Providing Utility to Utilities: The Value of Information Systems Enabled Flexibility in Electricity Consumption

Abstract

As the transition to renewable energy sources progresses, the integration of such sources makes electricity production increasingly fluctuate. To contribute to power grid stability, electric utilities must balance volatile supply by shifting demand. This measure of demand response depends on flexibility, which arises as the integration of information systems in the power grid grows. The option to shift electric loads to times of lower demand or higher supply bears an economic value. Following a design science research approach, we illustrate how to quantify this value to support decisions on short-term consumer compensation. We adapt real options theory to the design-a strategy that IS researchers have used widely to determine value under uncertainty. As a prerequisite, we develop a stochastic process, which realistically replicates intraday electricity spot price development. With this process, we design an artifact suitable for valuation, which we illustrate in a plug-in electric vehicle scenario. Following the artifact's evaluation based on historical spot price data from the electricity exchange EPEX SPOT, we found that real options analysis works well for quantifying the value of information systems enabled flexibility in electricity consumption.

One rate does not fit all: An empirical analysis of electricity tariffs for residential microgrids

“…We also caution against touting real-time pricing as an economic panacea for residential tariff design [19,54], as many microgrid operators might be reluctant to assume the implicit price risk. Energy retailers, on the other hand, can easily manage this risk by creating sufficiently large customer portfolios and trading in the wholesale market [55]. Nevertheless, real-time wholesale pricing might become the preferred option for microgrids that mainly act as IPPs.…”

Harnessing the Full Potential of Industrial Demand-Side Flexibility: An End-to-End Approach Connecting Machines with Markets through Service-Oriented IT Platforms

“…DR offers an attractive option by being able to react to short-term (minutes to hours) market price signals, and thus, it can be used as an insurance against unforeseen market volatility and even for arbitrage purposes for the intraday-or day-ahead-market (see Nos. 1 and 2, Table 1) [26,27]. Besides the use of DR in the energy-only market, industrial DR plays an important role in balancing power markets, in which loads are offered for compensation in the case of system instability [28].…”

Scheduling Flexible Demand in Cloud Computing Spot Markets

“…If the customer does not exercise the deferral option at time t ¼ T at the latest, he/she reaches the individual deadline in the next discrete time step (t ¼ T þ 1) and must purchase cloud services then. Technically speaking, modeling a deadline is already an extension of Cox et al's (1979) and Tian's (1993) traditional models, which Fridgen et al (2016) introduced for the former approach. Both approaches start option pricing by analyzing the possible exercise values in the binomial tree's end nodes:…”

“…We follow Fridgen et al (2016) as follows to model the time-of-day-specific spot price patterns in order to test Hypothesis 1:…”

“…While Fridgen et al (2016) extend the approach by Cox et al (1979) with mean reversion to the time-of-dayspecific mean price and volatility patterns, we also apply Tian's (1993) model and mean reversion to the time-ofday-specific mean return patterns. Financial asset pricing usually exhibits stationary mean returns, but non-stationary mean prices (Rossi and Spazzini 2014), which makes the former preferable for deriving predictions in these markets.…”