Optimization in day-ahead planning of energy trading

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Abstract

In the twentieth century electricity was produced and transmitted by and between monopolistic public electric power companies. Over the last twenty years, electricity markets have been deregulated allowing customers to choose from a number of competing suppliers and producers. On one hand electricity market participants try to first satisfy their own country's demand and, on the other hand, to transmit electricity across borders into neighborhood markets. Cross-border transmission is part of a competition where market participants have non-discriminatory access to interconnected transmission lines. This paper examines the problem of day-ahead planning at trading sections of electricity companies. The underlying assumption is that the demand and supply are known in advance. Available transmission capacities are also known as well as additional transmission capacities that can be purchased. The prices and amounts of trading and transmission are subjects of auctions. The problem of day-ahead planning is here disscussed from the perspective of a decision maker of an energy trading company (ETC). Decisions to be made are: where and how much electricity should the ETC buy and sell, and which transmission capacity will be used in order to maximize daily profit. The problem is formulated according to real- life experience of a Serbian ETC which trades in Central and South-East Europe. It is further modeled as a directed multiple-source and multiple-sink network and then represented by linear programming (LP) mathematical model in which the total daily profit is maximized subject to market constraints and flow capacities. The main goal of this model is to provide a useful tool for preparing auction bids. Numerical examples are given in order to illustrate possible applications of the model.

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CITATION STYLE

APA

Marinović, M., Makajić-Nikolić, D., & Stanojević, M. (2013). Optimization in day-ahead planning of energy trading. Journal of Applied Engineering Science, 11(4). https://doi.org/10.5937/jaes11-4604

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