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Modelling Flexible Resources in Smart Distribution Grid

Modelling Flexible Resources in Smart Distribution Grid

Published 27 April 2016

The development of Smart grids solutions is gaining momentum all over the world, supporting the vision of a sustainable and reliable future energy system. New regulations and directives for security of supply, sustainability and market efficiency, combined with EU's 20-20-20 targets, have increased the integration of renewable energy sources (RES) in the electricity system and measures for energy efficiency. Intermittent RES generation units will increase the need for flexibility in the grid.

A change in the electricity consumption is taking place. New customer segments, improved building standards and new electrical appliances such as electrical vehicles (EV), large heat pumps and instantaneous water heaters (without storage capacity) affect the electricity consumption pattern. Additionally, an increase in distributed generation (DG) and "prosumers" (customers that both produce and consume electricity) is expected. The trend is towards reduced electric energy consumption, increased peak load and reduced utilization time of the grid - compared to today's situation.

Flexibility from active customers with consumption, production and storage, will be valuable for the grid, to keep stable operation and support security of supply. With increased peak load, and reduced utilization time, the peak load occurs in a limited number of hours during the year. In these peak load hours, the flexibility and demand response can be a realistic alternative compared to traditional grid investments.

This project will develop dynamic models representing the consumption and production profiles for different flexible resources in the smart distribution grid, and address how such resources can be utilized to increase the flexibility in the grid - without introducing new peak load hours due to the rebound effect. Such models can improve today's software for grid planning, which often are evaluating loads as passive.

Research Scientist

Project duration

2016 - 2019