Agent-based learning model for assessing strategic generation investments in electricity markets

Baum, Gabriel; López, Soledad Mochales; Olsina, Fernando; Blanco, Gerardo; Rehtanz, Christian

doi:10.1109/ptc.2017.7980966

Cited by 3 publications

(2 citation statements)

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“…In [49], an ABM has been proposed for generation investment decisions when a GenCo agent doesn't have information about the operational and expansion decisions of the rivals. Reference [50] evaluate investment alternatives of GenCos by considering their expectations of risk and profit. Developed tool can assess performance of Investment Portfolio by linking its experience with electricity market conditions.…”

Section: Investment Decisionsmentioning

confidence: 99%

Agent-Based Models in Electricity Markets: A Literature Review

Shinde

Amelin

2019

2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)

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Section: Investment Decisionsmentioning

confidence: 99%

Agent-Based Models in Electricity Markets: A Literature Review

Shinde

Amelin

2019

2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)

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“…Agent-based modelling (ABM) simulations are a type of simulation where autonomous agents can evolve in a predefined environment to pursue their own strategy while following basic preestablished rules (Ringler et al 2016). Agents only access information from the environment in which they evolve through interactions with other agents (Wang and Paranjape 2017), and have limited knowledge of the overall state of the system (Baum et al 2017). ABM simulations are therefore suited to represent decision making processes in electricity markets which are decentralised with incomplete information availability (Christensen et al 2019).…”

Section: Introductionmentioning

confidence: 99%

An agent-based modelling framework for the simulation of large-scale consumer participation in electricity market ecosystems

Fatras

Jôrgensen

2022

Energy Inform

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The role of consumers as price-sensitive participants in electricity markets is considered essential to ensure efficient and secure operations of electricity systems. Yet the uncertain or unknown consequences of active market participation remain a large barrier for active consumer-side market participation. Simulations are a powerful tool to reduce this uncertainty by giving consumers an insight on the potential benefits and costs of market participation. However, the simulation setup must be adapted to each market context and each consumer market participation strategy. To simplify the simulation development process and improve the comparability of simulation results, this paper proposes a modular yet systematic electricity market modelling framework. The framework applies object-oriented programming concepts for business ecosystem modelling presented in previous works to develop an agent-based model of a consumer-centric electricity market ecosystem. The market ecosystem is represented by a multitude of interacting submarkets with their own logic. Within submarkets, context-independent and context-dependent elements are distinguished to provide model abstraction which can be adapted to different contexts. This framework is illustrated by applying it to three different submarkets in the Western Danish electricity market context: the Nordpool day-ahead market, the Nordpool intraday market, and the Frequency Containment Reserve market. The submarket role abstractions allow to benefit from the commonalities between the analysed submarkets during model implementation, while the role parametrisations allow to quickly adapt the roles to each market context. The implementation of the modelling framework in the Nordic context highlights the benefits of a modular approach in a liberalised and unbundled market context.

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