| description abstract | The growing share of renewable energy sources in the energy mix and the liberalization of electricity markets has drastically affected the operation of electricity generators. Especially, in the last decade, fossil fuel-based generators have shifted their role from providing continuous base load to covering the peak demand and providing backup capacity to stabilize the grid. At the same time, a large amount of storage capacity is foreseen to be integrated into electricity grids in the coming years to shave demand peaks, mitigate price volatility, and provide services to the grid. In such a situation, in order to properly manage these crucial technologies, and thus guarantee the economic viability of the operation, it is essential to properly optimize the dispatch and define the best scheduling. This paper considers a gas turbine combined cycle and battery energy storage to study the problem of dispatch optimization of both generators and storage technologies. Different optimization algorithms have been considered and mixed integer linear programming is selected for its ability to identify the global optimum and the reduced optimization time. The impact of optimization windows (i.e., the forecast horizon of electricity prices) is also investigated. It is highlighted that an increase in forecasting ability, at least up to 36 h, guarantees more effective scheduling; on the other hand, it may require a significantly longer time. Subsequently, different approaches to account for the operation and maintenance costs at the optimization stage are assessed, and, finally, a sensitivity analysis is carried out with respect to market parameters (price average and variability) and technology features (conversion efficiency, cycle cost, etc.). | |
