Mesut Baran
Publications
- A New LVRT Strategy with Reactive Power Support from Inverter-Based Resources During Unbalanced Faults on a Distribution System , 2024 IEEE TEXAS POWER AND ENERGY CONFERENCE, TPEC (2024)
- More Accurate Measurement Modeling to Improve the Performance of Distribution System State Estimation , IEEE ACCESS (2024)
- URLLC-Aided System Protection in Smart Electric Power Distribution Systems , 2024 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS, ICC WORKSHOPS 2024 (2024)
- A Secure and Adaptive Hierarchical Multi-Timescale Framework for Resilient Load Restoration Using a Community Microgrid , IEEE TRANSACTIONS ON SUSTAINABLE ENERGY (2023)
- Adaptive cold-load pickup considerations in 2-stage microgrid unit commitment for enhancing microgrid resilience , APPLIED ENERGY (2023)
- Adopting Dynamic VAR Compensators to Mitigate PV Impacts on Unbalanced Distribution Systems , IEEE ACCESS (2023)
- Topology Error Monitoring Using Bad Data Detection Methods , IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS (2023)
- Assessment of Anti-Islanding Schemes on a Distribution System with High DER Penetration and Dynamic VAR Compensators , 2022 IEEE 13TH INTERNATIONAL SYMPOSIUM ON POWER ELECTRONICS FOR DISTRIBUTED GENERATION SYSTEMS (PEDG) (2022)
- Improving Topology Error Detection with Distribution System State Estimation , 2022 IEEE TEXAS POWER AND ENERGY CONFERENCE (TPEC) (2022)
- Maximizing the Benefits of Dynamic VAR Compensators on Distribution Systems with High Penetration PV , 2022 IEEE 13TH INTERNATIONAL SYMPOSIUM ON POWER ELECTRONICS FOR DISTRIBUTED GENERATION SYSTEMS (PEDG) (2022)
Grants
The project will examine, using realistic system data, the effect of innovative EV charging rates, with special attention to managed charging, on EV growth, charging time, utility daily load, the utility system, especially at the distribution level.
Through multidisciplinary doctoral education in Cybersecurity for Electric Power Systems (CEPSE), North Carolina State University (NCSU) will increase its commitment to graduate training in two areas designated by the GAANN Program as critical to national need: Cybersecurity and Electrical Engineering. The goal of is to enlarge the pool of U.S. citizens and permanent residents who will pursue teaching and research careers in cybersecurity for electric power systems, thereby promoting workforce development and technological innovation impacting, national security, energy security, and environmental sustainability.
Project goal is to develop a strategy for relay settings and control algorithms for Inverter-based Resources (IBR) with high penetration levels of distributed energy resources (DER) at both the distribution and transmission levels with an integrated co-simulation model.
Utilities conduct power flow analysis on a regular basis. This project will focus on using artificial intelligence to identify which factors are relevant to the quality of a power flow solution, and which data is a good indicator of power flow success or failure.
This project will focus on investigating the benefits of single-phase voltage optimization on distribution systems, additionally, a mini-DVAR would be optimally incorporated to explore any further benefits that can be derived.
In this project, we will develop a Photovoltaic Analysis and Response Support (PARS) platform for improving solar situation awareness and providing resiliency services. The team will focus on developing new operation modes for solar energy systems and a PV+DER situation awareness tool to enable accurate estimation and predication of PV and DER operation conditions in both normal operation conditions and in emergency operation when there is a wide spread outage caused by natural disasters or coordinated cyber attacks. Real-time dynamic studies will be conducted to compute system operation conditions for different operation options. This tool will be run on real-time simulation platform so that optimal restoration plans can be developed in real-time using operation modes enabled by Tasks 1 and parameters derived in Task 2. The team will model transmission, distribution, and all the way down to each DER and inverter units at utility scale PV farms on a multi-core OPAL-RT real-time simulation platform.
Next year is our center?s critical review year. Demonstrating an operational green energy hub is important for the NSF as well as for our research needs. Such a hub will also serve as an important testbed to work with our member companies. The center recently moved into the brand new Keystone Science Center in June 2010. The FREEDM Systems Center occupies 20,000 square feet of office space, laboratory, and meeting room space in the building. The FREEDM Center lab space inside the Keystone Science Center was designed specifically to accommodate the 1 MW Green Energy Hub and will house the distributed generation, storage, and renewable energy technologies that FREEDM is working on. At the heart of the lab is a 12 kV distribution system (Figure 1), generated by the two 1 MVA transformer and the back to back (BTB) converter. The BTB converter acts as a substation solid state transformer (SST) to control the system fault current. The equipment marked in green color are already in place, while those marked in blue color are key project deliverables from various projects in the center in Year 3. Those marked in red color are those equipment that this project need to purchase.
D-VAR is an emerging technology which is designed for distribution level volt/VAR applications. This project focuses on development of methods which will facilitate the effective integration of D-VARs on Duke Energy feeders such that the benefits D-DAR offer can be maximized. This In this phase of the project the focus will be towards the development of more dynamic dispatching schemes for the D-VAR such that the expected benefits are maximized.
With new technologies such as AMI, utilities now have an abundance of data, however, they are doing very little with this data. Because of this situation, we will collaborate with our sponsor ElectriCities to investigate and develop applications for data analytics for utility operations and customers programs.
Apply for planning grant funding to establish an ERC.