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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
21

[en] THE BEHAVIOR OF FORWARD MARKET OF ELECTRICITY IN BRAZIL / [pt] O COMPORTAMENTO DO MERCADO A TERMO DE ENERGIA ELÉTRICA NO BRASIL

LEONARDO NOVELLO COSTA 04 September 2018 (has links)
[pt] O Setor Elétrico Brasileiro sofreu diversas mudanças regulatórias ao longo da década de 90, entretanto, após o racionamento de energia ocorrido entre 2001 e 2002 observou-se a necessidade de adoção de um arcabouço regulatório mais moderno e eficiente. Dentre as mudanças implementadas pelo novo modelo, destacamos a competição livre de preços para o setor de geração e o Ambiente de Comercialização Livre como as mais disruptivas. Essas mudanças, além de incentivar a modicidade tarifária, permitiu que os agentes do setor se protegessem de variações do preço da energia elétrica por meio de contratos futuros/a termo. Diferente dos mercados desenvolvidos que possuem um mecanismo formal de livre comercialização por meio de uma estrutura de bolsa centralizada, o Brasil ainda mantém um mercado informal através de uma estrutura de balcão descentralizado. Esse quadro resulta em uma falta de transparência nos preços, e que gera dificuldade na obtenção de dados e análise assertiva do comportamento do mercado futuro/a termo de energia elétrica brasileiro. O crescimento do mercado a termo brasileiro, em tamanho e importância, registrado nos últimos anos justifica a necessidade de aprofundamento das análises desse mercado. O objetivo deste trabalho é compreender o comportamento dos preços a termo em relação ao preço esperado à vista futuro a partir de uma metodologia de coleta de dados de mercado. O resultado do estudo aponta comportamento de contango para os contratos de 2017 com maturidade para 2018. O resultado é aderente a estudos realizados em mercados maduros para contratos com tempo de maturidade reduzido. / [en] The Brazilian Electricity Sector has undergone several regulatory changes throughout the 1990s, however, the energy rationing between 2001 and 2002, showed the need to adopt a more modern and efficient regulatory framework. Among the changes implemented by the new model, the free competition prices for the generation sector and a Free Trading Environment stands out as the most disruptives. These changes, as well as encourage tariff modicity, also allowed the players to hedge against changes in the electricity prices through futures/forward contracts. Unlike developed markets that have formal mechanism for free trading through a centralized stock exchange structure, Brazil still maintains an informal market through a decentralized counter structure, this situation results in a lack of transparency in the prices that generate difficulty in obtaining data and assertive analysis of the Brazilian futures/forward market behavior. The growth of the Brazilian forward market, in size and importance, recorded in recent years, justifies the need to deepen the analysis of this market. The objective of this paper is to understand the behavior of forward prices in relation to the expected future spot price based on market data collection methodology. The result of the study shows a contango behavior for the contracts of 2017 with maturity to 2018. The result is adherent to studies conducted in mature markets with reduced maturity time contracts.
22

Utilizing Energy Storage Applied on Floating Wind Turbine Economics Using a Spot-Price Based Algorithm

Johansson, Jim January 2017 (has links)
In this paper, a new algorithm for utilizing energy storage is proposed and applied on floating wind turbine economics. The proposed algorithm’s decision making on storing energy or selling electricity onto the grid is based on the electricity price, which makes it unique and different from similar algorithms. From the literature review, it was concluded Ocean Renewable Energy Storage to be most suitable with the Spar-Type and Semi-Submersible floating wind turbine to which the paper is based upon. The objective of this paper is to find the suitable ratio of energy storage versus wind farm, find the product of increase in wholesale, and evaluate whether the proposed method makes the hybrid economically sound. The algorithm was applied on spot-price data from Denmark due to its large share of wind energy with wind data from off the coast of Morro Bay in California, USA. Additionally, a sensitivity analysis is applied to evaluate to energy storage cost impact as well as evaluate the algorithm by lowering the required energy storage size.   Using the algorithm, the wind farm must account for nine days’ worth of energy production with a product of energy storage versus wind farm ratio of 1.42. The wholesale price increased with 11.9-21.5% for the four years studied, however, all financial results favored not utilizing energy storage. By the results derived from the sensitivity analysis, it was concluded that with future cost reductions, the algorithm will still favor no energy storage. However, by fine tuning the algorithm to reduce the need for storage, positive financial result might be achievable. The key to achieve a profitable result seems to rely on minimizing the need for energy storage, to which the proposed algorithm fail to achieve. Conclusively, spot-price decision-based energy storing is not economically sound.
23

Formação do preço da energia convencional nas transações entre agentes no mercado de curto prazo brasileiro. / The spot price of conventional energy at the brazilian free market.

