Open AccessEnergy and economic evaluation of Gas-electric hybrid energy system based on improved genetic algorithm
Author(s) -
Changhao Liang,
Yusheng Dou,
Yuchen Wang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2005/1/012075
Subject(s) - power to gas , natural gas , electric power system , genetic algorithm , power (physics) , electric power , grid , electricity , energy (signal processing) , automotive engineering , engineering , computer science , electrical engineering , electrolysis , chemistry , physics , geometry , mathematics , electrode , quantum mechanics , statistics , machine learning , electrolyte , waste management
In the future when there are more and more new energy sources in the grid, the Power-to-Gas(P2G) interconnected operation network will be affected by new external energy sources, resulting in an imbalance between the generated power and the actual power required for the normal operation of the grid. On the one hand, the application of P2G technology can guide the further integration of the power system and the natural gas system. The power-to-gas balance grid based on water electrolysis is a promising solution, which can effectively reduce the uncertainty of the system dispatching plan. On the other hand, the physical properties of natural gas determine that it can provide a method for the consumption of excess electricity. This paper proposes a peak load shifting calculation model based on an improved genetic algorithm, which smoothes the net load curve of the Gas-electric hybrid energy system through the coordination of P2G and gas-fired generators. The test example used in the algorithm adopts the modified IEEE39-node power network and the coupling system of the Belgian 20-node natural gas system to analyze the static load fluctuations of the system operation under various conditions. It is verified that the power-to-gas conversion and the algorithm researched in this paper can effectively smooth the net load fluctuation and improve the system's new energy absorption capacity.