Power-line-communication-based data transmission concept for an LVDC electricity distribution network – Analysis and implementation

Communications play a key role in modern smart grids. New functionalities that make the grids ‘smart’ require the communication network to function properly. Data transmission between intelligent electric devices (IEDs) in the rectifier and the customer-end inverters (CEIs) used for power conversion is also required in the smart grid concept of the low-voltage direct current (LVDC) distribution network. Smart grid applications, such as smart metering, demand side management (DSM), and grid protection applied with communications are all installed in the LVDC system. Thus, besides remote connection to the databases of the grid operators, a local communication network in the LVDC network is needed. One solution applied to implement the communication medium in power distribution grids is power line communication (PLC). There are power cables in the distribution grids, and hence, they may be applied as a communication channel for the distribution-level data. This doctoral thesis proposes an IP-based high-frequency (HF) band PLC data transmission concept for the LVDC network. A general method to implement the Ethernet-based PLC concept between the public distribution rectifier and the customerend inverters in the LVDC grid is introduced. Low-voltage cables are studied as the communication channel in the frequency band of 100 kHz–30 MHz. The communication channel characteristics and the noise in the channel are described. All individual components in the channel are presented in detail, and a channel model, comprising models for each channel component is developed and verified by measurements. The channel noise is also studied by measurements. Theoretical signalto- noise ratio (SNR) and channel capacity analyses and practical data transmission tests are carried out to evaluate the applicability of the PLC concept against the requirements set by the smart grid applications in the LVDC system. The main results concerning the applicability of the PLC concept and its limitations are presented, and suggestion for future research proposed.

Greenhouse gas emissions from peat and biomass-derived fuels, electricity and heat — Estimation of various production chains by using LCA methodology

More discussion is required on how and which types of biomass should be used to achieve a significant reduction in the carbon load released into the atmosphere in the short term. The energy sector is one of the largest greenhouse gas (GHG) emitters and thus its role in climate change mitigation is important. Replacing fossil fuels with biomass has been a simple way to reduce carbon emissions because the carbon bonded to biomass is considered as carbon neutral. With this in mind, this thesis has the following objectives: (1) to study the significance of the different GHG emission sources related to energy production from peat and biomass, (2) to explore opportunities to develop more climate friendly biomass energy options and (3) to discuss the importance of biogenic emissions of biomass systems. The discussion on biogenic carbon and other GHG emissions comprises four case studies of which two consider peat utilization, one forest biomass and one cultivated biomasses. Various different biomass types (peat, pine logs and forest residues, palm oil, rapeseed oil and jatropha oil) are used as examples to demonstrate the importance of biogenic carbon to life cycle GHG emissions. The biogenic carbon emissions of biomass are defined as the difference in the carbon stock between the utilization and the non-utilization scenarios of biomass. Forestry-drained peatlands were studied by using the high emission values of the peatland types in question to discuss the emission reduction potential of the peatlands. The results are presented in terms of global warming potential (GWP) values. Based on the results, the climate impact of the peat production can be reduced by selecting high-emission-level peatlands for peat production. The comparison of the two different types of forest biomass in integrated ethanol production in pulp mill shows that the type of forest biomass impacts the biogenic carbon emissions of biofuel production. The assessment of cultivated biomasses demonstrates that several selections made in the production chain significantly affect the GHG emissions of biofuels. The emissions caused by biofuel can exceed the emissions from fossil-based fuels in the short term if biomass is in part consumed in the process itself and does not end up in the final product. Including biogenic carbon and other land use carbon emissions into the carbon footprint calculations of biofuel reveals the importance of the time frame and of the efficiency of biomass carbon content utilization. As regards the climate impact of biomass energy use, the net impact on carbon stocks (in organic matter of soils and biomass), compared to the impact of the replaced energy source, is the key issue. Promoting renewable biomass regardless of biogenic GHG emissions can increase GHG emissions in the short term and also possibly in the long term.

