Strategic demand response framework for energy management in distribution system based on network loss sensitivity. Issue 8 (December 2020)

• Record Type: Journal Article
• Authors: Kumar, Sampath; Sushama, M
• Other Names: Caliskan Hakan guest-editor.; Reddy Koduru Janardhan guest-editor.; Sohret Yasin guest-editor.
• Is Part Of: Energy & environment. Volume 31:Issue 8(2020)
• Page Start: 1385
• Page End: 1402
• Publication Date: 2020-12
• Subjects: Demand response -- network loss sensitivity -- distribution system -- loss minimization -- voltage profile; Power resources -- Environmental aspects -- Periodicals; Power resources -- Periodicals; Renewable energy sources -- Periodicals; Energy policy -- Environmental aspects -- Periodicals; Ressources énergétiques; Politique énergétique; Energy policy -- Environmental aspects; Power resources; Power resources -- Environmental aspects; Renewable energy sources; Periodicals; 333.7
• DOI: 10.1177/0958305X19893041
• Languages: English
• ISSNs: 0958-305X

Abstract

This paper discusses an energy management system–based demand response scheduling strategy in distribution system. The proposed strategy includes customer payment minimization and network loss minimization as responsive load scheduling objectives through centralized approach. Two types of optimization strategies each based on payment minimization and network loss sensitivity are discussed in this paper. Thus, the proposed scheduling strategy can effectively resolve the optimality issue between different objectives of the distribution system scheduling under demand response penetration. The demand response scheduling strategies are simulated using standard IEEE 37 bus distribution test system through different cases of scheduling and optimization scenarios. The simulation results are presented, discussed, and compared with the base test cases without demand response penetration and without optimization strategies under demand response penetration to demonstrate the effectiveness of network loss, sensitivity consideration and optimization strategies in carrying out distribution system scheduling. In addition, sensitivity analysis is performed. The variation of distribution network performance is analyzed for various test cases and scenarios at different penetration levels.