A Comparative Analysis on Economic Load Dispatch Problem Using Soft Computing Techniques

2020 ◽  
Vol 12 (2) ◽  
pp. 50-73 ◽  
Author(s):  
O.V. Singh ◽  
M. Singh
Keyword(s):  
Search Algorithm ◽  
Optimal Solution ◽  
Inequality Constraints ◽  
Optimization Techniques ◽  
Flower Pollination Algorithm ◽  
Economic Load Dispatch ◽  
Flower Pollination ◽  
Soft Computing Techniques ◽  
Equality And Inequality Constraints ◽  
Optimization Search

This article aims at solving economic load dispatch (ELD) problem using two algorithms. Here in this article, an implementation of Flower Pollination (FP) and the BAT Algorithm (BA) based optimization search algorithm method is applied. More than one objective is hoped to be achieve in this article. The combined economic emission dispatch (CEED) problem which considers environmental impacts as well as the cost is also solved using the two algorithms. Practical problems in economic dispatch (ED) include both nonsmooth cost functions having equality and inequality constraints which make it difficult to find the global optimal solution using any mathematical optimization. In this article, the ELD problem is expressed as a nonlinear constrained optimization problem which includes equality and inequality constraints. The attainability of the discussed methods is shown for four different systems with emission and without emission and the results achieved with FP and BAT algorithms are matched with other optimization techniques. The experimental results show that conferred Flower Pollination Algorithm (FPA) outlasts other techniques in finding better solutions proficiently in ELD problems.

Implementation of Smooth and Non-Smooth Fuel Cost Function for Economic Load Dispatch using Cuckoo Search Method

2018 ◽  
Vol 8 (3) ◽  
Author(s):  
Apurva Gautam ◽  
Anupam Masih
Keyword(s):  
Cost Function ◽  
Power Plants ◽  
Search Algorithm ◽  
Inequality Constraints ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Economic Load Dispatch ◽  
Fuel Cost ◽  
Practical Applications ◽  
Equality And Inequality Constraints

Economic Load Dispatch (ELD) is an important topic in the operation of power plants which can help to build up effecting generating management plans. The ELD problem has no smooth cost function with equality and inequality constraints which make it difficult to be effectively solved. The paper presents an application of Cuckoo Search Algorithm (CSA) to solve Economic Load Dispatch (ELD) problems with smooth and non-smooth fuel cost objective functions. Main objective of ELD is to determine the most economic generating dispatch required to satisfy the predicted load demands including line losses over a certain period of time while relaxing various equality and inequality constraints. The unit Min/Max operational constraints, effects of valve-point loading ripples and line losses are considered for the practical applications. This paper describes the implementation of smooth and non smooth fuel cost function by CSA Method and its comparison with BAT method. We have used 6 and 12 bus system for calculating their total fuel cost.

scholarly journals Non-Convex Economic Dispatch with Prohibited Operating Zones through Gravitational Search Algorithm

2015 ◽  
Vol 5 (6) ◽  
pp. 1234
Author(s):  
Prakash Kumar Hota ◽  
Nakul Charan Sahu
Keyword(s):  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Optimal Solution ◽  
Inequality Constraints ◽  
New Approach ◽  
Prohibited Operating Zones ◽  
Optimal Power ◽  
Equality And Inequality Constraints ◽  
Simulation Results ◽  
Gravitational Search

This paper presents a new approach to the solution of optimal power generation for economic load dispatch (ELD) using gravitational search algorithm (GSA) when all the generators include valve point effects and some/all of the generators have prohibited operating zones. In this paper a gravitational search algorithm is suggested that deals with equality and inequality constraints in ELD problems. A constraint treatment mechanism is also discussed to accelerate the optimization process<strong>. </strong>To verify the robustness and superiority of the proposed GSA based approach, a practical sized 40-generators case with valve point effects and prohibited operating zones is considered. The simulation results reveal that the proposed GSA approach ensures convergence within an acceptable execution time and provides highly optimal solution as compared to the results obtained from well established heuristic optimization approaches.

Clearing Maximum Height With Constrained Kinetic Energy

1985 ◽  
Vol 52 (1) ◽  
pp. 179-184 ◽  
Author(s):  
M. Hubbard ◽  
J. C. Trinkle
Keyword(s):  
Kinetic Energy ◽  
Ground Plane ◽  
Optimal Solution ◽  
Inequality Constraints ◽  
Optimization Techniques ◽  
Initial Kinetic Energy ◽  
Maximum Height ◽  
Nonlinear Constrained Optimization ◽  
Moving Body ◽  
Equality And Inequality Constraints

This paper addresses the question: In order to clear a given height, defined as that which is passed over by all points in the moving body, what is the minimum initial kinetic energy required and what are the other conditions that specify the solution completely? An expression is derived for the height cleared above an original supporting ground plane. This transcendental expression is maximized numerically subject to certain equality and inequality constraints using nonlinear constrained optimization techniques. The optimal solution includes the height cleared and the required control variables. The parameter space of body descriptors in which the optimal solution is presented decomposes into two regions in which the solutions differ qualitatively.

