Energy network security management optimization method based on large-scale new energy grid connection
A technology of network security and optimization method, which is applied in the field of collaborative optimization and scheduling of multi-energy systems to achieve the effect of improving the utilization rate of new energy power generation, improving the safety level of energy supply, and maintaining the security and stability of the system.
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Embodiment 1
[0092] like figure 1 As shown, this embodiment provides an energy network security management optimization method based on large-scale new energy grid connection, including the following steps:
[0093] Step S1: establish the EH model and the P2G unit model of the multi-energy system;
[0094] Step S2: constructing a coordinated optimal scheduling model between multi-energy hub units including large-scale new energy grid-connected before and after an emergency occurs in the system power grid or natural gas network;
[0095] Step S3: solve the built model;
[0096] Step S4: Obtain an optimal scheme for collaborative optimization scheduling among multi-energy hub units including large-scale new energy grid-connected units.
[0097] The optimal scheduling model proposed by the present invention contains a large number of equality and inequality constraints, and its solution has certain complexity. The GAMS language has strong flexibility and versatility, and has high solving e...
Embodiment 2
[0162] like Figure 4 As shown, a network composed of 14 energy hub units is taken as the research object, in which energy exchange can be performed between each hub unit. Among them, the first, second and sixth energy hubs are energy centers in industrial areas, and the remaining units are energy centers in residential areas. The entire network includes two power grids and two gas grids, hubs 1 to 6 are powered by the first grid and the first gas grid, and hubs 7 to 14 are powered by the second grid and the second gas grid. P2G units supply gas to two gas networks respectively. Power can be exchanged between 1-6 hub units, and power can be exchanged between 7-14 hubs. 1, 5, and 6 hubs can only exchange thermal energy between each other, and all other hubs can exchange thermal energy. The optimal scheduling step is one hour.
[0163] Four different electricity and gas emergency scenarios are considered. The first and second scenarios are contingencies of the first and sec...
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