Network-Constrained Peer-to-Peer energy trading for multiple microgrids considering zoning pricing

Liu, Xubin; Chen, Xinyu; Jin, Tianyu; Liu, Zhangjie; Liu, Yonglu; Su, Mei; Li, Canbing; Wu, Qiuwei

doi:10.1016/j.ijepes.2022.108837

Cited by 7 publications

(2 citation statements)

References 38 publications

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“…In two-layer game optimization trading, the DN agent is regarded as the leader of the Stackelberg game (Liu et al, 2023), and an optimization model with the goal of maximizing profits is established for the DN agent.…”

Section: Upper-layer Optimization Model For the Dn Agentmentioning

confidence: 99%

Stackelberg game-based optimal electricity trading method for distribution networks with small-micro industrial parks

Chen,

Ye,

et al. 2024

Front. Energy Res.

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In order to improve the operating benefits of the distribution network (DN) and reduce the energy consumption costs of small-micro industrial parks (SMIPs), a two-layer optimal electricity trading method for DN with SMIPs is proposed. First, based on the Stackelberg game, a multi-objective two-layer optimal trading model for DN and SMIP is established. In the upper layer, the DN agent is regarded as the leader, and a trading model is established with the goal of maximizing the profits of agents. In the lower layer, an energy optimization model is proposed for the SMIP operators, which are regarded as the followers, with the goal of minimizing the operating costs. According to the buying and selling electricity prices at the upper and lower layers, a dynamic pricing strategy is formulated. The Karush–Kuhn–Tucker condition (KKT) is introduced to transform the two-layer model into a single-layer model, and based on linear transformations, the model is further converted into a mixed-integer linear programming model. The transformations aim to address the non-linear issues arising from multivariable coupling between the upper and lower-layer trading models. The simulation results show that the trading strategy proposed in this paper can effectively increase the profit of DNs while reducing the operating costs of SMIPs and can provide a reference for decision-making in the electricity market (EM) with the participation of SMIP.

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Section: Upper-layer Optimization Model For the Dn Agentmentioning

confidence: 99%

Stackelberg game-based optimal electricity trading method for distribution networks with small-micro industrial parks

Chen,

Ye,

et al. 2024

Front. Energy Res.

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“…Currently, there has been a considerable amount of research on network constraints in power systems. (Liu et al, 2023) investigated the peer-to-peer transaction model of multi-microgrids partitioned pricing under network constraints. (Zun et al, 2019) established a network model of the electric-gas-heat energy system for regional comprehensive energy systems and proposed a linearization method.…”

Section: Introductionmentioning

confidence: 99%

Research on decision-making behavior of power suppliers considering multi-market integration and network security

et al. 2023

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The construction of a power system including renewable energy has become the direction of development for the power industry as a result of the “carbon peaking and carbon neutrality” targets. Yet because the electricity market (EM), carbon market (CM), and green certificate market (GCM) have traditionally operated independently, with little interaction among them. To explore the interaction and correlation among the three markets, this paper analyzes the trading patterns and mutual influencing factors of the EM, CM and GCM and proposes the optimal decision-making model of “carbon-electricity-certificate” integration of multiple markets based on the decision-making behavior of power producers in each market. Finally, the golden jackal optimization algorithm (GJO) is used to solve the problem under the condition of network security. The simulation results show that the integration of multiple markets is more conducive to promoting the consumption of renewable energy source (RES), and also verify the feasibility and effectiveness of GJO in solving the optimal decision-making problem of power producers in EM.

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Bipartite graph-based community-to-community matching in local energy market considering socially networked prosumers

Xia,

Xu,

Fang

et al. 2024

Applied Energy

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Network-Constrained Peer-to-Peer energy trading for multiple microgrids considering zoning pricing

Cited by 7 publications

References 38 publications

Stackelberg game-based optimal electricity trading method for distribution networks with small-micro industrial parks

Stackelberg game-based optimal electricity trading method for distribution networks with small-micro industrial parks

Research on decision-making behavior of power suppliers considering multi-market integration and network security

Bipartite graph-based community-to-community matching in local energy market considering socially networked prosumers

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