Qazi Zafar Iqbal

PMAS - Arid Agriculture University | PMAS-AAUR · University Institute of Information Technology

Underwater Wireless Sensor Networks (UWSNs) are getting growing interest because of wide-range of applications. Most applications of these networks demand reliable data de-livery over longer period in an efficient and timely manner. However, resource-constrained nature of these networks makes routing in a harsh and unpredictable underwater environm...

Unique characteristics of Underwater Sensor Net-works (UWSNs) are very challenging in design of an efficient data gathering routing protocol. These characteristics include large propagation delay, high error rate, low bandwidth, and limited energy. In UWSNs, improved network lifetime, increased throughput and low end-to-end delay are prominent issu...

Design and development of adaptive, scalable and energy-efficient routing protocols for Wireless Sensor Networks (WSNs) is an active area of research. Many protocols and techniques have been proposed and implemented for energy efficient routing. In this research work, we present Bio inspired Distributed Energy Efficient Clustering (B-DEEC) protocol...

Underwater environment suffers from a number of impairments which effect reliability and integrity of data being transmitted. Cooperative transmission is well known for reliable data transfer. Hence, cooperative routing can be implemented in Underwater Wireless Sensor Networks (UWSNs) in order to reduce the impact of existing link impairments on tr...

My PhD Thesis final defence presentation.

In this paper, an efficient model based on factored conditional restricted boltzmann machine (FCRBM) is proposed for electric load forecasting of in smart grid (SG). This FCRBM has deep layers structure and uses rectified linear unit (RELU) function and multivariate autoregressive algorithm for training. The proposed model predicts day ahead and we...

Electrical load forecasting is a challenging problem due to random and non-linear behavior of the consumers. With the emergence of the smart grid (SG) and advanced metering infrastructure (AMI), people are capable to record, monitor, and analyze such a complicated non-linear behavior. Electric load forecasting models are indispensable in the decisi...

In this paper, an efficient model based on factored conditional restricted boltzmann machine (FCRBM) is proposed for electric load forecasting of in smart grid (SG). This FCRBM has deep layers structure and uses rectified linear unit (RELU) function and multivariate autoregressive algorithm for training. The proposed model predicts day ahead and we...

Micro-grid (MG) is an emerging component of a smart grid and it is increasing the efficiency and reliability of the power system with the passage of time. MGs often need power in order to fulfill its load requirements, which is transmitted form macro station (MS). Transmission of power from MS cause power line losses. To decrease these power line l...

Short term load forecasting is indispensable for industrial, commercial, and residential smart grid (SG) applications. In this regard, a large variety of short term load forecasting models have been proposed in literature spaning from legacy time series models to contemporary data analytic models. Some of these models have either better performance...

With the rapid pace in the evolution and development of technology, the demand of electrical energy is also increasing. Beside the production of energy from traditional and renewable energy sources, the energy management is also required to control the consumption of energy in commercial, industrial and residential houses. Improvement in technologi...

The integration of Smart Grid (SG) with cloud and fog computing has improved the energy management system. The conversion of traditional grid system to SG with cloud environment results in enormous amount of data at the data centers. Rapid increase in the automated environment has increased the demand of cloud computing. Cloud computing provides se...

The smart grid plays a vital role in decreasing electricity cost via Demand Side Management (DSM). Smart homes, being a part of the smart grid, contribute greatly for minimizing electricity consumption cost via scheduling home appliances. However, user waiting time increases due to the scheduling of home appliances. This scheduling problem is the m...

Renewable energy sources (RESs) are considered as future replacement of traditional energy generation sources with zero carbon emission and low price electricity producers. RESs are intermittent, uncertain and random in nature, they do not produce fixed amount of energy and heavily depend upon weather, season and area. In this paper, new trends in...

In the smart grid (SG) users in residential sector adopt various load scheduling methods to manage their consumption behavior with specific objectives. In this paper, we focus on the problem of load scheduling under utility and rooftop photovoltaic (PV) units. We adopt genetic algorithm (GA), binary particle swarm optimization (BPSO), wind driven o...

With the emergence of the smart grid, both consumers and electricity providing companies can benefit from real-time interaction and pricing methods. In this work, a smart power system is considered, where consumers share a common energy source. Each consumer is equipped with a home energy management controller (HEMC) as scheduler and a smart meter....

The integration of Smart Grid (SG) with cloud and fog computing has improved the energy management system. The conversion of traditional grid system to SG with cloud environment results in enormous amount of data at the data centers. Rapid increase in the automated environment has increased the demand of cloud computing. Cloud computing provides se...

In this paper, we propose a home energy management (HEM) scheme in the residential area for electricity cost and peak to average ratio (PAR) reduction. Furthermore, reduction in imported electricity from the external grid is also the objective of this study. Our proposed scheme schedules smart appliances as well as electrical vehicles (EVs) chargin...

Micro-grid (MG) is an emerging component of a smart grid and it is increasing the efficiency and reliability of the power system with the passage of time. MGs often need power in order to fulfill its load requirements, which is transmitted form macro station (MS). Transmission of power from MS cause power line losses. To decrease these power line l...

Short term load forecasting is indispensable for industrial, commercial, and residential smart grid (SG) applications. In this regard, a large variety of short term load forecasting models have been proposed in literature spaning from legacy time series models to contemporary data analytic models. Some of these models have either better performance...

With the rapid pace in the evolution and development of technology, the demand of electrical energy is also increasing. Beside the production of energy from traditional and renewable energy sources, the energy management is also required to control the consumption of energy in commercial, industrial and residential houses. Improvement in technologi...

