The market for natural gas in the United States follows a yearly price pattern of high prices during the winter heating season and lows during the summer months. During the winter heating season the daily and weekly price fluctuations for natural gas are normally related to ambient air temperature and other weather related phenomenon. This paper examines a natural gas price forecasting model developed by the U.S. Department of Energy, Energy Information Agency (EIA). This paper proposes that a more accurate forecasting model can be created from the EIA model by focusing on forecasting price during only the winter heating season and by adding other variables to the EIA model. The forecasting results of the core EIA model are compared to the results of other linear regression models. / Master of Arts

This paper seeks to investigate the current state of market integration among European electricity day-ahead spot prices. We provide reasoning that market integration brings about benefits, such as lower average prices and increased welfare from allocative efficiency. Yet, price convergence leads to higher prices in the low-price market and to lower prices in the high-price market, which creates winners and losers and thus makes the political implementation of market integration cumbersome. In our empirical analysis, we utilize a large sample of hourly spot prices of 25 European markets for the period 01.01.2010-30.06.2015 and combine it with other relevant data such as interconnector capacities and the existence of market coupling. Firstly, empirical results from cointegration analysis indicate that market integration increased from 2010 to 2012 but then declined until 2015, most likely due to increased feed-in from intermittent renewables. Secondly, we empirically assess the speed of adjustment from price shocks and reach the conclusion that the resulting efficiency of integration is rather modest. In general, our findings suggest that integration among European electricity markets has a large potential for improvements from additional capacity investments and further promotion of market coupling. (authors' abstract) / Series: Department of Economics Working Paper Series

The purpose of this research is to study and improve decision accuracy in the real world. Spot price prediction of petroleum products, in a budgeting context, is the task chosen to study prediction accuracy. Prediction accuracy of executives in a multinational oil company is examined. The Brunswik Lens Model framework is used to evaluate prediction accuracy. Predictions of the individuals, the composite group (mathematical average of the individuals), the interacting group, and the environmental model were compared. Predictions of the individuals were obtained through a laboratory experiment in which experts were used as subjects. The subjects were required to make spot price predictions for two petroleum products. Eight predictor variables that were actually used by the subjects in real-world predictions were elicited through an interview process. Data for a 15 month period were used to construct 31 cases for each of the two products. Prediction accuracy was evaluated by comparing predictions with the actual spot prices. Predictions of the composite group were obtained by averaging the predictions of the individuals. Interacting group predictions were obtained ex post from the company's records. The study found the interacting group to be the least accurate. The implication of this finding is that even though an interacting group may be desirable for information synthesis, evaluation, or working toward group consensus, it is undesirable if prediction accuracy is critical. The accuracy of the environmental model was found to be the highest. This suggests that apart from random error, misweighting of cues by individuals and groups affects prediction accuracy. Another implication of this study is that the environmental model can also be used as an additional input in the prediction process to improve accuracy.

