Modelling of residential side flexibility for distribution network planning

With the environmental impacts of the fossil fuel economy being more and more visible it became oblivious that action against further climate change needs to be taken. This led to theenergy transition effort undertaken by countries of the European Union with the goal of increased usage of sustainable energy at the costofnon-renewable fuel sources. And on the national level,it led to more regionalized targets.With this in mind, the Netherlands adopted several goals with a target of reducing dependence on fossil fuels. These ranged from a bigger percentage of renewable energy in energy supply, through electrification of heating, to widespread adoption of electric vehicles. All of theseintroduce changes to how the energy system is operated. And this is particularly visible forelectricitydistribution system operators. These new developmentscouldmeanthatthegrid assets that were previously assumed to be functioning for the next decades would be retired earlier than expected. However, progressin areas of flexibility in electrical energy consumption present opportunityfor deferred replacement of those otherwise prematurely retired assets.In this context, the main objective of this thesis was to assess the benefit thatactivation of electrical energy flexibility in households could bring to thedistribution system operator. Between two energy transition scenarios consideredand different simulation settings,it was discovered that from 3.3 to 35.4% cumulative investments into grid assets could be deferred in next 8 to 10 years into the future,for considered networks. This corresponds tobetween1.1 and16.7 million € for examined networks,whichcontained about 5% of assets(transformers,medium and low voltage cables)belonging tothe Dutchdistribution system operator Enexis. However, in order to arrive at these values,the followingsteps had to be taken.Firstly, possible methods used to activate flexibility were researchedand compared. These included tariff-and market-based solutions, connection agreements and direct control approach. Based on the review of current literature and pilot projects it was decided that power-based tariffs werethe most aligned with the goal of reducing the impact onto the DSO’s grid assetswithpresented requirements.This decision was taken dueto the cost-reflectiveness of network asset usagepresented by power-based tariffs. It was further reinforced by the factthe main criterion considered during asset sizingis expected loadingsince in medium and low voltage networks peak power corresponds to the majority of costs. Beside technical effectiveness,the power-based tariffwas found to promiseopportunity in other aspects. Thosewere social acceptance, influenced by customers alreadybeingaccustomed to the tariff system,the readinessof technology behind this approachand compliance with the legislative framework.Secondly, based on the outcome of the previous step it was decided to model the impact of the power-based tariff onto the grid assets. In order to analyse the impact of the potential solutiononto the real grid assets, the modelwas incorporatedinto the Enexis’ Scenariotool -bottom-up scenario analysis tool developed for short to medium-term network planning purposes. This decision posed a strict requirement onto a high computational performance in order to allow examination at network scale withinthe feasible timescale. The proposed model focused onsimulating the possible impact of the power-based tariff on the residential load profiles with a focus on electric vehicle charging and photovoltaic panel generation. Thirdly, model results were examined from the single household level up to multiple low voltage networks and connecting medium voltage network fragments. Examinationsat the network level were run for multiple sets of possible scenarios. Then based on the comparison with the baseline scenario, ones without activation of flexibility, assets for which deferred replacement is possible were identified. These deferral possibilities were later translated into the monetary values of cumulativesavingsup to a given year of simulation, resulting in the figures presented in the beginning.In conclusion,this project identified optimalmethod, from the viewpointof DSO,for activation of flexibility from the households, presented model that modifies residential loads according to this method and performed an economic evaluation of the tariff’s impact onto the part of DSO’s grid