Data Mining - Concepts and Techniques.

Introduction to stochastic programming

A systematic literature review of blockchain-based applications: Current status, classification and open issues

Trends in extreme learning machines

Differential Evolution (DE) is arguably one of the most powerful and versatile evolutionary optimizers for the continuous parameter spaces in recent times. Almost 5 years have passed since the first comprehensive survey article was published on DE by Das and Suganthan in 2011. Several developments have been reported on various aspects of the algorithm in these 5 years and the research on and with DE have now reached an impressive state. Considering the huge progress of research with DE and its applications in diverse domains of science and technology, we find that it is a high time to provide a critical review of the latest literatures published and also to point out some important future avenues of research. The purpose of this paper is to summarize and organize the information on these current developments on DE. Beginning with a comprehensive foundation of the basic DE family of algorithms, we proceed through the recent proposals on parameter adaptation of DE, DE-based single-objective global optimizers, DE adopted for various optimization scenarios including constrained, large-scale, multi-objective, multi-modal and dynamic optimization, hybridization of DE with other optimizers, and also the multi-faceted literature on applications of DE. The paper also presents a dozen of interesting open problems and future research issues on DE.

Recent advances in differential evolution – An updated survey

Renewable energy certificates and electricity trading models: Bi-level game approach

The overall goal of Project 2 has been to provide a comprehensive understanding of the impacts of distributed energy (DG) on the Australian Electricity System. The research team at the UQ Energy Economics and Management Group (EEMG) has constructed a variety of sophisticated models to analyse the various impacts of significant increases in DG. These models stress that the spatial configuration of the grid really matters - this has tended to be neglected in economic discussions of the costs of DG relative to conventional, centralized power generation. The modelling also makes it clear that efficient storage systems will often be critical in solving transient stability problems on the grid as we move to the greater provision of renewable DG. We show that DG can help to defer of transmission investments in certain conditions. The existing grid structure was constructed with different priorities in mind and we show that its replacement can come at a prohibitive cost unless the capability of the local grid to accommodate DG is assessed very carefully.

Market and Economic Modelling of the Intelligent Grid: End of Year Report 2009

This paper presents a portfolio management strategy to apply the financial options, especially put options, to earn extra monetary benefits (i.e. the premium) during the idle hours of the gas generator in the electricity market and to hedge the risk of electricity price fluctuations. In this paper three broad categories of cases are evaluated, involving the conventional operation case that no options are utilized and the put options with/without energy storage devices. In the mathematic model of these three cases, the revenues and costs have been aggregated to calculate the risks and the returns. For the case with the energy storage devices, this paper takes power-to-gas (P2G) and battery storage into account. To determine the optimal weight of the P2G and the battery, they will be arranged into a portfolio by using the mean-variance theory. A simulation is established based on the data of four sequential years from 2015 to 2018 in the Australian electricity market. The results show that the application of the put options will facilitate gas generators to earn more profits each year. Besides, the storage devices are key factors that make the put options worthwhile.

Gas Generation Portfolio Management Strategy Based on Financial Derivatives: Options

Residential customers-oriented customized electricity retail pricing design

Modern logistics system consists of physical resources composed by a large number of logistics nodes, logistics resources and transportation routes, and information resources composed by computer and communication systems. Traditional research on logistics optimization mainly focuses on the optimal utilization of the physical resources, while the impact and limitation of the information system are usually neglected. Using differential-algebraic equations, finite automata, stochastic process, queuing theory, this paper proposes a steady-state and dynamic model for quantitatively analyzing the information transmission performance in different communication networks. Based on the proposed model, a mathematical model for real-time vehicle route optimization is also proposed considering the information system. The information system design for logistics vehicle dispatching is also provided based on numerical simulations on different communication networks.

Junhua Zhao

Papers

Renewable energy certificates and electricity trading models: Bi-level game approach

Market and Economic Modelling of the Intelligent Grid: End of Year Report 2009

Gas Generation Portfolio Management Strategy Based on Financial Derivatives: Options

Residential customers-oriented customized electricity retail pricing design

Modeling and Analysis of the Cyber Infrastructure for Vehicle Route Optimization