Open AccessFlexible, reliable, and renewable power system resource expansion planning considering energy storage systems and demand response programs
Author(s) -
Hamidpour Hamidreza,
Aghaei Jamshid,
Pirouzi Sasan,
Dehghan Shahab,
Niknam Taher
Publication year - 2019
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
ISSN - 1752-1424
DOI - 10.1049/iet-rpg.2019.0020
Subject(s) - mathematical optimization , electric power system , unavailability , flexibility (engineering) , reliability (semiconductor) , computer science , demand response , linear programming , energy storage , renewable energy , stochastic programming , reliability engineering , engineering , power (physics) , electricity , mathematics , electrical engineering , physics , quantum mechanics , statistics
This study presents a flexible, reliable, and renewable power system resource planning approach to coordinate generation, transmission, and energy storage (ES) expansion planning in the presence of demand response (DR). The flexibility and reliability of the optimal resource expansion planning are ensured by means of appropriate constraints incorporated into the proposed planning tool where thermal generation units, ES systems, and DR programs are considered as flexibility resources. The proposed planning tool is a mixed‐integer non‐linear programming (MINLP) problem due to the non‐linear and non‐convex constraints of AC power flow equations. Accordingly, to linearise the proposed MINLP problem, the AC nodal power balance constraints are linearised by means of the first‐order expansion of Taylor's series and the line flow equations are linearised by means of a polygon. Additionally, the stochastic programming is used to characterise the uncertainty of loads, a maximum available power of wind farms, forecasted energy price, and availability/unavailability of generation units and transmission lines by means of a sufficient number of scenarios. The proposed planning tool is implemented on the IEEE 6‐bus and the IEEE 30‐bus test systems under different conditions. Case studies illustrate the effectiveness of the proposed approach based on both flexibility and reliability criteria.