Assessment of emission trading impacts on competitive electricity market price

2011 ◽  
Vol 5 (3) ◽  
pp. 333-344
Author(s):  
S.N. Singh ◽  
D. Saxena ◽  
Jacob Østergaard
Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3325
Author(s):  
Vanderson Aparecido Delapedra-Silva ◽  
Paula Ferreira ◽  
Jorge Cunha ◽  
Herbert Kimura

The electricity market in Brazil is basically organized under two parts: the regulated market, where energy is traded through auctions, and the free market, where market participants freely negotiate the price and quantity of electricity. Although revenues obtained in the regulated market tend to be lower than in the free market, the auctions’ results show that investors still value the lesser degree of uncertainty associated with the regulated market. However, a growing interest in the free market by investors is recognized since the price of electricity tends to be higher. Therefore, this study investigates four free market price scenarios to assess the expected return for investors, using the traditional discounted cash flow approach complemented with Monte Carlo simulation to address market uncertainty. The study breaks new ground by capturing the weekly price fluctuations and including the price elasticity of demand of the free market. The results seem to indicate that the disclosure of the ceiling and floor price limits for the spot price can signal important information about the agents’ price expectation in the free market and can be used for investment project evaluation.


Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7473
Author(s):  
Hakan Acaroğlu ◽  
Fausto Pedro García Márquez

Forecasting the electricity price and load has been a critical area of concern for researchers over the last two decades. There has been a significant economic impact on producers and consumers. Various techniques and methods of forecasting have been developed. The motivation of this paper is to present a comprehensive review on electricity market price and load forecasting, while observing the scientific approaches and techniques based on wind energy. As a methodology, this review follows the historical and structural development of electricity markets, price, and load forecasting methods, and recent trends in wind energy generation, transmission, and consumption. As wind power prediction depends on wind speed, precipitation, temperature, etc., this may have some inauspicious effects on the market operations. The improvements of the forecasting methods in this market are necessary and attract market participants as well as decision makers. To this end, this research shows the main variables of developing electricity markets through wind energy. Findings are discussed and compared with each other via quantitative and qualitative analysis. The results reveal that the complexity of forecasting electricity markets’ price and load depends on the increasing number of employed variables as input for better accuracy, and the trend in methodologies varies between the economic and engineering approach. Findings are specifically gathered and summarized based on researches in the conclusions.


2015 ◽  
Vol 15 (2) ◽  
pp. 115-127
Author(s):  
Ewa Drabik

Abstract The Polish energy market gained its competitive character in late 1990s. At that time in majority of European countries a new law was enacted (in Poland – in 1987), which enabled the creation of internal energy markets. The Polish Power Exchange has been functioning since the end of 1999. However, from the very onset it has constituted a vital component of under grounding liberalization of electricity market. Since it was created the Polish Power Exchange has served as a market mechanism for setting objective energy market price. Support and control of the Polish Financial Supervision Authority guarantee the security of concluded transactions. The spot energy market was created as the first one and has functioned according to the rule of the double auction. The model of Sadrieh will be used for the description of the auction rules applied to the spot energy trade on the Polish Power Exchange. Furthermore, an algorithm on the basis of which it is possible to forecast transaction prices is presented. The effectiveness of this algorithm will be compared with other traditional methods of forecasting transaction prices.


Author(s):  
Alicia Troncoso Lora ◽  
Jose Riquelme Santos ◽  
Jesus Riquelme Santos ◽  
Jose Luis Martinez Ramos ◽  
Antonio Gomez Exposito

Author(s):  
Paul W. Talbot ◽  
Abhinav Gairola ◽  
Konor Frick ◽  
Cristian Rabiti

Abstract This paper reports the development of HERON (Holistic Energy Resource Optimization Network), a newly-developed RAVEN (Risk Analysis Virtual ENvironment) plugin for grid and capacity optimization, to technoeconomic analysis in a deregulated market. A short description of the HERON plugin is provided, and the release process is described. HERON as a plugin enables RAVEN to perform stochastic technoeconomic analysis of grid-energy systems in a generic approach. The primary function of HERON is to generate the complex RAVEN workflows necessary to optimize component capacities under stochastic systems. HERON is capable of analyzing systems with complex components transferring a variety of commodities, including production components and varied markets. HERON is capable of optimizing high-resolution dispatch for such systems and guiding stochastic optimization algorithms in RAVEN for finding optimal component capacities. In particular, this document demonstrates the application of HERON to systems with deregulated markets. A system including a hyrdogen market, an electricity market, hydrogen storage, a hydrogen producer, and a nuclear power plant is considered. Stochastic histories for electricity prices at the electricity market are employed to perform stochastic analysis for ideal sizing of the hydrogen production facility and hydrogen storage unit. The impact of hydrogen market price and volatility of electricity price are also shown.


Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4557 ◽  
Author(s):  
Ilkay Oksuz ◽  
Umut Ugurlu

The intraday electricity markets are continuous trade platforms for each hour of the day and have specific characteristics. These markets have shown an increasing number of transactions due to the requirement of close to delivery electricity trade. Recently, intraday electricity price market research has seen a rapid increase in a number of works for price prediction. However, most of these works focus on the features and descriptive statistics of the intraday electricity markets and overlook the comparison of different available models. In this paper, we compare a variety of methods including neural networks to predict intraday electricity market prices in Turkish intraday market. The recurrent neural networks methods outperform the classical methods. Furthermore, gated recurrent unit network architecture achieves the best results with a mean absolute error of 0.978 and a root mean square error of 1.302. Moreover, our results indicate that day-ahead market price of the corresponding hour is a key feature for intraday price forecasting and estimating spread values with day-ahead prices proves to be a more efficient method for prediction.


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