The effect of rate design on power distribution reliability considering adoption of distributed energy resources

Abstract

Electricity rates are a main driver for adoption of Distributed Energy Resources (DERs) by private consumers. In turn, DERs are a major component of the reliability of energy access in the long run. Defining reliability indices in a paradigm where energy is generated both behind and in front of the meter is part of an ongoing discussion about the future role of utilities and system operators with many regulatory implications. This paper contributes to that discussion by analyzing the effect of rate design on the long term reliability indices of power distribution. A methodology to quantify this effect is proposed and a case study involving photovoltaic (PV) and storage technology adoption in California is presented. Several numerical simulations illustrate how electricity rates affect the grid reliability by altering dispatch and adoption of the DERs. We further document that the impact of rate design on reliability can be very different from the perspective of the utility versus that of the consumers. Our model affirms the positive connection between investments in DERs and the grid reliability and provides an additional tool to policy-makers for improving the reliability of the grid in the long term.

Probabilistic impact of electricity tariffs on distribution grids considering adoption of solar and storage technologies

“…These models are very popular for designing and predicting investments in DER infrastructure in buildings and microgrids, e.g. [18,19], and are widely used to estimate future adoption and netload when the number of consumers in a particular node is relatively low [33,34,35]. This economic rationality is typically represented as an optimization model, simulating optimal decisions from the perspective of the prosumers, including the size and dispatch of the DER assets in ways that minimize prosumers' overall energy bill.…”

“…Storage variable cost was assumed to be 250 $/kWh, considering a lifetime of 10 years, a charging/discharging efficiency of 90%, a maximum discharge rate of 0.3kW per kWh installed, and a minimum state of charge of 20%. The parameterization of the stochastic model, representing the adoption probability as a function of the solution costs, is presented in equation (35), considering that the fixed effect is set to zero. The probability of adoption is then found given the capital cost, C cap,k , and annual avoided cost of energy, A ann,k as shown in Fig.…”

“…From these two perspectives, it is clear that rate design decisions now have the potential to impact the grid in the future, if the economic dynamics of DER adoption are taken into account. However, as these two lines of research have evolved separately, only a reduced number of studies have focused on this impact [21,22,23,33,34].In particular, a methodology to quantify the grid security and reliability impacts of tariff driven adoption of solar technologies was presented in [33,34] and [35], respectively. In these papers, the authors used an optimization-based approach, from the prosumer perspective, to calculate the post-adoption netload and the consequent impact on the grid.…”

Techno-economic model for long-term revenue prediction in distribution grids incorporating distributed energy resources

“…Therefore, effective and reasonable distribution network investment planning is the necessary condition to solve the above problems (Yi et al, 2021). How to fully consider the influence of DG on the distribution network and make reasonable investment decisions is one of the core tasks of distribution network planning under the condition of limited investment (Maheshwari et al, 2020).…”

Energy equipment sizing and operation optimisation for prosumer industrial SMEs – A lifetime approach

“…Users have access to several key features, in particular the possibility of varying their load and deciding on the basis of economic and environmental criteria. To perform this optimisation, DER-CAM considers three typical days per month over the course of one year [27], leading to a simplified idealization of the decision-making process [28]. REopt is another software tool which serves as a technical-economic decision-support model for RES.…”