GreenNet: Agent based Game-Theoretic Domestic Cost Optimization Techniques for Smart Grid

Due to continuous increase of population, this century the old system unfortunately suffers from many problems i-e limited production of electricity, while demand is going to be higher side on daily bases. To resolve this and similar other problems a quantum leap is required to connect communication via information technology. This dive towards a new efficient technology is called Smart Grid. The central vision of smart grid is the development of smart appliances that will allow autonomous software agents, working as consumers to optimize the use of smart devices while interacting with agents at grid. Overall electricity consumption increased, resulted to increase the amount of electricity bills. Then we need efficient electricity consumption management techniques having minimum user interaction. This paper will discuss different existing methodologies used for energy optimization in smart grid and also portrays how consumer agents can reduce their electricity bills by utilizing incentives from energy suppliers. Different load prediction and game theoretic methodologies for energy management system are also discussed; at the end a novel smart home framework is proposed, which can automate the smart home by considering the energy optimization techniques. The stated system will not only reduce the co 2 emission, which is a main cause of global warming, but also reduced the cost of energy consumption for end users. [Ayesha Afzaal and Mohsin Nazir. GreenNet: Agent based Game-Theoretic Domestic Cost Optimization Techniques for Smart Grid. Life Sci J 2014;11(7s):61-67] (ISSN:1097-8135). http://www.lifesciencesite.com. 10