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.

Converter-Fed Induction Motor Losses: Determination With IEC Methods

Energy efficiency is an important topic when considering electric motor drives market. Although more efficient electric motor types are available, the induction motor remains as the most common industrial motor type. IEC methods for determining losses and efficiency of converter-fed induction motors were introduced recently with the release of technical specification IEC/TS 60034-2-3. Determining the induction motor losses with IEC/TS 60034-2-3 method 2-3-A and assessing the practical applicability of the method are the main interests of this study. The method 2-3-A introduces a specific test converter waveform to be used in the measurements. Differences between the induction motor losses with a test converter supply, and with a DTC converter supply are investigated. In the IEC methods, the tests are run at motor rated fundamental voltage, which, in practice, requires the frequency converter to be fed with a risen input voltage. In this study, the tests are run on both frequency converters with artificially risen converter input voltage, resulting in rated motor fundamental input voltage as required by IEC. For comparison, the tests are run with both converters on normal grid input voltage supply, which results in lower motor fundamental voltage and reduced flux level, but should be more relevant from practical point of view. According to IEC method 2-3-A, tests are run at rated motor load, and to ensure comparability of the results, the rated load is used in the grid-fed converter measurements, although motor is overloaded while producing the rated torque at reduced flux level. The IEC 2-3-A method requires also sinusoidal supply test results with IEC method 2-1-1B. Therefore, the induction motor losses with the recently updated IEC 60034-2-1 method 2-1-1B are determined at the motor rated voltage, but also at two lower motor voltages, which are according to the output fundamental voltages of the two network-supplied converters. The method 2-3-A was found to be complex to apply but the results were stable. According to the results, the method 2-3-A and the test converter supply are usable for comparing losses and efficiency of different induction motors at the operating point of rated voltage, rated frequency and rated load, but the measurements do not give any prediction of the motor losses at final application. One might therefore strongly criticize the method’s main principles. It seems, that the release of IEC 60034-2-3 as a technical specification instead of a final standard for now was justified, since the practical relevance of the main method is questionable.

Uncertainty of Efficiency Measurements in Electric Drives

The two central goals of this master's thesis are to serve as a guidebook on the determination of uncertainty in efficiency measurements and to investigate sources of uncertainty in efficiency measurements in the field of electric drives by a literature review, mathematical modeling and experimental means. The influence of individual sources of uncertainty on the total instrumental uncertainty is investigated with the help of mathematical models derived for a balance and a direct air cooled calorimeter. The losses of a frequency converter and an induction motor are measured with the input-output method and a balance calorimeter at 50 and 100 % loads. A software linking features of Matlab and Excel is created to process measurement data, calculate uncertainties and to calculate and visualize results. The uncertainties are combined with both the worst case and the realistic perturbation method and distributions of uncertainty by source are shown based on experimental results. A comparison of the calculated uncertainties suggests that the balance calorimeter determines losses more accurately than the input-output method with a relative RPM uncertainty of 1.46 % compared to 3.78 - 12.74 % respectively with 95 % level of confidence at the 93 % induction motor efficiency or higher. As some principles in uncertainty analysis are open to interpretation the views and decisions of the analyst can have noticeable influence on the uncertainty in the measurement result.

Hävittäjäohjaajan kognitiivisen kuormituksen tason mittaaminen NASA-Task Load Index ja Modified Cooper-Harper -mittareilla F/A-18 virtuaalisimulaattorissa

