A New Robust H∞ Control Power

Attention has been paid by many researchers to address the various challenges of grid connection of DFIG-based Wind Energy Conversion Systems (WECS). This chapter focuses on the design of a robust H8 controller for the power flow between the stator of the Doubly-Fed Induction Generator (DFIG) and the grid. The robust H8 controller design is formulated as a mixed-sensitivity problem. A mathematical model of the DFIG written in an appropriate d-q reference frame is established to carry out simulations. The proposed power control scheme is elaborated and compared with a conventional Proportional-Integral (PI) controller based on vector control technique. The results show interesting performance of the controlled system in terms of the power reference tracking (the active and reactive power) and robustness against parameter variations compared with the conventional PI controller.

Energy and Exergy Analysis on Gasification Processes

In recent years, attention has focused on exergy analysis, a type of thermodynamic analysis which is an important tool for the efficiency assessment and the processes optimization when dealing with energy conversion and, particularly, thermochemical processes such as gasification. Thus, this chapter aims to introduce the fundamental concepts of energy and exergy and describe the energy and exergy evaluation tools, elucidating its importance for calculations applied to gasification processes. A case study was performed to show the proposal of energy and exergy analysis. Therefore, a single global gasification chemical reaction was used to represent the gasification process. This analysis can provide a tool to assess and develop models, simulations, calculations, and to optimize real gasification processes. Information and experiences covered in this chapter help to be put into perspective the technology, research and overcoming of challenges.

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.

Optimal Operational Strategy for PV/Wind-Diesel Hybrid Power Generation System with Energy Storage

Telecommunications industry requires efficient, reliable and cost-effective hybrid power system as alternative to the power supplied by diesel generator. This paper proposed an operational control algorithm that will be used to control and supervise the operations of PV/Wind-Diesel hybrid power generation system for GSM base station sites. The control algorithm was developed in such a way that it coordinates when power should be generated by renewable energy (PV panels and Wind turbine) and when it should be generated by diesel generator and is intended to maximize the use of renewable system while limiting the use of diesel generator. Diesel generator is allocated only when the demand cannot be met by the renewable energy sources including battery bank. The developed algorithm was used to study the operations of the hybrid PV/Wind-Diesel energy system. The control simulation shows that the developed algorithm reduces the operational hours of the diesel generator thereby reducing the running cost of the hybrid energy system as well as the pollutant emissions. With the data collected from the site, a detailed economic and environmental analysis was carried out using micro power optimization software homer. The study evaluates savings associated with conversion of the diesel powered system to a PV/Wind-Diesel hybrid power system.

Signal Processing Techniques in Smart Grids

Basic concept of a smart grid is to have monitoring capability with data integration, advanced analysis to support system control, enhanced power security and effective communication to meet the power demand and reduce the energy consumption and cost. Implementing the smart grid will require intelligent interaction between the power generating and consuming devices that can be achieved by installing devices capable of processing data and communicating it to various parts in the grid. In short, we can say that the modern efficient data processing and communication technologies require advance digital signal processing techniques used in smart grid. This chapter first provides a comprehensive survey on the applications of signal processing techniques in smart grid. The challenges and limitations of signal processing techniques regarding the smart grid are also presented. Literature review of the recent advances in smart grid is also presented. This chapter also outlines some future research directions related to the field of applications of signal processing techniques in smart grid.

Dynamic Particle Swarm Optimization with Any Irregular Initial Small-World Topology

It is realized that the topological structure of the particle swarm optimization (PSO) algorithm has a great influence on its optimization ability. This paper presents a new dynamic small-world neighborhood PSO (D-SWPSO) algorithm whose neighbourhood structure can be constructed with any irregular initial networks. The choice of the learning exemplar is not only based upon the big clustering coefficient and the average shortest distance for a regular network, but also based upon the eigenvalues of Laplacian matrix for irregular networks. Therefore, the D-SWPSO is a PSO algorithm based on small-world topological neighbourhood with universal significance. The proposed algorithm is tested by some typical benchmark test functions, and the results confirm that there is a significant improvement over the basic PSO algorithm. Finally, the algorithm is applied to a real-world optimization problem, the economic dispatch on the IEEE30 system with wind farms. The results demonstrate that the proposed D-SWPSO is a practically feasible and effective algorithm.

