A Modern Approach to Solve of Economic Load Dispatch using Group Leader Optimization Technique

2017 ◽  
Vol 6 (1) ◽  
pp. 66-85 ◽  
Author(s):  
Subhajit Roy ◽  
Kuntal Bhattacharjee ◽  
Aniruddha Bhattacharya
Keyword(s):  
Optimization Algorithm ◽  
Large Scale ◽  
Power Transmission ◽  
Transmission Loss ◽  
Optimization Technique ◽  
Group Leader ◽  
Optimization Techniques ◽  
Economic Load Dispatch ◽  
Modern Approach

Economic load dispatch plays an important role of power system operation & control by using different soft techniques that have been used to solve convex and non-convex economic load dispatch (ELD) problems. This paper presents a new global optimization algorithm to the economic load dispatch problems for minimization of fuel cost of generations with different constraints such as ramp rate limits, valve-point loading and prohibited operating zones of large-scale thermal plants. Power transmission loss has also been considered in few cases. Group leader optimization algorithm (GLOA) is a relatively new optimization technique. Mathematical models of this algorithm demonstrate the efficiency, quality of solution and convergence speed of the method and successful application of the algorithm on ELD problems. Simulation results found that the proposed approach outperforms several other existing optimization techniques in terms quality of solution obtained and computational efficiency. Results also be confirmed the robustness of the proposed methodology.

Economic Dispatch Problems Using Backtracking Search Optimization

2018 ◽  
Vol 7 (2) ◽  
pp. 39-60
Author(s):  
Kuntal Bhattacharjee
Keyword(s):  
Large Scale ◽  
Transmission Loss ◽  
Optimization Problems ◽  
Optimization Technique ◽  
Inequality Constraints ◽  
Optimization Techniques ◽  
Backtracking Search ◽  
Search Optimization ◽  
Set Up ◽  
Optimum Solution

The purpose of this article is to present a backtracking search optimization technique (BSA) to determine the feasible optimum solution of the economic load dispatch (ELD) problems involving different realistic equality and inequality constraints, such as power balance, ramp rate limits, and prohibited operating zone constraints. Effects of valve-point loading, multi-fuel option of large-scale thermal plants, system transmission loss are also taken into consideration for more realistic application. Two effective operations, mutation and crossover, help BSA algorithms to find the global solution for different optimization problems. BSA has the capability to deal with multimodal problems due to its powerful exploration and exploitation capability. BSA is free from sensitive parameter control operations. Simulation results set up the proposed approach in a better stage compared to several other existing optimization techniques in terms quality of solution and computational efficiency. Results also reveal the robustness of the proposed methodology.

scholarly journals Real Power Loss Reduction by Cultivation of Soil Optimization Algorithm

2020 ◽  
Vol 7 (1) ◽  
pp. E1-E5
Author(s):  
K. Lenin
Keyword(s):  
Optimization Algorithm ◽  
Power Loss ◽  
Reactive Power ◽  
Power Transmission ◽  
Transmission Loss ◽  
Real Power ◽  
Nutrient Contents ◽  
The Poor ◽  
Power Loss Reduction

In this paper, the optimal reactive power problem has been solved by the cultivation of soil optimization (CSO) algorithm. The reduction of real power loss is a key objective of this work. The projected CSO algorithm has been modeled based on the quality of soil which has been used in the cultivation of various crops season to season. With respect to the quality of the soil in the cultivation land, there will be a change in the poor-quality soil since there will up the gradation of the poor soil is done through by adding the nutrient contents. Depend upon the needs and about the type of cultivation farmers will improve the quality of the soil by adding valuable and various types of fertilizers (natural and artificial) such that it will enhance the fertile and growth (green) of the crops. Time to time farmers will choose appropriate nutrient contents that will be mixed with the soil in order to enhance the fertility of the soil. In standard IEEE 14, 30, 57 bus test systems Cultivation of Soil Optimization (CSO) algorithm has been tested. The CSO algorithm reduced the real power loss and control variables are within the limits. Keywords: optimal reactive power, transmission loss, cultivation soil optimization algorithm.

