چكيده به لاتين
The smart grid is known as the next generation of power systems. The goal of the smart grid is to eliminate the challenges of power systems such as increasing demand for electricity, the old infrastructure of the grid and reducing greenhouse gas emissions caused by the generation of electricity in the environment. The current electricity grid has a hierarchical structure where large power plants (including coal / natural gas, nuclear, and hydroelectric power plants) are at the highest level and consumers are at the lowest level of the structure. In this structure, the networks are generally in the form of one-way distribution lines that deliver all supplied electricity to subscribers. In this structure, there is no bidirectional path for power flow and simultaneous exchange of information and decision-making at the national level of the grid.
Smart grid energy market also has distributed and distributed producers as well as distributed consumers, where the energy exchange between these dispersed producers and consumers is a kind of energy deal that requires an agreement on price and quality and other factors affecting the transaction. In this thesis, we have proposed a method based on the negotiation of the factors for this energy market, and also the proposed protocol for the cloud architecture of the smart grid is also used to allocate cloud resources to intelligent network components. This method, with the help of multi-agent systems, simplifies the management of the smart grid market and facilitates the determination of electricity prices and the transfer of energy between producers and consumers in the smart grid using the auctioning strategies. The results of the implementation of the proposed method show that the use of this method can improve the overall benefit of the entire system. This method is negotiated by the buyer agent and seller agent, along with the negotiation of a non-alignment fine. An automated negotiation process between agents in uncertain and complex environments where the agents do not have complete information about the environment and have a large state of space can perform well. One of the important points in this method is the autonomy of the agents, without the need for the supervisor and the agents to negotiate to increase their profits, which ultimately leads to a contract or fails.
