Informatics Publishing Limited

M. Srinivas ¹, K. S. Swarup ¹

Affiliations
1 Department of Electrical Engineering, Indian Institute of Technology, Madras, Chennai - 600 036, IN

Abstract

This paper describes the implementation of SCADA to the HVAC (Heat Ventilation and Air conditioning) system, which is one among physical systems present in the spent fuel storage facility. The spent fuel storage facility contains the large number of equipment and control devices to maintain the facility critical parameters in the permissible limits. The mathematical model of HVAC system is done to monitor the critical parameters like temperature and humidity with respect to zone conditions. Over time both the radioactivity and the cooling requirements decrease and these parameters are to be monitored and controlled. The work projects deals the implementation of SCADA system to the spent fuel storage facility and monitoring of the critical parameters, the alarms to be generated for the abnormality situation. The scope of the work covers the SCADA design, modelling and monitoring of the critical parameters of the HVAC.

Keywords

SCADA, HVAC, monitoring, spent fuel storage facility, nuclear power plant.

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P. Balakrishna ¹, K. Rajagopal ², K. S. Swarup ¹

Affiliations
1 Department of Electrical Engineering, IIT Madras, Chennai- 600036, T.N., IN
2 GE HTC, Cyber Pearl, Hitech City, Madhapur, Hyderabad - 500081. A.P., IN

Abstract

Power System or Grid is defined as the collection of group of devices, components that make a physical system to generate, transmit and distribute electricity to the end users. Complexity of power system has grown tremendously in the last few decades, facing new challenges during its operation. In order to meet some of these challenges there is a definite need of automation which helps in automatically operating & controlling the power system under various circumstances. The new era of smart grid in the 21st century has made automation really a need to operate grid under the dynamics of rapid load changes, making the system more time sensitive towards faults and failure modes. Automation being one of the critical components in realizing smart grid, this paper tries to present an overview of grid automation technology trend from generation to distribution over the past few years and future opportunities& challenges.

Keywords

Automation, Generation, Transmission, Distribution, Smart grid, Trends, Challenges

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Subhashree Patra ¹, K. S. Swarup ¹

Affiliations
1 Indian Institute of technology, Madras, Chennai, TN -600036, IN

Abstract

The purpose of this study is to develop a familiarity with the central control and management functions, the nerve of any power system. The paper considers a distribution system and emphasizes on distribution management system (DMS). DMS uses state estimation to maintain the healthy working condition of the system. It plays a very important role in the control of the distribution system, as the level of control that possible is restricted owing to the specifi c structure of distribution networks and penetration of real-time monitoring and control facilities. So far, the level of SCADA implementation in distribution networks has controlled around 10% of switching devices and has been limited to circuit breakers at the larger primary substations. The four main functions of the DMS have been discussed focusing mainly on Outage Management.

Keywords

Central control, Distribution system, DMS, Outage management

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Devika Jay ¹, K. S. Swarup ¹

Affiliations
1 Department of Electrical Engineering, Indian Institute of Technology, Madras, Chennai - 600036, IN

Abstract

A literature survey on the main control strategies used for load frequency control in electrical power systems is presented. This includes traditional as well as restructured power systems. As load becomes more and more unpredictable and also as supply becomes distributed, the frequency control strategies for the emerging Smart grid must include demand-side management also. A survey on demand response and active load control is also discussed.

Keywords

Load Frequency Control, PI Controller, Optimal Control, Adaptive Control, Artificial Neural Network, Neurofuzzy Control, Reinforcement Learning, Model Predictive Control, Deregulation, Smart Grid, Demand Response, Active Load Control.

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K. Yashwant ¹, K. S. Swarup ¹

Affiliations
1 Department of Electrical Engineering, Indian Institute of Technology, Madras, Chennai - 600036, IN

Abstract

This article looks at the development of substation automation systems and associated issues and challenges. The new but already quite popular IEC61850-based substations automation systems are discussed. The issue of interoperability which has been remarkably solved by IEC61850 has also been discussed. Additionally, issues and challenges associated with implementing these substation automation systems have been discussed.

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K. Jamuna ¹, K. S. Swarup ¹

Affiliations
1 Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai – 600036, IN

Abstract

This paper investigates the problem of combining both the Supervisory Control And Data Acquisition (SCADA) measurements and phasor measurements for state estimation. The SCADA measurements are slow dynamic in nature than phasor measurements. The latency between those measurements is compensated using Auto Regressive and Neural Networks. Weighted Least Square estimator technique is used for estimating states of the power system. A Traditional State Estimator (TSE) solution is obtained using SCADA measurements which already exist in energy management system. The proposed work is performed on the TSE estimated states for future state prediction. Future TSE state estimates are predicted at the instant of Phasor Measurement Unit (PMU) measurements received at the energy management systems. Auto Regressive, Feed Forward Neural Network and Nonlinear Auto Regression exogenous models are used for state prediction and the effectiveness of these models are evaluated. Then, the state vectors of Hybrid State Estimation (HSE) are calculated using predicted state vector and selected PMU measurements. The Neural Network based SE provides best state estimates over AR based SE. The working of the proposed process is validated through the simulations carried out on standard IEEE 14 bus, 30 bus, 57 bus and 118 bus systems.

Keywords

SCADA, Phasor measurements auto regressive and neural networks, Weighted least square estimator technique, Traditional state estimator (TSE), Hybrid state estimation (HSE), Auto regressive, Feed forward neural network, Nonlinear auto regression exogenous models and Analog measurements.

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G. A. Ezhilarasi ¹, K. S. Swarup ¹

Affiliations
1 Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai – 600036, IN

Abstract

This paper proposes a parallel processing approach to Contingency Analysis (CA) for power system security evaluation. Full AC power fl ow analysis is done for each contingency and violations of bus voltages and line fl ows are evaluated. All possible line outages are considered to avoid overlooking of certain critical cases. Parallel Processing is employed to increase the speed of execution. Parallelism is achieved by sharing each contingency across processors. The proposed methodology is implemented in a Linux Cluster. Data communication is performed through the Message Passing Interface (MPI). The effectiveness of parallelism is demonstrated by performing contingency analysis on standard IEEE Systems. The performance of the algorithm is analyzed in terms of computation speed and effi ciency in comparison with the sequential approach.

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