Research Projects

Project Description: 

The expansion of 5G networks increases the need for strategic antenna placement. With shared pole use, the location of antennas on the top of distribution poles is being investigated. The major concern with this use is the occurrence of lightning strikes to the antenna. Potential discharge paths exist not only to ground but also to adjacent phase conductors that are supported on the pole. This may degrade reliability and so require evaluation under a wide variety of operating conditions.

Student Research Activity: 

(1) baseline lightning susceptibility of a distribution line will be evaluated with a full size cross arm construction three-phase distribution line subjected to a full lightning wave supplied by an impulse generator in Clarkson’s high voltage lab; (2) modeling will be performed to determine the best conductor placement in combination with different candidate insulators to accommodate placement of a 5G antenna at the top of the pole; (3) flashover tests will then be performed to assess the validity of the design and examine changes in lightning susceptibility of a distribution line when a 5G antenna is mounted. The results will provide guidelines for electric grid asset hardening with 5G networks.

Project Description: 

Distribution systems have seen a proliferation of Distributed Energy Resources (DER) and sensors in the last decade, creating opportunities for improved grid efficiency. Even though centralized/distributed DER control for secure and economic operation of distribution grids has been proposed, there remain two open questions: (1) how to handle cyber abnormalities, e.g., communication issues and network insecurity, and (2) how to accommodate altered system topologies due to feeder reconfiguration. To address these challenges, this project will develop cyber-resilient DER control for autonomous distribution grid operation that meets the needs of real-time robust monitoring and control of millions of DERs against communication delays, cyber-attacks, and model-based control issues.

Student Research Activities:

(1) collect data, including PV generation data from Clarkson’s 2MW solar farm, load demand data from Clarkson’s Smart Housing testbed, and battery storage charging model and parameters; (2) establish a baseline testing case; and (3) investigate the impact of non-ideal communication infrastructure on the optimization-based DER control performance (using Clarkson’s Smart Grid Systems and Control lab for hardware in the loop testing). The investigation of resilient DER control in practical communication infrastructures will provide guidance on an affordable, low risk, and low cost solution for the grid of the future with high DERs.

Project Description: 

By Q1 of 2021, more than 100GW of solar capacity was installed nationwide with approximately 20GW and 15GW installed at residential and commercial premises, respectively. The massive amount of PV systems being installed on power distribution and transmission grids challenges grid planning and operations. The cost-effective but safe integration of PV installations on the grid is one of the most challenging barriers to unlocking the value of this source of clean energy. To streamline solar integration and mitigate the impact on grid operation, IEEE Std. 1547-2018 was developed and is being widely adopted by utilities. This standard specifies five voltage regulating functions required of compliant inverters. Each of these functions has multiple settings options. However, the standard does not provide guidance on the selection and settings of these functions. Thus, the impact on voltage regulation from smart inverters in different control modes and increased dynamic hosting capacity remains an as yet unanswered question for the system planners and operators.

Student Research Activity: 

(1) model representative distribution feeder circuits in OpenDSS; (2) implement different voltage regulating control models (volt-var, volt-watt, constant power factor, etc.) and simulate the distribution feeder circuits (candidate feeders are the ones serving Clarkson); (3) increase the size of PV (use data from Clarkson’s 2MW solar farm) and re-simulate the distribution feeder circuit under different voltage regulating modes to determine the hosting capacity; and 4) summarize the impact on system voltage and feeder circuit hosting capacity when smart inverters are running in different voltage regulating models. Findings will be used to develop a design guide for distribution engineers in selecting the most effective options of a given situation.

The U.S.’s target to deploy 30 GW of offshore wind by 2030 will create more than 44,000 jobs directly in the offshore wind sector and nearly 33,000 additional jobs in communities supported by offshore wind activities. Advancing this national initiative, New York State leads the nation with its goal to develop 9.0 GW of offshore wind power by 2035 for grid decarbonization. However, interconnecting offshore wind power to land poses many challenges to the power grid in New York and across the country, including complex behaviors of inverter-dominated power grids, computational modeling of offshore wind for bulk-power system analysis, and advanced converter control to support grid operation. This project aims to address these three critical challenges.

Student Research Activity:

(1) review the state-of-the-art modeling techniques for the inverter-based wind turbines; (2) develop the inverter models and offshore wind farm models in non-real-time platform (PSCAD/MATLAB) and in real-time platforms (Opal-RT/RTDS at Clarkson’s Smart Grid Systems and Control Lab); and (3) develop advanced controls algorithm for the inverters and power plant control to ensure the stable and reliable operation of offshore wind farms.

Project Description: 

The New York State’s Climate Leadership and Community Protection Act (CLCPA) requires the State to achieve a carbon-free electricity system by 2040 and reduce the greenhouse gas emissions by 85% by 2050. This calls for the deployment of 6,000 MW of Energy Storage systems (ESS) by 2030 and fast transportation electrification across the state (e.g., achieving 1 million EVs on the road by 2025 in New York State and banning new sales of internal combustion passenger vehicles from 2035). The fast transportation electrification and energy storage deployment in electric power distribution systems pose many challenges as well as opportunities for New York power industries. The increased EV charging demand and its variability may lead to grid issues, including overloading, voltage flickers, and voltage violation. The ESS provides a potential solution to mitigate these issues.

Student Research Activity: 

(1) collect EV charging demand data and feeder load SCADA measurement data in collaboration with utilities in upstate New York; (2) size the ESS MW and MWhr to mitigate the overload issues due to the proliferation of EVs; (3) with the collected data with the utility feeder circuit, run time-series time simulation in OpenDSS to determine the optimal configuration of ESS (e.g., the power factor) for mitigation of the voltage issues due to EVs. The study will provide guidance on energy storage installation and configurations to mitigate the negative impacts from grid integration of EVs.

