Scientific Program

Conference Series Ltd invites all the participants across the globe to attend 1st International Conference on Smart Grid Technologies Singapore.

Day 2 :

Keynote Forum

Tony Cox

Cryptsoft, Australia

Keynote: Standardized encryption key management for smart grids with KMIP

Time : 10:00-11:00

OMICS International Smart Grid Convention 2017 International Conference Keynote Speaker Tony Cox photo
Biography:

Tony Cox has worked with both state and federal government departments on integration of security technology and public key infrastructure, with over a decade experience in both the security and identity management fields. He has an experience in evaluation of multi-million dollar procurement contracts and in the establishment and operation of policy authorities for public key infrastructure for million-plus smartcard token rollouts. He regularly presents to various audiences on interoperable key management and holds the following roles in the security standards space as a Co-Chair-OASIS KMIP Technical Committee, Co-Chair- OASIS PKCS11 Technical Committee and Chair-SNIA-SSIF Governing Board.

Abstract:

With the increased focus on cyber security within our critical infrastructure, the need for encryption as a primary defense is also growing. Wherever encryption is deployed, must the encryption keys be managed? Deploying standard-based key management infrastructure ensures these encryption keys can be managed throughout their entire lifecycle in a secure manner, using commercially available equipment via the KMIP (Key Management Infrastructure Protocol) specification. Developed within OASIS (Organization for the Advancement of Structured Information Standards), KMIP has widespread adoption in storage, information infrastructure and cloud deployments where it underpins the use of many forms of security objects including encryption keys, certificates, tokens, passwords, biometrics and identities. Multiple smart grid technology suppliers are now deploying KMIP conformant technology within their infrastructure to ensure maximum interoperability without sacrificing security. Adopting a well deployed standard means security solutions are readily available from a competitive market, delivering a greater return on investment from cyber security budgets. The KMIP specification has been developed and deployed since early 2009 by members of the KMIP Technical Committee (TC) whose membership includes many well-known brands in the IT and Cyber security industries and is now in its 5th iteration (v1.4) with version 2.0 well on the way. The specification documents cover both the detail of the specification as well as specific deployment profiles, ranging from key foundries, to encrypting storage arrays to post quantum computer cryptography. As smart grid deployments increase, we expect to see more requirements presented to the KMIP TC for inclusion in continued development of the specification.

  • Solar Cells | Energy Storage | Cybersecurity | Smart Appliances
Location: Seletar Room 2
Speaker

Chair

Gabor Karsai

Vanderbilt University, USA

Speaker
Biography:

Abel Tablada de la Torre is an Assistant Professor at the Department of Architecture of the National University of Singapore (NUS). His interests cover the topics of tropical net-zero/low-carbon architecture, natural ventilation, building simulation and renewable resources. Presently, he is leading a research on productive facades which integrate solar and farming systems.

 

Abstract:

Increasing energy and food self-sufficiency in urban areas is crucial to achieve a drastic reduction of carbon footprint and greenhouse gases emissions. This is especially important for Singapore which imports most of the food and energy it consumes. This study discusses the potential energy and food production at urban and building scales in residential districts in Singapore. Radiance-based simulations are conducted to quantify the sunlight availability on a large number of cases with different densities for three building typologies in Singapore. Regression analysis are performed to determine the thresholds of density indices; plot ratio, site coverage and building height, in order to achieve certain percentages of energy and food self-sufficiency. Finally, more detailed facade arrangements are proposed according to the sunlight availability per case as well as a facade prototype to be fabricated and installed at the Tropical Technology Lab at NUS campus. The study shows that full energy and food self-sufficiency can be achieved for districts with average building height <33 m and plot ratios <1.7, respectively. However, 50% of autonomy can be achieved for building height <68 m and plot ratios <2.7. The four main facade orientations are feasible to be used for solar panels and farming systems. However, it is recommended that larger PV surface area is installed on top sections of facades and farming and solar collectors on less exposed surfaces. Finally, a balance between PV dimensions, energy yield, heat gain reduction and daylight requires a precise analysis and design for every specific facade and context.

Speaker
Biography:

Muhannad Al Jebouri is currently a PhD candidate at Architecture Department, Faculty of Engineering and Built Environment, UKM, Malaysia. He has completed his MSc and has experience in architectural practical field. Presently, he is a Lecturer and has published two technical papers in reputed journals.

