Special Sessions/Stream

Session 1

Prof. Amine Boudghene Stambouli

Department of Electronics, Electrical and Electronics Engineering Faculty

University of Sciences and Technology of Oran

BP 1505, EL M’Naouer, Oran (31000). Algeria.

Tel & Fax : 00 213 41 56 03 29/56 03 01

e-mail : aboudghenes@yahoo.com , boudghene@uni-usto.dz

Renewable Energy Systems for Electricity Generation and Clean Mechanism Development (CDM)

The issues of energy cost and sustainable development had boosted the research, business and market of renewable energy technology. Renewable energy sources can be used in many ways. They offer minimal environmental problems with usage and can also be utilized with appropriate technology. These sources hold the best promise for electrification, especially for remote and rural areas where the conventional electricity grid cannot be extended economically.

This proposed session will discuss all types of renewable energy sources taking into consideration the scientific, economic, policy making, environmental and social issues involved.

Session 2

Dr. Raymond Trevor Harris

Department of Electrical Engineering, Faculty of Engineering

The Built Environment and Information Technology

NMMU, South Africa

e-mail: rharris@nmmu.ac.za

Power Systems Optimization and Solution Techniques

Internationally electrical supply utilities are increasingly considering methods of reducing their energy cost and improving the quality of supply to the consumer. As a result new research is developing optimal solutions for improving power system reliability using novel techniques.

This proposed session will include all types of methodologies, technologies, strategies, economic and environmental issues faced by electrical supply utilities globally.

Session 3

Dr. Talib Hashim Hasan

Department of Science in Engineering, Faculty of Engineering
International Islamic University Malaysia
Kuala Lumpur, Malaysia
Office telephone:00-60-3-61965438
Fax :00-60-3-61964465
Mobile: 00-60-136407803
email :talib@iiu.edu.my
           
The Implementation of Homotopy Techniques for Solving Nonlinear Algebraic Equations in Engineering Problems

Although they arise in other problems, roots of equations frequently occur in the area of engineering design. Some of engineering problems are nonlinear algebraic equations taken from different disciplines of engineering as chemical, civil, electrical, and mechanical. Nonlinear algebraic equation (NLAE) can be formulized as f(x) = 0. The solution (root) of this equation is to find a value a satisfies the given problem; f(a) = 0. There are two main methods to solve NLAE analytical methods and numerical methods. Analytical Methods (AM) can be used to find the fixed (exact, real) solution for NLAE. The weakness of AM is the limitation of its ability in solving higher orders, trigonometric, transcendental, and hyperbolic NLAE. Numerical methods (NM) used to find the approximate solution for NLAE, a value b satisfies the given problem; f(b) 0.. These methods were considered as alternative methods of AM because of their ability in solving all types of NLAE. NM some times are going to be divergent from the desire solution unless start from a certain initial value. This fact made NM is not effective always for solving NLAE. As an alternative, it was suggested a new approach to solve NLAE based on homotopy mapping. We called this approach as Honotopy Approximation Methods (HAM). The idea of HAM is to convert NLAE f(x) = 0 to another nonlinear algebraic equation H(x, t) = 0 where t Î [0, 1] is an embedding parameter and then solve this new equation (Called Homotopy Nonlinear Algebraic Equation; HNLAE) using Taylor expansion series, differential equation, or basic parametric equation. The main advantage of HAM is its global convergence, which is all types of NLAE can be solved numerically for any arbitrary initial solution. Using HAM will enable us to avoid the divergence which usually appears in the classical numerical method either bracketing methods such as graphical methods, bisection method, and the false-position method or open methods such as fixed-point iteration, Newton-Raphson, and the secant method. Another important advantage of HAM is the number of iteration can be estimated by controlling the value of the parameter t based on the increment of Dt. The applications of HAM in engineering are to solve van der Waals to control the molal volume of both carbon dioxide and oxygen, the continuity equation for controlling a specific depth of the water in open-channel flow, and design of an electric circuit to determine and optimize the proper resistor to dissipate energy at a specified rate.

Session 4

Associate Professor Kwon-Hee Lee, Ph.D
Dept. of Mech. Eng., Dong-A Univ.
Hadan-2-Dong 840, Busan, Korea

E-mail: leekh@dau.ac.kr  
Tel.: +82-51-200-7638

Fax.: +82-51-200-7656

Numerical Analysis and Optimization for Valve Design

A valve is a device that regulates the flow or the pressure in a fluid flow or pressure system. This regulation may involve the stopping and starting of flow, flow rate control, flow diversion, back flow prevention, pressure control, or pressure relief. A valve should be designed for smooth operation and should satisfy the structural safety requirement under diverse environments. Generally, the flow coefficient is considered as the standard response in selecting a valve. The flow resistance coefficient and the flow coefficient are inversely proportional to each other. The optimization problem of a valve is a coupled problem that requires fluid flow analysis and structural analysis. Usually, the stress is calculated by FSI (Fluid Structural Interaction). FSI analysis applies the result (forces or temperature or convection load) at the fluid-structure interface as a load to the simulation analysis. This session will provide a forum for discussion of technologies used to perform numerical analysis and optimization for valve design.

