Energy transition: renewables, networks and electric vehicles (session two)
Anna Mortimore
Lecturer
Griffith University
Presentation title: RACE for 2030 Report: business fleets and EVs report, finds Australian Government’s one tax change: in exempting EVs from FBT is not enough to accelerate uptake of BEVs for business fleets and home charging.
Abstract: In Australia, transport is the fastest growing sector and accounted for 18.7% of Australia’s national inventory to March 2022, with road transport accounting for 85% of transport emissions and the cars we drive are the largest contributor.
Decarbonisation of transportation is critical to reducing transport emissions and relies on the transition from internal combustion engine vehicles (ICEVs) to zero-emission vehicles. Australia is behind many other advanced and emerging economies in EV uptake, with Australia‘s uptake just under 2% of new light vehicle sales in 2021, compared with New Zealand's market share had gone from 2.5% to over 11% of new registrations. Business fleets account for around 40% of light vehicle sales and are considered to be an effective pathway for the early adoption of zero-emission vehicles and the major supplier of second-hand EVs when business fleets are rolled over into the second-hand market in 3 to 4 years' time. However, EV sales to business fleets comprised a mere 487 vehicles in 2020, representing 0.08% of passenger and light vehicle sales. In effect, no time soon, will more affordable second-hand EVs flow through to middle and low-end consumers.
Businesses will not invest in workplace charging infrastructure when fleet managers are not choosing BEVs. A 2020 business fleet survey found over 47% of passenger and SUV business fleets are home garaged, and home charging will need to be considered as the key source of charging work fleet BEVs.
The Reliable Affordability Clean Energy for 2030 (RACE for 2030) project, investigated: how tax changes can accelerate the uptake of BEVs within business fleets by encouraging home charging. The research conducted by: Dr. Anna Mortimore (project leader) of Griffith University and Dr. Diane Kraal of Monash University and fellow researchers included: fleet manager interviews; case studies; modeling; and a review of select overseas jurisdictions' income tax changes.
The project findings suggested federal taxation laws can be a cost disincentive and recommended 17 short-term and long-term tax changes to address BEV affordability and support home charging. The Australian Government has only passed one tax change, exempting electric vehicles from Fringe Benefits Tax (FBT) as of 1 July 2022 to be reviewed in three years. The RACE for 2030 Report, finds one tax change is not enough for business work fleets to transition to BEVs and be home charged. RACE for 2030 Report recommends additional tax changes will be required.
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Scott Dwyer
Research Director
Institute for Sustainable Futures, UTS
Presentation title: The challenges and opportunities for Vehicle-to-Grid (V2G)
Abstract: Abstract: EVs are a critical part of international net zero commitments because electrification is a key piece in the puzzle to decarbonize the transport sector.
However, many challenges exist for effective EV grid integration. Policy, regulations, and standards that aren’t fit for purpose, ambiguous costs and benefits of the business models, the uncertainty of consumer attitudes and behaviour, and the technical challenges relating to integrating hardware and software with the increasingly cyber-physical electricity grid.
Vehicle-to-Grid (V2G) is one approach that is being explored to facilitate better integration. V2G refers to EVs that can both charge and discharge electricity to and from the distribution grid.
This has captured the interest of researchers, industry, governments who have been funding an increasing amount of studies and pilots involving V2G. However, it is still early days and questions remain about how ready markets like Australia are for V2G which ultimately requires scale in order to fully capitalise on the potential benefits.
In this presentation, the challenges and opportunities for V2G in Australia and its status will be covered along with what it means for the strategic integration of EVs into the grid.
Jing Zhu
PhD candidate
The University of Melbourne
Presentation title: Understanding the effects of EV management and TOU tariffs in future distribution networks
Abstract: To achieve net-zero emissions, people around the world are shifting towards electric vehicles (EVs). And the most common type of residential charger being used is the fast Level 2 charger (i.e., 7.4kW for single-phase customers in Australia, 230V). This, however, makes the adoption of EVs a clear concern for distribution companies as the additional uncontrolled EV charging demand could easily exceed what the infrastructure has been designed for.
To avoid large-scale network reinforcements and ensure high penetrations of EVs, this work evaluates two potential strategies of EV management:
• A direct approach of EV charger management, and
• An indirect approach that adopts a Time-of-Use (TOU) tariff.
