Artificial neural network approach for revealing market competitors’ behaviour

Kiannejad, Mohammad; Salehizadeh, Mohammad Reza; Buygi, Majid Oloomi; Shafie‐khah, Miadreza

doi:10.1049/iet-gtd.2019.1612

Cited by 13 publications

(12 citation statements)

References 14 publications

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“…As an example in this manner, the study in [36] including the aggregation of residential end-users including solar power and battery units to enable demand side flexibility provision can be given as an example. Besides, there are also some studies including the artificial intelligence based assessment of market participants such as in [37] and [38]. However, even the mentioned last two groups of studies have also relevance to the portfolio aggregation and bidding approaches, no more emphasis on further literature presentation for these groups is given as they are not fully parallel to the concept of this study.…”

Section: Relevant Backgroundmentioning

confidence: 97%

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Risk-averse optimal bidding strategy for a wind energy portfolio manager including EV parking lots for imbalance mitigation

Çiçek¹,

Erdinç²

2021

Turk J Elec Eng & Comp Sci

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In this study, an optimal bidding strategy for a wind energy portfolio manager (WEPM) including electric vehicle parking lots (EVPLs) that aims to maximize profits by trading in the day-ahead (DA) market and balancing market (BM) and through bilateral contracts, taking into account line capacities and risk management is proposed. The mentioned structure is modeled in Mixed-Integer Linear Programming (MILP) framework, and the uncertainties regarding electric vehicle (EV) behavior, electricity market data, wind power generation are captured via a stochastic approach. To demonstrate the effectiveness of the model, several case studies are carried out considering Sweden and Turkey electricity market prices with different risk aversion factors and bilateral contract situations. In this manner, the important results as well as useful findings regarding the economic impacts of the proposed concept are analyzed in detail.

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Section: Relevant Backgroundmentioning

confidence: 97%

“…The Eq. (36) is used to assign the energy states of EVs when they arrive at EVPL, while Eq (37). ensures that the EVs leave the EVPL with the desired energy states.…”

mentioning

confidence: 99%

Risk-averse optimal bidding strategy for a wind energy portfolio manager including EV parking lots for imbalance mitigation

Çiçek¹,

Erdinç²

2021

Turk J Elec Eng & Comp Sci

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“…To unveil future power market competition situations, many studies have been proposed to infer or predict aggregate supply curves (ASCs) or residual demand curves (RDCs). For example, a Bayesian inference approach is developed based on Markov chain Monte Carlo and sequential Monte Carlo methods, which can be used to infer ASC in day-ahead power markets [120] . Later, a feedforward neural network method is developed to predict ASCs.…”

Section: Information Acquisition Enhancementmentioning

confidence: 99%

The competition and equilibrium in power markets under decarbonization and decentralization

Chen

Fang

Guo

et al. 2022

iEnergy

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Equilibrium analysis has been widely studied as an effective tool to model gaming interactions and predict market results. However, as competition modes are fundamentally changed by the decarbonization and decentralization of power systems, analysis techniques must evolve. This article comprehensively reviews recent developments in modelling methods, practical settings and solution techniques in equilibrium analysis. Firstly, we review equilibrium in the evolving wholesale power markets which feature new entrants, novel trading products and multi-stage clearing. Secondly, the competition modes in the emerging distribution market and distributed resource aggregation are reviewed, and we compare peer-to-peer clearing, cooperative games and Stackelberg games. Furthermore, we summarize the methods to treat various information acquisition degrees, risk preferences and rationalities of market participants. To deal with increasingly complex market settings, this review also covers refined analytical techniques and agent-based models used to compute the equilibrium. Finally, based on this review, this paper summarizes key issues in the gaming and equilibrium analysis in power markets under decarbonization and decentralization.

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“…The DER concept is an extension of the equivalent rival concept that we presented in [20]. In the proposed approach of this paper, we define a DER entity, from the viewpoint of the intended LA, with one generation unit and one demand unit in each bus.…”

Section: Approach Overviewmentioning

confidence: 99%

“…A Bayesian inference approach is proposed in [21] to estimate the net aggregate supply curve which is based on Markov Chain Monte Carlo and Sequential Monte Carlo methods. In [20], we have shown the proposed approach can estimate the net aggregate supply curve more accurately than the proposed method of [21]. Moreover, the proposed approach of [20] allows prediction of the power allocated to the intended power plant and the market‐clearing price with high accuracy.…”

Section: Introductionmentioning

confidence: 99%

Two‐stage ANN‐based bidding strategy for a load aggregator using decentralized equivalent rival concept

Kiannejad

Salehizadeh

Buygi

2020

IET Generation Trans & Dist

Self Cite

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As an intermediator between the wholesale electricity market and retail market, a typical load aggregator submits an optimal bid to the system operator to meet the expected demands of its customers. In this regard, the provision of an effective optimal bidding strategy is very crucial for a load aggregator to increase its profit. Within this context, this paper proposes a two‐stage artificial neural network based adaptive bidding strategy procedure for an LA by revealing, modelling, and predicting the aggregative behaviour of the competitors in an hourly electricity market. To this end, we develop the concept of decentralized equivalent rival whose behaviour in the electricity market reflects the aggregation of behaviours of all individual competitors. Also, an equivalent market which its outcomes are approximately equal to those of the real market is modelled. The equivalent market's participants are the load aggregator and its corresponding DER. The proposed approach is capable enough to consider transmission constraints. The performance of the proposed approach has been examined on an illustrative example and the IEEE 30‐bus test system by considering transmission network constraints. The proposed artificial neural network‐based adaptive bidding strategy has compared with a Q –learning‐based bidding approach and the results are analysed.

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Artificial neural network approach for revealing market competitors’ behaviour

Cited by 13 publications

References 14 publications

Risk-averse optimal bidding strategy for a wind energy portfolio manager including EV parking lots for imbalance mitigation

Risk-averse optimal bidding strategy for a wind energy portfolio manager including EV parking lots for imbalance mitigation

The competition and equilibrium in power markets under decarbonization and decentralization

Two‐stage ANN‐based bidding strategy for a load aggregator using decentralized equivalent rival concept

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