Within the Netherlands, house owners set up projects in which all houses within a neighbourhood are collectively renovated and equipped with distributed energy resources (DERs) at the same time. These projects are called ‘neighbourhood distributed energy resource projects’ (NDPs). As some of the equipped DERs electrify much of the heating previously generated by natural gas, and other equipped DERs produce electricity themselves, the electricity grid experiences a rise in electricity flow in these neighbourhoods. At certain times, the limits of the electricity grid will be exceeded, and black-outs will occur. Therefore, the distribution system operator (DSO) will have to invest in strengthening the electricity grid to prevent black-outs from happening. These investments are costly and because the DSO can not charge the costs directly to the NDP causing them, the DSO has to cover all the costs itself. However, as ICT-technology is advancing, an alternative solution becomes available: Steering the production and consumption of electricity of DERs, as such that the limit of the electricity grid is not exceeded, and expensive investments in strengthening the grid are not necessary. Instead of investing in strengthening the grid, the DSO could apply this ‘flexibility management’ option. It is however unknown how much grid limit excess would be reduced, and what the influence would be on the house owners. Therefore, the main research question this thesis seeks to answer is: How can a distribution system operator feasibly mitigate grid limit excess in neighbourhoods with a high penetration of distributed energy resources by applying direct control flexibility management, given the current Dutch institutional context? To answer this question, a desk study was performed on both the socio-economical side and the technical side of neighbourhood distributed energy resource projects. The obtained knowledge was used to construct a spreadsheet model which enabled for the comparison of different combinations of DERs and flexibility management options and the influence of these combinations on predefined key performance indicators (KPIs). The model incorporated the perspectives of both the DSO and the house owners, and was based on the case of the Netherlands. The following KPIs were considered: Net present value (NPV), grid limit excess and carbon emission reduction. Input data for the DERs in the spreadsheet model was based, among others, on historical data obtained from real life NDPs. The answer to the main research question is: The possibilities for the DSO to feasibly apply flexibility management to DERs in neighbourhood with a high penetration of DERs are highly dependent on the type of DERs being applied. Results show that only rigorous peak clipping and valley filling flexibility management options are able to completely eliminate grid limit excess. Other DER combinations were found that mitigate grid limit excess, but not completely eliminate it. Rigorous peak clipping and valley filling could feasibly be applied to DER combinations consisting of hybrid heat pumps and photovoltaics (PV). For other DER combinations, consisting of electric heat pumps and PV, flexibility management is not feasibly able to completely eliminate grid limit excess. Furthermore, if electric vehicles (EVs) were to be introduced to the NDPs, it would become even more difficult to feasibly eliminate grid limit excess, even for DER combinations consisting of hybrid heat pumps and PV. Future research could focus on if and how the DSO should compensate the house owners for the flexibility management applied. Other topics for future research include the way flexibility management by a DSO fits within the Dutch market environment as present, legal changes necessary for flexibility management and the costs and privacy issues occurring from developing the ICT-infrastructure needed for flexibility management should be discussed here. Furthermore, the model simulation used in the research could be further developed.