Joint Scheduling Optimization of Virtual Power Plants and Equitable Profit Distribution Using Shapely Value Theory

Tan, Zhongfu; Li, Huanhuan; Ju, Liu; Tan, Qian

doi:10.1155/2018/3810492

Cited by 11 publications

(8 citation statements)

References 40 publications

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“…Nguyen et al propose a method to quickly solve the core selection problem in a coalition of wind power plants through a constraint generation algorithm [69] . For computational tractability, cost causation-based [70] , Aumann-Shapley value [71] , and minimum cost-remaining savings [72] methods for profit (cost) allocation within aggregators have been used to replace the Shapley value method in specific scenarios. In addition to the abovementioned DER types, there are also recent studies on DER coalitions containing interruptible loads [73] and EVs [74] .…”

Section: Reviewmentioning

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: Reviewmentioning

confidence: 99%

The competition and equilibrium in power markets under decarbonization and decentralization

Chen

Fang

Guo

et al. 2022

iEnergy

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“…Based on the satisfaction of all wind storage joint ventures, the Nash negotiation method is used to distribute profits among various wind storage joint ventures, achieving high satisfaction of all participants. According to the profits distributed by the various wind storage joint ventures, Tan, Li et al [20] proposed that the advantage of the Shapely value is easy to understand and the feasibility is high. The profit is distributed among the internal wind storage joint ventures, which is between the wind power supplier and the pumped storage power station.…”

Section: Lower-level Wind Storage Joint Venture Profit Distribution Mmentioning

confidence: 99%

Game Analysis of Wind Storage Joint Ventures Participation in Power Market Based on a Double-Layer Stochastic Optimization Model

Geng

Tan

et al. 2019

Processes

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The volatility of a new energy output leads to bidding bias when participating in the power market competition. A pumped storage power station is an ideal method of stabilizing new energy volatility. Therefore, wind power suppliers and pumped storage power stations first form wind storage joint ventures to participate in power market competition. At the same time, middlemen are introduced, constructing an upper-level game model (considering power producers and wind storage joint ventures) that forms equilibrium results of bidding competition in the wholesale and power distribution markets. Based on the equilibrium result of the upper-level model, a lower model is constructed to distribute the profits from wind storage joint ventures. The profits of each wind storage joint venture, wind power supplier, and pumped storage power station are obtained by the Nash negotiation and the Shapely value method. Finally, a case study is conducted. The results show that the wind storage joint ventures can improve the economics of the system. Further, the middlemen can smooth the rapid fluctuation of power price in the distribution and wholesale market, maintaining a smooth and efficient operation of the electricity market. These findings provide information for the design of an electricity market competition mechanism and the promotion of new energy power generation.

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“…This enables us to efficiently add new assets into the pool (polynomial complexity) provided that the constraints associated with each asset are linear. In Tan et al (2018), the authors explore the management of virtual power plants and their alliances involving wind and solar parks. They propose a model involving the separate operation of assets but joint scheduling of them.…”

Section: Introductionmentioning

confidence: 99%

Optimal Balancing of Wind Parks with Virtual Power Plants

Omelčenko¹,

Manokhin

2021

Front. Energy Res.

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In this paper, we explore the optimization of virtual power plants (VPP), consisting of a portfolio of biogas power plants and a battery whose goal is to balance a wind park while maximizing their revenues. We operate under price and wind production uncertainty and in order to handle it, methods of machine learning are employed. For price modeling, we take into account the latest trends in the field and the most up-to-date events affecting the day-ahead and intra-day prices. The performance of our price models is demonstrated by both statistical methods and improvements in the profits of the virtual power plant. Optimization methods will take price and imbalance forecasts as input and conduct parallelization, decomposition, and splitting methods in order to handle sufficiently large numbers of assets in a VPP. The main focus is on the speed of computing optimal solutions of large-scale mixed-integer linear programming problems, and the best speed-up is in two orders of magnitude enabled by our method which we called Gradual Increase.

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Joint Scheduling Optimization of Virtual Power Plants and Equitable Profit Distribution Using Shapely Value Theory

Cited by 11 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

Game Analysis of Wind Storage Joint Ventures Participation in Power Market Based on a Double-Layer Stochastic Optimization Model

Optimal Balancing of Wind Parks with Virtual Power Plants

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