Two‐stage algorithm for efficient transmission expansion planning with renewable energy resources. Issue 3 (1st February 2017)

• Record Type: Journal Article
• Authors: Majumder, Subir; Shereef, R. M.; Khaparde, Shrikrishna A.
• Is Part Of: IET renewable power generation. Volume 11:Issue 3(2017)
• Page Start: 320
• Page End: 329
• Publication Date: 2017-02-01
• Subjects: power transmission planning -- renewable energy sources -- deterministic algorithms -- minimisation -- power generation scheduling -- power transmission reliability -- investment; efficient transmission expansion planning -- renewable energy resources -- two‐stage deterministic algorithm -- RE generation forecast error mitigation -- zero‐RE penetration -- reference scenario -- cost‐minimisation objective -- network performance -- congestion cost -- locational marginal prices -- unit scheduling problem -- planning horizon -- delayed investment -- IEEE 24‐bus reliability test system; Renewable energy sources -- Periodicals; 333.79405
• DOI: 10.1049/iet-rpg.2016.0085
• Languages: English
• ISSNs: 1752-1416

Abstract

Abstract : In this study, a 'two‐stage' deterministic algorithm an for efficient transmission expansion planning with renewable energy (RE) resources under the assumption that existing conventional generators provide the reserve to mitigate RE generation forecast error has been proposed. Zero‐RE penetration has been considered as a 'reference scenario', as well as cost‐minimisation objective has been considered as a planning criterion in Stage 1 . In the proposed algorithm, Stage 2 is required to be solved only if the network performance degrades in relation to the reference scenario. In Stage 2, congestion cost is also incorporated as a sub‐objective. Here, the locational marginal prices of the unit scheduling problem obtained from the solution of Stage 1 have been used to calculate the congestion cost. In addition to being computationally tractable, the proposed algorithm guarantees performance improvement in the network. The planning horizon is divided into smaller blocks to facilitate delayed investment. When implemented on an IEEE 24‐bus reliability test system, the proposed algorithm generated minimum cost plan with better performance.