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Real-Time Driver and Traffic Data Integration for Enhanced Road Safety
Traditional roadway safety assessment heavily relies on historical crash data, overlooking real-time factors such as driver behaviors and current traffic conditions and lacking forward-looking analysis for predicting future trends. This study introduces an enhanced innovative data fusion method based on the safe route mapping (SRM) methodology with combined use of historical crash data and real-ti...Show More
Kernelytics: Multispectral Drone Imagery and Deep Learning for Early Corn Assessment
Oliver Aplin;Kavya Famolari;Sophia Liu;Bhaumik Mehta;Max Xiong;Michael Mesham;Mohsen Jafari
2023 IEEE MIT Undergraduate Research Technology Conference (URTC)
Year: 2023 | Conference Paper |
Rising pressures from climate change and population growth have prompted farmers to explore modern technologies, such as drones and artificial intelligence to optimize conventional and manual crop monitoring practices. We present a new algorithm, Kernelytics, to efficiently assess corn fields early in the season, producing more optimal yields, allocating resources more efficiently, and identifying...Show More
Accessible Framework for Automation in Precision Agriculture Leveraging Boston Dynamics' SPOT
Anthony Boyle;Rebecca Cui;William Dougherty;Ryan Lalani;Apurva Parasher;Mohsen Jafari;Patrick Rudawski
2023 IEEE MIT Undergraduate Research Technology Conference (URTC)
Year: 2023 | Conference Paper |
With the coming of the fourth agricultural revolution necessitating that farmers implement new technology to keep pace in an ever-expanding industry, there is a growing need for accessible means of automation that enable them to streamline farm management. Proposing a framework to meet this need, this research outlines the applications of Boston Dynamics' SPOT in precision agriculture. In evaluati...Show More
Probabilistic Integration of Demand Flexibilities in a Renewable Energy-Assisted Community Network
2023 IEEE PES GTD International Conference and Exposition (GTD)
Year: 2023 | Conference Paper |
This paper proposes a novel decision-making tool aiding community operators in optimally procuring their energy needs from available supply sources while incorporating potential demand-side flexibilities. The supply sources include community-operated solar plants, wind turbines, and the utility grid. Two flexible load types are modeled, that are optimally rescheduled and energized through the prop...Show More
Consumers' Willingness to Invest in Smart Home Technologies Using Machine Learning: A Survey-Based Analysis in Qatar
Taha J. Alhindi;Farhad Angizeh;Ammar Abulibdeh;Mohsen A. Jafari
2023 IEEE PES GTD International Conference and Exposition (GTD)
Year: 2023 | Conference Paper |
This paper investigates the consumers' willingness to invest in smart home technologies and the savings they expect by using machine learning. Data is gathered using questionnaires from 2,014 consumers who participated in a smart home technology-related survey in Qatar. Variable importance ranking based on decision tree models is carried out to identify the most critical questions in the survey an...Show More
Flexibility Sources for Local Distribution Operators
2023 IEEE Power & Energy Society General Meeting (PESGM)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
This paper proposes an integrated framework that unifies many flexibility sources within the context of local distribution operators (LDOs) that are ranging from single-node to multi-node operators. The proposed framework aids the operators in recognizing flexibility sources within a given system application by decomposing a generic power flow-based model into semantically meaningful blocks. Furth...Show More
Energy storage is inherently a flexible asset that can be used to reduce renewable energy curtailment and the congestion at its host network, enhance system resilience, and provide ancillary services at peak times. But the cost of technology still hampers the large-scale adoption of storage in power distribution networks. With EV parking lots included in its asset portfolio, a city can take advant...Show More
Analysis of the Optimal Adjustment Frequency for a Dual-Axis Solar Tracker
Nicholas Gibson;Adham Ibrahim;Samuel Lihn;Jenna Mullin;Mohsen Jafari;Max Powers;Patrick Rudawski;Yufei Huang
2022 IEEE MIT Undergraduate Research Technology Conference (URTC)
Year: 2022 | Conference Paper |
With the rising need for clean energy around the world, sources of clean energy must be improved upon to increase their efficiency and meet global demands. This project aims to investigate an improvement to solar panel efficiency through the construction of a dual-axis solar tracker equipped with light sensors and an accompanying robotic light source that can simulate the motion of the Sun. The pe...Show More
