Estimating the Price of ROCs

The UK government introduced the Renewable Obligation (RO), a system of tradable quotas, to encourage the installation of renewable electricity capacity. Each unit of generation from renewables created a renewable obligation certificate (ROC). Electricity generators must either; earn ROCs through their own production, purchase ROCs in the market or pay the buy-out price to comply with the quota set by the RO. A unique aspect of this regulation is that all entities holding ROCs receive a share of the buy-out fund (the sum of all compliance purchases using the buy-out price). This set-up ensures that the difference between the market price for ROCs and the buy-out price should equal the expected share of the buy-out fund, as regulated entities arbitrage these two compliance options. The expected share of the buy-out fund depends on whether enough renewable generation is available to meet the quota. This analysis tests whether variables associated with renewable generation or electricity demand are correlated with, and thus can help predict, the price of ROCs.

Fractional Integration of the Price-Dividend Ratio in a Present-Value Model of Stock Prices

We re-examine the dynamics of returns and dividend growth within the present-value framework of stock prices. We find that the finite sample order of integration of returns is approximately equal to the order of integration of the first-differenced price-dividend ratio. As such, the traditional return forecasting regressions based on the price-dividend ratio are invalid. Moreover, the nonstationary long memory behaviour of the price-dividend ratio induces antipersistence in returns. This suggests that expected returns should be modelled as an AFIRMA process and we show this improves the forecast ability of the present-value model in-sample and out-of-sample.

Optimointijärjestelmän kehittäminen sähköä ja lämpöä tuottavaan voimalaitokseen

Työn tavoitteena oli kehittää automaattinen optimointijärjestelmä energiayhtiön omistamaan pieneen sähkön- ja lämmöntuotantolaitokseen (CHP-laitos). Optimointitarve perustuu energiayhtiön sähkön hankintaan sähköpörssistä, kaasun hankintahintaan, kohteen paikallisiin sähkö- ja lämpökuormituksiin ja muihin laitoksen talouteen vaikuttaviin tekijöihin. Kehitettävällä optimointijärjestelmällä ontarkoitus tulevaisuudessa hallita useita hajautetun energiantuotannon yksiköitäkeskitetysti. Työssä kehitettiin algoritmi, joka optimoi voimalaitoksen taloutta sähkötehoa säätävillä ajomalleilla ja suoralla sähköteho-ohjeella. Työssä kehitetyn algoritmin tuottamia hyötyjä selvitettiin Harjun oppimiskeskuksen CHP-laitoksen mittaushistoriatiedoilla. CHP-laitosten käytön optimointiin luotiin keskitettyyn laskentaan ja hajautettuun ohjaukseen perustuva järjestelmä. Se ohjaa CHP-laitoksia reaaliaikaisesti ja ennustaa historiatietoihin perustuvalla aikasarjamallilla laitoksen tulevaa käyttöä. Optimointijärjestelmän toimivuus ja saatu hyöty selvitettiin Harjun oppimiskeskuksen CHP-laitoksella vertaamalla mittauksista laskettua toteutunutta hyötyä optimointijärjestelmän laskemaan ennustettuun hyötyyn.

Sähkön markkinahintaa selittävät tekijät. Case: Nord Pool 2000-2005

Sähkön markkinahinta on saanut osakseen suurta huomiota viimeaikoina. Sähkömarkkinoiden vapautuminen ja päästökaupan avaaminen Euroopassa onentisestään nostanut sähkömarkkinoita näkyville lehdissä. Tämä tutkielma tutkii erilaisten tekijöiden vaikutusta sähkön markkinahintaan regressioanalyysin avulla. Edellä mainitun päästösopimusten markkinahinnan lisäksi tutkittiin kivihiilen sekä maakaasun markkinahintojen, lämpötilojen, jokien virtaamien, vesivarantojen täyttöasteiden sekä Saksan sähkömarkkinoiden hinnan vaikutusta sähkön markkinahintaan Nord Pool -sähköpörssissä. Työssä luotiin myös sähkön markkinahintaa ennustava malli. Kaikkien selittävien tekijöiden korrelaatiot olivat oletusten mukaiset ja regressioanalyysi onnistui selittämään yli 80 % sähkön markkinahinnan vaih-teluista. Merkittävimpiä selittäviä tekijöitä olivat vesivarannot sekä jokien virtaamat. Ennustavan mallin keskimääräinen suhteellinen virhe oli noin 10 %, joten ennustetarkkuus oli melko hyvä.

