“…Frequently, the benchmark is the nodal market design as first-best solution (e.g. [Ehrenmann and Smeers 2005;Bjørndal and Jörnsten 2001;Bjørndal and Jörnsten 2007;Oggioni and Smeers 2013;Grimm et al 2016;Grimm et al 2017]). Some of these studies [Ehrenmann and Smeers 2005;Bjørndal and Jörnsten 2001;Bjørndal and Jörnsten 2007;Oggioni and Smeers 2013] also assume or determine alternative PZCs for their stylized examples.…”
Part I of this two-part paper has presented flow-based market coupling (FBMC), the implicit congestion management method used to couple the Central Western European (CWE) electricity markets. It has also introduced a large-scale model framework for FBMC assessments, focusing on modeling the capacity allocation and market clearing processes. The paper at hand lays the focus on the newly developed redispatch model, thereby completing the description of the overall model framework. Furthermore, we provide a case study assessing improved price zone configurations (PZCs) for the extended CWE electricity system. Our case study is motivated by the ineffectiveness of managing congestion of intra-zonal lines described in Part I and by the possibility to reduce their relevance by improved PZCs. The importance of this study is substantiated by the controversial discussions on the currently-existing PZC. Thus, we assess the existing PZC and five novel PZCs determined by a cluster algorithm. Our results show that improved PZCs can reduce redispatch quantities and overall system costs significantly. Notably, we show that substantial improvements are possible when redesigning PZCs while maintaining a similar or slightly increased number of price zones. Moreover, under use of the theoretical considerations in Part I, we explain that increasing the number of price zones may not always increase welfare when using FBMC.
“…Frequently, the benchmark is the nodal market design as first-best solution (e.g. [Ehrenmann and Smeers 2005;Bjørndal and Jörnsten 2001;Bjørndal and Jörnsten 2007;Oggioni and Smeers 2013;Grimm et al 2016;Grimm et al 2017]). Some of these studies [Ehrenmann and Smeers 2005;Bjørndal and Jörnsten 2001;Bjørndal and Jörnsten 2007;Oggioni and Smeers 2013] also assume or determine alternative PZCs for their stylized examples.…”
Part I of this two-part paper has presented flow-based market coupling (FBMC), the implicit congestion management method used to couple the Central Western European (CWE) electricity markets. It has also introduced a large-scale model framework for FBMC assessments, focusing on modeling the capacity allocation and market clearing processes. The paper at hand lays the focus on the newly developed redispatch model, thereby completing the description of the overall model framework. Furthermore, we provide a case study assessing improved price zone configurations (PZCs) for the extended CWE electricity system. Our case study is motivated by the ineffectiveness of managing congestion of intra-zonal lines described in Part I and by the possibility to reduce their relevance by improved PZCs. The importance of this study is substantiated by the controversial discussions on the currently-existing PZC. Thus, we assess the existing PZC and five novel PZCs determined by a cluster algorithm. Our results show that improved PZCs can reduce redispatch quantities and overall system costs significantly. Notably, we show that substantial improvements are possible when redesigning PZCs while maintaining a similar or slightly increased number of price zones. Moreover, under use of the theoretical considerations in Part I, we explain that increasing the number of price zones may not always increase welfare when using FBMC.
“…In contrast to the second stream, authors set up optimization problems to identify optimal PZCs rather than using heuristics based on approximate criteria. (Grimm et al, 2017) formulate a three-level problem that includes the configuration of PZs on the first level while on the second and third level the DA market and RD measures are optimized. In (Bjørndal and Jörnsten, 2001) authors also formulate an optimization problem.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Moreover, the application on a large-scale system of such optimizations problems with thousands of nodes is computationally too challenging (Felling and Weber, 2018;Breuer, 2014). Thus, (Grimm et al, 2017) investigate networks with only up to 28 nodes. The proposed optimization problem in (Bjørndal and Jörnsten, 2001) remains unsolved.…”
Section: Literature Reviewmentioning
confidence: 99%
“…Figure 1 presents a general overview of the problem structure. In chronological order and as presented in (Grimm et al, 2017), the problem can be formulated as a three-level problem as visualized on the left-hand side in Figure 1. At first, a regulator decides on a PZC.…”
Section: Problem Structurementioning
confidence: 99%
“…This enables a combination of the third and first level to a new first level, a so-called "system perspective". A similar approach is also used in (Grimm et al, 2017). The newly restructured two-level problem is presented on the right-hand side of Figure 1.…”
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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