An efficient multi-objective based squirrel search optimization for optimal placement of FACTS devices

2021 ◽  
pp. 1-19
Author(s):  
G. Adline Priya ◽  
C. Sundar ◽  
S. Pavalarajan
Keyword(s):  
Control System ◽  
Optimal Placement ◽  
Objective Functions ◽  
Power Networks ◽  
Multi Objective ◽  
Facts Devices ◽  
Search Optimization ◽  
Intellectual Control ◽  
Flexible Alternating Current Transmission ◽  
Transmission Capability

The adoption of a new transmission line is extremely complex because of its socio-economic problems such as environmental clearances. Thus, there is a prominence of better utility over available transmission infrastructure. The Flexible Alternating Current Transmission System (FACTS) devices can offer transmission capability enhancement, power compensation, and stability as well as voltage improvement. However, the FACTS devices have a higher penetration impact of wind generation for the dynamic stability of power networks. In this work, an efficient Intellectual Control system has been proposed to stabilize the FACTS devices placement. The Squirrel Search Optimization is adapted with an intellectual control system to enhance the steady-state voltage stability of FACTS devices. The proposed system has been evaluated with the assist of IEEE 14 and 26 standard bus systems to handle the multi-objective functions like cost, reduction in power loss, reducing risks, and maximizing user’s benefit. These multi-objective functions facilitate to attain the optimal placement and load flows at various sites. The simulation can be carried out with MATLAB/SIMULINK environment and the results manifest that the proposed system outperforms well when compared with existing approaches.

Multi-objective FACTS placement using improved harmony search optimization

2020 ◽  
Vol 39 (3) ◽  
pp. 3839-3851
Author(s):  
Arun Nambi Pandian ◽  
Aravindhababu Palanivelu
Keyword(s):  
Power Systems ◽  
Harmony Search ◽  
Optimal Number ◽  
Optimal Placement ◽  
Voltage Profile ◽  
Placement Problem ◽  
Facts Devices ◽  
Search Optimization ◽  
Solution Methods ◽  
Improved Harmony Search

Optimal placement of FACTS devices attempts to improve power transfer, minimize active power loss, enhance voltage profile and improve voltage stability, thereby making the operation of power systems more flexible and secured. The classical methods experience difficulties in solving the FACTS placement problem (FPP) with discontinuous functions and may diverge or result oscillatory convergence. Besides the number of FACTS devices for placement should be given as an input while solving the problem. The solution methods then attempts to forcefully place all the specified number of devices in the power system, but in reality, the system may require an optimal number of FACTS for placement. The application of swarm-intelligence based optimization algorithms strives to overcome the drawbacks of classical methods. This paper presents a new solution method for FACTS placement problem using improved harmony search optimization (IHSO) with a newly suggested dissonance mechanism that avoids badly composed music, with a view of avoiding the sub-optimal solutions. Besides, the method requires to specify only the maximum number of FACTS devices for placement and places only the optimal number of devices within the specified maximum number of devices. The paper also includes simulation results of three IEEE test systems for exhibiting the superiority of the proposed method.

Metaheuristic optimization based placement of SVCs with multiple objectives

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Arun Nambi Pandian ◽  
Aravindhababu Palanivelu
Keyword(s):  
Harmony Search ◽  
Optimal Placement ◽  
Voltage Profile ◽  
Mathematical Methods ◽  
Content Type ◽  
Multi Objective ◽  
Search Optimization ◽  
Improved Harmony Search ◽  
The Given ◽  
Self Adaptive

Purpose Optimal placement of static VAR compensator (SVC) devices not only improves the voltage profile (VP) but also reduces the active power loss (APL) and enhances the voltage stability (VS) through injecting appropriate VARs at optimal buses. The traditional mathematical methods may not provide global best solution and pose difficulties in handling multi-objective SVC placement (SVCP) problem with complex constraints and forcefully place all the given number of SVCs in the system without assessing their real requirements in enhancing the chosen performances. The purpose of this paper is to formulate the SVCP as a multi-objective optimization problem and solve it using a metaheuristic algorithm for global best solution. Design/methodology/approach The proposed SVCP method uses improved harmony search optimization (IHSO) with dissonance-avoiding mechanism for obtaining the global best solution through driving away the solution from the sub-optimal traps. In addition, the method uses a self-adaptive technique for optimally tuning the IHSO parameters and places only the required number of SVCs from the given number of SVCs. Findings This paper presents the results of the proposed method for 14, 30 and 57 bus systems and exhibits that the proposed method outperforms the existing SVCP methods in achieving the desired performances. Originality/value This paper proposes a new self-adaptive IHSO based SVCP method for optimally placing only the required number of SVCs with a goal of attaining the global best performances.

