Bidding Strategies for Flexible and Inflexible Generation in a Power Market Simulation Model

Weidlich, Anke; Künzel, Thomas; Klumpp, Florian

doi:10.1145/3208903.3214347

Cited by 6 publications

(3 citation statements)

References 14 publications

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“…This section presents the bidding strategies for thermal power plants and energy storage units. The bidding strategies formulated here have similarly been presented in [38].…”

Section: Bidding Strategiesmentioning

confidence: 99%

Understanding Power Market Dynamics by Reflecting Market Interrelations and Flexibility-Oriented Bidding Strategies

2022

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Power markets are becoming increasingly complex as they move towards (i) integrating higher amounts of variable renewable energy, (ii) shorter trading intervals and lead times, (iii) stronger interdependencies between related markets, and (iv) increasing energy system integration. For designing them appropriately, an enhanced understanding of the dynamics in interrelated short-term physical power and energy markets is required, which can be supported by market simulations. In this paper, we present an agent-based power market simulation model with rule-based bidding strategies that addresses the above-mentioned challenges, and represents market participants individually with a high level of technical detail. By allowing agents to participate in several interrelated markets, such as the energy-only market, a procurement platform for control reserve and a local heat market representing district heating systems, cross-market opportunity costs are well reflected. With this approach, we were able to reproduce EPEX SPOT market outcomes for the German bidding zone with a high level of accuracy (mean absolute percentage error of 8 €/MWh for the years 2016–2019). We were also able to model negative market prices at the energy-only market realistically, and observed that the occurrence of negative prices differs among data inputs used. The simulation model provides a useful tool for investigating different short-term physical power/energy market structures and designs in the future. The modular structure also enables extension to further related markets, such as fuel, CO2, or derivative markets.

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“…This section presents the bidding strategies for thermal power plants and energy storage units. The bidding strategies formulated here have similarly been presented in [38].…”

Section: Bidding Strategiesmentioning

confidence: 99%

Understanding Power Market Dynamics by Reflecting Market Interrelations and Flexibility-Oriented Bidding Strategies

2022

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“…For example, a plant that successfully sold control reserve capacity needs to operate at a certain generation level, and therefore strives to sell the related output on the energy-only market. Following [17], market participants distinguish two parts of the capacity when formulating their bids: (i) the minimum capacity level which is necessary for avoiding cost-intensive shut-down and later restart, or for fulfilling obligations from previous markets (e. g. the minimum stable output, if the plant has successfully sold positive control reserve), and (ii) the flexible capacity which can be supplied if prices are high enough to make the operation profitable. The corresponding bid price is determined as in [17].…”

Section: B Sequence Of Actionsmentioning

confidence: 99%

“…Following [17], market participants distinguish two parts of the capacity when formulating their bids: (i) the minimum capacity level which is necessary for avoiding cost-intensive shut-down and later restart, or for fulfilling obligations from previous markets (e. g. the minimum stable output, if the plant has successfully sold positive control reserve), and (ii) the flexible capacity which can be supplied if prices are high enough to make the operation profitable. The corresponding bid price is determined as in [17]. The bid price formulation takes into account opportunity costs (based on the price forward curve), possible restart cost (for the minimum capacity level) and variable generation cost (for the flexible capacity).…”

Section: B Sequence Of Actionsmentioning

confidence: 99%

Effects of a Coal Phase-Out on Market Dynamics: Results from a Simulation Model for Germany

Qussous

Künzel

Weidlich

2019

2019 16th International Conference on the European Energy Market (EEM)

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Modeling power market dynamics is increasingly challenging, as both spatial and temporal imbalances of demand and supply are becoming more pronounced with higher shares of variable renewable energy (VRE). Therefore, a high-resolution spatial and temporal distribution of both VRE and conventional generation, as well as the load, is necessary for modeling the effect of policy measures on the electricity market. Besides, technical constraints must be considered in detail, as they fundamentally influence market outcomes. This contribution presents the results and findings from a power market simulation model for the case of the German market zone under different scenarios phasing out coal-fired power generation. It is shown that the developed spatially resolved model can realistically reproduce market outcomes and is, therefore, suitable for the analysis of future scenarios with increased VRE integration and reduced conventional generation capacity.

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ElecSim

Kell

Forshaw

McGough

2019

Proceedings of the Tenth ACM International Conference on Future Energy Systems

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Due to the threat of climate change, a transition from a fossil-fuel based system to one based on zero-carbon is required. However, this is not as simple as instantaneously closing down all fossil fuel energy generation and replacing them with renewable sources -careful decisions need to be taken to ensure rapid but stable progress. To aid decision makers, we present a new tool, ElecSim, which is an open-sourced agent-based modelling framework used to examine the effect of policy on long-term investment decisions in electricity generation. ElecSim allows non-experts to rapidly prototype new ideas. Different techniques to model long-term electricity decisions are reviewed and used to motivate why agent-based models will become an important strategic tool for policy. We motivate why an open-source toolkit is required for long-term electricity planning.Actual electricity prices are compared with our model and we demonstrate that the use of a Monte-Carlo simulation in the system improves performance by 52.5%. Further, using ElecSim we demonstrate the effect of a carbon tax to encourage a low-carbon electricity supply. We show how a £40 ($50) per tonne of CO 2 emitted would lead to 70% renewable electricity by 2050. CCS CONCEPTS• Computing methodologies → Modeling methodologies; Model verification and validation; Modeling methodologies.

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Bidding Strategies for Flexible and Inflexible Generation in a Power Market Simulation Model

Cited by 6 publications

References 14 publications

Understanding Power Market Dynamics by Reflecting Market Interrelations and Flexibility-Oriented Bidding Strategies

Understanding Power Market Dynamics by Reflecting Market Interrelations and Flexibility-Oriented Bidding Strategies

Effects of a Coal Phase-Out on Market Dynamics: Results from a Simulation Model for Germany

ElecSim

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