The impact of long-term brand development strategies on brand value of companies operating in high-technology markets

The objective of the current research is to investigate brand value generation. The study is conducted in the context of high-technology companies. The research aims at finding the impact of long-term brand development strategies, including advertising investments, R&D investments, R&D intensity, new products developed and design. The empirical part of the study incorporated collection of primary and secondary data on 36 companies operating in high-technology sector and being rated as top companies with the most valuable brands by Interbrand consultancy. The data contained information for six consequent years from 2008 to 2013. Obtained data was analyzed using the methods of fixed effect and random effect model (panel data analysis). The analysis showed positive effect of advertising and R&D investments on brand value of high-technology companies in the long run. The impact of remaining three strategies was not approved and further investigation is required.

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.

Yliopiston sähköverkon mallintaminen

Lappeenrannan teknillinen yliopisto tutkii älykkäiden sähköverkkojen kehittämistä. Yliopisto on hankkinut sähköverkkoonsa tuuliturbiinin ja aurinkopaneeleita, joilla pystytään tuottamaan sähköenergiaa sähköverkkoon. Näitä tuotantoja voidaan käyttää myös tutkimuksessa. Tässä työssä luodaan simulaatiomalli yliopiston sähköverkosta Matlab® Simulink® -ohjelmalla. Simulaatiomalliin mallinnetaan yliopiston sisäinen keskijänniteverkko ja osa pienjänniteverkosta. Simulaatiomalli toteutetaan ohjelman valmiilla komponenteilla, joihin lasketaan tarvittavat parametrit. Tuuliturbiinin ja aurinkopaneelien sähköntuotantotehot määritetään säätiladatojen avulla. Verkon komponenteille lasketaan arvot komponenttien tyyppitietojen perusteella ja asetetaan simulaatiomallin parametreiksi. Simulaatiomalli luodaan yliopiston sisäisen verkon tehonjaon tarkastelemiseksi. Työssä selvitetään myös mahdollisuuksia luodun simulaatiomallin käyttämiseen vikatilanteiden tarkastelussa.

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.

Suomessa ja Itävallassa toimivien liiketoimintamallien siirrettävyys puupohjaisen uusiutuvan energian tuotantoon Puolaan, Romaniaan ja Slovakiaan

Tutkimus kuvaa tiedon, osaamisen ja teknologian siirtoa Suomesta ja Itävallasta Puolaan, Romaniaan ja Slovakiaan hajautetussa puupohjaisessa sähkö- ja lämpöenergian tuotannossa. Metsävaroiltaan rikas ja bioenergia-asioissa toimintatavoiltaan edistynyt Suomi toimi Metsäntutkimuslaitoksen (nykyisin Luonnonvarakeskus) johdolla tutkimuksen empiirisen aineiston tuottaneen kehittäjäverkostohankkeen pääkoordinaattorina vuosina 2011-2014. Tutkimusmenetelmänä käytettiin hankkeen dokumentaation sisällönanalyysiä. Itävalta on tunnettu edistyksellisistä bioenergia-alan tuki- ja ohjausjärjestelmistä. Suomi ja Itävalta kuuluvat EU:n viiden edistyneimmän maan joukkoon uusiutuvien energialähteiden hyödyntämisessä. Tämän työn tavoitteena oli selvittää, miten Suomessa ja Itävallassa hyvin toimivia liiketoimintamalleja voidaan siirtää kohdemaihin puupohjaisen uusiutuvan energian tuotannossa hyödynnettäviksi. Työssä kuvataan tiedonsiirtäjämaiden eli Suomen ja Itävallan ydinosaaminen kiinteän biomassan energiantuotannossa politiikkatasolta käytännön liiketoiminnan tasolle. Lisäksi työssä analysoidaan poliittisen ohjauksen merkitystä alan kehittämisessä, missä käydään läpi maakohtaiset uusiutuvan energian toimintasuunnitelmat vuodelta 2010. Lopuksi arvioidaan tiedonsiirtäjä- ja tiedonhyödyntäjämaiden välisiä eroavaisuuksia kyseisellä liiketoiminta-alueella, ja onko olemassa sellaisia tekijöitä, mitkä estävät tiedonsiirtoa tai hyväksi todettujen liiketoimintamallien soveltamista kohdemaissa. Kussakin maassa metsänomistusolosuhteet ratkaisevat kiinteän biomassan tarjonnan toimivuuden eli tilanteen toimitusketjun alkupäässä. Tuotannon ohjauksen pyrkimys on myös hyödyntää mekaanisen puunjalostuksen sivutuotevirrat mahdollisimman tarkoin energiantuotannon tarpeisiin. Yleiset taloudelliset suhdanteet vaikuttavat ketjun toimivuuteen ja tehokkuuteen. Yksin energiantuotannon tarpeisiin puunkorjuuta ei kannata suunnitella, koska se harvemmin erikseen toteutettuna on kannattavaa liiketoimintaa. Puun käyttö energiantuotantoon tarvitsee hyvin suunniteltua tuki- ja ohjausjärjestelmää, joista kansalliset hallitukset vastaavat. Suomalainen tuotannon suunnittelun ja ohjauksen ajattelutapa sekä itävaltalainen energiapuun varastointi biomassan logistiikkakeskuksiin koettiin kohdemaiden yrittäjäkunnassa varteenotettavimpina liiketoiminnan kehittämisvaihtoehtoina paikallisissa toimintaympäristöissä. Lean-tuotantoajatteluun kuuluva hukan poistaminen toimitusketjusta liittyy mm. varastonhallinnan järjestelyihin ja sivutuotevirtojen hyödyntämiseen. Näitä piirteitä oli myös löydettävissä tiedonhyödyntäjämaiden yritysten toiminnassa hankkeen toteutuksen aikana.

