The shift towards more renewable energy sources is imminent, this shift is accelerated by the technological advancement and the rise of environmental awareness. However, this shift causes major operational problems to the current grid that is optimised for unidirectional power flow. Besides the operational problems, there are problems related to the optimal tariff scheme. In this thesis a study on the effect of the adoption of photovoltaic solar panels and the electric vehicles on the households' electricity demand profile is presented. The change on the demand profile is going to affect the current tariffs, this effect is also explored in this thesis. In this thesis real life data on household electricity use and photovoltaic power production was used. For electric vehicle charging simulated data was used. Besides that, a demand response scheme for electric vehicle is proposed in order to estimate the savings potential of this demand response on the electricity bill. The results show that the change in the demand profile is not merely a change in the total energy consumption, but it is a change in the power peaks as well. The peaks change significantly in condominiums and rental apartments, in this households' type it increases by around 80%, while in detached and row houses little change is noticed on the peaks, yet they still increase by around 10%. The demand response shows around 1- 12% savings in the distribution bill depending on the household, however it showed more incentives for condominiums and rental apartments. The current distribution tariffs perform asymmetrically with the various households. However, one tariff ensures 11.7 MSEK financial revenue for the distribution system operator, this is higher than the other tariffs' revenue by more than 28.5%. The new prospective situation requires totally different tariffs that ensure a balance between firstly a reasonable revenue for the distribution system operator and secondly incentives for consumers to self produce electricity as well as to reduce their peaks. 

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Published on 01/01/2016

Volume 2016, 2016
Licence: CC BY-NC-SA license

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