Design challenges of smart meter-based applications

© 2017 Dr. Athauda Arachchige Bhagya AmarasekaraThe smart grid is an interconnected electricity network. It integrates the electricity grid with powerful control and communications networks that can dynamically respond to customer demands and energy supply scenarios with increased reliability. One of the key components of the smart grid is the smart meter, which is the main sensor in the electricity distribution grid. As of today, the introduction of the smart meter has transformed manual electricity billing system to an automated meter reading system. In the future, the capabilities of smart meters will not only be limited to meter-readings but are expected to facilitate outage detections and demand side management, allowing the grid to respond dynamically to both customer demands and energy market pricing signals. However, these smart meters based applications face many challenges in implementing them in the network including provisioning adequate resources for smart metering traffic to guarantee the required quality of service (QoS) level, maintaining scalability of applications that require complex computations, ensuring the security of the smart metering data, and providing a platform to identify the effect of communications networks on smart meter applications. This thesis investigates approaches to overcome the challenges in implementing smart meter based applications to achieve a reliable and cost-efficient electricity network. In particular, this thesis examines efficient solutions to overcome three key challenges: mechanisms to guarantee QoS levels when smart meters use public communications networks to transport their data, approaches to guarantee the scalable deployment of the complex smart meter based applications, and a platform to efficiently simulate smart grid networks along with its control and communication operations in order to assess smart grid applications. For the smart meter communications network, the public telecommunications network is considered as a cost-effective solution as it does not involve any separate installation or maintenance costs. However, when sharing network resources with both public traffic and smart metering traffic, required QoS levels of essential broadband services along with those of smart meters should be satisfied. To this end, this thesis explores resource allocation mechanisms in both core network and access networks on providing adequate services for all users in the shared network. In particular, this thesis proposes approaches to classify and schedule traffic in the core network, in addition to scheduling algorithms for long-term evolution (LTE) wireless access network when it shares its resources with smart meter traffic. Our simulation results indicate that the proposed scheduling mechanisms can significantly improve the QoS performance of the public traffic and smart grid traffic related to automatic meter reading and outage detection applications. Another key challenge faced by smart meter applications is to provide scalable deployment for the smart grid applications such as the demand side management (DSM). Though it is important to integrate a large number of energy customers to DSM to achieve desired cost-effective supply demand balance, limited computational resources such as memory hinder this integration. Therefore, this thesis explores efficient ways to accommodate a large number of customers into DSM by using aggregators that consolidate underlying customer’s energy, power, and cost requirements. We also present simplified methods to distribute the aggregated optimal decisions to the end customers and demonstrate the applicability of the proposed method, by using it in a large electricity network. The results reveal that the proposed aggregated method is better in providing scalability and also in achieving a higher satisfaction level among customers. Moreover, as the smart grid is an interconnected network comprising of both electricity and communications networks, smart grid applications would be affected by imperfect communications networks. Therefore, these applications should be evaluated based on their robustness to communications errors and their design should be improved considering those effects. Hence, in this thesis, we present the design of a co-simulation platform, which is capable of simulating smart grid applications with both electricity and communications networks. The feasibility of this proposed platform is analysed by using it to assess the real-time pricing (RTP) application, which is one of the important DSM application. Furthermore, by using this designed simulation platform, we explore the ways of utilising features of the public LTE communications networks for different RTP designs. Overall, our studies reported in this thesis, provide insight into deployment strategies that can be used to realise scalable smart meter based applications in cost-effective manner with guaranteed QoS and user satisfaction