Hanif Tayarani - Academia.edu (original) (raw)

Papers by Hanif Tayarani

Research paper thumbnail of Life Cycle Assessment of Hydrogen Transportation Pathways via Pipelines and Truck Trailers: Implications as a Low Carbon Fuel

Sustainability

Hydrogen fuel cells have the potential to play a significant role in the decarbonization of the t... more Hydrogen fuel cells have the potential to play a significant role in the decarbonization of the transportation sector globally and especially in California, given the strong regulatory and policy focus. Nevertheless, numerous questions arise regarding the environmental impact of the hydrogen supply chain. Hydrogen is usually delivered on trucks in gaseous form but can also be transported via pipelines as gas or via trucks in liquid form. This study is a comparative attributional life cycle analysis of three hydrogen production methods alongside truck and pipeline transportation in gaseous form. Impacts assessed include global warming potential (GWP), nitrogen oxide, volatile organic compounds, and particulate matter 2.5 (PM2.5). In terms of GWP, the truck transportation pathway is more energy and ecologically intensive than pipeline transportation, despite gaseous truck transport being more economical. A sensitivity analysis of pipeline transportation and life cycle inventories (LCI...

Research paper thumbnail of Optimal droop parameter adjustments for an islanded micro-grid considering unexpected perturbation in load demand In the presence of energy storages

2018 Smart Grid Conference (SGC), 2018

The growing need for islanded micro-grids has made the controlling strategies a critical requirem... more The growing need for islanded micro-grids has made the controlling strategies a critical requirement in micro-grid operation. The integration of renewable energy sources and the weak frequency response of the other types of distributed generators underlines the importance of a rigorous controlling technique. In this paper, the parameters of the well-known droop controlling method alongside the output power of the dispatchable units have been optimized in order to stabilize the frequency response of the micro-grid and minimize the cost of energy production. The proposed controlling strategy is formulated as an optimization model and is then implemented in a real-life micro-grid system considering common types of generation technologies. The General Algebraic Modelling System (GAMS) software has been employed to solve the optimization problem. The effects of the energy storage system and droop control technique is evaluated in the presence of unexpected load demand surges.

Research paper thumbnail of Evaluating Energy Systems and Optimizing Consumption in a Hospital Unit by Considering Supply-Side Scenarios

The purpose of this paper is to audit and manage electrical and thermal energy in a hospital, by ... more The purpose of this paper is to audit and manage electrical and thermal energy in a hospital, by taking into account the goals of reducing consumption and increasing the independence of energy production. Reducing energy consumption will reduce current costs as well as reduce greenhouse gas emissions. On the other hand, independence in the generation side, in addition to increasing the reliability of energy supply, in some cases leads to economic profitability for the consumer. To achieve these goals, first of all, the systems of consumption on the site should be analyzed quantitatively and qualitatively and then, subsequently, according to the results of the review of these systems, some selected scenarios are presented on the demand side. In the following, supply-side scenarios will be proposed in both cases, before and after apply demand-side scenarios, and results of each scenarios will be compared.

Research paper thumbnail of Optimal Charging of Plug-In Electric Vehicle: Considering Travel Behavior Uncertainties and Battery Degradation

Applied Sciences, 2019

The negative environmental impacts of using fossil fuel-powered vehicles underlined the need for ... more The negative environmental impacts of using fossil fuel-powered vehicles underlined the need for inventing an alternative eco-friendly transportation fleet. Plug-in electrical vehicles (PEVs) are introduced to cut the continuing increase in energy use and carbon emission of the urban mobility. However, the increased demand for mobility, and therefore energy, can create constraints on the power network which can reduce the benefits of electrification as a certain and reliable source. Thus, the rise in the use of electric vehicles needs electric grids to be able to feed the increased energy demand while the current infrastructure supports it. In this paper, we introduce a methodological framework for scheduling smart PEVs charging by considering the uncertainties and battery degradation. This framework includes an economic model for charging and discharging of PEVs which has been implemented in a 21-node sample distribution network with a wind turbine as a distributed generation (DG) ...

