Sakeena Javaid

Institute of Space Technology KICSIT Campus · Department of Computer Science

Maintaining the records of domestic consumers’ electricity consumption patterns is very complex task for the utilities, especially for extracting the meaningful information to maintain their demand and supply. Due to the increase in population, large amount of valuable data from the domestic sector is extracted by the smart meters and it becomes a...

The transformation of conventional grid into Smart Grid (SG) requires strategic implementation of the demand-sensitive programs while considering the varying fluctuations in the consumers’ load. The core challenges faced by existing electric system are that how to utilize electrical devices, how to tackle large amount of data generated by end devic...

The transformation of conventional grid into Smart Grid (SG) requires strategic implementation of the demand-sensitive programs while considering the varying fluctuations in the consumers’ load. The core challenges faced by existing electric system are that how to utilize electrical devices, how to tackle large amount of data generated by end devic...

Energy management of residential buildings plays an important role in a smart grid. Region specific fuzzy logic strategies are proposed recently. However, no such approach exists that covers all regions of the world. A fuzzy logic-based strategy for the construction of fuzzy controller covering the entire globe would be cost effective due to the in...

Local energy generation and peer to peer (P2P) energy trading in the local market can reduce the energy consumption cost, emission of harmful gases (as renewable energy sources are used to generate energy at user's premises) and increase the smart grid resilience. However, local energy trading with peers can have trust and privacy issues. A central...

The emergence of the smart grid has empowered the consumers to manage the home energy in an efficient and effective manner. In this regard, home energy management (HEM) is a challenging task that requires efficient scheduling of smart appliances to optimize energy consumption. In this paper, we proposed a meta-heuristic based HEM system (HEMS) by i...

In this paper, two energy management controllers: Binary Particle Swarm Optimization Fuzzy Mamdani (BPSOF-MAM) and BPSOF Sugeno (BPSOFSUG) are proposed and implemented. Daily and seasonally used appliances are considered for the analysis of the efficient energy management through these controllers. Energy management is performed using the two Deman...

In this paper, an artificial neural network (ANN)based methodology is proposed to forecast electricity load and price. The performance of an ANN forecast model depends on appropriate input parameters. Parameter tuning of ANN is very important to increase the accuracy of electricity price and load prediction. This is done using mutual information an...

Short term electricity load and price accurate fore-casting are the key areas that need to be addressed in Smart Grids (SG). In this paper, a new model is proposed for accurate short term forecasting of load and price. First, irrelevant features are removed using Recursive Feature Elimination (RFE) and Decision Tree Regressor (DTR). Then, further d...

Nowadays, there exists strong need to enable the Intelligent Vehicle (IV) communication for applications such as safety messaging, traffic monitoring and many other internet access purposes. In this work, we have introduced an Intelligent Vehicle Trust Points (IVTPs) sharing mechanism between vehicle to vehicle, vehicle to infrastructure and vehicl...

In a complex network of smart vehicles, some issues arise related to security, privacy, selfishness of nodes and node failures. We have proposed an architecture of vehicular network in a smart city based on blockchain. Some scenarios and design principles are also provided. Contrary to prior architectures of vehicular networks, our proposed model p...

The feature of bidirectional communication in a smart grid involves the interaction between consumer and utility for optimizing the energy consumption of the users. For optimal management of the energy at the end user, several demand side management techniques are implemented. This work proposes a home energy management system, where consumption of...

Cloud servers provide services over the internet by using Virtual Machines (VMs). The power consumption of Physical Machines (PMs) needs to be considered, as VMs are running on physical machines. When a consumer sends request to the cloud, it takes time to respond because of distant location of cloud. Due to which delay and latency issue arises. Fo...

Management of increasing amount of the electricity information provided by the smart meters is becoming more valuable and a very challenging issue in modern era, especially in residential sector for maintaining the records of consumers' consumption patterns. It becomes the necessity of retailers and utilities to provide the consumers more effective...

In this work, a new orchestration of Consumer to Fog to Cloud (C2F2C) based framework is proposed for efficiently managing the resources in residential buildings. C2F2C is a three layered framework consisting of cloud layer, fog layer and consumer layer. Cloud layer deals with on-demand delivery of the consumer’s demands. Resource management is int...

Signature of Student: Summary of the Research This synopsis describes that residential energy management systems which are leveraged by the penetration of the renewable energy sources (RESs) such as: photovoltaic (PV) systems and wind turbines. These are the major sources used in residential energy and the concurrent penetration of these resources...

PhD Synopsis Presentation

Recently big data analytics are gaining popularity in the energy management systems (EMS). The EMS are responsible for controlling, optimization and managing the energy market operations. Energy consumption forecasting plays a key role in EMS and helps in generation planning, management and energy conversation. A large amount of data is being colle...

A user's requirement and designing goal for a computing machine are to process and respond the requests in real time with cost efficiency. System modeling with efficient resource allocation develops time and cost efficient platform. The cloud has enhanced resources with resource sharing techniques for efficient processing. However, it suffers from...

In this work, we propose a DSM scheme for electricity expenses and peak to average ratio (PAR) reduction using two well-known heuristic approaches: the cuckoo search algorithm (CSA) and strawberry algorithm (SA). In our proposed scheme, a smart home decides to buy or sell electricity from/to the commercial grid for minimizing electricity costs and...

In this paper, an integrated fog and cloud based environment for effective energy management is proposed in which fogs are connected to cloud in order to reduce the burden of cloud. It handles the data of clusters of buildings at consumers’ end. Six fogs are used on six different regions in the world which are based on six continents. Furthermore,...