Using Dual-Axis Autonomous Solar Tracking to Maximize Solar Panel Power Output
Anshul Chandaliya;Griffin Forminard;Brendan Glennon;Katherine Zhou;Yufei Huang;Max Powers;Patrick Rudawski;Mohsen Jafari;Cole Jenkins
2022 IEEE MIT Undergraduate Research Technology Conference (URTC)
Year: 2022 | Conference Paper |
Recent global pushes for sustainability have resulted in advances in the development and distribution of green technologies. While solar panels have largely dominated the green energy landscape, their inherent inefficiencies invite technological improvements. To address this real-world problem, this project aimed to create a dual-axis solar panel with autonomous solar tracking capabilities. When t...Show More
Data-Driven Optimization for Dynamic Shortest Path Problem Considering Traffic Safety
Shan Jiang;Yilun Zhang;Ran Liu;Mohsen Jafari;Mohamed Kharbeche
Traffic congestion is an inescapable problem that frustrates drivers in megacities. Although there is hardly a way to eliminate the congestion, it is possible to mitigate the impact through predictive methods. This paper develops a data-driven optimization approach for the dynamic shortest path problems (DSPP), considering traffic safety for urban navigations. The dynamic risk scores and travel ti...Show More
The proliferation of renewable distributed energy resources and transportation electrification has created new challenges for the utilities in integrating these new technologies. Consequently, the utilities and electric distribution companies need to adapt their current business models to maintain service reliability, while higher granular data scarcity hinders accurate decision-making processes. ...Show More
A Distributed Multi-Agent Reinforcement Learning With Graph Decomposition Approach for Large-Scale Adaptive Traffic Signal Control
With the emerging connected-vehicle technologies and smart roadways, the need for intelligent adaptive traffic signal controls (ATSC) is more than ever before. This paper first proposes an Accumulated Exponentially Weighted Waiting Time-based Adaptive Traffic Signal Control (AEWWT-ATSC) model to calculate priorities of roadways for signal scheduling. As the size of the traffic network grows, it ad...Show More
Safe Route Mapping of Roadways Using Multiple Sourced Data
Shan Jiang;Mohsen Jafari;Mohamed Kharbeche;Mohammad Jalayer;Khalifa N. Al-Khalifa
The use of systematic techniques with historical crash data and qualitative measures has long been a common practice to identify the problematic road features and develop countermeasures to mitigate the crash risk in crash-prone locations. This paper proposes a novel approach, Safe Route Mapping (SRM) model that integrates crash-based estimates with conflict risks computed from driver-based data t...Show More
Immunization of mission-critical facilities such as hospitals and first responders against power outages is crucial for the operators due to their significant value of the lost load, affecting citizens' lives. This paper proposes a novel evaluating framework which enables facility operators to efficiently size and optimally dispatch their behind-the-meter energy storage systems (BTM-ESS) for resil...Show More
On Evaluation of Onsite Energy Storage for Various End-Use Facilities with Utility Bill Management, Arbitrage, and Frequency Regulation Opportunities
2021 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)
Year: 2021 | Conference Paper |
Cited by: Papers (3)
This paper proposes a comprehensive evaluating framework that enables facility operators to optimally size and dispatch their onsite energy storage systems (ESS) that might be operated as either standalone or integrated solar-plus-storage systems. The proposed model is developed on an energy procurement-based model with a mixed-integer linear programming (MILP) format, wherein the potential energy...Show More
Techno-Economic Analysis and Optimization of a Microgrid Considering Demand-Side Management
Seyyed Danial Nazemi;Khashayar Mahani;Ali Ghofrani;Mahraz Amini;Burcu E. Kose;Mohsen A. Jafari
2020 IEEE Texas Power and Energy Conference (TPEC)
Year: 2020 | Conference Paper |
Cited by: Papers (16)
The control and management of power demand and supply become very crucial due to the penetration of renewables in the electricity networks and energy demand increase in residential and commercial sectors. In this paper, a new approach is presented to bridge the gap between Demand-Side Management (DSM) and microgrid (MG) portfolio, sizing, and placement optimization. Although DSM helps customers to...Show More
An Automated Cluster-Based Approach for Asset Rescheduling in Building Communities
2020 IEEE Texas Power and Energy Conference (TPEC)
Year: 2020 | Conference Paper |
Cited by: Papers (2)
