Developing a Smart Grid that Customers can Afford: The Impact of Deferrable Demand

Abstract

With more electricity generated from renewable sources, the importance of effective storage capacity is increasing due to its capability to mitigate the inherent variability of these sources, such as wind and solar power. However, the cost of dedicated storage is high and all customers eventually have to pay. Deferrable demand offers an alternative form of storage that is potentially less expensive because the capital cost is shared between providing an energy service and supporting the grid. This paper presents an empirical analysis to illustrate the beneficial effects of Plug-in Hybrid Electric Vehicles (PHEV) and thermal storage on the total system cost using data for a hot summer day in New York City. The analysis shows how customers can reduce total system costs and their bills by 1) shifting load from expensive peak periods to less expensive off-peak periods, 2) reducing the amount of installed conventional generating capacity needed to maintain System Adequacy, and 3) providing ramping services to mitigate the variability of generation from renewable sources. Moreover, this paper demonstrates economic benefits of different types of customers with different deferrable demand capabilities under two bill payment policies, flat price payment and optimum price payment, and it finally shows how long it takes for customers to fully pay back their initial capital costs of PHEV or thermal storage under two different policies.

Using deferrable demand in a smart grid to reduce the cost of electricity for customers

“…T , where u t , v t and w t are ARMA(p, q) residuals. The specific form of each individual equation is explained in more detail in (Jeon et al 2015) but it should be noted that the structure of the model assumes that there is no feedback of price on load. 3 Since the equations for predicting load depend on temperature (Cooling Degree Days and Heating Degree Days), it is possible to distinguish temperature sensitive load (TSL) from non-temperature sensitive load (N-TSL) by making a set of predictions assuming the temperature is always 65 • F and comparing them with predictions made using observed temperatures.…”

“…(CUOMO 2014) The results from our earlier research in (Jeon et al 2015) and (Lamadrid et al 2014) using much simpler models indicates that the main thrust of the REV is a viable way to reduce customer costs. With deferrable demand controlled by a system operator, our research shows that the main savings in operating cost come from the displacement of conventional generation by spilling less wind generation and committing fewer generating units as reserve capacity.…”

How Does Energy Storage Increase the Efficiency of an Electricity Market with Integrated Wind and Solar Power Generation?—A Case Study of Korea

“…This cost has been discussed in recent studies, including Troy et al [12], Kumar et al [13], Lamadrid et al [14], and Wogrin et al [15]. The methodology of applying ramp wear and tear costs in this model follows Jeon [16]. The ramp wear and tear cost is proportional to net demand change.…”

The Impact of Regulation on a Firm’s Incentives to Invest in Emergent Smart Grid Technologies

“…3 The rhythm of development of these distributed energy resources also has an effect in the value of the new "smarter" infrastructure. For instance, demand response (DR) can help system operators to integrate increasing intermittent generation as well as to flatten the load diagram of the networks, allowing to defer the need for costly investments in the expansion of the electrical system (Jeon et al, 2015a(Jeon et al, , 2015bMoslehi and Kumar, 2010). A number of markets in the U.S. are already negotiating DR, and in some cases this is becoming a significant market resource (Rahimi and Ipakchi, 2010).…”

“…The benefits of a higher participation of demand for the electricity system are potentially manifold (Jeon, 2015a(Jeon, , 2015b. Active demand may delay the need for costly expansions and upgrades of the system by attenuating the peaks of consumption (Gelazanskas and Gamage, 2014).…”