scholarly journals Description of Colombian Electricity Pricing Derivatives

2021 ◽  
Vol 2 (3) ◽  
pp. 191-211
Author(s):  
Sellamuthu Prabakaran
Keyword(s):  
Electricity Markets ◽  
Electricity Market ◽  
Jump Process ◽  
Electricity Price ◽  
Price Dynamics ◽  
Model Estimation ◽  
Electricity Pricing ◽  
Electricity Derivatives ◽  
Analytical Formulas ◽  
Electricity Spot Market

Electricity markets are becoming a popular field of research amongst academics because of the lack of appropriate models for describing electricity price behavior and pricing derivatives instruments. Models for price dynamics must consider seasonality and spiky behavior of jumps which seem hard to model by standard jump process. Without good models for electricity price dynamics, it is difficult to think about good models for futures, forward, swaps and option pricing. In this paper we attempt to introduce an algorithm for pricing derivatives to intuition from Colombian electricity market. The main ambition of this study is fourfold:  1) First we begin our approach through to simple stochastic models for electricity pricing. 2) Next, we derive analytical formulas for prices of electricity derivatives with different derivatives tools. 3) Then we extent short of the model for price risk in the electricity spot market 4) Finally we construct the model estimation under the physical measures for Colombian electricity market. And this paper end with conclusion.

scholarly journals Neural Network Based Model Comparison for Intraday Electricity Price Forecasting

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4557 ◽  
Author(s):  
Ilkay Oksuz ◽  
Umut Ugurlu
Keyword(s):  
Neural Networks ◽  
Electricity Markets ◽  
Electricity Market ◽  
Network Architecture ◽  
Model Comparison ◽  
Market Price ◽  
Absolute Error ◽  
Electricity Price ◽  
Price Forecasting ◽  
Electricity Price Forecasting

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.

A Research into Probabilistic Electricity Load Prediction Based on Demand Response Feature under Smart Grid Environment

2013 ◽  
Vol 380-384 ◽  
pp. 3098-3102
Author(s):  
Ning Lu ◽  
Ying Liu
Keyword(s):  
Real Time ◽  
Demand Response ◽  
Electricity Market ◽  
Electricity Price ◽  
Electricity Pricing ◽  
Load Prediction ◽  
Characteristics Analysis ◽  
System Risk ◽  
Probabilistic Load ◽  
Demand Changes

The construction of grid plays an important role in national economic development, social stability and peoples life. In case that electricity market adopts real time electricity price, users active participation and real time response to electricity price will change the traditional load prediction from rigid forecasting to flexible forecasting which takes electricity demand response into consideration. By using wavelet analysis and error characteristics analysis, the researches into the probabilistic predicting method for demand changes under the real time electricity pricing is carried out. The probabilistic load prediction result shall enable decision makers to better understand the load change range in the future and make more reasonable decision. Meanwhile, it shall provide support to electricity system risk analysis.

scholarly journals Essays on the Interaction  Between Risk and Market  Structure in Electricity  Markets

2021 ◽  
Author(s):  
◽  
Gabriel Godofredo Fiuza de Braganca
Keyword(s):  
Market Structure ◽  
Market Power ◽  
Electricity Markets ◽  
Electricity Market ◽  
Hybrid Approach ◽  
Spot Market ◽  
Spot Price ◽  
Policy Makers ◽  
Forward Markets ◽  
Electricity Spot Market

<p>This thesis proposes a new framework to jointly analyze electricity spot market and hedging decisions in an oligopolistic setup. Firstly, we find that, when exogenous, both quantity of electricity hedged by contract and vertical integration decrease the equilibrium spot price. Secondly, we use a hybrid approach and show that market structure can affect a generator’s decision to vertically integrate under uncertain demand. Thirdly, we consider uncertainty in costs and demand and show that concentration in the spot market, for a given hedge quantum, can increase forward prices and affect the slope of the forward curve. Our empirical results indicate that the model fits the New Zealand electricity market well. This evidence that market structure and hedging decisions are closely connected is further explored in a three period equilibrium model for the spot and forward markets, where hedging occurs prior to the submission of supply curves. Taking into account demand-side and supply-side uncertainties, we find that when hedging is endogenous, hedging quantities are affected by spot market parameters, but market power is itself mitigated in the conscious hedging choice of generators. We also show that forward markets can coexist with highly vertically integrated markets. The importance of our results is general. Our models can be used by policy makers to analyze investment and forward price implications of changes in the spot market structure. Our results also indicate that electricity generators, in equilibrium, face a trade-off between market power and hedging. Given that it is socially beneficial to manage risk, the equilibrium impact of their choices on welfare should not be considered in isolation by competition authorities.</p>