The direct approach of EV management uses a hierarchal control method to remotely disconnect and reconnect EV chargers depending on the thermal and/or voltage issues in the network. This approach is rule-based and does not require LV network models which is significant since many distribution companies lack comprehensive models of their LV feeders down to the customer connection point. The adoption of a TOU tariff, considered as an indirect approach, assumes customers are incentivized to shift their charging events from peak to off-peak hours. This, in turn, can reduce the coincident EV demand and, thus, help mitigate network impacts.
To investigate the benefits and drawbacks of two strategies, a real Australian MV-LV network is used in case study as part of the project “EV Integration” [1]. Residential customers are modelled using anonymised Australian smart meter data, and EVs are modelled using demand profiles produced by real trial data.
The results show that, with uncontrolled EV charging, the EV hosting capacity of the studied network is largely limited by the widespread thermal and voltage issues. It also suggests that that distribution companies can significantly benefit from mixing strategies, i.e., managing EV chargers while also encouraging charging at off-peak hours with TOU tariffs. This can reduce potential delays whilst increasing the EV hosting capacity of existing distribution networks.
The presentation will, particularly, demonstrate the results from realistic simulations using proposed EV management strategies (i.e., the control of EV charging points at homes, and the use of TOU tariffs), and the corresponding potential effects on both customers and distribution networks, which is valuable information for future distribution networks planning and operation.
References
[1] W. J. Nacmanson, J. Zhu, and L. F. Ochoa, ‘EV Integration -Milestone 8: EV Management and Time-of-Use Tariff Profiles’, May 2022. [Online]. Available: https://www.researchgate.net/publication/360887067_Milestone_8_EV_Management_and_Time-of-Use_Tariff_Profiles
Nanduni Nimalsiri
Research Fellow
Australian National University
Presentation title: A network-aware, distributed coordination approach for electric vehicle charging and discharging in unbalanced distribution grids
Abstract: Large-scale integration of electric vehicles (EVs) enabling vehicle-to-grid (V2G) operations accentuates the need for managing bi-directional power flows in distribution grids, especially when they lead to violations in regulatory voltage thresholds, resulting in costly remediation for distribution operators. Most of the existing EV charging approaches that are focused on voltage regulation are designed for single-phase or balanced distribution grids, however, distribution circuits are typically unbalanced in both load and impedance across phases.
Therefore, we propose a network-aware, robust V2G control algorithm to manage voltages in unbalanced distribution grids, where we support distributed EV charge-discharge coordination and also incorporate EV customer economics to incentivize EV customers. Specifically, we seek to minimize the daily operational costs attributed to EV charging and discharging (thereby benefiting EV customers), while regulating voltages in unbalanced distribution grids to stay within steady-state power quality limits (thereby benefiting electrical distributors). Here, the operational costs include financial costs associated with purchasing (or otherwise being compensated for delivering) electricity for EV (dis)charging on a time-of-use (ToU) net-metering tariff, and battery degradation costs due to frequent charging and discharging. We also accommodate network constraints and individual EV battery constraints, including EV charge-discharge rate limits, EV battery state-of-health thresholds, and customer-specified charge requirements. Then, by leveraging from the Alternating Direction Method of Multipliers (ADMM) and the consensus theory, we develop a distributed coordination algorithm wherein EVs locally determine their charge-discharge profiles by exchanging limited information in a peer-to-peer communication network (can be realized with a low-cost wireless network). Whilst most of the existing distributed EV coordination approaches require information exchange between the EVs and a central coordinating agent through two-way communications, our approach requires neighbor-wise communication between customers only, and as such, it reduces the communication overhead and remains robust against a communication-based single point of failure.
Moreover, we integrate a receding horizon optimization approach to enable near-real-time updates in EV arrival and departure times, and updates in day-ahead forecasts of non-EV demand and rooftop solar generation. We also prove that our algorithm is guaranteed to asymptotically converge to the globally optimal solution to the underlying centralized optimization problem. By means of numerical simulations carried on the IEEE 13 node test feeder populated with a real-world dataset of residential load collected from households within an Australian distribution network, we confirm that our algorithm mitigates both under- and over-voltage steady-state excursions potentially arising from peak load demand and excess rooftop solar generation.