On robust synchronization of nonlinear systems with application to grid integration of renewable energy sources

Many systems in the natural and physical world often work in unison with similar other systems. This process of simultaneous operation is known as synchronization. In the past few decades, owing to this phenomenon’s importance, extensive research efforts have been made. However, many of the existing results consider the systems are identical and/or linear time-invariant, while practical systems are often nonlinear and nonidentical for various reasons. This observation motivated several recent studies on the synchronization of nonidentical (i.e., heterogeneous) nonlinear systems. This paper summarizes some recent results on the synchronization of heterogeneous nonlinear systems, as developed in the thesis (Ahmed 2016). First, the results on the synchronization of a particular class of robustly stable nonlinear systems are presented. Then, these results are applied to an example model known as Brockett oscillator. Finally, using the Brockett oscillator as a common dynamics, output oscillatory synchronization results are given for heterogeneous nonlinear systems of relative degree 2 or higher. An application example of Brockett oscillator for power-grid synchronization is also presented. Some outlooks are provided regarding future research directions.     

Video-sharing educational tool applied to the teaching in renewable energy subjects

The impact and evaluation of an educational tool “Renewable Energy Video sharing”, based on videocast techniques is presented in this paper. This tool arose from a learning innovation project developed in the Electronics and Automation Engineering Department at the University of Jaén. This experience consists of the elaboration of multimedia materials showing different ways of obtaining thermal energy and electricity from renewable resources as well as the equipment and the technology implicated in these process. Thus a video channel, implemented in YouTube™ platform, and an online space were implemented where these multimedia materials can be found and played, bringing technological reality closer to the final user – to the students in this specific case – in an easy, interactive and free way from any device with an internet connection. This learning tool was applied and used as a support in two ambits, face-to-face and non face-to-face education, in two different educational levels: Undergraduate and Postgraduate Education. Three subjects in the field of photovoltaic solar energy experienced the e-learning tool, obtaining a high degree of general satisfaction among students. After analyzing the impact of the implemented tool through personal final questionnaires among students, an improvement of the understanding of the theoretic concepts previously studied as well as the facility of access to the contents being the most appreciated benefits.     

Geographical information systems and location science

Since the 1970s the field of Geographical Information Systems (GIS) has evolved into a mature research and application area involving a number of academic fields including Geography, Civil Engineering, Computer Science, Land Use Planning, and Environmental Science. GIS can support a wide range of spatial queries that can be used to support location studies. GIS will play a significant role in future location model development and application. We review existing work that forms the interface between GIS and Location Science and discuss some of the potential research areas involving both GIS and Location Science.Scope and purposeDuring the past 30 years there have been many developments in spatial data analysis, spatial data storage and retrieval, and mapping. Many of these developments have occurred in the field of Geographical Information Science. Geographical Information Systems software now supports many elementary and advanced spatial analytic approaches including the production of high quality maps. GIS will have a major impact on the field of Location Science in terms of model application and model development. The purpose of this paper is to explore the interface between the field of Location Science and GIS.     

Enhancement of hybrid renewable energy systems control with neural networks applied to weather forecasting: the case of Olvio

In this paper, an intelligent forecasting model, a recurrent neural network (RNN) with nonlinear autoregressive architecture, for daily and hourly solar radiation and wind speed prediction is proposed for the enhancement of the power management strategies (PMSs) of hybrid renewable energy systems (HYRES). The presented model (RNN) is applicable to an autonomous HYRES, where its estimations can be used by a central control unit in order to create in real time the proper PMSs for the efficient subsystems’ utilization and overall process optimization. For this purpose, a flexible network-based design of the HYRES is used and, moreover, applied to a specific system located on Olvio, near Xanthi, Greece, as part of Systems Sunlight S.A. facilities. The simulation results indicated that RNN is capable of assimilating the given information and delivering some satisfactory future estimation achieving regression coefficient from 0.93 up to 0.99 that can be used to safely calculate the available green energy. Moreover, it has some sufficient for the specific problem computational power, as it can deliver the final results in just a few seconds. As a result, the RNN framework, trained with local meteorological data, successfully manages to enhance and optimize the PMS based on the provided solar radiation and wind speed prediction and make the specific HYRES suitable for use as a stand-alone remote energy plant.     

新能源电力系统控制与优化

新能源电力的规模化开发以及传统能源的清洁高效利用已成为当前能源革命的主题.目前,我国新能源电力比例持续增加,但受限于化石能源占主导的电源结构,未来很长一段时间内我国将处于混合能源时代.强随机波动性、间歇性以及不确定性使得规模化新能源电力的消纳问题日益严重,我国弃风弃光现象十分突出.深入认知电源侧、电网侧、负荷侧的基本特性,着重解决其控制与优化难题,是实现新能源电力系统安全高效运行的基本前提.本文围绕电源效应、电网响应、负荷响应,着重从电网友好型发电控制、基于多源互补的火力发电弹性控制、适应高比例新能源电力消纳的电网调度控制、需求侧资源特性与主动适应控制以及基于分布式能源的微电网控制5个方面阐述了新能源电力系统局部与全局控制中存在的关键科学问题.     

