Multi-energy microgrid distributed scheduling method based on potential game

A scheduling method and multi-energy technology, applied in the direction of resources, genetic models, genetic laws, etc., can solve problems such as information complexity and asymmetry, and achieve the effects of improving search capabilities, increasing population evolution, and avoiding rapid decline.

Pending Publication Date: 2021-01-08
SHANGHAI UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the above existing problems, the present invention relates to a multi-energy micro-grid distributed scheduling method based on potential game, which aims to deal with the information complexity and asymmetry probl

Method used

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  • Multi-energy microgrid distributed scheduling method based on potential game
  • Multi-energy microgrid distributed scheduling method based on potential game
  • Multi-energy microgrid distributed scheduling method based on potential game

Examples

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Embodiment 1

[0105] In this example, see figure 1 , a distributed scheduling method for multi-energy microgrid based on potential game. The multi-energy microgrid system consists of an electric energy subnet and a natural gas subnet. The electric energy subnet has distributed photovoltaic resources, energy storage equipment and diesel generator sets , and connected to the external distribution network; the gas energy sub-network has a gas storage device and is connected to the external natural gas pipeline; the two networks realize the electricity-gas flow through G2P and P2G technology respectively, and through the only information processing center-energy The router communicates, and it is assumed that the subnet can only choose one of P2G and G2P in the same period of time; the distributed scheduling method of the multi-energy microgrid is as follows:

[0106] (1) First, the energy router determines the scope of the interaction between the two subnets according to the output constraints...

Embodiment 2

[0110] This embodiment is basically the same as Embodiment 1, especially in that:

[0111] In this example, see figure 1 , using an improved agent-based particle swarm optimization algorithm to improve the optimization ability in multimodal functions.

[0112]In this embodiment, during the multi-energy microgrid scheduling process, through the mutual influence of G2P and P2G interaction quantities, a single subnet must consider the decisions of other subnets in order to ensure its own optimal benefit. The decision process belongs to a Game process; the three elements of the multi-energy microgrid game are as follows:

[0113] (a) Game participants: including electric energy subnet and gas energy subnet;

[0114] (b) The strategy space of decision makers: the output of diesel generators, the charge and discharge capacity of energy storage devices, the interaction with the main grid, and the power of P2G at each time period of electric energy subnetwork decision-making; The i...

Embodiment 3

[0119] This embodiment is basically the same as the above-mentioned embodiment, and the special features are:

[0120] In this example, see Figure 1-Figure 10 , when implementing the multi-energy microgrid distributed dispatching method based on potential game, the decision-making model of the electric energy subnetwork is: Considering that the dispatching period is T hours, the goal of the economical dispatching model of the electric energy subnetwork is to minimize the daily operating economic cost of the microgrid, These include: fuel consumption costs, equipment operation and maintenance costs, transaction costs with large power grids, compensation for user participation in demand response, photovoltaic power generation compensation, environmental costs, and interaction costs with natural gas sub-networks; the decision variable is diesel generators at each time period The output size of the energy storage device, the amount of charge and discharge of the energy storage de...

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Abstract

The invention relates to a multi-energy microgrid distributed scheduling method based on a potential game, which can give consideration to the benefits of different energy operators, can improve the decision autonomy of the energy operators, and can model the scheduling problem of a multi-energy microgrid system with electric energy, gas energy, G2P, P2G, energy storage and other devices into a game problem among subnets. A multi-energy microgrid scheduling model based on a potential game is established, and a potential function is constructed; and according to the method, the autonomy and economy of each subnet in the multi-energy microgrid are effectively improved, the method better conforms to the actual situation, and the introduction of G2P and P2G in the model can effectively improvethe overall economy of the system. The invention aims to solve the problems of information complexity and asymmetry existing in multi-energy microgrid scheduling, realize the autonomy of decision making of each energy subnet operator, and provide a solution for a manager of the multi-energy microgrid to search for an optimal strategy of multi-energy distributed scheduling.

Description

technical field [0001] The present invention relates to a distributed scheduling method for a multi-energy micro-grid, in particular to using a distributed algorithm based on potential game and IAPSO (Improved Agent-based Particle Swarm Optimization) to solve the problem of information asymmetry in multi-energy micro-grid scheduling, and to realize The autonomy of the decision-making of each energy sub-network operator protects the information security of each decision-making subject, which belongs to the multi-disciplinary interdisciplinary field of integrated energy systems, game theory, and intelligent algorithms. Background technique [0002] With the rapid development of technologies such as wind power generation and photovoltaic power generation, the utilization of distributed new energy has attracted increasing attention. As a bridge between distributed power supply and large power grid, microgrid is a kind of effective integration of distributed power supply (micro p...

Claims

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Application Information

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IPC IPC(8): H02J3/46H02J3/38H02J3/32G06Q50/06G06Q10/06G06N3/12
CPCH02J3/466H02J3/381H02J3/32G06Q10/067G06Q50/06G06N3/126H02J2203/20H02J2300/40Y04S10/50Y02E40/70
Inventor 邵崇张少华樊豆
Owner SHANGHAI UNIV
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