EVsmartPV2H - EV Integration Smart Power Systems

This project will be organized as the equivalent of an REU (Research Experience for Undergraduates) for one University Scholar Program (USP) - BS for PhD student to work under the guidance of one senior faculty advisor, researchers, and other PhD students at University of Kentucky. The electrification of transportation is supported by national and state level initiatives. The TVA service area expects substantial growth in the deployment of electrical vehicles (EV). As a result, the typical load profiles are forecasted to change in the following years and better understanding of the specifics, including the possible load peaks due to simultaneous EV charging in the evening and before storms is required. Studies should be conducted both at aggregated power level and electric distribution circuit level to quantify the effects on lines, feeders, transformers, and buildings. The main objectives, which will be addressed through the systematic program of tasks, within the resources allocated and based on the research progress and findings, are: • Experimental characterization of typical representative Type 2 chargers using an Eaton GMEV32BR-WC system • Develop a data base with EV charging information for power vs. time • Research options for EV charging monitoring using data provided by EV chargers • Identify EV charging using only smart meter data (AI and ML algorithms with combined experimental and synthetic data). The new learnings provided by this research project include systematic methods to identify EV charging loads as technology is being deployed in the field on electric power distributions with dedicated methods: • In collaboration with residential customers • Independent of the residential customers, i.e. non-intrusive load monitoring methods with different time resolutions and based on a variety of data sources The new learnings will be summarized in project reports suitable for communication with TVA and Local Power Companies (LPCs). Benefits • Contribute to the knowledge base of TVA and LPCs for the large-scale deployment of EVs • Monitoring of EV charging loads will allow the typical spatial load distributions and load profiles to be established and support optimal planning for future electric power system updates and developments. Tasks The project will comprise the following major tasks with the milestones, deliverables, and timing specified in the following sections. Task # 1 – Install the EV charger in the UK SPARK Labs • Research the best set up options; likely 208V single phase supply • Develop portable option suitable for UK Solar Car charging. Task # 2 – Acquire and commission a fully controllable battery emulator for the UK SPARK Labs • Funding provided from other resources than this project, i.e. previous private donation for the SPARK Labs • The emulator will also be used also for other projects. Task # 3 – Test in the UK SPARK Lab the EV charger • Perform lab tests with the battery emulator • Perform UK Solar Car or other EV tests • Validate EV charger capabilities in terms of data capabilities, i.e. power, time resolution, data format, communications. Task # 4 – Study other typical EV chargers and available data sets • Systematic literature and documentation search and review • Search for publicly available information and data sets • Seek data sets from other contacts: OEMs and national labs, incl. ORNL. Task # 5 – Curate EV charging data • Create, organize, and maintain experimental and synthetic data sets • Develop recommendations for best practices on how to collect, store, and use data provided by EV chargers. Task # 6 – Machine learning (ML) artificial intelligence (AI) algorithms for automatic detection of EV charging • Automatically detect using only smart meter data • Establish confidence levels and determine typical errors. Task # 7 – Final reporting • Prepare deliverables for documentation, software code, and data • Organize final review workshop. Deliverables Deliverables include: • documentation, in the form of milestone technical reports, presentations for monthly teleconference updates with the sponsor, and software instructions • computer code for the developed co-simulation software framework INSPIRED+ with examples; it should be noted, especially for the software, that this will be delivered “as is” without warranties, and that will be solely aimed for script-based expert use • final review workshop to summarize developments and discuss main findings/learnings. Estimated Period of Performance / Estimated Schedule Start and End dates, Milestone Durations, Planned Deliverable dates with associated Invoicing. Period of performance: May 15, 2023 to August 31, 2023 Milestones Start Date End Date Deliverable Invoice Date and Amount Tasks1, 2,and 3 5/15/23 8/31/23 As specified in a previous section N/A Tasks 4 and 5 5/15/23 7/31/23 As specified in a previous section N/A Task 6 5/15/23 7/31/23 As specified in a previous section N/A Task 7 5/15/23 8/31/23 As specified in a previous section Aug 31, 2023 Total Estimated Budget $18,000 Contract R&D $ Other Direct Costs (ODCs) $ OH on Contract R&D & ODCs ( $ Burdened Labor XX hrs. @ $YY Rate TOTAL $ 18,000