چكيده به لاتين
With the increasing use of distributed energy resources, the development of energy systems integrated with power systems has become an important issue. An energy hub can manage, store and transfer multiple energy carriers. To facilitate the participation of an energy hub in the electric and thermal energy markets, the concept of virtual energy hub has been introduced, which is a combination of the two concepts of virtual power plant and energy hub. This thesis presents the self-scheduling of a virtual energy hub to participate in the multiple energy and reserve markets. The hybrid CNG and plug-in electric vehicles (HPEVs) are considered in the virtual energy hub structure that can use both electrical energy and compressed natural gas (CNG) to fulfill their energy needs. These vehicles emit no pollutants during the electric mode and emit lower amounts of pollutants when consuming CNG compared to gasoline vehicles. The alternative fuel can tackle the limitations of prolonged charging of electric vehicles and excess load caused by these vehicles at peak hours. To supply the secondary fuel of HPEVs, the modeled VEH includes a CNG station, which compresses the natural gas imported from the natural gas grid before delivering it to the vehicles. Furthermore, phase change material-based thermal energy storage (PCMTES) is considered in VEH configuration, which operates at a constant temperature during the charging and discharging period, unlike other common thermal energy storage systems. To solve the proposed system, robust scenario-based and deep learning methods in two separate modelings have been used. The robust scenario-based approach in this thesis has been modified to be able to control the downside risk of the problem without adding excess constraints. To develop optimization based on deep learning, deep bidirectional long short-term memory networks have been used, which show good performance in predicting values of uncertain parameters. The results of the two models developed for the virtual energy hub show the importance of the proposed system of this thesis in integrating the power systems with natural gas grid, thermal network, and transportation systems and reducing the pollutants produced by these networks.
