Das Ziel der Masterarbeit ist es zu klären, ob private Haushalte variable Strompreise akzeptieren und die Stärke der charakteristischen Merkmale zu ermitteln. Der dazu benötigte Datensatz wurde mit Hilfe einer Stated Choice Befragung im Internet ermittelt. Dafür wurden drei Gerätekategorien und ein Dreitarifmodell formuliert. Für die Auswertung wurde ein additiv verknüpftes Teilwert-Nutzenmodell und ein binäres Logit-Choice-Modell verwendet. Signifikante Variablen wurden über das Top-down-Verfahren bestimmt. Das Modell und die Schätzer der Preise wurden im Anschluss durch Hypothesentest getestet. Als signifikante Schätzer, mit stark negativen Werten, stellten sich in allen Kategorien die Preise heraus. Die Hypothesentests ergaben, dass es sinnvoll ist, die Schätzer der Preise für die ersten beiden Gerätetypen zusammenzufassen. Es stellte sich eine unterproportionale Preiselastizität der Nachfrage heraus und eine hohe Akzeptanz ein Teil der Geräte in den Nachtstunden zu nutzen. Insgesamt sprachen sich mehr Teilnehmer für ein Smart-Meter-Gateway aus als dagegen. / The aim of the master thesis is to clarify whether private households accept variable electricity prices and determine the strength of the characteristic attributes. The data set was determined with a Stated Choice survey on the Internet. For this purpose, three device categories and a three-tariff model were formulated. An additive-linked partial-value model and a binary logit choice model were used for the evaluation. Significant variables were determined by using the top-down method. Afterwards the model and the estimators of the prices were tested with statistical hypothesis testings. The price emerged as a significant estimator, with strongly negative values in all categories. The hypothesis tests showed that it is useful to conclude the estimators of the prices for the first two device types. The results showed an inelastic price elasticity of demand and a high acceptance of the subjects to use a part of the devices in the night hours. Overall, more participants decide to use a smart meter gateway than to refuse it.

Första och andra världskrigen medförde stora importrestriktioner för bensin och diesel och Sverigestod inför en potentiell kris. Lösningen till drivmedelsbristen var gengas som produceras genom attförbränna träd eller kol i en syrefattig miljö. Med dagens kontinuerligt stigande bensin, diesel ochelpriser står Sverige inför en liknande situation och nya lösningar för att kompensera för de högapriserna söks. Detta kandidatarbete undersöker potentialen med att använda gengas som ett alternativ för attbedriva fordon och småhus för att sänka kostnaden. Arbetet tittar på hur gengas kan användas i treolika fall; i en taxi, lätt lastbil samt ett småhus över ett års tid där kostnadsvinsten beräknas genom attbestämma hur mycket ved som krävs utifrån hur mycket energi som krävs vid användning. Resultatettyder på att med dagens elpriser är el det billigare alternativet för bostäder. Däremot går det att se attdet kan vara ekonomiskts fördelaktigt att använda gengas istället för flytande bränsle när vedprised är billigt. / The First and Second World Wars imposed major import restrictions on gasoline and diesel andSweden faced a potential crisis. The solution to the fuel shortage was producer gas, which isproduced by burning trees or coal in a low-oxygen environment. With today's continuously risinggasoline, diesel and electricity prices, Sweden faces a similar situation and new solutions tocompensate for the high prices are being sought.This bachelor thesis examines the potential for using producer gas as an alternative to power vehiclesand small houses to reduce the cost. The thesis looks at how producer gas can be used in threedifferent cases; in a taxi, light truck and a small house over a years time where the cost benefit iscalculated by determining how much wood is required based on how much energy is required in use.The results indicate that with current electricity prices, electricity is the cheaper option for poweringhouses. However, it can be seen that it can be economically advantageous to use producer gas instead of liquid fuel when the price of wood is cheap.

