A multistage stochastic programming model for the optimal bid of a wind producer
Wed, 07/11/2018 - 11:20 — admin
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | F.-Javier Heredia; Marlyn D. Cuadrado; J.-Anton Sánchez |
| Conference Name | 23th International Symposium on Mathematical Programming |
| Conference Date | 01-06/07/2018 |
| Conference Location | Bordeaux |
| Type of Work | contributed presentation |
| Key Words | research; Battery energy storage systems; Electricity markets; Ancillary services market; Wind power generation; Virtual power plants; Stochastic programming |
| Abstract | Abstract: Battery Energy Storage Systems (BESS) can be used by wind producers to improve the operation of wind power plants (WPP) in electricity markets. Associating a wind power plant with a BESS (the so-called Virtual Power Plant (VPP)) provides utilities with a tool that converts uncertain wind power production into a dispatchable technology that can operate not only in spot and adjustment markets (day-ahead and intraday markets) but also in ancillary services markets that, up to now, were forbidden to non-dispatchable technologies. We present in this study a multi-stage stochastic programming model to find the optimal operation of a VPP in the day-ahead, intraday and secondary reserve markets while taking into account uncertainty in wind power generation and clearing prices (day-ahead, secondary reserve, intraday markets and system imbalances). A new forecasting procedure for the random variables involved in stochastic programming model has been developed. The forecasting model is based on Time Factor Series Analysis (TFSA) and gives suitable results while reducing the dimensionality of the forecasting mode. The quality of the scenario trees generated using the TFSA forecasting models with real electricity markets and wind production data has been analysed through multistage VSS. |
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