PEVs For Renewables Integration ("Managing the Duck")

Note: This case study is in the process of being revised using an improved managed charging and discharging controller for PEVs to mitigate impacts on the Net Load curve. The results presented in the current version of the case study illustrate the methodology to examine PEV impacts on renewables integration, however the controller applied in this version was not an optimal controller.

Background

Figure 1: Net load curve for California, from 2012 to 2020

The net load curve in Figure 1 points to two important challenges that California's grid will face as substantial levels of intermittent renewable generation are deployed. First, during the day time (i.e. 9 am to 5 pm) when there are many solar plants providing power to the grid there are likely to be over generation problems potentially requiring either renewable generation or base generation plants to ramp down their output. This is a challenge because it is very difficult for base generation to ramp up and down, and it is wasteful to not utilize the renewable power when it is available. Second, in the evening the time when demand is ramping up may coincide with the time when solar generation is ramping down. The resulting sharp upward ramp rate on the net load curve exceeds the ramp rate that can be supported by most generators, including peaker plants.

These two challenges identified by the duck curve can be mitigated by deploying energy storage on the grid, which can be charged during the daytime over generation period and discharged during the sharp evening ramp period. California also has targets for the deployment of substantial amounts of grid storage, however this requires large amounts of capital investment. As more plug-in electric vehicles (PEVs) are deployed in California, the batteries in these vehicles have the potential to provide some of the grid storage necessary to alleviate the challenges identified in the duck curve. In this manner, PEVs can simultaneously advance two high level state goals in the adoption of clean transportation and the deployment of grid storage that can facilitate renewables deployment. This case study examines how PEV deployment can help or hurt the challenges identified by the duck curve.

Methodology

V2G-Sim simulations are run to quantify how PEV charging or discharging will impact the duck curve. As the duck curve does not include charging loads from PEVs, one scenario is run to quantify how the duck curve will change if PEVs are charged in an uncontrolled manner, where vehicles begin charging as soon as they are plugged in. A second scenario quantifies the impact of smart charging, where vehicle charging is controlled to favor charging during the over generation period and disfavored during the sharp evening ramp period. The smart charging period is referred to as "V1G", a term that is commonly being adopted in California to refer to smart charging of PEVs. A third scenarios quantifies the impact on the duck curve if vehicles favor charging during the over generation period and are allowed to discharge to provide power to the grid during the evening ramp period.

Each V2G-Sim simulation scenario includes almost 3 Million PEVs. The vast majority of these vehicles are plug-in hybrids that have specifications similar to a Chevrolet Volt. A smaller fraction of vehicles are pure EVs with specifications similar to a Nissan Leaf. Different scenarios are simulated with vehicles charging  on L1 or L2 chargers in different locations. The simulation results from V2G-Sim are superimposed on top of the 2020 duck curve.

Results

Conclusions