Analysis of Demand-Response Participation Strategies for Congestion Management in an Island Distribution Network

Abstract: The Master Thesis is part of the Smart Grid Gotlandproject. This project aims at implementing smart grid solutionson the island of Gotland in order to be able to efficientlyintegrate large quantities of renewable energy production.In situations of high wind power production and lowconsumption, energy export problems may occur betweenGotland and the mainland. A novel approach to manageanticipated congestions, compared to traditional gridreinforcements, consists of using flexibility from demandresponse(DR) resources. However, such an approach presentschallenges as it requires both technical and economic considerations.This Master Thesis proposes and analyses twomarket-based strategies applied to detached houses for dayaheadcongestion management. The strategies are implementedin an Ancillary Service toolbox developed in theMATLAB programming environment.The first strategy involves using a dynamic network tariffwhile the second uses spot price optimization. Simulationsare performed for seasonal worst-case congestion scenarioswhile satisfying comfort and economic constraints ofthe DR participants. A sensitivity analysis is carried out toassess the impact of different spot price profiles and windpower production prognosis errors on the results.Results show that congestions are managed with a feasiblenumber of participants, but that their savings are negligiblefor both strategies (between 2 and 40 SEK/participant).Moreover, using a dynamic network tariff strategy impliesa DSO cost in the range of 1700-89000 SEK. These resultsapply for a 3-days congestion period, which is estimated tooccur 5-6 times a year if the maximum hosting capacity isincreased by 5 MW.To conclude, an AS toolbox with economic constraintsis feasible for Gotland conditions with a reasonable numberof DR participants. However, the simple cost-benefitanalysis that was carried out showed that the AS toolboxapproach was still much more costly than traditional gridreinforcement.