F/A-18-monitoimihävittäjän ohjaajan tehtävän kognitiiviset vaatimukset ovat korkeat. Kognitiivisen kuormituksen taso vaikuttaa hävittäjäohjaajan suoritustasoon ja subjektiivisiin tun-temuksiin. Yerkesin ja Dodsonin periaatteen mukaisesti erittäin matala tai erittäin korkea kuormituksen taso laskee suoritustasoa. Optimaalinen kuormituksen taso ja suoritustaso saa-vutetaan jossain ääripäiden välillä. Hävittäjäohjaajan kognitiivisen kuormituksen tasoon vaikuttaa lentotehtävän suorittamiseen vaadittava henkinen ponnistelu. Vaadittavan ponnistelun taso riippuu tehtävien vaatimustasosta ja määrästä, tehtäviin käytettävissä olevasta ajasta sekä yksilöllisistä ominaisuuksista. Tutkimuksessa mitattiin kognitiivisen kuormituksen tasoa subjektiivisen arvioinnin menetelmällä NASA-TLX (National Aeronautics and Space Administration - Task Load Index) ja MCH (Modified Cooper-Harper) -mittareilla. Tutkimuksessa selvitettiin mittareiden havaintoarvojen muutosta, sensitiivisyyttä ja yhdenmukaisuutta kognitiivisen kuormituksen tason muuttuessa. Tutkimuksen mittauksiin osallistui 35 Suomen ilmavoimien aktiivisessa palveluksessa olevaa F/A-18-monitoimihävittäjäohjaajaa. Koehenkilöiden lentotuntien keskiarvo F/A-18-monitoimihävittäjällä oli 598 tuntia ja keskihajonta 445 tuntia. Koehenkilöiden tehtävänä oli lentää F/A-18-virtuaalisimulaattorilla 11 ILS (Instrument Landing System) -mittarilähestymistä eri aloitusetäisyyksiltä kiitotien kynnyksestä. Kognitiivisesti kuormitta-van mittarilähestymistehtävän aikana kuormituksen tasoa nostettiin lisätehtävillä ja vähentä-mällä tehtäviin käytettävissä olevaa aikaa. Koehenkilöitä pyydettiin ponnistelemaan mahdollisimman paljon tehtävien suorittamisen aikana hyvän suoritustason ylläpitämiseksi. Tulosten perusteella mittareiden havaintoarvot muuttuivat kognitiivisen kuormituksen tason muuttuessa. Käytettävissä olevan ajan vaikutus kognitiivisen kuormituksen tasoon oli tilastollisesti erittäin merkitsevä. Mittarit olivat sensitiivisiä kognitiivisen kuormituksen tason muutokselle ja antoivat yhdenmukaisia havaintoarvoja.

Glycemic index and glycemic load of tropical fruits and the potential risk for chronic diseases

The objective was to determine the glycemic index and glycemic load of tropical fruits and the potential risk for chronic diseases. Nine fruits were investigated: coconut water (for the purpose of this study, coconut water was classified as a “fruit”), guava, tamarind, passion fruit, custard apple, hog plum, cashew, sapodilla, and soursop. The GI and GL were determined according to the Food and Agriculture Organization protocol. The GL was calculated taking into consideration intake recommendation guidelines; 77.8% of the fruits had low GI although significant oscillations were observed in some graphs, which may indicate potential risks of disease. Coconut water and custard apple had a moderate GI, and all fruits had low GL. The fruits evaluated are healthy and can be consumed following the daily recommended amount. However, caution is recommended with fruits causing early glycemic peak and the fruits with moderated GI (coconut water and custard apple).

Effect of ultrasound treatment on quality and microbial load of carrot juice

Effect of ultrasound treatment on carrot juice was investigated through measuring pH, electrical conductivity, viscosity, visual color, total soluble solids, total sugars, total carotenoids, ascorbic acid contents and microbial load. No significant effect (p>0.05) of ultrasound treatment on pH of carrot juice was observed. Electrical conductivity, viscosity and color values gradually increased (p<0.05) with treatment time increase. Total soluble solids, total sugars, total carotenoids and ascorbic acid contents of carrot juice were significantly improved (p<0.05) due to ultrasound treatment. Moreover, significant decrease (p<0.05) in microbial load of sonicated carrot juice was observed. Results from present study suggested that ultrasound treatment could improve quality and safety of carrot juice.

A Project Portfolio Tool for Forecasting Small Projects Profitability

The case company in this study is a large industrial engineering company whose business is largely based on delivering a wide-range of engineering projects. The aim of this study is to create and develop a fairly simple Excel-based tool for the sales department. The tool’s main function is to estimate and visualize the profitability of various small projects. The study also aims to find out other possible and more long-term solutions for tackling the problem in the future. The study is highly constructive and descriptive as it focuses on the development task and in the creation of a new operating model. The developed tool focuses on estimating the profitability of the small orders of the selected project portfolio currently on the bidding-phase (prospects) and will help the case company in the monthly reporting of sales figures. The tool will analyse the profitability of a certain project by calculating its fixed and variable costs, then further the gross margin and operating profit. The bidding phase of small project is a phase that has not been covered fully by the existing tools within the case company. The project portfolio tool can be taken into use immediately within the case company and it will provide fairly accurate estimate of the profitability figures of the recently sold small projects.

