Integrated transmission-distribution systems modeling framework to support grid edge technologies

With the advancements in sensing, control & computing technologies, the integration of distribution system resources (such as, solar PV, electric vehicles etc.,) in transmission system operations, markets & planning is considered viable by regulatory bodies, system operators, and other stakeholders. The recent trends in the power industry (policy reforms & new business models) incline towards facilitating the aggregated distribution resource participation in wholesale markets and models inclusive of distributed resources when performing transmission system studies. However, this is limited by, (i) existing policies/practices that restrict data sharing between different stakeholders across the transmission & distribution systems & (ii) lack of a framework that considers these when modeling distributed resource management. This work aims to develop a framework for effective management of distributed energy resources that considers both system & stakeholder (system operators, customers etc.,) perspective. To address these concerns, a new clustering technique and resource allocation algorithm for aggregator formation and aggregator level demand scheduling respectively, are proposed in this work. These proposed techniques consider the system perspective along with customer privacy and preference. Also, a loosely coupled integrated transmission & distribution analysis is developed for an effective impact assessment of proposed techniques on both the systems. In addition, a power flow tracing tool for transmission system is also developed to assess the contribution of transmission node level injection to loads & line flows. The proposed techniques are implemented on combination of real Midwest network & synthetic test system and the results are compared with existing methods are presented in this dissertation. These tools would help utilities to assess the locational impact of distributed resources and indicate potential sites to incentivize customers to participate in aggregator-based schemes.

Author

• Manoharan, Arun Kaarthick

Identifier

hdl:10057/25410

OAI identifier oai:identifier

oai:soar.wichita.edu:10057/25410