Abstract
In the electricity market, different pricing models can be applied to increase market competitiveness. Different electricity systems use different market structures. Uniform marginal pricing, zonal marginal pricing, and nodal marginal pricing methods are commonly used market structures. For markets wishing to move from a uniform pricing structure to a more competitive zonal pricing structure, the determination of price zones is critical for achieving a competitive market that generates accurate price signals. Three different pricing zone detection algorithms are analyzed in this paper including the k-means clustering and queen/rook spatially constraint clustering. Finally, the results of a case study for the Turkish electricity system are shared to compare each method.
Highlights
IntroductionDetermination of Price Zones duringTransition from Uniform to ZonalElectricity Market: A Case Study for Turkey
While designing a national electricity market, which is generally built on creating a single national price in the first place, deepen with the transition to zonal or locational pricing methods and create a more competitive structure
This paper describes three clustering methods that might be used in zone detection for a power market in the transition from a uniform price to a zonal price mechanism in the day-ahead electricity market
Summary
Determination of Price Zones duringTransition from Uniform to ZonalElectricity Market: A Case Study for Turkey. Electricity Market: A Case Study for Turkey. Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations
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