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This degree project investigated how the introduction of a capacity-based component (Effektavgift) in Swedish electricity network tariffs may influence residential end users. The study focused on households in Eskilstuna, Sweden. A mixed-methods approach was applied, combining a qualitative review of 110 Distribution System Operators (DSOs) and a quantitative analysis of real hourly electricity consumption data from 100 households during 2024, divided equally between district heated (DH) and non-district heated (non-DH). From the reviewed DSOs, the existing and proposed tariff structures were classified according to monthly peak count methods, seasonal variation, and time of the day differentiation. By developing mathematical billing models in MATLAB, five representative tariff structures were evaluated against the old energy-based billing model. Revenue neutrality analyses were also conducted to evaluate how tariff design parameters affect user costs. Furthermore, the study analyzed the peak demand and total electricity cost reduction that prosumers equipped with either photovoltaic (PV) or combined PV with battery energy storage systems (BESS) can achieve under rule-based and optimization-based control strategies, and the potential reductions were examined for different tariff structures. In this analysis, three scenarios were simulated: PV system only, PV + BESS under rule-based control strategy and PV + BESS under optimization-based control strategy. The results indicated that the financial impact of new tariffs depends heavily on household load profiles, heating type, and tariff design; while some structures remained revenue neutral, others led to significant cost increases for all users. Users with high simultaneous peak demand were generally more affected than households with flatter demand patterns. Non-DH users generally exhibited higher peak demand and stronger correlations between temperature and bill impact. The optimization-based PV + BESS configuration achieved the most substantial reductions in both peak power and annual electricity costs across both user categories and all the tariff structures. The study concluded that power tariffs effectively penalize high peak loads, but their outcomes depend strongly on tariff structure and users’ consumption.