Antonio Sanfilippo

Hamad bin Khalifa University | HBKU · Qatar Environment & Energy Research Institute

The creation of distributed energy generation that eliminates conventional differences between energy producers and consumers creates a new role called prosumer. This study aims at deploying a general ABM simulation framework to facilitate electricity exchange and demonstrate the functionality of blockchain. The simulation involved a Transactive En...

A growing number of studies suggest that climate may impact the spread of COVID-19. This hypothesis is supported by data from similar viral contagions, such as SARS and the 1918 Flu Pandemic, and corroborated by US influenza data. However, the extent to which climate may affect COVID-19 transmission rates and help modeling COVID-19 risk is still no...

Solar PV Energy Trading Market Blockchain-based: Agent-Models Community

Understanding the effect of atmospheric aerosols on the climate is a very challenging task. These small particles absorb and scatter sunlight and alter the properties of clouds in the atmosphere. They are greatly diverse in nature, size, optical and physical properties, and in their sources of emission and way of elimination. More particularly for...

Predicting solar radiation at diverse time horizons is crucial for optimizing solar energy integration, ensuring grid stability, and regulating energy markets. Two main levels of time granularity are usually recognized as requiring different treatment: solar nowcasting for predictions up to 6 h, and solar forecasting for predictions beyond 6 h. Sol...

The growing interest in decentralized production of renewables calls for new energy trade approaches. An energy blockchain platform enables a decentralized energy market, to eliminate the need of an intermediary trust entity. We proposed to explore the design of an energy blockchain platform in the Qatari context using an ABM simulation framework w...

An accurate assessment of solar radiation resources is crucial in supporting the management of solar energy-based projects. When available, high-quality ground radiometric measurements present the best data source for resource assessment and variability analysis due to their low error rate. Qatar is blessed with high solar radiation levels. However...

Multi-Criteria Decision Analysis (MCDA) is a sub-discipline of operations research that aims to solve multi-objective optimization problems by evaluating competing factors in decision-making. MCDA supports multidimensional decision-making processes through the analysis of diverse inputs at several levels of description, e.g. economic, technical, so...

This paper presents an agent-based model of innovation diffusion for Renewable Energy Technologies (RET) based on the spread of information in social networks within city neighborhoods. The resulting approach provides a methodology for capturing how RET innovation diffusion in online social networks and city neighborhood networks may jointly influ...

This paper designs and develops a Geographic Information System (GIS) and a new, yet realistic Agent-Based Modeling (ABM) simulator for Education City Community housing ECCH in Qatar to carry out energy trading in a residential neighborhood market. The methodology of simulating spatiotemporal dynamics of trading in a small market collects and analy...

The growing interest in decentralized production of renewables calls for new energy trade approaches. An energy blockchain platform enables a decentralized energy market, to eliminate the need of an intermediary trust entity. We proposed to explore the design of an energy blockchain platform in the Qatari context using an ABM simulation framework w...

Recently proposed blockchain-based LEMs use auction designs to match future demand and supply. Thus, such blockchain-based LEMs rely on accurate short-term forecasts of individual households’ energy consumption and production. Often, such accurate forecasts are simply assumed to be given. The present research tested this assumption by first evaluat...

A growing number of studies has suggested potential impacts of meteorological variables on the spread of the COVID-19 pandemic. These impacts are supported by data from similar viral contagions, such as SARS and the 1918 Flu Pandemic, and corroborated by US influenza data relative to the last decade. However, there is still limited understanding ab...

Home energy management systems (HEMSs) help manage electricity demand to optimize energy consumption and distributed renewable energy generation without compromising consumers’ comfort. HEMSs operate according to multiple criteria, including energy cost, weather conditions, load profiles, and consumer comfort. They play an increasingly ubiquitous r...

The growing interest for decentralized production of renewables calls for new energy trade approaches. An energy blockchain platform enables a decentralized energy market, eliminating the need of an intermediary trust entity. We propose to explore the design of an energy blockchain platform in the Qatari context using an ABM simulation framework wi...

With the increasing ubiquity of blockchain technologies, the opportunity has arisen for energy producers, consumers, and prosumers to trade energy without the intervention of an intermediary, using the most secure and resilient methods. Energy trade applications based on blockchain technology automate the execution of direct energy transactions usi...

