A smart load appliance application using a single compressor fridge-freezer to support grid operations

This paper describes a fridge-freezer smart load model, which responds to external signals from the wholesale electricity market to support grid operations while switching the fridge-freezer on and off to maintain optimum operations for the owner. The key parameters of the model are the appliance dimensions, thermal mass, the fridge and freezer thermal time constants and the compressor power consumption. The model demonstrates that control strategies help to minimise load at times when the grid is under stress from high demand, and shift some load to a lower wholesale price or when there is excess renewable power. Three control strategies are proposed, based on peak shaving and valley filling, price signals and wind availability.

Assessment of Domestic Load Suitable for Smart Consumer Load Participation

This study characterizes the domestic loads suitable to participate in the load participation scheme to make the power system more carbon and economically efficient by shifting the electricity demand profile towards periods when there is plentiful renewable in-feed.

A series of experiments have been performed on a common fridge-freezer, both completely empty and half full. The results presented are ambient temperature, temperature inside the fridge, temperature inside the drawer of the fridge, temperature inside the freezer, thermal time constants, power consumption and electric energy consumed.

The thermal time constants obtained clearly demonstrate the potential of such refrigeration load for Smart Customer Load Participation.

Evidence reasoning for event inference in smart transport video surveillance

In this paper we present a new event recognition framework, based on the Dempster-Shafer theory of evidence, which combines the evidence from multiple atomic events detected by low-level computer vision analytics. The proposed framework employs evidential network modelling of composite events. This approach can effectively handle the uncertainty of the detected events, whilst inferring high-level events that have semantic meaning with high degrees of belief. Our scheme has been comprehensively evaluated against various scenarios that simulate passenger behaviour on public transport platforms such as buses and trains. The average accuracy rate of our method is 81% in comparison to 76% by a standard rule-based method.

An analysis of implied volatility jump dynamics: Novel functional data representation in crude oil markets

The predominant fear in capital markets is that of a price spike. Commodity markets differ in that there is a fear of both upward and down jumps, this results in implied volatility curves displaying distinct shapes when compared to equity markets. The use of a novel functional data analysis (FDA) approach, provides a framework to produce and interpret functional objects that characterise the underlying dynamics of oil future options. We use the FDA framework to examine implied volatility, jump risk, and pricing dynamics within crude oil markets. Examining a WTI crude oil sample for the 2007–2013 period, which includes the global financial crisis and the Arab Spring, strong evidence is found of converse jump dynamics during periods of demand and supply side weakness. This is used as a basis for an FDA-derived Merton (1976) jump diffusion optimised delta hedging strategy, which exhibits superior portfolio management results over traditional methods.

Secure Communications in Smart Grid: Networking and Protocols

The key attributes of a smarter power grid include: pervasive interconnection of smart devices; extensive data generation and collection; and rapid reaction to events across a widely dispersed physical infrastructure. Modern telecommunications technologies are being deployed across power systems to support these monitoring and control capabilities. To enable interoperability, several new communications protocols and standards have been developed over the past 10 to 20 years. These continue to be refined, even as new systems are rolled out.

This new hyper-connected communications infrastructure provides an environment rich in sub-systems and physical devices that are attractive to cyber-attackers. Indeed, as smarter grid operations become dependent on interconnectivity, the communications network itself becomes a target. Consequently, we examine cyber-attacks that specifically target communications, particularly state-of-the-art standards and protocols. We further explore approaches and technologies that aim to protect critical communications networks against intrusions, and to monitor for, and detect, intrusions that infiltrate Smart Grid systems.

Implementation Experiences from Smart Grid Security Applications and Outlook on Future Research

Experiences from smart grid cyber-security incidents in the past decade have raised questions on the applicability and effectiveness of security measures and protection mechanisms applied to the grid. In this chapter we focus on the security measures applied under real circumstances in today’s smart grid systems. Beginning from real world example implementations, we first review cyber-security facts that affected the electrical grid, from US blackout incidents, to the Dragonfly cyber-espionage campaign currently focusing on US and European energy firms. Provided a real world setting, we give information related to energy management of a smart grid looking also in the optimization techniques that power control engineers perform into the grid components. We examine the application of various security tools in smart grid systems, such as intrusion detection systems, smart meter authentication and key management using Physical Unclonable Functions, security analytics and resilient control algorithms. Furthermore we present evaluation use cases of security tools applied on smart grid infrastructure test-beds that could be proved important prior to their application in the real grid, describing a smart grid intrusion detection system application and security analytics results. Anticipated experimental results from the use-cases and conclusions about the successful transitions of security measures to real world smart grid operations will be presented at the end of this chapter.

Electric vehicles and opportunities to displace tailgate emissions using Smart Charging controls

Under the European Union Renewable Energy Directive each Member State is mandated to ensure that 10% of transport energy (excluding aviation and marine transport) comes from renewable sources by 2020. The Irish Government intends to achieve this target with a number of policies including ensuring that 10% of all vehicles in the transport fleet are powered by electricity by 2020. This paper investigates the impact of the 10% electric vehicle target in Ireland in 2020 using a dynamic programming based long term generation expansion planning model. The model developed optimizes power dispatch using hourly electricity demand curves up to 2020, while incorporating generator characteristics and certain operational requirements such as energy not served and loss of load probability while satisfying constraints on environmental emissions, fuel availability and generator operational and maintenance costs. Two distinct scenarios are analysed based on a peak and off-peak charging regimes in order to simulate the effects of the electric vehicles charging in 2020. The importance and influence of the charging regimes on the amount of energy used and tailgate emissions displaced is then determined.

