5. Conclusions
This paper presented two methods to predict elevator annual electricity consumption based on short-term electrical energy measurements of a few days to a week. The simpler method relies on linearly extrapolating the annual consumption based on the attained daily consumption measurements. The other method additionally incorporates the effect of seasonal differences in the elevator usage, which are caused by, e.g., holiday seasons, and is expected to provide a more accurate prediction than the simpler method but requires more detailed data on the intra-year traffic patterns. This paper analyzed the performance of the proposed methods with one elevator in an office building. Clearly, measurements, surveys, and other possibly employed methods for estimating and projecting the annual electricity consumptions of office elevators should be conducted outside the holiday season to gain reliable results, as the consumption heavily depends on the traffic. This claim is also supported by our findings of the elevator group having significantly lower average daily consumption on workdays during the holiday season. However, without accounting the effect of seasonal holidays, the annual usage estimate may result in a higher figure than actual. Nevertheless, both of the proposed methods provided adequate consumption projections of the entire year with the studied elevator. Furthermore, additional measurements in other office elevators support the idea of utilizing shortterm measurements of energy over the most significant day types to predict the long-term energy consumption. Competing methods, such as the VDI 4707-1 guideline and the ISO 25745-2 standard, seem to yield similar results as the proposed methods when applying high-quality traffic data. However, attaining reliable traffic data is a challenge in most elevator installations. Moreover, with the elevator analyzed in this paper, the VDI and ISO schemes estimated the annual consumption much higher than actual and performed worse than the proposed methods. Nonetheless, for a more solid analysis of the reliability of the results, significantly more sites with different varying usage and day types need to be monitored. On the basis of the findings, this paper suggests the following considerations when estimating the annual elevator energy consumption: Base projections on measurements of most prevailing day types Consider the effect of seasonal differences, such as holidays Future research will expand the performance analyses of the proposed methods to escalators and moving walks. Furthermore, the authors will focus on momentary and hourly average powers to analyze the potential of employing elevator control system in demand response-related operations. These operations could include limiting the number of units operating, reducing the elevator speed, and increasing the stop time in floors to allow more passengers aboard the elevator, decreasing the amount of starts and, consequently, power peaks in the grid of the building.
