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A feasible architectural framework for the smart grid in home areas is provided based on the latest NIST (National Institute of Standards and Technology, U.S.) smart grid interoperability standards (release 1.0). In this paper, we propose an accountable communication protocol using this architecture with certain reasonable assumptions. Analysis results indicate that our design makes all power loads...
Most residential-used electricity is nowadays generated at inefficient central power plants consuming environmental unfriendly resources like coal or natural gas. However, a trend towards distributed generation, distributed storage and demand side load management is seen to improve the energy efficiency. In order to analyze the impact and requirements of these emerging technologies and control methodologies,...
Electricity demand in developing countries is expected to rise significantly by the year 2020. Electricity consumers in both developed and developing countries are not active participants in the operations of electrical networks. Research has shown that significant benefits may be achieved when consumers participate in such electrical network operations. In these instances consumers were able to reduce...
Smart grid provides remarkable opportunities for residential energy management. Residential energy management covers a large number of devices and techniques, from basic components, such as energy saving light bulbs to more complex methods, such as coordinating the household load. With the use of smart meters, smart grid enables two-way communication between the utilities and their consumers, where...
Recently, resource monitoring systems to visualize energy consumptions such as electricity and gas for home users, are developed. In the home, user's daily behavior affects total amount of consumption energy significantly. Such monitoring systems aim at making a user conscious of energy-saving behavior. Most of conventional systems provide summarized data on consumed energy to a user. From the data,...
By combining a cluster of microCHP appliances, a virtual power plant can be formed. To use such a virtual power plant, a good heat demand prediction of individual households is needed since the heat demand determines the production capacity. In this paper we present the results of using neural networks techniques to predict the heat demand of individual households. This prediction is required to determine...
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