The Grid 2: Blueprint for a New Computing Infrastructure

A communication infrastructure is an essential part to the success of the emerging smart grid. A scalable and pervasive communication infrastructure is crucial in both construction and operation of a smart grid. In this paper, we present the background and motivation of communication infrastructures in smart grid systems. We also summarize major requirements that smart grid communications must meet. From the experience of several industrial trials on smart grid with communication infrastructures, we expect that the traditional carbon fuel based power plants can cooperate with emerging distributed renewable energy such as wind, solar, etc, to reduce the carbon fuel consumption and consequent green house gas such as carbon dioxide emission. The consumers can minimize their expense on energy by adjusting their intelligent home appliance operations to avoid the peak hours and utilize the renewable energy instead. We further explore the challenges for a communication infrastructure as the part of a complex smart grid system. Since a smart grid system might have over millions of consumers and devices, the demand of its reliability and security is extremely critical. Through a communication infrastructure, a smart grid can improve power reliability and quality to eliminate electricity blackout. Security is a challenging issue since the on-going smart grid systems facing increasing vulnerabilities as more and more automation, remote monitoring/controlling and supervision entities are interconnected.

https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1315&context=electricalengineeringfacpub

A Survey on Smart Grid CommunicationInfrastructures: Motivations, Requirements andChallenges

Multiagent Systems is the title of a collection of papers dedicated to surveying specific themes of Multiagent Systems (MAS) and Distributed Artificial Intelligence (DAI). All of them authored by leading researchers of this dynamic multidisciplinary field.

/pdf/multiagent-systems-a-modern-approach-to-distributed-5fon0donq1.pdf

Multiagent systems: a modern approach to distributed artificial intelligence

A smart grid is a new form of electricity network with high fidelity power-flow control, self-healing, and energy reliability and energy security using digital communications and control technology. To upgrade an existing power grid into a smart grid, it requires significant dependence on intelligent and secure communication infrastructures. It requires security frameworks for distributed communications, pervasive computing and sensing technologies in smart grid. However, as many of the communication technologies currently recommended to use by a smart grid is vulnerable in cyber security, it could lead to unreliable system operations, causing unnecessary expenditure, even consequential disaster to both utilities and consumers. In this paper, we summarize the cyber security requirements and the possible vulnerabilities in smart grid communications and survey the current solutions on cyber security for smart grid communications.

/pdf/a-survey-on-cyber-security-for-smart-grid-communications-3ah12orzeu.pdf

A Survey on Cyber Security for Smart Grid Communications

Resonance conditions for a substrate-superstrate printed antenna geometry which allow for large antenna gain are presented. Asymptotic formulas for gain, beamwidth, and bandwidth are given, and the bandwidth limitation of the method is discussed. The method is extended to produce narrow patterns about the horizon, and directive patterns at two different angles.

Gain enhancement methods for printed circuit antennas

Enhancing vehicle drivers’ safety and decreasing accidents are the current new challenges in traffic safety. Vehicular ad-hoc networks (VANETs) offer improvements addressing these challenges through their frequent topology changes. More specifically, VANETs communicate via vehicle-to-vehicle (V2V) and vehicle-to-roadside networks (V2R) mainly by broadcast. However, an effective rebroadcasting protocol must be designed carefully in order to maximize the reachability and minimize the delay and number of rebroadcasts, even in congested areas. Prior work minimizes one parameter at a time, congestion or latency, at the expense of reachability and the number of rebroadcasts. However, by considering environmental factors such as the number of received messages and distance to the event location, our proposed algorithm called Dynamic Hybrid Broadcasting Protocol DHBP outperforms prior work on reachability, number of rebroadcasts and delay, in different scenarios such as congested areas. We evaluate DHBP’s performances through NS2 simulations. Simulation results show that DHBP outperforms prior work in terms of several metrics.

