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Articles 1 - 7 of 7
Full-Text Articles in Engineering
A Kinetic Monte Carlo Study Of Mesoscopic Perovskite Solar Cell Performance Behavior, Behzad Bahrami
A Kinetic Monte Carlo Study Of Mesoscopic Perovskite Solar Cell Performance Behavior, Behzad Bahrami
Electronic Theses and Dissertations
Perovskite solar cells have received considerable attention in recent years due to their low processing cost and high energy conversion efficiency. However, the mechanisms of perovskite solar cell performance are not fully understood. Models based on probabilistic and statistical approaches can be used to simulate, optimize, and predict perovskite solar cell photovoltaic performance, and they can also guide experimental processing and fabrication conditions to achieve higher photovoltaic efficiency. This work developed a 3D model based on the kinetic Monte Carlo (KMC) approach to simulate 3D morphology of perovskite-based solar cells and predict their photovoltaic performance. The model incorporated the physical …
Techno-Economic And Sustainability Study Of Pv Inverter Controllers In Distribution Networks For Voltage Regulation, Kapil Duwadi
Techno-Economic And Sustainability Study Of Pv Inverter Controllers In Distribution Networks For Voltage Regulation, Kapil Duwadi
Electronic Theses and Dissertations
Increasing distributed solar installations in low voltage distribution grids tend to increase the feeder voltage. The rise in voltage is only acceptable to a certain limit, and control strategies are required to keep voltage within defined bounds for equipment safety and system reliability. PV inverter control strategies are cost-effective methods to prevent overvoltage. Different inverter control strategies have different impacts on their techno-economic performance, ultimately affecting their sustainability. An evaluation framework for long-term techno-economic and sustainability analysis of overvoltage prevention methods in PV-rich LV networks is proposed to decide suitable control methods by making use of quasi-steady-state time-series (QSTS) software …
Energy Optimization And Coordination Frameworks For Smart Homes Considering Incentives From Discomfort And Market Analysis, Priti Paudyal
Energy Optimization And Coordination Frameworks For Smart Homes Considering Incentives From Discomfort And Market Analysis, Priti Paudyal
Electronic Theses and Dissertations
The electricity demand is increasing with the growing use of electricity-based appliances in today’s world. The residential sector’s electricity consumption share is also increasing. Demand response (DR) is a typical way to schedule consumers’ energy consumption and help utility to reduce the peak load demand. Residential demand management can contribute to reduce peak electric demand, decrease electricity costs, and maintain grid reliability. Though the demand management has benefits to the utility and the consumers, controlling the consumers electricity consumption provides inconvenience to the consumers. The challenge here is to properly address the customers’ inconvenience to encourage them to participate and …
Intra-Day Solar Irradiance Forecasting For Remote Microgrids Using Hidden Markov Model, Abhilasha Bajracharya
Intra-Day Solar Irradiance Forecasting For Remote Microgrids Using Hidden Markov Model, Abhilasha Bajracharya
Electronic Theses and Dissertations
Accurate solar irradiance forecasting is the key to accurate estimation of solar power output at any given time. The accuracy of this information is especially crucial in diesel-PV based remote microgrids with batteries to determine the set points of the batteries and generators for their optimal dispatch. This, in turn, is related directly to the overall operating cost because both an overestimation and an underestimation of the irradiance means additional operating costs for either suddenly ramping up the backup resources or causing under-utilization of the available PV power output. Accurately predicting the solar irradiance is not an easy task because …
Reinforcement Learning And Game Theory For Smart Grid Security, Shuva Paul
Reinforcement Learning And Game Theory For Smart Grid Security, Shuva Paul
Electronic Theses and Dissertations
This dissertation focuses on one of the most critical and complicated challenges facing electric power transmission and distribution systems which is their vulnerability against failure and attacks. Large scale power outages in Australia (2016), Ukraine (2015), India (2013), Nigeria (2018), and the United States (2011, 2003) have demonstrated the vulnerability of power grids to cyber and physical attacks and failures. These incidents clearly indicate the necessity of extensive research efforts to protect the power system from external intrusion and to reduce the damages from post-attack effects. We analyze the vulnerability of smart power grids to cyber and physical attacks and …
Data-Driven Test Cases For Sustainability Assessment Of Smart Grid Initiatives In Organized Electricity Markets, Venkat Durvasulu
Data-Driven Test Cases For Sustainability Assessment Of Smart Grid Initiatives In Organized Electricity Markets, Venkat Durvasulu
Electronic Theses and Dissertations
The primary aim of this dissertation is to deliver a technique to augment power system test cases with realistic open-source data to represent a deregulated power system. These test cases are intended to be used by power system researchers who require a test case that is capable of performing economic and environmental analysis on a bulk-power level. These test cases are capable of estimating the cost of bulk-energy for economic analysis and harmful greenhouse gas (GHG) and air polluting (AP) emissions for environmental sustainability analysis. These cases are developed for simulations that are intended to be at the transmission level …
Machine Learning For Load Profile Data Analytics And Short-Term Load Forecasting, Md. Rashedul Haq
Machine Learning For Load Profile Data Analytics And Short-Term Load Forecasting, Md. Rashedul Haq
Electronic Theses and Dissertations
Short-term load forecasting (STLF) is a key issue for the operation and dispatch of day ahead energy market. It is a prerequisite for the economic operation of power systems and the basis of dispatching and making startup-shutdown plans, which plays a key role in the automatic control of power systems. Accurate power load forecasting not only help users choose a more appropriate electricity consumption scheme and reduces a lot of electric cost expenditure but also is conducive to optimizing the resources of power systems. This advantage helps while improving equipment utilization for reducing the production cost and improving the economic …