Battery Energy Storage Systems (BESSs) have become an increasingly popular feature of the electrical grid in the California ISO (CAISO) as a means to address the challenges posed by renewable energy variability and escalating peak demand. Due to their ability to reduce peak load demand on traditional generators and extend the benefits of the merit order effect, they have been theorized and claimed to reduce peak electricity prices. The purpose of this study is to test these claims within CAISO and understand what effects BESSs have had on peak electricity prices. Our findings show that there has been a significant decrease in prices after the introduction of BESSs into the grid although we found no significant effects of an increasing utilization of BESSs on peak electricity prices. We conclude that BESS utilization in CAISO has had no effect on peak electricity prices. We are contributing to the literature on the tangible market impacts of BESSs, highlighting the need for further empirical research in this domain.

Since the late 1980s, the energy sector in Great Britain has undergone some core changes in its functionality; beginning with the early 1990s privatisation, followed by an increased green ambition, and commencing a transition towards a low-carbon economy. As the British energy sector prepares itself for another major overhaul, it also puts itself at risk for not being sufficiently prepared for the consequences this transition will have on the existing generating capacity, security of supply, and the national electricity market. Upon meeting existing targets, the government of the United Kingdom risks becoming complacent, putting energy regulation to the backseat and focusing on other regulatory tasks, while introducing cuts for thriving renewable and other low-carbon energy generating technologies. The government has implemented a variety of directives, initiatives, and policies that have sometimes been criticised due to their lack of clarity and potential overlap between energy and climate change directives. The government has introduced policies that aim to provide stable short-term solutions. However, a concrete way of resolving the energy trilemma and some of the long-term objectives and more importantly ways of achieving them are yet to be developed. This work builds on analysing each low-carbon technology individually by assessing its past and current state in the British energy mix. By accounting for the changes and progress the technology underwent in its journey towards becoming a part of the energy capacity in Great Britain, its impact on the future wholesale electricity prices is studied. Research covered in this thesis presents an assessment of the existing and incoming low-carbon technologies in Great Britain and their individual and combined impact on the future of British energy economics by studying their implications for the electricity market. The methodological framework presented here uses a cost-minimisation merit order model to provide useful insights for novel methods of electricity production and conventional thermal energy generation to aid with the aftermath of potential inadequate operational and fiscal flexibility. The thesis covers a variety of scenarios differing in renewable and thermal penetration and examines the impact of interconnection, energy storage, and demand side management on the British wholesale electricity prices. The implications of increasing low-carbon capacity in the British energy mix are examined and compared to similar developments across Europe. The analysis highlights that if the optimistic scenarios in terms of green energy installation are followed, there is sufficient energy supply, which results in renewable resources helping to keep the wholesale price of electricity down. However, if the desired capacity targets are not met, the lack of available supply could result in wholesale prices going up, especially in the case of a natural gas price increase. Although initially costly, the modernisation of the British grid leads to a long-term decrease in wholesale electricity prices and provides a greater degree of security of supply and flexibility for all market participants.

This thesis comprises three papers examining the impact of competitive pricing or competition on participants in energy markets. The scope of each paper is narrow but focused, dealing with one particular aspect of competition in each market under study. It is hoped that results from these three studies could provide valuable policy lessons to public policy makers in their task to create or maintain competition in different energy markets, so as to improve efficiencies in these markets. The first and second papers examine the load shifting behavior of industrial customers in Ontario under real time pricing (RTP). Using Hourly Ontario Energy Price (HOEP) data from 2005 to 2008 and industry-level consumption data from all industrial customers directly connected to the transmission grid, the first paper adopts a Generalized Leontief specification to obtain elasticities of substitution estimates for various industry groups, while the second paper adopts a specification derived from standard consumer theory to obtain price elasticity estimates. The findings of both papers confirm that in some industries, industrial customers who are direct participants of the wholesale market tend to shift consumption from peak to off-peak periods in order to take advantage of lower off-peak prices. Furthermore, in the first paper, a demand model is estimated and there is evidence that the marginal effect of hourly load on hourly price during peak periods is larger than the marginal effect during off-peak periods. An important policy implication from the results of these papers is that while RTP is currently limited to industrial customers, it does have positive spillover effects on all consumers. The third paper uses a unique panel dataset of all retail gasoline stations across five Canadian cities from late-2006 to mid-2007 to examine the effect of local competition on market shares and sales of individual stations. The base empirical specification includes explanatory variables representing the number of same brand stations and the number of different brand stations within a 3km radius to identify brand affiliation effect. It is found that the number of local competitors is negatively correlated with market share and sales. More interestingly, a same brand competitor has a larger marginal impact on market share and sales than a competitor of a different brand. These findings suggest that additional local competition leads to cannibalization of market share among existing stations, rather than create new demand. Another implication is that relying only on the number of different brands operating within a geographic market could understate the competition intensity in the local market.

