Modeling and Analyzing the Effect of Human Preferences on a Local Electricity Market

Abstract

Local electricity markets (LEMs) have progressed significantly in recent years, but a research gap exists in understanding the influence of human preferences on the effectiveness of LEMs when home energy management systems (HEMSs) are involved. Motivated by this, this work aims to model and integrate human preferences into a HEMS, bridging the gap between end-participant and LEM. A sensitivity analysis of the parameter choices of the HEMS and their impact on the performance and outcomes of a LEM is done. Hereby, a behavior model is used to formulate the preferences and motives of households within a LEM in a bottom-up approach. Various distributed energy resources are modeled and controlled via a HEMS, allowing households to input their preferences and motives to output a tailor-made bidcurve for the LEM. A sensitivity analysis reveals that different preference settings result in different consumption profiles, which to a large extent align with the preferences. In addition, the importance of aligning market mechanisms and steering signals with the participants' goals is highlighted.