Competitiveness Comparison of the Electricity Production Alternatives

The competitiveness comparison is carried out for merely electricity producing alternatives. In Finland, further construction of CHP (combined heat and power) power plants will continue and cover part of the future power supply deficit, but also new condensing power plant capacity will be needed. The following types of power plants are studied: - nuclear power plant, - coal-fired condensing power plant - combined cycle gas turbine plant, - peat-fired condensing power plant. - wood-fired condensing power plant - wind power plant The calculations have been made using the annuity method with a real interest rate of 5 % perannum and with a fixed price level as of March 2003. With the annual full load utilization time of 8000 hours the nuclear electricity would cost 23,7 ¤/MWh, the gas based electricity 32,3 ¤/MWh and coal based electricity 28,1 ¤/MWh. If the influence of emission trading is taken into account,the advantage of the nuclear power will still be improved. Inorder to study the impact of changes in the input data, a sensitivity analysis has been carried out. It reveals that the advantage of the nuclear power is quite clear. E.g. the nuclear electricity is rather insensitive tothe changes of the uranium price, whereas for natural gas alternative the rising trend of gas price causes the greatest risk.

New Climate Change Related EC Directives and Their Interrelations to Green Electricity and Certificate Practices

Työn päätavoite on tutkia vihreän sähkön ja sertifikaattien kaupan ja EY:n uusien ilmastonmuutosta koskevien direktiivien ja direktiiviehdotusten välisiä yhteyksiä. Tutkimuksessa käsitellään direktiiviä sähköntuotannosta uusiutuvilla energialähteillä ja direktiiviehdotuksia Euroopan Unionin alueen päästökaupasta sekä yhdistetyn sähkön ja lämmön tuotannon lisäämisestä. Työ keskittyy erään suomalaisen metsäteollisuusyrityksen toimiin ilmastonmuutoksen hidastamiseksi. Tutkimus keskittyy pääosin EU:n suunnitelmaan aloittaa Unionin jäsenvaltioiden välinen päästökauppa, koska tämä järjestelmä tulee toteutuessaan olemaan teollisuuden kannalta merkittävä. Tilannetta on analysoitu neljän sellu- ja paperitehtaan hiilidioksidipäästölaskelmien avulla. Työssä kehitettyjä laskumalleja voidaan käyttää avuksi yhtiön muilla tehtailla. Tämän lisäksi työssä on luotu malli energiainvestointien arvioimiseksi tulevaisuudessa ottamalla päästöoikeuden hinnan vaikutus huomioon. Päästökaupan vaikutukset pohjoismaisilla vapautuneilla sähkömarkkinoilla on analysoity, koska teollinen sähkönhankinta on suuresti riippuvainen tästä markkinasta. Suomen metsäteollisuuden oma yhdistetty sähkön ja lämmön tuotanto erityisesti uusiutuvista energialähteistä tulee olemaan entistäkin tärkeämpää tiukentuvassa toimintaympäristössä. Tällä hetkellä on käynnissä kokeilu lisäarvon saamiseksi omalle sähköntuotannolle. Tällä haetaan kokemuksia ja valmiutta tulevaa päästökauppaa varten.

Comparison of electricity generation costs

The economical competitiveness of various power plant alternatives is compared. The comparison comprises merely electricity producing power plants. Combined heat and power (CHP) producing power will cover part of the future power deficit in Finland, but also condensing power plants for base load production will be needed. The following types of power plants are studied: nuclear power plant, combined cycle gas turbine plant, coal-fired condensing power plant, peat-fired condensing power plant, wood-fired condensing power plant and wind power plant. The calculations are carried out by using the annuity method with a real interest rate of 5 % per annum and with a fixed price level as of January 2008. With the annual peak load utilization time of 8000 hours (corresponding to a load factor of 91,3 %) the production costs would be for nuclear electricity 35,0 €/MWh, for gas based electricity 59,2 €/MWh and for coal based electricity 64,4 €/MWh, when using a price of 23 €/tonCO2 for the carbon dioxide emission trading. Without emission trading the production cost of gas electricity is 51,2 €/MWh and that of coal electricity 45,7 €/MWh and nuclear remains the same (35,0 €/MWh) In order to study the impact of changes in the input data, a sensitivity analysis has been carried out. It reveals that the advantage of the nuclear power is quite clear. E.g. the nuclear electricity is rather insensitive to the changes of nuclear fuel price, whereas for natural gas alternative the rising trend of gas price causes the greatest risk. Furthermore, increase of emission trading price improves the competitiveness of the nuclear alternative. The competitiveness and payback of the nuclear power investment is studied also as such by using various electricity market prices for determining the revenues generated by the investment. The profitability of the investment is excellent, if the market price of electricity is 50 €/MWh or more.

