Profit allocation analysis among the distributed energy network participants based on Game-theory

Wu, Qiong; Ren, Hongbo; Gao, Weijun; Ren, Jianxing; Lao, Changshi

doi:10.1016/j.energy.2016.10.117

Cited by 57 publications

(28 citation statements)

References 28 publications

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“…Min et al [63] defined the generators' strategies by Nash equilibria. Wu et al [64] discussed coalition formation and profit allocation of RES generators within a distributed energy network comprised of controllable demand. Zheng et al [65] proposed a novel, crowdsourced funding model for renewable energy investments, using a sequential game-theoretic approach.…”

Section: Review Of Game Theory and Artificial Intelligence Techniquesmentioning

confidence: 99%

Game-theoretic modeling of curtailment rules and network investments with distributed generation

et al. 2017

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Renewable energy has achieved high penetration rates in many areas, leading to curtailment, especially if existing network infrastructure is insufficient and energy generated cannot be exported. In this context, Distribution Network Operators (DNOs) face a significant knowledge gap about how to implement curtailment rules that achieve desired operational objectives, but at the same time minimise disruption and economic losses for renewable generators. In this work, we study the properties of several curtailment rules widely used in UK renewable energy projects, and their effect on the viability of renewable generation investment. Moreover, we propose a new curtailment rule which guarantees fair allocation of curtailment amongst all generators with minimal disruption. Another key knowledge gap faced by DNOs is how to incentivise private network upgrades, especially in settings where several generators can use the same line against the payment of a transmission fee. In this work, we provide a solution to this problem by using tools from algorithmic game theory. Specifically, this setting can be modelled as a Stackelberg game between the private transmission line investor and local renewable generators, who are required to pay a transmission fee to access the line. We provide a method for computing the equilibrium of this game, using a model that captures the stochastic nature of renewable energy generation and demand. Finally, we use the practical setting of a grid reinforcement project from the UK and a large dataset of wind speed measurements and demand to validate our model. We show that charging a transmission fee as a proportion of the feed-in tariff price between 15%-75% would allow both investors to implement their projects and achieve desirable distribution of the profit. Overall, our results show how using gametheoretic tools can help network operators to bridge the knowledge gap about setting the optimal curtailment rule and determining transmission charges for private network infrastructure. $ This paper builds on significant extensions, both in theoretical results and new datasets, of preliminary work presented at two international conferences: AAMAS 2016 [1] and IEEE ISGT Europe 2016 [2].it might have negative effects on the operation, resilience and safety of the electricity grid. RES are intermittent and have variable power outputs due to constantly changing primary resources and weather patterns, which are difficult to predict. The challenges faced by network operators relate to reverse power flows, increased power losses, harmonics, voltage fluctuations, thermal capacity of equipment, frequency and voltage regulation and can compromise the system reliability [5].An additional barrier is that grid infrastructure is inadequate to support continuous RES development or distributed generation (DG), especially in the area of distribution networks. Often high investment takes place in remote areas of the grid, where projects face favourable resource conditions and planning approval. Typically, in the UK, ...

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Section: Review Of Game Theory and Artificial Intelligence Techniquesmentioning

confidence: 99%

Game-theoretic modeling of curtailment rules and network investments with distributed generation

et al. 2017

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“…Therefore, game theory was used to solve this problem. Game theory has been studied and applied in many fields, such as power grid vulnerability analysis [21], power plant pricing [22], and profit distribution [23,24]. In the field of integrated energy systems, a cooperative game model is established to determine the optimal scheduling strategy of the integrated energy system, aiming at the daytime economic optimal scheduling problem of the system [25].…”

Section: Introductionmentioning

confidence: 99%

An Optimal Scheduling Method for Multi-Energy Hub Systems Using Game Theory

et al. 2019

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The optimal scheduling of multi-energy hub systems plays an important role in the safety, stability, and economic operation of the system. However, due to the strong uncertainty of renewable energy access, serious coupling, and the interaction among energy hubs of multi-energy hub systems, it is difficult for the traditional optimal scheduling method to solve these problems. Therefore, game theory was used to solve the optimal scheduling problem of multi-energy hub systems. According to the internal connection mode and energy conversion relationship of energy hubs, along with the competitive and cooperative relationship between multi-energy hubs, the game theoretic optimal scheduling model of the multi-energy hub system was established. Then, two cases and 50 groups of wind speed series were used to test the robustness of the proposed method. Simulation results show that the total power injection is −16,805.8, 104.1847, and −865.561 and the natural gas injection is 46,046.81, 27,727.65, and 63,039.54 in spring/autumn, summer, and winter, respectively, which is consistent with the characteristics of the four seasons. Furthermore, the optimal scheduling method using game theory has a strong robustness in multi-energy hub systems.

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“…The Shapley value method distributes cooperative benefits according to scientific calculation of the contribution of each member in a cooperation union. Since the Shapley value method has been proved to be highly effective in distributing cooperative benefits [88,92,94,99,100], this paper apply this method to allocate cooperative benefits from electricity utilization.…”

Section: Benefit Allocation Model Of Cooperative Electricity Savingmentioning

confidence: 99%

“…On the other hand, cooperative game theory has begun to be used to realize energy saving on the micro level. Based on cooperative game theory, Wu et al [86][87][88] developed models for optimization of distributed energy networks which were integrated with heating interchanges to realize cooperative energy saving and cost effectiveness. However, research exploring cooperative energy saving from the perspective of macro-management remains scant.…”

Section: Introductionmentioning

confidence: 99%

Modeling Interprovincial Cooperative Energy Saving in China: An Electricity Utilization Perspective

et al. 2018

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Abstract:As the world faces great challenges from climate change and environmental pollution, China urgently requires energy saving, emission reduction, and carbon reduction programmes. However, the non-cooperative energy saving model (NCESM), the simple regulation mode that is China's main model for energy saving, is not beneficial for optimization of energy and resource distribution, and cannot effectively motivate energy saving at the provincial level. Therefore, we propose an interprovincial cooperative energy saving model (CESM) from the perspective of electricity utilization, with the object of maximizing the benefits from electricity utilization of the cooperation union based on achieving the energy saving goals of the union as a whole. The CESM consists of two parts: (1) an optimization model that calculates the optimal quantities of electricity consumption for each participating province to meet the joint energy saving goal; and (2) a model that distributes the economic benefits of the cooperation among the provinces in the cooperation based on the Shapley value method. We applied the CESM to the case of an interprovincial union of Shanghai, Sichuan, Shanxi, and Gansu in China. The results, based on the data from 2001-2014, show that cooperation can significantly increase the benefits of electricity utilization for each province in the union. The total benefits of the union from utilization of electricity increased 38.38%, or 353.98 billion CNY, while the benefits to Shanghai, Sichuan, Shanxi, and Gansu were 200.28, 58.37, 57.11, and 38.22 billion CNY respectively greater under the CESM than the NCESM. The implementation of the CESM provides the provincial governments not only a flexible and incentive way to achieve short-term goals, but also a feasible and effective path to realize long-term energy saving strategies. To test the impact of different parameter values on the results of the CESM, a sensitivity analysis was conducted. Some policy recommendations are made at the central government level and the provincial government level to promote the implementation of the CESM.

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Profit allocation analysis among the distributed energy network participants based on Game-theory

Cited by 57 publications

References 28 publications

Game-theoretic modeling of curtailment rules and network investments with distributed generation

Game-theoretic modeling of curtailment rules and network investments with distributed generation

An Optimal Scheduling Method for Multi-Energy Hub Systems Using Game Theory

Modeling Interprovincial Cooperative Energy Saving in China: An Electricity Utilization Perspective

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