Heat Demand Forecasting Models’ Development: Use of Data Mining Tools in SQL Server Analysis Services

This thesis introduces heat demand forecasting models which are generated by using data mining algorithms. The forecast spans one full day and this forecast can be used in regulating heat consumption of buildings. For training the data mining models, two years of heat consumption data from a case building and weather measurement data from Finnish Meteorological Institute are used. The thesis utilizes Microsoft SQL Server Analysis Services data mining tools in generating the data mining models and CRISP-DM process framework to implement the research. Results show that the built models can predict heat demand at best with mean average percentage errors of 3.8% for 24-h profile and 5.9% for full day. A deployment model for integrating the generated data mining models into an existing building energy management system is also discussed.

Energy Management System for LVDC Island Networks

Recent developments in power electronics technology have made it possible to develop competitive and reliable low-voltage DC (LVDC) distribution networks. Further, islanded microgrids—isolated small-scale localized distribution networks— have been proposed to reliably supply power using distributed generations. However, islanded operations face many issues such as power quality, voltage regulation, network stability, and protection. In this thesis, an energy management system (EMS) that ensures efficient energy and power balancing and voltage regulation has been proposed for an LVDC island network utilizing solar panels for electricity production and lead-acid batteries for energy storage. The EMS uses the master/slave method with robust communication infrastructure to control the production, storage, and loads. The logical basis for the EMS operations has been established by proposing functionalities of the network components as well as by defining appropriate operation modes that encompass all situations. During loss-of-powersupply periods, load prioritizations and disconnections are employed to maintain the power supply to at least some loads. The proposed EMS ensures optimal energy balance in the network. A sizing method based on discrete-event simulations has also been proposed to obtain reliable capacities of the photovoltaic array and battery. In addition, an algorithm to determine the number of hours of electric power supply that can be guaranteed to the customers at any given location has been developed. The successful performances of all the proposed algorithms have been demonstrated by simulations.

Forecasting with social media – Using Facebook likes to predict the results of the 2015 Finnish Parliamentary elections

Already one-third of the human population uses social media on a daily basis. The biggest social networking site Facebook has over billion monthly users. As a result, social media services are now recording unprecedented amount of data on human behavior. The phenomenon has certainly caught the attention of scholars, businesses and governments alike. Organizations around the globe are trying to explore new ways to benefit from the massive databases. One emerging field of research is the use of social media in forecasting. The goal is to use data gathered from online services to predict offline phenomena. Predicting the results of elections is a prominent example of forecasting with social media, but regardless of the numerous attempts, no reliable technique has been established. The objective of the research is to analyze how accurately the results of parliament elections can be forecasted using social media. The research examines whether Facebook “likes” can be effectively used for predicting the outcome of the Finnish parliament elections that took place in April 2015. First a tool for gathering data from Facebook was created. Then the data was used to create an electoral forecast. Finally, the forecast was compared with the official results of the elections. The data used in the research was gathered from the Facebook walls of all the candidates that were running for the parliament elections and had a valid Facebook page. The final sample represents 1131 candidates and over 750000 Facebook “likes”. The results indicate that creating a forecast solely based on Facebook “likes” is not accurate. The forecast model predicted very dramatic changes to the Finnish political landscape while the official results of the elections were rather moderate. However, a clear statistical relationship between “likes” and votes was discovered. In conclusion, it is apparent that citizens and other key actors of the society are using social media in an increasing rate. However, the volume of the data does not directly increase the quality of the forecast. In addition, the study faced several other limitations that should be addressed in future research. Nonetheless, discovering the positive correlation between “likes” and votes is valuable information that can be used in future studies. Finally, it is evident that Facebook “likes” are not accurate enough and a meaningful forecast would require additional parameters.