A Distributed Priority-Based Rebroadcasting Protocol for VANETs: Mitigating the Storm Problem

The climate of Houston, classified as a humid subtropical climate with tropical influences, makes the heating, ventilation, and air conditioning (HVAC) systems the largest electricity consumers in buildings. HVAC systems in commercial buildings are usually operated by a centralized control system and/or an energy management system based on a fixed schedule and scheduled control of a zone setpoint, which is not appropriate for many buildings with changing occupancy rates. Lately, as part of energy efficiency analysis, attention has focused on collecting and analyzing smart meters and building-related data, as well as applying supervised learning techniques, to propose new strategies to operate HVAC systems and reduce energy consumption. On the other hand, unsupervised learning techniques have been used to study the consumption information and profile characterization of different buildings after cluster analysis is performed. This paper adopts a different approach by revealing the power of unsupervised learning to cluster data and unveiling hidden patterns. In this study, we also identify energy inefficiencies after exploring the cluster results of a single building’s HVAC consumption data and building usage data as part of the energy efficiency analysis. Time series analysis and the K-means clustering algorithm are successfully applied to identify new energy-saving opportunities in a highly efficient office building located in the Houston area (TX, USA). The paper uses 1-year data from a highly efficient Leadership in Energy and Environment Design (LEED)-, Energy Star-, and Net Zero-certified building, showing a potential energy savings of 6% using the K-means algorithm. The results show that clustering is instrumental in helping building managers identify potential additional energy savings.

Smart Building Energy Inefficiencies Detection through Time Series Analysis and Unsupervised Machine Learning

In this paper we propose a technique to design compact multi-band and UWB bandpass filters based on coupled half wave resonators. The proposed design consists of the modification of a conventional parallel coupled Chebyshev bandpass filter structure by setting a very small or null coupling gap between the resonators of the center sections jointly with a very small spacing between resonators of the extremity sections. This spacing determines the performances of selected frequency bands. An ultrawideband response is accomplished by applying null spacing between all the adjacent resonators. We analysed the effect of the separation distance between the coupled lines on both the fractional bandwidth and group velocity of the filter response. The effect of the order assumed for the initial Chebyshev filter was also discussed. As an illustration of the proposed technique, we designed and measured a dual band and a tri-band filter for the frequencies covering the WiMAX/WLAN/X system bands demonstrating an excellent performance, with a fractional bandwidth covering the 40% and 100% of the FCC bandwidth respectively. The proposed technique alleviates the fabrication accuracy requirements. The designs show an optimal improvement in terms of group velocity flatness.

Design of compact wideband multi-band and ultrawideband band pass filters based on coupled half wave resonators with reduced coupling gap

Ventilation, heating and air conditioning systems are the main energy consumers in building sector Improving the energy consumption of these systems, while satisfying the occupants’ comfort, is the major concern of control and automation designers and researchers Model predictive control (MPC) methods have been widely studied in order to reduce the energy usage while enhancing the occupants’ comfort In this paper, a generalized predictive control (GPC) algorithm based on controlled auto-regressive integrated moving average is investigated for standalone ventilation systems’ control A building’s ventilation system is first modeled together with the GPC and MPC controllers Simulations have been conducted for validation purposes and are structured into two main parts In the first part, we compare the MPC with two traditional controllers, while the second part is dedicated to the comparison of the MPC against the GPC controller Simulation results show the effectiveness of the GPC in reducing the energy consumption by about 434% while providing significant indoor air quality improvement

https://www.mdpi.com/1996-1073/13/12/3246/pdf

Towards a Real-Time Predictive Management Approach of Indoor Air Quality in Energy-Efficient Buildings

In this paper, a compact parallel coupled microstrip band-pass filter (BPF) is used to design a wideband third order of the Tschebyshev elements for an unlicensed WiMAX technology. Some techniques based on the parametrical study are proposed to obtain the desired 10 % operating bandwidth filter response. The new filter is implemented on Arlon AR 1000 substrate having a relative permittivity of 10 and substrate thickness 1.1938 mm respectively. The results based on the transmission line theory approach and the commercial electromagnetic Agilent ADS and CST-MS simulators show a good agreement.

Mohamed Essaaidi

Papers

A Distributed Priority-Based Rebroadcasting Protocol for VANETs: Mitigating the Storm Problem

Smart Building Energy Inefficiencies Detection through Time Series Analysis and Unsupervised Machine Learning

Design of compact wideband multi-band and ultrawideband band pass filters based on coupled half wave resonators with reduced coupling gap

Towards a Real-Time Predictive Management Approach of Indoor Air Quality in Energy-Efficient Buildings

Study and Design of a Compact Parallel Coupled Microstrip Band-Pass Filter for a 5 GHz Unlicensed Mobile WiMAX Networks