Behavioral decision-making in power demand-side response management: A multi-population evolutionary game dynamics perspective

Abstract

Traditional single-agent decision-based optimization theory system is gradually hard to address long-term dynamic interaction problems in power demand-side response management (DRM). To this end, this paper thoroughly investigates the behavioral decision-making issues in power DRM from a perspective of multi-population evolutionary game dynamics. First, the evolutionary dynamics of general two-strategy three-population evolutionary games (2s3pEGs) is discussed, and relative net payoffs (RNPs) are defined for them in engineering. Discussion reveals that long-term evolutionary stable equilibrium (ESE) achieved in 2s3pEGs is only determined by RNPs. Further, the modeling idea of general two-strategy n-population (n ≥ 2) evolutionary games (npEGs) is elaborated. Second, a two-strategy npEG-based power DRM model is developed, as well as an npEG algorithm. Based on these, this paper investigates the long-term ESE of user engagement in power DRM using six subcases, which verifies the practicality and effectiveness of the obtained findings. Moreover, the case study reveals that incentive pricing from utility companies plays a major role in increasing user engagement in power DRM, thereby promoting different user populations to participate in smart power consumption, dispatching and distribution. Finally, the future work is prospected. This paper attempts to apply npEG dynamics to power DRM. The findings could provide guidelines for the investigations on bounded rationality and limited information-based behavioral decision-making issues, especially in the power DRM field.