Overview
This project is the first step in developing a holistic design and validation framework for roadside Microgrid configurations that deliver optimal electric vehicle fast charging, grid interaction, and value-added grid services as well as a bankable foundation for a reliable and sustainable nationwide electric vehicle (EV) charging network. The MFCS project is a joint research and development initiative created by Xendee Corporation and Idaho National Laboratory (INL) with funding by the U.S. Department of Energy, Office of Electricity.
With a focus on the next generation of roadside infrastructure, the project team has identified charging requirements, load profiles and power requirements that are particular to fast charging heavy duty trucks and EV charging at scale, defined two test cases to simulate and validate the capabilities of fast charging Microgrids, and assured compliance with standards for functionality and interconnection. The two test cases represent a grid connected MFCS with 5.83 MW of fast charging capacity as well as an islanded MFCS with 3.75 MW of fast charging capacity. Using these case studies, the project team has successfully validated Xendee's integrated Microgrid design and analysis tool for high power fast charging of large Megawatt loads for electric vehicle fleets and trucks. Additionally, power flow and distribution system modeling (e.g., voltage, frequency, transformer, and cable sizing, etc.) have been integrated with the economic design and validated via real-time simulations at INL. INL also performed transient simulations for various cases that model extreme EV charging load increases and the impact on voltage and currents.
The MFCS project also includes and integrates (a) the development and evaluation of a technical planning and economic analysis tool for the design and implementation of Microgrid Fast Charging Stations, (b) the design of the Microgrids’ underlying infrastructure, (c) and the appropriate testing algorithms to interpret the results. Additionally, it is the first tool of its kind that integrates power systems engineering for electric vehicle charging with Distributed Energy Resource (DER) modeling while also connecting local distribution and utility interactions with the financial design to capture the lowest costs and the fastest return on investment.
The steps below were concluded within the project for the two selected test cases including:
- Research on charging infrastructure costs, unit sizes, fees, EV truck status quo, driving distances, DER technology costs, public and private-sector electrification goals, and research on how these goals can influence the optimal design of a MFCS project.
- Research and algorithm design for economic and financial modeling of MFCS.
- Energy System Analysis extended by Xendee's:
- Process of constructing models and scenarios to address goals relevant to MFCS design, optimal DER portfolio, and optimal controller dispatch and logic.
- Financial projections to assess business cases of Microgrid design and operation.
- Power System Analysis:
- Process of integrating energy systems analysis results into creation of circuits.
- One-line diagram for planning purposes.
- Power flow models for the Hardware in the Loop analysis.
- Balance of system sizing for cables and transformers.
- Snapshot power flow showing response of power systems under full loading conditions.
- Quasi-Static Time Series (QSTS) studies showing response of power systems to time-dependent conditions.
- Real-time simulation of power flow evaluation at INL confirming that all power flow results from the Xendee platform are within 5% of the detailed INL simulations.
- In addition to these steps INL also performed transient analyses for changes in EV charging loads for the islanded case, which is considered critical due to the missing utility connection.
- Assessment of missing capabilities and platform limitations.
The completed R&D together with the MFCS platform allows the Microgrid and EV industry to address and assess the:
- Lowest cost technology mix for fast charging of EV and truck fleets; optimal capacities for photovoltaic (PV), electric storage, generators, Combined Heat and Power (CHP), etc.; the net present value (NPV) or the return on investment (ROI) for the project including the EV fleet loads.
- Optimal operation of the system to minimize costs or maximize the revenues.
- Optimal charging and discharging of the electric storage and EV fleet to minimize overall costs.
- Optimized management of EV fleet charging times.
- Optimal placement of FCS and local generation resources to mitigate bottlenecks in the utility system.
- Impact of grid outages on the EV charging and costs/oversizing of equipment.
- Sales of excess energy back to the utility or revenues from providing Ancillary Services.
- Proper electrical engineering for cables and transformers.
All the steps and features listed above can be addressed for grid-connected MFCS projects as well as for completely disconnected ones (islanded cases). This flexibility offers vast opportunities for wide scale integration of renewable energy generation at fast charging stations and is backed by optimized Microgrid design, dispatch, and investment decision support.
The next R&D steps for future projects will include:
- Electromagnetic and transient analyses algorithms in Xendee that utilize the insights from the INL HIL simulations.
- Vehicle to Grid (V2G) as well as Vehicle to Building (V2B) modeling and revenue streams.
- DC Microgrid versus AC Microgrid FCS structures.
The roll-out of the platform for nation-wide testing can also be considered.
Xendee
