Informatics Publishing Limited

G. Sreenivasan ¹, C. H. Saibabu ², S. Sivanagaraju ³

Affiliations
1 Department of Electrical Engineering, Intell Engineering College, Anantapur, AP, IN
2 Department of Electrical Engineering, JNTU Kakinada, Kakinada, AP, IN
3 Department of Electrical Engineering, JNTU Kakinada, Kakinada, AP, IN

Abstract

In this paper, a new method based on “Brent Approach” for the solution of Non linear Economic Dispatch Problem, with transmission losses, having quadratic fuel cost functions is presented. In the present approach the qualitative solution can be achieved with less computational time and it converges within the few iterations. The algorithm involves selection of lambda values then the optimal lambda value is evaluated from the power balance equation by Brent method. The proposed algorithm has be tested on power system having 3, 6 and 15 generating units using MATLAB and Simulation results compared with the Genetic Algorithm approach.

Keywords

Non-Linear ELD Problem, Quadratic Fuel Cost Functions, Transmission Losses, Genetic Algorithm.

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A. Suresh Babu ¹, Ch. Saibabu ², S. Sivanagaraju ²

Affiliations
1 Department of EEE, BITIT, Hindupur, Andhra Pradesh, IN
2 Department of EEE, JNTUK, Kakinada, Andhra Pradesh, IN

Abstract

In classical multi area AGC systems integral (I)- controller or proportional plus integral(PI)-controller is used to mitigate the deviations in frequency and tie line power error caused due to load variations. But due to some disadvantages only with using I-controller or P-controller, the researchers are en route for new findings to get better control. In this paper, application of super magnetic energy storage system (SMES) and Static series synchronous compensator (SSSC) based multi area AGC system under load following in the open market scenario is presented. The I-controller of AGC is tuned by employing PSO (particle swarm optimization) technique. A two area load following based hydrothermal system is considered to exemplify the optimum parameter search. The integral of square of error performance index is considered in the search of optimal Automatic Generation Control (AGC) parameters. The results presented in this paper illustrate the superior working of the proposed technique.

Keywords

Particle Swam Optimization, Load Following, SMES, SSSC, Hydrothermal System.

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M. Venkateswara Rao ¹, Chintalapudi V. Suresh ², S. Sivanagaraju ³

Affiliations
1 Department of EEE, GMRIT, Rajam - 532 127, Andhra Pradesh, IN
2 Department of EEE, VVIT, Guntur - 522509, Andhra Pradesh, IN
3 Department of EEE, JNTUK, Kakinada - 533003, Andhra Pradesh, IN

Abstract

Objectives: One of the drawbacks of the power system network, i.e. Optimum Reactive Power Dispatch (ORPD) is optimized. Due to this, system transmission power losses and bus voltage magnitudes are optimized Methods/Statistical Analysis: A unique optimization rule, Uniformly Distributed Two-stage Particle Swarm Optimization (UDTPSO) are enforced in conjunction with the traditional Particle Swarm Optimization (PSO).The power injection model for the Generalized Unified Power Flow Controller (GUPFC) is used to enhance the power flow in a power system network. Findings: The proposed technique has fast convergence rate in less number of iterations which validates the effectiveness of UDTPSO. The study is tested on a standard IEEE-30 bus system and the results obtained with UDTPSO are valid with the existing PSO. Applications: Effective utilization of a Flexible Alternating Current Transmission system (FACTS) device called Generalized Unified Power Flow Controller (UPFC) for power flow control which will improve existing transmission capability.

Keywords

Generalized Unified Power Flow Controller, Loss Minimization, Optimal Reactive Power Dispatch, Uniformly Distributed Two Stage Particle Swarm Optimization, Voltage Deviation.

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Mahaboob Shareef Syed ¹, S. Sivanagaraju ¹

Affiliations
1 EEE Department, UCEK, JNTUK, Kakinada - 533003, Andhra Pradesh, IN

Abstract

Objectives: To enrich the accuracy of the wind speed forecasting to calculate wind power generation connecting to grid with the help of machine learning algorithms. Methods/Statistical Analysis: A novel hybrid method, Persistence - Extreme Learning Machine (P-ELM) algorithm is proposed. It uses the features of both Persistent and Extreme Learning Machine algorithms. The historical data of meteorological parameters viz. pressure, temperature and past wind speeds are considered as input parameters and wind speed for the next instant as the output, measured at one hour interval for a period of a month are used for the study. Findings: The forecasting is carried out for three areas Guntur, Vijayawada and Ongole of Andhra Pradesh state, India for winter, summer and rainy seasons. The performance of the P-ELM is evaluated in terms of Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). From the results obtained it can be concluded that the P-ELM algorithm leaves behind the fundamental Persistent and Extreme Learning Machine algorithm not only in terms of error metrics but also in simulation time. The entire simulation is carried out with the help of MATLAB 2013a software. Application/Improvements: This technique is very much helpful in real time forecasting of wind speed to avoid the high level of uncertainty involved in wind generation, there by increases the power system security and stability.

Keywords

Extreme Learning Machine (ELM), Forecasting, Machine Learning Algorithms, Persistent Extreme Learning Machine (P-ELM), Wind Speed

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Chintalapudi V. Suresh ¹, M. S. Giridhar ², S. Sivanagaraju ³, U. Ramanaiah ⁴

Affiliations
1 Department of EEE, Vasireddy Venkatadri Institute of Technology, Guntur – 522508, Andhra Pradesh, IN
2 Department of EEE, Lakireddy Bali Reddy college of Engineering, Mylavaram, Vijayawada – 521230, Andhra Pradesh, IN
3 Department of EEE, UCEK, JNTUK, Kakinada – 533003, Andhra Pradesh, IN
4 EEE, Vasireddy Venkatadri Institute of Technology, Guntur – 522508, Andhra Pradesh, IN

Abstract

Objectives: This paper presents a two stage solution strategy to solve multi objective optimization problem in the presence of Distributed Generators (DG) in planning a primary distribution system. Methods/Statistical Analysis: Using this, the economical aspects such as net savings and the technical aspects such as voltage deviation and section current index objectives are optimized while satisfying system equality and in-equality constraints. The optimum number of DGs and its optimal locations are identified in a given system so as to enhance the system security by minimizing the system power losses. The proposed methodology uses fuzzy decision approach to select the best compromised solution from the total generation Pareto solution as per the operators' requirement. Findings: According to the analytical results, the proposed framework in the presence of DGs enhances the system performance more effectively. Application/Improvements: The feasibility and effectiveness of the proposed method are examined on standard 15-node, 33-node and 69-node test systems.

Keywords

Effect of Distributed Generators, NSMCSA, Optimal Placement, Savings, Section Current Index, Voltage Deviation.

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