This paper presents a new multi-objective harmony search (MOHS) algorithm for environmental/economic dispatch (EED) problem. The EED problem is formulated as a non linear and constrained optimization problem with competing and non-commensurable objectives. The two competing objectives, fuel cost and emission, were optimized simultaneously using the proposed MOHS algorithm. The MOHS algorithm uses a non dominated sorting and ranking procedure with dynamic crowding distance to develop and maintain a well distributed Pareto-optimal set. The proposed algorithm has been tested on the standard IEEE 30 bus and 118 bus systems. Simulation results are compared with the fast non dominated sorting genetic algorithm (NSGA-II) method. The results clearly show that the proposed method is able to produce a well distributed Pareto-optimal solutions than the NSGA-II method. © 2011 Elsevier B.V. All rights reserved.

Shanti K. Swarup

Department of Electrical Engineering

Bus systems

Constrained optimization problems

Cost minimization

CROWDING DISTANCE

ENVIRONMENTAL/ECONOMIC DISPATCH

FUEL COST

Harmony search

HARMONY SEARCH ALGORITHMS

Multi objective

NON-DOMINATED SORTING

NON-DOMINATED SORTING GENETIC ALGORITHMS

Non-linear

NSGA-II

Pareto optimal solutions

PARETO-OPTIMAL SETS

RANKING PROCEDURES

Simulation result

constrained optimization

Learning algorithms

Multiobjective optimization

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Electric Power Systems Research

Power system is a large-scale network with a number of components and interconnections for which centralized control becomes cumbersome. For multi-area computations, decentralization is necessary. For implementation of this approach network decomposition becomes an essential task. In this paper the network decomposition problem is solved as an optimization problem using the harmony search (HS) algorithm. To improve the performance of the HS algorithm, a widely used graph bi-partitioning method called Kernighan-Lin (KL) strategy is used in the improvisation process. KL strategy is used in the partitioning of digital and VLSI circuits and is suitable for bi-partitioning networks. The connectivity of the partitioned clusters are checked by means of graph traversal techniques. Simulation are carried out on IEEE Standard systems and found to be very effective in decomposition of the system hierarchically. © 2012 Elsevier B.V. All rights reserved.

Swarm and Evolutionary Computation

Network decomposition using Kernighan-Lin strategy aided harmony search algorithm

Power system has a highly interconnected network that requires intense computational effort and resources for centralized control. Distributed computing needs the systems to be partitioned optimally into clusters. The network partitioning is an optimization problem whose objective is to minimize the number of nodes in a cluster and the tie lines between the clusters. Harmony Search(HS) Algorithm is one of the recently developed meta heuristic algorithms that can be applied to optimization problems. In this work, the HS algorithm is applied to the network partitioning problem and power flow based equivalencing is done to represent the external system. Simulation is done on IEEE Standard Test Systems. The algorithm is found to be very effective in partitioning the system hierarchically and the equivalencing method gives accurate results in comparison to the centralized control. © 2012 Elsevier Inc. All rights reserved.

Journal of Parallel and Distributed Computing

Network partitioning using harmony search and equivalencing for distributed computing

The purpose of the combined economic emission dispatch of generation in an electric power is to offer the finest schedule for the generating units which must run with both lesser fuel cost and emission levels concurrently thereby fulfilling the system equality and inequality constraints. This paper presents an interior search algorithm (ISA) for solving multi-objective combined economic emission dispatch (CEED) problems. Simulation results obtained substantiate the efficiency of ISA algorithm in solving the CEED problems. The effectiveness of the proposed ISA is investigated on five various test systems which comprise three-unit system, IEEE 30-bus system, 10-unit system, 20-unit system, and Taiwan 40-unit generating system. Simulation results and their comparison with other meta-heuristic optimization techniques reveal that the proposed ISA is proficient in solving CEED problem of fossil fuel generators. © 2018 John Wiley &amp; Sons, Ltd.

International Transactions on Electrical Energy Systems

Multi-objective economic emission dispatch using interior search algorithm

Arabian Journal for Science and Engineering

Application and Comparison of PSO, its Variants and HDE Techniques to Emission/Economic Dispatch

A differential evolution approach to solve optimal power flow problem with multiple and competing objectives is presented. Two sub-problems of optimal power flow namely active power dispatch and reactive power dispatch are considered. The problem is formulated as a nonlinear constrained true multi-objective optimisation problem with competing objectives. Constrain-domination approach have been used to handle inequality constraints, which eliminates the use of penalty factors. The performance of the proposed approach was tested on standard IEEE 30-bus system and is compared with a conventional method. The result demonstrates the capability of the proposed approach to generate diverse and well-distributed Pareto-optimal solutions. © 2008 The Institution of Engineering and Technology.

IET Generation, Transmission and Distribution

Solving multi-objective optimal power flow using differential evolution

Environmental/economic power dispatch problem using multi-objective differential evolution algorithm

International Journal of Electrical Power & Energy Systems

Environmental/economic power dispatch using a hybrid multi-objective optimization algorithm

Electric Power Components and Systems

Application of Biogeography-based Optimization for Solving Multi-objective Economic Emission Load Dispatch Problems

Energy Conversion and Management

An improved harmony search algorithm for power economic load dispatch

Environmental/economic dispatch using multi-objective harmony search algorithm

Journal	Electric Power Systems Research
ISSN	03787796
Open Access	No