Sozzi, Gustavo 10 April 2015 (has links)
Hoje no mercado brasileiro de eletricidade, o preço da energia convencional é composto pela soma do valor do Preço de Liquidação das Diferenças (PLD) divulgado pela Câmara de Comercialização de Energia Elétrica (CCEE) semanalmente com o valor do Spread negociado bilateralmente no mercado à vista (mercado de curto prazo), resultante do equilíbrio entre oferta e demanda. Em alguns momentos, o valor do Spread chega a representar mais de 100% do custo total da energia. Este trabalho faz uma análise do mercado brasileiro, bem como, de alguns mercados no exterior de energia elétrica e destaca os pontos que tem influência direta, na formação do Spread da energia convencional e como isso afeta a decisão de contratação dos agentes. Além disso, o trabalho busca encontrar correlações entre dados divulgados, como carga e oferta de energia, com o ágio negociado no mercado de curto prazo, buscando entender o real impacto de cada um desses fatores e explicar as grandes variações já observadas. Sugere-se também um modelo de regressão linear múltipla para a projeção de valores do ágio. Para tanto, foram utilizadas informações proveniente de um banco de dados de cotações de negócios efetivamente realizados no curto prazo desde janeiro de 2011 até julho de 2014, bem como informações retiradas da CCEE e Operador Nacional do Sistema (ONS). / The Brazilian wholesales energy market price is formed by de sum of the PLD (Market Clearing Price which is released weekly by the Commercial Chamber) and a Spread value, resulting from the negotiation between the market agents. In some cases, the Spread represent more than 100% of the energy total cost. This paper presents an overview about some energy markets, focusing the Brazilian Energy Market, so as to highlight points that affect the Spread value at the spot market and, as consequence, the strategy of the market agents. Additionally, this paper shows the correlation between energy demand and energy offer and energy spread negotiated at the short term market, trying to understand the real impact of each variable trying to get the right explanation regarding the big variations observed. It has been suggested a mathematical model of multiple linear regression to forecast the spread value. In order to accomplish this purpose it was used (i) a historical data of effectively trading situations at the short term market, comprising the period between January 2011 to July 2014, as well as (ii) informations released by the Commercial Chamber (CCEE) and the System Operator (ONS).
24

[en] SPOT PRICE FORECASTING IN THE ELECTRICITY MARKET / [pt] PREVISÃO DO PREÇO SPOT NO MERCADO DE ENERGIA ELÉTRICA

LUCIO DE MEDEIROS 14 April 2004 (has links)
[pt] O objetivo da tese é propor uma metodologia para previsão do preço de curto prazo (spot) da energia elétrica no Brasil baseada em sistemas neuro-fuzzy e nos programas do planejamento da operação do sistema elétrico brasileiro. Com essa abordagem, obtém-se distribuições estimadas do preço spot para o curto prazo com menor dispersão do que as obtidas somente com os programas do planejamento da operação. Além disso, por ser rápido, o sistema de previsão final possibilita análises de cenários ou simulações Monte Carlo. As principais variáveis que afetam o preço spot no Brasil são consideradas, tais como a energia natural afluente e a energia armazenada, entre outras. Ainda, é possível incluir também variáveis que não têm um histórico definido ou dados suficientes para o treinamento, tais como o plano de obras, limites de intercâmbio, demanda etc. Comparações com modelos de redes neurais são feitas. Apresenta-se, também, o estado da arte em modelagem para a política e o mercado de energia elétrica e os principais conceitos de gerenciamento de risco no mercado de eletricidade. / [en] This thesis focuses on spot price forecasting and risk management in the Brazilian electricity industry. It is proposed a new methodology for the problem based on neuro- fuzzy systems and the dispatching and planning operation programs. The main advantage of the approach is to be able to get more informative spot price distributions than using the operation and planning programs alone. Furthermore, it allows Monte Carlo simulations or scenarios analysis as the forecasting system runs in less than 1 minute. The main variables which affect the spot price (inflow river, storage capacity of reservoir, among others) are included in the model. Even variables such as the interchange limits, without a well-defined time series and which could be important, could also be included because of the intrinsic characteristics of each fuzzy model. Comparisons with neural networks models are made. It is also presented the state-of-the-art in the market and politics modelling for the electricity market around the world, as well as some main concepts of the risk management.
25

Formação do preço da energia convencional nas transações entre agentes no mercado de curto prazo brasileiro. / The spot price of conventional energy at the brazilian free market.

