Distributed Communication Architecture for Smart Grid Applications

One big challenge in building a smart grid arises from the fast growing amount of data and limited communication resources. The traditional centralized communication architecture does not scale well with the explosive increase of data and has a high probability of encountering communication bottlenecks due to long communication paths. To address this challenging issue, this article presents a distributed communication architecture that implements smart grid communications in an efficient and cost-effective way. This distributed architecture consists of multiple distributed operation centers, each of which is connected to several data concentrators serving one local area and only sends summary or required integrated information to a central operation center. Using this distributed architecture, communication distance is much shortened, and thus data will be delivered more efficiently and reliably. In addition, such a distributed architecture can manage and analyze data locally, rather than backhauling all raw data to the central operation center, leading to reduced cost and burden on communication resources. Advanced metering infrastructure is chosen as an example to demonstrate benefits of this architecture on improving communication performance. The distributed communication architecture is also readily applicable to other smart grid applications, for example, demand response management systems

Performance Evaluation of Communication Technologies and Network Structure for Smart Grid Applications

The design of an effective and reliable communication network supporting smart grid applications requires the selection of appropriate communication technologies and protocols. The objective of this study is to study and quantify the capabilities of an advanced metring infrastructure (AMI) to support the simultaneous operation of major smart grid functions. These include smart metring, price-induced controls, distribution automation, demand response, and electric vehicle charging/discharging applications in terms of throughput and latency. OPNET is used to simulate the performance of selected communication technologies and protocols. Research findings indicate that smart grid applications can operate simultaneously by piggybacking on an existing AMI infrastructure and still achieve their latency requirements

Investigation into the impact of wind power generation on demand side management (DSM) practices

The construction of a number of wind farms in South Africa will lay the foundation for the country to embrace the generation of greener energy into the National Grid. Despite the benefits derived from introducing wind power generation into the grid, this source encompasses adverse effects which need to be managed. These adverse effects include the intermittency and lack of predictability of wind. In power systems with a high penetration of wind energy, these effects can severely affect the power system’s security and reliability in the event of significant rapid ramp rates. Recently, many utilities around the world have been exploring the use of Demand Side Management (DSM) and Demand Response (DR) initiatives and programmes to support and manage the intermittency of wind power generation. This report outlines the programmes and benefits of DSM/DR and provides a critical analysis of the challenges facing South Africa with implementing these initiatives. Introducing these programmes necessitates the employment of a number of Smart Grid technologies including Advanced Metering Infrastructure (AMI), next generation telecommunications technologies, smart meters, enterprise system integration and dynamic pricing. These tools and techniques are discussed and their challenges described within the context of South Africa’s current state of the power system. The current practices for DSM/DR in South Africa have been evaluated in this report. Despite, the success of many DSM/DR initiatives in the commercial, industrial and agricultural sectors, it is found that much work is still required in the residential sectors as the current DSM initiatives are not adequate for managing wind power generation. A detailed analysis and recommendations for South Africa’s DR program is then presented based on industry best practices and experiences from other utilities who are currently exploring DSM/DR in the residential sector using Smart Grid technologies

Performance evaluation of information and communications technology infrastructure for smart distribution network applications

This thesis was submitted for the degree of Master of Philosophy and awarded by Brunel University.Current electrical networks require secure, scalable and cost-effective Information and Communications Technology (ICT) solutions to facilitate the novel functionalities required by Smart Grids. Countries around the globe are investigating alternative energy sources to mitigate the current energy crisis and environmental issues experienced by many countries due to global warming, rapid growth of population, inefficient energy management, dwindling fossil fuel resources, etc. Therefore, alternative or renewable energy sources, such as wind, solar, hydro, combined heat and power, etc., are required to mitigate such a crisis and such sources will also need to be integrated in to the power grid in a distributed manner. Such distributed energy sources are mainly connected to the distribution networks and introduce huge challenges to the distribution network operator (DNO). Many of these challenges cannot be dealt with effectively using existing network operation mechanisms therefore the research and development of novel ICT solutions to support smart distribution network operation is required. This research investigated suitable ICT solutions to enable the Smart Grid to tackle these challenges and proposes ICT infrastructure models that can be used for simulation studies in order to investigate cost-effective, scalable and secure solutions for the DNOs. Initially, a Quality of Service (QoS) monitoring test-bed was proposed to evaluate the performance of bandwidth intensive applications, such as smart meter data transmission. Simulation studies for different communication technologies, cellular and Power Line Communication (PLC), were also carried out and the simulation models were verified using experimental test results. Finally, the modelling and analysis of smart metering infrastructure was carried out using simulation and extensive studies were performed to evaluate the data transmission rate performance for different configurations of smart meters and concentrators