Design and Implementation of Tuning PID Controller using Modern Optimization Techniques for Micro-Robotics System

2021 ◽  
Vol 10 (11) ◽  
pp. 51-68
Author(s):  
Ehab S. Ghith ◽  
◽  
Mohamed Sallam ◽  
Islam S. M. Khalil ◽  
Mohamed Youssef Serry ◽  
...  
Keyword(s):  
Steady State ◽  
Optimization Problems ◽  
Model Simulation ◽  
Search Algorithm ◽  
Optimal Parameter ◽  
Fitness Function ◽  
Optimization Techniques ◽  
Control Technique ◽  
Pid Controllers ◽  
Flower Pollination Algorithm

One of the main difficult tasks in the field of micro-robotics is the process of the selection of the optimal parameters for the PID controllers. Some methods existed to solve this task and the common method used was the Ziegler and Nichols. The former method require an accurate mathematical model. This method is beneficial in linear systems, however, if the system becomes more complex or non-linear the method cannot produce accurate values to the parameters of the system. A solution proposed for this problem recently is the application of optimization techniques. There are various optimization techniques can be used to solve various optimization problems. In this paper, several optimization methods are applied to compute the optimal parameter of PID controllers. These methods are flower pollination algorithm (FPA), grey wolf optimization (GWO), sin cosine algorithm (SCA), slime mould algorithm (SMA), and sparrow search algorithm (SSA). The fitness function applied in the former optimization techniques is the integral square Time multiplied square Error (ISTES) as the performance index measure. The fitness function provides minimal rise time, minimal settling time, fast response, and no overshoot, Steady state error equal to zero, a very low transient response and a non-oscillating steady state response with excellent stabilization. The effectiveness of the proposed SSA-based controller was verified by comparisons made with FPA, GWO, SCA, SMA controllers in terms of time and frequency response. Each control technique will be applied to the identified model (simulation results) using MATLAB Simulink and the laboratory setup (experimental results) using LABVIEW software. Finally, the SSA showed the highest performance in time and frequency responses.

Real-Time Implementation for Tuning PID Controller Based on Advanced Optimization Techniques for Micro-Robotics System

2021 ◽  
Vol 10 (6) ◽  
pp. 161-173
Author(s):  
Ehab S. Ghith ◽  
◽  
Mohamed Sallam ◽  
Islam S. M. Khalil ◽  
Mohamed Serry ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Pid Controller ◽  
Model Simulation ◽  
Search Algorithm ◽  
Optimization Techniques ◽  
Control Technique ◽  
Flower Pollination Algorithm ◽  
Labview Software ◽  
Laboratory Setup ◽  
Sine Cosine Algorithm

The process of tuning the PID controller’s parameters is considered to be a difficult task. Several approaches were developed in the past known as conventional methods. One of these methods is the Ziegler and Nichols that relies on accurate mathematical model of the linear system, but if the system is complex the former method fails to compute the parameters of PID controller. To overcome this problem, recently there exist several techniques based on artificial intelligence such as optimization techniques. The optimization techniques does not require any mathematical model and they are considered to be easy to implement on any system even if it complex, can reach optimal solutions on the parameters. In this study, a new approach to control the position of the micro-robotics system proportional - integral - derivative (PID) controller is designed and a recently developed algorithm based on optimization is known as the sparrow search algorithm (SSA). By using the sparrow search algorithm (SSA), the optimal PID controller parameters were obtained by minimizing a new objective function, which consists of the integral square Time multiplied square Error (ISTES) performance index. The effectiveness of the proposed SSA-based controller was verified by comparisons made with the Sine Cosine algorithm (SCA), and Flower pollination algorithm (FPA) controllers in terms of time and frequency response. Each control technique will be applied to the identified model (simulation results) using MATLAB Simulink and the laboratory setup (experimental results) using LABVIEW software. Finally, the SSA showed the highest performance in time and frequency responses.

