Decentralized trading and demand side response in inter-intelligent renewable energy network

We propose the use of a new decentralized autonomous smart grid model involving adaptive trading agents which can sell and buy electric power in a local electric power network. We name the electric power network einter-intelligent renewable energy network´, i-Rene. Trading agents in the local grid manage the amount of electric power generated by PV or other renewable energies stored in batteries in residences. The agents learn trading policies by maximizing their profits. Based on the proposed system, we evaluated its price formation and effectiveness of the adaptive trading method analytically. To model demand side management which can control the amount of electric power consumption, developing an elastic additional consumption model is essential. We added an elastic additional consumption model to the model. We also performed a simulation experiment with a hundred agents and additional noise term for load profiles.