scholarly journals Buyer Inspired Meta-Heuristic Optimization Algorithm

2020 ◽  
Vol 10 (1) ◽  
pp. 194-219 ◽  
Author(s):  
Sanjoy Debnath ◽  
Wasim Arif ◽  
Srimanta Baishya
Keyword(s):  
Optimization Algorithm ◽  
Optimization Technique ◽  
Statistical Test ◽  
Heuristic Optimization ◽  
Product Choice ◽  
Exploration And Exploitation ◽  
The Social ◽  
Engineering Problems ◽  
The Mean

AbstractNature inspired swarm based meta-heuristic optimization technique is getting considerable attention and established to be very competitive with evolution based and physical based algorithms. This paper proposes a novel Buyer Inspired Meta-heuristic optimization Algorithm (BIMA) inspired form the social behaviour of human being in searching and bargaining for products. In BIMA, exploration and exploitation are achieved through shop to shop hoping and bargaining for products to be purchased based on cost, quality of the product, choice and distance to the shop. Comprehensive simulations are performed on 23 standard mathematical and CEC2017 benchmark functions and 3 engineering problems. An exhaustive comparative analysis with other algorithms is done by performing 30 independent runs and comparing the mean, standard deviation as well as by performing statistical test. The results showed significant improvement in terms of optimum value, convergence speed, and is also statistically more significant in comparison to most of the reported popular algorithms.

scholarly journals Solving the Real Power Limitations in the Dynamic Economic Dispatch of Large-Scale Thermal Power Units under the Effects of Valve-Point Loading and Ramp-Rate Limitations

2021 ◽  
Vol 13 (3) ◽  
pp. 1274
Author(s):  
Loau Al-Bahrani ◽  
Mehdi Seyedmahmoudian ◽  
Ben Horan ◽  
Alex Stojcevski
Keyword(s):  
Large Scale ◽  
Thermal Power ◽  
Optimization Technique ◽  
Economic Dispatch ◽  
Pso Algorithm ◽  
Search Space ◽  
Economic Benefits ◽  
Optimization Techniques ◽  
Ramp Rate ◽  
Dynamic Economic Dispatch

Few non-traditional optimization techniques are applied to the dynamic economic dispatch (DED) of large-scale thermal power units (TPUs), e.g., 1000 TPUs, that consider the effects of valve-point loading with ramp-rate limitations. This is a complicated multiple mode problem. In this investigation, a novel optimization technique, namely, a multi-gradient particle swarm optimization (MG-PSO) algorithm with two stages for exploring and exploiting the search space area, is employed as an optimization tool. The M particles (explorers) in the first stage are used to explore new neighborhoods, whereas the M particles (exploiters) in the second stage are used to exploit the best neighborhood. The M particles’ negative gradient variation in both stages causes the equilibrium between the global and local search space capabilities. This algorithm’s authentication is demonstrated on five medium-scale to very large-scale power systems. The MG-PSO algorithm effectively reduces the difficulty of handling the large-scale DED problem, and simulation results confirm this algorithm’s suitability for such a complicated multi-objective problem at varying fitness performance measures and consistency. This algorithm is also applied to estimate the required generation in 24 h to meet load demand changes. This investigation provides useful technical references for economic dispatch operators to update their power system programs in order to achieve economic benefits.

Large-scale economic load dispatch using squirrel search algorithm

2020 ◽  
Vol 14 (6) ◽  
pp. 1351-1380
Author(s):  
Sakthivel V.P. ◽  
Suman M. ◽  
Sathya P.D.
Keyword(s):  
Power Plants ◽  
Large Scale ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Optimization Technique ◽  
Research Work ◽  
Superior Performance ◽  
Economic Load Dispatch ◽  
Fuel Cost ◽  
Content Type