Research paper thumbnail of Forecasting Travel Behavior of PEV Users: A Deep Learning Approach Equipped with a Clustering Technique based on Travel Purpose

• Our proposed method is constructed based on deep learning and "Big Data" concept and to achieve... more • Our proposed method is constructed based on deep learning and "Big Data" concept and to achieve the accurate result we need as much as possible data. • The 23,514 trips dairy that includes information on individual socioeconomic status and trip characteristics are extracted from NHTS data.

Research paper thumbnail of Travel behavior and System Objectives Uncertainties In Electric Vehicle Optimal Charging

The negative environmental impacts of using fossil fuel-powered vehicles underlined the need for ... more The negative environmental impacts of using fossil fuel-powered vehicles underlined the need for inventing an alternative eco-friendly transportation fleet. Electrical vehicles (EVs) were introduced as an eligible substitute for the conventional vehicle fleet. The significant uncertainties associated with EVs usage, however, make their performance unpredictable. In this paper, we introduce a methodological framework for scheduling smart charging of EVs which considers the colligated uncertainties. Furthermore, the framework includes an ecumenical model for charging and discharging of EVs which is utilized in a 21-node sample distribution network which contains wind turbine as a Distributed Generation units. Our proposed approach extracted that the welfare of Vehicle to Grid effectuation in the network is much more beneficial than the uncoordinated mode. The simulation result indicates that smart charging effectuation is economical.

Research paper thumbnail of A Novel Electricity Price Forecasting Approach Based on Dimension Reduction Strategy and Rough Artificial Neural Networks

IEEE Transactions on Industrial Informatics

Research paper thumbnail of Deep Learning-Based Forecasting Approach in Smart Grids With Microclustering and Bidirectional LSTM Network

IEEE Transactions on Industrial Electronics

Research paper thumbnail of Charging Demand of Plug-in Electric Vehicles: Forecasting Travel Behavior Based on a Novel Rough Artificial Neural Network Approach

Journal of Cleaner Production

Research paper thumbnail of Life Cycle Assessment of Hydrogen Transportation Pathways via Pipelines and Truck Trailers: Implications as a Low Carbon Fuel

Sustainability

Hydrogen fuel cells have the potential to play a significant role in the decarbonization of the t... more Hydrogen fuel cells have the potential to play a significant role in the decarbonization of the transportation sector globally and especially in California, given the strong regulatory and policy focus. Nevertheless, numerous questions arise regarding the environmental impact of the hydrogen supply chain. Hydrogen is usually delivered on trucks in gaseous form but can also be transported via pipelines as gas or via trucks in liquid form. This study is a comparative attributional life cycle analysis of three hydrogen production methods alongside truck and pipeline transportation in gaseous form. Impacts assessed include global warming potential (GWP), nitrogen oxide, volatile organic compounds, and particulate matter 2.5 (PM2.5). In terms of GWP, the truck transportation pathway is more energy and ecologically intensive than pipeline transportation, despite gaseous truck transport being more economical. A sensitivity analysis of pipeline transportation and life cycle inventories (LCI...

Research paper thumbnail of Optimal droop parameter adjustments for an islanded micro-grid considering unexpected perturbation in load demand In the presence of energy storages

2018 Smart Grid Conference (SGC), 2018

The growing need for islanded micro-grids has made the controlling strategies a critical requirem... more The growing need for islanded micro-grids has made the controlling strategies a critical requirement in micro-grid operation. The integration of renewable energy sources and the weak frequency response of the other types of distributed generators underlines the importance of a rigorous controlling technique. In this paper, the parameters of the well-known droop controlling method alongside the output power of the dispatchable units have been optimized in order to stabilize the frequency response of the micro-grid and minimize the cost of energy production. The proposed controlling strategy is formulated as an optimization model and is then implemented in a real-life micro-grid system considering common types of generation technologies. The General Algebraic Modelling System (GAMS) software has been employed to solve the optimization problem. The effects of the energy storage system and droop control technique is evaluated in the presence of unexpected load demand surges.