The role of nuclear power in the future energy system

Currently widely accepted consensus is that greenhouse gas emissions produced by the mankind have to be reduced in order to avoid further global warming. The European Union has set a variety of CO2 reduction and renewable generation targets for its member states. The current energy system in the Nordic countries is one of the most carbon free in the world, but the aim is to achieve a fully carbon neutral energy system. The objective of this thesis is to consider the role of nuclear power in the future energy system. Nuclear power is a low carbon energy technology because it produces virtually no air pollutants during operation. In this respect, nuclear power is suitable for a carbon free energy system. In this master's thesis, the basic characteristics of nuclear power are presented and compared to fossil fuelled and renewable generation. Nordic energy systems and different scenarios in 2050 are modelled. Using models and information about the basic characteristics of nuclear power, an opinion is formed about its role in the future energy system in Nordic countries. The model shows that it is possible to form a carbon free Nordic energy system. Nordic countries benefit from large hydropower capacity which helps to offset fluctuating nature of wind power. Biomass fuelled generation and nuclear power provide stable and predictable electricity throughout the year. Nuclear power offers better energy security and security of supply than fossil fuelled generation and it is competitive with other low carbon technologies.

Promoting Growth in the Use of Bioenergy in Europe by Converting Existing Coal-Fired Power Plants to Biomass

Repowering existing power plants by replacing coal with biomass might offer an interesting option to ease the transition from fossil fuels to renewable energy sources and promote a fur-ther expansion of bioenergy in Europe, on account of the potential to decrease greenhouse gas emissions, as well as other pollutants (SOx, NOx, etcetera). In addition, a great part of the appeal of repowering projects comes from the opportunity to reuse the vast existing invest-ment and infrastructure associated with coal-based power generation. Even so, only a limited number of experiences with repowering are found. Therefore, efforts are required to produce technical and scientific evidence to determine whether said technology might be considered feasible for its adoption within European conditions. A detailed evaluation of the technical and economic aspects of this technology constitutes a powerful tool for decision makers to define the energy future for Europe. To better illustrate this concept, a case study is analyzed. A Slovakian pulverized coal plant was used as the basis for determining the effects on perfor-mance, operation, maintenance and cost when fuel is shifted to biomass. It was found that biomass fuel properties play a crucial role in plant repowering. Furthermore, results demon-strate that this technology offers renewable energy with low pollutant emissions at the cost of reduced capacity, relatively high levelized cost of electricity and sometimes, a maintenance-intensive operation. Lastly, regardless of the fact that existing equipment can be reutilized for the most part, extensive additions/modifications may be required to ensure a safe operation and an acceptable performance.

