thesis insiders’ profits were found not to differ from the returns from broad stock index. However, their individual transactions were found to be linked to future stock returns. The initial model was found to be unstable but some of the predictive power could be sacrificed to achieve greater stability. Even after sacrificing some predictive power the relationship was significant enough to allow external investors to achieve abnormal profits after transaction costs and taxes. The thesis does not go into great detail about timing of transactions. Delay in publishing insiders’ transactions is not taken into account in the calculations and the closed windows are not studied in detail. The potential effects of these phenomena are looked into and they do not cause great changes in the findings. Additionally the remuneration policy of an insider or a company is not taken into account even though it most likely affects the trading patterns of insiders. Even with the limitations the findings offer promising opportunities for investors to improve their investment processes by incorporating additional information from insiders’ transaction into their decisions. The findings also raise questions on how insider trading should be regulated. Insiders achieve greater returns than other investors based on superior information. On the other hand, more efficient information transfer could warrant more lenient regulation. The fact that insiders’ returns are dominated by the large investment stake they maintain all the time in their own companies also speaks for more leniency. As Sarbanes Oxley Act considerably modified the insider trading landscape, this analysis provides information that has not been available before. The thesis also constitutes a thorough analysis of insider trading phenomenon which has previously been somewhat separated into several studies.

Achieving EU energy targets – Impacts of evolutionary and revolutionary transition paths on power systems

Ambitious energy targets set by EU put pressures to increase share of renewable electricity supply in this and next decades and therefore, some EU member countries have boosted increasing renewable energy generation capacity by implementing subsidy schemes on national level. In this study, two different change approaches to increase renewable energy supply and increase self-sufficiency of supply are assessed with respect to their impacts on power system, electricity market and electricity generation costs in Finland. It is obtained that the current electricity generation costs are high compared to opportunities of earnings from present-day investor’s perspective. In addition, the growth expectations of consumptions and the price forecasts do not stimulate investing in new generation capacity. Revolutionary transition path is driven by administrative and political interventions to achieve the energy targets. Evolutionary transition path is driven by market-based mechanisms, such as market itself and emission trading scheme. It is obtained in this study that in the revolutionary transition path operation of market-based mechanisms is distorted to some extent and it is likely that this path requires providing more public financial resources compared to evolutionary transition path. In the evolutionary transition path the energy targets are not achieved as quickly but market-based mechanisms function better and investment environment endures more stable compared to revolutionary transition path.

On advancing business intelligence in the electricity retail market

In recent decades, business intelligence (BI) has gained momentum in real-world practice. At the same time, business intelligence has evolved as an important research subject of Information Systems (IS) within the decision support domain. Today’s growing competitive pressure in business has led to increased needs for real-time analytics, i.e., so called real-time BI or operational BI. This is especially true with respect to the electricity production, transmission, distribution, and retail business since the law of physics determines that electricity as a commodity is nearly impossible to be stored economically, and therefore demand-supply needs to be constantly in balance. The current power sector is subject to complex changes, innovation opportunities, and technical and regulatory constraints. These range from low carbon transition, renewable energy sources (RES) development, market design to new technologies (e.g., smart metering, smart grids, electric vehicles, etc.), and new independent power producers (e.g., commercial buildings or households with rooftop solar panel installments, a.k.a. Distributed Generation). Among them, the ongoing deployment of Advanced Metering Infrastructure (AMI) has profound impacts on the electricity retail market. From the view point of BI research, the AMI is enabling real-time or near real-time analytics in the electricity retail business. Following Design Science Research (DSR) paradigm in the IS field, this research presents four aspects of BI for efficient pricing in a competitive electricity retail market: (i) visual data-mining based descriptive analytics, namely electricity consumption profiling, for pricing decision-making support; (ii) real-time BI enterprise architecture for enhancing management’s capacity on real-time decision-making; (iii) prescriptive analytics through agent-based modeling for price-responsive demand simulation; (iv) visual data-mining application for electricity distribution benchmarking. Even though this study is from the perspective of the European electricity industry, particularly focused on Finland and Estonia, the BI approaches investigated can: (i) provide managerial implications to support the utility’s pricing decision-making; (ii) add empirical knowledge to the landscape of BI research; (iii) be transferred to a wide body of practice in the power sector and BI research community.

