Impact of reliability of supply on long-term development approaches to electricity distribution networks

The Finnish electricity distribution sector, rural areas in particular, is facing major challenges because of the economic regulation, tightening supply security requirements and the ageing network asset. Therefore, the target in the distribution network planning and asset management is to develop and renovate the networks to meet these challenges in compliance with the regulations in an economically feasible way. Concerning supply security, the new Finnish Electricity Market Act limits the maximum duration of electricity supply interruptions to six hours in urban areas and 36 hours in rural areas. This has a significant impact on distribution network planning, especially in rural areas where the distribution networks typically require extensive modifications and renovations to meet the supply security requirements. This doctoral thesis introduces a methodology to analyse electricity distribution system development. The methodology is based on and combines elements of reliability analysis, asset management and economic regulation. The analysis results can be applied, for instance, to evaluate the development of distribution reliability and to consider actions to meet the tightening regulatory requirements. Thus, the methodology produces information for strategic decision-making so that DSOs can respond to challenges arising in the electricity distribution sector. The key contributions of the thesis are a network renovation concept for rural areas, an analysis to assess supply security, and an evaluation of the effects of economic regulation on the strategic network planning. In addition, the thesis demonstrates how the reliability aspect affects the placement of automation devices and how the reserve power can be arranged in a rural area network.

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.

Pienvesivoimalan uusinta

Diplomityön tavoitteena on tutkia eri vaihtoehtojen kannattavuutta pienvesivoimalan uusinnassa. Sähkönhinnan muodostus ja tulokseen vaikuttavat tekijät käsitellään kokonaisuuksinaan. Työssä tehdään kustannuslaskenta valmistajien tarjouksien perusteella ja suoritetaan esittely eri tarjouksista. Valmisteluosassa tutustutaan mitoitusarvoihin ja jos niitä ei ole miten ne selvitetään. Mittauksen kautta saadut arvot käsitellään ja sovelletaan siten, että valmistajat pystyvät käyttämään niitä. Lisäksi tutustutaan turbiinin laskentaan ja mitoitetaan Kaplan-turbiini työssä käytettyyn pienvesivoimalaan.

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.

Estudo da movimentação de plantas aquáticas imersas presentes no reservatório da UHE Eng. Souza Dias - Jupiá

O objetivo deste estudo foi desenvolver um método para determinação de pontos de reprodução e de suas respectivas importâncias na disseminação das espécies E. densa, E. najas e C. demersum no reservatório de Jupiá. Foram monitorados dez locais nos quais se encontrou registro de altas infestações dessas espécies. Dois desses locais situam-se no rio Paraná, nas lagoas denominadas de "Ferradura" e "Pernilongo"; os outros oito sítios estão localizados no rio Tietê, nas lagoas marginais "Testemunha", "Barrenta", "Vírgula" e "Flórida", e no leito do rio nos pontos "Acima da Ponte dos Barrageiros", "Abaixo da Ponte", "Baía ao Lado da Ponte" e em frente da "Praia de Itapura". Em cada um desses sítios de reprodução foram liberados e monitorados dez blocos de plantas aquáticas imersas por mês. Os blocos possuíam volume de 0,14 cm³ e receberam uma etiqueta plástica de identificação externa e uma bóia de cor laranja, com o objetivo de serem facilmente localizadas ou visualizadas à distância. Após a soltura, cada bloco foi georreferenciado por meio de um aparelho GPS, sendo o seu deslocamento avaliado a cada 15 dias. Os sítios "Lagoa Vírgula", "Lagoa Testemunha" e "Lagoa Barrenta" destacaram-se quanto ao número de blocos (30, 20 e 19 blocos, respectivamente), que percorreram distâncias superiores a 500 m e, conseqüentemente, saíram de seus respectivos locais de reprodução. A grande maioria dos blocos permaneceu dentro da "Lagoa Flórida"; somente 12 blocos saíram e alcançaram o leito do rio Tietê. O sítio denominado "Leito Acima da Ponte" foi o que mais se destacou dentre os três localizados no leito do rio Tietê, pois forneceu 18 blocos de plantas, enquanto os sítios "Abaixo da Ponte" e "Baía ao Lado da Ponte" forneceram 15 e 14 blocos, respectivamente. O sítio "Praia de Itapura" foi o que apresentou menor importância em relação ao fornecimento de plantas imersas no rio Tietê, sendo localizadas apenas 11 bóias com deslocamento superior a 500 m. Os sítios de reprodução localizados no rio Paraná também contribuíram para o fornecimento de plantas imersas ao reservatório de Jupiá; nove blocos saíram da "Lagoa Pernilongo" e apresentaram deslocamentos superiores a 500 m. Entretanto, os sítios "Lagoa Barrenta" e "Lagoa Ferradura" foram aqueles que mais contribuíram com a chegada de plantas na tomada de água da UHE Eng. Souza Dias, uma vez que foram recolhidos, respectivamente, seis e quatro blocos de plantas provenientes desses locais de dispersão. A metodologia utilizada mostrou-se eficaz quanto à avaliação da movimentação de plantas aquáticas imersas dentro do reservatório de Jupiá.

