Agent based simulation of centralized electricity transaction market using bi-level and Q-learning algorithm approach

Namalomba, Ellen; Hu, Feihu; Shi, Huaitao

doi:10.1016/j.ijepes.2021.107415

Cited by 26 publications

(6 citation statements)

References 40 publications

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“…However, the Q-learning algorithm is weak in dealing with the continuous bidding action space. Some studies are also investigating policy-based models, such as the deep policy gradient (DPG) [148] , deep deterministic policy gradient (DDPG) [142][143][144]147] , multi-actor-attention-critic (MAAC) [136] , and asynchronous advantage actor-critic (A3C) [138] .…”

Section: Multi-agent-based Models and Solving Methodsmentioning

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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Section: Multi-agent-based Models and Solving Methodsmentioning

confidence: 99%

The competition and equilibrium in power markets under decarbonization and decentralization

Chen

Fang

Guo

et al. 2022

iEnergy

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“…Namalomba et al [20] have suggested that Market players must contend with the volatility of market prices as well as the unpredictability of demand patterns, notwithstanding the numerous restructuring initiatives aimed at reorganizing the Chinese power sector. We looked at the pricing and bidding strategies used by companies that produce and supply energy in two-way auctions in a centralized elastic demand market to try to close this gap.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization Research on Provincial Users' Participation in Regional Electricity Spot Market Bidding Based on Hierarchically Gated Recurrent Neural Network

Jinqing Luo

2024

jes

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The creation of strategic pricing models is crucial in the highly competitive centralized energy markets in order to maximize revenues. In order to achieve maximum profit, market participants must act intelligently while bidding on electrical energy purchases or sales. Notwithstanding the many restructuring changes of the Chinese electricity sector, market participants are nonetheless exposed to risks associated with volatility in market prices and uncertainty over demand behavior. The data are collected from New South Wales electricity market. Data-adaptive Gaussian average filtering (DAGAF) is used to pre-process the data during the pre-processing step. Hierarchically Gated Recurrent Neural Networks (HGRNNs) are successfully used to classify both long-term and spot transactions. The neural network's weight parameter is optimized by the Lotus Effect Optimization Algorithm (LEA), which enhances the HGRNN. The RESMB-HGRNN-LEA proposed is implemented on the Python working platform. To calculate the suggested approach, performance measures including accuracy, precision, sensitivity, computation time, and recall were looked at.In comparison to the existing technique, the proposed RESMB-HGRNN-LEA method yields better results in terms of accuracy (16.65% and 18.85%), sensitivity (16.34% and 12.23%), precision (14.89% and 16.89%), and computing time (82.37% and 94.47%).

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Section: Introductionmentioning

confidence: 99%

“…At present, the comprehensive evaluation research on the power industry is relatively rich, and the evaluation angle mainly focuses on the reform of the power system and the development of the power grid: (1) The reform of the power system. Aiming at the risks of market price fluctuations and uncertainty in demand behavior faced by market participants, Namalomba Ellen et al [1] studied the pricing and bidding behaviors of power generation and electricity sales companies in a centralized electricity trading market with elastic demand. Xun Lu et al [2] constructed a comprehensive evaluation index system for distribution network planning under multiple levels, and set up a comprehensive evaluation model for smart distribution network planning under the new pattern of the power market to achieve the coordination and unity of individual and group interests.…”

Section: Introductionmentioning

confidence: 99%

Research on the Evaluation Model of Physical Asset Management Maturity of China's Inter-provincial Grid Enterprises

Zhang¹,

Xia²,

Xu³

et al. 2023

Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022

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A comprehensive evaluation of the physical assets of power grid enterprises is conducive to promoting the management of assets of enterprises and avoiding the loss and waste of state-owned assets. This paper collects the objective statistics of the enterprise and the subjective scoring data of the experts in the index system for the past 5 years, and determines the comprehensive weight of each index through the combination of subjective and objective weights. Grey correlation and topsis method is used to establish a dynamic evaluation model for objective data to capture the trend of the comprehensive value of physical assets, and subjective data is used to establish a maturity model to calculate the maturity level of physical assets. In this way, the results of dynamic assessment and maturity assessment are combined to obtain the results of grid enterprise asset evaluation under multi-dimensional dynamic perspective. Finally, an empirical analysis using a grid data shows that the company should learn from the scientific management experience of 2016, maintain a high level of asset structure and utilization efficiency, and focus on improving the optimal management of asset decommissioning and health.

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Agent based simulation of centralized electricity transaction market using bi-level and Q-learning algorithm approach

Cited by 26 publications

References 40 publications

The competition and equilibrium in power markets under decarbonization and decentralization

The competition and equilibrium in power markets under decarbonization and decentralization

Optimization Research on Provincial Users' Participation in Regional Electricity Spot Market Bidding Based on Hierarchically Gated Recurrent Neural Network

Research on the Evaluation Model of Physical Asset Management Maturity of China's Inter-provincial Grid Enterprises

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