Coordinating generation and load pickup during load restoration with discrete load increments and reserve constraints. Issue 15 (1st November 2015)

• Record Type: Journal Article
• Authors: Qin, Zhijun; Hou, Yunhe; Liu, Chen‐Ching; Liu, Shanshan; Sun, Wei
• Is Part Of: IET generation, transmission & distribution. Volume 9:Issue 15(2015)
• Page Start: 2437
• Page End: 2446
• Publication Date: 2015-11-01
• Subjects: power system restoration -- power generation reliability -- decision making -- integer programming -- nonlinear programming -- load flow -- IEEE standards -- tree searching; generation coordination -- power system reliability -- IEEE 118‐bus system -- RTS 24‐bus system -- problem‐specific branching method -- branch‐and‐cut solver -- MINLR model -- reserve constraint -- AC power flow -- multistage decision making process -- power system restoration -- coordinate control action -- mixed‐integer nonlinear load restoration model -- discrete load increment; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2015.0240
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : After a major outage happens, the independent system operator, transmission owners (TOs), generation owners (GOs), and distribution owners (DOs) should coordinate control actions to restore the power system timely and reliably. This study proposes a methodology to establish load restoration plans for the coordination among these participants. This methodology models the load restoration as a multi‐stage decision‐making process. At each stage, a mixed‐integer nonlinear load restoration model (MINLR) is formulated to maximise load pickup subject to AC power flow and reserve constraints. Comprehensive load characteristics are considered in this model. The solution of the MINLR model provides power set points for GOs/TOs and load pickup amount for DOs. A complete load restoration plan is obtained by solving a series of MINLR models. To solve MINLR models efficiently, a branch‐and‐cut solver is constructed by identifying efficient cutting planes and a reliable problem‐specific branching method. The applicability of cutting planes is proven. This methodology is tested using a 24‐bus system with 170 interrupted load increments, and a 118‐bus system with 637 interrupted load increments. The simulation results show that the proposed methodology can be efficiently applied to aid restoration participants pickup load increments within the TO's islands, while maintaining adequate reserve margins.