The imbalance between load demand and power generation and high peak loads in the smart grid become a big concern for utility companies. Increasing the flexibility of the grid by using innovative demand response programs can improve the quality of the power grid and reduce the peak demand. In this paper, we propose a cluster-based approach for building assets rescheduling in a smart building commu...Show More
Economic and Operational Evaluation of PV and CHP combined with Energy Storage Systems considering Energy and Regulation Markets
Khashavar Mahani;Maryam Arabzadeh Jamali;Seyyed Danial Nazemi;Mohsen A. Jafari
2020 IEEE Texas Power and Energy Conference (TPEC)
Year: 2020 | Conference Paper |
Cited by: Papers (7)
The efficient and clean energy utilization paradigm has proved to be a realistic and economical solution to reduce greenhouse gas emissions and increase the efficiency of the energy network. Recently, more projects have been focused on Distributed Energy Resources (DERs) including photovoltaic (PV) panel, combined heat and power (CHP), fuel-cell (FC), and energy storage systems, due to their capab...Show More
This paper aims at co-optimizing day-ahead operation schedules of distributed energy resources (DER) in a coordinated microgrids (MG) cluster to enhance resiliency. The proposed model strategically integrates the potential flexibility provided by the DERs in neighboring MGs, while capturing the joint portfolio flexibilities on an hourly basis scheduling scheme. In this context, the proposed optimi...Show More
Joint Optimization of Operation and Maintenance Policies for Solar-Powered Microgrids
Khashayar Mahani;Zhenglin Liang;Ajith Kumar Parlikad;Mohsen A. Jafari
In a solar-powered microgrid (MG), the optimal maintenance strategy is influenced by the downtime cost of the photovoltaic (PV) system, which in turn depends on the operation PV within the MG network. Also, the dispatch policy used in the MG will influence the economic feasibility of maintenance plans. In this paper, we present an approach for optimizing the operation and maintenance policy jointl...Show More
Solar-Powered Microgrid Capacity Planning for a General Hospital
2018 IEEE Green Energy and Smart Systems Conference (IGESSC)
Year: 2018 | Conference Paper |
Cited by: Papers (4)
This paper investigates the impact of investment budget, solar system efficiency, and project area limitation on the capacity planning, and daily operation of a microgrid (MG), which consists of photovoltaic (PV) and Energy storage systems (ESS). A general grid-connected hospital located in NJ is considered as an illustrative case study. Access to reliable, affordable and sustainable energy is ess...Show More
A Data-Driven Approach for Driving Safety Risk Prediction Using Driver Behavior and Roadway Information Data
Future roadways will have a mix of autonomous and automated vehicles with regular vehicles that require human operators. To ensure the safety of all the road users in such a network, it is necessary to enhance the performance of the present Advanced Driver Assistance System (ADAS) for lower classes of vehicles. Real-time driving safety risk prediction is an essential element of an ADAS. In this pa...Show More
Sizing methodology for combined renewable energy systems
2017 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)
Year: 2017 | Conference Paper |
In this work we develop a process to size the renewable energy system that can power a microgrid community. We begin by collecting the community's varying load, location dependent data, and commercially available generation types. According to rules of thumb and relevant physics equations, we then recommended the quantity and configuration of each generation component. Finally, we combine the desi...Show More
Integration of Demand Dynamics and Investment Decisions on Distributed Energy Resources
IEEE Transactions on Smart Grid
Cited by: Papers (14)
This research directly couples investment decisions on distributed energy resources (DERs) with demand side management (DSM) strategies that can be adopted over time by residential communities. The formulation also takes into account factors that usually contribute to long-term market variations and short-term operational volatilities. This paper uses a high resolution adaptive model (Hi-RAM) for ...Show More
A Hybrid Physics-Based and Data Driven Approach to Optimal Control of Building Cooling/Heating Systems
This work integrates a physics-based model with a data driven time-series model to forecast and optimally manage building energy. Physical characterization of the building is partially captured by a collection of zonal energy balance equations with parameters estimated using a least squares estimation (LSE) technique and data initially generated from the EnergyPlus building model. A generalized Co...Show More
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