Open AccessMultistage multiobjective electricity generation expansion planning for Tamil Nadu considering least cost and minimal GHG emission
Author(s) -
Bhuvanesh Ananthan,
Jaya Christa Sargunam Thomas,
Kannan Subramanian,
Karuppasamy Pandiyan Murugesan
Publication year - 2019
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/etep.2708
Subject(s) - sorting , greenhouse gas , time horizon , electricity generation , multi objective optimization , mathematical optimization , genetic algorithm , electricity , economic dispatch , term (time) , computer science , operations research , electric power system , engineering , power (physics) , mathematics , algorithm , physics , quantum mechanics , electrical engineering , ecology , biology
Summary Developing countries like India necessitates installation of new power plants to meet the elevating electricity demand. Several single‐objective mathematical formulations are modeled and solved previously for short‐term and long‐term power generation expansion planning aiding power system planners to ensure optimal decision. The input data, such as forecasted demands, economic and technical data of the generating units are numerous and unmanageable to be analyzed manually. Modern power systems have faced major challenge in solving multiple objectives such as least cost and minimal greenhouse gas emissions simultaneously. This paper presents an application of multiobjective differential evolution algorithm to multistage, multiobjective generation expansion planning problem for Tamil Nadu, a state in India. The multiobjective generation expansion planning problem has been solved for short‐term (6 years) and long‐term (12 years) planning horizon by considering 8 different cases and also compared with Nondominated Sorting Genetic Algorithm version II.