Abstract:

Most cities are in a trend of non-sustainability, against that, the concept of sustainability development has immerged and gave rise to Green Building Movement. The Brundtland Report 1987 considered as a Triple Bottom Line (TBL) based on environmental, economic and social issues. Pioneering eco-cities such as Masdar in UAE, Hammarby in Sweden and Dongtan in China have introduced the concept of sustainability, renewable energy sources, zero-carbon and zero-waste ecology. This study is to develop a framework for sustainable building in Oman. The structure of the proposed system development is composed of 5 themes (environmental, economic, social, cultural and governance requirements), 11 categories and 86 indicators. This study involves two main stages; the first stage concentrates on the formulation of the proposed system structure in relation to Oman by reviewing the literature on sustainable development and buildings, as well as analyzing international and regional sustainability-rating systems. The second stage focuses on formulating assessment categories and their relevant performance indicators which are validated through conducting a survey including different stakeholders of the industry from building engineers, building regulators and sustainability experts. Pairwise and direct ranking method comparisons are used as data collection methods to examine the relative importance and weights of each category and each indicator respectively. The analysis of survey data shows that a prominent relative importance and balanced weights are given to indoor environment quality, natural and human resources, social and governance requirements. The research output will help and promote future studies to develop a detailed assessment system for sustainable construction in Oman. The proposed framework is named Oman Building Environment Certificate (OMBEC). It is used as a pilot rating system for homes at present and then to be further expanded in the future to address other building types. The proposed rating system follows a hierarchy of three levels: Categories, indicators and parameters.

Biography:

Abstract:

Nowadays, electricity has become essential for improving the quality of life of the population; in developing countries, millions of people do not always have access to electricity. These people mainly reside in rural areas. The classical solution which is unrealistic below a certain power threshold, delays rural electrification and aggravates the exodus towards urban centers already congested and unable to absorb this migration, thus, to combat late electrification, new techniques are required for the countryside. In this paper, we describe the principles of some energy extraction techniques directly from the high voltage lines, profitable methods for the developing countries.

Speaker
Biography:

Koksal Erenturk has received his BS degree from Yildiz Technical University, Turkey, MS degree from Istanbul University, Turkey and PhD degree from Karadeniz Technical University, Turkey all in Electrical Engineering. His work has focused on the smart grid, renewable energy systems and development and application of control theory to a variety of mechatronic systems with a focus on observation and estimation based control and also on the analysis and control of dynamical systems that arise in engineering applications.

Abstract:

Smart energy systems are defined as an approach in which smart electricity, thermal and gas grids are combined and coordinated to identify synergies between them to achieve an optimal solution for each individual sector as well as for the overall energy system. The challenge of integrating the fluctuating renewable energy power sources such as wind, solar and ocean energy depends strongly on the share of the input. The following three phases of implementing renewable energy technologies can be defined as: (1) The introduction phase, (2) The large-scale integration phase and (3) The 100% renewable energy phase. The introduction phase represents a situation in which there is no or only a small share of renewable energy in the existing energy system. The phase is characterized by marginal proposals for the introduction of renewable energy, e.g., wind turbines are integrated into a system with only a limited share of wind power. The system will respond in the same way during all hours of the year and the technical influence of the integration on the system is easy to identify in terms of saved fuel on an annual basis. Moreover, the input of renewable power does not pose a challenge to the operation of the grid and the electricity balance. The large scale integration phase represents a situation in which there is already a major share of renewable energy in the system, e.g., when more wind turbines are added to a system which already has a high share of wind power. The phase is defined by the fact that further increase in renewable energy penetration will have an influence on the system and this will vary from one hour to another, e.g., depending on whether heat demand is high or low in the given hour, whether a heat storage is full or not or whether the electricity demand is high or low during the given hour. The integration of wind and solar power in the system becomes complex and requires consideration with regard to grid stabilization. The 100% renewable energy phase represents a situation in which the energy system is currently or is being transformed into a system. The system is characterized by the fact that new investments in renewable energy will have to be compared not to nuclear or fossil fuels, but to other sorts of renewable energy system technologies. These include conservation, efficiency improvements and storage and conversion technologies. The influence on the system is complex not only with regard to differences from one hour to another but also with regard to the identification of a suitable combination of changes in conversion and storage technologies. Moreover, the challenge of operating the grid in terms of ensuring frequency and voltage stability is of major importance.

Speaker
Biography:

Kshitija Bhasme has completed her Bachelor of Technology in the Faculty of Electronics and Communication from Usha Mittal Institute of Technology, SNDT Women’s University, India. She is currently working as a Research Intern in the field of Smart Grid Technologies at Center for Development of Advanced Computing (CDAC) which is an Autonomous Scientific Society of Department of Electronics and Information Technology (DeitY), Ministry of Communications and Information Technology, Government of India. Her past research experiences include a Research Internship with the Bhabha Atomic Research Center (BARC), Government of India where she has worked as a Research Project Trainee with some of the best scientific officers in India.

