Pneumoelectric combined system distribution network reinforcing method considering natural disasters
A joint system and natural disaster technology, applied in the direction of power network operating system integration, AC network with the same frequency from different sources, AC network circuits, etc., can solve problems such as security threats and economic losses
Inactive Publication Date: 2020-12-01
SICHUAN UNIV
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In recent years, the distribution network of gas-electricity combined system has been threatened by more frequent natural disasters and caused huge economic losses.
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[0095] In order to describe the technical solutions disclosed in the present invention in detail, the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.
[0096] The invention discloses a gas-electricity combined system distribution network reinforcement method under consideration of natural disasters. The specific implementation steps are as follows: figure 1 Shown, technical scheme of the present invention comprises the following steps:
[0097] Step 1: Establish the reinforcement model of the distribution network power lines and natural gas pipelines of the combined gas-electricity system. Equation (1) gives the feasible region of the upper reinforcement constraints, that is, the reinforcement measures have a certain budget limit. Coefficient κ ij and κ mn Represents the financial and manpower consumption required for the reinforcement of power lines and natural gas pipelines with different character...
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The invention discloses a pneumoelectric combined system distribution network reinforcing method considering natural disasters, which comprises the following steps of firstly, establishing a natural disaster model under the condition of considering different failure probabilities of an overhead power line and an underground natural gas pipeline, establishing a multi-layer robust pneumoelectric combined system distribution network reinforcing model by taking minimization of the pneumoelectric total weighted load loss in the worst scene as a target and combining with set distribution network related operation constraints, and in view of nonlinear natural gas flow equation constraints of a gas distribution network, using a Taylor series expansion method to convert a non-linear pneumoelectricintegrated energy system distribution network reinforcing model into a mixed integer linear programming (MILP) problem, and solving the established multi-layer robust pneumoelectric combined system network reinforcing model by adopting a CCG algorithm to obtain a prospective optimal network reinforcing strategy for coping with upcoming natural disasters, thereby improving the toughness of the pneumoelectric combined system distribution network to the natural disasters.
Description
technical field [0001] The invention belongs to the technical field of comprehensive energy system planning and design, and particularly relates to a method for reinforcing a gas-electricity combined system distribution network under consideration of natural disasters. Background technique [0002] With the continuous development of the distribution network of the power system, distributed gas-fired power generation has deepened the dependence of the power distribution network on the natural gas distribution network. In recent years, the distribution network of gas-electricity combined system has been threatened by more frequent natural disasters and caused huge economic losses. When the distribution network equipment of the gas-electricity system is damaged by natural disasters, it is necessary to ensure that the high-priority gas-electricity loads are supplied first. Network reinforcement is considered to be an effective measure to improve the resilience of the distributi...
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IPC IPC(8): H02J3/06H02J3/14H02J3/46G06F30/20G06Q10/04G06Q50/06G06F111/04G06F113/14
CPCG06Q10/04G06Q50/06G06F30/20G06F2111/04G06F2113/14H02J3/06H02J3/144H02J3/466H02J2203/10H02J2203/20H02J2300/40Y02B70/3225Y04S20/222
Inventor 何川张琪刘天琪
Owner SICHUAN UNIV