Dynamic reconfiguration method for multi-agent participation AC and DC hybrid distribution network

An AC-DC hybrid and dynamic reconfiguration technology, applied to AC network circuits, AC networks with the same frequency from different sources, AC networks with energy trade/energy transmission rights, etc., can solve problems that need further research

Active Publication Date: 2018-02-02
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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Problems solved by technology

The distribution network operation under the participation of multiple agents, its optimization problem is the multi-time scale problem of multiple participants, and the distribution network reconfiguration method under the participation of multiple agents needs to be further studied

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  • Dynamic reconfiguration method for multi-agent participation AC and DC hybrid distribution network
  • Dynamic reconfiguration method for multi-agent participation AC and DC hybrid distribution network
  • Dynamic reconfiguration method for multi-agent participation AC and DC hybrid distribution network

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Embodiment 1

[0122] This embodiment adopts the IEEE-33 node calculation example system with AC and DC hybrid for detailed description, as shown in figure 2 The system structure diagram of the IEEE-33 node calculation example of AC and DC hybrid shown in the figure includes the distribution network operator (DNO) operating the standard IEEE-33 node power distribution system, and the operation of the multi-microgrid alliance composed of three microgrids There are multiple subjects of business operators (MCO) and microgrid (MG) operators, and multiple microgrids form a cooperative alliance through DC-link capacitors, thereby conducting transactions with power distribution operators. Within the alliance, due to the randomness and volatility of distributed power generation and the randomness of user loads, there are errors in the forecast values ​​of photovoltaics and wind turbines. DC-link connects the AC microgrid through DC to share backup, improve the power supply reliability of the micro...

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Abstract

The present invention belongs to the technical field of power system optimal scheduling and particularly relates to a dynamic reconfiguration method for a multi-agent participation AC and DC hybrid distribution network. According to the method, with the consideration of the risk of a day-ahead prediction error, the optimization solution is carried out with a day-ahead dispatch cost minimum as a target function. In addition, after the completion of a transaction of a micro-grid alliance and a distribution network is completed, a self-based settlement strategy is used by a micro grid in the alliance, and a lower-cost renewable energy trading strategy is used preferentially to carry out cost distribution. A power distribution operator adopts a genetic algorithm to decide a distribution network reconfiguration plan in the next 24 hours based on an exchange power plan uploaded by multiple micro-grid alliances and power prediction values of other load points. According to the method, a day-ahead load value and a prediction error of a distributed power supply are fully considered, the fluctuation of scheduling cost is effectively reduced, and the method is very instructive for the scheduling of the AC and DC hybrid distribution network for the widespread access of the multiple micro grids to the power distribution network in the future.

Description

technical field [0001] The invention belongs to the technical field of power system optimization dispatching, and in particular relates to a dynamic reconfiguration method of an AC / DC hybrid distribution network with participation of multiple subjects. Background technique [0002] With the continuous development of microgrid technology, multi-microgrid access to distribution network will be widely used. Compared with a single microgrid, multi-microgrids are connected through DC links, which have greater advantages in terms of capacity backup, emergency energy supply, and power trading. The optimal scheduling of multi-microgrids has attracted much attention from researchers. The current optimal scheduling methods include day-ahead optimal scheduling and real-time optimal scheduling. For day-ahead optimal scheduling, this method has errors in the prediction of load, photovoltaic and wind turbine data, and random Optimized approach to reduce the risk of scheduling fees. Dist...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/00H02J3/06H02J3/38H02J3/46
CPCH02J3/003H02J3/008H02J3/06H02J3/383H02J3/386H02J3/46H02J2203/20Y02E10/56Y02E10/76
Inventor 刘念郭斌
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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