Cross-border transmission capacity development – Experiences from the Nordic electricity markets

The liberalisation of the wholesale electricity markets has been considered an efficient way to organise the markets. In Europe, the target is to liberalise and integrate the common European electricity markets. However, insufficient transmission capacity between the market areas hampers the integration, and therefore, new investments are required. Again, massive transmission capacity investments are not usually easy to carry through. This doctoral dissertation aims at elaborating on critical determinants required to deliver the necessary transmission capacity investments. The Nordic electricity market is used as an illustrative example. This study suggests that changes in the governance structure have affected the delivery of Nordic cross-border investments. In addition, the impacts of not fully delivered investments are studied in this doctoral dissertation. An insufficient transmission network can degrade the market uniformity and may also cause a need to split the market into smaller submarkets. This may have financial impacts on market actors when the targeted efficient sharing of resources is not met and even encourage gaming. The research methods applied in this doctoral dissertation are mainly empirical ranging from a Delphi study to case studies and numerical calculations.

Impacts of capacity remunerative mechanisms on cross-border trade

The European ambitious targets to increase the share of renewable generation pose a challenge to the generation adequacy. Many European member states are concerned that energy-only markets alone might not be able to deliver sufficient capacity required to meet the future electricity demand and back up shortfalls of energy from renewable energy sources (RES) during periods of low wind and sun. Many EU members consider to re-design their energy-only markets and establish different forms of capacity remunerative mechanisms (CRMs) to maintain the security of supply. There is a certain concern that market design changes at the level of EU member countries might conflict with the European goal of a single market. As soon as many European markets are highly interconnected, uncoordinated CRMs might create negative crossborder effects and hinder the achievement of the Internal Electricity Market in Europe. The pros and cons of capacity markets are well examined at the national level. However, the cross-border effects of capacity markets within the European market aiming at higher integration have received less attention. This doctoral dissertation examines the cross-border effects of unilateral implementation of CRMs applying both theoretical and case study analyses. The results show that capacity remunerative mechanisms (CRMs) may cause negative cross-border effects, especially if they are implemented unilaterally.

Modelling of changes in electricity end-use and their impacts on electricity distribution

The electricity distribution sector will face significant changes in the future. Increasing reliability demands will call for major network investments. At the same time, electricity end-use is undergoing profound changes. The changes include future energy technologies and other advances in the field. New technologies such as microgeneration and electric vehicles will have different kinds of impacts on electricity distribution network loads. In addition, smart metering provides more accurate electricity consumption data and opportunities to develop sophisticated load modelling and forecasting approaches. Thus, there are both demands and opportunities to develop a new type of long-term forecasting methodology for electricity distribution. The work concentrates on the technical and economic perspectives of electricity distribution. The doctoral dissertation proposes a methodology to forecast electricity consumption in the distribution networks. The forecasting process consists of a spatial analysis, clustering, end-use modelling, scenarios and simulation methods, and the load forecasts are based on the application of automatic meter reading (AMR) data. The developed long-term forecasting process produces power-based load forecasts. By applying these results, it is possible to forecast the impacts of changes on electrical energy in the network, and further, on the distribution system operator’s revenue. These results are applicable to distribution network and business planning. This doctoral dissertation includes a case study, which tests the forecasting process in practice. For the case study, the most prominent future energy technologies are chosen, and their impacts on the electrical energy and power on the network are analysed. The most relevant topics related to changes in the operating environment, namely energy efficiency, microgeneration, electric vehicles, energy storages and demand response, are discussed in more detail. The study shows that changes in electricity end-use may have radical impacts both on electrical energy and power in the distribution networks and on the distribution revenue. These changes will probably pose challenges for distribution system operators. The study suggests solutions for the distribution system operators on how they can prepare for the changing conditions. It is concluded that a new type of load forecasting methodology is needed, because the previous methods are no longer able to produce adequate forecasts.

