Power Grid Capacity Extension with Conditional Loads Instead of Physical Expansions

Abstract

A dramatic increase in network capacity demand is to be expected in the future, especially at times of high production or consumption. This is due to the electrification of the global energy system and a shift towards distributed power production from sustainable sources. Energy management solutions have been proposed that help mitigate high costs of physical grid extension by utilizing existent grid capacities more efficiently. Yet, these solutions often interfere with customer processes and/or restrict free access to the energy market. The RLS “regional load shaping” approach proposes a market-based solution that resolves this dilemma for the mid voltage grid: the RLS business model gives incentives to all stakeholders to allocate so-called “conditional loads”, which are flexible loads that are not subjected to (n – 1) security of supply; the RLS load management solution then assigns these loads to cost-optimized time slots in the traditionally unused N – 1 capacity band. The paper provides a validation of the technical aspects of the RLS approach: an evaluation of the day-ahead load forecasting method for industry customers is given, as well as a validation of the load optimization heuristics based on simulated capacity bottlenecks. It is shown that the prediction model provides competitive results in terms of accuracy, and that RLS method handles all provoked critical network capacity situations as expected. Particularly, (n – 1) security of supply is retained at all times for “unconditional” loads.