The scheme of a novel methodology for zonal division based on power transfer distribution factors

Klos, Michal; Wawrzyniak, Karol; Jakubek, Marcin; Orynczak, Grzegorz

doi:10.1109/iecon.2014.7049033

Cited by 18 publications

(9 citation statements)

References 7 publications

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“…Further algorithms based on LMPs are applied in (Wawrzyniak et al, 2013;Imran and Bialek, 2008). In contrast to the LMP-based methodology, cluster algorithms based on PTDFs are applied by (Bergh et al, 2016;Sarfati et al, 2015;Klos et al, 2014;Kang et al, 2013;Wawrzyniak et al, 2013;Duthaler et al, 2012). (Bergh et al, 2016) also investigate improved PZCs for CWE and Italy, Czech Republic and Poland.…”

Section: Literature Reviewmentioning

confidence: 99%

Solving the Bi-level Problem of a Closed Optimization of Electricity Price Zone Configurations using a Genetic Algorithm

Felling

2019

SSRN Journal

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The topic of alternative price zone configurations is frequently discussed in Central Western Europe where-so far-national borders coincide with borders of price zones. Reconfiguring these price zones is one option in order to improve congestion management, foster trading across borders of price zones and, thus, to increase welfare. In view of the significant increase in redispatch volumes and costs over the last years due to increasing feed-in from renewable energy sources in conjunction with delayed grid expansion, this topic has gained in importance. To determine these improved price zone configurations for a large-scale system like Central Western Europe, often either configurations based on expert guesses are considered or heuristics using approximate criteria like locational marginal prices are used to obtain price zones through clustering. In contrast, the present paper formulates a bi-level optimization problem of how to determine optimal configurations in terms of system costs and-given the size and nature of the problem-solves it with a specially developed genetic algorithm. Resulting price zone configurations are compared to both exogenously given, expert-based price zone configurations from the Entso-E bidding zone study and endogenously assessed configurations from a hierarchical cluster algorithm. Results show that the genetic algorithm achieves best results in terms of system costs. Moreover, the comparison with solutions from a hierarchical cluster analysis reveals important drawbacks of the latter methodology.

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Section: Literature Reviewmentioning

confidence: 99%

Solving the Bi-level Problem of a Closed Optimization of Electricity Price Zone Configurations using a Genetic Algorithm

Felling

2019

SSRN Journal

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“…In contrast to the LMP-method (Duthaler, 2012), (Kang et al, 2013), (Klos et al, 2014), (Kłos et al, 2015), (Sarfati et al, 2015) and (Bergh et al, 2016) apply cluster algorithms based on PTDF-values. (Kłos et al, 2015) aim to reduce loop effects by clustering PTDF values.…”

Section: Investigate Zonal Solutions Based Onmentioning

confidence: 99%

“…The authors cluster PTDF values on selected critical branches and, after investigating a base scenario, analyse several delimitations with different amounts of price zones. (Klos et al, 2014) identify critical branches using a clustering based on KKT-multipliers first and cluster PTDFvalues afterwards. (Kang et al, 2013) investigate the IEEE-39 system for a given number of zones.…”

Section: Investigate Zonal Solutions Based Onmentioning

confidence: 99%

Consistent and robust delimitation of price zones under uncertainty with an application to Central Western Europe

Felling

2018

Energy Economics

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New and alternative delimitations of price zones for Central Western Europe (CWE) might constitute a mid-term solution to cope with the increasing congestion in the electricity transmission grids. The significantly growing infeed from renewable energy sources puts more and more pressure on the grid and emphasizes the need for improved congestion management. Thus, a new delimitation of price zones is frequently considered in current discussions and research. The present paper applies a novel hierarchical cluster algorithm that clusters locational marginal prices and weights nodes depending on their demand-and supply situation to identify possible new price zone configurations. The algorithm is applied in a scenario analysis of six scenarios reflecting main drivers that influence the future development of European Electricity markets in line with the trilemma of energy policy targets. Robustness of the new configuration is an important criterion for price zone configurations according to the European Guideline on Capacity Allocation and Congestion Management (CACM). Therefore, a robust price zone configuration is computed taking into account all the six individual scenarios. Results show that shape, size and price variations of price zones on the one hand strongly depend on the individual scenario. On the other hand, the identified robust configuration is shown to outperform other configurations, particularly also the current price zone configuration in CWE.

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“…Yet studies have also shown the substantial effects of congestion management and have reported more frequent zero and negative prices in the more peripherical northern areas of Germany. With regard to our investigation, the considered studies essentially deal with two aspects: the computation of robust configurations with different cluster algorithms (Burstedde 2012;Kang et al 2013;Breuer and Moser 2014;Klos et al 2014) and the analysis of the system's effects with exogenously given bidding zones (Trepper et al 2015;Egerer et al 2016;Blume-Werry et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Spatial Incentives for Power-to-Hydrogen through Market Splitting

2022

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The scheme of a novel methodology for zonal division based on power transfer distribution factors

Cited by 18 publications

References 7 publications

Solving the Bi-level Problem of a Closed Optimization of Electricity Price Zone Configurations using a Genetic Algorithm

Solving the Bi-level Problem of a Closed Optimization of Electricity Price Zone Configurations using a Genetic Algorithm

Consistent and robust delimitation of price zones under uncertainty with an application to Central Western Europe

Spatial Incentives for Power-to-Hydrogen through Market Splitting

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