Optimal siting and sizing of demand response in a transmission constrained system with high wind penetration. (June 2015)

• Record Type: Journal Article
• Authors: Wang, Beibei; Gayme, Dennice F.; Liu, Xiaocong; Yuan, Chenghao
• Is Part Of: International journal of electrical power & energy systems. Volume 68(2015:Jun.)
• Page Start: 71
• Page End: 80
• Publication Date: 2015-06
• Subjects: Demand response -- Transmission constraints -- High wind integration; 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.2014.12.019
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: An economic dispatch with transmission, DR capacity and operational constraints is proposed. The model can be used to decide the optimal sizing and distribution of DR. The results show buses electrically close to congested lines tend to have more DR resources. Enabling technology can be installed at particular nodes requiring faster response times. Abstract: This paper describes algorithms that use demand-side management to address large-scale integration of wind power. In particular, demand response (DR) is used to manage wind power intermittency by shifting the time that electrical power system loads occur in response to real-time prices and wind availability. An economic dispatch with transmission, DR capacity and operational constraints is used to model the operation of a transmission constrained system with a high penetration of wind power. This optimization model is used to determine the optimal sizing and distribution of DR given a fixed budget for customer incentives and the installation of enabling technology. We demonstrate the effectiveness of the operational model based on a simple PJM 5-bus system and an IEEE 118-bus system. Simulation results show that transmission constraints have a greater effect on sizing of DR capacity than the location of wind power, which means that buses electrically close to congested lines tend to have higher incentives to deploy DR resources than other buses. The second part of the work examines optimal siting of technology that enables DR based on the frequency of DR based load changes, which are generally a function of the network location.