**Commenced**in January 2007

**Frequency:**Monthly

**Edition:**International

**Paper Count:**10

# Search results for: Economic load dispatch

##### 10 Ramp Rate and Constriction Factor Based Dual Objective Economic Load Dispatch Using Particle Swarm Optimization

**Authors:**
Himanshu Shekhar Maharana,
S. K .Dash

**Abstract:**

Economic Load Dispatch (ELD) proves to be a vital optimization process in electric power system for allocating generation amongst various units to compute the cost of generation, the cost of emission involving global warming gases like sulphur dioxide, nitrous oxide and carbon monoxide etc. In this dissertation, we emphasize ramp rate constriction factor based particle swarm optimization (RRCPSO) for analyzing various performance objectives, namely cost of generation, cost of emission, and a dual objective function involving both these objectives through the experimental simulated results. A 6-unit 30 bus IEEE test case system has been utilized for simulating the results involving improved weight factor advanced ramp rate limit constraints for optimizing total cost of generation and emission. This method increases the tendency of particles to venture into the solution space to ameliorate their convergence rates. Earlier works through dispersed PSO (DPSO) and constriction factor based PSO (CPSO) give rise to comparatively higher computational time and less good optimal solution at par with current dissertation. This paper deals with ramp rate and constriction factor based well defined ramp rate PSO to compute various objectives namely cost, emission and total objective etc. and compares the result with DPSO and weight improved PSO (WIPSO) techniques illustrating lesser computational time and better optimal solution.

**Keywords:**
Economic load dispatch,
constriction factor based particle swarm optimization,
dispersed particle swarm optimization,
weight improved particle swarm optimization,
ramp rate and constriction factor based particle swarm optimization.

##### 9 Non-Convex Multi Objective Economic Dispatch Using Ramp Rate Biogeography Based Optimization

**Authors:**
Susanta Kumar Gachhayat,
S. K. Dash

**Abstract:**

Multi objective non-convex economic dispatch problems of a thermal power plant are of grave concern for deciding the cost of generation and reduction of emission level for diminishing the global warming level for improving green-house effect. This paper deals with ramp rate constraints for achieving better inequality constraints so as to incorporate valve point loading for cost of generation in thermal power plant through ramp rate biogeography based optimization involving mutation and migration. Through 50 out of 100 trials, the cost function and emission objective function were found to have outperformed other classical methods such as lambda iteration method, quadratic programming method and many heuristic methods like particle swarm optimization method, weight improved particle swarm optimization method, constriction factor based particle swarm optimization method, moderate random particle swarm optimization method etc. Ramp rate biogeography based optimization applications prove quite advantageous in solving non convex multi objective economic dispatch problems subjected to nonlinear loads that pollute the source giving rise to third harmonic distortions and other such disturbances.

**Keywords:**
Economic load dispatch,
Biogeography based optimization,
Ramp rate biogeography based optimization,
Valve Point loading,
Moderate random particle swarm optimization method,
Weight improved particle swarm optimization method

##### 8 Optimal Economic Load Dispatch Using Genetic Algorithms

**Authors:**
Vijay Kumar,
Jagdev Singh,
Yaduvir Singh,
Sanjay Sood

**Abstract:**

**Keywords:**
ELD,
Equality constraints,
Genetic algorithms,
Strings.

##### 7 Optimal Dynamic Economic Load Dispatch Using Artificial Immune System

**Authors:**
I. A. Farhat

**Abstract:**

The dynamic economic dispatch (DED) problem is one of the complex constrained optimization problems that have nonlinear, con-convex and non-smooth objective functions. The purpose of the DED is to determine the optimal economic operation of the committed units while meeting the load demand. Associated to this constrained problem there exist highly nonlinear and non-convex practical constraints to be satisfied. Therefore, classical and derivative-based methods are likely not to converge to an optimal or near optimal solution to such a dynamic and large-scale problem. In this paper, an Artificial Immune System technique (AIS) is implemented and applied to solve the DED problem considering the transmission power losses and the valve-point effects in addition to the other operational constraints. To demonstrate the effectiveness of the proposed technique, two case studies are considered. The results obtained using the AIS are compared to those obtained by other methods reported in the literature and found better.

