The overarching goal of this tutorial is to present the emerging optimization problems and formulations within the smart microgrid research area from the communications, security and privacy perspectives. We provide optimization formulations for various problems in microgrid scheduling, communications and control, including optimization of deployment, power consumption, and integration of distributed energy sources with a particular attention given to the security and privacy dimensions and aspects.
The conception of the Smart Grid (SG) paradigm is to offer many benefits to the transmission, distribution, and consumption of energy . One catalyzer ingredient of the SG repertoire of changes is the idea of microgrids. As an integrated energy system network for the low-voltage distribution subsystem consisting of distributed energy resources (DER) and multiple electrical loads and/or meters operating as a single, autonomous grid either in parallel to or islanded from the existing utility power grid, microgrids are expected to improve reliability, help integrate distributed resources, isolate power disturbances, and ameliorate load and supply balance [2, 3]. In this tutorial, we initially provide an overview of the Smart Grid of the future, its communications infrastructure and the research problems it has spawned, especially from the networking topics perspective. On top of the foundational coverage of the Smart Grid, we delve into optimization issues of one of the underlying enabling technologies, commonly referred to as microgrids .
In order to utilize the microgrid functionalities efficiently and get the maximum benefit from such a structure, it is crucial to manage the distributed generation and consumption within the microgrid via a control center, which is referred to as a Microgrid Control Center (MGCC). Automatic Meter Reading (AMR) and Automatic Metering Infrastructure (AMI) systems are smart metering technologies which are key for linking MGCC to homes and appliances in the grid. Our system assumes the existence of a smarter grid consisting of microgrids equipped with AMI systems, smarter appliances, renewable resources and stored energy. A model to allocate the available resources among the loads in accordance with various Quality-of-Service (QoS) requirements, as determined by prioritization weight and minimum required total energy, and different time and power transference or shift-ability profiles within an islanded microgrid will be presented.
Any optimization problem consists of an objective function and constraints. The level of detail and usefulness of the model, in general, are working in opposite directions. We do not want to include too much detail which result in large numbers of variables and constraints, therefore, make the model computationally too heavy to be solved, especially, for large scale problems. Therefore, the key in building an optimization model for microgrid is choosing the important mechanisms and variables to be used in the model instead of putting every detail into the model. In other words, efficient abstractions are the vital elements of realistic modeling of microgrid as an optimization model that scales up to sufficiently large dimensions. We will present efficient modeling techniques and approaches for microgrid, Mixed Integer Programming (MIP) models to maximize weighted energy utilization with the help of an energy consumption scheduler will be elaborated during the process. Algorithmic approaches based on heuristics and approximation techniques will also be provided for intractable problem formulations.
A detailed description of the tutorial, its contents and learning objectives are available in this PDF document (along with further references).
Assoc. Prof. Suleyman Uludag
Suleyman Uludag received his Ph.D. from DePaul University, Chicago in 2007. He is an associate professor of computer science at the University of Michigan - Flint. He has served in the TPC of many networking conferences, including ICC, Infocom, Globecom, LCN, WCNC, Broadnets, etc., and reviewer for many journals. The general areas of his research include network quality of service, routing in wireless and wired networks, microgrids, network security, smart grid, and automatic time-series models. He has co-chaired the IEEE LCN Workshop on Smart Grid Networking Infrastructure held in conjunction with IEEE LCN 2010 Conference in Denver, CO. He has been awarded the Lois Matz Rosen Junior Faculty Excellence in Teaching Award in September 2010 at the University of Michigan - Flint. He has also been a Fulbright Scholar (Core Program) at TOBB University of Economics and Technology in Ankara, Turkey during the 2012-2013 academic year. He was a visiting scholar at the TCIPG (Trustworthy Cyber Infrastructure for the Power Grid — a preeminent research center on power grid cybersecurity) at the University of Illinois at Urbana-Champaign and the MONET research group of Professor Klara Nahrstedt at UIUC from August of 2013 to August of 2014.
Assoc. Prof. Bulent Tavli
Bulent Tavli is currently an associate professor at the Electrical and Electronics Engineering Department, TOBB University of Economics and Technology, Ankara, Turkey. He received the BSc degree in Electrical and Electronics Engineering in 1996 from the Middle East Technical University, Ankara, Turkey. He received the MSc and PhD degrees in Electrical and Computer Engineering in 2001 and 2005 from the University of Rochester, Rochester, NY, USA. Telecommunications, mathematical programming, and embedded systems
are his current research areas.
are his current research areas.