Load Shaping Strategy Based on Energy Storage and Dynamic Pricing in Smart Grid

Jiang, Tao; Cao, Yang; Yu, Liang; Wang, Zhiqiang

doi:10.1109/tsg.2014.2320261

Cited by 72 publications

(40 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Optimization of the network smart grid system implies that, in the transient process to reach the equilibrium, some indexes can be optimized. The grid provider is capable of influencing decisions of users in the network by presenting dynamic pricing strategies (Liang et al, 2013;Jiang et al, 2014). It is possible that the smart grid provider and some of the users cooperate to affect decisions of other users, such that the common benefit can be improved.…”

Section: Introductionmentioning

confidence: 99%

Evolutionary game theoretic demand-side management and control for a class of networked smart grid

Zhu

Xia

2016

Automatica

View full text Add to dashboard Cite

In this paper, a new demand-side management problem of networked smart grid is formulated and solved based on evolutionary game theory. The objective is to minimize the overall cost of the smart grid, where individual communities can switch between grid power and local power according to strategies of their neighbors. The distinctive feature of the proposed formulation is that, a small portion of the communities are cooperative, while others pursue their own benefits. This formulation can be categorized as control networked evolutionary game, which can be solved systematically by using semi-tensor product. A new binary optimal control algorithm is applied to optimize transient performances of the networked evolutionary game.

show abstract

Section: Introductionmentioning

confidence: 99%

Evolutionary game theoretic demand-side management and control for a class of networked smart grid

Zhu

Xia

2016

Automatica

View full text Add to dashboard Cite

show abstract

“…36 Storage units can contribute to load shaping, too. 37 The consumer can draw less electricity from the grid by discharging energy when the demand is higher than the quota and more electricity from the grid at a lower price by storing energy when the demand is lower than the quota. As a result, the utility can implement load shaping, and consumers can save energy cost.…”

Section: Demand Side Managementmentioning

confidence: 99%

A review on the features and technologies for energy efficiency of smart grid

Anjana¹,

Shaji

2017

Int J Energy Res

View full text Add to dashboard Cite

Summary In today's world striving for efficiency in every sector, especially power generation and distribution, smart grids emerge as the solution for efficiently meeting the increasing demand. They adjust themselves to optimally deliver energy at the lowest cost and highest quality possible. The grid successfully makes use of renewable energy resources, electric vehicles, and smart pricing techniques in its attempt to achieve energy efficiency. It also promotes a greener environment by striving to reduce greenhouse gas emissions. Information communication technology (ICT) helps the grid in collecting consumption data from the consumers and in sharing tariff information. ICT also helps to gather information about the status of the grid with regard to aspects like power quality, faults etc. The purpose of this paper is to review recent literature with a view to comprehensively present the technologies employed in the smart grid for achieving energy efficiency and the challenges involved therein.

show abstract

“…2) Static M2M Systems Energy M2M System: Energy M2M system is a representative static M2M system, which is an important component in the smart grid [26]. By integrating communication capabilities with electric power generation, delivery and distribution infrastructures, energy M2M system can achieve automatic monitoring and control.…”

Section: M2m Systemsmentioning

confidence: 99%

A Survey of Emerging M2M Systems: Context, Task, and Objective

Cao

Jiang

Han

2016

IEEE Internet Things J.

Self Cite

View full text Add to dashboard Cite

Machine-to-machine (M2M) systems enable machines or devices to collect data, exchange information, and act on the environment without direct human intervention. A device in an M2M system not only collects data for its own usage, but also shares the data with other devices automatically to achieve certain goals. Therefore, emerging M2M systems for civil transportation, electric power grid, medical treatment, industrial automation and etc., can be set up based on the networking of devices. In this survey paper, we first introduce the general architecture and communication networks for M2M systems. Then, we categorize emerging M2M systems according to the types of M2M context, M2M task and M2M objective. We further survey recent solutions for M2M systems from both academia and industry with the insights of the M2M system categorization. Finally, we summarize challenges in developing M2M system solutions.Index Terms-M2M systems, M2M context, M2M task, M2M objective, categorization.

show abstract

Load Shaping Strategy Based on Energy Storage and Dynamic Pricing in Smart Grid

Cited by 72 publications

References 15 publications

Evolutionary game theoretic demand-side management and control for a class of networked smart grid

Evolutionary game theoretic demand-side management and control for a class of networked smart grid

A review on the features and technologies for energy efficiency of smart grid

A Survey of Emerging M2M Systems: Context, Task, and Objective

Contact Info

Product

Resources

About