A produção de energia elétrica em usinas de açúcar e álcool em sistema de co-geração tendo como combustível o bagaço da cana-de-açúcar é uma prática tradicional. No Brasil, desde os anos 1980, as usinas evoluíram para uma posição de quase auto-suficiência na produção de eletricidade, indicando um forte potencial de produção de eletricidade excedente que pode ser incorporado à matriz energética nacional como complemento. O interesse pela geração de energia por fontes renováveis ganhou destaque devido ao risco de desabastecimento e à necessidade de adequações tecnológicas por parte das usinas. Entretanto, embora o potencial exista, há fatores que influenciam e colocam em risco a decisão de uma usina investir na geração de excedentes que devem ser analisados, dentre eles a volatilidade dos preços da energia. O objetivo deste trabalho é analisar o processo de formação de preço da energia elétrica gerada a partir de biomassa negociada no Ambiente de Contratação Livre (ACL). Neste ambiente, a energia gerada por biomassa pode ser negociada bilateralmente por agentes privados (geradores e consumidores livres). Mais precisamente, pretende-se mostrar como o risco hidrológico incorporado no processo de formação de preço e no despacho físico da geração do sistema hidrotérmico brasileiro afeta o preço da energia elétrica gerada a partir de biomassa negociada no ACL, dadas suas atuais características institucionais. Para isso, desenvolve-se um mercado artificial de energia elétrica gerada por biomassa que busca captar as principais características institucionais do ACL. Várias simulações são geradas pelo modelo computacional, as quais mostram o impacto negativo da volatilidade do preço de curto prazo sobre os preços da energia elétrica gerada por biomassa negociada no ACL. / Electricity generation in ethanol and sugar mills using bagasse as a fuel in cogeneration process is a traditional practice. In Brazil, since the 1980s mills have evolved to a position of almost self-sufficiency in electricity production, which indicates a strong potential of electricity surplus that can be used as a complement in the electricity national matrix. Such interest for electricity generation from renewable sources got outstanding due to the lack of supply risk and also the mills necessity of technological adaptations. However, even though the potential exists, there are some factors that influence and put in risk a mills decision to invest in electricity surplus generation which must be evaluated, such as energy prices volatility. The objective of this work is to analyze the electricity price setting process generated by sugarcane biomass and negotiated in the Free Agreement Environment (ACL). In this environment, biomass generated electricity can be negotiated among private agents (free consumers and generators). More precisely, the aim is to show how the hydrological risk that is part of the price setting process and of the system physical dispatch affects the price of the biomass electricity in the ACL, given its actual institutional features. To enable that, an electricity biomass artificial market is developed with the aim to capture the main institutional features of ACL. Several simulations are generated by this computational model, which show the negative impact of spot price volatility over the biomass electricity prices in ACL.

Sustainable development is now being recognised as a vital component of our society in the environmental, ethical, social, technological, economic, and institutional aspects, or dimensions, so, this thesis develops a framework to quantitatively measure sustainability. This thesis is distinctive in that it focuses on quantitative methods encapsulated in a formal assessment procedure and includes sustainability concepts that have rarely been put into practical use in sustainability reports. The framework is designed along the strategy that the methodology needs to be scale invariant and recursive, meaning the procedure is the same irrespective of the scale the user is interested in, and that different people can focus at different levels of sustainability by following a similar procedure. While the quantification process is aimed to be as unbiased as possible, a configuration of the tools from Total Quality Management (TQM) is adapted to identify sustainability indicators which are then mapped onto a scalar with mathematical functions. The sustainability indices are presented according to the amount of details needed by different users ─ some may need just one overall figure while others may need sustainability indices broken down by the six sustainability dimensions and presented on a spider diagram, while others may need all the details for analysis. This methodology also caters for sustainability analysis by different stakeholders. To fully demonstrate the potential of the methodology, the author has chosen to test it on a large-size industry sector so that it can have the capacity to be scaled up to a country or down to a small business, and on an industry sector that is important on its own right. Furthermore, this sector needs to be illustrative and has nontrivial complex problems. Under these criteria, the electricity sector of New Zealand was selected. The robustness of the methodology was investigated with inputs from three evaluators with different views: a standard view from the author that was made after much research in the sector and in the concepts of sustainability, a view with an environmental bias and one that focuses on commercial interests.

In this report six different models for predicting the electrical spot price on the Nordic power exchange, Nord Pool, are developed and compared. They are evaluated against the already existing model as well as the naive test, which is a forecast where the last week’s observations are used as a prognosis for the coming week. The models developed are constructed so that the models for different time resolutions are combined to create a full model. Harmonic regression with a linear trend are used to identify a yearly trend while SARIMAX/SARIMA time series models are used on a daily and hourly basis to reveal dependencies in the data.   The model with the best prediction performance is shown to be a SARIMAX model with temperature as exogenous variable on a daily resolution, together with a SARIMA model on an hourly resolution. With an average MAPE of 12.69% and a MAPE2 of 6.90% it has the smallest prediction error out of all of the competing models when doing one week forecasts on the whole year 2009.

