Profit-Sharing Mechanism for Aggregation of Wind Farms and Concentrating Solar Power

Wu, Zhaoyuan; Zhou, Ming; Wang, Jianxiao; Wang, Jianxiao; Zhang, Ning; Li, Gengyin

doi:10.1109/tste.2020.2967860

Cited by 56 publications

(12 citation statements)

References 24 publications

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“…A stochastic programming model based on multiple scenarios [25] is adopted to describe the characteristics representing the behaviour of PEVs. The PEV scenarios are generated by combining the corresponding probability density functions.…”

Section: Model Of a Charging Stationmentioning

confidence: 99%

Optimal bidding strategy for virtual power plants considering the feasible region of vehicle‐to‐grid

Wang

Gao

Zhao

et al. 2020

Energy Conversion and Economics

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With the rapid development of vehicle‐to‐grid (V2G) technology, the use of the internet of things and advanced information technology to achieve the optimal dispatch of large‐scale plug‐in electric vehicles (PEVs) has become an important focus of scientific research and engineering practice worldwide. In order to achieve a balance between mass distributed energy resources and the secure and economic operation of the power grid, the authors propose an optimal market bidding strategy for a virtual power plant considering the feasible region of V2G. A detailed battery model considering the V2G mode of PEVs is established. A two‐stage stochastic optimisation model for the virtual power plant considering massive volumes of PEVs is built, taking into account the day‐ahead market revenue and the costs brought about by real‐time market deviations. Three bidding strategies—PEVs charging immediately after arrival, without V2G, and considering V2G—are compared using case studies to demonstrate the efficiency and effectiveness of the proposed strategy. Through the complete interaction between PEVs and the virtual power plant, this V2G‐based strategy can coordinate distributed energy resources, promote the accommodation of renewable energy, and significantly improve the economy of the virtual power plant operation.

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Section: Model Of a Charging Stationmentioning

confidence: 99%

Optimal bidding strategy for virtual power plants considering the feasible region of vehicle‐to‐grid

Wang

Gao

Zhao

et al. 2020

Energy Conversion and Economics

Self Cite

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show abstract

“…Du et al [9] established a four-day unit commitment model for a power system equipped with concentrated solar power units. In [10], Wu et al presented a profit-allocation algorithm for wind farms and concentrated solar units jointly participating in electricity markets using a stochastic model. Zhao et al [11] provided an Information Gap Decision Theory (IGDT)-based structure to tackle the self-scheduling problem of concentrated solar power units and various responsive loads.…”

Section: Introductionmentioning

confidence: 99%

Day-Ahead and Intraday Dispatch of an Integrated Biomass-Concentrated Solar System: A Multi-Objective Risk-Controlling Approach

Khaloie

Vallée

Lai

et al. 2022

IEEE Trans. Power Syst.

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“…Leveraging nucleolus and Shapley-value approaches, the profit allocation for the joint trading of wind and power-to-gas technologies was addressed in [15]. A Nash bargaining theory for profit allocation between wind and concentrating solar power facilities was proposed in [16]. The profit allocation approach between demandside resources taking part in the energy and reserve markets using the Aumann-Shapley method was discussed in [17].…”

Section: Introductionmentioning

confidence: 99%

An Innovative Coalitional Trading Model for a Biomass Power Plant Paired With Green Energy Resources

Khaloie

Toubeau

Vallée

et al. 2022

IEEE Trans. Sustain. Energy

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The role of biomass resources to diminish the dependency on fossil fuels is steadily increasing worldwide. More importantly, governments set goals to boost the share of renewable energy resources in the power sector to face up to global warming issues. In this paper, a coalitional game model for the trading of a Biomass Power Plant (BPP) paired with a concentrating solar power facility and a wind park is proposed. In the proposed coalitional trading architecture, the physical coupling between biomass and concentrating solar power facilities is embedded, while cost sources related to operation and maintenance of all units as well as harvesting and transportation of forestry residue are taken into account to represent a more pragmatic trading approach. The suggested coalitional trading model is formulated as a stochastic model with three sequential stages. Moreover, game theory concepts, i.e., τ -value, nucleolus, and Shapleyvalue, are exploited and compared for profit allocation to the coalition members. A cost-benefit analysis is also conducted to investigate the effect of cooperative and non-cooperative trading models on the BPP's investment feasibility. The results highlight the lucrativeness of the proposed coalitional trading model and remarkable reduction in the payback period of the BPP under a cooperative game framework.

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Profit-Sharing Mechanism for Aggregation of Wind Farms and Concentrating Solar Power

Cited by 56 publications

References 24 publications

Optimal bidding strategy for virtual power plants considering the feasible region of vehicle‐to‐grid

Optimal bidding strategy for virtual power plants considering the feasible region of vehicle‐to‐grid

Day-Ahead and Intraday Dispatch of an Integrated Biomass-Concentrated Solar System: A Multi-Objective Risk-Controlling Approach

An Innovative Coalitional Trading Model for a Biomass Power Plant Paired With Green Energy Resources

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