scholarly journals Day-ahead electricity price forecasting using WPT, VMI, LSSVM-based self adaptive fuzzy kernel and modified HBMO algorithm

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rahmad Syah ◽  
Mohammad Rezaei ◽  
Marischa Elveny ◽  
Meysam Majidi Nezhad ◽  
Dadan Ramdan ◽  
...  
Keyword(s):  
Electricity Markets ◽  
Electricity Market ◽  
Input Data ◽  
Wavelet Packet ◽  
Electricity Price ◽  
Support Vector ◽  
Accurate Information ◽  
Price Forecasting ◽  
Adaptive Fuzzy ◽  
Self Adaptive

AbstractDue to focal liberality in electricity market projection, researchers try to suggest powerful and successful price forecasting algorithms. Since, the accurate information of future makes best way for market participants so as to increases their profit using bidding strategies, here suggests an algorithm for electricity price anticipation. To cover this goal, separate an algorithm into three steps, namely; pre-processing, learning and tuning. The pre-processing part consists of Wavelet Packet Transform (WPT) to analyze price signal to high and low frequency subseries and Variational Mutual Information (VMI) to select valuable input data in order to helps the learning part and decreases the computation burden. Owing to the learning part, a new Least squares support vector machine based self-adaptive fuzzy kernel (LSSVM-SFK) is proposed to extract best map pattern from input data. A new modified HBMO is introduced to optimally set LSSVM-SFK variables such as bias, weight, etc. To improve the performances of HBMO, two modifications are proposed that has high stability in HBMO. Suggested forecasting algorithm is examined on electricity markets that has acceptable efficiency than other models.

Time-of-Use Pricing in the Electricity Market: An Application of Stackelberg Game

2019 ◽  
Author(s):  
Atharva Ketkar ◽  
Joselyn Koonamparampath ◽  
Mayur Sawant
Keyword(s):  
Power Consumption ◽  
Demand Response ◽  
Electricity Market ◽  
Stackelberg Game ◽  
Electrical Power ◽  
Electricity Industry ◽  
Electricity Price ◽  
Electricity Pricing ◽  
Best Response ◽  
Time Of Use Pricing

Abstract Electrical power, generated and consumed, is perhaps, one of today’s most important construct in determining the progress of a people. The power mismatch between the generated and consumed power is one of the major issues faced in the electricity industry. This can be addressed by analysing user behaviour and manipulating it. This paper attempts to put forth a demand response (DR) technique using the concept of Time-of-Use (ToU) electricity pricing. The utilities have an upper hand of quoting the electricity price whereas the users must follow this price and give their best response of power consumption. This process is similar to a leader-follower setting as in a Stackelberg game where the follower acts according to the leader’s strategy and gives its best response in every situation. This paper proposes a pricing technique where the users are charged according to the amount of power consumed in the specific period of time.

scholarly journals Influence of Wind Power on Intraday Electricity Spot Market: A Comparative Study Based on Real Data

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 2974 ◽  
Author(s):  
Pedro Frade ◽  
João Vieira-Costa ◽  
Gerardo Osório ◽  
João Santana ◽  
João Catalão
Keyword(s):  
Wind Power ◽  
Electricity Markets ◽  
Electricity Market ◽  
Consumer Satisfaction ◽  
Renewable Energy Sources ◽  
Spot Market ◽  
Electricity Sector ◽  
Market Condition ◽  
New Paradigm ◽  
Electricity Spot Market