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.

The obstacles for cross-border transmission network investments in the Nordic electricity market: Case South-West link

The Nordic electricity market is often seen as an example of how to create a working, developed and integrated electricity market. Nevertheless, this thesis studies the obstacles of transmission network investments and the market integration challenges in the Nordic electricity market. The main focus is in the Nordic Transmission system operators (TSOs), which have a key role in grid development. This study introduces a case study of cancellation of South-West link, Western part, which was seen as essential grid investment in order to improve the Nordic electricity market functioning but ended up with cancellation in 2013. This study includes semi-structured theme interviews of the experts among Nordic electricity industry stakeholders. Despite the political will to create more equal prices for electricity in the Nordic market, the differing national regulation, mixed incentives created by bottleneck income and the focus moving from Nordic integration to European integration may create challenges to the Nordic electricity market integration in the future.

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.

Analyzing the Effects of the New Renewable Energy Policy in Russia on Investments into Wind, Solar and Small Hydro Power

This thesis presents an analysis of recently enacted Russian renewable energy policy based on capacity mechanism. Considering its novelty and poor coverage by academic literature, the aim of the thesis is to analyze capacity mechanism influence on investors’ decision-making process. The current research introduces a number of approaches to investment analysis. Firstly, classical financial model was built with Microsoft Excel® and crisp efficiency indicators such as net present value were determined. Secondly, sensitivity analysis was performed to understand different factors influence on project profitability. Thirdly, Datar-Mathews method was applied that by means of Monte Carlo simulation realized with Matlab Simulink®, disclosed all possible outcomes of investment project and enabled real option thinking. Fourthly, previous analysis was duplicated by fuzzy pay-off method with Microsoft Excel®. Finally, decision-making process under capacity mechanism was illustrated with decision tree. Capacity remuneration paid within 15 years is calculated individually for each RE project as variable annuity that guarantees a particular return on investment adjusted on changes in national interest rates. Analysis results indicate that capacity mechanism creates a real option to invest in renewable energy project by ensuring project profitability regardless of market conditions if project-internal factors are managed properly. The latter includes keeping capital expenditures within set limits, production performance higher than 75% of target indicators, and fulfilling localization requirement, implying producing equipment and services within the country. Occurrence of real option shapes decision-making process in the following way. Initially, investor should define appropriate location for a planned power plant where high production performance can be achieved, and lock in this location in case of competition. After, investor should wait until capital cost limit and localization requirement can be met, after that decision to invest can be made without any risk to project profitability. With respect to technology kind, investment into solar PV power plant is more attractive than into wind or small hydro power, since it has higher weighted net present value and lower standard deviation. However, it does not change decision-making strategy that remains the same for each technology type. Fuzzy pay-method proved its ability to disclose the same patterns of information as Monte Carlo simulation. Being effective in investment analysis under uncertainty and easy in use, it can be recommended as sufficient analytical tool to investors and researchers. Apart from described results, this thesis contributes to the academic literature by detailed description of capacity price calculation for renewable energy that was not available in English before. With respect to methodology novelty, such advanced approaches as Datar-Mathews method and fuzzy pay-off method are applied on the top of investment profitability model that incorporates capacity remuneration calculation as well. Comparison of effects of two different RE supporting schemes, namely Russian capacity mechanism and feed-in premium, contributes to policy comparative studies and exhibits useful inferences for researchers and policymakers. Limitations of this research are simplification of assumptions to country-average level that restricts our ability to analyze renewable energy investment region wise and existing limitation of the studying policy to the wholesale power market that leaves retail markets and remote areas without our attention, taking away medium and small investment into renewable energy from the research focus. Elimination of these limitations would allow creating the full picture of Russian renewable energy investment profile.