Abstract:

Nowadays, power grids are being integrated into the smart grid concept for efficiently managing and delivering electric power. A smart grid provides a two-way dialogue where electricity and the information can be exchanged between the utility and its customers by allowing them to sell and purchase electricity. Attacks on such systems may have catastrophic impact, especially on the customers which is a particular threat in the winter, when people can be left without heat. Hence, the mitigation solutions for these situations are necessary. It is impractical to test attacks and mitigation strategies on real-time networks. Therefore, we propose a predictive analysis to make the smart grid prepared to address power failure faults and attacks in the time of emergencies. We explain different power system scenarios and network designs by simulating IEEE 14 bus system models through Power System Analysis Toolbox (PSAT) in MATLAB for the assessment of power flow and to perform a complete and accurate power system analysis. A data sheet of power system analysis is created and fed into various machine learning algorithms in WEKA data mining tool. The goal is to make our machine learn different power system analysis scenarios in order to be able to detect normal, fault and attack instances in a power system by checking the accuracy of the instances being learnt by the machine and cluster formations of all the correctly classified instances. This can help save millions of dollars and long hours of investigation invested to study and detect unusual occurrences in a power system. We embark upon a journey towards a new era of reliability, availability and efficiency of the smart grid by bringing in the machine learning domain in the assessment process which is a faster and more reliable way of detecting adversities in a power system than the conventional way.

Muhammad Kamran

University of Engineering and Technology, Pakistan

Title: Efficient nonintrusive load monitoring technique
Speaker
Biography:

Muhammad Kamran has received his BSc and MSc Electrical Engineering (EE) (specialization in power) degree from University of Engineering & Technology (UET), Lahore, Pakistan in 1992 and 1999, respectively. He has completed his PhD in Computer Engineering from Beijing Institute of Technology, China in 2007. He is presently serving as a Professor and Campus Coordinator of a campus of UET, Lahore, Pakistan. He has 53 national and international publications focusing on computers and power engineering. Currently he is dealing with power system protection, power system quality and high voltage engineering at graduate and undergraduate level. He is also a Reviewer of famous international journals and conferences, Member of Pakistan Engineering Council Accreditation Committee, Convener of Higher Education Commission (HEC) and Pakistan Technology Curriculum Development Committee (2015).

Abstract:

 

With the advancement in smart grids, easy access to load monitoring and management is becoming essential feature of this modern system. In order to comply with this parameter, a novel nonintrusive load monitoring (NILM) technique is proposed in this paper. This technique is found cost effective, state of the art load monitoring and energy disaggregation that can be employed in conjunction with smart grids for smart energy management systems. NILM involves extracting load signatures of individual appliances from composite voltage and current signals and identifying those signatures by employing machine learning techniques. An introduction of novel feature extraction techniques involving fractal analysis has made it novel and comparison is made with other methods involving discrete wavelet analysis. Research has highlighted that fractal analysis has become emerging method for data extraction and analysis even utilizing artificial intelligence and neural networks. The results obtained in this research are appreciable to verify the effectiveness of novel technique of data extraction using fractal analysis which saves the time and cost of data management system and has become valuable feature of smart grids.

 

Biography:

Geetha S has completed her Post-graduation in Information Technology and pursuing her Doctoral studies. Presently, she is working as an Assistant Professor in an Engineering Institution. Her research interest includes smart grid, natural language processing and soft computing. Her research focuses on developing an optimization problem for demand response in smart grid and trying out its implementation in a real test bed.

Abstract:

Introduction: Smart Grids will be the promising solution to the future energy crisis. One of the most important features of the smart grid is its active Demand Response (DR) model through which the consumer can shape their daily energy consumption patterns so that they can reduce their energy usage and peak to average ratio (PAR).

Aim: In our work, bidirectional communication architecture has been proposed between the end users and the service provider. Real time pricing models (RTP) has been adapted to reflect the fluctuations in the electricity market. Load scheduling method encourages the users to adopt smart usage of electricity. The method aims at scheduling the appliances based on their need, hence to optimize the energy usage and to minimize the usage cost. The optimization problem for load scheduling has been solved using genetic algorithm. The load balancing approach spreads the electrical load over a time horizon in order to appropriately schedule the requests that have been rejected by the admission control, while minimizing a cost function related to the energy price. Every appliance, represented by a task has to be processed in a certain time window according to power load, preemption state and priority characteristics.

Results: Based on the assumptions of consumption patterns of the consumer from an Indian middle class scenario, an approximation of the daily power consumption pattern in the household is made and demand load profile for a day has been computed. The load scheduling algorithm is applied to the residential demand load with the target of scheduling the operation of burst loads found in the household.

Conclusion: From the results we conclude that we get a better dispersive load with our proposed scheduling method which in turn will definitely optimize the usage cost in a real time environment.