This paper proposes an improved social spider optimization (ISSO) for achieving different objectives of optimal reactive power dispatch (ORPD). The proposed ISSO method is developed by applying two modifications on new solution generation process. The proposed method uses only one modified equation for producing the first new solution generation and the second new solution generation while the standard SSO uses two equations for each process. The improvement in the proposed method is confirmed by solving benchmark optimization functions, IEEE 30-bus system and IEEE 118-bus system. Obtained results from ISSO are compared to those from other existing methods available in other studies together with other popular and state-of-the-art methods, which are implemented in the work. As compared to standard SSO for application to ORPD problem, ISSO can reduce the number of computation steps and one control parameter, and shorten simulation time. About the result comparisons with SSO and other remaining methods, ISSO can find more favorable solutions with higher quality and ISSO can stabilize solution search function with approximately all trial runs finding lower value of fitness. Furthermore, the strong search ability of ISSO is also indicated because it uses less value for control parameters. As a result, the proposed ISSO method can be a very effective optimization tool for dealing with the ORPD problem.

Improved social spider optimization algorithm for optimal reactive power dispatch problem with different objectives

The Industrial Control System Cyber Defence Triage Process

Optimal allocation of distributed generations (DGs) is vital to the proper operation of the distribution systems, which leads to power loss minimization and acceptable voltage regulation. In this paper, an Enhanced Artificial Ecosystem-based Optimization (EAEO) algorithm is proposed and used to solve the optimization problem of DG allocations to minimize the power loss in distribution systems. In the suggested algorithm, the search space is reduced using operator G and sine-cosine function. The G-operator affects the balance between explorative and exploitative phases. At the same time, it gradually decreases during the iterative process in order to converge to the optimal global solutions. On the other hand, the sine-cosine function creates different and random solutions. The EAEO algorithm is applied for solving the standard 33-bus 69-bus, and 119-bus distribution systems with the aim of minimizing the total power losses. Multiple DG units operating at various power factors, including unity-, fixed-, and optimal-power factors, are considered. Both single and multiple objectives are considered to minimize the total voltage deviation (TVD), maximize the system stability, and reduce the total power losses. The obtained results are compared with those obtained by the AEO and other algorithms. The results demonstrate a significant reduction of total power losses and improvement of the voltage profile of the network, especially for the DGs operating at their optimal power factors. Comparisons show the dominance of the proposed EAEO algorithm against other analytical, metaheuristic, or hybrid algorithms. Moreover, the EAEO outperforms the original AEO algorithm with a faster convergence speed and better system performance.

/pdf/an-enhanced-artificial-ecosystem-based-optimization-for-2dcgz2szny.pdf

An Enhanced Artificial Ecosystem-Based Optimization for Optimal Allocation of Multiple Distributed Generations

海外諸国向け火力発電所の設計(英国)("IEEE Transactions on Power Apparatus and Systems"1968年5月号)

This paper presents an innovative design of a prototype TudungSaji that involves both hardware and software development. This project is designed an effective TudungSaji is able to maintain the food warm and to protect food from pests like flies and rats. Smart TudungSaji uses an Arduino microcontroller to produce an automated function. The main parts of this project consist of chassis, 2 sensors which are temperature sensor LM35 and limit switch sensor as an inputs, the ATmega328p microcontroller and 2 bulbs as an outputs. This is to ensure the warming process operates more efficiently and effectively. The algorithm is developed and implemented with Arduino Uno. It is really practical for human, especially working woman to make their life simpler. This project helps people to keep their food warm and it is portable to bring anywhere. The performance of this project was validated with the simulation circuit using Proteus 6 Lite, and the results and findings from conducting experiments on the prototype. The bulbs are activated by the LM35 sensor detected temperature below 60oC.Then, the bulbs will automatically off when temperature reaches upper 60oC.This project uses 240V 100W bulb as a heating element. It can be improvised by replacing bulbs with thermistor coil. The thermistor coil can produce more heat energy because of the material of the coil, for example in the oven.

Design an automatic temperature control system for smart TudungSaji using arduino microcontroller

Background/Objectives: The main objectives are to define the concept and application of PID control in parallel structure of PID controller and to describe implementation of the continuous PID controller in SIMATIC STEP 7. Methods/Statistical Analysis: Various designs of PID controllers in SIMATIC STEP 7 are available for different kinds of feedback control systems. Parallel structure is used in the algorithm of PID controllers in Siemens PLCs. In this study PID controller with the continuous control function block FB41 (CONT_C) is analyzed. Programming with PID controller in Siemens PLCs with continuous Manipulated Variable output and the option of influencing the Manipulated Value manually is thoroughly discussed. Findings: PID controller is the most common form of feedback control and it can be found in all the areas where control loops exist. The simplicity of understanding of the PID algorithm is one of its advantages but due to a wide range of systems and different manufacturers of control systems with various design and tuning methods of PID controllers in their products, the implementation process gets complicated. This difficulty is reduced by using several kinds of PID controllers for different types of systems in Siemens control systems. FB41 is a function block of continuous PID controller which was designed for Siemens PLCs to provide control performance with analog signals; it can function both in a manual and automatic mode.The most important part of FB41 functioning is addressing of the analog Input and Output in this function block. The results of P, I, D, PI, PD and PID controller implementation in FB41 have been compared. Applications/Improvements: This continuous control function block can be used in different kinds of control loop systems where analog input is sensed and analog output is required.

