scholarly journals Collaborative Decision Approach for Electricity Pricing-demand Response Stackelberg Game

Author(s):  
Yang Chen ◽  
Mohammed Olama
Author(s):  
Atharva Ketkar ◽  
Joselyn Koonamparampath ◽  
Mayur Sawant

Abstract Electrical power, generated and consumed, is perhaps, one of today’s most important construct in determining the progress of a people. The power mismatch between the generated and consumed power is one of the major issues faced in the electricity industry. This can be addressed by analysing user behaviour and manipulating it. This paper attempts to put forth a demand response (DR) technique using the concept of Time-of-Use (ToU) electricity pricing. The utilities have an upper hand of quoting the electricity price whereas the users must follow this price and give their best response of power consumption. This process is similar to a leader-follower setting as in a Stackelberg game where the follower acts according to the leader’s strategy and gives its best response in every situation. This paper proposes a pricing technique where the users are charged according to the amount of power consumed in the specific period of time.


Energies ◽  
2020 ◽  
Vol 13 (19) ◽  
pp. 5213
Author(s):  
Zishan Guo ◽  
Zhenya Ji ◽  
Qi Wang

Demand response (DR) can offer a wide range of advantages for electrical systems by facilitating the interaction and balance between supply and demand. However, DR always requires a central agent, giving rise to issues of security and trust. Besides this, differences in user response cost characteristics are not taken into consideration during incentive pricing, which would affect the equal participation of users in DR and increase the costs borne by the electricity retail company. In this paper, a blockchain-enabled DR scheme with an individualized incentive pricing mode is proposed. First, a blockchain-enabled DR framework is proposed to promote the secure implementation of DR. Next, a dual-incentive mechanism is designed to successfully implement the blockchain to DR, which consists of a profit-based and a contribution-based model. An individualized incentive pricing mode is adopted in the profit-based model to decrease the imbalance in response frequency of users and reduce the costs borne by the electricity retail company. Then, the Stackelberg game model is constructed and Differential Evolution (DE) is used to produce equilibrium optimal individualized incentive prices. Finally, case studies are conducted. The results demonstrate that the proposed scheme can reduce the cost borne by the electricity retail company and decrease the imbalance among users in response frequency.


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