Stavrogiannis, Lampros C.
Electricity Tariff Design and Implementation for the Smart Grid.
University of Southampton, Electronics and Computer Science Department,
The electric power system is one of the largest complex adaptive systems, yet its centralized electromechanical operation remains unaltered since its invention in the last century. This model used to be adequate for the previous decades. However, energy demand continuously increases and we will soon be unable to satisfy it with current technology. Additionally, there is a need for reduction in CO2 emissions. More specifically, in the U.K., the 2008 Climate Change Act mandates an 80% CO2 emission reduction by 2050. These facts will inevitably lead to the mainstream usage of renewable energy systems during the following years. Moreover, today's power system lacks transparency as customers have no way of monitoring and controlling their energy usage besides reading their monthly bills, communication is one-way, and there is no real supervision of the distribution system. All these factors led researchers to the quest for a new power system model, which was named the Smart Grid. This model is influenced by the World Wide Web, operating in a decentralized manner, with many producers and consumers of various generation capabilities and consumption patterns. Consumers are able to obtain real-time information on their energy and carbon footprints with the use of smart-metering devices but, most important, are capable of responding appropriately to signals they receive from the Grid. Along with the technical issues, a transformation of current business models is essential. Although electricity market deregulation has decreased wholesale prices, this change has not been perceived by final customers. This is due to the fact that most of electricity trading is performed through long-term contracts between generators and suppliers via risk management instruments so that customers can pay fixed prices no matter what is the true cost of delivery on behalf of the utilities. In this project we have made an effort to study customer bill savings for a variety of electricity tariffs on real data from a U.K. neighbourhood. New types of tariffs that have been previously applied to large industrial and commercial clients have been tested on a population of residential customer agents. To our knowledge, this is the first time that an agent-based simulation for this type of tariffs has been performed in the U.K. based on a realistic wholesale market setting. Our results show that both customers and suppliers could benefit from real-time pricing rates in terms of profit attained as well as corresponding risk.
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