Open AccessSystem state model based multi‐period robust generation, transmission, and demand side resource co‐optimisation planning
Author(s) -
Dai Chenxi,
Wu Lei,
Zeng Bo,
Liu Cong
Publication year - 2019
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.5936
Subject(s) - time horizon , mathematical optimization , software deployment , computer science , constraint (computer aided design) , transmission system , transmission (telecommunications) , operations research , cluster analysis , resource (disambiguation) , engineering , mathematics , artificial intelligence , telecommunications , computer network , mechanical engineering , operating system
This study discusses a multi‐period co‐optimised generation and transmission expansion planning (GTEP) problem while considering a proliferation of demand side resources (DSR). Uncertain renewable energy variations and load fluctuations in the long‐term planning horizon are addressed, and a system state model derived via k‐means clustering algorithm is adopted to capture temporal operation features. The problem is formulated as a two‐stage robust optimisation model with mixed‐integer recourse, in which annual investment decisions of generation, transmission, and DSR assets are determined in the first stage and short‐term operation decisions of individual system states are made in the second stage. In recognising that considering DSR deployment and the system state model brings significant computational complexity, an extended column‐and‐constraint‐generation algorithm is adopted to effectively solve the proposed planning problem. Numerical studies show that integrating DSRs into multi‐period GTEP could effectively postpone or even avoid expensive generation/transmission investment in the planning stage, and improve economic efficiency in the operation stage.