Apply of energy storages in electricity distribution networks and reserve capacity applications

The Thesis is dedicated to development of an operative tool to support decision making of battery energy storages implementation in distribution networks. The basics of various battery technologies, their perspectives and challenges are represented in the Thesis. Mathematical equations that describe economic effect from battery energy storage installation are offered. The main factors that influence profitability of battery settings have been explored and mathematically defined. Mathematical model and principal trends of battery storage profitability under an impact of the major factors are determined. The meaning of annual net value was introduced to show the difference between savings and required costs. The model gives a clear vision for dependencies between annual net value and main factors. Proposals for optimal network and battery characteristics are suggested.

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.

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.

Forced-air, vacuum, and hydro precooling of cauliflower (Brassica oleracea L. var. botrytis cv. Freemont): part I. determination of precooling parameters

The aim of the present study was to precool cauliflower using forced-air, vacuum and high and low flow hydro cooling methods. The weight of the precooled cauliflower heads (5000±5 g) was measured before they were placed in standard plastic crates. Cauliflower heads, whose initial temperature was 23.5 ± 0.5 ºC, were cooled until the temperature reached at 1 ºC. During the precooling process, time-dependent temperature and energy consumption were measured, and during vacuum precooling, the decreasing pressure values were recorded, and a curve of time-dependent pressure decrease (vacuum) was built. The most suitable cooling method to precool cauliflower in terms of cooling time and energy consumption was vacuum, followed by the high and low flow hydro and forced-air precooling methods, respectively. The highest weight loss was observed in the vacuum precooling method, followed by the forced-air method. However, there was an increase in the weight of the cauliflower heads in the high and low flow hydro precooling method. The best colour and hardness values were found in the vacuum precooling method. Among all methods tested, the most suitable method to precool cauliflower in terms of cooling and quality parameters was the vacuum precooling method.

Forced-air, vacuum, and hydro precooling of cauliflower (Brassica oleracea L. var. botrytis cv. Freemont): Part II. Determination of quality parameters during storage

Cauliflower heads, which were precooled using four different methods including vacuum, forced-air, and high and low flow hydro precooling, were stored under controlled atmosphere and room conditions. Controlled atmosphere conditions (CA) were as follows: 1°C temperature, 90 ± 5% relative humidity, and 0:21 [(%CO2:%O2) – (0:21) control] atmosphere composition. Room conditions (RC) were: 22±1°C temperature and 55-60% humidity. Various quality parameters of the cauliflower heads were assessed during storage (days 0, 7, 14, 21, 28, and 35) under controlled atmosphere and room conditions (days 0, 5, and 10). During storage, weight loss, deterioration rate, overall sensory quality score, hardness, and colour (L, a, b, C and α) were evaluated. In the present study, the strength and quality parameters of cauliflower under CA and RC conditions were obtained. Vacuum precooling was found to be most suitable method before cauliflower was submitted to cold storage and sent to market. Furthermore, the storage of cauliflower without precooling resulted in a significant decrease in quality parameters.

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.