This thesis comprises three papers examining the impact of competitive pricing or competition on participants in energy markets. The scope of each paper is narrow but focused, dealing with one particular aspect of competition in each market under study. It is hoped that results from these three studies could provide valuable policy lessons to public policy makers in their task to create or maintain competition in different energy markets, so as to improve efficiencies in these markets. The first and second papers examine the load shifting behavior of industrial customers in Ontario under real time pricing (RTP). Using Hourly Ontario Energy Price (HOEP) data from 2005 to 2008 and industry-level consumption data from all industrial customers directly connected to the transmission grid, the first paper adopts a Generalized Leontief specification to obtain elasticities of substitution estimates for various industry groups, while the second paper adopts a specification derived from standard consumer theory to obtain price elasticity estimates. The findings of both papers confirm that in some industries, industrial customers who are direct participants of the wholesale market tend to shift consumption from peak to off-peak periods in order to take advantage of lower off-peak prices. Furthermore, in the first paper, a demand model is estimated and there is evidence that the marginal effect of hourly load on hourly price during peak periods is larger than the marginal effect during off-peak periods. An important policy implication from the results of these papers is that while RTP is currently limited to industrial customers, it does have positive spillover effects on all consumers. The third paper uses a unique panel dataset of all retail gasoline stations across five Canadian cities from late-2006 to mid-2007 to examine the effect of local competition on market shares and sales of individual stations. The base empirical specification includes explanatory variables representing the number of same brand stations and the number of different brand stations within a 3km radius to identify brand affiliation effect. It is found that the number of local competitors is negatively correlated with market share and sales. More interestingly, a same brand competitor has a larger marginal impact on market share and sales than a competitor of a different brand. These findings suggest that additional local competition leads to cannibalization of market share among existing stations, rather than create new demand. Another implication is that relying only on the number of different brands operating within a geographic market could understate the competition intensity in the local market.

Das Ziel der Masterarbeit ist es zu klären, ob private Haushalte variable Strompreise akzeptieren und die Stärke der charakteristischen Merkmale zu ermitteln. Der dazu benötigte Datensatz wurde mit Hilfe einer Stated Choice Befragung im Internet ermittelt. Dafür wurden drei Gerätekategorien und ein Dreitarifmodell formuliert. Für die Auswertung wurde ein additiv verknüpftes Teilwert-Nutzenmodell und ein binäres Logit-Choice-Modell verwendet. Signifikante Variablen wurden über das Top-down-Verfahren bestimmt. Das Modell und die Schätzer der Preise wurden im Anschluss durch Hypothesentest getestet. Als signifikante Schätzer, mit stark negativen Werten, stellten sich in allen Kategorien die Preise heraus. Die