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.
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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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