Microgrid is a community-based power generation and distribution system that interconnects smart homes with renewable energy sources (RESs). Microgrid efficiently and economically generates power for electricity consumers and operates in both islanded and grid-connected modes. In this study, we proposed optimization schemes for reducing electricity...

Smart Grid (SG) plays vital role to utilize electric power with high optimization through Demand Side Management (DSM). Demand Response (DR) is a key program of DSM which assist SG for optimization. Smart Home (SH) is equipped with smart appliances and communicate bidirectional with SG using Smart Meter (SM). Usually, appliances considered as worki...

With the advent of Smart Grid (SG), it provides the consumers with the opportunity to schedule their power consumption load efficiently in such a way that it reduces their energy cost while also minimizing their Peak to Average Ratio (PAR) in the process. We in this paper target the appliances to schedule in such a way that it increases User Comfor...

With the emergence of automated environments, energy demand by consumers is increasing rapidly. More than 80% of total electricity is being consumed in the residential sector. This brings a challenging task of maintaining the balance between demand and generation of electric power. In order to meet such challenges, a traditional grid is renovated b...

Smart Grid (SG) plays vital role to utilize electric power with high optimization through Demand Side Management (DSM). Demand Response (DR) is a key program of DSM which assist SG for optimization. Smart Home (SH) is equipped with smart appliances and communicate bidirectional with SG using Smart Meter (SM). Usually, appliances considered as worki...

The smart grid plays a vital role in decreasing electricity cost through Demand Side Management (DSM). Smart homes, a part of the smart grid, contribute greatly to minimizing electricity consumption cost via scheduling home appliances. However, user waiting time increases due to the scheduling of home appliances. This scheduling problem is the moti...

In the smart grid (SG) users in residential sector adopt various load scheduling methods to manage their consumption behavior with specific objectives. In this paper, we focus on the problem of load scheduling under utility and rooftop photovoltaic (PV) units. We adopt genetic algorithm (GA), binary particle swarm optimization (BPSO), wind driven o...

Renewable energy sources (RESs) are considered as future replacement of traditional energy generation sources with zero carbon emission and low price electricity producers. RESs are intermittent, uncertain and random in nature, they do not produce fixed amount of energy and heavily depend upon weather, season and area. In this paper, new trends in...

Recently, Home Energy Management (HEM) controllers have been widely used for residential load management in a smart grid. Generally, residential load management aims {to reduce the electricity bills and also curtail the Peak-to-Average Ratio (PAR)}. In this paper, we design a HEM controller on the {basis} of four heuristic algorithms: Bacterial For...

Demand Side Management (DSM) will play a significant role in the future smart grid by managing loads in a smart way. DSM programs, realized via Home Energy Management (HEM) systems for smart cities, provide many benefits; consumers enjoy electricity price savings and utility operates at reduced peak demand. In this paper, Evolutionary Algorithms (E...

This paper presents real time information based energy management algorithms to reduce electricity cost and peak to average ratio (PAR) while preserving user comfort in a smart home. We categorize household appliances into thermostatically controlled (tc), user aware (ua), elastic (el), inelastic (iel) and regular (r) appliances/loads. An optimizat...

Due to smart grid applications the consumers and producers are able to meet the demand of each others and thus take part in demand side management and demand response program. Hence smart grid leads to optimization of energy consumption and reduce high cost in today extensive demand of energy. In this research work we are reducing electricity consu...

In this paper we propose an ECG optimization model for a smart home based on DSM.The proposed model is an efficient SHEM strategy. The model is proposed keeping in view the minimization of energy consumption,energy consumption cost and energy generation cost.The model is based on efficient scheduling of appliances and an ECG optimization algorithm...

In this paper, we introduce a generic architecture for demand side management (DSM) and use combined model of time of use tariff and inclined block rates. The problem formulation is carried via multiple knapsack and its solution is obtained via ant colony optimization (ACO). Simulation results show that the designed model for energy management achi...

In this paper, we propose a novel strategy for a Demand Side Management (DSM) in a Smart Grid (SG). In this strategy, three types of loads are considered, i.e., residential load, commercial load and industrial load. The larger number of appliances of different power rating for each type of load is considered in this work. The focus of this work is...

Demand Side Management (DSM) mechanism is used for the implementation of different strategies to encourage residential users to reduce electricity bill as well as energy demand. There is also a close relationship between the consumer and utility for equally benefiting to both in terms of grid stability and bill reduction. Extensive research is unde...

Efficient energy management requires smart approaches in demand side as well as demand response management assisted by smart, innovative, and computationally feasible schemes. Artificial intelligence algorithms are increasingly becoming helpful in generating multiple scenarios for a range of real world problems on the pattern of human Intelligence....

The energy demand of residential end users has been so far largely uncontrollable and inelastic with respect to the power grid conditions. In this paper, we describe a scheme to solve multiple knapsack problems (MKP) using heuristic algorithms. Keeping total energy consumption of each household appliance under certain threshold with maximum benefit...

Many researcher has paid their to explore and monitor the under water environment. There are lot of application of Underwater WSNs like environment monitoring, exploration of under water surfaces, disaster preventions assisted navigation etc. Underwater sensors are totally different from the terrestrial sensors. Terrestrial sensor network uses the...

The main purpose of the Wireless Sensor Network protocols is to enhance the network life time and balance the energy consumption in network. Sensor nodes send their data to the BS. So the nodes which are far away from the BS need more energy to send data. To overcome this problem we introduce a multilevel hierarchical protocol which enhances networ...

In order to increase network life time scalable, efficient and adaptive routing protocols are need of current time. Many energy efficient protocols have been proposed, the Clustering algorithm is also a basic technique used for energy efficiency.In this paper we propose an energy efficient routing protocol that is based on Artificial Bee Colony (AB...