Hypothesentests ergaben, dass es sinnvoll ist, die Schätzer der Preise für die ersten beiden Gerätetypen zusammenzufassen. Es stellte sich eine unterproportionale Preiselastizität der Nachfrage heraus und eine hohe Akzeptanz ein Teil der Geräte in den Nachtstunden zu nutzen. Insgesamt sprachen sich mehr Teilnehmer für ein Smart-Meter-Gateway aus als dagegen.:Kurzfassung I Abstract I Themenbeschreibung für eine Forschungsarbeit II Inhaltsverzeichnis III Abbildungsverzeichnis V Tabellenverzeichnis VI Abkürzungsverzeichnis VII 1. Einleitung - 1 - 2. Gegenwärtiger Strommarkt - 3 - 2.1 Aufbau der Elektrizitätswirtschaft - 3 - 2.2 Strombörse - 5 - 2.3 Preisbildung des Stroms - 8 - 3. Nutzung variabler Strompreise - 13 - 3.1 Probleme und Gestaltung eines zukünftigen Strommarktes - 14 - 3.2 Funktionsweise des Demand Side Management - 19 - 3.3 Ausblick auf zukünftige Tarife - 25 - 3.4 Aufbau einer zukünftigen überregionalen und häuslichen Energieinfrastruktur - 28 - 3.5 Bandbreite möglicher Speichertechnologien des zukünftigen Strommarktes - 32 - 4. Theoretische Grundlagen - 39 - 4.1 Stated Preference vs. Revealed Preference - 39 - 4.2 Conjoint-Analyse - 40 - 4.3 Diskrete Wahlmodelle - 42 - 5. Hintergründe zur Erstellung des Fragebogens - 50 - 6. Modellspezifikation - 53 - 7. Analyse der Umfrage - 57 - 7.1 Auswertung des Modells - 57 - 7.2 Teststatistik - 62 - 8. Interpretation der Ergebnisse - 66 - 9. Fazit - 68 - Literaturverzeichnis IX Anhang XIV Erklärung zur Urheberschaft XXII / The aim of the master thesis is to clarify whether private households accept variable electricity prices and determine the strength of the characteristic attributes. The data set was determined with a Stated Choice survey on the Internet. For this purpose, three device categories and a three-tariff model were formulated. An additive-linked partial-value model and a binary logit choice model were used for the evaluation. Significant variables were determined by using the top-down method. Afterwards the model and the estimators of the prices were tested with statistical hypothesis testings. The price emerged as a significant estimator, with strongly negative values in all categories. The hypothesis tests showed that it is useful to conclude the estimators of the prices for the first two device types. The results showed an inelastic price elasticity of demand and a high acceptance of the subjects to use a part of the devices in the night hours. Overall, more participants decide to use a smart meter gateway than to refuse it.:Kurzfassung I Abstract I Themenbeschreibung für eine Forschungsarbeit II Inhaltsverzeichnis III Abbildungsverzeichnis V Tabellenverzeichnis VI Abkürzungsverzeichnis VII 1. Einleitung - 1 - 2. Gegenwärtiger Strommarkt - 3 - 2.1 Aufbau der Elektrizitätswirtschaft - 3 - 2.2 Strombörse - 5 - 2.3 Preisbildung des Stroms - 8 - 3. Nutzung variabler Strompreise - 13 - 3.1 Probleme und Gestaltung eines zukünftigen Strommarktes - 14 - 3.2 Funktionsweise des Demand Side Management - 19 - 3.3 Ausblick auf zukünftige Tarife - 25 - 3.4 Aufbau einer zukünftigen überregionalen und häuslichen Energieinfrastruktur - 28 - 3.5 Bandbreite möglicher Speichertechnologien des zukünftigen Strommarktes - 32 - 4. Theoretische Grundlagen - 39 - 4.1 Stated Preference vs. Revealed Preference - 39 - 4.2 Conjoint-Analyse - 40 - 4.3 Diskrete Wahlmodelle - 42 - 5. Hintergründe zur Erstellung des Fragebogens - 50 - 6. Modellspezifikation - 53 - 7. Analyse der Umfrage - 57 - 7.1 Auswertung des Modells - 57 - 7.2 Teststatistik - 62 - 8. Interpretation der Ergebnisse - 66 - 9. Fazit - 68 - Literaturverzeichnis IX Anhang XIV Erklärung zur Urheberschaft XXII

