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Georgios C. Christoforidis

Bio: Georgios C. Christoforidis is an academic researcher from University of Western Macedonia. The author has contributed to research in topics: Photovoltaic system & Renewable energy. The author has an hindex of 18, co-authored 104 publications receiving 980 citations. Previous affiliations of Georgios C. Christoforidis include Technological Educational Institute of Western Macedonia & Aristotle University of Thessaloniki.


Papers
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Journal ArticleDOI
TL;DR: In this paper, a comprehensive methodology for the investigation of the electricity behavior of buildings, using clustering techniques, is proposed, which is applied to the load curves of different buildings leading to the determination of an optimum clustering procedure.

90 citations

Journal ArticleDOI
TL;DR: In this paper, the influence of a soil structure composed of layers with different resistivities, both horizontally and vertically, on the inductive part of power transmission lines to buried pipelines is investigated.
Abstract: The interference of power transmission lines to buried pipelines, sharing the same rights of way, has been a research subject for many years. Especially under fault conditions, large currents and voltages are induced on the pipelines, posing a threat to operating personnel, equipment, and the integrity of the pipeline. The soil structure is an important parameter that affects the level of this interference. In this study, the influence of a soil structure composed of layers with different resistivities, both horizontally and vertically, on the inductive part of this interference is investigated. The method used to determine the inductive interference comprises finite-element calculations and standard circuit analysis. The results show that good knowledge of the soil structure is necessary in order to estimate the above interference with minimum error. Therefore, it is desirable that soil resistivity measurements are made both at adequate depths and at locations far away from the rights-of-way.

82 citations

Journal ArticleDOI
TL;DR: In this article, a hybrid method employing finite element calculations and standard circuit analysis is discussed that may be used in order to calculate the induced voltages and currents on a pipeline running in parallel to a faulted line.
Abstract: The interference of power transmission lines to nearby buried pipelines has been a research subject for many years. Especially during fault conditions, large currents and voltages are induced on the pipelines, which may pose a threat to operating personnel and equipment. In this work, a new hybrid method employing finite element calculations and standard circuit analysis is discussed that may be used in order to calculate the induced voltages and currents on a pipeline running in parallel to a faulted line. Nonparallel exposures are converted to parallel ones and dealt with similarly. The fault is assumed to be a single earth-to-ground one and outside the exposure, so that only inductive interference is considered. A specific case taken from literature is used to validate the proposed method. The results obtained are in good agreement with previously published ones. Important parameters such as the earth resistivity, location of grounding and pipeline coating resistance are evaluated, producing graphs that may be useful to engineers.

75 citations

Journal ArticleDOI
TL;DR: Results indicate that disaggregation performance is significantly improved when relying on harmonic current vectors in respect to the case with only current amplitudes, which makes the methodology potentially suitable for the new smart meters that are expected to be widely installed.

68 citations

Journal ArticleDOI
TL;DR: In this article, the interference between double circuit power lines and nearby pipelines is investigated and the influence of some important parameters, such as the phase shift and the different loading between the two circuits, the unbalanced loading and the phase sequence, are revealed.

63 citations


Cited by
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Journal Article
TL;DR: A detailed review of the education sector in Australia as in the data provided by the 2006 edition of the OECD's annual publication, 'Education at a Glance' is presented in this paper.
Abstract: A detailed review of the education sector in Australia as in the data provided by the 2006 edition of the OECD's annual publication, 'Education at a Glance' is presented. While the data has shown that in almost all OECD countries educational attainment levels are on the rise, with countries showing impressive gains in university qualifications, it also reveals that a large of share of young people still do not complete secondary school, which remains a baseline for successful entry into the labour market.

2,141 citations

Book ChapterDOI
06 Jan 2000
TL;DR: Methods of numerical integration will lead you to always think more and more, and this book will be always right for you.
Abstract: Want to get experience? Want to get any ideas to create new things in your life? Read methods of numerical integration now! By reading this book as soon as possible, you can renew the situation to get the inspirations. Yeah, this way will lead you to always think more and more. In this case, this book will be always right for you. When you can observe more about the book, you will know why you need this.

784 citations

Journal ArticleDOI
TL;DR: The conclusions drawn in this review could facilitate future micro-scale changes of energy use for a particular building through the appropriate retrofit and the inclusion of renewable energy technologies and paves an avenue to explore potential in macro-scale energy-reduction with consideration of customer demands.
Abstract: A recent surge of interest in building energy consumption has generated a tremendous amount of energy data, which boosts the data-driven algorithms for broad application throughout the building industry. This article reviews the prevailing data-driven approaches used in building energy analysis under different archetypes and granularities, including those methods for prediction (artificial neural networks, support vector machines, statistical regression, decision tree and genetic algorithm) and those methods for classification (K-mean clustering, self-organizing map and hierarchy clustering). The review results demonstrate that the data-driven approaches have well addressed a large variety of building energy related applications, such as load forecasting and prediction, energy pattern profiling, regional energy-consumption mapping, benchmarking for building stocks, global retrofit strategies and guideline making etc. Significantly, this review refines a few key tasks for modification of the data-driven approaches in the context of application to building energy analysis. The conclusions drawn in this review could facilitate future micro-scale changes of energy use for a particular building through the appropriate retrofit and the inclusion of renewable energy technologies. It also paves an avenue to explore potential in macro-scale energy-reduction with consideration of customer demands. All these will be useful to establish a better long-term strategy for urban sustainability.

447 citations

01 Jan 2018
TL;DR: The feasibility of mitigation and adaptation options, and the enabling conditions for strengthening and implementing the systemic changes, are assessed in this article, where the authors consider the global response to warming of 1.5oC comprises transitions in land and ecosystem, energy, urban and infrastructure, and industrial systems.
Abstract: The global response to warming of 1.5oC comprises transitions in land and ecosystem, energy, urban and infrastructure, and industrial systems. The feasibility of mitigation and adaptation options, and the enabling conditions for strengthening and implementing the systemic changes, are assessed in this chapter.

272 citations

Journal ArticleDOI
TL;DR: An overview of AI methods utilised for DR applications is provided, based on a systematic review of over 160 papers, 40 companies and commercial initiatives, and 21 large-scale projects, where AI methods have been used for energy DR.
Abstract: Recent years have seen an increasing interest in Demand Response (DR) as a means to provide flexibility, and hence improve the reliability of energy systems in a cost-effective way. Yet, the high complexity of the tasks associated with DR, combined with their use of large-scale data and the frequent need for near real-time de-cisions, means that Artificial Intelligence (AI) and Machine Learning (ML) — a branch of AI — have recently emerged as key technologies for enabling demand-side response. AI methods can be used to tackle various challenges, ranging from selecting the optimal set of consumers to respond, learning their attributes and pref-erences, dynamic pricing, scheduling and control of devices, learning how to incentivise participants in the DR schemes and how to reward them in a fair and economically efficient way. This work provides an overview of AI methods utilised for DR applications, based on a systematic review of over 160 papers, 40 companies and commercial initiatives, and 21 large-scale projects. The papers are classified with regards to both the AI/ML algorithm(s) used and the application area in energy DR. Next, commercial initiatives are presented (including both start-ups and established companies) and large-scale innovation projects, where AI methods have been used for energy DR. The paper concludes with a discussion of advantages and potential limitations of reviewed AI techniques for different DR tasks, and outlines directions for future research in this fast-growing area.

251 citations