In this paper, we address the household (as agent): consumer and prosumer based behaviors model in order to take optimal decisions in peer-to-peer energy (P2P) trading. Keeping in view the scenario of multiple-objective optimization problem, the proposed model considers various factors which have significant impact to optimize the energy cost like...

Multi-Criteria Decision Analysis (MCDA), an approach which defines a class of Operations Research models addressing complex problems, provides a solution to complex decision making that has been gaining momentum in the energy field. MCDA has been successfully applied to renewable energy analysis in endeavors that include evaluating the feasibility...

Multi-Criteria Decision Analysis (MCDA), an approach which defines a class of Operations Research models addressing complex problems, provides a solution to complex decision making that has been gaining momentum in the energy field. MCDA has been successfully applied to renewable energy analysis in endeavors that include evaluating the feasibility...

With the increasing ubiquity of solar energy systems, solar nowcasting is needed to redress short-term power system imbalances emerging from solar energy integration and normalize electricity markets in near real time. In this chapter, we provide an overview of the applications, solar resource data, evaluation procedures, modeling methods, and emer...

We present an agent-based model for residential model adoption of solar photovoltaic (PV) systems in the state of Qatar as a case study for the Arabian Gulf Region. Agents in the model are defined as households. The objective of the model is to evaluate PV adoption across households under diverse regulatory and incentive scenarios determined by hom...

Predicting the popularity of online content has attracted much attention in the past few years. In news rooms, for instance, journalists and editors are keen to know, as soon as possible, the articles that will bring the most traffic into their website. In this paper, we propose a new approach for predicting the popularity of news articles before t...

We present an agent-based model for residential model adoption of solar photovoltaic (PV) systems in the state of Qatar as a case study for the Arabian Gulf Region. Agents in the model are defined as households. The objective of the model is to evaluate PV adoption across households under diverse regulatory and incentive scenarios determined by hom...

Modeling the diffusion of residential solar photovoltaic (PV) systems in their social, political and economic context is crucial to help policymakers assess which policies may best support adoption. Current models of renewable energy adoption [1, 2, 3, 4] assume regulatory and incentive frameworks that do not apply to Gulf Cooperation Council (GCC)...

Modeling the diffusion of residential solar photovoltaic (PV) systems in their social, political and economic context is crucial to help policymakers assess which policies may best support adoption. Current models of renewable energy adoption [1, 2, 3, 4] assume regulatory and incentive frameworks that do not apply to Gulf Cooperation Council (GCC)...

The chapter focuses on the impact of solar energy adoption on natural gas (NG) trade and CO2 emissions in Qatar. First, we forecast electricity production to estimate the NG needed for power generation in Qatar through the next 11 years. The ensuing NG estimates are then used with national targets of solar PV adoption to evaluate NG savings 11 year...

We present an agent-based model for residential adoption of photovoltaic (PV) systems in Qatar where agents are defined as households within the Al Rayyan municipality in Doha. Each household corresponds to a villa type accommodation, which is either owned or rented. The objective of the model is to evaluate PV adoption behaviors across these two h...

We present an agent-based model for residential adoption of photovoltaic (PV) systems in Qatar where agents are defined as households within the Al Rayyan municipality in Doha. Each household corresponds to a villa type accommodation, which is either owned or rented. The objective of the model is to evaluate PV adoption behaviors across these two h...

The ability to forecast solar irradiance in near-real time is useful in managing power grid integration of renewable energy harnessed through such technologies as solar heating, photovoltaics (PV), solar thermal energy, solar architecture, and artificial photosynthesis. Solar irradiance is subject to sudden variations due to meteorological change,...

The impact of international graduate students on the enrolment of US students in advanced degree programmes has been the subject of intense debate in the last decade. Overall, arguments pro and against the view that international graduate students displace US students in the pursuit of higher degrees in science and engineering have been based on op...

The ability to forecast solar irradiance in near-real time (nowcasting) is crucial in managing the integration of solar energy in power grids. This paper focuses on minute-by-minute forecasts of the normalized clearness index, a measure of global horizontal irradiation, within a fifteen steps-ahead temporal horizon, using data collected with a radi...

