This paper presents a system of computer vision designed to be used in industry for product classification. The system is based on the TensorFlow and Keras software libraries and the Python programming language. In the production process, uniform cylindrical parts reach the conveyor designed so that each part can be in one of two possible positions. The computer vision system detects the exact position of the part, or its orientation, and this information is further used during the transportation process. The purpose of the procedure is for all parts to take the same orientation in relation to the production line.
Abstract:Electricity market deregulation and liberalization have led to high volatility on power exchanges, which require the use of derivatives in energy markets for more efficient risk management which the participants at the market are exposed to. The available options are one of the derivatives that have entered liquid markets. Therefore, this paper presents an example from the most developed energy exchange EEX (European Energy Exchange), with the aim of applying verified scientific methods to check the practice of functioning of liquid energy market, by using options to reduce the risk. The most frequently used models for hedging future open positions and evaluation of premium on options in practice are the Black -Scholes and Black 76 model, which are therefore presented in the text. South East European Power Exchange (SEEPEX) has started operating in Serbia. Its development is going to be via integration with regional markets in the direction of integration of the total electric energy market in Europe. That path will be long, but it has already required the knowledge of market instruments used in trading and risk management at the power exchanges. Presented results refer to the essential knowledge of dynamic variables that options bring into the energy market in order to reduce the risk.
Research Question: The launch and the beginning of trade on the South East Electric Power Exchange (SEEPEX) in Belgrade, early in 2016, opened the issue of forecasting volatility and price movements in the market. Motivation: The issue is of vital importance for all market actors for the purpose of maximising profits, reducing risks, planning production and making investment decisions. Forecasting volatility and price movements in electric power markets is important for traders with profit maximisation and yield-to-risk ratio optimisation in mind and, equally, for producers, large industrial consumers, investors and portfolio managers. Idea: Exploring models and techniques to forecast volatility in electricity markets and subsequently testing statistical methods based on time series data, the ARMA-GARCH being the preferred model, with a view to identifying optimal methods for this market. The volatility of the power market and price movements have been tested during a given period. The results can be used to gauge market parameters and opportunities to extrapolate future volatility and movements in electricity prices. Data: For the purposes of this analysis, a time series involving price movements and trade volumes were used, covering a period between the SEEPEX trade launch and the end of 2019. Tools: In the empirical part of the paper, "Stata 13" statistical and econometric software was used to explore stylised facts and model the volatility of SEEPEX electricity price returns. Findings: The authors offer an overview of different methods used in the research, having selected different specifications of the ARMA-GARCH model as the most reliable in predicting volatility in the given market. The exponential GARCH model with student-t error distribution is believed to have provided the best overall performance in modelling the SEEPEX return volatility, as well as the best volatility forecast. Contribution: This is one of the first empirical studies of the Serbian power market that deals with risk modelling. Forecasting time-varying electricity exchange volatility is important for all market participants interested in variance forecasts to be used to calculate risk and hedging measures.
The research subject of this paper is the possibility of market power misuse in electricity market. The primary hypothesis is that electricity markets are supposed to function according to similar principles used in financial and commodity markets, but that they are susceptible to bigger constraints which can impair the efficient performance, as well as to higher possibilities of market position misuse by the trading participants. The main purpose of this paper is both to identify and define those potential misuses and to propose the ways in which they could be reduced like: the reduction of market concentration, the increase of the demand responsiveness to a change in price, the reduction of asphyxiation on the electrical grid, the increase of the average level of hedging and bidding control.
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