Impulsive control for synchronizing delayed discrete complex networks with switching topology
- Authors: Li, Chaojie , Gao, David , Liu, Chao , Chen, Guo
- Date: 2014
- Type: Text , Journal article
- Relation: Neural Computing and Applications Vol. 24, no. 1 (2014), p. 59-68
- Full Text: false
- Reviewed:
- Description: In this paper, global exponential synchronization of a class of discrete delayed complex networks with switching topology has been investigated by using Lyapunov-Ruzimiki method. The impulsive scheme is designed to work at the time instant of switching occurrence. A time-varying delay-dependent criterion for impulsive synchronization is given to ensure the delayed discrete complex networks switching topology tending to a synchronous state. Furthermore, a numerical simulation is given to illustrate the effectiveness of main results © 2013 The Author(s).
An efficient algorithm for optimal real-time pricing strategy in smart grid
- Authors: Zhang, Wang , Chen, Guo , Dong, Zhaoyang , Li, Jueyou
- Date: 2014
- Type: Text , Conference paper
- Relation: Power & Energy Society General Meeting/Conference & Exposition, 2014 IEEE; National Harbor, MD, USA; 27th-31st July 2014 p. 1-5
- Full Text: false
- Reviewed:
- Description: Abstract— the new dynamic pricing schemes encourage the consumers to participate more actively in the electricity energy market, and the smart meter and demand side management (DSM) make it possible. In this paper, we consider a smart grid environment with multiple users equipped with smart meters and energy management devices (EMD). An improved optimization method is proposed to maximize the social welfare of both users and the provider under a real-time pricing strategy. More specifically, we proposed a more practical and advanced gradient algorithm – fast distributed dual gradient algorithm (FDDGA). Compared with traditional distributed dual sub- gradient algorithm, this improved method does not only accelerate the convergence rate but also overcome the possible oscillation that caused by the uncertainty in choosing step size over iteration process in sub-gradient projection method. The simulation results also validate that the proposed algorithm is effective and efficient in solving the real time pricing problem for demand response.
A dynamic game behavior : Demand side management based on utility maximization with renewable energy and storage integration
- Authors: Zhang, Wang , Chen, Guo , Su, Yu , Dong, Zhaoyang , Li, Jeuyou
- Date: 2014
- Type: Text , Conference paper
- Relation: 24th Australasian Universities Power Engineering Conference, AUPEC 2014; Curtin University, Perth, Australia; 28th September-1st October 2014
- Full Text: false
- Reviewed:
- Description: In the smart grid environment, customers are offered to participate more actively in the electricity energy market with the promise of demand side management (DSM) with distributed energy resources and energy storage. By utilizing proper incentive scheme such as dynamic pricing, numerous objectives could be achieved so that it could benefit both the utility companies and consumers. In this paper, a smart grid environment with multiple users with renewable energy and energy storage devices equipped with smart meters and energy management devices (EMD) is considered. We present a fast distributed algorithm for demand-side management based on the social welfare maximization problem under the dynamic pricing scheme. We also introduced the dynamic game to illustrate the interaction between the utility company and its subscribers, which eventually leads to an equilibrium point. The simulation result validates that the proposed demand side management framework with real time pricing has an effective impact on reducing the peak demand as well as utilizing the renewable energy resources and energy storage devices. © 2014 ACPE.