A qualitative study of perspectives on household and societal impacts of demand response

Abstract

Despite the importance of demand response (DR), there has been little exploration of its potential impact on the individual or society. To address this gap, semi-structured interviews were conducted with 21 households in the south of England, in which two DR vignettes were presented: peak pricing and remote demand control during critical peaks. Peak pricing was seen as inequitable, burdening the less affluent, the less healthy, families and working mothers. Adverse societal outcomes may result from peak pricing, with potential for disruption of time-dependent household routines including the socially vital ritual of family mealtimes. Householders perceived their peak-time consumption to be determined by society's temporal patterns and not within their control to change. Third-party control in demand-side management was perceived to contravene householders' rights of control inside their homes. Alternative approaches to shifting peak demand, which combine technological, economic and socio-psychological insights, are considered.Keywords: demand response; demand-side management; dynamic pricing; peak energy consumption; qualitative; inequity IntroductionDemand response (DR) has been positioned as essential to energy policy in Europe (EU 2011). In response to the threat of global warming, which greenhouse gas emissions from human activities are exacerbating (IPCC 2013), policy-makers are seeking to reduce emissions through improved energy efficiency. Smart grids are seen as crucial facilitators of this objective, but it is DR which is expected to facilitate greatly increased levels of energy efficiency (Faruqui, Harris, and Hledik 2010). To date, there has been extensive research on the economic and engineering aspects of DR but little exploration of its potential impact on the individual or society. The current paper aims to address this gap.Traditionally, energy systems were designed and planned from the perspective of energy generation (Bilton et al. 2008). However, seasonal variation and overcapacity to deal with peaks * Corresponding author. Email: n.murtagh@ucl.ac.uk mean that significant inefficiency has been designed into existing power systems. In the UK, total consumption can be under 55% of capacity (Strbac 2008). In the smart grid, the electricity infrastructure will be augmented with a two-way digital communications network between enduse premises, distribution and transmission nodes and generating centres. The smart grid will reach end-user premises through smart meters. Already underway in several European countries, national rollout of smart meters in the UK is planned from 2015 to 2020, and an accompanying communications campaign emphasises that this will enable consumers to 'take control' (Smart Energy GB, 2014). With smart metering, there is the potential not only to predict demand to a much finer degree of granularity but also to influence demand. This capability is known as DR and is critical to realising the anticipated benefits of the smart grid (EU 2011).Definitions in the literature of DR o...

Uncertainty, vision, and the vitality of the emerging smart grid

“…To overcome this difficulty, more and more smart grid demonstration projects are working with end users who provide feedback on their perception of energy and their behaviors [25,34]. First, outcomes have confirmed the theoretical hypothesis of inequity in demand-response management [22], showing, for instance, that peak pricing is perceived negatively and would primarily impact households with limited financial means [48]. Furthermore it appears that feedback devices as they are currently designed have limited influence on household energy consumption [52,56].…”

“…[4,13,48]). These actors' typologies usually propose three categories: (1) energy utility suppliers (i.e., energy suppliers and operators on transmission and distribution systems), (2) smart grid technology suppliers (i.e., suppliers of infrastructure for energy transmission and distribution, metering equipment suppliers and ICT firms), and (3) research institutes (i.e., universities and research centers).…”

Acceptance among residential electricity consumers regarding scenarios of a transformed energy system in Switzerland—a focus group study

“…In terms of dynamic tariffs, automated response by smart appliances finds better acceptance than manual response by the consumer (Fell et al 2015). However, also DLC has its flaws, as it interferes particularly strongly with individual needs of privacy and autonomy (Murtagh et al 2014). Acceptance of DLC is also highly dependent on the type of appliance to which it is applied: Whereas DLC is accepted to a certain extent for washing machines, dishwashers, pool pumps and air conditioning, it is seen as out of bounds for television or personal computers (Gardner and Ashworth 2007;Bossi et al 2013).…”

“…Moreover, if applied with override ability, DLC is also more popular (Fell et al 2015). Nicholls and Strengers (2015) and Murtagh et al (2014) point to the lack of fairness with TOU pricing: In particular, families with children are constrained in their time-related flexibility in electricity use (e.g. cooking).…”

“…DLC allows the electric utility to directly shift loads to periods of lower demand (Bload shifting^) by remotely controlling electric devices-typically, boilers and heat pumps in households (Murtagh et al 2014). As DLC may considerably curtail the consumers' autonomy, some DLC systems have a switch so that consumers can manually override the remote control signal from the utility (Fell et al 2015).…”