Abstract
The cooperative, reliable and responsive characteristics make smart grid more popular than traditional power grid. However, with the extensive employment of smart grid concepts, the traditional centralized control methods expose a lot of shortcomings, such as communication congestion, computing complexity in central management systems, and so on. The distributed control method with flexible characteristics can meet the timeliness and effectiveness of information management in smart grid and ensure the information collection timely and the power dispatch economically. This article presents a decentralized approach based on multi agent system (MAS) for solving data collection and economic dispatch problem of smart grid. First, considering the generators and loads are distributed on many nodes in the space, a flooding-based consensus algorithm is proposed to achieve generator and load information for each agent. Then, a suitable distributed algorithm called λ-consensus is used for solving the economic dispatch problem, eventually, all generators can automatically minimize the total cost in a collective sense. Simulation results in standard test cases are presented to demonstrate the effectiveness of the proposed control strategy.
Highlights
MotivationPower is carried from a few central generators (e.g., thermal power plant, hydroelectric station, etc.) to a large number of users, and traditional power grid concentrates on the electricity generation, transmission, distribution and control [1,2]
Power is carried from a few central generators to a large number of users, and traditional power grid concentrates on the electricity generation, transmission, distribution and control [1,2]
Most of conventional the value of parameter, λ∗, is determined, the values of PGi approaches to gain the values of λ are centralized methods, such a Lambda-iteration [45] and gradient methods, where the total demand or total losses as global information must be known to the centralized computing center
Summary
Power is carried from a few central generators (e.g., thermal power plant, hydroelectric station, etc.) to a large number of users, and traditional power grid concentrates on the electricity generation, transmission, distribution and control [1,2]. The demand for electricity is diversified, and the traditional power grid is inadequate to overcome modern day challenges. The data communication network infrastructures [3] include wide area measurement systems (WAMSs), sensor and actuator networks (SANETs), home area networks (HANs), neighborhood area network (NANs), and wide area networks (WANs). As an alternative to traditional power grid, SG can relieve the burden caused by various energy demands. The increasing electricity demand, together with the complex and nonlinear nature of the electric power distribution network, have caused many challenges for the future grid, for example, serious network communication issues [11,12], and it is expensive and unreliable to solve economic dispatch problem (EDP) using traditional centralized methods. SG, with distributed energy sources accessing, require distributed approaches to deal with its energy management problems
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