Research paper thumbnail of Evaluating Energy Systems and Optimizing Consumption in a Hospital Unit by Considering Supply-Side Scenarios

The purpose of this paper is to audit and manage electrical and thermal energy in a hospital, by ... more The purpose of this paper is to audit and manage electrical and thermal energy in a hospital, by taking into account the goals of reducing consumption and increasing the independence of energy production. Reducing energy consumption will reduce current costs as well as reduce greenhouse gas emissions. On the other hand, independence in the generation side, in addition to increasing the reliability of energy supply, in some cases leads to economic profitability for the consumer. To achieve these goals, first of all, the systems of consumption on the site should be analyzed quantitatively and qualitatively and then, subsequently, according to the results of the review of these systems, some selected scenarios are presented on the demand side. In the following, supply-side scenarios will be proposed in both cases, before and after apply demand-side scenarios, and results of each scenarios will be compared.

Research paper thumbnail of Optimal Charging of Plug-In Electric Vehicle: Considering Travel Behavior Uncertainties and Battery Degradation

Applied Sciences, 2019

The negative environmental impacts of using fossil fuel-powered vehicles underlined the need for ... more The negative environmental impacts of using fossil fuel-powered vehicles underlined the need for inventing an alternative eco-friendly transportation fleet. Plug-in electrical vehicles (PEVs) are introduced to cut the continuing increase in energy use and carbon emission of the urban mobility. However, the increased demand for mobility, and therefore energy, can create constraints on the power network which can reduce the benefits of electrification as a certain and reliable source. Thus, the rise in the use of electric vehicles needs electric grids to be able to feed the increased energy demand while the current infrastructure supports it. In this paper, we introduce a methodological framework for scheduling smart PEVs charging by considering the uncertainties and battery degradation. This framework includes an economic model for charging and discharging of PEVs which has been implemented in a 21-node sample distribution network with a wind turbine as a distributed generation (DG) ...

Research paper thumbnail of Forecasting Travel Behavior of PEV Users: A Deep Learning Approach Equipped with a Clustering Technique based on Travel Purpose

• Our proposed method is constructed based on deep learning and "Big Data" concept and to achieve... more • Our proposed method is constructed based on deep learning and "Big Data" concept and to achieve the accurate result we need as much as possible data. • The 23,514 trips dairy that includes information on individual socioeconomic status and trip characteristics are extracted from NHTS data.

Research paper thumbnail of Travel behavior and System Objectives Uncertainties In Electric Vehicle Optimal Charging

The negative environmental impacts of using fossil fuel-powered vehicles underlined the need for ... more The negative environmental impacts of using fossil fuel-powered vehicles underlined the need for inventing an alternative eco-friendly transportation fleet. Electrical vehicles (EVs) were introduced as an eligible substitute for the conventional vehicle fleet. The significant uncertainties associated with EVs usage, however, make their performance unpredictable. In this paper, we introduce a methodological framework for scheduling smart charging of EVs which considers the colligated uncertainties. Furthermore, the framework includes an ecumenical model for charging and discharging of EVs which is utilized in a 21-node sample distribution network which contains wind turbine as a Distributed Generation units. Our proposed approach extracted that the welfare of Vehicle to Grid effectuation in the network is much more beneficial than the uncoordinated mode. The simulation result indicates that smart charging effectuation is economical.

Research paper thumbnail of A Novel Electricity Price Forecasting Approach Based on Dimension Reduction Strategy and Rough Artificial Neural Networks

IEEE Transactions on Industrial Informatics

Research paper thumbnail of Deep Learning-Based Forecasting Approach in Smart Grids With Microclustering and Bidirectional LSTM Network

IEEE Transactions on Industrial Electronics

Research paper thumbnail of Charging Demand of Plug-in Electric Vehicles: Forecasting Travel Behavior Based on a Novel Rough Artificial Neural Network Approach

Journal of Cleaner Production