| Abstract | The electricity markets (EM) is a regulated system which allows producers and consumers to sell and buy energy at a given price that is fixed through an auction mechanism. Thanks to the tasks done by this system, the safe generation, transportation and distribution of electricity needed to satisfy the demand of the national population is assured. The electricity markets is made up of several markets, that can be considered either spot markets (day-ahead and intraday markets, whose trading commodity is energy) or ancillary services markets (the commodity negotiated is energy used to assure the stability of the energy delivering).
On the other hand, interacting with the EM there is a wind power plant (WPP) which is in charge of the wind power energy production. A battery energy storage system (BESS) is usually associated to the WPP. The union of the WPP and the BESS is called virtual power plant (VPP).
In this context, an optimization model can be presented: the WBVPP model (WPP+BESS Virtual Power Plant). The aim of this optimization model is the maximization of the expected value of the total profit of the VPP. To calculate this value, it is necessary to quantify the amount of wind power energy that fluctuates between the VPP and the EM, as well as the clearing prices of the auctions.
The main purpose of this project is to obtain scenario trees using a dynamic generation algorithm in order to satisfy the need to solve, in a reasonable period of time, complex optimization problems of optimal supply of wind power plants in electricity markets. The scenarios trees that are going to be obtained include information regarding the production of wind power energy and the clearing prices of the auctions of the different studied electricity markets.
In this study a scenario tree generation algorithm is presented, together with all the theoretical background needed to understand and assure a correct implementation of it, as well as the definition of the different agents that perform in the context of electricity markets. In addition to that, some data will be applied to this algorithm in order to obtain a representation of the scenario trees and to understand the interpretation of them. |
