Cloud computing in the upstream oil & gas industry : a proposed way forward

Despite the compelling case for moving towards cloud computing, the upstream oil & gas industry faces several technical challenges—most notably, a pronounced emphasis on data security, a reliance on extremely large data sets, and significant legacy investments in information technology infrastructure—that make a full migration to the public cloud difficult at present. Private and hybrid cloud solutions have consequently emerged within the industry to yield as much benefit from cloud-based technologies as possible while working within these constraints. This paper argues, however, that the move to private and hybrid clouds will very likely prove only to be a temporary stepping stone in the industry's technological evolution. By presenting evidence from other market sectors that have faced similar challenges in their journey to the cloud, we propose that enabling technologies and conditions will probably fall into place in a way that makes the public cloud a far more attractive option for the upstream oil & gas industry in the years ahead. The paper concludes with a discussion about the implications of this projected shift towards the public cloud, and calls for more of the industry's services to be offered through cloud-based “apps.”

Synthetic rating system for railway bridge management

Railway bridges deteriorate with age. Factors such as environmental effects on different materials of a bridge, variation of loads, fatigue, etc will reduce the remaining life of bridges. Bridges are currently rated individually for maintenance and repair actions according to the structural conditions of their elements. Dealing with thousands of bridges and several factors that cause deterioration, makes the rating process extremely complicated. Current simplified but practical rating methods are not based on an accurate structural condition assessment system. On the other hand, the sophisticated but more accurate methods are only used for a single bridge or particular types of bridges. It is therefore necessary to develop a practical and accurate system which will be capable of rating a network of railway bridges. This paper introduces a new method for rating a network of bridges based on their current and future structural conditions. The method identifies typical bridges representing a group of railway bridges. The most crucial agents will be determined and categorized to criticality and vulnerability factors. Classification based on structural configuration, loading, and critical deterioration factors will be conducted. Finally a rating method for a network of railway bridges that takes into account the effects of damaged structural components due to variations in loading and environmental conditions on the integrity of the whole structure will be proposed. The outcome of this research is expected to significantly improve the rating methods for railway bridges by considering the unique characteristics of different factors and incorporating the correlation between them.

Synthetic rating system for railway bridge management

Railway bridges deteriorate with age. Factors such as environmental effects on different materials of a bridge, variation of loads, fatigue, etc. will reduce the remaining life of bridges. Dealing with thousands of bridges and several factors that cause deterioration, makes the rating process extremely complicated. Current simplified but practical methods of rating a network of bridges are not based on an accurate structural condition assessment system. On the other hand, the sophisticated but more accurate methods are only used for a single bridge or particular types of bridges. It is therefore necessary to develop a practical and accurate system, which will be capable of rating a network of railway bridges. This article introduces a new method to rate a network of bridges based on their current and future structural conditions. The method identifies typical bridges representing a group of railway bridges. The most crucial agents will be determined and categorized to criticality and vulnerability factors. Classification based on structural configuration, loading, and critical deterioration factors will be conducted. Finally a rating method for a network of railway bridges that takes into account the effects of damaged structural components due to variations in loading and environmental conditions on the integrity of the whole structure will be proposed. The outcome of this article is expected to significantly improve the rating methods for railway bridges by considering the unique characteristics of different factors and incorporating the correlation among them.

A proposed Australian industrial control system security curriculum

The security of industrial control systems in critical infrastructure is a concern for the Australian government and other nations. There is a need to provide local Australian training and education for both control system engineers and information technology professionals. This paper proposes a postgraduate curriculum of four courses to provide knowledge and skills to protect critical infrastructure industrial control systems. Our curriculum is unique in that it provides security awareness but also the advanced skills required for security specialists in this area. We are aware that in the Australian context there is a cultural gap between the thinking of control system engineers who are responsible for maintaining and designing critical infrastructure and information technology professionals who are responsible for protecting these systems from cyber attacks. Our curriculum aims to bridge this gap by providing theoretical and practical exercises that will raise the awareness and preparedness of both groups of professionals.

