Short Term Hydro-Thermal Scheduling Using Backtracking Search Algorithm

Short Term Hydro-Thermal Scheduling Using Backtracking Search Algorithm

Koustav Dasgupta (Techno India University, West Bengal, India) and Provas Kumar Roy (Kalyani Government Engineering College, West Bengal, India)
Copyright: © 2020 |Pages: 26
DOI: 10.4018/IJAMC.2020100103


In this article, a new optimization technique, the backtracking search algorithm (BSA), is proposed to solve the hydrothermal scheduling problem. The BSA has mainly unique five steps: (i) Initialization; (ii) Selection – I; (iii) Mutation; (iv) Crossover; and (v) Selection – II; which have been applied to minimize fuel cost of the hydro-thermal scheduling problem. The BSA is very fast, robust, reliable optimization technique and gives an accurate, optimized result. Mutation and crossover are very effective steps of the BSA, which help to determine the better optimum value of the objective function. Here, four hydro and three thermal power generating units are considered. Performance of each committed generating units (hydro and thermal) are also analyzed using a new proposed algorithm, the BSA. A multi-reservoir cascaded hydroelectric with a nonlinear relationship between water discharge rate and power generation is considered. The valve point loading effect is also considered with a fuel cost function. The proposed optimum fuel cost obtained from the BSA shows the better result as compared to other techniques like particle swarm optimization (PSO), teaching learning-based optimization (TLBO), quasi-oppositional teaching learning-based optimization (QOTLBO), real-coded genetic algorithm (RCGA), mixed-integer linear programming (MILP) and krill herd algorithm (KHA), etc.
Article Preview

1. Introduction

Hydrothermal scheduling (HTS) is one of the important optimization problem, and it is solved using different optimization techniques. Recently different optimization techniques have been implemented in an advanced power system area to solve different problems. The objective of the hydrothermal scheduling problem is a task of allocation of power among different committed generating units for the fulfillment of demand power of scheduled period with minimum generation cost and fulfillment of generating constraints of different generating units. HTS problem consists of complex and nonlinear characteristics with various types of constraints. Hydro and thermal power are considered to the fulfillment of demand power of scheduled period for the problem, HTS. The thermal power plant has low installation cost but high running cost. The hydropower plant has high installation cost but low running cost. The integrated operation of the hydro and thermal plants in the same grid has become more economical. The main goal of the hydrothermal scheduling problem is to determine the water releases from each reservoir of the hydro system at each stage so that the operating cost is minimized along the scheduling period. Literature survey shows that over the past years, HTS problem was solved using various types of optimization technique. Over the past years, HTS problems have been solved using various mathematical optimization techniques. Such classical optimization techniques have some drawbacks which require a longer time to yield optimal results.

Table 1.
List of symbols
IJAMC.2020100103.m01Emission coefficients of IJAMC.2020100103.m02thermal unitIJAMC.2020100103.m03Number of hydro generating units
IJAMC.2020100103.m04Fuel cost curve coefficients of IJAMC.2020100103.m05 thermal unitIJAMC.2020100103.m06Load demand at time m
IJAMC.2020100103.m07Power generation coefficients of jth hydro unitIJAMC.2020100103.m08, IJAMC.2020100103.m09Minimum and maximum power generation limits for IJAMC.2020100103.m10 hydro unit
DljWater transport delay from reservoir lth to jth reservoirIJAMC.2020100103.m11Transmission loss at time m
IJAMC.2020100103.m12Total fuel cost of the thermal unitsIJAMC.2020100103.m13, IJAMC.2020100103.m14Minimum and maximum power generation limits for IJAMC.2020100103.m15 thermal unit
IJAMC.2020100103.m16inflow rate of jth reservoir at timeIJAMC.2020100103.m17Power generation of IJAMC.2020100103.m18 thermal unit at time m
IJAMC.2020100103.m19Number of time intervals i.e., scheduling periodIJAMC.2020100103.m20Power generation of jth hydro unit at time m
NTNumber of thermal generating unitsIJAMC.2020100103.m21Water discharge rate of jth hydro reservoir at time m
IJAMC.2020100103.m22Minimum and maximum water discharge rate for jth hydro reservoirIJAMC.2020100103.m23Water storage volume of jth hydro reservoir at the beginning of time m
IJAMC.2020100103.m24Number of upstream hydro generating plants directly above the jth hydro reservoirIJAMC.2020100103.m25Minimum and maximum water storage volume of the jth hydro reservoir
IJAMC.2020100103.m26Spillage discharge rate of the jth reservoir at time m

Complete Article List

Search this Journal:
Open Access Articles: Forthcoming
Volume 12: 4 Issues (2021): Forthcoming, Available for Pre-Order
Volume 11: 4 Issues (2020)
Volume 10: 4 Issues (2019)
Volume 9: 4 Issues (2018)
Volume 8: 4 Issues (2017)
Volume 7: 4 Issues (2016)
Volume 6: 4 Issues (2015)
Volume 5: 4 Issues (2014)
Volume 4: 4 Issues (2013)
Volume 3: 4 Issues (2012)
Volume 2: 4 Issues (2011)
Volume 1: 4 Issues (2010)
View Complete Journal Contents Listing