A Comparative Study of Improved Teaching Learning Based Optimization Technique on Economic Load Dispatch Problem with Generator Constraints

2016 ◽  
Vol 5 (4) ◽  
pp. 1-25 ◽  
Author(s):  
Sumit Banerjee ◽  
Chandan Chanda ◽  
Deblina Maity
Keyword(s):  
Optimization Technique ◽  
Inequality Constraints ◽  
Test System ◽  
Economic Load Dispatch ◽  
Thermal Plant ◽  
Equality And Inequality Constraints ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning ◽  
Operational Constraints ◽  
Rate Limit

This article presents a novel improved teaching learning based optimization (I-TLBO) technique to solve economic load dispatch (ELD) problem of the thermal plant without considering transmission losses. The proposed methodology can take care of ELD problems considering practical nonlinearities such as ramp rate limit, prohibited operating zone and valve point loading. The objective of economic load dispatch is to determine the optimal power generation of the units to meet the load demand, such that the overall cost of generation is minimized, while satisfying different operational constraints. I-TLBO is a recently developed evolutionary algorithm based on two basic concepts of education namely teaching phase and learning phase. The effectiveness of the proposed algorithm has been verified on test system with equality and inequality constraints. Compared with the other existing techniques demonstrates the superiority of the proposed algorithm.

A Weighted Flexible Tolerance Algorithm for Constrained Minimization

1975 ◽  
Vol 97 (4) ◽  
pp. 1291-1294 ◽  
Author(s):  
M. A. Townsend ◽  
F. Y. Lam
Keyword(s):  
Objective Function ◽  
Search Algorithm ◽  
Inequality Constraints ◽  
Constrained Minimization ◽  
Rapid Convergence ◽  
Flexible Polyhedron ◽  
Equality And Inequality Constraints ◽  
Direct Search Algorithm ◽  
Tolerance Method ◽  
Nonlinear Equality

A direct search algorithm based upon the flexible tolerance method developed by Paviani and Himmelblau [1] for minimization of a functional subject to nonlinear equality and inequality constraints is proposed and evaluated. The modification incorporates a weighting on the direction of search in which the flexible polyhedron formed orients itself toward the gradient of the objective function (and clings to all active constraints). This is accomplished by weighting the centroid, in the sense of minimization, of the polyhedron with respect to the objective function. A number of problems have been solved satisfactorily by this algorithm, generally with more rapid convergence.

scholarly journals Linear programming with inequality constraints via entropic perturbation

1996 ◽  
Vol 19 (1) ◽  
pp. 177-184 ◽  
Author(s):  
H.-S. Jacob Tsao ◽  
Shu-Cherng Fang
Keyword(s):  
Linear Inequality ◽  
Optimal Solution ◽  
Path Following ◽  
Inequality Constraints ◽  
Computational Effort ◽  
Optimization Techniques ◽  
Linear Program ◽  
Programming Approach ◽  
Linear Programs ◽  
Dual Program

A dual convex programming approach to solving linear programs with inequality constraints through entropic perturbation is derived. The amount of perturbation required depends on the desired accuracy of the optimum. The dual program contains only non-positivity constraints. Anϵ-optimal solution to the linear program can be obtained effortlessly from the optimal solution of the dual program. Since cross-entropy minimization subject to linear inequality constraints is a special case of the perturbed linear program, the duality result becomes readily applicable. Many standard constrained optimization techniques can be specialized to solve the dual program. Such specializations, made possible by the simplicity of the constraints, significantly reduce the computational effort usually incurred by these methods. Immediate applications of the theory developed include an entropic path-following approach to solving linear semi-infinite programs with an infinite number of inequality constraints and the widely used entropy optimization models with linear inequality and/or equality constraints.

An optimal force distribution scheme for cooperating multiple robot manipulators

Robotica ◽  
1993 ◽  
Vol 11 (1) ◽  
pp. 49-59 ◽  
Author(s):  
Yong Dal Shin ◽  
Myung Jin Chung
Keyword(s):  
Efficient Method ◽  
Optimal Solution ◽  
Inequality Constraints ◽  
Force Distribution ◽  
Weak Point ◽  
Contact Points ◽  
Optimal Force ◽  
Distribution Scheme ◽  
Equality And Inequality Constraints ◽  
Optimal Force Distribution

SUMMARYIn this paper, we suggest an optimal force distribution scheme by weak point force minimization and we also present an efficient method to solve the problem. The concept of a weak point is a generalized one which is applicable to any points of interest, as well as joints or contact points between end-effectors and an object. The problem is formulated by a quadratic objective function of the forces exerted at weak points subject to the linear equality and inequality constraints, and its optimal solution is obtained by an efficient method. As regards the solution of the problem, the original problem is reformulated to a reduced order dual problem after the equality constraints are eliminated by force decomposition.

Sign in / Sign up

Export Citation Format

Share Document