Pamir Shams

Pamir Shams
COMSATS University Islamabad | CUI · Department of Computer Sciences

MS Software Engineering

About

30
Publications
3,207
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53
Citations
Introduction
Pamir has recently done with his MS studies at the Department of Computer Science, COMSATS University Islamabad (CUI). Pamir does research on Home Energy Management in Smart Grid, Optimal Power Flow (OPF), Meta-heuristic Algorithms and Deep Learning (DL).

Publications

Publications (30)
Article
Full-text available
Electricity theft is one of the challenging problems in smart grids. The power utilities around the globe face huge economic loss due to ET. The traditional electricity theft detection (ETD) models confront several challenges, such as highly imbalance distribution of electricity consumption data, curse of dimensionality and inevitable effects of no...
Chapter
In this paper, a novel hybrid deep learning approach is proposed to detect the nontechnical losses (NTLs) that occur in smart grids due to illegal use of electricity, faulty meters, meter malfunctioning, unpaid bills, etc. The proposed approach is based on data-driven methods due to the sufficient availability of smart meters’ data. Therefore, a bi...
Article
Electricity theft is considered one of the most significant reasons of the non technical losses (NTL). It negatively influences the utilities in terms of the power supply quality, grid’s safety, and economic loss. Therefore, it is necessary to effectively deal with the electricity theft problem. For detecting electricity theft in smart grids (SGs),...
Chapter
In this paper, a data driven based solution is proposed to detect Non-Technical Losses (NTLs) in the smart grids. In the real world, the number of theft samples are less as compared to the benign samples, which leads to data imbalance issue. To resolve the issue, diverse theft attacks are applied on the benign samples to generate synthetic theft sa...
Chapter
In this paper, a problem of misclassification due to cross pairs across a decision boundary is investigated. A cross pair is a junction of the two opposite class samples. These cross pairs are identified using Tomek links technique. The majority class sample associated with cross pairs are removed to segregate the two opposite classes through an af...
Chapter
In this paper, we present a novel approach for the electricity theft detection (ETD). It comprises of two modules: (1) implementations of the six theft attacks for dealing with the data imbalanced issue and (2) a gated recurrent unit (GRU) to tackle the model’s poor performance in terms of high false positive rate (FPR) due to some non malicious re...
Chapter
Full-text available
In this paper, a hybrid deep learning model is presented to detect electricity theft in the power grids, which happens due to the Non-Technical Losses (NTLs). The NTLs emerge due to meter malfunctioning, meter bypassing, meter tampering, etc. The main focus of this study is to detect the NTLs. However, the detection of NTLs faces three major challe...
Conference Paper
Full-text available
In this paper, we present a novel approach for the electricity theft detection (ETD). It comprises of two modules:(1) implementations of the six theft attacks for dealing with the data imbalanced issue and (2) a gated recurrent unit (GRU)to tackle the model’s poor performance in terms of high false positive rate (FPR) due to some non malicious reas...
Conference Paper
Full-text available
In this paper, a novel hybrid deep learning approach is proposed to detect the nontechnical losses (NTLs) that occur in smart grids due to illegal use of electricity, faulty meters, meter malfunctioning, unpaid bills, etc. The proposed approach is based on data-driven methods due to the sufficient availability of smart meters' data. Therefore, a bi...
Conference Paper
Full-text available
In this paper, a hybrid deep learning model is presented to detect electricity theft in the power grids, which happens due to the Non-Technical Losses (NTLs). The NTLs emerge due to meter malfunctioning, meter bypassing, meter tampering, etc. The main focus of this study is to detect the NTLs. However, the detection of NTLs faces three major challe...
Conference Paper
Full-text available
In this paper, a data driven based solution is proposed to detect Non-Technical Losses (NTLs) in the smart grids. In the real world, the number of theft samples are less as compared to the benign samples, which leads to data imbalance issue. To resolve the issue, diverse theft attacks are applied on the benign samples to generate synthetic theft sa...
Thesis
Full-text available
Demand side management (DSM) in smart grid (SG) makes users able to take informed decisions according to their power usage pattern and assists the electric utility in minimizing higher power demand in the duration of higher energy demand intervals. Where, this ultimately leads to carbon emission reduction, electricity monetary cost minimization and...
Chapter
