Two-stage stochastic optimization for hybrid AC/DC microgrid embedded energy hub

Abstract

To enhance the interaction between the thermal and electrical, a hybrid AC/DC microgrid (MG) embedded energy hub (EH) is proposed. In EH, electrical, thermal, i.e. heat and cooling are supplied and managed to increase the operational efficiency while meeting the energy demand. It formulates a two-stage stochastic optimization problem. In the first stage, i.e. day-ahead operation, the hourly generation, conversion, and storage are optimized to minimize the fuel cost. In the second stage, considering the stochastic nature of photovoltaic and demand, the heat and cooling supply are adjusted to realize the power balancing in the electrical system, while meeting the thermal energy demand. The two-stage optimization problem is reformulated to a deterministic optimization problem, using sample average approximation. Simulations have been carried out on the test system. Results have verified the effectiveness of the proposed method, collecting the flexibility of the thermal system to the electrical networks via EH.