Perfect power system voltage stability is not possible in practice. Generally, the power grid is continually exposed to changes in its load and operating conditions. Therefore, dynamic stability analysis is one the most important and effective elements for greater security and reliability of planning, design, operation and economic aspects of elect...

Qatar seeks to generate 2% of its electricity from solar power by 2020 (Bryden et al., 2013, REN 2015), and 20% by either 2024 (PV Insider, 2014) or 2030 (REN, 2015). Since electricity is produced almost entirely from natural gas in Qatar, these renewable energy targets introduce the prospect of natural gas savings that can be made use to increase...

We present a computational approach to modeling the intent of a communication source representing a group or an individual to engage in violent behavior. Our aim is to identify and rank aspects of radical rhetoric that are endogenously related to violent intent to predict the potential for violence as encoded in written or spoken language. We use c...

We present a computational approach to modeling the intent of a communication source representing a group or an individual to engage in violent behavior. Our aim is to identify and rank aspects of radical rhetoric that are endogenously related to violent intent to predict the potential for violence as encoded in written or spoken language. We use c...

“Gamification”, the application of gameplay to real-world problems, enables the development of human computation systems that support decision-making through the integration of social and machine intelligence. One of gamification’s major benefits includes the creation of a problem solving environment where the influence of cognitive and cultural bi...

We describe an approach to analyzing anomalies in trade data based on the identification of cluster outliers. The approach uses unsupervised machine learning methods to discover semantically coherent clusters of shipping records in large collections of trade data. Trade data with cluster annotations are then used as input to a supervised machine le...

Welcome to Seattle for the eleventh IEEE International Conference on Intelligence and Security Informatics (IEEE ISI)! We are delighted to have your participation. We hope that the conference will meet your expectations and your sojourn in Seattle will be pleasant.

The use of predictive modeling in the analysis of gene expression data can greatly accelerate the pace of scientific discovery in biomedical research by enabling in silico experimentation to test disease triggers and potential drug therapies. Techniques such as agent-based modeling and multi-agent simulations are of particular interest as they supp...

Edge consistency between models and injurious versus non-injurious combined models (data file). (XLSX)

Optimization results for model ensembles from all pretreatments (data file). (XLSX)

External validation of network model using different interaction sets. (XLSX)

Prototype code for dynamic simulations performed in the paper. (TGZ)

The ability to examine the behavior of biological systems in silico has the potential to greatly accelerate the pace of discovery in diseases, such as stroke, where in vivo analysis is time intensive and costly. In this paper we describe an approach for in silico examination of responses of the blood transcriptome to neuroprotective agents and subs...

Challenges to the security, health, and sustainable growth of our society keep escalating asymmetrically due to the growing pace of globalization and global change. The increasing velocity of information sharing, social networking, economic forces, and environmental change has resulted in a rapid increase in the number and frequency of “game-changi...

The innate immune system plays important roles in a number of disparate processes. Foremost, innate immunity is a first responder to invasion by pathogens and triggers early defensive responses and recruits the adaptive immune system. The innate immune system also responds to endogenous damage signals that arise from tissue injury. Recently it has...

Coexpression networks provide an abstraction of expression dynamics in the system. A portion of the inferred network from the blood transcriptomic data set is shown with circles representing probesets and lines the CLR relationships between them. Each heatmap represents a number of genes located at the indicated point in the network. The time cours...

Regulation of the conserved Ifit1 neighborhood in dendritic cells. RT-PCR expression of target genes included in our Ifit1 neighborhood (rows) are shown against a panel of 125 siRNA knock-downs of regulators (columns) taken from the study by Amit, et al. [13]. In the heatmap, green represents downregulation relative to control siRNA treatment and r...

Cytoscape file containing annotated macrophage, blood and brain networks. (TAR)

Local networks of conserved IFN-regulated bottleneck genes. Local networks surrounding conserved bottlenecks in macrophage (A), blood (B) and brain (C) networks are shown for the set of four putative interferon-stimulated conserved bottlenecks (green nodes), Ifi47, Tgtp, Ifit1, and Oasl2. Neighbors of these bottlenecks are colored according to the...