Power Research

M. Anuradha ¹, B. K. Keshavan ², T. S. Ramu ³, V. Sankar ⁴

Affiliations
1 Professor, PES Institute of Technology, 100ft. Road, BSK III Stage, Bangalore - 560 085, IN
2 Professor and Dean(Academics), PES Institute of Technology, 100ft. Road, BSK III Stage, Bangalore - 560 085, IN
3 Professor,Indian Institute of Science, C V Raman Avenue, Bangalore - 560 012, IN
4 Professor and Director (Foreign affairs and Alumni Matters), Jawaharlal Nehru Technological University Anantapur, Saradha Nagar, Ananthapuramu - 515002, IN

Abstract

Modeling of generation of wind power systems is useful for an effective management and balancing of a power grid, supporting real-time operations. Forecasting the expected wind power production could help to deal with uncertainties. In comparison with the mathematical approach, the data driven approach is useful where both detailed information about the system and real time measurements are unavailable. Winds being a natural phenomenon, statistical methods are more suitable for wind power plants than that of conventional power plants. In this paper, the data on the wind speed and power generated from a location in the state of Karnataka, India, has been analyzed and shown that the probability distribution of wind speed follows Rayleigh or Gaussian/Normal distribution. Short-term wind power forecasting is carried out using Autoregressive models.

Keywords

Wind power forecasting,rayleigh distribution, gaussian distribution, auto - regression.

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D. Ravi Kumar ¹, V. Sankar ²

Affiliations
1 VNR Vignana Jyothi Institute of Engineering & Technology, Hyderabad-500090, IN
2 JNTU Anantapur, College of Engineering, Anantapur-515 002, IN

Abstract

Network reconfigurationis an operation strategy, which alters the topological structure of the distribution feeders by rearranging the status of switches in order to obtain an optimal configuration, minimise system losses and to improve reliability. In this paper, an approach using Distribution Load Flow(DLF) solution and a reconfiguration algorithm that enhances voltage profile, reliability and voltage stability index besides minimising losses is developed. The proposed algorithm has been implemented on33 bus Radial Distribution System (RDS) in the MATLAB^TM environment.

Keywords

Radial distribution system, distribution load flow, Voltage Stability Index(vsi ), network reconfiguration (NR), performance indices.

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Nagarajupalle Naveen ¹, V. Sankar ²

Affiliations
1 P. G. Student, Reliability Engineering, JNTUA, Anantapuramu - 515002, IN
2 Prof. in EEE, JNTUA, Anantapuramu - 515002, IN

Abstract

In power system studies, the reliability of protection systems has a considerable effect on the reliability of supply, and hence appropriate reliability models must be incorporated. A majority of studies conducted assuming perfectly reliable protection systems, and hence do not take into account the effects of failure scenarios in their operation.Modelling of the failure modes in protection systems associated with their dependability and security features is essential for comprehensive evaluation of power system reliability. There are relatively fewer works in the literature on power system reliability accounting for the impact of protection system. In this paper, common mode failure operations such as dependability failures of protection of neighbouring lines in a Power System network is considered. In an existing method, only first order and second order failures of transmission lines are considered, whereas, failure modes using higher order Cutsets are not considered. Expressions for reliability analysis are developed and software has been developed using MATLAB. The results for sample systems are obtained and analysed. From the results, it can be concluded that although probability of failure indices are increased as compared to an existing method, the proposed method is more general, realistic and approximate analysis can be carried out for any system having higher order dependable failures.

Keywords

Reliability, dependent failure, neighbouring line, probability logic diagram

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P. Chandhra Shekar ¹, R. A. Deshpande ¹, V. Sankar ²

Affiliations
1 Distribution Systems Division (DSD), Central Power Research Institute, Bangalore-560080, IN
2 Jawaharlal Nehru Technological University, Anantapur, A.P. - 515 002, IN

Abstract

Reliability assessment of distribution network is an important subject due to increasing demand for more reliable service with less interruption frequency and duration. An effective way to solving this issue is by the use of quantitative assessment of reliability, measure the reliability indices to find out the probability of availability and unavailability of supply. This paper describes the energy not supplied to the customers in terms of customer kWh loss and revenue loss to the customers and the revenue loss to the utility in profit making areas is presented for two practical networks by calculating the reliability indices. The software module CYMDIST Reliability Assessment Module (RAM) is used for the simulation and analysis.

Keywords

Distribution system, customer cost of interruption, reliability indices, CYMDIST-RAM.

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P. Chandhra Shekar ¹, R. A. Deshpande ¹, V. Sankar ², P. Manohar ²

Affiliations
1 Distribution Systems Division (DSD), Central Power Research Institute, Bangalore-560 080, IN
2 Jawaharlal Nehru Technological University, Anantapur, A. P. - 515 002, IN

Abstract

Reliability assessment is of primary importance in designing and planning distribution systems that operate in an economical manner with minimal interruption of customer loads. Distributed Generation (DG) is expected to play an increasing role in emerging power systems because they use different type of resources and technologies to serve energy to power systems. DG is expected to improve the system reliability as its backup generation. Since DG units are subject to failures like all other generation units, the random behavior of these units must be taken into account in the analysis. Existence of DG units in a distribution system will effect on restoration time of load points. The algorithm for restoration time assessment of load point is developed when DG unit is installed. In this paper, the reliability performance of distribution system is analyzed in terms of SAIFI, SAIDI, CAIDI, ASAI, ASUI, ENS and AENS. The algorithm to calculate the reliability indices for simple 9-bus radial distribution feeder with and without DG is developed. The improvement in the reliability of the feeder is studied for different locations of DG with respect to fault point. All the above analysis is carried out by developing MATLAB software.

Keywords

SAIFI, SAIDI, CAIDI, ASAI, ASUI, ENS and AEN.

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K. Amaresh ¹, V. Sankar ²

Affiliations
1 Associate Professor, Department of EEE, KSRM College of Engineering, Kadapa, AP - 516 002, IN
2 Professor in Electrical Engineering, Director of Academic Planning, JNTUA, Anantapur. Cell No.9000551418. AP - 515 002, IN

Abstract

Integration of renewable energy based distributed generation units provide potential benefits to conventional distribution systems. The power injections from renewable DG units located close to the load centers provide an opportunity for system voltage support, reduction in energy losses and reliability improvement. Therefore, the allocation of DG units should be carefully determined with the consideration of different planning incentives. In this paper, a simple method for real power loss reduction, voltage profile improvement which is based on voltage sensitivity index analysis is considered. Power flow analysis is done using the forward-backward sweep method, the placement and sizing of DG in distribution system are determined using optimization.The objective is to improve the reliability indices. The placement and size of DGs are optimized using a Genetic Algorithm. To evaluate the proposed algorithm, the 10 bus distribution feeder is used. The results illustrate the efficiency of the proposed method.

Keywords

Distribution Generation, Distribution System, Backward-Forward Sweep,Optimization, Reliability, Genetic Algorithm, Voltage sensitivity index

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