Design Concept for a Failover Mechanism in Distributed SDN Controllers

Software defined networking allows the separation of the control plane and data plane in networking. It provides scalability, programmability, and centralized control. It will use these traits to reach ubiquitous connectivity. Like all concepts software defined networking does not offer these advantages without a cost. By utilizing a centralized controller, a single point of failure is created. To address this issue, this paper proposes a distributed controller failover. This failover will provide a mechanism for recovery when controllers are not located in the same location. This failover mechanism is based on number of hops from orphan nodes to the controller in addition to the link connection. This mechanism was simulated in Long Term Evolution telecommunications architecture

On Idle Energy Consumption Minimization in Production: Industrial Example and Mathematical Model

This paper, inspired by a real production process of steel hardening, investigates a scheduling problem to minimize the idle energy consumption of machines. The energy minimization is achieved by switching a machine to some power-saving mode when it is idle. For the steel hardening process, the mode of the machine (i.e., furnace) can be associated with its inner temperature. Contrary to the recent methods, which consider only a small number of machine modes, the temperature in the furnace can be changed continuously, and so an infinite number of the power-saving modes must be considered to achieve the highest possible savings. To model the machine modes efficiently, we use the concept of the energy function, which was originally introduced in the domain of embedded systems but has yet to take roots in the domain of production research. The energy function is illustrated with several application examples from the literature. Afterward, it is integrated into a mathematical model of a scheduling problem with parallel identical machines and jobs characterized by release times, deadlines, and processing times. Numerical experiments show that the proposed model outperforms a reference model adapted from the literature.Comment: Accepted to 9th International Conference on Operations Research and Enterprise Systems (ICORES 2020

Supporting group maintenance through prognostics-enhanced dynamic dependability prediction

Condition-based maintenance strategies adapt maintenance planning through the integration of online condition monitoring of assets. The accuracy and cost-effectiveness of these strategies can be improved by integrating prognostics predictions and grouping maintenance actions respectively. In complex industrial systems, however, effective condition-based maintenance is intricate. Such systems are comprised of repairable assets which can fail in different ways, with various effects, and typically governed by dynamics which include time-dependent and conditional events. In this context, system reliability prediction is complex and effective maintenance planning is virtually impossible prior to system deployment and hard even in the case of condition-based maintenance. Addressing these issues, this paper presents an online system maintenance method that takes into account the system dynamics. The method employs an online predictive diagnosis algorithm to distinguish between critical and non-critical assets. A prognostics-updated method for predicting the system health is then employed to yield well-informed, more accurate, condition-based suggestions for the maintenance of critical assets and for the group-based reactive repair of non-critical assets. The cost-effectiveness of the approach is discussed in a case study from the power industry

Assisting Inhabitants of Residential Homes with Management of Their Energy Consumption

Although there are already a range of energy monitoring and automation systems available in the market that target residential homes, mostly with the aim of reducing their total energy consumption, very few of these systems are directly concerned with how those energy savings are actually made. As such, these systems do not provide tools that would allow users to make intelligent decisions about their energy usage strategies, and encourage them to change their energy use behaviour. In this paper we describe a system designed to facilitate planning and control of energy usage activities in residential homes. We also report on a user study of this system which demonstrates its potential for making energy savings possible

Development of Economic Water Usage Sensor and Cyber-Physical Systems Co-Simulation Platform for Home Energy Saving

In this thesis, two Cyber-Physical Systems (CPS) approaches were considered to reduce residential building energy consumption. First, a flow sensor was developed for residential gas and electric storage water heaters. The sensor utilizes unique temperature changes of tank inlet and outlet pipes upon water draw to provide occupant hot water usage. Post processing of measured pipe temperature data was able to detect water draw events. Conservation of energy was applied to heater pipes to determine relative internal water flow rate based on transient temperature measurements. Correlations between calculated flow and actual flow were significant at a 95% confidence level. Using this methodology, a CPS water heater controller can activate existing residential storage water heaters according to occupant hot water demand. The second CPS approach integrated an open-source building simulation tool, EnergyPlus, into a CPS simulation platform developed by the National Institute of Standards and Technology (NIST). The NIST platform utilizes the High Level Architecture (HLA) co-simulation protocol for logical timing control and data communication. By modifying existing EnergyPlus co-simulation capabilities, NIST’s open-source platform was able to execute an uninterrupted simulation between a residential house in EnergyPlus and an externally connected thermostat controller. The developed EnergyPlus wrapper for HLA co-simulation can allow active replacement of traditional real-time data collection for building CPS development. As such, occupant sensors and simple home CPS product can allow greater residential participation in energy saving practices, saving up to 33% on home energy consumption nationally

A new DC micro-grid system using renewable energy and electric vehicles for smart energy delivery

This paper proposes a new DC micro-grid system, which fully utilizes the renewable energy and electric vehicle for smart energy delivery. The proposed DC grid incorporates the AC supply module, standby energy module, renewable energy module, and storage energy module together, to execute the energy distribution. Hence, this grid system can offer a high quality power for the three types of loads, namely 110V AC single-phase output, 48V DC output, and 100V DC output. The control strategy of the grid system for performing smart energy delivery will be discussed in the full paper. The simulation results will be also given to verify the four operation modes of the grid system.published_or_final_versionThe 2010 IEEE Vehicle Power and Propulsion Conference (VPPC), Lille, France, 1-3 September 2010. In Proceedings of VPPC, 2010, p. 1-

Preprototype nitrogen supply subsystem development

The design and development of a test stand for the Nitrogen Generation Module (NGM) and a series of tests which verified its operation and performance capability are described. Over 900 hours of parametric testing were achieved. The results from this testing were then used to design an advanced NGM and a self contained, preprototype Nitrogen Supply Subsystem. The NGM consists of three major components: nitrogen generation module, pressure controller and hydrazine storage tank and ancillary components. The most important improvement is the elimination of all sealing surfaces, achieved with a total welded or brazed construction. Additionally, performance was improved by increasing hydrogen separating capability by 20% with no increase in overall packaging size

Supporting high penetrations of renewable generation via implementation of real-time electricity pricing and demand response

The rollout of smart meters raises the prospect that domestic customer electrical demand can be responsive to changes in supply capacity. Such responsive demand will become increasingly relevant in electrical power systems, as the proportion of weather-dependent renewable generation increases, due to the difficulty and expense of storing electrical energy. One method of providing response is to allow direct control of customer devices by network operators, as in the UK 'Economy 7' and 'White Meter' schemes used to control domestic electrical heating. However, such direct control is much less acceptable for loads such as washing machines, lighting and televisions. This study instead examines the use of real-time pricing of electricity in the domestic sector. This allows customers to be flexible but, importantly, to retain overall control. A simulation methodology for highlighting the potential effects of, and possible problems with, a national implementation of real-time pricing in the UK domestic electricity market is presented. This is done by disaggregating domestic load profiles and then simulating price-based elastic and load-shifting responses. Analysis of a future UK scenario with 15 GW wind penetration shows that during low-wind events, UK peak demand could be reduced by 8-11 GW. This could remove the requirement for 8-11 GW of standby generation with a capital cost of £2.6 to £3.6 billion. Recommended further work is the investigation of improved demand-forecasting and the price-setting strategies. This is a fine balance between giving customers access to plentiful, cheap energy when it is available, but increasing prices just enough to reduce demand to meet the supply capacity when this capacity is limited