Fuel cell electric vehicles, powered by hydrogen are an enticing alternative to fossil-fuel vehicles in order to reduce greenhouse gas emissions and consequently accomplish the environmental targets set to tackle the environmental crisis. It is crucial to develop the appropriate infrastructure if the FCEVs are to be successfully accepted as an alternative to fossil-fuel vehicles. This study aims to carry out a techno-economic analysis of different hydrogen supply chain designs, that are coupled with the Swedish electricity system in order to study the inter-dependencies between them. The supply chain designs comprehend centralised production, decentralised production and a combination of both. The outputs of the hydrogen supply chain model include the hydrogen refuelling stations’ locations, the electrolyser’s locations and their respective sizes as well as the operational schedule. Both the hydrogen supply chain designs and the electricity system were parameterized with data for 2030. The supply chain design is modelled to minimize the overall cost while ensuring the hydrogen demands are met. The mixed-integer linear programming problems were modelled using Python and the optimisation software was Gurobi. The hydrogen models were run for two different scenarios, one that considers seasonal variations in hydrogen demand, and another that does not. The results show that for the scenario with seasonal variation the supply chain costs are higher than for the scenario without seasonal variation, regardless of the supply chain design. In addition, the hydrogen supply chain design with the minimal cost is based on decentralised hydrogen production. / Bränslecellsdrivna elbilar, som drivs av vätgas, är ett lockande alternativ till fossildrivna fordon för att minska växthusgasutsläppen och därigenom uppnå de miljömål som satts för att tackla miljökrisen. Det är avgörande att utveckla lämplig infrastruktur om FCEV:er ska accepteras som ett alternativ till fossildrivna fordon. Denna studie syftar till att utföra en teknisk-ekonomisk analys av olika vätgas supply kedjedesign som är kopplade till det svenska elsystemet för att studera beroendeförhållandena mellan dem. Försörjningskedjans design omfattar centraliserad produktion, decentraliserad produktion och en kombination av båda. Resultaten från vätgas supply kedja modellen inkluderar vätgasmackarnas placeringar, elektrolysörernas placeringar och deras respektive storlekar samt den operationella schemat. Både vätgas supplykedjedesi och elsystemet parameteriserades med data för 2030. Supplykedjedesignen modellerades för att minimera de totala kostnaderna samtidigt som vätgasbehoven uppfylls. Mixed-integer lineära programmeringsproblem modellerades med hjälp av Python och optimeringsprogramvaran Gurobi. Vätgasmodellerna kördes för två olika scenarier, ett som tar hänsyn till säsongsvariationer i vätgasbehovet och ett annat som inte gör det. Resultaten visar att för scenariet med säsongsvariation är supply kedja kostnaderna högre än för scenariot utan säsongsvariation, oavsett supplykedjedesignen. Dessutom är vätgas supply kedjedesignen med minimal kostnad baserad på decentraliserad vätgasproduktion.

