The effect of technological learning on cost development and economical attractiveness of net zero energy house renovations in the Netherlands

Abstract

The purpose of this research is to gain insight in the historical price development of net zero energy (NZE) renovation packages and future price developments of NZE house renovations in the Netherlands. This research analyses what the effect of the development of energy prices is on the economical attractiveness of an NZE house in relation to a fossil fuel reference scenario.

A house renovated to NZE is a house with NZE use, and thus NZE costs during a calendar year. Based on the concept of technological learning and future projections of NZE renovations in the Netherlands, the historical and future price development of the NZE renovation concept are determined. The historical price development of NZE renovation packages in the Netherlands were determined by gathering price data of these renovations for the period 2014-2019. These price data were processed to make them suitable for constructing several experience curves. Based on these experience curves, several learning rates were determined. Consequently, in combination with projected amounts of NZE renovations in 2025, 2030, and 2050, future prices were calculated in the relevant years. These prices are all representing optimistic, normal, or pessimistic price development paths of the NZE renovation packages. The prices were further used to determine the economical attractiveness of the NZE renovation packages by using the net present value method. The investment in an NZE renovation was compared to a reference house connected to the Dutch gas grid.

From the scenario analysis it can be concluded that an investment in an NZE renovation is most of the times economically attractive in the normal and optimistic scenarios. In the pessimistic scenario, an NZE renovation is mostly an economically unattractive investment. Moreover, a Monte Carlo simulation was performed on the energy costs to simulate the NPV values for eighteen different investments. The variables simulated were the energy costs. This simulation concluded that fifteen out of eighteen investment scenarios are economical attractive with a probability of 95%.