A New Model to Simulate Local Market Power in a Multi-Area Electricity Market: Application to the European Case

Abstract

The work presented in this article proposes an original method that models the medium-term market equilibrium under imperfect competition circumstances in multi-area electricity systems. It provides a system analysis considering multiple market splitting possibilities, where local market power may appear according to the status of the interconnections. As a result of new policies and regulations, power systems are increasingly integrating the existing electricity markets in unified frameworks. The integration of electricity markets poses highly challenging tasks due to the uncertainty that comes from the agents’ strategic behaviors which depend on multiple factors, for instance, the state of the interconnections. When it comes to modeling these effects, the purpose is to identify each strategy by using conjectured-price responses that depend on the different states of the system. Consequently, the problem becomes highly combinatorial, which heightens its size as well as its complexity. Therefore, the purpose of this work’s methodology is the reduction of the possible network configurations so as to ensure a computational tractability in the problem. In order to validate this methodology, it has been put to the test in a realistic and full-scale two-year operation planning model of the European electricity market that consists of a group of nine countries.

Temporal aggregation for large‐scale multi‐area power system models

“…The temporal structure resulting from the clustering procedure is applied to the formulation of a fundamental optimization model. For this purpose, a similar model to the one presented in [25] is used. This section is intended to provide a brief description of the formulation of the model as well as its integration together with the clustering process presented above.…”

“…As stated in [8], and later extended in [25] to account for several areas, the market equilibrium is found with the following quadratic optimization problem (1)–(4): $$\begin{equation} \begin{split} \mathop {\min }\limits _{{Q_{e,a,p}},f_{l,p}} \sum \limits _{e,a,p}& \left(\vphantom{\sum \limits _{a^\prime }}C_{e,a,p}(Q_{e,a,p})\right.\\ + &\left.\sum \limits _{a^\prime } {\dfrac{{{\theta _{e,a,a^\prime ,p}}}}{2}{Q_{e,a,p}}{Q_{e,a^\prime ,p}}} + {S_{e,a,p}}{Q_{e,a,p}}\right) \end{split} \end{equation}$$…”

“…In this case, through the use of conjectures, it is possible to have a more realistic representation of the outcome of the system, when strategic behaviours are present among market participants. As discussed in [25], considering these strategies is particularly important in multi‐area systems, since the exercise of market power in certain regions may be determined to a great extent by the status of the interconnections.…”

“…As stated in [8], and later extended in [25] to account for several areas, the market equilibrium is found with the following quadratic optimization problem (1)-( 4…”

A Systematic Review of European Electricity Market Design Options

“…A model to calculate market equilibrium and to simulate local market power under non-perfect competition in a transboundary electricity system is proposed and implemented in a case study of the Central Western European (CWE) and Iberian electricity markets in Ref. [71]. The market equilibrium model is Conjectural-Variation-based, in which companies make a conjecture about the reaction of their competitors when they change their price or quantities.…”