Robust <scp>self‐scheduling</scp> of a virtual <scp>multi‐energy</scp> plant in thermal and electricity markets in the presence of <scp>multi‐energy</scp> flexible technologies
Yasin Pezhmani, Mohammad Amin Mirzaei, Kazem Zare, Behnam Mohammadi‐Ivatloo
Abstract
Virtual power plant (VPP) aggregates a diverse set of renewable energy sources, energy storages, and flexible loads to operate them as a single power plant in the energy markets. With the advent of multi-energy systems, the operation and mechanism of traditional VPPs are enhanced for acting in multiple markets and providing more flexibility for energy management systems. In this work, a robust optimization method is proposed for optimal self-scheduling of a new VPP termed as a virtual multi-energy plant (VMEP) in electricity and thermal markets in the presence of different energy storages. The proposed VMEP consists of wind turbines, heat-only units, combined heat and power units, photovoltaic panels, electrical energy storages, and thermal storages. Also, thermal and electrical price-based demand response (DR) programs are employed to shift the multi-carrier energy demand of the VMEP's consumers into low price periods. In addition, a robust decision-making model is implemented to deal with the uncertainty of electricity market prices in the optimal self-scheduling of the VMEP without the need for a probability distribution function. The simulation results demonstrate that the implementation of multi-energy DR programs can increase the VMEP's daily profit by about 8.5%. Additionally, the economic performance of the VMEP in multi-energy markets is enhanced up to 10.5% by utilizing multi-carrier energy storages.