Demand side management (DSM) in smart grid (SG) makes users able to take informed decisions according to the power usage pattern of the electricity users and assists the utility in minimizing peak power demand in the duration of high energy demand slots. Where, this ultimately leads to carbon emission reduction, total electricity cost minimization...
Chapter
In smart grid (SG), demand side management (DSM) is a set or group of programs, allow consumers to play a vital role in transferring of their own load demand during peak time periods and minimizing their hourly based power consumption and total monetary cost of the electricity consumed and it also helps the electric utility in reducing higher power...
Conference Paper
In this paper, we used two techniques: Enhanced Differential Evolution (EDE) and Crow Search Algorithm (CSA), in order to evaluate the performance of Home Energy Management System (HEMS). The total load is categorized into three groups based on their energy consumption pattern, and time of use of appliances. Critical Peak Pricing (CPP) scheme is us...
Conference Paper
The electricity demand from residential buildings is increasing gradually day by day. Home Energy Management Systems (HEMS) are used to meet this demand by using Demand Sides Management (DSM) to reduce the pressure on consumers and utility companies. In this paper, HEMS is facilitated by using different meta-heuristic scheduling techniques: The Str...
Conference Paper
In this paper, two meta-heuristic techniques Chicken Swarm Optimization (CSO) and Enhanced Differential Evolution (EDE) are used for demand side management. We have integrated Traditional Grids with Demand Side Management (DSM) We have categorized appliances in two categories; fixed and shiftable/elastic appliances. Real Time Pricing (RTP) is used...
Conference Paper
Today, electricity is the most worthwhile resource which makes human life very easy. To overcome the gap among demand and supply of electricity, new techniques and methods are being explored. However, electricity demand is increasing constantly, which causes serious crisis. To tackle this problem, demand side management integrated with traditional...
Conference Paper
In this work, we evaluated the performance of home energy management system (HEMS) using two meta-heuristic optimization algorithms: harmony search algorithm (HSA) and crow search algorithms (CSA). For electricity bill calculation we use real time pricing (RTP) signals. Our main objectives are optimization of energy consumption, electricity cost mi...
Conference Paper
Demand side management (DSM) in smart grid (SG) makes users able to take informed decisions according to the power usage pattern of the electricity users and assists the utility in minimizing peak power demand in the duration of high energy demand slots. Where, this ultimately leads to carbon emission reduction, total electricity cost minimization...
Conference Paper
In smart grid (SG), demand side management (DSM) is a set or group of programs, allow consumers to play a vital role in transferring of their own load demand during peak time periods and minimizing their hourly based power consumption and total monetary cost of the electricity consumed and it also helps the electric utility in reducing higher power...
Conference Paper
In this paper, we used two techniques: Enhanced Differential Evolution (EDE) and Crow Search Algorithm (CSA), in order to evaluate the performance of Home Energy Management System (HEMS). The total load is categorized into three groups based on their energy consumption pattern, and time of use of appliances. Critical Peak Pricing (CPP) scheme is us...
Conference Paper
The electricity demand from residential buildings is increasing gradually day by day. Home Energy Management Systems (HEMS) are used to meet this demand by using Demand Sides Management (DSM) to reduce the pressure on consumers and utility companies. In this paper, HEMS is facilitated by using different meta-heuristic scheduling techniques: The Str...
Conference Paper
In this paper, two meta-heuristic techniques Chicken Swarm Optimization (CSO) and Enhanced Differential Evolution (EDE) are used for demand side management. We have integrated Traditional Grids with Demand Side Management (DSM) We have categorized appliances in two categories; fixed and shiftable/elastic appliances. Real Time Pricing (RTP) is used...
Conference Paper
Today, electricity is the most worthwhile resource which makes human life very easy. To overcome the gap among demand and supply of electricity, new techniques and methods are being explored. However, electricity demand is increasing constantly, which causes serious crisis. To tackle this problem, demand side management integrated with traditional...
Conference Paper
In this work, we evaluated the performance of home energy management system (HEMS) using two meta-heuristic optimization algorithms: harmony search algorithm (HSA) and crow search algorithms (CSA). For electricity bill calculation we use real time pricing (RTP) signals. Our main objectives are optimization of energy consumption, electricity cost mi...

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