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Energy sharing in smart grids : a game theory approach

The need for energy conservation, grid reliability, and improved operational efficiencies have led to the changes from conventional electricity grids which have “blind” and manual operations, along with the electromechanical components, to interconnected and flexible “smart grids” that ensure a bidirectional flow of electricity and information between power plants and appliances, and all points in between. This transformation is necessary to meet environmental targets, to accommodate date a greater emphasis on demand response, and to support distributed generation and storage capabilities. 
The smart grid infrastructure can be divided into three main components: i) the smart energy system, ii) the smart information system, and iii) the smart communication system. In this dissertation, we start our study by investigating the energy efficiency in Wireless Sensor Networks (WSNs) as key communication enablers in the smart communication system component of the smart grid infrastructure. First of all, we explore how game theory has been used to achieve energy efficiency and maximize network lifetime. The literature is surveyed at different levels: i) Power Control and Medium Access Control (MAC), ii) Routing and Clustering, iii) Coverage and Topology Control, and iv) Data Aggregation, Security, Task Allocation and Energy Harvesting. Second of all, we investigate the energy efficiency in low-data rate Wireless Multimedia Sensor Networks (WMSNs) by studying the energy consumption of the MAC layer in this kind of networks and its application scenarios in smart grids. 
After that, we shift our attention to the smart energy system component of the smart grid infrastructure. We focus on maximizing the utilization of locally harvested renewable energy in the residential sector. In this regard, renewable energy sharing is proposed as a possible solution to tackle this problem. Two different energy sharing frameworks are proposed for microgrids, where game theory is used as an analytical tool. In the first one, the energy sharing between households is modeled as a repeated game. In this framework, households share their surplus renewable energy with each other directly in a distributed manner. In the second one, a reputation-based energy sharing framework for microgrids with a shared Energy Storage System (ESS) is proposed. In this framework, households share their surplus renewable energy by storing it in the shared storage unit, which manages their demand, and allocates the shared renewable energy among them based on their reputation, represented by the amount of energy they shared previously. We aim at investigating how game theory can increase the efficiency of energy sharing frameworks in smart grids by modeling households’ interactions and providing incentive mechanisms for cooperation. It is expected that this dissertation will fill a gap in the area of smart grids and raise the interest to further explore and develop this promising research area.