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Power Grids

Introduction​

The utility industry is undergoing a transformational period driven by technological and competitive forces, as well as changing customer expectations and growing regulatory constraints. As these forces accelerate, electric power distributors must tap new technologies to expand opportunities to improve operational efficiencies, reduce costs and maximize customer satisfaction.

Similar to its impact on other major industries, advanced analytics have the potential to unlock novel groundbreaking opportunities in the power grid sector. As power grid technologies evolve in conjunction with measurement and communication technologies, this results in an unprecedented amount of heterogeneous and deeply interconnected data from diverse sources. The effective combination and utilization of this electrical data with external data sources (e.g. weather), has the potential to revolutionize electrical grid operations by enhancing observability of system-wide conditions, the behavior of end-users, and energy availability.

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Applying graphs​

Minimum spanning tree designed for power grids​

In the case of a network failure, a smart grid should be able to automatically reconfigure itself and continue energy distribution without additional disruptions. The generation of minimum spanning trees could overcome potential points of failure by enabling smart grids to heal themselves and propose new configurations within the network. While such an algorithm would require significant resources, Memgraph, with its in-memory implementation, ensures real-time computation.

Finding shortest paths​

This type of network analysis is crucial to infrastructure managers. It helps uncover vulnerabilities and bottlenecks, model the impact incidents and outages may have on the network, and carry out critical contingency planning. By examining the power grid as a graph, this task is transformed into a simple graph problem which can be tackled in a myriad of ways.

Handling failures in power grids​

Because of their size and locations, power grids are prone to multiple failures throughout the year. Individual elements can experience technical problems due to their age or weather effects which means that the grid needs to have certain redundancies in place.

By examining the grid through a graph, we can simulate the behavior in case of a critical failure. The graph should provide enough information to predict potential shortcomings. We can also simulate new elements such as transformers or high voltage transmission lines to find the most appropriate locations.

Where to next?​

This text is a summary of one area that fits perfectly with the application of graphs. Therefore, we would like to have you with us when implementing some of these solutions. Share opinions, experiences and problems you encounter when working with Memgraph on our Discord server. We are here for you and we will help you along the way.