A methodology to analyse the impact of offshore wind forecasting error on electricity markets

Currently wind power is dominated by onshore wind farms in the British Isles, but both the United Kingdom and the Republic of Ireland have high renewable energy targets, expected to come mostly from wind power. However, as the demand for wind power grows to ensure security of energy supply, as a potentially cheaper alternative to fossil fuels and to meet greenhouse gas emissions reduction targets offshore wind power will grow rapidly as the availability of suitable onshore sites decrease. However, wind is variable and stochastic by nature and thus difficult to schedule. In order to plan for these uncertainties market operators use wind forecasting tools, reserve plant and ancillary service agreements. Onshore wind power forecasting techniques have improved dramatically and continue to advance, but offshore wind power forecasting is more difficult due to limited datasets and knowledge. So as the amount of offshore wind power increases in the British Isles robust forecasting and planning techniques are even more critical. This paper presents a methodology to investigate the impacts of better offshore wind forecasting on the operation and management of the single wholesale electricity market in the Republic of Ireland and Northern Ireland using PLEXOS for Power Systems. © 2013 IEEE.

Reductive photocatalysis and smart inks

Semiconductor-sensitised photocatalysis is a well-established and growing area of research, innovation and commercialisation; the latter being mostly limited to the use of TiO2 as the semiconductor. Most of the work on semiconductor photocatalytic systems uses oxygen as the electron acceptor and explores a wide range of electron donors; such systems can be considered to be examples of oxidative photocatalysis, OP. OP underpins most current examples of commercial self-cleaning materials, such as: glass, tiles, concrete, paint and fabrics. OP, and its myriad of applications, have been reviewed extensively over the years both in this journal and elsewhere. However, the ability of TiO2, and other semiconductor sensitisers, to promote reductive photocatalysis, RP, especially of dyes, is significant and, although less well-known, is of growing importance. In such systems, the source of the electrons is some easily oxidised species, such as glycerol. One recent, significant example of a RP process is with respect to photocatalyst activity indicator inks. paiis, which provide a measure of the activity of a photocatalytic film under test via the rate of change of colour of the dye in the ink coating due to irreversible RP. In contrast, by incorporating the semiconductor sensitiser in the ink, rather than outside it, it is possible to create an effective UV dosimeter, based on RP, which can be used as a sun-burn warning indicator. In the above examples the dye is reduced irreversibly, but when the photocatalyst in an ink is used to reversibly photoreduce a dye, a novel, colourimetric oxygen-sensitive indicator ink can be created, which has commercial potential in the food packaging industry. Finally, if no dye is present in the ink, and the semiconductor photocatalyst-loaded ink film coats an easily reduced substrate, such as a metal oxide film, then it can be used to reduce the latter and so, for example, clean up tarnished steel. The above are examples of smart inks, i.e. inks that are active and provide either dynamic information (such as UV dose or O2 level) or a useful function (such as tarnish removal), and all work via a RP process and are reviewed here

Assessment of the Activity of Photocatalytic Paint Using a Simple Smart Ink Designed for High Activity Surfaces

The use of an acid violet 7 (AV7) smart ink to assess the activity of photocatalytic paint is demonstrated. A linear correlation is established between the change in oxidized dye concentration, as measured by diffuse reflectance, and the change in the green component of the RGB color values, obtained using a portable hand-held scanner, suggesting that such tests can be monitored easily using an inexpensive piece of hand-held office equipment, as opposed to an expensive lab-based instrument, such as a diffuse reflectance UV/vis spectrophotometer. The bleaching of the AV7 follows first order kinetics, at a rate that is linearly dependent upon the UVA irradiance (0.30–3.26 mW cm–2). A comparison of relative rate of bleaching of the AV7 ink with the relative rate of removal of NOx, as determined using the ISO test (ISO 22197-1:2007), established a linear relationship between the two sets of results and the relevance of this correlation is discussed briefly.

A smart ink for the assessment of low activity photocatalytic surfaces

The azo dye, basic blue 66 (BB66) is used in a photocatalyst activity indicator ink (paii) to assess the activity of low activity photocatalytic surfaces, such as commercial photocatalytic tiles and silicone contaminated self-cleaning glass. The BB66 paii is shown to respond much faster than a previously reported, resazurin (Rz) based paii, i.e. the use of a BB66 paii on low activity self-cleaning tiles was found to be >6 times faster than the Rz paii. The BB66 paii is also shown to be effective at assessing the activity of piece of commercial self-cleaning glass contaminated with a coating of silicone, on which the Rz ink, in contrast, failed to show any significant change in colour over the same time period.

Smart, Reusable labels for assessing self-cleaning films

Novel, reversible (reusable) photocatalyst activity indicator labels, which undergo a rapid colour change when in contact with a photocatalytic film via the photoreduction of methylene blue contained within the label’s adhesive, are explored as a method for assessing the activity of self-cleaning glass in situ and the laboratory, using digital photography.