Скачать или смотреть GRAPH THEORY BASED CONSENSUS PROTOCOL-FREQUENCY CONTROL METHOD-ROBUST DISTRIBUTED ECONOMIC DISPATCH

DESIGN DETAILS
Economic dispatch is one of the most important problems in power systems. The solution of the economic dispatch (ED) ensures the power system to be operated under the most economical condition. This design is based on consensus-based control scheme for distributed power systems to solve the distributed economic dispatch (DED) problem. With the development of renewable energy, smart grid and microgrid, more and more distributed generators (DGs) will be connected to power systems. Thus, the distributed control schemes become more and more important for power systems to control and manage the distributed equipment. Existing consensus-based methods does not to solve the DED problem since the main challenge to apply the consensus-based method is to meet the power balance constraint without the centralized facility, since the value of power mismatch is hard to be obtained for a distributed control system. This Matlab design is mainly focused to solve the problem, which is based on the method to combine the frequency control methods with the consensus protocol from graph theory to develop the DED control method, so that the real power between the load and the generation can be balanced during the economic dispatch. With this method, a totally distributed optimal control scheme is obtained. The robust DED control method is to improve the robustness of this distributed control method, allowing the system to stay at the optimal dispatching even if the communication is failed. In addition, the model of transmission line losses is incorporated in the DED problem to reduce the line losses. Using Matlab simulation, a 10-generator 39-bus system is used to verify the robust DED control method.

REFERENCES
Reference Paper-1: Consensus-Based Distributed Economic Dispatch Control Method in Power Systems
Author’s Name: Qiao Li, David Wenzhong Gao, Huaguang Zhang, Ziping Wu and Fei-Yue Wang
Source: IEEE
Year: 2017

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