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High penetration of novel building energy technologies has prompted a growing concern about their microeconomic effect and grid influence. Deployment of photovoltaic (PV) and solar collectors together with energy storage solutions and the growth of electric vehicles (EV) fleet are amongst the key influencing technologies. Reliable forecasting of the acceptance of these and other energy-related solutions is necessary to guide the decision-making process that would satisfy the needs of both, energy consumers and the suppliers. Whereas electric energy cost is one of the key influencing factors of technologies acceptance for households, peak grid loads and grid feed-in are the important parameters for sizing the grid capacity by energy suppliers. In this study, long-term energy pathways of the existing Norwegian residential buildings were evaluated. A number of electricity pricing models were analysed together with the aggregated grid load and grid feed-in profiles. Detailed energy performance simulations were used to evaluate the effect of aforementioned technologies at a single building level. The forecasting of likely future state of their implementation at a built stock level was done by using the Monte Carlo method. When observing a single building, the results indicated that some technologies were instrumental in decreasing the electricity load variation. At the aggregated level of 1000 buildings, the expected peak load decrease might be between 1% and 13% compared to the current level. Grid feed-in would likely be within the range 0 and 2500 kW by 2050. Considering different pricing methods, those based on the pricing of power extraction would cover better electricity grid cost, while they would result in highest electricity price per kW h.

Influence of emerging technologies deployment in residential built stock on electric energy cost and grid load