Geographical information systems for map based navigation in urban environments

In order to solve most of the existing mobile robotics applications, the robot needs some information about its spatial environment encoded in what it has been commonly called a map. The knowledge contained in such a map, whatever approach is used to obtain it, will mainly be used by the robot to gain the ability to navigate in a given environment. We are describing in this paper, a method that allows a robot or team of robots to navigate in large urban areas for which an existing map in a standard human understandable fashion is available. As detailed maps of most urban areas already exist, it will be assumed that a map of the zone where the robot is supposed to work is given, which has not been constructed using the robot’s own sensors. We propose in this paper, the use of an existing Geographical Information System based map of an urban zone so that a robot or a team of robots can connect to this map and use it for navigation purposes. Details of the implemented system architecture as well as a position tracking experiment in a real outdoor environment, a University Campus, are provided.     

The academic field of information systems in Europe

This paper reviews the institutional and cognitive profile of the information systems (IS) field in Europe, using the results of a survey of IS academics in 18 European countries. The emerging picture suggests that the study of IS in European academia is dispersed in small units with various names, which are hosted in various disciplines across the science/social science spectrum. Our survey confirms the widespread view that the IS field is concerned with the study of a wide range of themes, from developing technologies per se, to assessing the social impact of new information and communication technologies. Moreover, a variety of research perspectives and approaches is found to be pursued, drawing from both the positivist and interpretative epistemological traditions. Reflecting upon the survey findings, we argue that while the institutional dispersion is a weakness that requires remedying action, the cognitive diversity should not be considered as a characteristic of immaturity. In Europe, the diversity of themes and research perspectives probably manifests more fundamental differences of the socioeconomic context which gives rise to, and sustains, different types of IS research in different countries.     

Advanced chance-constrained predictive control for the efficient energy management of renewable power systems

This study presents a complete advanced control structure aimed at the optimal and most efficient energy management for a Grid-Connected Hybrid Power plant. This control scheme is composed of process supervision and process control layers, and it is a possible technology to enable improvements in the energy consumption of industrial systems subject to constraints and process demands. The proposed structure consists of the combination of a Model-Based Predictive Controller, formulated within the Chance Constraints framework to deal with stochastic disturbances (renewable sources, as solar irradiance), an optimal finite-state machine decision system and the use of disturbance estimation techniques for the prediction of renewable sources. The predictive controller uses feedforward compensation of estimated future disturbances, obtained by the use of Nonlinear Auto-Regressive Neural Networks with time delays. The proposed controller aims to perform the management of which energy system to use and to decide where to store energy between multiple storage options. This has to be done while always maximizing the use of renewable energy and optimizing energy generation due to contract rules (maintain maximal economic profit). The proposed method is applied to a case study of energy generation in a sugar cane power plant, with non-dispatchable renewable sources (such as photovoltaic and wind power generation), as well as dispatchable sources (as biomass and biogas). This hybrid power system is subject to operational constraints, as to produce steam in different pressures, sustain internal demands and, imperiously, produce and maintain an amount of electric power throughout each month, defined by strict contract rules with a local Distribution Network Operator (DNO). This paper aims to justify the use of this novel approach to optimal energy generation in hybrid microgrids through simulation, illustrating the performance improvement for different cases.     

A quantile-based simulation optimization model for sizing hybrid renewable energy systems

As the public has gradually realized the adverse impacts brought by global warming, hybrid renewable energy system (HRES) has become increasingly popular because it can reduce dependence on fossil fuels, while maintaining the stability of power supply. While the HRES is an attractive option in many aspects, the fundamentally uncertain nature of renewable energy sources makes the determination of the proper sizing of the HRES a very challenging task. Contrasting with the existing models that are largely focused on expectation-based system performance, this paper provides a quantile-based simulation optimization model, followed by the development of an efficient solution methodology, to enable the control of the upside risk and, as a result, to enhance the decision quality regarding the sizing of HRES. One advantage of the proposed model is that they can be based on any existing deterministic model that carries a cost structure regarding the sizing of the HRES. Moreover, the proposed solution methodology, consisting of a Monte Carlo simulation method, quantile estimation techniques, and an efficient stochastic optimizer, allows for not only accurate estimation of the objective function value, but also quick identification of the optimal solution due to a uniquely-defined neighborhood structure. An extensive numerical experiment is conducted to verify the efficacy and efficiency of the proposed solution methodology. Finally, in collaboration with a partner in industry, the proposed model and the solution methodology are integrated into a decision support system to provide visualized results for sizing HRES in practice.     

