scholarly journals Real-Time Pricing Strategy Based on the Stability of Smart Grid for Green Internet of Things

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Huwei Chen ◽  
Hui Hui ◽  
Zhou Su ◽  
Dongfeng Fang ◽  
Yilong Hui
Keyword(s):  
Internet Of Things ◽  
Smart Grid ◽  
Real Time ◽  
Power Supply ◽  
Stackelberg Game ◽  
Supply And Demand ◽  
Pricing Strategy ◽  
Maximal Profit ◽  
Real Time Pricing ◽  
The Stability

The ever increasing demand of energy efficiency and the strong awareness of environment have led to the enhanced interests in green Internet of things (IoTs). How to efficiently deliver power, especially, with the smart grid based on the stability of network becomes a challenge for green IoTs. Therefore, in this paper we present a novel real-time pricing strategy based on the network stability in the green IoTs enabled smart grid. Firstly, the outage is analyzed by considering the imbalance of power supply and demand as well as the load uncertainty. Secondly, the problem of power supply with multiple-retailers is formulated as a Stackelberg game, where the optimal price can be obtained with the maximal profit for retailers and users. Thirdly, the stability of price is analyzed under the constraints. In addition, simulation results show the efficiency of the proposed strategy.

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

2017 ◽  
Vol 260 ◽  
pp. 149-156 ◽  
Author(s):  
Yeming Dai ◽  
Yan Gao ◽  
Hongwei Gao ◽  
Hongbo Zhu
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Stackelberg Game ◽  
Pricing Scheme ◽  
Multiple Power ◽  
Real Time Pricing

scholarly journals Real-Time Pricing for Demand Response in Smart Grid Based on Alternating Direction Method of Multipliers

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Hongbo Zhu ◽  
Yan Gao ◽  
Yong Hou
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Supply And Demand ◽  
Iteration Process ◽  
Optimization Method ◽  
Alternating Direction Method ◽  
Lagrangian Multiplier ◽  
Method Of Multipliers ◽  
Alternating Direction ◽  
Real Time Pricing

The real-time pricing (RTP) scheme is an ideal method to adjust the power balance between supply and demand in smart grid systems. This scheme has a profound impact on users’ behavior, system operation, and overall grid management in the electricity industry. In this research, we conduct an extended discussion of a RTP optimization model and give a theoretical analysis of the existence and uniqueness of the Lagrangian multiplier. A distributed optimization method based on the alternating direction method of multipliers (ADMM) algorithm with Gaussian back substitution (GBS) is proposed in this study. On the one hand, the proposed algorithm takes abundant advantage of the separability among variables in the model. On the other hand, the proposed algorithm can not only speed up the convergence rate to enhance the efficiency of computing, but also overcome the deficiency of the distributed dual subgradient algorithm, the possibility of nonconvergence in the iteration process. In addition, we give the theoretical proof of the convergence of the proposed algorithm. Furthermore, the interdependent relationship between variables has been discussed in depth during numerical simulations in the study. Compared with the dual subgradient method, the simulation results validate that the proposed algorithm has a higher convergence speed and better implementation effect.

scholarly journals Real-Time Pricing Scheme in Smart Grid Considering Time Preference: Game Theoretic Approach

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6138
Author(s):  
Ri Piao ◽  
Deok-Joo Lee ◽  
Taegu Kim
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Time Preference ◽  
Stackelberg Game ◽  
Price Policy ◽  
Theoretic Approach ◽  
Time Zone ◽  
Efficient Operation ◽  
Game Theoretic ◽  
Real Time Pricing

Unbalanced power demand across time slots causes overload in a specific time zone. Various studies have proved that this can be mitigated through smart grid and price policy, but research on time preference is insufficient. This study proposed a real-time pricing model on a smart grid through a two-stage Stackelberg game model based on a utility function that reflects the user’s time preference. In the first step, the suppliers determine the profit-maximizing price, and then, the users decide the electricity usage schedule according to the given price. Nash equilibrium and comparative analysis of the proposed game explain the relationship between time preference, price, and usage. Additionally, a Monte Carlo simulation demonstrated the effect of the change in time preference distribution. The experimental results confirmed that the proposed real-time pricing method lowers peak-to-average ratio (PAR) and increases overall social welfare. This study is meaningful in that it presents a pricing method that considers both users’ and suppliers’ strategies with time preference. It is expected that the proposed method would contribute to a reduction in the need for additional power generation facilities through efficient operation of the smart grid.