Forecasting financial weather - can we foresee market sentiment? Quantitative analysis of nodal prices in the New Zealand Electricity Spot Market

Time series of hourly electricity spot prices have peculiar properties. Electricity is by its nature difficult to store and has to be available on demand. There are many reasons for wanting to understand correlations in price movements, e.g. risk management purposes. The entire analysis carried out in this thesis has been applied to the New Zealand nodal electricity prices: offer prices (from 29 May 2002 to 31 March 2009) and final prices (from 1 January 1999 to 31 March 2009). In this paper, such natural factors as location of the node and generation type in the node that effects the correlation between nodal prices have been reviewed. It was noticed that the geographical factor affects the correlation between nodes more than others. Therefore, the visualisation of correlated nodes was done. However, for the offer prices the clear separation of correlated and not correlated nodes was not obtained. Finally, it was concluded that location factor most strongly affects correlation of electricity nodal prices; problems in visualisation probably associated with power losses when the power is transmitted over long distance.

Productizing of advanced service for power plants

Työn tavoitteena on kehittää ABB:lle palvelutuote, jota voidaan tarjota voimalaitosasiakkaille. Uuden palvelutuotteen tulee vastata ABB:n uuden strategian linjauksiin. Palvelulla tarjotaan asiakkaille 1.1.2015 voimaan tulleen energiatehokkuuslain määrittelemien pakollisten toimenpiteiden suoritusta. Työssä kerätään, käsitellään ja analysoidaan tietoa voimalaitosasiakkaille suunnatun palvelun tuotteistamisprosessin päätöksenteon tueksi. Palvelutuotteen kehittämistä varten tutkitaan ABB:n nykyisiä palvelutuotteita, osaamista ja referenssi projekteja, energiatehokkuuslakia, voimalaitosten energiatehokkuus-potentiaalia ja erilaisia energiakatselmusmalleja. Päätöksenteon tueksi tehdään referenssiprojektina energia-analyysi voimalaitokselle, jossa voimalaitoksesta tehdään ipsePRO simulointiohjelmalla mallinnus. Mallinnuksen ja koeajojen avulla tutkitaan voimalaitoksen minimikuorman optimointia. Markkinatutkimuksessa selvitetään lainsäädännön vaikutusta, nykyistä markkinatilannetta, potentiaalisia asiakkaita, kilpailijoita ja ABB:n mahdollisuuksia toimia alalla SWOT–analyysin avulla. Tutkimuksen tulosten perusteella tehdään päätös tuotteistaa voimalaitoksille palvelutuote, joka sisältää kaikki toimet energiatehokkuuslain asettamien vaatimusten täyttämiseen yrityksen energiakatselmuksen vastuuhenkilön, energiakatselmuksen ja kohdekatselmuksien teon osalta. Lisäksi työn aikana Energiavirasto myönsi ABB:lle pätevyyden toimia yrityksen energiakatselmuksen vastuuhenkilönä, mikä on edellytyksenä palvelun tarjoamiselle.

Kalman filter for computational market dynamics

Kalman filter is a recursive mathematical power tool that plays an increasingly vital role in innumerable fields of study. The filter has been put to service in a multitude of studies involving both time series modelling and financial time series modelling. Modelling time series data in Computational Market Dynamics (CMD) can be accomplished using the Jablonska-Capasso-Morale (JCM) model. Maximum likelihood approach has always been utilised to estimate the parameters of the JCM model. The purpose of this study is to discover if the Kalman filter can be effectively utilized in CMD. Ensemble Kalman filter (EnKF), with 50 ensemble members, applied to US sugar prices spanning the period of January, 1960 to February, 2012 was employed for this work. The real data and Kalman filter trajectories showed no significant discrepancies, hence indicating satisfactory performance of the technique. Since only US sugar prices were utilized, it would be interesting to discover the nature of results if other data sets are employed.