Sustainable development is now being recognised as a vital component of our society in the environmental, ethical, social, technological, economic, and institutional aspects, or dimensions, so, this thesis develops a framework to quantitatively measure sustainability. This thesis is distinctive in that it focuses on quantitative methods encapsulated in a formal assessment procedure and includes sustainability concepts that have rarely been put into practical use in sustainability reports. The framework is designed along the strategy that the methodology needs to be scale invariant and recursive, meaning the procedure is the same irrespective of the scale the user is interested in, and that different people can focus at different levels of sustainability by following a similar procedure. While the quantification process is aimed to be as unbiased as possible, a configuration of the tools from Total Quality Management (TQM) is adapted to identify sustainability indicators which are then mapped onto a scalar with mathematical functions. The sustainability indices are presented according to the amount of details needed by different users ─ some may need just one overall figure while others may need sustainability indices broken down by the six sustainability dimensions and presented on a spider diagram, while others may need all the details for analysis. This methodology also caters for sustainability analysis by different stakeholders. To fully demonstrate the potential of the methodology, the author has chosen to test it on a large-size industry sector so that it can have the capacity to be scaled up to a country or down to a small business, and on an industry sector that is important on its own right. Furthermore, this sector needs to be illustrative and has nontrivial complex problems. Under these criteria, the electricity sector of New Zealand was selected. The robustness of the methodology was investigated with inputs from three evaluators with different views: a standard view from the author that was made after much research in the sector and in the concepts of sustainability, a view with an environmental bias and one that focuses on commercial interests.

A produção de energia elétrica em usinas de açúcar e álcool em sistema de co-geração tendo como combustível o bagaço da cana-de-açúcar é uma prática tradicional. No Brasil, desde os anos 1980, as usinas evoluíram para uma posição de quase auto-suficiência na produção de eletricidade, indicando um forte potencial de produção de eletricidade excedente que pode ser incorporado à matriz energética nacional como complemento. O interesse pela geração de energia por fontes renováveis ganhou destaque devido ao risco de desabastecimento e à necessidade de adequações tecnológicas por parte das usinas. Entretanto, embora o potencial exista, há fatores que influenciam e colocam em risco a decisão de uma usina investir na geração de excedentes que devem ser analisados, dentre eles a volatilidade dos preços da energia. O objetivo deste trabalho é analisar o processo de formação de preço da energia elétrica gerada a partir de biomassa negociada no Ambiente de Contratação Livre (ACL). Neste ambiente, a energia gerada por biomassa pode ser negociada bilateralmente por agentes privados (geradores e consumidores livres). Mais precisamente, pretende-se mostrar como o risco hidrológico incorporado no processo de formação de preço e no despacho físico da geração do sistema hidrotérmico brasileiro afeta o preço da energia elétrica gerada a partir de biomassa negociada no ACL, dadas suas atuais características institucionais. Para isso, desenvolve-se um mercado artificial de energia elétrica gerada por biomassa que busca captar as principais características institucionais do ACL. Várias simulações são geradas pelo modelo computacional, as quais mostram o impacto negativo da volatilidade do preço de curto prazo sobre os preços da energia elétrica gerada por biomassa negociada no ACL. / Electricity generation in ethanol and sugar mills using bagasse as a fuel in cogeneration process is a traditional practice. In Brazil, since the 1980s mills have evolved to a position of almost self-sufficiency in electricity production, which indicates a strong potential of electricity surplus that can be used as a complement in the electricity national matrix. Such interest for electricity generation from renewable sources got outstanding due to the lack of supply risk and also the mills necessity of technological adaptations. However, even though the potential exists, there are some factors that influence and put in risk a mills decision to invest in electricity surplus generation which must be evaluated, such as energy prices volatility. The objective of this work is to analyze the electricity price setting process generated by sugarcane biomass and negotiated in the Free Agreement Environment (ACL). In this environment, biomass generated electricity can be negotiated among private agents (free consumers and generators). More precisely, the aim is to show how the hydrological risk that is part of the price setting process and of the system physical dispatch affects the price of the biomass electricity in the ACL, given its actual institutional features. To enable that, an electricity biomass artificial market is developed with the aim to capture the main institutional features of ACL. Several simulations are generated by this computational model, which show the negative impact of spot price volatility over the biomass electricity prices in ACL.

