Real-time pricing scheme based on Stackelberg game in smart grid with multiple power retailers

Dai, Yeming; Gao, Yan; Gao, Hongwei; Zhu, Hongbo

doi:10.1016/j.neucom.2017.04.027

Cited by 65 publications

(42 citation statements)

References 21 publications

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“…In this paper, we assume that the users are risk-averse. The utility function is non-minus and the marginal benefit function is non-plus, thus the utility function is defined as follows [16]:…”

Section: Utility Function and Cost Functionmentioning

confidence: 99%

Real-time Pricing Mechanism in Smart Grid based on System of Incentive and Penalty

Li¹,

Dai²,

Gao³

2019

Proceedings of the 1st International Conference on Business, Economics, Management Science (BEMS 2019)

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In the smart grid, users, power suppliers and Power Market Scheduling Center are the main participants. In view of the increasing demand response ability of users, an identification mechanism of punishing malicious users and unstable power providers while incenting nonmalicious users is proposed, and an optimization model to maximize social welfare is considered to study the real-time pricing problem in smart grid managed by PMSC. The model is analyzed by Lagrange dual method and finally solved by heuristic algorithm to obtain the optimal electricity price and power demand. The simulation results show that the algorithm can converge well and the reliability and stability of power system are optimized under the dual regulation of penalty and incentive. In addition, there is a positive correlation between the incentive factor and users' utility and social welfare within proper range.

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Section: Utility Function and Cost Functionmentioning

confidence: 99%

Real-time Pricing Mechanism in Smart Grid based on System of Incentive and Penalty

Li¹,

Dai²,

Gao³

2019

Proceedings of the 1st International Conference on Business, Economics, Management Science (BEMS 2019)

Self Cite

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show abstract

“…Dai and Gao presented a game model with multiple leaders and multiple followers based on an incentive factor . They also established a multileader and multifollower Stackelberg game model to study the RTP scheme of residential users in another paper and used evolutionary game and noncooperative game, respectively, to describe the price competition between users and electricity providers …”

Section: Introductionmentioning

confidence: 99%

“…19 They also established a multileader and multifollower Stackelberg game model to study the RTP scheme of residential users in another paper and used evolutionary game and noncooperative game, respectively, to describe the price competition between users and electricity providers. 20 Compared with the general optimization method, the application of the game theory is closer to the real electricity market, but most of the above researches use the traditional game theory methods, in which the description of human behavior is mostly limited to discrete situation. To depict the change of human behavior in a continuous time, the differential game theory is applied.…”

Section: Introductionmentioning

confidence: 99%

Real‐time pricing in smart community with constraint from the perspective of advertising game

Dai

Zhao

et al. 2019

Int Trans Electr Energ Syst

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Summary The advertising differential game is introduced to depict the competition among electricity retailers in continuous time. A Stackelberg game model with one leader and multiple followers is established to study the real‐time pricing scheme in a smart community. By solving the optimization problem on users' side with budget constraint and the noncooperative differential game among retailers, the Stackelberg equilibrium between the retailers and the users is obtained. Finally, numerical simulation is carried out to discuss the influence of different factors on the payoff of electricity retailers and users and verify the rationality of the pricing scheme.

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“…With the further opening of power market and emergence of new renewable energy sources, power users get easy access to power from different power suppliers, which indeed complicates the interaction process between power suppliers and users. Thus, some sophisticated SG are leveraged to shed light on the multiseller‐multibuyer RTP problem in the complex power network, see for other studies . In Dai and Gao, a SG was proposed for electricity retailers who coexist in each region and serve 2 types of electricity users in smart grid using RTP, but the response behavior of the user side was ignored.…”

Section: Introductionmentioning

confidence: 99%

“…In Maharjan et al, an SG between utility companies and end users was proposed, and some analytical results were obtained. The authors of Dai et al also studied RTP scheme in smart grid with multiple retailers and multiple residential users using SG. At the same time, the price competition among power retailers and the coordination among the residential users were formulated into different game models.…”

Section: Introductionmentioning

confidence: 99%

A demand response approach considering retailer incentive mechanism based on Stackelberg game in smart grid with multi retailers

Dai

Gao

et al. 2018

Int Trans Electr Energ Syst

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Summary As the key component of demand response management in smart grid, real‐time pricing has been an open issue to address. In this paper, a Stackelberg game with multiple power retailers and multiple users is proposed to maximize the revenue of each retailer and the payoff of each user in power retail market. The existence of Stackelberg equilibrium is analyzed and proved. A distributed algorithm is developed to ensure the convergence of Stackelberg equilibrium for retailers and users with only local information. Additionally, we design an incentive factor that adjusts the price information from retailers to guarantee the grid operation and assure supply‐demand balance since the smart grid still can be susceptible to the issues about privacy and security. The simulation results show the effectiveness of algorithm and the impact of incentive factor.

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Real-time pricing scheme based on Stackelberg game in smart grid with multiple power retailers

Cited by 65 publications

References 21 publications

Real-time Pricing Mechanism in Smart Grid based on System of Incentive and Penalty

Real-time Pricing Mechanism in Smart Grid based on System of Incentive and Penalty

Real‐time pricing in smart community with constraint from the perspective of advertising game

A demand response approach considering retailer incentive mechanism based on Stackelberg game in smart grid with multi retailers

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