Research on Reactive Power Compensation Algorithm Based on Game Theory in Wind Farm

Xu, Xiang; Chen, Qi

doi:10.4028/www.scientific.net/kem.439-440.989

Cited by 7 publications

(5 citation statements)

References 1 publication

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“…It is possible that, in iteration γ + 1, the best response changes the total amount a (γ+1) i in (21) and this can lead to a price changing loop.…”

Section: B Double Auction Mechanism For Market Analysismentioning

confidence: 99%

“…In [20], a new technique based on cooperative game theory is proposed to allow wind turbines to aggregate their generated energy and optimize their profits. Reactive power compensation was studied in [21] using game theory with the objective of optimizing wind farm generation. A strategic game model was developed in [22] to analyze an oligopoly within an energy market with various grid-level constraints.…”

Section: Introductionmentioning

confidence: 99%

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A Game-Theoretic Approach to Energy Trading in the Smart Grid

Wang

Saad

Han

et al. 2014

IEEE Trans. Smart Grid

374

213

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Abstract-Electric storage units constitute a key element in the emerging smart grid system. In this paper, the interactions and energy trading decisions of a number of geographically distributed storage units are studied using a novel framework based on game theory. In particular, a noncooperative game is formulated between storage units, such as PHEVs, or an array of batteries that are trading their stored energy. Here, each storage unit's owner can decide on the maximum amount of energy to sell in a local market so as to maximize a utility that reflects the tradeoff between the revenues from energy trading and the accompanying costs. Then in this energy exchange market between the storage units and the smart grid elements, the price at which energy is traded is determined via an auction mechanism. The game is shown to admit at least one Nash equilibrium and a novel proposed algorithm that is guaranteed to reach such an equilibrium point is proposed. Simulation results show that the proposed approach yields significant performance improvements, in terms of the average utility per storage unit, reaching up to 130.2% compared to a conventional greedy approach.Index Terms-Electric storage unit, noncooperative games, double auctions, energy management. I. INTRODUCTIONModernizing the electric power grid and realizing the vision of a "smart grid" is contingent upon the deployment of novel smart grid elements such as renewable energy sources and energy storage units [1]. In this respect, electric storage units are inherently devices that can store energy, or extra electricity available at participating customers. Deployment of storage units in future smart grid systems faces many challenges at different levels such as studying the impact of integrating storage units on the grid's operation, determining the required grid infrastructure (communication and control nodes) to enable smart energy exchange, and developing new power management strategies [2]- [6]. The potential economic impact of deploying energy storage units was explored in [7], which also studied the feasible level of energy storage in the distribution system. The possibility of having groups of controllable loads and sources of energy in power systems was investigated in [8] which deployed a distribution network of solar panels or wind turbines. In [9], distributed resources are allocated by the provision of twoway energy flow and a unified, operational value proposition of energy storage is presented. Other related problems have assessed the advantages of deploying and maintaining storage units such as [10]-[18].One main challenge pertaining to introducing energy storage units within the smart grid is the analysis of the energy trading decision making processes involving complex interactions be-

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“…It is possible that, in iteration γ + 1, the best response changes the total amount a (γ+1) i in (21) and this can lead to a price changing loop.…”

Section: B Double Auction Mechanism For Market Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Game-Theoretic Approach to Energy Trading in the Smart Grid

Wang

Saad

Han

et al. 2014

IEEE Trans. Smart Grid

374

213

View full text Add to dashboard Cite

show abstract

“…Por otra parte, se propuso una nueva técnica basada en la Teoría de Juegos Cooperativa para gestionar la energía generada por turbinas eólicas y optimizar las ganancias [3]. También se estudiaron la compensación de potencia reactiva con el objetivo de optimizar la generación en parques eólicos [4], y el despacho económico de energía y reservas en mercados competitivos mediante algoritmos metaheurísticos [5,6]. Un modelo de juego estratégico se desarrolló para analizar un oligopolio dentro de un mercado de energía con varias restricciones a nivel de la red [7].…”

Section: Introductionunclassified

A Double-Auction Mechanism for Distribution of Electrical Supply Capacities among Enterprises of an Industrial Park

Rocchi

Fernandez

Vega

2021

IEEE Latin Am. Trans.

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“…Second, the reactive power configuration was configured based on the target of transient stability in the regional power grids connected with renewable energy generation [21][22][23]. The literature [24][25][26] analyzed the operation mode of the wind farm and then determined the reactive power configuration of the wind farm through the transient simulation using the typical operation mode and the limit operation mode.…”

Section: Introductionmentioning

confidence: 99%

Multiobjective Reactive Power Optimization of Renewable Energy Power Plants Based on Time-and-Space Grouping Method

Zhang

Lin

et al. 2020

Energies

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The large-scale renewable energy power plants connected to a weak grid may cause bus voltage fluctuations in the renewable energy power plant and even power grid. Therefore, reactive power compensation is demanded to stabilize the bus voltage and reduce network loss. For this purpose, time-series characteristics of renewable energy power plants are firstly reflected using K-means++ clustering method. The time group behaviors of renewable energy power plants, spatial behaviors of renewable energy generation units, and a time-and-space grouping model of renewable energy power plants are thus established. Then, a mixed-integer optimization method for reactive power compensation in renewable energy power plants is developed based on the second-order cone programming (SOCP). Accordingly, power flow constraints can be simplified to achieve reactive power optimization more efficiently and quickly. Finally, the feasibility and economy for the proposed method are verified by actual renewable energy power plants.

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Research on Reactive Power Compensation Algorithm Based on Game Theory in Wind Farm

Cited by 7 publications

References 1 publication

A Game-Theoretic Approach to Energy Trading in the Smart Grid

A Game-Theoretic Approach to Energy Trading in the Smart Grid

A Double-Auction Mechanism for Distribution of Electrical Supply Capacities among Enterprises of an Industrial Park

Multiobjective Reactive Power Optimization of Renewable Energy Power Plants Based on Time-and-Space Grouping Method

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