The evolution over time of Distributed Energy Resource’s penetration: A robust framework to assess the future impact of prosumage under different tariff designs

Cristian Bustos, David Watts and Daniel Olivares

Applied Energy, 2019, vol. 256, issue C

Abstract: In the future, drastic cost reductions of Distributed Energy Resources will probably drive their deployment without the need of economic incentives - especially photovoltaic energy. Dynamic Grid Parity Models combine learning curves with grid-parity. They are the state-of-the-art solution to assess the time-evolving competitiveness of generation technologies, but fail to capture the residential end-user’s choices of installing Distributed Energy Resources once they become feasible. We propose a robust framework based on a local and optimal microgrid combined with learning curves to assess the potential penetration of Distributed Energy Resources in households. This framework adds a notably richer interaction between the elements of the distribution system, e.g., optimal dispatch or peak shaving. We quantify the time-evolution of residential end-user’s bills and the utility’s revenue, applied to four tariff designs. Today Chile pioneers a massive deployment of photovoltaic systems without incentives, becoming a unique example worldwide, specially the so called “Solar City of Diego de Almagro”, a town with a remarkable solar resource and massive PV deployment, chosen as the case study. Results show PV dominance with flat bundled volumetric tariffs and the increase of utility’s bankruptcy risk if tariffs are not updated (47% revenue reduction). If updated, bills would increase 24%, affecting non-owners. A two-part tariff overcomes this but it is regressive and it delays PV deployment. A three-part tariff improves efficiency and introduces prosumage, with a small peak-shaving effect. Owners could face regulatory risks due to possible tariff design changes. This study lays the foundation for future rate cases, and for distribution and transmission planning.

Keywords: Learning rates; Tariff design; Distributed Energy Resources (DER); End-user decision; Microgrid optimization; PV systems (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (8)

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DOI: 10.1016/j.apenergy.2019.113903

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