Non‐cooperative and cooperative optimisation of battery energy storage system for energy management in multi‐microgrid

Liu, Xiaofeng; Gao, Bingtuan; Zhu, Zhenyu; Tang, Yi

doi:10.1049/iet-gtd.2017.0401

Cited by 52 publications

(20 citation statements)

References 31 publications

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“…Moghim et al [13] developed the battery energy storage system (BESS) control algorithm to concurrently overcome the outage issue and shave the peak demand considering the BESS sizing and degradation, microgrid system cost reduction, as well as microgrid scheduling. Liu et al [14] studied the energy management with battery energy storage system (BESS) optimisation by bearing in mind the cost of distributed generations, cost of battery system, and bi-directional energy trading. Dongol et al [15] developed the Model Predictive Control (MPC) scheme that could be applied to an existing grid linked household with PV-battery system such that the use of battery is maximized and at the same time, peaks in PV power and load demand are reduced.…”

Section: Concept Of Maximum Demand Reduction (Mdred) Modelmentioning

confidence: 99%

Techno-Economic Optimization of Grid-Connected Photovoltaic (PV) and Battery Systems Based on Maximum Demand Reduction (MDRed) Modelling in Malaysia

et al. 2019

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Under the present electricity tariff structure in Malaysia, electricity billing on a monthly basis for commercial and industrial consumers includes the net consumption charges together with maximum demand (MD) charges. The use of batteries in combination with photovoltaic (PV) systems is projected to become a viable solution for energy management, in terms of peak load shaving. Based on the latest studies, maximum demand (MD) reduction can be accomplished via a solar PV-battery system based on a few measures such as load pattern, techno-economic traits, and electricity scheme. Based on these measures, the Maximum Demand Reduction (MDRed) Model is developed as an optimization tool for the solar PV-battery system. This paper shows that energy savings on net consumption and maximum demand can be maximized via optimal sizing of the solar PV-battery system using the MATLAB genetic algorithm (GA) tool. GA optimization results revealed that the optimal sizing of solar PV-battery system gives monthly energy savings of up to 20% of net consumption via solar PV self-consumption, 3% of maximum demand (MD) via MD shaving and 2% of surplus power supplied to grid via net energy metering (NEM) in regards to Malaysian electricity tariff scheme and cost of the overall system.

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Section: Concept Of Maximum Demand Reduction (Mdred) Modelmentioning

confidence: 99%

Techno-Economic Optimization of Grid-Connected Photovoltaic (PV) and Battery Systems Based on Maximum Demand Reduction (MDRed) Modelling in Malaysia

et al. 2019

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“…MS is the bidding tradable power and price corresponding to the j-th MEP in the k-th round. The k-th iteration equation is expressed as follows (16), as shown at the bottom of the next page.…”

Section: B Game Relationship Among Sellersmentioning

confidence: 99%

“…The relation between DTO and MEP is in Figure 3. ; z( P k * , p k * ) end for Algorithm iteration is conducted based on Equation (16). The electricity price for trade and the tradable power offered by the seller MEPs are updated.…”

Section: Congestion Management Model Based On Market Capacitymentioning

confidence: 99%

“…Algorithm iteration was conducted based on Equation (16). The trade price and the tradable power offered by the seller MEPs are updated.…”

Section: Ms End Formentioning

confidence: 99%

“…Some studies have also explored the economic benefits of transaction users under the second trading mechanism described above. By using non-cooperative game theory, Liu et al [16] analyzed ''selfish'' strategies adopted by different microgrid systems in the sole pursuit of profit, which involves adjusting the charge and discharge states of energy storage. The cooperative game theory was used to analyze the trading strategies of microgrid systems to optimize the overall economy of the microgrid cluster.…”

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confidence: 99%

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Distributed Day-Ahead Peer-to-Peer Trading for Multi-Microgrid Systems in Active Distribution Networks

Liu

et al. 2020

IEEE Access

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Developing a reasonable, efficient distributed market transaction mechanism is an important issue in distribution systems. The gaming relation between distributed transaction market entities has yet to be fully elucidated in various trading links, and the impact of distributed transactions on distribution network operations has yet to be comprehensively analyzed. This paper proposes a novel distributed Peerto-Peer (P2P) day-ahead trading method under multi-microgrid congestion management in active distribution networks. First, a flexible load model for price-based demand response load and an autonomous microgrid economic scheduling model are constructed. Second, under normal operation of the distribution network, a non-cooperative game model and Stackelberg game model are employed to separately and comprehensively analyze gaming relationship among sellers, and between sellers and buyers. Thereafter, a congestion management method based on market capacity is established from the perspective of distribution network control centers. Finally, the impact of end energy consumption characteristics on microgrid economic scheduling and P2P trading is analyzed through a modified IEEE 33-node power distribution system. The economic and technical benefits such as congestion mitigation and network loss reduction that produced by P2P trading to the operation of microgrid systems are analysed with specific indicators. INDEX TERMS Multi-microgrid cluster, active distribution network, peer-to-peer trading, non-cooperative game, Stackelberg game, congestion management.

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Planning optimization for islanded microgrid with electric-hydrogen hybrid energy storage system based on electricity cost and power supply reliability

Qiu

Zhao

et al. 2021

Renewable Energy Microgeneration Systems

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Non‐cooperative and cooperative optimisation of battery energy storage system for energy management in multi‐microgrid

Cited by 52 publications

References 31 publications

Techno-Economic Optimization of Grid-Connected Photovoltaic (PV) and Battery Systems Based on Maximum Demand Reduction (MDRed) Modelling in Malaysia

Techno-Economic Optimization of Grid-Connected Photovoltaic (PV) and Battery Systems Based on Maximum Demand Reduction (MDRed) Modelling in Malaysia

Distributed Day-Ahead Peer-to-Peer Trading for Multi-Microgrid Systems in Active Distribution Networks

Planning optimization for islanded microgrid with electric-hydrogen hybrid energy storage system based on electricity cost and power supply reliability

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