Survey on demand side sensitivity to power quality in Ireland

Power systems require a reliable supply and good power quality. The impact of power supply interruptions is well acknowledged and well quantified. However, a system may perform reliably without any interruptions but may have poor power quality. Although poor power quality has cost implications for all actors in the electrical power systems, only some users are aware of its impact. Power system operators are much attuned to the impact of low power quality on their equipment and have the appropriate monitoring systems in place. However, over recent years certain industries have come increasingly vulnerable to negative cost implications of poor power quality arising from changes in their load characteristics and load sensitivities, and therefore increasingly implement power quality monitoring and mitigation solutions. This paper reviews several historical studies which investigate the cost implications of poor power quality on industry. These surveys are largely focused on outages, whilst the impact of poor power quality such as harmonics, short interruptions, voltage dips and swells, and transients is less well studied and understood. This paper examines the difficulties in quantifying the costs of poor power quality, and uses the chi-squared method to determine the consequences for industry of power quality phenomenon using a case study of over 40 manufacturing and data centres in Ireland.

Optimisation of the food dairy coop supply chain

In the European Union under the Common Agricultural Policy (CAP) milk production was restricted by milk quotas since 1984. However, due to recent changes in the Common Agricultural Policy (CAP), milk quotas will be abolished by 2015. Therefore, the European dairy sector will soon face an opportunity, for the first time in a generation, to expand. Numerous studies have shown that milk production in Ireland will increase significantly post quotas (Laepple and Hennessy (2010), Donnellan and Hennessy (2007) and Lips and Reider (2005)). The research in this thesis explored milk transport and dairy product processing in the Irish dairy processing sector in the context of milk quota removal and expansion by 2020. In this study a national milk transport model was developed for the Irish dairy industry, the model was used to examine different efficiency factors in milk transport and to estimate milk transport costs post milk quota abolition. Secondly, the impact of different milk supply profiles on milk transport costs was investigated using the milk transport model. Current processing capacity in Ireland was compared against future supply, it was concluded that additional milk processing capacity would not be sufficient to process the additional milk. Thirdly, the milk transport model was used to identify the least cost locations (based on transport costs) to process the additional milk supply in 2020. Finally, an optimisation model was developed to identify the optimum configuration for the Irish dairy processing sector in 2020 taking cognisance of increasing transport costs and decreasing processing costs.

Profiling side-channel attacks on cryptographic algorithms

Traditionally, attacks on cryptographic algorithms looked for mathematical weaknesses in the underlying structure of a cipher. Side-channel attacks, however, look to extract secret key information based on the leakage from the device on which the cipher is implemented, be it smart-card, microprocessor, dedicated hardware or personal computer. Attacks based on the power consumption, electromagnetic emanations and execution time have all been practically demonstrated on a range of devices to reveal partial secret-key information from which the full key can be reconstructed. The focus of this thesis is power analysis, more specifically a class of attacks known as profiling attacks. These attacks assume a potential attacker has access to, or can control, an identical device to that which is under attack, which allows him to profile the power consumption of operations or data flow during encryption. This assumes a stronger adversary than traditional non-profiling attacks such as differential or correlation power analysis, however the ability to model a device allows templates to be used post-profiling to extract key information from many different target devices using the power consumption of very few encryptions. This allows an adversary to overcome protocols intended to prevent secret key recovery by restricting the number of available traces. In this thesis a detailed investigation of template attacks is conducted, along with how the selection of various attack parameters practically affect the efficiency of the secret key recovery, as well as examining the underlying assumption of profiling attacks in that the power consumption of one device can be used to extract secret keys from another. Trace only attacks, where the corresponding plaintext or ciphertext data is unavailable, are then investigated against both symmetric and asymmetric algorithms with the goal of key recovery from a single trace. This allows an adversary to bypass many of the currently proposed countermeasures, particularly in the asymmetric domain. An investigation into machine-learning methods for side-channel analysis as an alternative to template or stochastic methods is also conducted, with support vector machines, logistic regression and neural networks investigated from a side-channel viewpoint. Both binary and multi-class classification attack scenarios are examined in order to explore the relative strengths of each algorithm. Finally these machine-learning based alternatives are empirically compared with template attacks, with their respective merits examined with regards to attack efficiency.