The cost of carbon : capital market effects of the proposed emission trading scheme (ETS)

In March 2008, the Australian Government announced its intention to introduce a national Emissions Trading Scheme (ETS), now expected to start in 2015. This impending development provides an ideal setting to investigate the impact an ETS in Australia will have on the market valuation of Australian Securities Exchange (ASX) firms. This is the first empirical study into the pricing effects of the ETS in Australia. Primarily, we hypothesize that firm value will be negatively related to a firm's carbon intensity profile. That is, there will be a greater impact on firm value for high carbon emitters in the period prior (2007) to the introduction of the ETS, whether for reasons relating to the existence of unbooked liabilities associated with future compliance and/or abatement costs, or for reasons relating to reduced future earnings. Using a sample of 58 Australian listed firms (constrained by the current availability of emissions data) which comprise larger, more profitable and less risky listed Australian firms, we first undertake an event study focusing on five distinct information events argued to impact the probability of the proposed ETS being enacted. Here, we find direct evidence that the capital market is indeed pricing the proposed ETS. Second, using a modified version of the Ohlson (1995) valuation model, we undertake a valuation analysis designed not only to complement the event study results, but more importantly to provide insights into the capital market's assessment of the magnitude of the economic impact of the proposed ETS as reflected in market capitalization. Here, our results show that the market assesses the most carbon intensive sample firms a market value decrement relative to other sample firms of between 7% and 10% of market capitalization. Further, based on the carbon emission profile of the sample firms we imply a ‘future carbon permit price’ of between AUD$17 per tonne and AUD$26 per tonne of carbon dioxide emitted. This study is more precise than industry reports, which set a carbon price of between AUD$15 to AUD$74 per tonne.

Which procurement system? Towards a universal procurement selection technique

Two approaches are described, which aid the selection of the most appropriate procurement arrangements for a building project. The first is a multi-attribute technique based on the National Economic Development Office procurement path decision chart. A small study is described in which the utility factors involved were weighted by averaging the scores of five 'experts' for three hypothetical building projects. A concordance analysis is used to provide some evidence of any abnormal data sources. When applied to the study data, one of the experts was seen to be atypical. The second approach is by means of discriminant analysis. This was found to provide reasonably consistent predictions through three discriminant functions. The analysis also showed the quality criteria to have no significant impact on the decision process. Both approaches provided identical and intuitively correct answers in the study described. Some concluding remarks are made on the potential of discriminant analysis for future research and development in procurement selection techniques.

Estimating the effects of ambient temperature on mortality : methodological challenges and proposed solutions