Purpose Economic load dispatch (ELD) is one of the crucial optimization problems in power system planning and operation. The ELD problem with valve point loading (VPL) and multi-fuel options (MFO) is defined as a non-smooth and non-convex optimization problem with equality and inequality constraints, which obliges an efficient heuristic strategy to be addressed. The purpose of this study is to present a new and powerful heuristic optimization technique (HOT) named as squirrel search algorithm (SSA) to solve non-convex ELD problems of large-scale power plants. Design/methodology/approach The suggested SSA approach is aimed to minimize the total fuel cost consumption of power plant considering their generation values as decision variables while satisfying the problem constraints. It confers a solution to the ELD issue by anchoring with foraging behavior of squirrels based on the dynamic jumping and gliding strategies. Furthermore, a heuristic approach and selection rules are used in SSA to handle the constraints appropriately. Findings Empirical results authenticate the superior performance of SSA technique by validating on four different large-scale systems. Comparing SSA with other HOTs, numerical results depict its proficiencies with high-qualitative solution and by its excellent computational efficiency to solve the ELD problems with non-smooth fuel cost function addressing the VPL and MFO. Moreover, the non-parametric tests prove the robustness and efficacy of the suggested SSA and demonstrate that it can be used as a competent optimizer for solving the real-world large-scale non-convex ELD problems. Practical implications This study has compared various HOTs to determine optimal generation scheduling for large-scale ELD problems. Consequently, its comparative analysis will be beneficial to power engineers for accurate generation planning. Originality/value To the best of the authors’ knowledge, this manuscript is the first research work of using SSA approach for solving ELD problems. Consequently, the solution to this problem configures the key contribution of this paper.

Linear Programming Approach for Power System State Estimation Using Upper Bound Optimization Techniques

2010 ◽  
Vol 11 (3) ◽  
Author(s):  
Thukaram Dhadbanjan ◽  
Seshadri Sravan Kumar Vanjari
Keyword(s):  
Linear Programming ◽  
State Estimation ◽  
Upper Bound ◽  
Measurement Errors ◽  
Large Scale ◽  
Optimization Technique ◽  
Optimization Techniques ◽  
Programming Approach ◽  
Linear Programming Approach ◽  
Bound Optimization

State estimation plays an important role in real time security monitoring and control of power systems. There are many problems in the implementation of state estimator for large scale networks due to measurement errors, weights given and the numerical ill-conditioning associated with the solution techniques. In this paper a new formulation using linear programming approach is presented. The formulation is devoid of weights and errors associated with the measurements are taken care of in constraints. The non linear problem is linearized at previous operating state and constraints are set up using flow mismatches. The implementation of the formulation exploits sparse features of the network matrices and avoids matrix inversions. Upper bound optimization technique is employed to solve the linear programming problem. Illustration of the proposed approach on sample 3-bus and 6-bus systems and a practical Indian Southern grid 72 bus equivalent system are presented.

scholarly journals Optimal Tuning of SVC-PI Controller using Whale Optimization Algorithm for Angle Stability Improvement

2018 ◽  
Vol 12 (2) ◽  
pp. 620
Author(s):  
N. A. M. Kamari ◽  
I. Musirin ◽  
Z. A. Hamid ◽  
A. A. Ibrahim
Keyword(s):  
Optimization Algorithm ◽  
Damping Ratio ◽  
Optimization Technique ◽  
Computation Time ◽  
Synchronous Generator ◽  
Pi Controller ◽  
Optimization Techniques ◽  
Whale Optimization Algorithm ◽  
Whale Optimization ◽  
Angle Stability

This paper proposed a new swarm-based optimization technique for tuning conventional proportional-integral (PI) controller parameters of a static var compensator (SVC) which controls a synchronous generator in a single machine infinite bus (SMIB) system. As one of the Flexible Alternating Current Transmission Systems (FACTS) devices, SVC is designed and implemented to improve the damping of a synchronous generator. In this study, two parameters of PI controller namely proportional gain, K<sub>P</sub> and integral gain, K<sub>I</sub> are tuned with a new optimization method called Whale Optimization Algorithm (WOA). This technique mimics the social behavior of humpback whales which is characterized by their bubble-net hunting strategy in order to enhance the quality of the solution. Validation with respect to damping ratio and eigenvalues determination confirmed that the proposed technique is more efficient than Evolutionary Programming (EP) and Artificial Immune System (AIS) in improving the angle stability of the system. Comparison between WOA, EP and AIS optimization techniques showed that the proposed computation approach gives better solution and faster computation time.

scholarly journals Real Power Loss Reduction by Rock Dove Optimization and Fuligo Septica Optimization Algorithms

