
NSF Org: |
ECCS Division of Electrical, Communications and Cyber Systems |
Recipient: |
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Initial Amendment Date: | September 20, 2019 |
Latest Amendment Date: | July 25, 2023 |
Award Number: | 1952683 |
Award Instrument: | Standard Grant |
Program Manager: |
Aranya Chakrabortty
ECCS Division of Electrical, Communications and Cyber Systems ENG Directorate for Engineering |
Start Date: | July 1, 2019 |
End Date: | September 30, 2023 (Estimated) |
Total Intended Award Amount: | $472,601.00 |
Total Awarded Amount to Date: | $472,601.00 |
Funds Obligated to Date: |
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History of Investigator: |
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Recipient Sponsored Research Office: |
201 MULLICA HILL RD GLASSBORO NJ US 08028-1702 (856)256-4057 |
Sponsor Congressional District: |
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Primary Place of Performance: |
NJ US 08028-1701 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): | EPCN-Energy-Power-Ctrl-Netwrks |
Primary Program Source: |
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Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.041 |
ABSTRACT
In response to the urgent need to improve societal capabilities to withstand and recover from major natural or man-made catastrophic events, community microgrids are designed to provide sustainable and resilient electric energy supply for critical services. With increased penetration of community microgrids and distributed energy resources, distribution systems are transforming from traditionally passive radial networks operated by a single utility to more sophisticated active networked topologies with multiple autonomic entities. This transformation in distribution systems has resulted in a need to reshape the way electricity services are delivered and distribution systems are designed and managed. To address these challenges, this CAREER project will investigate new approaches for comprehensive modeling of distinct characteristics of emerging distribution systems with a proliferation of community microgrids, and explore optimal operation strategies for enhancing the sustainability and resiliency of distribution systems. Specifically, a two-tier hierarchical restructuring framework is proposed for guiding the optimal operation and coordination of distribution systems and community microgrids, with special focus on investigating fundamental market clearing mechanisms and efficient computation tools. Results from this research could facilitate the optimal design of future fully liberalized retail distribution markets and related energy policies, and guide the active participation of microplayer-like electricity prosumers (producer-consumers) in such distribution-level markets. The research efforts will be complemented by an education and outreach plan aimed at increasing public awareness and understanding of the complexity of distribution systems restructuring, and to prepare the next generation workforce with needed skills to meet the needs of the power industry.
Both physical feasibility and financial viability of individual autonomic entities are key to the successful implementation of distribution system restructuring and retail electricity markets. This project will address such challenges via five integrated research and educational activities, namely: (i) Exploring market operation and pricing mechanisms for distribution system operators based on comprehensive unbalanced three-phase alternating current optimal power flow models and efficient computation methods. The proposed per-phase nodal distribution locational marginal pricing concept can effectively incentivize the continued participation of various distribution customers in retail electricity markets; (ii) Investigating market operation and pricing mechanisms for community microgrid operators based on comprehensive unbalanced three-phase alternating current unit commitment models and efficient computation methods. The proposed per-phase nodal community locational marginal pricing concept can effectively coordinate heterogeneous community partners under both grid-connected and islanded operation modes, and incentivize their continued participation in community microgrids. Flexibilities of typical community microgrid partners are also investigated to help guide their strategic bidding in community microgrids; (iii) Addressing major research questions via the proposed models and computation methods to further promote the implementation of distribution systems restructuring; (iv) Validating the proposed research in simulated and realistic system models; and (v) Exploring knowledge and skill requirements for the sustainable operation and effective restructuring of emerging distribution systems and community microgrids, and investigating education and training needs for retooling existing power engineering programs and curricula.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Recognizing the ongoing energy system transition attributed to the increasing penetration of different distributed energy resources (DERs) and systems, this CAREER project aims to investigate new modeling and computation approaches as well as business models for the optimal operation of emerging electricity distribution systems, explore a feasible distribution system restructuring framework, and ultimately enhance the sustainability and resiliency of the electric grid in the face of emerging challenges. During the entire period of this CAREER project, the PI worked 2.5 years at Clarkson University, and 4 years at Rowan University on this project. In total, four Ph.D. students (one in Clarkson and three in Rowan), three M.S. students (two in Clarkson and one in Rowan), and a large group of undergraduate students (mainly in Rowan) are supported by and involved in this project to conduct the proposed research activities. Specifically, the major research outcomes include:
1. Detailed and rigorous mathematical modeling for future power distribution system short-term operations, together with a suite of high-performance computation methods, are designed and developed to support the efficient and effective retail electricity market clearing and energy trading mechanisms.
2. Advanced and coordinated hierarchical control mechanisms (including tertiary economic operation, secondary automatic generation control, and primary droop control) are investigated, developed, and simulated for enabling the actual implementation of economic and secure microgrid/distribution system operations considering the increasing penetration of DERs (including photovoltaics, battery energy storages, and supercharging stations, etc.), as well as their interactions with the transmission systems. Furthermore, data-driven transient stability evaluation of future distribution systems is explored.
3. Advanced artificial intelligence/machine learning techniques are explored for supporting enhanced community microgrid operations, establishing market trading/clearing business models of residential/retail electricity markets, and investigating their interaction with the wholesale market to assist the execution of FERC order 2222.
The educational objective of this CAREER project is to explore knowledge and skill requirements for the sustainable operation and effective restructuring of emerging electricity distribution systems, and to investigate education and training needs for retooling existing power engineering programs and curricula. In addition to the training of Ph.D., M.S., and undergraduate students, a set of undergraduate and graduate level courses and certificates are designed, developed, and offered in both Clarkson University and Rowan University to promote power engineering education, for addressing the industry challenges of lack of qualified workforce.
Last Modified: 01/15/2024
Modified by: Jie Li
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