An approach for establishing a common grid model for flow-based market mechanism simulations

The discussions on the development of an electricity market model for accommodating cross-border cooperation remains active in Europe. The main interest is the establishment of market couplings without curtailing the fair use of the scarce transmission capacity. However, it is difficult to gain mutu...

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Bibliographic Details
Main Authors: See, Phen Chiak, Fosso, Olav Bjarte, Wong, Kuan Yew, Molinas, Marta
Format: Article
Published: China Electric Power Research Institute 2019
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Online Access:http://eprints.utm.my/id/eprint/89181/
http://dx.doi.org/10.17775/CSEEJPES.2018.01270
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Summary:The discussions on the development of an electricity market model for accommodating cross-border cooperation remains active in Europe. The main interest is the establishment of market couplings without curtailing the fair use of the scarce transmission capacity. However, it is difficult to gain mutual consensus on this subject because of the absence of convincing simulation results for the entire region. To achieve that, researchers need a common grid model (CGM) which is a simplified representation of the detailed transmission model which comprises aggregated buses and transmission lines. A CGM should sufficiently represent the inter-area power flow characteristics. Generally, it is difficult to establish a standard CGM that represents the actual transmission network with a sufficient degree of exactness because it requires knowledge on the details of the transmission network, which are undisclosed. This paper addresses the issue and reviews the existing approaches in transmission network approximation, and their shortcomings. Then, it proposes a new approach called the adaptive CGM approximation (ACA) for serving the purpose. The ACA is a data-driven approach, developed based on the direct current power flow theory. It is able to construct a CGM based on the published power flow data between the inter-connected market areas. This is done by solving the issue as a non-linear model fitting problem. The method is validated using three case studies.