Overtime, in the electricity sector, there has been a technological transfer to renewable electricity generation. With this change, processes, in the economic and availability terms, are expected to improve. In this new paradigm, society demands electricity without an impact on the environment and with the lowest possible cost. The wind power (WP) integration appears in this evolution process by achieving important technological advances, supporting in 2017 a growth of 44% of new projects in Europe, higher than any other renewable technology. However, the renewable energy sources (RES) integration in the electricity networks still presents technical difficulties and challenges, leading to challenges in the electricity markets (EMs). Therefore, this work evaluates the importance of WP and its influence on the Iberian Electricity Market (MIBEL), at the level of the intraday electricity spot market (IESM). This is an innovative study because literature usually focuses on day-ahead WP impact and this study focuses on intraday markets, which are closer to the consumption periods. The goal was to make an analysis on the impacts when betting on WP sources, in order to improve the market interaction with WP integration, considering as criteria the consumer satisfaction, in terms of lower electricity prices and WP availability. For this study, the market bids registered by the Iberian Electricity Market Operator (OMIE), from 2015 to 2017, ran over a new market simulator, specially developed for this proposal, considering a virtual market condition, but not considering the bids made by WP producers. The comparison of the results allowed the evaluation of the WP influence on the EM quantitative, which is noteworthy.

scholarly journals Research on Funding Differences among Regional Electricity Markets in Northern China based on Thermoelectric Decoupling

2020 ◽  
Vol 185 ◽  
pp. 01017
Author(s):  
Sen Wang ◽  
Can Sun ◽  
Zhiyong Gan ◽  
Liansheng Zhou ◽  
Guilin Wang ◽  
...  
Keyword(s):  
Market Power ◽  
Electricity Markets ◽  
Electricity Market ◽  
Supply And Demand ◽  
Market Price ◽  
Northern China ◽  
Spot Market ◽  
Market Mechanism ◽  
Large Influence ◽  
Electricity Spot Market

With the development of China’s electricity spot market, planned power and market power will coexist for a long time. At the same time, by avoiding the risk of market price fluctuation through medium and long-term market, spot market guarantees electricity balance and secure operation of the grid. The electricity market mechanism has an increasingly large influence on the operation and dispatching model of power system. In spot market, decoupling operation model of market and non-market power has a large influence on both supply and demand sides and improper dredging mechanism may cause significant settlement deviation. To solve this problem, the paper, taking a city in northern China as an example, analyzes the electricity spot market, compares the sources of difference fund of market and non-market power under decoupling and non-decoupling models and compares the pros and cons of coupling and decoupling. The paper also studies the disparity of difference fund and proposes advice adapted to the electricity spot market development of northern China.

scholarly journals Essays on the Interaction  Between Risk and Market  Structure in Electricity  Markets

2021 ◽  
Author(s):  
◽  
Gabriel Godofredo Fiuza de Braganca
Keyword(s):  
Market Structure ◽  
Market Power ◽  
Electricity Markets ◽  
Electricity Market ◽  
Hybrid Approach ◽  
Spot Market ◽  
Spot Price ◽  
Policy Makers ◽  
Forward Markets ◽  
Electricity Spot Market

<p>This thesis proposes a new framework to jointly analyze electricity spot market and hedging decisions in an oligopolistic setup. Firstly, we find that, when exogenous, both quantity of electricity hedged by contract and vertical integration decrease the equilibrium spot price. Secondly, we use a hybrid approach and show that market structure can affect a generator’s decision to vertically integrate under uncertain demand. Thirdly, we consider uncertainty in costs and demand and show that concentration in the spot market, for a given hedge quantum, can increase forward prices and affect the slope of the forward curve. Our empirical results indicate that the model fits the New Zealand electricity market well. This evidence that market structure and hedging decisions are closely connected is further explored in a three period equilibrium model for the spot and forward markets, where hedging occurs prior to the submission of supply curves. Taking into account demand-side and supply-side uncertainties, we find that when hedging is endogenous, hedging quantities are affected by spot market parameters, but market power is itself mitigated in the conscious hedging choice of generators. We also show that forward markets can coexist with highly vertically integrated markets. The importance of our results is general. Our models can be used by policy makers to analyze investment and forward price implications of changes in the spot market structure. Our results also indicate that electricity generators, in equilibrium, face a trade-off between market power and hedging. Given that it is socially beneficial to manage risk, the equilibrium impact of their choices on welfare should not be considered in isolation by competition authorities.</p>

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