A Methodology for Determining the Appropriate Level of Power Flow Model Detail

The rapid changes in the electric power grid highlight the need for newly addressing them when planning and designing the power system for more accurate and reliable system operation and management. Improvement of power flow analysis is necessary since it can provide planners and operators with a full understanding of the current and future electric grid. Two main transitions are needed to be considered for better power flow analysis. The first one is increasing uncertainty due to the high penetration of renewable energy, drastic climate change, and rising demand. Another one is the introduction of new power grid models that can be used in the power flow. However, as is common to all engineering analysis tools, there are trade-off issues in including a lot of amount of details into the power flow such as the computational complexity, the availability of the model information, the ultimate impact of the models on the results, etc. Therefore, it is not an easy task to determine what details should be included in the power flow. This work develops an algorithm that determines the level of detail of complex electric grid models that should be included in the power flow. The significant role of transformer impedance correction tables, generator capability curves, and explicit parameters in the power flow is validated and they are considered for the trade-off model applications. The basic concept of the proposed algorithm is that the most impactful electric components in the grid that greatly influence the power flow are selectively updated with those accurate electric grid models. While this method can efficiently aid in obtaining more precise and optimal power flow solutions, it can help to avoid possible trade-off issues such as heavy computational burdens, divergence, and low availability. For the ranking determination of the critical electric elements, sensitivity analysis is conducted to measure how changing each of the inputs of interest independently impacts the solution. In order to comprehensively assess each element’s influence, various scenarios with different degrees of uncertainty are tested. A chronological power system operation simulation framework is presented in this work. It includes a full process of developing synthetic load and explicit weather time series data and generating representative scenarios with diverse uncertainty levels as input data for the ranking determination. After adding accurate model information to the critical elements based on the ranking results, the proposed updated case’s performance is evaluated using the trade-off validation method. Since the considered accurate electric grid models involve trade-off characteristics, diverse and opposite decision criteria such as accuracy, reliability, and efficiency are looked at to ensure that the proposed method provides balanced performance. For comparison, two different alternatives are also created and their performances are evaluated. The alternatives include an original case that does not include any detailed model information in the power flow and a fully updated case that considers every detailed model information for the power flow.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Electrical Engineering

Grantor

Texas A&M University

Year dc:date.issued

2023

Author dc:creator

• Yeo, Ju Hee

Advisor dc:contributor.advisor

• Overbye, Thomas

Committee members dc:contributor.committeemember

• Davis, Katherine
• Davis, Timothy
• Zou, Jun

• power flow
• electric grid model
• uncertainty
• parameter ranking
• sensitivity analysis

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/1969.1/198919

OAI record oai:identifier

https://oaktrust.library.tamu.edu/server/oai/request?verb=GetRecord&metadataPrefix=dim&identifier=oai%3Aoaktrust.library.tamu.edu%3A1969.1%2F198919