The health impacts of exposure to ambient temperature have been drawing increasing attention from the environmental health research community, government, society, industries, and the public. Case-crossover and time series models are most commonly used to examine the effects of ambient temperature on mortality. However, some key methodological issues remain to be addressed. For example, few studies have used spatiotemporal models to assess the effects of spatial temperatures on mortality. Few studies have used a case-crossover design to examine the delayed (distributed lag) and non-linear relationship between temperature and mortality. Also, little evidence is available on the effects of temperature changes on mortality, and on differences in heat-related mortality over time. This thesis aimed to address the following research questions: 1. How to combine case-crossover design and distributed lag non-linear models? 2. Is there any significant difference in effect estimates between time series and spatiotemporal models? 3. How to assess the effects of temperature changes between neighbouring days on mortality? 4. Is there any change in temperature effects on mortality over time? To combine the case-crossover design and distributed lag non-linear model, datasets including deaths, and weather conditions (minimum temperature, mean temperature, maximum temperature, and relative humidity), and air pollution were acquired from Tianjin China, for the years 2005 to 2007. I demonstrated how to combine the case-crossover design with a distributed lag non-linear model. This allows the case-crossover design to estimate the non-linear and delayed effects of temperature whilst controlling for seasonality. There was consistent U-shaped relationship between temperature and mortality. Cold effects were delayed by 3 days, and persisted for 10 days. Hot effects were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. It is still unclear whether spatiotemporal models using spatial temperature exposure produce better estimates of mortality risk compared with time series models that use a single site’s temperature or averaged temperature from a network of sites. Daily mortality data were obtained from 163 locations across Brisbane city, Australia from 2000 to 2004. Ordinary kriging was used to interpolate spatial temperatures across the city based on 19 monitoring sites. A spatiotemporal model was used to examine the impact of spatial temperature on mortality. A time series model was used to assess the effects of single site’s temperature, and averaged temperature from 3 monitoring sites on mortality. Squared Pearson scaled residuals were used to check the model fit. The results of this study show that even though spatiotemporal models gave a better model fit than time series models, spatiotemporal and time series models gave similar effect estimates. Time series analyses using temperature recorded from a single monitoring site or average temperature of multiple sites were equally good at estimating the association between temperature and mortality as compared with a spatiotemporal model. A time series Poisson regression model was used to estimate the association between temperature change and mortality in summer in Brisbane, Australia during 1996–2004 and Los Angeles, United States during 1987–2000. Temperature change was calculated by the current day's mean temperature minus the previous day's mean. In Brisbane, a drop of more than 3 �C in temperature between days was associated with relative risks (RRs) of 1.16 (95% confidence interval (CI): 1.02, 1.31) for non-external mortality (NEM), 1.19 (95% CI: 1.00, 1.41) for NEM in females, and 1.44 (95% CI: 1.10, 1.89) for NEM aged 65.74 years. An increase of more than 3 �C was associated with RRs of 1.35 (95% CI: 1.03, 1.77) for cardiovascular mortality and 1.67 (95% CI: 1.15, 2.43) for people aged < 65 years. In Los Angeles, only a drop of more than 3 �C was significantly associated with RRs of 1.13 (95% CI: 1.05, 1.22) for total NEM, 1.25 (95% CI: 1.13, 1.39) for cardiovascular mortality, and 1.25 (95% CI: 1.14, 1.39) for people aged . 75 years. In both cities, there were joint effects of temperature change and mean temperature on NEM. A change in temperature of more than 3 �C, whether positive or negative, has an adverse impact on mortality even after controlling for mean temperature. I examined the variation in the effects of high temperatures on elderly mortality (age . 75 years) by year, city and region for 83 large US cities between 1987 and 2000. High temperature days were defined as two or more consecutive days with temperatures above the 90th percentile for each city during each warm season (May 1 to September 30). The mortality risk for high temperatures was decomposed into: a "main effect" due to high temperatures using a distributed lag non-linear function, and an "added effect" due to consecutive high temperature days. I pooled yearly effects across regions and overall effects at both regional and national levels. The effects of high temperature (both main and added effects) on elderly mortality varied greatly by year, city and region. The years with higher heat-related mortality were often followed by those with relatively lower mortality. Understanding this variability in the effects of high temperatures is important for the development of heat-warning systems. In conclusion, this thesis makes contribution in several aspects. Case-crossover design was combined with distribute lag non-linear model to assess the effects of temperature on mortality in Tianjin. This makes the case-crossover design flexibly estimate the non-linear and delayed effects of temperature. Both extreme cold and high temperatures increased the risk of mortality in Tianjin. Time series model using single site’s temperature or averaged temperature from some sites can be used to examine the effects of temperature on mortality. Temperature change (no matter significant temperature drop or great temperature increase) increases the risk of mortality. The high temperature effect on mortality is highly variable from year to year.

A two-stage approach for generating topic models

Topic modeling has been widely utilized in the fields of information retrieval, text mining, text classification etc. Most existing statistical topic modeling methods such as LDA and pLSA generate a term based representation to represent a topic by selecting single words from multinomial word distribution over this topic. There are two main shortcomings: firstly, popular or common words occur very often across different topics that bring ambiguity to understand topics; secondly, single words lack coherent semantic meaning to accurately represent topics. In order to overcome these problems, in this paper, we propose a two-stage model that combines text mining and pattern mining with statistical modeling to generate more discriminative and semantic rich topic representations. Experiments show that the optimized topic representations generated by the proposed methods outperform the typical statistical topic modeling method LDA in terms of accuracy and certainty.