scholarly journals Distributed Real-Time Pricing Method Incorporating Load Uncertainty Based on Nonsmooth Equations for Smart Grid

2019 ◽  
Vol 2019 ◽  
pp. 1-18
Author(s):  
Hongjie Wang ◽  
Yan Gao
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Distributed Algorithm ◽  
Energy Supply ◽  
Supply And Demand ◽  
Nonsmooth Equations ◽  
Lagrangian Multipliers ◽  
Load Uncertainty ◽  
The Real ◽  
Real Time Pricing

The real-time pricing mechanism of smart grid based on demand response is an effective means to adjust the balance between energy supply and demand, whose implementation will impact the user's electricity consumption behaviour, the operation, and management in the future power systems. In this paper, we propose a complementarity algorithm to solve the real-time pricing of smart grid. The Karush–Kuhn–Tucker condition is considered in the social welfare maximisation model incorporating load uncertainty to transforming the model into a system of nonsmooth equations with Lagrangian multipliers, i.e., the shadow prices. The shadow price is used to determine the basic price of electricity. The system of nonsmooth equations is a complementarity problem, which enables us to study the existence and uniqueness of the equilibrium price and to design an online distributed algorithm to achieve the equilibrium between energy supply and demand. The proposed method is implemented in a simulation system composed of an energy provider and 100 users. Simulations results show that the proposed algorithm can motivate the users’ enthusiasm to participate in the demand side management and shift the peak loading. Furthermore, the proposed algorithm can improve the supply shortage. When compared with an online distributed algorithm based on the dual optimisation method, the proposed algorithm has a significantly lower running time and more accurate Lagrangian multipliers.

scholarly journals Real-Time Pricing Decision Based on Leader-Follower Game in Smart Grid

2015 ◽  
Vol 3 (4) ◽  
pp. 348-356 ◽  
Author(s):  
Yeming Dai ◽  
Yan Gao
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Equilibrium Solution ◽  
Demand Function ◽  
Pricing Strategy ◽  
Demand Side ◽  
Pricing Decision ◽  
Game Situation ◽  
Simulation Results ◽  
Real Time Pricing

AbstractThe real-time pricing plays an important role in demand-side management for smart grid. In this paper, we study real-time pricing strategy of electricity retailers by means of game theory in smart grid. The retailers are in the game situation where there is one leader with multi-followers. We propose a real-time electricity demand function and analyze the interactions between the retailers, then obtain its equilibrium solution. The analysis and simulation results of the equilibrium solution show the effectiveness of the proposed method.

scholarly journals A Real-Time Pricing Scheme for Energy Management in Integrated Energy Systems: A Stackelberg Game Approach

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2858 ◽  
Author(s):  
Tengfei Ma ◽  
Junyong Wu ◽  
Liangliang Hao ◽  
Huaguang Yan ◽  
Dezhi Li
Keyword(s):  
Real Time ◽  
Stackelberg Game ◽  
Supply And Demand ◽  
Energy System ◽  
Stackelberg Equilibrium ◽  
Energy Hub ◽  
Pricing Scheme ◽  
Real Time Pricing ◽  
Aggregated Load ◽  
Energy Provider

This paper proposes a real-time pricing scheme for the demand response management between one energy provider and multiple energy hub operators. A promising energy trading scenario has been designed for the near future integrated energy system. The Stackelberg game approach was employed to capture the interactions between the energy provider (leader) and energy consumers (follower). A distributed algorithm was proposed to derive the Stackelberg equilibrium, then, the best strategies for the energy provider and each energy hub operator were explored in order to maximize their benefits. Simulation results showed that the proposed method can balance the energy supply and demand, improve the payoffs for all players, as well as smooth the aggregated load profiles of all energy consumers.

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