**Keywords:**
Artificial Immune System (AIS),
Dynamic Economic Dispatch (DED).

##### 6 Optimal Dynamic Economic Load Dispatch Using Artificial Immune System

**Authors:**
I. A. Farhat

**Abstract:**

The The dynamic economic dispatch (DED) problem is one of the complex constrained optimization problems that have nonlinear, con-convex and non-smooth objective functions. The purpose of the DED is to determine the optimal economic operation of the committed units while meeting the load demand. Associated to this constrained problem there exist highly nonlinear and non-convex practical constraints to be satisfied. Therefore, classical and derivative-based methods are likely not to converge to an optimal or near optimal solution to such a dynamic and large-scale problem. In this paper, an Artificial Immune System technique (AIS) is implemented and applied to solve the DED problem considering the transmission power losses and the valve-point effects in addition to the other operational constraints. To demonstrate the effectiveness of the proposed technique, two case studies are considered. The results obtained using the AIS are compared to those obtained by other methods reported in the literature and found better.

**Keywords:**
Artificial Immune System (AIS),
Dynamic Economic Dispatch (DED).

##### 5 Application of Particle Swarm Optimization for Economic Load Dispatch and Loss Reduction

**Authors:**
N. Phanthuna,
J. Jaturacherdchaiskul,
S. Lerdvanittip,
S. Auchariyamet

**Abstract:**

This paper proposes a particle swarm optimization (PSO) technique to solve the economic load dispatch (ELD) problems. For the ELD problem in this work, the objective function is to minimize the total fuel cost of all generator units for a given daily load pattern while the main constraints are power balance and generation output of each units. Case study in the test system of 40-generation units with 6 load patterns is presented to demonstrate the performance of PSO in solving the ELD problem. It can be seen that the optimal solution given by PSO provides the minimum total cost of generation while satisfying all the constraints and benefiting greatly from saving in power loss reduction.

**Keywords:**
Particle Swarm Optimization,
Economic Load Dispatch,
Loss Reduction.

##### 4 Economic Load Dispatch with Daily Load Patterns and Generator Constraints by Particle Swarm Optimization

**Authors:**
N. Phanthuna V. Phupha N. Rugthaicharoencheep,
S. Lerdwanittip

**Abstract:**

This paper presents an optimization technique to economic load dispatch (ELD) problems with considering the daily load patterns and generator constraints using a particle swarm optimization (PSO). The objective is to minimize the fuel cost. The optimization problem is subject to system constraints consisting of power balance and generation output of each units. The application of a constriction factor into PSO is a useful strategy to ensure convergence of the particle swarm algorithm. The proposed method is able to determine, the output power generation for all of the power generation units, so that the total constraint cost function is minimized. The performance of the developed methodology is demonstrated by case studies in test system of fifteen-generation units. The results show that the proposed algorithm scan give the minimum total cost of generation while satisfying all the constraints and benefiting greatly from saving in power loss reduction

**Keywords:**
Particle Swarm Optimization,
Economic Load Dispatch,
Generator Constraints.

##### 3 An Intelligent Water Drop Algorithm for Solving Economic Load Dispatch Problem

**Authors:**
S. Rao Rayapudi

**Abstract:**

**Keywords:**
Economic load dispatch,
Transmission loss,
Optimization,
Valve point loading,
Intelligent Water Drop Algorithm.

##### 2 Economic Dispatch Fuzzy Linear Regression and Optimization

**Authors:**
A. K. Al-Othman

**Abstract:**

**Keywords:**
Economic Dispatch,
Fuzzy Linear Regression (FLP)and Optimization.

##### 1 Application of Computational Intelligence Techniques for Economic Load Dispatch

**Authors:**
S.C. Swain,
S. Panda,
A.K. Mohanty,
C. Ardil

**Abstract:**

This paper presents the applications of computational intelligence techniques to economic load dispatch problems. The fuel cost equation of a thermal plant is generally expressed as continuous quadratic equation. In real situations the fuel cost equations can be discontinuous. In view of the above, both continuous and discontinuous fuel cost equations are considered in the present paper. First, genetic algorithm optimization technique is applied to a 6- generator 26-bus test system having continuous fuel cost equations. Results are compared to conventional quadratic programming method to show the superiority of the proposed computational intelligence technique. Further, a 10-generator system each with three fuel options distributed in three areas is considered and particle swarm optimization algorithm is employed to minimize the cost of generation. To show the superiority of the proposed approach, the results are compared with other published methods.

**Keywords:**
Economic Load Dispatch,
Continuous Fuel Cost,
Quadratic Programming,
Real-Coded Genetic Algorithm,
Discontinuous Fuel Cost,
Particle Swarm Optimization.