Application of Soft Computing Techniques in Power Engineering

A discharge estimator is designed and analyzed in this chapter to estimate the discharge with voltage, frequency and current without prior knowledge of head. A control of discharge in submersible pump is achieved by varying the motor speed. In VSI fed induction motor the speed is varied by varying the switching frequency. The ratio of frequency to the applied voltage is maintained constant, to keep the air gap flux at a desired value. The development of discharge estimator, PID and Fuzzy controllers are discussed in this chapter.

Parameter Estimation of an High Performance I.M. Drive for Sensorless Operation

A modern AC motor drive is a very intelligent system which covers a wide range of different electro technical apparatus and a wide scope of electrical engineering skills. A modern AC motor drive consists of four closely acting main parts: the AC machine, the power electronics, the motor control algorithm and the control hardware, i.e. the signal electronics. The advances in semiconductors and microelectronics have made the rapid development of AC motor drives possible. Semiconductors used in the switching converters provide the electric energy processing capability and microcontrollers and digital signal processors provide the data processing power for complex control algorithms.

Global and Local Clustering-Based Regression Models to Forecast Power Consumption in Buildings

The study of energy efficiency in buildings is an active field of research. Modeling and predicting energy related magnitudes leads to analyze electric power consumption and can achieve economical benefits. In this study, classical time series analysis and machine learning techniques, introducing clustering in some models, are applied to predict active power in buildings. The real data acquired corresponds to time, environmental and electrical data of 30 buildings belonging to the University of León (Spain). Firstly, we segmented buildings in terms of their energy consumption using principal component analysis. Afterwards, we applied state of the art machine learning methods and compare between them. Finally, we predicted daily electric power consumption profiles and compare them with actual data for different buildings. Our analysis shows that multilayer perceptrons have the lowest error followed by support vector regression and clustered extreme learning machines. We also analyze daily load profiles on weekdays and weekends for different buildings.

STATCOM Based Solid State Voltage Regulation for Isolated Self-Excited Induction Generator

Self-Excited Induction Generator (SEIG) offers many advantages such as low cost, simplicity, robust construction, self-protection against faults and maintenance free in today's renewable energy industry. However, the SEIG demands an external supply of reactive power to maintain the constant terminal voltage under the varying loading conditions, which limits the application of SEIG as a standalone power generator. The regulation of speed and voltage does not result in a satisfactory improvement although several studies have been emphasized on this topic in the past. To improve the performance of the SEIG system in isolated areas and to regulate the terminal voltage STATic COMpensator (STATCOM) has been modelled and developed in this dissertation. The STATCOM consists of AC inductors, a DC bus capacitor and solid-state self-commutating devices. The ratings of these components are quite important for designing and controlling of STATCOM to maintain the constant terminal voltage. The proposed generating system is modelled and simulated in MATLAB along with Simulink and sim power system block set toolboxes. The simulated results are presented to demonstrate the capability of an isolated power generating system for feeding three-phase resistive loads.

Energy Management Strategies to Improve Electrical Networks Using Storage Systems

The successive energy crises, usually linked to the rising prices of oil, bring about new topics of the energy systems management in general terms. Over all, the electrical system is one of these cases. In addition, a greater concern for environmental issues has introduced, to a greater or lesser extent, the generation from renewable sources in the electrical system. In this context, the possibility of developing and using electricity storage systems would manage mismatches between generation and demand at electricity networks, making them more efficiently. In this research, we propose a number of possible strategies based on technical peak shaving and valley filling. The tool is used as energy storage systems in general terms, regardless of the accumulation technique used. The classification of strategies essentially serves two criteria: optimization service and increased profitability.

Energy-Efficient Routing Techniques for Wireless Sensors Networks

Wireless sensor networks (WSNs), which normally consist of hundreds or thousands of sensor nodes each capable of sensing, processing, and transmitting environmental information, are deployed to monitor certain physical phenomena or to detect and track certain objects in an area of interests. The sensor nodes in WSN transmit data depending on local information and parameters such as signal strength, power consumption, location of data collection and accretion. Only reachable nodes are able to communicate with each other directly to collect and transmit data. The motes have limited energy resources along with constraints on its computational and storage capabilities. Thus, innovative techniques that eliminate energy inefficiencies that would shorten the lifetime of the network are highly required. Such constraints combined with a typical deployment of large number of sensor nodes pose many challenges to the design and management of WSNs and necessitate energy-awareness at all layers of the networking protocol stack. In this chapter, we present a survey of the state-of-the-art routing techniques in WSNs that take into consideration the energy issue.

Contemporary Energy Management Systems and Future Prospects

The transformation of electric grid into smart grid has improved management of available resources and increased energy efficiency. Energy management systems (EMS) play an important role in enhancing user participation in control of energy management. Using such systems, consumers can obtain information about their energy consumption patterns and shape their energy consumption behaviors for efficient energy utilization. Contemporary EMS utilizes advanced analytics and ICT to provide consumers actionable feedback and control of energy management. These systems provide high availability, an easy-to-use user interface, security, and privacy. This chapter explores the contemporary EMS, their applications, classifications, standards, and frameworks. The chapter defines a set of requirements for EMS and provides feature comparison of various EMS. The chapter also discusses emerging trends and future research areas in EMS.

Electrical Faults in Power Systems

The identification and classification of electrical faults have a great importance in power system analysis. They help in the dimensioning and the adequate choice of electrical equipment, especially, for protective and interrupting devices. This chapter describes the various faults undergone by the power system and removes some ambiguities causing confusions and difficulties for the correct classification of faults. Once the faults terminologies are well understood and properly assessed; they can be used efficiently to develop enhanced algorithms dedicated to fault detection, classification, isolation and diagnostics.

Restructuring Power Industry in India

Since the beginning of the nineties decade, many nations have undergone a change in the method of operations of the power network. The power sector was switched to open access market from vertically integrated market. The reasons for this change are many and they differ from nation to nation. The developing countries faced the problem of high demand growth along with irrational tariff policies and lack of efficiency in managing the power system. On the contrary, the developed countries restructured the power sector to provide electricity at lower prices and give the customers a number of operators to choose from. In short, the goal of restructuring is to encourage competition in the market along with providing consumers with more choices in purchasing economic energy and economic benefits. This might seem to be less complex but involves several issues which are discussed further. This chapter describes this restructuring of power sector with special reference to Indian scenario.

Energy Management in Cloud Computing

Due to the growing demand of businesses, enterprises are concentrating on performance improvement as well as investment reduction for their applications. Cloud Computing, an emerging technology which provides enormous services through internet is the best choice for the enterprises to improve their business performance and to reduce their capital budget. Cloud datacenters have thousands of servers to provide uninterrupted services to the consumers. These High Performance Computing systems consumes high energy, which leads to increase in Cloud Service Providers operational cost. Apart from the operational cost it also increases CO2 emission, which causes Global warming. So many researchers are evolving engineering techniques that are required to improve performance as well as optimization in power consumption. This chapter describes some of the techniques that are used to reduce operational cost, CO2 emission, SLA violation and able to maintain Quality of Service (QoS). It also describes about limitations on existing methods and further enhancement issues for better performance.