Electromagnetic and thermal design of a multilevel converter with high power density and reliability

Electric energy demand has been growing constantly as the global population increases. To avoid electric energy shortage, renewable energy sources and energy conservation are emphasized all over the world. The role of power electronics in energy saving and development of renewable energy systems is significant. Power electronics is applied in wind, solar, fuel cell, and micro turbine energy systems for the energy conversion and control. The use of power electronics introduces an energy saving potential in such applications as motors, lighting, home appliances, and consumer electronics. Despite the advantages of power converters, their penetration into the market requires that they have a set of characteristics such as high reliability and power density, cost effectiveness, and low weight, which are dictated by the emerging applications. In association with the increasing requirements, the design of the power converter is becoming more complicated, and thus, a multidisciplinary approach to the modelling of the converter is required. In this doctoral dissertation, methods and models are developed for the design of a multilevel power converter and the analysis of the related electromagnetic, thermal, and reliability issues. The focus is on the design of the main circuit. The electromagnetic model of the laminated busbar system and the IGBT modules is established with the aim of minimizing the stray inductance of the commutation loops that degrade the converter power capability. The circular busbar system is proposed to achieve equal current sharing among parallel-connected devices and implemented in the non-destructive test set-up. In addition to the electromagnetic model, a thermal model of the laminated busbar system is developed based on a lumped parameter thermal model. The temperature and temperature-dependent power losses of the busbars are estimated by the proposed algorithm. The Joule losses produced by non-sinusoidal currents flowing through the busbars in the converter are estimated taking into account the skin and proximity effects, which have a strong influence on the AC resistance of the busbars. The lifetime estimation algorithm was implemented to investigate the influence of the cooling solution on the reliability of the IGBT modules. As efficient cooling solutions have a low thermal inertia, they cause excessive temperature cycling of the IGBTs. Thus, a reliability analysis is required when selecting the cooling solutions for a particular application. The control of the cooling solution based on the use of a heat flux sensor is proposed to reduce the amplitude of the temperature cycles. The developed methods and models are verified experimentally by a laboratory prototype.

Households’ willingness to engage in demand response in the Finnish retail electricity market: an empirical study

If electricity users adjusted their consumption patterns according to time-variable electricity prices or other signals about the state of the power system, generation and network assets could be used more efficiently, and matching intermittent renewable power generation with electricity demand would be facilitated. This kind of adjustment of electricity consumption, or demand response, may be based on consumers’ decisions to shift or reduce electricity use in response to time-variable electricity prices or on the remote control of consumers’ electric appliances. However, while demand response is suggested as a solution to many issues in power systems, actual experiences from demand response programs with residential customers are mainly limited to short pilots with a small number of voluntary participants, and information about what kinds of changes consumers are willing and able to make and what motivates these changes is scarce. This doctoral dissertation contributes to the knowledge about what kinds of factors impact on residential consumers’ willingness and ability to take part in demand response. Saving opportunities calculated with actual price data from the Finnish retail electricity market are compared with the occurred supplier switching to generate a first estimate about how large savings could trigger action also in the case of demand response. Residential consumers’ motives to participate in demand response are also studied by a web-based survey with 2103 responses. Further, experiences of households with electricity consumption monitoring systems are discussed to increase knowledge about consumers’ interest in getting more information on their electricity use and adjusting their behavior based on it. Impacts of information on willingness to participate in demand response programs are also approached by a survey for experts of their willingness to engage in demand response activities. Residential customers seem ready to allow remote control of electric appliances that does not require changes in their everyday routines. Based on residents’ own activity, the electricity consuming activities that are considered shiftable are very limited. In both cases, the savings in electricity costs required to allow remote control or to engage in demand response activities are relatively high. Nonmonetary incentives appeal to fewer households.