With the development of artificial intelligence techniques and increased installation of smart meters in recent years, time series analysis using historical data in the energy domain becomes applicable. In this thesis, microdata analysis approaches are used, which consist of data acquisition, data processing, data analysis and data modelling, aiming to address two research problems in the energy domain. The first research problem is short-term electricity price forecasting of a deregulated market and the second one is anomaly detection of heat energy usage in district heating substations. As a result of electricity market deregulation, third party suppliers can enter the market and consumers are free to choose electricity suppliers, which leads to a more transparent and competitive market. Accurate short-term electricity price forecasting is crucial to the market participants in terms of maximizing profits, risk management and other short-term market operations. Literature review is performed aiming to identify the suitable methods. It is concluded that long short-term memory (LSTM) based methods are superior to other methods for time series analysis. Since the gating mechanisms of long short-term memory alleviate the problem of gradient vanishing. Another conclusion form the literature is that hybrid approach that consists of two or more artificial intelligence algorithms complimenting each other is more effective to solve complex real world problem. Based on the conclusions derived, a hybrid approach based on bidirectional LSTM (BDLSTM) and Catboost is proposed for short-term electricity price forecasting of NordPool. Performance of support vector regression (SVR), ARIMA, ensemble tree, multi-layer perception (MLP), gated recurrent unit (GRU), BDLSTM and LSTM are evaluated. Experiment results show that BDLSTM outperforms the other models in terms of Mean percentage error (MAPE), root mean square error (RMSE) and mean absolute error (MAE). Statistics show that market shares of district heating have increased steadily in the past five decades. District heating shares approximately 55% of the heat supply market in Sweden. Therefore, energy efficiency of district heating systems is of great interest to energy stakeholders. Anomalies are rare observations deviated significantly from the majority of the data, and such suspicious observations are important indicators of potential faults. To reduce the financial loss and improve energy efficiency, detecting anomalies from meter readings is essential. Another type of neural network architecture, LSTM variational autoencoder (LSTMVAE) combined with a heat signature model is proposed for anomaly detection using the dataset from an anonymous substation in Sweden. Results show that the proposed method outperforms other two baseline models LSTM, LSTM autoencoder (LSTMAE) in terms of F1 score and AUC. In this thesis, various approaches based on neural networks are explored to solve different time series data analysis in the energy domain, aiming for supporting decision makings of market participants to maximize profits, enhancing risk managements and improving energy efficiency. Although, two problems domains are covered, methods reviewed and applied in the thesis can be tailored for other energy time series analysis problems as well.

Ogni tecnologia produttiva ha un proprio profilo di dispacciamento ottimale che non dovrebbe essere alterato dall’ingresso delle intermittenti tecnologie rinnovabili per mantenere la migliore allocazione di prezzo e quantità. La nostra ricerca si focalizza sul mercato elettrico italiano. Considerando il comportamento di Edison Trading sul mercato, noi analizziamo se l’incremento di energia rinnovabile porta alla riduzione del prezzo e della produzione di energia grazie all’efficienza. I nostri principali risultati suggeriscono che le rinnovabili hanno un impatto negativo sulle quantità offerte. Gli impianti solari e di pompaggio portano ad un consistente incremento del prezzo elettrico; il contrario vale per le altre rinnovabili. La nostra analisi sul mercato italiano aggregato considera il comportamento di tutti gli operatori del mercato elettrico (quelli aventi consistenti e limitate quote di mercato) nel quindicesimo giorno di ogni mese nel periodo gennaio 2013 - giugno 2015. Possiamo aspettarci lo stesso risultato in termini di impatto sul prezzo e quantità, data la crescente potenza lorda eolica e solare? I nostri risultati empirici sottolineano che le tecnologie intermittenti possono solamente portare ad incrementi di prezzo, mentre i più grandi operatori di mercato (Enel, Eni ed Edison) utilizzano la tecnologia CCGT efficientemente, poichè producono quando il prezzo è più alto. / Each power plant has its own optimal dispatchable profile that should not be altered by the entrance of intermittent renewables to maintain the best allocation of price and quantity. Our research focuses on the Italian electricity market. Focusing on the market behaviour of Edison Trading, we investigate if the increase in renewable energy leads to a decrease in energy price and in energy production due to efficiency. Our main results suggest that renewables have a negative impact on the quantity supplied. Solar and pumped-storage technologies lead to a consistent increase in the electricity price, while the reverse is true for the other renewables. Our analysis on the aggregate Italian electricity market considers the behaviour of all electricity market operators (with low and high market shares) on the 15th day of each month in the period January 2013 - June 2015. Can we expect the same results in terms of the impact on price and quantity, given the increase in gross wind and solar power? Our empirical findings point out that the intermittent technologies can only lead to price increases, whereas the biggest market players (Enel, Eni and Edison) use CCGT technology efficiently since they produce when the price is higher.