TY - GEN
T1 - Two-stage stochastic optimization for hybrid AC/DC microgrid embedded energy hub
AU - Zhao, Tianyang
AU - Xiao, Jianfang
AU - Hai, Koh Leong
AU - Wang, Peng
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/6/28
Y1 - 2017/6/28
N2 - 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.
AB - 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.
KW - Hybrid AC/DC microgrid
KW - energy router
KW - multi-carrier energy system
KW - two-stage stochastic programming
UR - https://www.scopus.com/pages/publications/85049138118
U2 - 10.1109/EI2.2017.8245648
DO - 10.1109/EI2.2017.8245648
M3 - 会议稿件
AN - SCOPUS:85049138118
T3 - 2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017 - Proceedings
SP - 1
EP - 6
BT - 2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017
Y2 - 27 November 2017 through 28 November 2017
ER -