Session 5

Prof. Dr. Suhail A. Qureshi 
Electrical Engg. Dept. UET

Lahore-Pakistan
saqureshi@uet.edu.pk

Prof. Dr. M. Kamran
Electrical Engg. Deptt.  UET

Lahore-Pakistan

kamran.uet@gmail.com

Scope of Renewable Energy Resources in Developing Countries in South Asia
Energy Crisis are the main issue in Developing countries in South.  Renewable Energy resources seems to be the only solution to over-come these crisis.  The emphasis will be given on the possibilities of Wind and Solar Energy resources.

Session 6

Donald Davendra, Dr. Roman Senkerik and Prof. Ivan Zelinka

Department of Applied Informatics, Faculty of Applied Informatics

Tomas Bata Univerzity in Zlin

Nad Stranemi Czech Republic

davendra@fai.utb.cz senkerik@fai.utb.cz zelinka @fai.utb.cz

Evolutionary Algorithms and Chaotic Systems

Evolutionary Algorithms (EA) is one of the most important tools for complex systems evaluation. Some of the recent EA’s are Differential Evolution, Particle Swamp, and Self Organising Migrating Algorithm amongst others. The recent advents in ES have been in the ideology of hybrid systems and more recently Chaotic Systems. The theory of chaos is one of the most considerable products of physics in the 20th century. Systems that exhibit mathematical chaos are deterministic. When we say that chaos theory deals with deterministic systems, it means that these systems are exactly given by the system of mathematic equations and in spite of it, exhibits chaotic behavior. In mathematics and physics, chaos theory deals with the certain nonlinear dynamical systems that under certain conditions, the phenomenon known as chaos, exhibits in their behavior. This is most famously characterized by the phenomenon of sensitivity to initial conditions, which is the most commonly described as “butterfly effect”. Examples of such systems can be seen in ordinary word around us and of course in almost every science disciplines include the earth’s atmosphere, the solar system (three body problem), turbulent fluids, economies (exchange rate and stock markets), population growth, physics (control of plasma) and chemistry. Deterministic chaos can also be found in either very simple mechanical systems (double pendulum) or simple electronic circuits. Chaos theory has also a big significance in communication and cryptography. This track is focused on both the EA’s and Chaos but also in the scope of the coupled systems of these two. Coupled chaotic systems with metaheuristics, either induced, synchronized, hybridized or in tandem is a growing field of research.

Session 7

Professor Dr. Sergey KRYZHEVICH

Faculty of Mathematics and Mechanics

Saint-Petersburg State University

Complex Systems and Chaotic Dynamics

Different approaches to chaos and complexity (numerical, analytical and experimental) shall be studied. The different results on modeling of physical, mechanical systems, new numerical methods and pure mathematical ones will be considered.

Session 8

Dr. Abdeen Mustafa Omer

abdeenomer2@yahoo.co.uk

Renewable Energy Technologies

The move towards a low-carbon world, driven partly by climate science and partly by the business opportunities it offers, will need the promotion of environmentally friendly alternatives if an acceptable stabilisation level of atmospheric carbon dioxide is to be achieved. This requires the harnessing and use of natural resources that produce no air pollution or GHGs and provides comfortable coexistence of humans, livestock, and plants. Therefore, promoting innovative renewable energy applications including the renewable energy sources may contribute to preservation of the ecosystem by reducing emissions at local and global levels. This will also contribute to the amelioration of environmental conditions by replacing conventional fuels with renewable energies that produce no air pollution or GHGs.

The main purpose of the session is to:

1. Bring together scientists and technologists from the globe to present, discuss and further develop views on various fields of renewable energy.

2. Identify the most feasible and cost-effective applications of both technologies.

3. Review the conversion and efficient utilisation methods of traditional energy sources and discuss implications of energy efficiency on the development of renewable energy technologies.

4. Ensure that renewable energy takes its proper place in the sustainable supply and use of energy, taking due account of research requirements, energy efficiency, conversion and cost criteria for renewable energy.