Evolutionary genetics and human assisted movement of a globally invasive pest (Russian wheat aphid : Diuraphis noxia)

This PhD study has examined the population genetics of the Russian wheat aphid (RWA, Diuraphis noxia), one of the world’s most invasive agricultural pests, throughout its native and introduced global range. Firstly, this study investigated the geographic distribution of genetic diversity within and among RWA populations in western China. Analysis of mitochondrial data from 18 sites provided evidence for the long-term existence and expansion of RWAs in western China. The results refute the hypothesis that RWA is an exotic species only present in China since 1975. The estimated date of RWA expansion throughout western China coincides with the debut of wheat domestication and cultivation practices in western Asia in the Holocene. It is concluded that western China represents the limit of the far eastern native range of this species. Analysis of microsatellite data indicated high contemporary gene flow among northern populations in western China, while clear geographic isolation between northern and southern populations was identified across the Tianshan mountain range and extensive desert regions. Secondly, this study analyzed the worldwide pathway of invasion using both microsatellite and endosymbiont genetic data. Individual RWAs were obtained from native populations in Central Asia and the Middle East and invasive populations in Africa and the Americas. Results indicated two pathways of RWA invasion from 1) Syria in the Middle East to North Africa and 2) Turkey to South Africa, Mexico and then North and South America. Very little clone diversity was identified among invasive populations suggesting that a limited founder event occurred together with predominantly asexual reproduction and rapid population expansion. The most likely explanation for the rapid spread (within two years) from South Africa to the New World is by human movement, probably as a result of the transfer of wheat breeding material. Furthermore, the mitochondrial data revealed the presence of a universal haplotype and it is proposed that this haplotype is representative of a wheat associated super-clone that has gained dominance worldwide as a result of the widespread planting of domesticated wheat. Finally, this study examined salivary gland gene diversity to determine whether a functional basis for RWA invasiveness could be identified. Peroxidase DNA sequence data were obtained for a selection of worldwide RWA samples. Results demonstrated that most native populations were polymorphic while invasive populations were monomorphic, supporting previous conclusions relating to demographic founder effects in invasive populations. Purifying selection most likely explains the existence of a universal allele present in Middle Eastern populations, while balancing selection was evident in East Asian populations. Selection acting on the peroxidase gene may provide an allele-dependent advantage linked to the successful establishment of RWAs on wheat, and ultimately their invasion potential. In conclusion, this study is the most comprehensive molecular genetic investigation of RWA population genetics undertaken to date and provides significant insights into the source and pathway of global invasion and the potential existence of a wheat-adapted genotype that has colonised major wheat growing countries worldwide except for Australia. This research has major biosecurity implications for Australia’s grain industry.

ICT shared services in the higher education sector : foundations, benefits, success factors and issues

