Open AccessIntegrated Power System Planning of Multiple Resources with Natural Gas Network and Power Sources
Author(s) -
Jie He,
Zixia Sang,
Jiaqi Huang,
Sicong Wang,
Jiong Yan,
Rengcun Fang
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/621/1/012062
Subject(s) - electricity , power to gas , electricity generation , network planning and design , mathematical optimization , network information system , natural gas , computer science , stand alone power system , distributed generation , power (physics) , engineering , renewable energy , network architecture , mathematics , electrical engineering , network management station , telecommunications , electrolysis , computer security , chemistry , electrolyte , waste management , quantum mechanics , physics , electrode
In order to promote all types of energy utilization, interaction between supply and demand as well as efficient operation, a new generation of energy systems which treats the electricity grid as the core came into being. Unlike traditional power system, the electricity network and gas network in the new generation of energy systems are closely linked through gas-fired units, and influence each other. Therefore, to ensure the safe operation of the future electricity network and natural gas network, the integrated framework for generation, electricity network and gas network expansion planning need to be carried out. Under the premise of meeting the electricity network and gas network safe operation constraints, we propose a multi-stage planning model for the combined generation, electricity network and gas network, in which investment cost and operating cost of the combined system are minimized. Combined generation, electricity network and gas network expansion planning is a large-scale, high-dimensional, non-convex and nonlinear optimization problem, which is difficult to solve. To solve this problem, we propose an incremental piecewise linear method to convert the original model into a large-scale mixed-integer linear optimization problem, allowing the use of sophisticated mathematical optimization method to quickly obtain the optimal solution.