Gustavo Sozzi 10 April 2015 (has links)
Hoje no mercado brasileiro de eletricidade, o preço da energia convencional é composto pela soma do valor do Preço de Liquidação das Diferenças (PLD) divulgado pela Câmara de Comercialização de Energia Elétrica (CCEE) semanalmente com o valor do Spread negociado bilateralmente no mercado à vista (mercado de curto prazo), resultante do equilíbrio entre oferta e demanda. Em alguns momentos, o valor do Spread chega a representar mais de 100% do custo total da energia. Este trabalho faz uma análise do mercado brasileiro, bem como, de alguns mercados no exterior de energia elétrica e destaca os pontos que tem influência direta, na formação do Spread da energia convencional e como isso afeta a decisão de contratação dos agentes. Além disso, o trabalho busca encontrar correlações entre dados divulgados, como carga e oferta de energia, com o ágio negociado no mercado de curto prazo, buscando entender o real impacto de cada um desses fatores e explicar as grandes variações já observadas. Sugere-se também um modelo de regressão linear múltipla para a projeção de valores do ágio. Para tanto, foram utilizadas informações proveniente de um banco de dados de cotações de negócios efetivamente realizados no curto prazo desde janeiro de 2011 até julho de 2014, bem como informações retiradas da CCEE e Operador Nacional do Sistema (ONS). / The Brazilian wholesales energy market price is formed by de sum of the PLD (Market Clearing Price which is released weekly by the Commercial Chamber) and a Spread value, resulting from the negotiation between the market agents. In some cases, the Spread represent more than 100% of the energy total cost. This paper presents an overview about some energy markets, focusing the Brazilian Energy Market, so as to highlight points that affect the Spread value at the spot market and, as consequence, the strategy of the market agents. Additionally, this paper shows the correlation between energy demand and energy offer and energy spread negotiated at the short term market, trying to understand the real impact of each variable trying to get the right explanation regarding the big variations observed. It has been suggested a mathematical model of multiple linear regression to forecast the spread value. In order to accomplish this purpose it was used (i) a historical data of effectively trading situations at the short term market, comprising the period between January 2011 to July 2014, as well as (ii) informations released by the Commercial Chamber (CCEE) and the System Operator (ONS).
26

Business Case Tools för distribuerade solcellsanläggningar : En Power BI-modell för investeringsmodellering och visualisering i Sverige / Business Case Tools for distributed solar PV systems

Hennings, Erik, Ingvarsson, Johan, Fält, Gustav January 2023 (has links)
The global climate and energy crisis has amplified the need for renewable energy sources, withsolar photovoltaic (PV) systems expected to play a significant role in the future energy mix. In this context, distributed energy systems (DES) are identified as part of the solution to address climate and energy challenges.With the increasing demand for photovoltaic energy sources, there is a growing requirement forefficient Business Case Tools (BCT) to analyze investments in distributed solar PV installations.A two-part model, consisting of a solar model and spot price data, was developed based onparameters such as solar radiation, location, angle, orientation, system losses, installedcapacity, and historical spot price data. The model was integrated with Power BI for investment calculations and visualization of results. The developed model provides approximations for solar PV system electricity production, which were validated against selected installations in allelectricity areas of Sweden. The validation revealed an average relative absolute error of 14.72 percent for the model. The conclusion drawn is that BCT can be utilized to analyze and visualize solar PV investments at specific locations in Sweden. The results indicate that Power BI, as a BCT, has limitations indynamic data collection but performs well in executing calculation of investments and visualizingthe results. Well-developed BCT can facilitate decision-making through real-time calculations and contribute to smoother implementation of distributed systems by providing detailed insightsinto their financial characteristics. Further research is needed to develop a model specificallytailored for distributed installations with storage capabilities. / Världen befinner sig i en global klimat- och energikris vilket ökat behovet av och efterfrågan på förnybara energikällor. Solceller förväntas utgöra en betydande del av den framtida energimixen. I kombination med detta identifieras distribuerade energisystem (DES) som endel av lösningen på klimat- och energifrågan. I takt med den ökade efterfrågan på fotovoltaiska energikällor ställs större krav på effektiva Business Case Tools (BCT) för att analysera investeringar i distribuerade solcellsanläggningar. En modell bestående av två delar, en solmodell och spotprisdata,utvecklades utifrån parametrarna solstrålning, plats, vinkel, riktning, systemförluster, installerad effekt samt historiska spotprisdata. Modellen sammankopplas med Power BI föratt utföra investeringskalkyler och visualisera resultatet. Den utvecklade modellen gerapproximationer för solcellsanläggningars elproduktion, vilket validerades mot utvaldaanläggningar i Sveriges samtliga elområden. Enligt valideringen uppgår modellens genomsnittliga relativa absoluta fel till 14,72 procent. Slutsatsen dras att BCT kan användas för att analysera och visualisera solcellsinvesteringar på specifika platser i Sverige. Resultatet visar att Power BI som BCT har brister när detkommer till dynamisk datainsamling, men genomför och visualiserar investerings kalkyler med enkelhet. Välutvecklade BCT kan användas för att underlätta beslutsfattande genomrealtidsberäkningar och kan bidra till en smidigare implementering av distribuerade systemgenom att belysa deras finansiella karaktär på ett detaljerat sätt. Fortsatt forskning krävs föratt ta fram en modell anpassad för distribuerade anläggningar med lagringsmöjligheter.

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