Applications of Vibration-Based Energy Harvesting (VEH) Devices

This chapter reviews present usage of vibration-based energy harvesting (VEH) devices and applications. The evolution of energy resources and advance in electronic technologies has resulting the need of self-sustainable wireless/portable electronic devices in current modern society. Batteries are non-beneficial in the miniaturization process of electronic designing and alternative power supplies are desperately needed to fill in the falling behind technologies gap to drive the advance of the wireless/portable development further. VEH mechanism is suggested in this chapter as the solution for the bottleneck. Various consideration of creating an optimal vibration energy harvester are suggested through an analytical model of a mechanical transducer. Useful applications and usages of VEH are presented and some suggestion for improvement are also given. Lastly, the trend of energy harvesting is annotated and commented in-line with the demand of electronic sensors market.

Intelligent Computing on the Basis of Cognitive and Event Modeling, and Its Application in Energy Security Research

The paper considers the issues of implementation and application of intelligent computing on the basis of cognitive and event modeling in research on energy security. The authors suggest a two-level information technology for the research. The first level suggests a situation analysis using the intelligent computing techniques. The analysis results are then used to choose rational variants of energy development in Russia (or its regions). At the second level these variants are computed with the multi-agent software INTEC-M. Transition from the first to the second level is automated by the tools of deductive program synthesis, that are based on declarative descriptions, i.e. formulae of restricted predicate calculus, and representation of input data by XML files. Cognitive and event modeling is considered in more detail. The examples of cognitive and event models are presented. The structure of a knowledge space is developed to support the intelligent computations. The knowledge space includes ontological models, databases of cognitive and event models, and the database on the cases of energy emergency situations. The authors developed the CogMap and EventMap tools to support cognitive and event modeling on the basis of common graphical environment GirModeling, and the expert system “Emergency”. The tools and expert system that support the knowledge base on energy emergencies are integrated within the intelligent IT environment. The research presented in the paper was partially supported by the grant of Presidium of RAS No. 2.2-2012 and grants of Russian Foundation of Basic Research No. 10-07-00264, No. 11-07-00192, No. 11-07-00245, and No. 12-07-00359.

Intelligent Bidding in Smart Electricity Markets

This paper has two aims. Firstly, to briefly present overall objectives and expected outcome of an on-going effort concerning design, implementation and the analysis of next generation energy systems based on anticipatory control and a set of ICT emerging technologies and innovations. Secondly, to describe an early proof-of-concept implementation and the associated experimentation of a simulation platform focused on holistic detailed studies of electric energy markets. The proposed platform allows us to elucidate issues related to the open and smart participation of producers and consumers on large-scale e-markets. Based on an existing simulation system, the authors present the required theoretical studies, the enabling technologies, and the practical tools that contribute to the development of such a platform capable of truly large scale simulations. Elements of game theory are utilized to solve the optimization problem related to the maximization of the social welfare of producers and consumers. Selected simulation results associated with the basic required characteristics are presented.

A Game Theoretic Framework for Green HetNets Using D2D Traffic Offload and Renewable Energy Powered Base Stations

This chapter investigates the interplay between cooperative device-to-device (D2D) communications and green communications in LTE heterogeneous networks (HetNets). Two game theoretic concepts are studied and analyzed in order to perform dynamic HetNet base station (BS) on/off switching. The first approach is a coalition-based method whereas the second is based on the Nash bargaining solution. Afterwards, a method for coupling the BS on/off switching approach with D2D collaborative communications is presented and shown to lead to increased energy efficiency. The savings are additionally increased when a portion of the small cell BSs in a HetNet are powered by renewable energy sources. Different utility functions, modeling the game theoretic framework governing the energy consumption balance between the cellular network and the mobile terminals (MTs), are proposed and compared, and their impact on MT quality of service (QoS) is analyzed.