Project Description:

Due to progressive energy infrastructure goals in New York State, the future bulk electric system will have a large concentration of renewable generation and energy storage assets. In addition to the generation and storage mix that are prescribed by state policy goals, the electric demand in NY is projected to increase considerably with the growing electric vehicle (EV) industry and electrification of commercial and residential heating.

Student Research Activity:

The student will use Clarkson's NYS Test Bed model to perform electric system generation expansion and production cost analysis to support their research. Additional analysis tools can be used as needed for the project. Guidance on the use of the NYS Test Bed and power system economic dispatch concepts will be provided, and specific experience with optimization problem formulation, mathematical programming, or python are not necessarily required. The modeling tools are open source and students are encouraged to modify or add to them as needed for the project.

Upon completion of the research, students are required to provide insights on the required capabilities of energy storage and flexible emissions-free generation in the future NYS electric grid. These insights shall be presented to Clarkson ECE faculty and should include (locational capacity and ramping) characterization of energy storage and flexible emissions-free generation to meet load with a highly intermittent generation mix, and technology investment or policy solutions that would cost-effectively reduce reliability risk. Students are also encouraged to document their work for potential publication.

Project Description:

Due to progressive energy infrastructure goals in New York State (6,000 MW Energy Storage by 2030, 9,000 MW offshore wind by 2035, and 100% decarbonization of electricity system), carbon emitting power generation technologies will need to be replaced by emissions-free technologies, renewable generation, and energy storage. Building and sustaining such replacement technologies requires out-of-market subsidies and economic incentive that works well within New York's deregulated wholesale market. Some out-of-market subsidies to economically enable replacement technologies exist today, such as Renewable Energy Credits (RECs), the NY-Sun program, and new energy storage build programs. As well, the federal government provides production tax credits (PTCs) and investment tax credits (ITCs) for qualified facilities.

Student Research Activity:

The student will use Clarkson's NYS Test Bed model to perform electric system generation expansion and production cost analysis to support their research. Additional analysis tools can be used as needed for the project. Guidance on the use of the NYS Test Bed and power system economic dispatch concepts will be provided, and specific experience with optimization problem formulation, mathematical programming, or python are not necessarily required. The modeling tools are open source and students are encouraged to modify or add to them as needed for the project.

Upon completion of the research, students are required to provide insights on the required subsidies and market design constructs needed to fulfill NYS policy goals and encourage continued investment in maintaining decarbonization of the future NYS electric grid. These insights shall be presented to Clarkson ECE faculty and should include well-defined options for subsidy and market pricing constructs based on the results of modeling and other research. Students are also encouraged to document their work for potential publication.

Project Description:

Electric vehicles (EVs) are a means to realize transportation electrification and to push forward grid decarbonization. The spatial diffusion of EV depends on the landscape of charging infrastructure, and might reversely influence the decision of siting charging stations. Knowing where the charging stations are and the key factors of siting decisions is critical to predict EV roll-out and the associated charging demand. This project aims at developing models to predict geo-concentration & distribution of EV charging stations. Findings of this project can be used to inform grid capacity planning and resource allocation.

Student research activities:

(1) review parametric models and data-driven algorithms to predict station locations, (2) collect data sets including charging station data, socio-demographic data and other geo-associated variables, (3) apply the model/algorithm to predict geo-concentration and distribution of EV charging stations, (4) visualize the result and present research findings.

Project Description:

This project will focus on the sensing of faults and switching transients on offshore wind farms that are connected to the power grid through AC transmission lines. Offshore wind farms present significant challenges for performance sensing due to the power electronic converters that connect the turbines to the grid, as well as the undersea transmission cables that connect the farm to the onshore substation. The project involves real time simulation of the wind farm installation and the performance of the fault sensing devices based on these simulation results.

Project Description:

This project will be to develop a closed-loop control algorithm for a wind turbine that optimizes the power output of the turbine for time varying wind conditions. A physics based model will be used for the turbine that includes inertia effects of the rotor and varying angle attack effects on the blade torque and thrust. Several different feedback signals will be considered including the voltage and/or current of the generator or the net thrust imposed on rotor. The results of the closed-loop control model will be compared to “perfect” results where there is complete knowledge of the wind signal a-priori.

Project Description:

Vehicle electrification is critical to the clean energy transition. This implementation will be highly dependent on thoughtful policy design that integrates economic, social, and technological concerns. In particular, addressing grid capacity for large scale increases in electric car charging, clear access to charging infrastructure at peak demand periods, and attention to costs and incentives will be critical. Just as importantly, designing policy that addresses increases in EVs will require managing all of these concerns simultaneously.

Student research activities:

The student will assist in the development of data sets, analysis, and policy research to inform a wide variety of different aspects of this research project depending on needs at the time. This will include modeling analyses of different components of EV integration over time, policy analysis and comparisons to assess best practices, and assessments of policy success for current practices in the U.S. and beyond.

Project Description:

New York State has aggressive goals to electrify all passenger and light duty vehicles over the next couple of decades. This transition has many challenges related to charging and electric power infrastructure and EV adoption as a vehicle of choice. But it also provides substantial environmental and health benefits associated with reducing our dependence on inefficient internal combustion engines that use gasoline. These benefits, especially related to air quality and health implications, vary geographically depending on the density of vehicular traffic. This research opportunity will make use of geographic information system (GIS) tools and numerous state and federal databases to explore the distribution of vehicular use across New York and the related emissions. The results will be used to map geographic hot spots for emission-related health impacts. These results will help to identify priority areas to rapidly increase the adoption of EVs and charging infrastructure.