Why Smart Appliances May Result in a Stupid Energy Grid?

TL;DR

This paper analyzes how demand-response policies based on smart appliances can unintentionally destabilize power grids due to synchronization effects, emphasizing the need for holistic system modeling.

Contribution

It introduces a multi-layered approach to model power grids, highlighting the limitations of individual appliance-based decision models and proposing a comprehensive system perspective.

Findings

Synchronization among appliances can destabilize the grid

Holistic modeling improves understanding of system dynamics

Methodological choices influence system stability

Abstract

This article discusses unexpected consequences of idealistic conceptions about the modernization of power grids. We will focus our analysis on demand-response policies based on automatic decisions by the so-called smart home appliances. Following the usual design approach, each individual appliance has access to a universal signal (e.g. grid frequency or electricity price) that is believed to indicate the system state. Such information is then used as the basis of the appliances' individual decisions. While each single device has a negligible impact in the system, the aggregate effect of the distributed appliances' reactions is expect to bring improvements in the system efficiency; this effect is the demand-response policy goal. The smartness of such an ideal system, composed by isolated appliances with their individual decisions, but connected in the same physical grid, may worsen the system stability. This first-sight undesirable outcome comes as a consequence of synchronization among agents that are subject to the same signal. We argue that this effect is in fact byproduct of methodological choices, which are many times implicit. To support this claim, we employ a different approach that understands the electricity system as constituted by physical, informational and regulatory (networked and structured) layers that cannot be reduced to only one or two of them, but have to be viewed as an organic whole. By classifying its structure under this lens, more appropriate management tools can be designed by looking at the system totality in action. Two examples are provided to illustrate the strength of this modeling.