Concept and Application of PID Control and Implementation of Continuous PID Controller in Siemens PLCs

This Paper presents an approach to solve the single objective optimal power flow problem considering the critical objective function of minimization of sum of squares of voltage deviations from desired voltages at all load buses while satisfying a set of constraints associated with the control variables such as generator excitations, tap positions of on-load tap changing transformers and switched var compensators and also dependent variable reactive power generation of all generators. This problem has been solved by using the Particle Swarm Optimization (PSO) method and the results obtained from this proposed method have been compared with the results obtained by the conventional Non-Linear Programming interior point method(NLP). To test the effectiveness of the proposed method, the results are obtained for a practical 24 bus EHV southern region equivalent Indian power system network. Analysis of results including effect on power loss, voltage stability indices as well as sum squared voltage deviations are done and superiority of the proposed method in comparison to NLP method is demonstrated.

PSO based optimal reactive power dispatch for voltage profile improvement

This paper presents a hybrid evolutionary computation algorithm termed as hybrid bacterial foraging-particle swarm optimization (HBFPSO) algorithm, to optimal reactive power dispatch (ORPD) problem. HBFPSO algorithm merges velocity and position updating strategy of particle swarm optimization (PSO) algorithm and reproduction and elimination dispersal of bacterial foraging algorithm (BFA). The ORPD is solved for minimization of two objective functions; system real power loss and voltage stability L-index. The objective is minimized by optimally choosing the control variables; generator excitations, tap positions of on-load tap changing transformers and switched var compensators while satisfying their constraints and also the constraints of dependent variabl es; voltages of all load buses and reactive power generation of all generators. The proposed approach has been evaluated on a standard IEEE 30 bus test system and 24 bus EHV southern region equivalent Indian power system. The results offered by the proposed algorithm are compared with those offered by other evolutionary computation algorithms reported in the recent state of the art literature and the superiority of the proposed algorithm is demonstrated.

https://ijape.iaescore.com/index.php/IJAPE/article/download/20252/12893

A hybrid bacterial foraging-particle swarm optimization technique for solving optimal reactive power dispatch problem

This paper presents a simplified Fuzzy Logic technique for enhancement of security of power system considering economics of generators. Alleviation of transmission line overload is a critical problem in the present day power system operation; hence a control strategy is necessary to effectively reduce the line overloads to the security limits in shortest time, by considering the economy involved in rescheduling of generators. A technique has been formulated using fuzzy logic for curtailing the number of generators to be rescheduled based on Relative Electrical Distance (RED) concept and the incremental fuel cost of generators. A fuzzy rule based system is developed to select the generators to be rescheduled on a priority based order. The proposed approach not only helps for improvement of voltage stability but also reduces the cost involved in generation rescheduling process. Under emergency operating conditions the proposed approach helps the operator in the load dispatch centre for improving the system security with the rescheduling of few number of generators for overload relieving. Numerical results for the IEEE 39-bus New England system having ten generators have been presented to demonstrate the performance of the proposed fuzzy system.

http://www.wseas.us/e-library/conferences/2012/CambridgeUK/AIKED/AIKED-24.pdf

Congestion management technique using fuzzy logic based on security and economy criteria

Optimal Power Flow (OPF) problem in electrical power system is considered as a constrained non- linear, single objective or multi- objective optimization problem with multiple variables and multiple constraints. As the Power Transmission companies have been moving into much more competitive markets , this necessitates the implementation of Optimal Power Flow Programs for both, the planning and operation of a power system. This paper presents an approach to solve the single objective OPF problem considering the reactive power loss minimization as the objective function, while satisfying a set of constraints (which may be continuous , discrete or Binary ) associated with control variables such as automatic voltage regulator (AVR) operating values of generators, tap positions of on-load tap changer (OLTC) of transformers, and the switched reactive power compensation equipment (Shunt Capacitors). Constrained Non-Linear Programming-Interior Point (IP) Method and Particle Swarm Optimization (PSO) have been used for this purpose. The proposed algorithm's have been applied to IEEE 14 bus, IEEE 30 Bus and 24 bus systems. Results obtained with both the Optimization algorithms are compared. I. INTRODUCTION The requirement of Electrical Power in the world has grown tremendously due to the Industrialization, Urbanization and Improvement in the standard of living of people. The demand has been running ahead of supply. Construction of new Infrastructure for Generation, Transmission and Distribution of Power is imminent to meet this situation. It is also very important to reduce the Technical Losses in Transmission, Distribution System and also the Non-Technical losses caused by energy thefts and in-efficient metering so as to reduce the disparities in demand and supply of Power and avoid power cuts. By reducing the Technical & Non-Technical Losses, there can be potential savings in terms of utilization of existing Infrastructure and energy resources to meet the demand at an optimal generation and transmission costs. This necessitates the implementation of Optimal Power Flow (OPF) Program for both, the operation and planning of a power system. The desired solution/objective of an Optimal Power Flow problem is to identify the appropriate control variables and allocate the corresponding operating values with a specific objective of minimizing the losses in the network with respect to the Equality constraints (derived from power balance equation) and Inequality constraints (derived from the limits on control variables) which may be continuous, discrete or binary..

P. Lokender Reddy

Papers

Concept and Application of PID Control and Implementation of Continuous PID Controller in Siemens PLCs

PSO based optimal reactive power dispatch for voltage profile improvement

A hybrid bacterial foraging-particle swarm optimization technique for solving optimal reactive power dispatch problem

Congestion management technique using fuzzy logic based on security and economy criteria

Reactive Power Optimization of Power System based on Particle Swarm Optimization and Non Linear Programming