Collaborative optimization of distribution network and 5G mobile network with renewable energy sources in smart grid. (September 2021)

• Record Type: Journal Article
• Authors: Han, Jianpei; Liu, Nian; Huang, Yujing; Zhou, Zhenyu
• Is Part Of: International journal of electrical power & energy systems. Volume 130(2021)
• Publication Date: 2021-09
• Subjects: Distribution network -- Renewable energy sources -- Demand response -- Stackelberg game -- Distributed solution; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2021.107027
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: The collaborative optimization framework of distribution network and mobile network is proposed. Optimal models of DNO and MNO with coupon incentive-based DR are established. Stackelberg game model is employed to model the interaction between DNO and MNO. Decentralized solution algorithm is designed to obtain SE with limited information exchange. Abstract: Renewable energy sources are beneficial for both distribution network and mobile network in the context of Smart Grid, but brings greater challenges with high proportions of renewable energy penetration. In this regard, a Stackelberg game-based collaborative optimization approach is proposed for distribution network and 5G mobile network based on demand response, where the distribution network operator (DNO) works as a leader who chooses proper interactive price to reduce the peak-valley difference of net load while mobile network operator (MNO) serves as a follower who minimizes its total energy cost in response to the interactive price set by DNO. Besides, an exact convex relaxation method is proposed to omit the complementarity constraint in the optimal model of MNO, which makes the model strictly convex. Then, the existence and uniqueness of the Stackelberg equilibrium (SE) are analyzed and a distributed solution algorithm is suggested to reach the SE. The simulation results demonstrate that the proposed collaborative optimization approach can not only reduce the cost of DNO and MNO, but helpful to enhance renewable energy utilization, which realizes a win–win result.