Antonio Sanfilippo

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

The escalation of the global population has accelerated the demand for sustainable energy sources such as bioethanol. Traditionally, bioethanol was obtained by the fermentation of sugar from agricultural crops and grains. However, this technique creates serious threats on the global food supplies, thus hindering the commercial production of bioetha...

A long-term regional solar energy assessment improves decision-making processes for the selection of the best solar energy technology and helps understand how to define focused policies and investments. This study presents long-term solar resource monthly maps for Qatar. The availability of solar radiation throughout the country has been mapped her...

Distributed energy generation disrupts traditional energy markets by blurring the line between producers and consumers and enabling the emerging prosumers to trade energy in per-to-peer transactions. Blockchain technology automates peer-to-peer energy trades in a distributed database architecture that achieves security and cost-effectiveness using...

This paper describes a peer-to-peer (P2P) energy trading market framework based on game theory and agent-based modeling (ABM) that enables owners of photovoltaic (PV) systems to sell the electricity they produce to neighbors and the grid. Energy is traded at a rate determined by local energy producers and consumers. The energy price is dynamic and...

Soiling of photovoltaic (PV) modules is a major issue due to its critical impact on PV performance and reliability, especially in the desert and arid regions such as the state of Qatar. Soiling frequently results in a severe reduction in PV power generation, which drastically affects the economical profitability of the PV plant, and therefore, must...

The future of solar energy in Qatar is evolving steadily. Hence, high-quality spatial solar radiation data is of the uttermost requirement for any planning and commissioning of solar technology. Generally, two types of solar radiation data are available: satellite data and ground observations. Satellite solar radiation data is developed by the phys...

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...

Peer-to-peer (P2P) energy trading has gained significant importance in recent years due to the growing energy needs worldwide. To ensure the effective and efficient implementation of P2P energy trading, it is necessary to analyze the concept from multiple dimensions. This study aims to investigate the challenges that may hinder the smooth flow of P...

Escalation of the global population has accelerated the demand for sustainable energy sources such as bioethanol. Traditionally, bioethanol has been produced using fossil fuels, which are non-renewable, non-sustainable, and not eco-friendly. Thus, there is a need to develop new technologies and low-cost raw materials in order to ensure that bioetha...

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

This paper describes the development of a co-simulation of electricity distribution networks and blockchain-based for a transactive energy marketplace (TEM) framework for housing community. The venue used in this work as case study is the Education City Community Housing ECCH located in Doha, Qatar. First, we process the grid data for the purpose o...

The Fixed Set Search (FSS) is a novel metaheuristic that adds a learning mechanism to the Greedy Randomized Adaptive Search Procedure (GRASP). In recent publications, its efficiency has been shown on different types of combinatorial optimization problems like routing, machine scheduling and covering. In this paper the FSS is adapted to multi-object...

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...

The COVID-19 impacts go beyond healthcare systems as they also challenge global markets and society. A comprehensive knowledge involving the elements to contain the virus is fundamental for properly planning and implementing a quick response to the problems faced worldwide. Learning to coexist with the COVID-19 pandemic has become part of our daily...

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...