Computational Intelligent Algorithm for Optimal Generation Scheduling of Thermal Units with Renewable Energy Source

T.Anbazhagi,K. Asokan,R. Ashokkumar

This paper presents an intelligent methodology for generation scheduling of thermal generators considering renewable energy source of hydro plants. A novel approach of an Improved Ant line optimizer (IALO) algorithm is proposed to solve the Sort-Term Hydrothermal Scheduling (SHTS) problem. The prime objective of hydrothermal scheduling is to minimize the fuel cost over the planning period and satisfying standard system, thermal and hydro plants constraints. The proposed SHTS problem is modelled as a non linear, non convex and mixed integer optimization problem. This paper considering valve point loading effects and a set of equality and inequality constraints. The projected algorithm is based on the best and worst solutions obtained during the optimization process and the random interactions between the candidate solutions. It require only the common control parameters like population size and number of iterations and do not require any algorithm-specific control parameters. The effectiveness and applicability of the proposed algorithm is tested on two standard test systems such as four hydro with an equivalent thermal system and four hydro with three thermal test systems both system having a 24 hour time period. The simulation results are obtained from the proposed method in terms of water discharge ware storage volume, hydro and thermal power generation and total fuel cost. The total fuel cost of proposed method is compared to those other methods in the literature. The comparisons of results validated that the proposed method is more effective for solving the scheduling problem under regulated environment.

Volume 12 | 06-Special Issue

Pages: 7-21

DOI: 10.5373/JARDCS/V12SP6/SP20201002