Session 9

Dr.  Manu P. Singh

Department of Computer Science,

Institute of Computer and Information Science

Dr. B. R. Ambedkar University, Agra 28202, Uttar Pradesh, India

Hybrid Evolutionary Systems for Multi objective Optimization

In the multi-objective optimization problem we have number of objective functions, which are to be minimized or maximized or some functions are minimized and simultaneously other are maximized. In most practical decision-making problems, multiple objectives are evident. Because of lack of suitable solution methodologies, a multi-objective optimization problem has been mostly cast and solved as a single objective optimization problem in the past. However there exist a number of fundamental differences between the working principals of single and multi objective optimization problem, the task is to find one solution, so there is only one goal which is to search for an optimum solution. However, in multi-objective optimization problem, there is more than one goal. There are various possibilities may occur for these number of goals. It may happen that all the goals will  minimized or maximized and some of the goals will minimized & others will maximized. It has been very well established that techniques of neural networks specially feedforward and feedback neural network are extensively used for the various optimization problems. In the pattern classification or mapping task the MLP has used with descent gradient method for the multidimensional local errors minimization as well as the minimization of unknown global error. This task is clearly evident for the multi-objective problem.  The descent gradient method suffers with the problem of local minima’s or non optimal solutions for a large set of problems. A local minimum is defined as a point such that all points in a neighborhood have an error value greater than or equal to the error value in that point. The Genetic Algorithm (GA) is very popular method for exploring the optimum solution. The GA is a good candidate for skipping the local minima of errors and explores the global minimum of the error for pattern classification and mapping problem with MLP. In fact the simple random GA is not suitable for the multi-objective optimization problem instead of this it has been used very well only for the single objective optimization problems. The recent era of soft computing is emerging with hybrid evolutionary systems as a tool for handling these types of problems for pattern recognition. The feedforward neural network architecture evolves with the sub optimal solution in the starting after the training of conventional backpropagation algorithm. The hybrid GA evolves the population of weights and biases on the each iteration and this iteration continue till the network is not converged for the given problem set. The converged network exhibits the global optimal solution. The global optimal solution reflects the minimization of local error as well the minimization of global error simultaneously. It also explore the number of optimal solutions those are possible for the given problem. Thus, the nature of the solution is multiple solution of multi-objective optimization problem. In this theme the papers on following sub areas may consider:

1.      Evolutionary algorithms for optimization.

2.      Optimization with soft computing techniques

3.      Heuristic multi-objective optimization

4.      Neural network’s optimization

5.      Optimization for pattern recognition

6.      Machine learning and multi-objective optimization.  

Session 10

Professor Weerakorn

Asia Institute of Technology, Thailand

Energy market operation and optimization

This session includes power system operation and optimization in liberalized environment. Various research viewpoints in market operating, planning and decision making would be discussed. For example, congestion management is a main task of the market operator for delivering energy to consumers completely. In addition, market analysis is necessary to enhance participants’ competitiveness. Suppliers and consumers develop trading strategies to gain payoff and reduce cost. The proposed session could be benefit for engineers and researchers who are investigating solutions in energy market treatment

Session 11

Dr. N. A. Wassan

Centre for Heuristic Optimisation,

Kent Business School,

The University of Kent, Canterbury, UK

Metaheuristics for Combinatorial Optimization Problems

 Metaheuristics have been very successful in tackling hard Combinatorial Optimization problems in areas such as Industry, Business, logistics, Computer Science, Engineering, Government etc. The most well-known Metaheuristics are Tabu Search, Simulated Annealing, Genetic Algorithms, Scatter Search, Variable Neighbourhood Search, Ant Colony Optimization, Greedy Randomized Adaptive Search, Particle Swarm Optimization, etc.

For this session we are inviting papers contributing to methodological developments and successful implementations of Metaheuristics and their hybrids.

Session 12

M.G.C. Bosman

Department of Electrical Engineering, Mathematics and Computer Science

University of Twente, Enschede, The Netherlands

Evolving electricity networks

In the development of electricity generators the focus is often on energy efficiency, CO2 reduction or use of renewable sources. However, the implications on the total electricity grid are often neglected. Questions are rising whether the existing network dimensions are sufficient for mass introduction of various kinds of distributed generators, hard-to-predict wind mills or photovoltaic cells, etcetera. Can we still guarantee that the network produces a stable output under all circumstances? For example, we can think of different weather conditions or the impact of seasonal behaviour on the resulting generation of different types of electricity generators, or the customer behaviour of owners of distributed generators, resulting in conflicting objectives for customers, suppliers and network operators. Is the existing network capable of coping with these new types of generators and the stochastic variation that comes along with them? Energy storage and delayed generation/consumption can help to compensate for the mismatch between generation and consumption.

In this session we address the following questions:

• What is the impact of new technologies on the stability of the network?

• Can we control this evolving network by steering the production of distributed generators?

• Can we improve the overall efficiency of production and transportation and control, including all additional generation, losses and overhead which are necessary or inevitable for a seamless (stable) introduction in the electricity network?

Keywords: distributed generation, storage, demand side load management, scheduling

Stream 1

Continuous Optimization and Applications

Professor Gerhard-Wilhelm Weber (Turkey)

Professor Erik Kropat (Germany)

Professor Zeev Volkovich (Israel): "Optimization Approaches in Classification Problems"

Professor Adil Baghirov (Australia)

Associate Professor Vadim Strijov (Russia)

Associate Professor Inci Batmaz (Turkey)

Stream 2

Global Optimization

Professor Celso (Brazil): "Applications of meta-heuristics to power problems"

Ramesh C. Bansal (Australia): "Reactive power control in renewable energy systems"

Kamal K Saini (India): "Neuro-Fuzzy Networks & their advance applications"

Special Sessions Committee

Musa Mammadov, m.mammadov@ballarat.edu.au

Zari Dzalilov, z.dzalilov@ballarat.edu.au