Question

give example (tutorial) to calculate optimal power flow using ant colony optimization for any system. please answer step by step

Answer 1

INTRODUCTION

This chapter covers existing methodologies for solution of Optimal Power Flow (OPF) problem. They include formulation of OPF problem, objective function, constraints, applications and in-depth coverage of various popular OPF methods.

The OPF methods are broadly grouped as Conventional and Intelligent. The conventional methodologies include the well known techniques like Gradient method, Newton method, Quadratic Programming method, Linear Programming method and Interior point method. Intelligent methodologies include the recently developed and popular methods like Genetic Algorithm, Particle swarm optimization. Solution methodologies for optimum power flow problem are extensively covered in this chapter.

OPTIMAL POWER FLOW PROBLEM

In an OPF, the values of some or all of the control variables need to be found so as to optimise (minimise or maximize) a predefined objective. It is also important that the proper problem definition with clearly stated objectives be given at the onset. The quality of the solution depends on the accuracy of the model studied. Objectives must be modeled and its practicality with possible solutions.

Objective function takes various forms such as fuel cost, transmission losses and reactive source allocation. Usually the

objective function of interest is the minimisation of total production cost of scheduled generating units. This is most used as it reflects current economic dispatch practice and importantly cost related aspect is always ranked high among operational requirements in Power Systems.

OPF aims to optimise a certain objective, subject to the network power flow equations and system and equipment operating limits. The optimal condition is attained by adjusting the available controls to minimise an objective function subject to specified operating and security requirements.

Some well-known objectives can be identified as below:

Active power objectives

1. Economic dispatch (minimum cost, losses, MW generation or transmission losses)

2. Environmental dispatch

3. Maximum power transfer

Reactive power objectives

MW and MVAr loss minimization

General goals

1. Minimum deviation from a target schedule

2. Minimum control shifts to alleviate Violations

3. Least absolute shift approximation of control shift

Among the above the following objectives are most commonly used:

1. (a) Fuel or active power cost optimisation

2. (b) Active power loss minimisation

3. (c) VAr planning to minimise the cost of reactive power support