Fuzzy multi-objective decision making approach for nuclear power plant installation

2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan
Keyword(s):  
Linear Programming ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Energy Supply ◽  
Energy Demand ◽  
Nuclear Power ◽  
Power Plants ◽  
Total Duration ◽  
Objective Functions ◽  
Multi Objective

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.

Intellectual control system for spacecraft rendezvous and docking based on active optical markers and its laboratory prototyping

2015 ◽  
Vol 21 (2(93)) ◽  
pp. 53-55
Author(s):  
V.B. Taranenko ◽  
◽  
R.A. Lymarenko ◽  
V.A. Topolnikov ◽  
V.A. Yatsenko ◽  
...  
Keyword(s):  
Control System ◽  
Intellectual Control ◽  
Optical Markers ◽  
Rendezvous And Docking

Multi-Objective Design Problem of Tire Wear and Visualization of Its Pareto Solutions2

2006 ◽  
Vol 34 (3) ◽  
pp. 170-194 ◽  
Author(s):  
M. Koishi ◽  
Z. Shida
Keyword(s):  
Inverse Problems ◽  
Conceptual Design ◽  
Dimensional Space ◽  
Design Stage ◽  
Objective Functions ◽  
Pareto Solutions ◽  
Design Problems ◽  
Multi Objective ◽  
Design Engineers ◽  
Design Variables

Abstract Since tires carry out many functions and many of them have tradeoffs, it is important to find the combination of design variables that satisfy well-balanced performance in conceptual design stage. To find a good design of tires is to solve the multi-objective design problems, i.e., inverse problems. However, due to the lack of suitable solution techniques, such problems are converted into a single-objective optimization problem before being solved. Therefore, it is difficult to find the Pareto solutions of multi-objective design problems of tires. Recently, multi-objective evolutionary algorithms have become popular in many fields to find the Pareto solutions. In this paper, we propose a design procedure to solve multi-objective design problems as the comprehensive solver of inverse problems. At first, a multi-objective genetic algorithm (MOGA) is employed to find the Pareto solutions of tire performance, which are in multi-dimensional space of objective functions. Response surface method is also used to evaluate objective functions in the optimization process and can reduce CPU time dramatically. In addition, a self-organizing map (SOM) proposed by Kohonen is used to map Pareto solutions from high-dimensional objective space onto two-dimensional space. Using SOM, design engineers see easily the Pareto solutions of tire performance and can find suitable design plans. The SOM can be considered as an inverse function that defines the relation between Pareto solutions and design variables. To demonstrate the procedure, tire tread design is conducted. The objective of design is to improve uneven wear and wear life for both the front tire and the rear tire of a passenger car. Wear performance is evaluated by finite element analysis (FEA). Response surface is obtained by the design of experiments and FEA. Using both MOGA and SOM, we obtain a map of Pareto solutions. We can find suitable design plans that satisfy well-balanced performance on the map called “multi-performance map.” It helps tire design engineers to make their decision in conceptual design stage.

Voltage Stability Enhancement with Optimal Placement of IPFC

2019 ◽  
Vol 8 (4) ◽  
pp. 9465-9471
Keyword(s):  
Transmission Line ◽  
Objective Function ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Test System ◽  
Optimal Location ◽  
Optimal Placement ◽  
Utilization Factor ◽  
Location Selection ◽  
Multi Objective

This paper presents a novel technique based on Cuckoo Search Algorithm (CSA) for enhancing the performance of multiline transmission network to reduce congestion in transmission line to huge level. Optimal location selection of IPFC is done using subtracting line utilization factor (SLUF) and CSA-based optimal tuning. The multi objective function consists of real power loss, security margin, bus voltage limit violation and capacity of installed IPFC. The multi objective function is tuned by CSA and the optimal location for minimizing transmission line congestion is obtained. The simulation is performed using MATLAB for IEEE 30-bus test system. The performance of CSA has been considered for various loading conditions. Results shows that the proposed CSA technique performs better by optimal location of IPFC while maintaining power system performance

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