Universities are more and more challenged by the emerging global higher education market, facilitated by advances in Information and Communication Technologies (ICT). This requires them to reconsider their mission and direction in order to function effectively and efficiently, and to be responsive to changes in their environment. In the face of increasing demands and competitive pressures, Universities like other companies, seek to continuously innovate and improve their performance. Universities are considering co-operating or sharing, both internally and externally, in a wide range of areas to achieve cost effectiveness and improvements in performance. Shared services are an effective model for re-organizing to reduce costs, increase quality and create new capabilities. Shared services are not limited to the Higher Education (HE) sector. Organizations across different sectors are adopting shared services, in particular for support functions such as Finance, Accounting, Human Resources and Information Technology. While shared services has been around for more than three decades, commencing in the 1970’s in the banking sector and then been adopted by other sectors, it is an under researched domain, with little consensus on the most fundamental issues even as basic as defining what shared services is. Moreover, the interest in shared services within Higher Education is a global phenomenon. This study on shared services is situated within the Higher Education Sector of Malaysia, and originated as an outcome resulting from a national project (2005 – 2007) conducted by the Ministry of Higher Education (MOHE) entitled "Knowledge, Information Communication Technology Strategic Plan (KICTSP) for Malaysian Public Higher Education"- where progress towards more collaborations via shared services was a key recommendation. The study’s primary objective was to understand the nature and potential for ICT shared services, in particular in the Malaysian HE sector; by laying a foundation in terms of definition, typologies and research agenda and deriving theoretically based conceptualisations of the potential benefits of shared services, success factors and issues of pursuing shared services. The study embarked on this objective with a literature review and pilot case study as a means to further define the context of the study, given the current under-researched status of ICT shared services and of shared services in Higher Education. This context definition phase illustrated a range of unaddressed issues; including a lack of common understanding of what shared services are, how they are formed, what objectives they full fill, who is involved etc. The study thus embarked on a further investigation of a more foundational nature with an exploratory phase that aimed to address these gaps, where a detailed archival analysis of shared services literature within the IS context was conducted to better understand shared services from an IS perspective. The IS literature on shared services was analysed in depth to report on the current status of shared services research in the IS domain; in particular definitions, objectives, stakeholders, the notion of sharing, theories used, and research methods applied were analysed, which provided a firmer base to this study’s design. The study also conducted a detailed content analysis of 36 cases (globally) of shared services implementations in the HE sector to better understand how shared services are structured within the HE sector and what is been shared. The results of the context definition phase and exploratory phase formed a firm basis in the multiple case studies phase which was designed to address the primary goals of this study (as presented above). Three case sites within the Malaysian HE sector was included in this analysis, resulting in empirically supported theoretical conceptualizations of shared services success factors, issues and benefits. A range of contributions are made through this study. First, the detailed archival analysis of shared services in Information Systems (IS) demonstrated the dearth of research on shared services within Information Systems. While the existing literature was synthesised to contribute towards an improved understanding of shared services in the IS domain, the areas that are yet under-developed and requires further exploration is identified and presented as a proposed research agenda for the field. This study also provides theoretical considerations and methodological guidelines to support the research agenda; to conduct better empirical research in this domain. A number of literatures based a priori frameworks (i.e. on the forms of sharing and shared services stakeholders etc) are derived in this phase, contributing to practice and research with early conceptualisations of critical aspects of shared services. Furthermore, the comprehensive archival analysis design presented and executed here is an exemplary approach of a systematic, pre-defined and tool-supported method to extract, analyse and report literature, and is documented as guidelines that can be applied for other similar literature analysis, with particular attention to supporting novice researchers. Second, the content analysis of 36 shared services initiatives in the Higher Education sector presented eight different types of structural arrangements for shared services, as observed in practice, and the salient dimensions along which those types can be usefully differentiated. Each of the eight structural arrangement types are defined and demonstrated through case examples, with further descriptive details and insights to what is shared and how the sharing occurs. This typology, grounded on secondary empirical evidence, can serve as a useful analytical tool for researchers investigating the shared services phenomenon further, and for practitioners considering the introduction or further development of shared services. Finally, the multiple case studies conducted in the Malaysian Higher Education sector, provided further empirical basis to instantiate the conceptual frameworks and typology derived from the prior phases and develops an empirically supported: (i) framework of issues and challenges, (ii) a preliminary theory of shared services success, and (iii) a benefits framework, for shared services in the Higher Education sector.

