Identification of the Efficiency Gap by Coupling a Fundamental Electricity Market Model and an Agent-Based Simulation Model

Abstract

A reliable and cost-effective electricity system transition requires both the identification of optimal target states and the definition of political and regulatory frameworks that enable these target states to be achieved. Fundamental optimization models are frequently used for the determination of cost-optimal system configurations. They represent a normative approach and typically assume markets with perfect competition. However, it is well known that real systems do not behave in such an optimal way, as decision-makers do not have perfect information at their disposal and real market actors do not take decisions in a purely rational way. These deficiencies lead to increased costs or missed targets, often referred to as an “efficiency gap”. For making rational political decisions, it might be valuable to know which factors influence this efficiency gap and to what extent. In this paper, we identify and quantify this gap by soft-linking a fundamental electricity market model and an agent-based simulation model, which allows the consideration of these effects. In order to distinguish between model-inherent differences and non-ideal market behavior, a rigorous harmonization of the models was conducted first. The results of the comparative analysis show that the efficiency gap increases with higher renewable energy shares and that information deficits and policy instruments affect operational decisions of power market participants and resulting overall costs significantly.

Profitability of Power-to-Heat-to-Power Storages in Scenarios With High Shares of Renewable Energy

“…We apply the open agent-based electricity market model AMIRIS [7] in order to simulate the German dayahead market. AMIRIS investigates market dynamics caused by the interactions of market actors, taking into account political frameworks [8,9] and actors' behavior under uncertainty [10,11]. For this purpose, agent-based modeling, which has its origins in artificial intelligence research, offers a powerful approach, since the actors with their perceptions and action patterns are at the center of modeling.…”

Integrating System and Operator Perspectives for the Evaluation of Power-to-Gas Plants in the Future German Energy System

“…One continuing challenge in interdisciplinary energy system research is the coupling of models [11]. Additionally, the identification of business models for power-to-gas plant operators remains challenging [9,12,13].…”

Self-Reinforcing Electricity Price Dynamics under the Variable Market Premium Scheme

“…For the simulation-based analyses we used the model AMIRIS (Agent-based Market model for the Investigation of Renewable and Integrated energy Systems) [21][22][23][24], an agent-based wholesale electricity market model for Germany. The model allows studying the impact of energy policy instruments on the economic performance of power plant operators and marketers.…”

“…Instead, the simulation results were generated from the interplay of the actions of the individual actors depicted as agents under selected regulatory conditions. Further information and a model scheme are provided in Appendix A.1 and in [21][22][23][24].…”

“…The storage operators have a special role in AMIRIS in so far as they can carry out arbitrage transactions as independent traders on the energy exchange on the one hand, but can also be used by direct marketers to reduce the balancing energy demand caused by forecasting errors on the other hand [21]. The agent-based simulation AMIRIS is heavily based on the Open-Source framework FAME.…”