عنوان مقاله [English]
In this paper, a robust optimization model is proposed for energy management of a Virtual Power Plant (VPP) including solar power stations, energy storage facilities and demands interconnected within a microgrid. In the robust optimization model, the uncertain parameters of solar power production and energy prices are modelled as confidence intervals. On the other hand, equipped with smart grid technology, the two-way communication between the energy management system and microgrid components, as well as between the energy management system and main grid is possible. The energy management system can make decisions while monitoring conditions of microgrid components and updating available information. Thus, the energy management system is informed about microgrid contingencies in real-time, and modifies its decisions related to power traded with the main grid, solar power production and power load shedding or shifting. The confidence intervals of energy price and solar energy production are forecasted based on real-world historical data collected from the New England electricity market, US. Impact of forecast accuracy, contingency occurrence and confidence level on the performance of the robust optimization model is investigated. Simulation results indicate good performance of the robust optimization model compared with a conventional deterministic method.