2020 ◽  
Vol 7 (2) ◽  
pp. E1-E6
Author(s):  
L. Kanagasabai
Keyword(s):  
Optimization Algorithm ◽  
Power Loss ◽  
Reactive Power ◽  
Power Transmission ◽  
Transmission Loss ◽  
Loss Reduction ◽  
Exploration And Exploitation ◽  
Real Power ◽  
Fitness Value ◽  
Power Loss Reduction

This paper aims to use the Rock Dove (RD) optimization algorithm and the Fuligo Septica optimization (FSO) algorithm for power loss reduction. Rock Dove towards a particular place is based on the familiar (sight) objects on the traveling directions. In the formulation of the RD algorithm, atlas and range operator, and familiar sight operators have been defined and modeled. Every generation number of Rock Dove is reduced to half in the familiar sight operator and Rock Dove segment, which hold the low fitness value that occupying the lower half of the generation will be discarded. Because it is implicit that the individual’s Rock Dove is unknown with familiar sights and very far from the destination place, a few Rock Doves will be at the center of the iteration. Each Rock Dove can fly towards the final target place. Then in this work, the FSO algorithm is designed for real power loss reduction. The natural vacillation mode of Fuligo Septica has been imitated to develop the algorithm. Fuligo Septica connects the food through swinging action and possesses exploration and exploitation capabilities. Fuligo Septica naturally lives in chilly and moist conditions. Mainly the organic matter in the Fuligo Septica will search for the food and enzymes formed will digest the food. In the movement of Fuligo Septica it will spread like a venous network, and cytoplasm will flow inside the Fuligo Septica in all ends. THE proposed RD optimization algorithm and FSO algorithm have been tested in IEEE 14, 30, 57, 118, and 300 bus test systems and simulation results show the projected RD and FSO algorithm reduced the real power loss. Keywords: optimal reactive power, transmission loss, Rock Dove, Fuligo Septica.

scholarly journals Loss Minimization by Reconfiguration in Radial Distribution Network using Whale Optimization Technique

2020 ◽  
Vol 9 (2) ◽  
pp. 1746-1751
Keyword(s):  
Radial Distribution ◽  
Optimization Algorithm ◽  
Distribution Systems ◽  
Heuristic Algorithms ◽  
Optimization Technique ◽  
Optimization Techniques ◽  
Whale Optimization Algorithm ◽  
Function Evaluation ◽  
Voltage Profile ◽  
Whale Optimization

This paper provides a new approach for solving the problem of network reconfiguration in the presence of Whale Optimization Algorithm (WOA). It is aimed at reducing actual power loss and enlightening the voltage profile in the supply system. The voltage and branch current capacity constraints have been included in the objective function evaluation. The method has been evaluated at three separate heuristic algorithms on 33-bus radial distribution systems to demonstrate the performance and effectiveness of the proposed method. In this paper the comparison of performance of two latest optimization techniques such as Whale Optimization Algorithm (WOA) with classic optimization techniques such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The new optimization technique produces better result compare to other two optimization logarithm..

scholarly journals OPTIMAL POWER FLOW WITH TCSC DEVICE USING CUCKOO OPTIMIZATION ALGORITHM

2018 ◽  
Vol 54 (3A) ◽  
pp. 52
Author(s):  
Duong Thanh Long
Keyword(s):  
Power System ◽  
Optimization Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Power Transmission ◽  
Optimization Techniques ◽  
Operating Conditions ◽  
Cuckoo Optimization Algorithm ◽  
Facts Devices ◽  
Optimal Power

Optimal Power Flow (OPF) problem is an optimization tool through which secure and economic operating conditions of power system is obtained. In recent years, Flexible AC Transmission System (FACTS) devices, have led to the development of controllers that provide controllability and flexibility for power transmission. Series FACTS devices such as Thyristor controlled series compensators (TCSC), with its ability to directly control the power flow can be very effective to power system security. Thus, integration TCSC in the OPF is one of important current problems and is a suitable method for better utilization of the existing system. This paper is applied Cuckoo Optimization Algorithm (COA) for the solution of the OPF problem of power system equipped with TCSC. The proposed approach has been examined and tested on the IEEE 30-bus system. The results presented in this paper demonstrate the potential of COA algorithm and show its effectiveness for solving the OPF problem with TCSC devices over the other evolutionary optimization techniques.

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