Study On The Distributed Cooperative Control Methods For Energy Internet

Energy Internet is composed of many energy local area networks. The centralized control method can quickly achieve voltage and frequency stability in energy LAN. However, due to the high demand of the amount, distribution and reliability among multiple LANs, it's nearly impossible for the centralized control method to meet all the requirements, thus the distributed cooperative control methods need to be introduced. This paper is focused on solving the power balancing and optimal allocation problem among the LANs by adopting the distributed cooperative control methods, and a distributed cooperative control system scheme based on JADE for Energy Internet is proposed.First of all, the power balancing problem among LANs is solved based on multi-agent coordination. This paper presents an adaptive distributed corporation method based on the recruitment of distributed collaborative algorithm for the power balancing among LANs. Meanwhile, an agent including three basis states and a MAS cooperative scheme are designed. This improved distributed cooperative control method for adaptive power balancing is adopted in Stateflow to simulate the distributed interaction among multiple LANs based on finite state machine method.Then, the optimal power allocation problem is tackled based on multi-agent collaboration. With the traditional control algorithms based on incremental cost consensus being the foundation, a gossip spread mechanism is introduced to boost the performance of the improved method in distribution and reliability.Finally, due to the high demand on the distributed cooperative control of Energy Internet, a distributed cooperative control system framework for Energy Internet is proposed based on JADE since JADE has outstanding performance on distributed control. The design flow, functional components, communication structure and corporation process for the distributed cooperative control system for Energy Internet are all discussed in this paper. Moreover, the agent interaction process for power balancing and optimal power allocation is discussed in detail.