Analysis of PWR-PACTEL Small Break LOCA experiment using TRACE

Currently, the power generation is one of the most significant life aspects for the whole man-kind. Barely one can imagine our life without electricity and thermal energy. Thus, different technologies for producing those types of energy need to be used. Each of those technologies will always have their own advantages and disadvantages. Nevertheless, every technology must satisfy such requirements as efficiency, ecology safety and reliability. In the matter of the power generation with nuclear energy utilization these requirements needs to be highly main-tained, especially since accidents on nuclear power plants may cause very long term deadly consequences. In order to prevent possible disasters related to the accident on a nuclear power plant strong and powerful algorithms were invented in last decades. Such algorithms are able to manage calculations of different physical processes and phenomena of real facilities. How-ever, the results acquired by the computing must be verified with experimental data.

Distributed energy resources in an electricity retailer’s short-term profit optimization

Liberalization of electricity markets has resulted in a competed Nordic electricity market, in which electricity retailers play a key role as electricity suppliers, market intermediaries, and service providers. Although these roles may remain unchanged in the near future, the retailers’ operation may change fundamentally as a result of the emerging smart grid environment. Especially the increasing amount of distributed energy resources (DER), and improving opportunities for their control, are reshaping the operating environment of the retailers. This requires that the retailers’ operation models are developed to match the operating environment, in which the active use of DER plays a major role. Electricity retailers have a clientele, and they operate actively in the electricity markets, which makes them a natural market party to offer new services for end-users aiming at an efficient and market-based use of DER. From the retailer’s point of view, the active use of DER can provide means to adapt the operation to meet the challenges posed by the smart grid environment, and to pursue the ultimate objective of the retailer, which is to maximize the profit of operation. This doctoral dissertation introduces a methodology for the comprehensive use of DER in an electricity retailer’s short-term profit optimization that covers operation in a variety of marketplaces including day-ahead, intra-day, and reserve markets. The analysis results provide data of the key profit-making opportunities and the risks associated with different types of DER use. Therefore, the methodology may serve as an efficient tool for an experienced operator in the planning of the optimal market-based DER use. The key contributions of this doctoral dissertation lie in the analysis and development of the model that allows the retailer to benefit from profit-making opportunities brought by the use of DER in different marketplaces, but also to manage the major risks involved in the active use of DER. In addition, the dissertation introduces an analysis of the economic potential of DER control actions in different marketplaces including the day-ahead Elspot market, balancing power market, and the hourly market of Frequency Containment Reserve for Disturbances (FCR-D).

Dynamic Modelling of Circulating Fluidized Bed Plant with Gas Turbine Repowering

Increasing amount of renewable energy source based electricity production has set high load control requirements for power grid balance markets. The essential grid balance between electricity consumption and generation is currently hard to achieve economically with new-generation solutions. Therefore conventional combustion power generation will be examined in this thesis as a solution to the foregoing issue. Circulating fluidized bed (CFB) technology is known to have sufficient scale to acts as a large grid balancing unit. Although the load change rate of the CFB unit is known to be moderately high, supplementary repowering solution will be evaluated in this thesis for load change maximization. The repowering heat duty is delivered to the CFB feed water preheating section by smaller gas turbine (GT) unit. Consequently, steam extraction preheating may be decreased and large amount of the gas turbine exhaust heat may be utilized in the CFB process to reach maximum plant electrical efficiency. Earlier study of the repowering has focused on the efficiency improvements and retrofitting to maximize plant electrical output. This study however presents the CFB load change improvement possibilities achieved with supplementary GT heat. The repowering study is prefaced with literature and theory review for both of the processes to maximize accuracy of the research. Both dynamic and steady-state simulations accomplished with APROS simulation tool will be used to evaluate repowering effects to the CFB unit operation. Eventually, a conceptual level analysis is completed to compare repowered plant performance to the state-of-the-art CFB performance. Based on the performed simulations, considerably good improvements to the CFB process parameters are achieved with repowering. Consequently, the results show possibilities to higher ramp rate values achieved with repowered CFB technology. This enables better plant suitability to the grid balance markets.