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.

Managing regulatory risks when outsourcing network-related services in the electricity distribution sector

Deregulation of the electricity sector liberated the electricity sale and production for competitive forces while in the network business, electricity transmission and distribution, natural monopoly positions were recognised. Deregulation was accompanied by efficiencyoriented thinking on the whole electricity supply industry. For electricity distribution this meant a transition from a public service towards profit-driven business guided by economic regulation. Regulation is the primary means to enforce societal and other goals in the regulated monopoly sector. The design of economic regulation is concerned with two main attributes; end-customer price and quality of electricity distribution services. Regulation limits the costs of the regulated company but also defines the desired quality of monopoly services. The characteristics of the regulatory framework and the incentives it provides are therefore decisive for the electricity distribution sector. Regulation is not a static factor; changes in the regulatory practices cause discontinuity points, which in turn generate risks. A variety of social and environmental concerns together with technological advancements have emphasised the relevance of quality regulation, which is expected to lead to the large-scale replacement of overhead lines with underground cables. The electricity network construction activity is therefore currently witnessing revolutionary changes in its competitive landscape. In a business characterised by high statutory involvement and a high level of sunk costs, recognising and understanding the regulatory risks becomes a key success factor. As a response, electricity distribution companies have turned into outsourcing to attain efficiency and quality goals. This doctoral thesis addresses the impacts of regulatory risks on electricity network construction, which is a commonly outsourced activity in the electricity distribution network sector. The chosen research approach is characterised as an action analytical research on account of the fact that regulatory risks are greatly dependent on the individual nature of the regulatory regime applied in the electricity distribution sector. The main contribution of this doctoral thesis is to develop a concept for recognising and managing the business risks stemming from economic regulation. The degree of outsourcing in the sector is expected to increase in years to come. The results of the research provide new knowledge to manage the regulatory risks when outsourcing services.

A comparison of electricity spot prices simulation using ARMA-GARCH and mean-reverting models

The aim of this work is to compare two families of mathematical models for their respective capability to capture the statistical properties of real electricity spot market time series. The first model family is ARMA-GARCH models and the second model family is mean-reverting Ornstein-Uhlenbeck models. These two models have been applied to two price series of Nordic Nord Pool spot market for electricity namely to the System prices and to the DenmarkW prices. The parameters of both models were calibrated from the real time series. After carrying out simulation with optimal models from both families we conclude that neither ARMA-GARCH models, nor conventional mean-reverting Ornstein-Uhlenbeck models, even when calibrated optimally with real electricity spot market price or return series, capture the statistical characteristics of the real series. But in the case of less spiky behavior (System prices), the mean-reverting Ornstein-Uhlenbeck model could be seen to partially succeeded in this task.

Analysis of Patterns in Electricity Spot Market Time Series

Due to its non-storability, electricity must be produced at the same time that it is consumed, as a result prices are determined on an hourly basis and thus analysis becomes more challenging. Moreover, the seasonal fluctuations in demand and supply lead to a seasonal behavior of electricity spot prices. The purpose of this thesis is to seek and remove all causal effects from electricity spot prices and remain with pure prices for modeling purposes. To achieve this we use Qlucore Omics Explorer (QOE) for the visualization and the exploration of the data set and Time Series Decomposition method to estimate and extract the deterministic components from the series. To obtain the target series we use regression based on the background variables (water reservoir and temperature). The result obtained is three price series (for Sweden, Norway and System prices) with no apparent pattern.

