Analysis of Demand Response Solutions for Congestion Management in Distribution Networks
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
According to the 20-20-20 targets set by the European Union, 50 percent of the Swedish electricity share is to be provided by renewable energy sources by 2020. The Smart Grid Gotland (SGG) project has emerged as a response to this target. The project aims at demonstrating a proof of concept on how smart grid solutions can be used to integrate large
quantities of renewable energy sources in an existing network. The outcomes of the project are intended to pave the way for future renewable energy integration projects in Sweden.
The Thesis focuses on one of the technical objectives of the SGG project, i.e. to increase the hosting capacity of wind power on Gotland from 195 MW to 200 MW by using Demand-Response (DR) from households and industries. DR consist of shifting peak-loads to peakproduction hours. The integration of additional wind power causes a risk of exceeding the transmission capacity of the power export cable between Gotland and the Swedish mainland.
The approach considered for this Thesis is to use an Ancillary Service (AS) toolbox scheme based on multi-agent systems. The AS toolbox consist of flexibility tools such as DR on long-term, short-term, a battery energy storage system and a wind curtailment scheme. The DR activity includes space heating and domestic hot water consumption from detached houses on Gotland.
The simulation results indicate that 1900 household participants are sufficient to balance the additional 5 MW for worst case scenarios. Furthermore, it is shown that the DR participation from industries contributes in some cases to a reduction of 700 household participants.
The findings helped conclude that using an AS toolbox solution on Gotland is fully possible from a technical perspective. However, barriers that stand against its realisation are of economical nature and need to be investigated in future studies.
Place, publisher, year, edition, pages
2013. , 93 p.
EES Examensarbete / Master Thesis, XR-EE-ICS 2013:014
smart grid, demand side management, demand response, load shift, wind power integration, distribution network, stationary battery
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:kth:diva-138575OAI: oai:DiVA.org:kth-138575DiVA: diva2:681429
Master of Science in Engineering - Electrical Engineering
Nordström, Lars, Professor