Smart Prices for the Smart Grid Master Thesis

The ongoing transition from the traditional electrical grid to the digitally interconnected smart grid and the increasing deregulation of electricity markets, allow to envision new types of distributed local energy markets. In order to develop such markets, it is important that energy producers and consumers can access a local energy price. In this project, we define an agent-based real-time local energy pricingmodel for the electrical grid, based on supply and demand. We describe how such a model can be computed, by solving a minimum-cost flow problem. We derive theoretical bounds and perform simulations, that show the low-sensitivity of our solution approach. We develop realistic trading-strategies for the network-agents and use them, to perform experiments that validate its dynamic stability. Finally, we present the implementation of a working prototype, analyze its performance, to locate possible bottlenecks, and propose solutions, to remove them.