Agent-Based Models in Electricity Markets: A Literature Review

Shinde, Priyanka; Amelin, Mikael

doi:10.1109/isgt-asia.2019.8880889

Cited by 7 publications

(2 citation statements)

References 45 publications

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“…This approach allows ABMs to capture the emergent behavior of groups arising from the sum of each individual agent's decision making and their interactions with other agents. Because of their ability to capture emergent phenomena, which are difficult to model using top-down approaches, ABMs are considered the best tool to simulate behavior in financial markets [217][218][219], including electricity markets [220]. In models of electricity markets, ABMs are typically used to simulate either participation in electricity markets [97,147,148,163,[221][222][223] or optimization of household electricity demand according to defined goals [137,194,[224][225][226].…”

Section: Types Of Behavior Modelsmentioning

confidence: 99%

Demand Side Management in Industrial, Commercial, and Residential Sectors: A Review of Constraints and Considerations

et al. 2023

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Demand Side Management (DSM) is a cost-effective approach to managing electricity networks, aimed at reducing capacity requirements and costs, increasing the penetration of renewable generation, and reducing power system emissions. This review article explores the distinctive characteristics of electricity demand in the industrial, commercial, and residential sectors, and their relationship to successful implementation of DSM. The constraints and considerations for DSM are characterized as technical, economic, and behavioral factors, such as process requirements, business operation constraints, and consumer decisions, respectively. By considering all three types of factors and their impacts in each sector, this review contributes novel insights that can inform the future implementation of DSM. DSM in the industrial and commercial sectors is found to be primarily constrained by technical considerations, while DSM in the commercial sector is also subject to economic constraints. Conversely, residential demand is found to be primarily constrained by human behavior and outcomes, highly variable, and the largest contributor to peak demand. This review identifies sector-specific opportunities to enhance DSM uptake. Industrial DSM uptake will benefit from technological and process improvements; commercial DSM uptake can benefit from enhanced economic incentivization; and residential DSM uptake can benefit from improved understanding of the interactions between human behavior, human outcomes, and energy use. Finally, this review investigates behavioral models and concludes that agent-based models are best suited for integrating these interactions into energy models, thereby driving the uptake of DSM, particularly in the important residential sector.

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Section: Types Of Behavior Modelsmentioning

confidence: 99%

Demand Side Management in Industrial, Commercial, and Residential Sectors: A Review of Constraints and Considerations

et al. 2023

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“…Some recent research work on agent-based modeling includes [27][28][29][30][31]. A literature review of contemporary ABMs in different electricity markets can be found in [32]. However, none of the aforementioned ABMs is well suited for modeling the European CID market since the trading mechanism (limit order book) and the rules are not explicitly considered.…”

Section: Related Workmentioning

confidence: 99%

Analyzing Trade in Continuous Intra-Day Electricity Market: An Agent-Based Modeling Approach

et al. 2021

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In recent years, the vast penetration of renewable energy sources has introduced a large degree of uncertainty into the power system, thus leading to increased trading activity in the continuous intra-day electricity market. In this paper, we propose an agent-based modeling framework to analyze the behavior and the interactions between renewable energy sources, consumers and thermal power plants in the European Continuous Intra-day (CID) market. Additionally, we propose a novel adaptive trading strategy that can be used by the agents that participate in CID market. The agents learn how to adapt their behavior according to the arrival of new information and how to react to changing market conditions by updating their willingness to trade. A comparative analysis was performed to study the behavior of agents when they adopt the proposed strategy as opposed to other benchmark strategies. The effects of unexpected outages and information asymmetry on the market evolution and the market liquidity were also investigated.

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Representation of uncertainty in market models for operational planning and forecasting in renewable power systems: a review

et al. 2023

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As the power system is becoming more weather-dependent and integrated to meet decarbonization targets, the level and severity of uncertainty increase and inevitably introduce higher risk of demand rationing or economic loss. This paper reviews the representation of uncertainty in power market models for operational planning and forecasting. A synthesis of previous reviews is used to find the prevalence of stochastic tools in power and energy system applications, and it concludes that most approaches are deterministic. A selection of power market tools handling uncertainty is reviewed in terms of the uncertain parameters they capture, and the methods used to describe them. These all use probabilistic methods and typically cover weather-related uncertainty, including demand. Random outages are also covered by several short-term power market models, while uncertainty in fuel and CO$$_2$$ 2 emission prices were generally not found to be included, nor other types of uncertainty. A gap in power market models representing multiple dimensions of uncertainty, solvable on a realistic, large-scale system in a reasonable time, is identified. The paper concludes with a discussion on topics to address when representing uncertainty, where the main challenges are that uncertainty can be difficult to describe and quantify, and including uncertainty adds additional complexity and computational burden to the problem.

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Agent-Based Models in Electricity Markets: A Literature Review

Cited by 7 publications

References 45 publications

Demand Side Management in Industrial, Commercial, and Residential Sectors: A Review of Constraints and Considerations

Demand Side Management in Industrial, Commercial, and Residential Sectors: A Review of Constraints and Considerations

Analyzing Trade in Continuous Intra-Day Electricity Market: An Agent-Based Modeling Approach

Representation of uncertainty in market models for operational planning and forecasting in renewable power systems: a review

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