A5022346431- Energy Load and Power Forecasting
- Solar Radiation and Photovoltaics
- Electric Power System Optimization
- Nuclear Materials and Properties
- Photovoltaic System Optimization Techniques
- Building Energy and Comfort Optimization
- Smart Grid Energy Management
- Molten salt chemistry and electrochemical processes
- Nuclear reactor physics and engineering
- Perovskite Materials and Applications
- Energy Efficiency and Management
- IoT Networks and Protocols
- Neural Networks and Applications
- Smart Grid Security and Resilience
- Advancements in Solid Oxide Fuel Cells
- Air Quality Monitoring and Forecasting
- Advanced Computational Techniques and Applications
- Currency Recognition and Detection
- Urban Heat Island Mitigation
- Geoscience and Mining Technology
- Image and Signal Denoising Methods
- Power Systems and Renewable Energy
- Engineering Education and Pedagogy
- Transportation Planning and Optimization
- IoT and Edge/Fog Computing
Mirpur University of Science and Technology
2023-2025
NED University of Engineering and Technology
2018
Accurate short-term solar irradiance (SI) forecasting is crucial for renewable energy integration to ensure unit commitment and economic load dispatch. However, hourly SI prediction very challenging due atmospheric conditions weather fluctuations. This study proposes a hybrid approach using classification boosting algorithms global horizontal (GHI) forecasting. In data pre-processing steps, we employ random forest feature selection K-means clustering classification. The weather-based...
Accurate Solar Irradiance (SI) forecasting is an important aspect of solar energy harvesting and it depends on various meteorological features. Numerous feature selection algorithms have been implemented for the suitable parameters. However, boosting are not explored widely applications. Therefore, in this study, a novel perspective introduced by exploring efficacy In proposed we perform comparative analysis different applications including Extreme Gradient Boosting (XgBoost), Categorical...
Rapidly increasing global energy demand and environmental concerns have shifted the attention of policymakers toward large-scale integration renewable resources (RERs). Wind is a type RERs with vast potential no pollution associated it. The sustainable development goals: affordable clean energy, climate action, industry, innovation infrastructure, can be achieved by integrating wind into existing power systems. However, will bring instability challenges due to its intermittent nature....
This paper presents a simulation study on home energy management system (HEMS) with the contribution of renewable sources (RESs) for effective demand-side (DSM). The HEMS refers to network that combines various smart appliances and control unit optimize utilization minimize overall costs. proposes an cost minimization model, which is solved using single Knapsack algorithm combined dynamic programming (DP). problem used schedule ensure users producers receive maximum benefits in terms...
Abstract The transition to sustainable energy has become imperative due the depletion of fossil fuels. Solar presents a viable alternative owing its abundance and environmental benefits. However, intermittent nature solar requires accurate forecasting irradiance (SI) for reliable operation photovoltaics (PVs) integrated systems. Traditional deep learning (DL) models decision tree (DT)-based algorithms have been widely employed this purpose. DL often demand substantial computational resources...
The widespread integration of renewable energy resources (RERs) is needed for achieving sustainable development goals (SDGs) like affordable and clean energy, climate action industry, innovation, infrastructure. Wind a type RER with huge potential to fulfill the ever‐increasing electricity demand world. However, intermittent nature wind hinders large‐scale turbines into existing power system. main source intermittency due speed (WS), this can be overcome by implementing an accurate...
The occupancy datasets are useful for planning important buildings' related tasks such as optimal design, space utilization, energy management, maintenance, etc. Researchers currently working on two key issues in building management systems. First, feasible and economical deployment of indoor outdoor weather monitoring sensors data acquisition. Second, the development implementation cost-effective data-driven models with regular to ensure satisfactory performance prediction. In this context,...
The ever-increasing electricity demand, its dependency on fossil fuels, and the consequent environmental degradation are major concerns of this era. worldwide domination fuels in bulk generation is rapidly increasing emissions CO 2 other environmentally dangerous gases that contributing to climate change. economic emission dispatch two important problems thermal power whose combination produces a complex highly constrained nonlinear optimization problem known as combined dispatch. aims...
The world's energy consumption is continuously rising due to rapidly growing human population and expanding industrial sector. Integrating Renewable Energy Resources (RERs) with the power system comes up severe challenges as nature of these resources intermittent. Among RERs, solar a viable means producing power. However, intermittent energy, accurate forecasting necessary for smooth operation systems. operational applications such load balancing economic dispatch can be facilitated made...
For a sustainable environment, countries are planning to increase the share of Renewable Energy Resources (RERs) in their energy mix. Wind is type RERs that has potential overcome fossil reserves. However, due uncertain nature wind, its integration with existing power systems brings instability. This instability can be by implementing some accurate wind forecasting techniques. Therefore, this proposed study, we present novel integrated approach for hour-ahead forecasting. The two levels. At...
This research presents a comprehensive case study on medium-term load forecasting (MTLF) in the intricate dynamics of Pakistan’s power sector, Gujranwala Electric Power Company (GEPCO). The time horizon for MTLF ranges from few weeks to one year and it has applications energy management planning. deep-learning networks (DLNs), proposed recent years, have black-box nature, which reduces interpretability results. Therefore, study, mathematical model, Market Survey (PMS), is implemented...
This report gives all information and details of our project which is based on the concept `SELF-ENERGY SUSTAINABLE PLAYGROUND FOR CHILDREN. According to research a lot energy consumed by rides in playgrounds parks, while also given away. Which actually consumable, but it wasted. Rides like merry-go-rounds, sea-saw, swings Ferris wheel can be used as sources. The conserved through these for amendment park such lighting etc. main idea this create green culture saving electricity method...
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Energy harvesting is a versatile approach that holds promise for generating clean energy and enhancing the sustainability of infrastructure. Given challenges associated with nuclear waste, such as radiation levels long-term storage requirements, developing suitable materials crucial. These must be capable withstanding harsh conditions present in waste facilities while efficiently capturing converting energy. The objective this work was to study lead halide perovskites ( MAPbCl3 MAPbI3) terms...
Abstract The smart buildings’ load forecasting is necessary for efficient energy management, and it easily possible because of the data availability based on widespread use Internet Things (IoT) devices automation systems. information occupancy directly associated with consumption. Therefore, we present a hybrid model consisting Long Short-Term Memory (LSTM) network, Extreme Gradient Boosting (XgBoost), Random Forest (RF) Linear Regression (LR) commercial academic forecasting. correlation...
Smart Grid is a way of providing bidirectional energy flow with the integration latest communication technologies and advanced control methods to overcome issues associated current power grid such as unidirectional flow, resource wastage, reliability, security, enhanced quality, increasing demand energy. Integrating Internet Things (IoTs) makes hyperaware agile enhance efficiency, sustainability electricity distribution. IoT‐enabled Grids use IoT devices sensors collect real‐time data,...
Given the intermittent nature of solar energy, widespread adoption Photovoltaics (PVs) in existing electrical systems requires more accurate forecasting. Hourly forecasting Solar Irradiance (SI) comes under short-term horizon, which helps finding better solutions to problems such as unit commitment, energy demand balance and economic load dispatch etc. However, SI is very challenging due variety factors, including weather, atmospheric conditions position sun. Therefore, this study proposes a...