Proposed REDD+ project for the Sundarbans : legal and institutional issues

Sundarbans, a Ramsar and World Heritage site, is the largest single block of tidal halophytic mangrove forest in the world covering parts of Bangladesh and India. Natural mangroves were very common along the entire coast of Bangladesh. However, all other natural mangrove forests, including the Chakaria Sundarbans with 21,000 hectares of mangrove, have been cleared for shrimp cultivation. Against this backdrop, the Forest Department of Bangladesh has developed project design documents for a project called ‘Collaborative REDD+ Improved Forest Management (IFM) Sundarbans Project’ (CRISP) to save the only remaining natural mangrove forest of the country. This project, involving conservation of 412,000 ha of natural mangrove forests, is expected to generate, over a 30-year period, a total emissions reduction of about 6.4 million tons of CO2. However, the successful implementation of this project involves a number of critical legal and institutional issues. It may involve complex legal issues such as forest ownership, forest use rights, rights of local people and carbon rights. It may also involve institutional reforms. Ensuring good governance of the proposed project is very vital considering the failure of the Asian Development Bank (ADB) funded and Bangladesh Forest Department managed ‘Sundarbans Biodiversity Conservation Project’. Considering this previous experience, this paper suggests that a comprehensive legal and institutional review and reform is needed for the successful implementation of the proposed CRISP project. This paper argues that without ensuring local people’s rights and their participation, no project can be successful in the Sundarbans. Moreover, corruption of local and international officials may be a serious hurdle in the successful implementation of the project.

Load frequency control in a microgrid : challenges and improvements

A microgrid can span over a large area, especially in rural townships. In such cases, the distributed generators (DGs) must be controlled in a decentralized fashion, based on the locally available measurements. The main concerns are control of system voltage magnitude and frequency, which can either lead to system instability or voltage collapse. In this chapter, the operational challenges of load frequency control in a microgrid are discussed and few methods are proposed to meet these challenges. In particular, issues of power sharing, power quality and system stability are addressed, when the system operates under decentralized control. The main focus of this chapter is to provide solutions to improve the system performance in different situations. The scenarios considered are (a) when the system stability margin is low, (b) when the line impedance has a high R to X ratio, (c) when the system contains unbalanced and/or distorted loads. Also a scheme is proposed in which a microgrid can be frequency isolated from a utility grid while being capable of bidirectional power transfer. In all these cases, the use of angle droop in converter interfaced DGs is adopted. It has been shown that this results in a more responsive control action compared to the traditional frequency based droop control.

A framework for cost-aware process management : cost reporting and cost prediction

Organisations are constantly seeking efficiency gains for their business processes in terms of time and cost. Management accounting enables detailed cost reporting of business operations for decision making purposes, although significant effort is required to gather accurate operational data. Process mining, on the other hand, may provide valuable insight into processes through analysis of events recorded in logs by IT systems, but its primary focus is not on cost implications. In this paper, a framework is proposed which aims to exploit the strengths of both fields in order to better support management decisions on cost control. This is achieved by automatically merging cost data with historical data from event logs for the purposes of monitoring, predicting, and reporting process-related costs. The on-demand generation of accurate, relevant and timely cost reports, in a style akin to reports in the area of management accounting, will also be illustrated. This is achieved through extending the open-source process mining framework ProM.

Distributed low-power image processing in wireless sensor networks for intelligent video surveillance applications

Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.

Photovoltaic DC-DC module integrated converter for novel cascaded and bypass grid connection topologies - design and optimisation

Grid connected photovoltaic (PV) inverters fall into three broad categories - central, string and module integrated converters (MICs). MICs offer many advantages in performance and flexibility, but are at a cost disadvantage. Two alternative novel approaches proposed by the author - cascaded dc-dc MICs and bypass dc-dc MICs - integrate a simple non-isolated intelligent dc-dc converter with each PV module to provide the advantages of dc-ac MICs at a lower cost. A suitable universal 150 W 5 A dc-dc converter design is presented based on two interleaved MOSFET half bridges. Testing shows zero voltage switching (ZVS) keeps losses under 1 W for bi-directional power flows up to 15 W between two adjacent 12 V PV modules for the bypass application, and efficiencies over 94% for most of the operational power range for the cascaded converter application. Based on the experimental results, potential optimizations to further reduce losses are discussed.