ANT LION OPTIMIZATION ALGORITHM FOR SOLVING GENERATION EXPANSION PLANNING ISSUES

Abstract

In this paper, a mathematical optimization algorithm is utilized to solve the Generation Expansion Planning (GEP) problem. To address the issues of emissions of carbon dioxide and to reduce their effects to a reasonable limit, the CCS (carbon capture and storage) technologies are to be incorporated with the conventional plants. The combination of GEP including CCS problem is proposed to minimize the planning cost as well as environmental greenhouse gasses simultaneously, while it considers CCS cost and revenue cost over a long term planning horizon. In this paper, an Ant lion Optimization (ALO) algorithm, a nature inspired algorithm is used to simplify the mathematical problem. It is based on the hunting process of ant lions in nature. Main objective of the paper is to minimize the planning cost and emission cost based on their security constraints like reliability and reserve margin and the financial constraints. The investment cost and cost of operation of existing and new generating units are also be analyzed. MATLAB/Simulink is used to determine the performance of the proposed method and its performance is with Artificial Bee Colony (ABC) Algorithm and Gravitational Search Algorithm (GSA).