TY - JOUR
T1 - Hierarchical optimization and grid scheduling model for energy internet
T2 - a genetic algorithm-based layered approach
AU - Lin, Lihua
AU - Abdallah, Abdallah
AU - Ishak, Mohamad Khairi
AU - Ali, Ziad M.
AU - Khan, Imran
AU - Rabie, Khaled
AU - Bayram, Islam Safak
AU - Li, Xingwang
AU - Madsen, Dag Øivind
AU - Kim, Ki-Il
PY - 2022/7/19
Y1 - 2022/7/19
N2 - The old economic and social growth model, characterized by centralized fossil energy consumption, is progressively shifting, and the third industrial revolution, represented by new energy and Internet technology, is gaining traction. Energy Internet, as a core technology of the third industrial revolution, aims to combine renewable energy and Internet technology to promote the large-scale use and sharing of distributed renewable energy as well as the integration of multiple complex network systems, such as electricity, transportation, and natural gas. This novel technology enables power networks to save energy. However, multienergy synchronization optimization poses a significant problem. As a solution, this study proposed an optimized approach based on the concept of layered control–collaborate optimization. The proposed method allows the distributed device to plan the heat, cold, gas, and electricity in the regional system in the most efficient way possible. Moreover, the proposed optimization model is simulated using a real-number genetic algorithm. It improved the optimal scheduling between different regions and the independence of distributed equipment with minimal cost. Furthermore, the inverse system and energy and cost saving rate of the proposed method are better than those of existing methods, which prove its effectiveness.
AB - The old economic and social growth model, characterized by centralized fossil energy consumption, is progressively shifting, and the third industrial revolution, represented by new energy and Internet technology, is gaining traction. Energy Internet, as a core technology of the third industrial revolution, aims to combine renewable energy and Internet technology to promote the large-scale use and sharing of distributed renewable energy as well as the integration of multiple complex network systems, such as electricity, transportation, and natural gas. This novel technology enables power networks to save energy. However, multienergy synchronization optimization poses a significant problem. As a solution, this study proposed an optimized approach based on the concept of layered control–collaborate optimization. The proposed method allows the distributed device to plan the heat, cold, gas, and electricity in the regional system in the most efficient way possible. Moreover, the proposed optimization model is simulated using a real-number genetic algorithm. It improved the optimal scheduling between different regions and the independence of distributed equipment with minimal cost. Furthermore, the inverse system and energy and cost saving rate of the proposed method are better than those of existing methods, which prove its effectiveness.
KW - optimization
KW - stability analysis
KW - genetic algorithm
KW - internet of energy
U2 - 10.3389/fenrg.2022.921411
DO - 10.3389/fenrg.2022.921411
M3 - Article
SN - 2296-598X
VL - 10
JO - Frontiers in Energy Research
JF - Frontiers in Energy Research
M1 - 921411
ER -