The ambition of the Swedish government is rapidly concentrating on the development of the renewable energy systems especially on wind energy, bio energy and solar energy. It has been observed on the growth of the production of electricity and heat from these three mentioned renewable energy systems. But, relatively in Sweden the share of production of electricity obtained from PV is quite smaller than the other two. The PV electricity production in Sweden comprises in a large scale of mainly the grid connected distributed PV systems and with a small number of installed solar parks. The aim of this paper is to analyze the viability of installing mid -size PV solar parks in Sweden and to simulate the effect of the proposed project in the village’s (Åled is the village where the proposed site is located) and the country’s electricity production. This study includes designing, simulation and financial analysis of different grid connected centralized mid -size capacities of PV solar parks of 250 kWp,500 kWp,1MWp and 2MWp. They are all fixed ground mounted systems. Moreover, it also discusses the main reasons that hinders decision makers, the PV complications that are connected to the grid, Sweden’s energy regulations particularly the emission regulation and the financial policies of PV. Also, study visit, telephone and email contacts have supplemented it. This study was done with the collaboration of Nyedal Solenergi, in which the proposed site was owned by the company and this paper will be a future guide for the investment of the mid-size PV solar park. According to the study a discussion has been made with the grid supplier (EON) in that area on the investment on one of the designed projects which are presented in this paper. The results of the study show that the effect of the proposed systems on the production of electricity in the village of Åled was between 2.68 – 21.4 % and the impact on the country’s PV electricity production was 0.2 – 1.58 %. And, the possibility of installing mid-size PV solar parks generally in Sweden particularly in the proposed site is possible and economically it is viable but not profitable for system capacities less than 1 MW. As the IRR found for all capacities is greater than the estimated WACC, hence each proposed capacity has the possibility of paying back all its investment costs in about 23 years. So, the profitability is very low in case of the 250 kWp and 500 kWp but for the others they have about 7-8 years of profitability. A sensitivity analysis also has shown the impact of initial investment costs, O & M costs and electricity export rate on the IRR, NPV and equity payback. The initial investment cost and electricity export rate were seen with high effect on the IRR, NPV and equity payback. The LCOE calculated was higher than the average electricity spot price (300 SEK/MWh) for 250 kWp and 500 kWp but lower for the other two capacities. The overall impact for the financial analysis was due to the decreasing of module prices, the rules that changes every year on electricity subsidies for renewables, tax reductions and rapid decreasing of electricity spot prices. In the future if the price of modules continues decreasing, spot price increases, more modification of the subsidy and introduction of new PV technologies integrated with other sources of energy is done then such projects could be more profitable.

This bachelor thesis investigates the development of value factors on the Swedish electricity market and how the development can be explained. Value factor is a parameter that indicates how well an energy source’s market price corresponds to the average spot price for the electricity mix. Value factors for nuclear-, thermal-, wind-, solar- and hydropower are calculated for the years 2014-2019. Electricity production- and spot price data has been sourced from Svenska Kraftnät, Nord Pool and Uppsala University. The influence of weather conditions, spot price, production and consumption on the development of the value factors is discussed. The Pearson correlation coefficient is used for analytical purposes, showing the correlation between two specific variables. The conclusion is that the value factor for each power source is the result of the conditions present during the specific time period. The value factors for solar- and thermal power are discontinuous since they are temperature-dependent. For nuclear-, wind- and hydropower, the value factors are more continuous during the time span. This is due to, for instance, their important roles in the Swedish energy system and their ability to match demands.