From Fluid Dynamics to Human Psychology.What Drives Financial Markets Towards Extreme Events

For decades researchers have been trying to build models that would help understand price performance in financial markets and, therefore, to be able to forecast future prices. However, any econometric approaches have notoriously failed in predicting extreme events in markets. At the end of 20th century, market specialists started to admit that the reasons for economy meltdowns may originate as much in rational actions of traders as in human psychology. The latter forces have been described as trading biases, also known as animal spirits. This study aims at expressing in mathematical form some of the basic trading biases as well as the idea of market momentum and, therefore, reconstructing the dynamics of prices in financial markets. It is proposed through a novel family of models originating in population and fluid dynamics, applied to an electricity spot price time series. The main goal of this work is to investigate via numerical solutions how well theequations succeed in reproducing the real market time series properties, especially those that seemingly contradict standard assumptions of neoclassical economic theory, in particular the Efficient Market Hypothesis. The results show that the proposed model is able to generate price realizations that closely reproduce the behaviour and statistics of the original electricity spot price. That is achieved in all price levels, from small and medium-range variations to price spikes. The latter were generated from price dynamics and market momentum, without superimposing jump processes in the model. In the light of the presented results, it seems that the latest assumptions about human psychology and market momentum ruling market dynamics may be true. Therefore, other commodity markets should be analyzed with this model as well.

Paperitehtaan sähkötasehallinta ja sähkön kysyntäjousto energiakustannusten hallinnassa

Paperiteollisuus on energiaintensiivistä teollisuutta, jossa on tehty pitkään työtä tuotantoprosessien energiatehokkuuden parantamiseksi. Paperitehtaan energiakustannuksiin voidaan kuitenkin vaikuttaa myös sähkötaseen hallinnalla ja sähkön kysyntäjouston avulla. Tehtaan seuraavan vuorokauden sähkön kulutus pyritään ennustamaan mahdollisimman tarkasti, mutta esimerkiksi paperitehtaan häiriötilanteissa sähkötase poikkeaa ennustetusta. Tällöin sähkötasetta voidaan korjata ensisijaisesti sähkön jälkimarkkinoiden eli Elbas- kaupankäynnin avulla. Ellei tasetta saada korjattua sähkön jälkimarkkinoilla tase-ero korjataan tasesähköllä, jonka hinta muodostuu säätösähkömarkkinoilla. Tasesähkön hinta saattaa poiketa Elspot- markkinahinnasta voimakkaasti, jolloin tase-erosta joko hyödytään tai hävitään kustannusmielessä. Tämän työn tarkoituksena on selvittää sähkötasehallinnan parantamisen ja sähkön kysyntäjouston vaikutukset paperitehtaan energiakustannuksiin. Työssä tutkittiin tehtaan sähkö-tasehallinnan nykytilannetta ja selvitettiin tase-erojen kustannusvaikuttavuutta. Lisäksi työssä luotiin ajomalleja sähkön kysyntäjouston toteuttamiselle massatehtaan eri tuotantoprosesseille, sekä määritettiin rajahintoja seuraavan vuorokauden energiaennusteeseen. Onnistunut energiaennuste perustuu paperitehtaan käynnin tarkkoihin ja ajankohtaisiin lähtötietoihin. Sähkötaseen poikkeamiin voidaan puolestaan varautua paremmin, kun informaatio tehtaan prosessien alasajosta tulee voimalaitoksen tietoon mahdollisimman aikaisin. Sähkötaseen poikkeamien hallinta voidaan tehdä, joko Elbas- kaupan tai tasesähkön avulla. Ajankohdasta ja tasepoikkeaman volyymista riippuen täytyy tehdä valinta, kumpi vaihtoehdoista on kustannusmielessä kannattavampi. Paperitehtaan eri prosesseille luoduilla ajomalleilla saatiin esiin huomattava säästöpotentiaali. Ajomallien noudattaminen vaatii suunnitelmallista tuotannon hallintaa ja sähkön Elspot- hinnan käyttäytymisen säännöllistä seurantaa. Seuraavan vuorokauden rajahintatietojen määrittämisen pohjalta voidaan arvioida, millä Elspot- hinnalla sähkön myynti muuttuu paperin tuotantoa kannattavammaksi.

Economical potential of controlling charging of electric vehicles by using price signal

The number of electric vehicles grows continuously and the implementation of charging electric vehicles is an important issue for the future. Increasing amount of electric vehicles can cause problems to distribution grid by increasing peak load. Currently charging of electric vehicles is uncontrolled, but as the amount of electric vehicles grows, smart charg-ing (controlled charging) will be one possible solution to handle this situation. In this thesis smart charging of electric vehicles is examined from electricity retailers` point of view. The purpose is to find out plausible saving potentials of smart charging, when it´s controlled by price signal. Saving potential is calculated by comparing costs of price signal controlled charging and uncontrolled charging.

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.