Thesis Topics on Smart GridsA smart grid is a modernized electrical grid that uses analog or digital information and communications technology to gather and act on information in an automated fashion to improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity.
One the main problems in Smart Grids is balancing energy production and consumption. In 20th century, the production of electricity was concentrated in a group of large power stations (mainly coal, nuclear or water) and these sources were designed to be able to control their output according to demands. However in recent years, the production from renewable energy sources (especially solar and wind) have been significantly increasing. These sources cannot be easily controlled and furthermore, their future output is hard to estimate. Therefore, devices and batteries are being developed to be able to plan their consumption according to the availability of the electricity network. Efficient usage of these devices requires advanced algorithms that can estimate production and consumption of energy, schedule each devices according to their possibilities and dynamically react on every event in real time.
Smart Grids offer various topics for thesis assignments for master students. First, different fields of Theoretical Computer Science can be applied. Then, many models can studied. Furthermore, thesis can be theoretical, experimental or a combination of both.
Applied fieldIn order to improve efficiency of electricity networks, various tools from Theoretical Computer Science can be applied. The typical tools follows and other can be discuss individually.
OptimizationA typical approach to improve the usage of energy in scientific publications is creating a global optimization problem describing all feasible states of all devices. Such an optimization problem can be linear, integer, convex or non-convex. Appropriate algorithms are used for solving these problems, e.g. simplex method, branch and bound, gradient methods, evolutionary algorithms and genetic algorithms.
Data predictionSolutions of global optimization problems gives a scheduling of all devices for several hours ahead. However, the optimization problems require some estimations of the usage of each devices. These prediction can be obtained using some statistical methods, neural networks, etc.
On-line and real-time algorithmsDetermining exact predictions is impossible in practice, so planning obtained from optimization problems may become inappropriate when an expected event occurs. One may try to adopt the planning to fulfill new situation. Another approach is developing on-line or real-time algorithms.
Models and problemsStudents can create their own problems or use one of the following scenarios. Students can attend competitions described below if they are interested but it is not obligatory.
Grid optimizationThe Grid Optimization Competition is a series of challenges to develop software management solutions for a resilient and secure American electricity grid. The site offers detailed description, testing datasets and scripts verifying correctness of a solution. The problem requires knowledge from physics and may be too complex for younger students, so the task may be simplified.