Optimal reactive power dispatch with uncertainties in load demand and renewable energy sources adopting scenario-based approach

Optimizing reactive power flow in electrical network is an important aspect of system study as the reactive power supports network voltage which needs to be maintained within desirable limits for system reliability. A network consisting of only conventional thermal generators has been extensively studied for optimal active and reactive power dispatch. However, increasing penetration of renewable sources into the grid necessitates power flow studies incorporating these sources. This paper presents a formulation and solution procedure for stochastic optimal reactive power dispatch (ORPD) problem with uncertainties in load demand, wind and solar power. Appropriate probability density functions (PDFs) are considered to model the stochastic load demand and the power generated from the renewable energy sources. Numerous scenarios are created running Monte-Carlo simulation and scenario reduction technique is implemented to deal with reduced number of scenarios. Real power loss and steady state voltage deviation of load buses in the network are set as the objectives of optimization. Success history based adaptive differential evolution (SHADE) is adopted as the basic search algorithm. SHADE has been successfully integrated with a constraint handling technique, called epsilon constraint (EC) handling, to handle constraints in ORPD problem. The effectiveness of a proper constraint handling technique is substantiated with case studies for deterministic ORPD on base configurations of IEEE 30-bus and 57-bus systems using SHADE-EC algorithm. The single-objective and multi-objective stochastic ORPD cases are also solved using the SHADE-EC algorithm. The results are discussed, compared and critically analyzed in this study.     

Defining information systems as work systems: implications for the IS field

The lack of an agreed upon definition of information system (IS) is one of many obstacles troubling the academic IS discipline. After listing a number of definitions of IS, this paper defines IS as a special case of work system as defined in Alter (1999a). This definition has many desirable characteristics: it is easy to understand; differentiates IS from information technology (IT); covers totally manual, partially automated, and totally automated ISs; links to a life cycle model that generates many insights about development and implementation problems; provides a simple guideline that helps in interpreting common IS/IT jargon; and has other useful implications related to IS concepts, IS terminology, and the analysis and design of ISs. The paper presents the proposed IS definition and evaluates the definition in terms of simplicity, clarity, scope, systematic power, explanatory power, validity, reliability, and fruitfulness. An Appendix summarizes previously published concepts and two frameworks that flow from the proposed definition and are useful for appreciating many points in the evaluation section.     

Supervisory control design for systems of multiple sources of energy

This paper describes a supervisory control strategy for electrical energy transfers in multisource renewable energy systems. The sources are coupled onto a DC bus through DC/DC power converters. The aim is to control the energy transfers, according to the sources power and load variations. The controller determines the operating mode of the system. Then, it calculates the power ratio provided by each source and drives the DC/DC power converters with local current and voltage loops in order to regulate the voltage on the DC bus according to a reference value. The main contributions are to use the duty cycle values of the DC/DC power converters as decision criteria to switch the power sources and drive the power ratios, and to present the complete strategy in a single hierarchical control scheme with three stages. A non linear model of the closed loop system is also detailed in order to work out sufficient conditions for asymptotic stability. Finally, the proposed control scheme is validated with an experimental device developed by GREAH Research Group for the control of energy transfers in multi-source renewable energy systems.     

可再生能源分布式微网电源规划方法及应用

近年来, 可再生能源分布式发电微网技术研究引起国内外广泛关注. 本论文将遗传算法应用到风–光–柴–蓄组成的可再生能源分布式微网电源规划中, 建立微网电源规划模型及相关约束条件, 以满足能量平衡控制、费效率等为最优原则, 给出了算法的实现流程. 最后, 结合案例说明了算法的应用.     

Expert systems applied to problems in geographic information systems: Introduction, review and prospects

This paper critically reviews current expert system developments relevant to geographic information systems, and identifies several research topics for application of expert system technology in geographic information systems. We have identified four major problem domains of geographic information systems in which expert system technology has been applied—automated map design, terrain/feature extraction, database management/user interface, and geographic decision support systems. Efforts in each problem domain are critically reviewed. Considering the accomplishments and shortcomings of efforts to date, we identify areas likely to gain importance in this field. Our view of these prospects is moderated by constraints of current technology and a realistic view of current efforts. Future research will place more emphasis on formal representation of both knowledge and uncertainty. Another future research area will be the development of advanced tools for geographic knowledge acquisition. Finally, better methods for working with large-scale geographic databases will be needed.     

智能电网中可再生能源在需求侧的智能管理方法

针对当前火力发电电网中用户花费偏高和环境污染的问题,提出了一种智能电网中可再生能源在需求侧的智能管理方法。通过可再生能源与不可再生能源同时产生能源的方法,实现对环境污染程度的降低和需求侧用户累积开支的减少。仿真结果表明所提出的方法实现了用户的总开支最小。