The latency issue of cloud based system can degrade smart grid's real-time applications. This paper introduces a fog computing layer between the cloud and clients to provide energy management service in near real-time with optimised computing cost. In a region, in proposed system model, two clusters of residential buildings have access to two fogs...

Presently, the advancements in the electric system, smart meters, and implementation of renewable energy sources (RES) have yielded extensive changes to the current power grid. This technological innovation in the power grid enhances the generation of electricity to meet the demands of industrial, commercial and residential sectors. However, the in...

A demand response (DR) based home energy management systems (HEMS) synergies with renewable energy sources (RESs) and energy storage systems (ESSs). In this work, a three-step simulation based posteriori method is proposed to develop a scheme for eco-efficient operation of HEMS. The proposed method provides the trade-off between the net cost of ene...

This survey paper is based on comprehensive study of optimization techniques used in smart grid and reviews one of the most popular evolutionary optimization technique i.e., differential evolution (DE) optimization. In addition, different types of DE algorithm currently used in literature are also discussed. These include enhanced DE, modified DE a...

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...

The introduction of Smart Grid (SG) in recent years provide the opportunity to the consumer to schedule their load in such an efficient manner that reduces the bill and also minimizes the Peak to Average Ratio. This paper focuses on scheduling the appliances in a more feasible and energy conservative way to satisfy both consumer and utility. In thi...

Ever increasing demand of electricity necessitates cheaper electric supply. Electricity forecasting plays very important role in order to reduce operational cost of generation, transmission and delivery system. In this paper, a novel electricity forecasting technique enhanced recurrent extreme learning machine (ERELM) has been proposed. It forecast...

Renewable energy sources (RESs) are considered as reliable and green electric power generations. Photovoltaic (PV) and wind turbine (WT) are used to provide electricity in remote areas. The optimum unit sizing of hybrid RESs components is a vital challenge in a stand-alone system. This paper presents Jaya algorithm for optimum unit sizing of a PV-W...

Electricity Price Forecasting (EPF) plays a significant role in competitive electricity markets. Market participants rely on price forecast for generation, assets scheduling and effective bidding plan formulation. The uncertainty and volatility of energy market makes price forecasting a very challenging task. This paper gives a survey on methods an...

In a transmission network, optimal power flow (OPF) is considered as one of the most widely studied non-linear, non-convex and highly constrained problem. While solving the conventional OPF problem, power generation system mainly consists of fossil fuel thermal generators; however, with the increased energy demand, renewable energy sources like win...

The greenhouse gas emission is increasing around the globe. In order to reduce its emission factor, the concept of microgrid is introduced, which integrates renewable energy sources. The microgrid has a point of common coupling which helps to exchange power with utility during different times of a day to meet load demand. Based on all the system co...

A smart grid (SG) is a modernized electric grid that enhances the reliability, efficiency, sustainability, and economics of electricity services. Moreover, it plays a vital role in modern energy infrastructure. The core challenge faced by SGs is how to efficiently utilize different kinds of front-end smart devices, such as smart meters and power as...

In this work, we propose a DSM scheme for electricity expenses and peak to average ratio (PAR) reduction using two well-known heuristic approaches: the cuckoo search algorithm (CSA) and strawberry algorithm (SA). In our proposed scheme, a smart home decides to buy or sell electricity from/to the commercial grid for minimizing electricity costs and...

In this work, we propose a DSM scheme for electricity expenses and peak to average ratio (PAR) reduction using two well-known heuristic approaches: the cuckoo search algorithm (CSA) and strawberry algorithm (SA). In our proposed scheme, a smart home decides to buy or sell electricity from/to the commercial grid for minimizing electricity costs and...

In this paper, an integrated fog and cloud based environment for effective energy management is proposed in which fogs are connected to cloud in order to reduce the burden of cloud. It handles the data of clusters of buildings at consumers' end. Six fogs are used on six different regions in the world which are based on six continents. Furthermore,...

Energy management of residential buildings plays an important role in a smart grid. Region specific fuzzy logic strategies are proposed recently. However, no such approach exists that covers all regions of the world. A fuzzy logic based strategy for the construction of fuzzy controller covering the entire globe would be cost effective due to the in...

In this paper, a new orchestration of Fog-2-Cloud based framework is presented for efficiently managing the resources in the residential buildings. It is a three layered framework having: cloud layer, fog layer and consumer layer. Cloud layer is responsible for the on-demand delivery of the resources. Effective resource management is done through t...

In this research work, two energy management controllers are proposed: swarm optimization fuzzy mamdani (SOFM) and swarm optimization fuzzy sugeno (SOFS) for the efficient scheduling and controlling of the electric loads in a residential building which is comprised of 10 apartments having the single family setup. Two types of electric loads are con...

This survey paper is based on comprehensive study of optimization techniques used in smart grid and reviews one of the most popular evolutionary optimization technique i.e., differential evolution (DE) optimization. In addition, different types of DE algorithm currently used in literature are also discussed. These include enhanced DE, modified DE a...

The introduction of Smart Grid (SG) in recent years provide the opportunity to the consumer to schedule their load in such an efficient manner that reduces the bill and also minimizes the Peak to Average Ratio. This paper focuses on scheduling the appliances in a more feasible and energy conservative way to satisfy both consumer and utility. In thi...

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...

Controlling power utilization in the residential area is one of the major challenges in the smart grid (SG). Demand response (DR) has played a vital role in energy management and improved it with the involvement of residential consumers who participate in such programs from utilities for scheduling their appliances to the off peak hours. In this pa...

The greenhouse gas emission is increasing around the globe. In order to reduce its emission factor, the concept of microgrid is introduced, which integrates renewable energy sources. The microgrid has a point of common coupling which helps to exchange power with utility during different times of a day to meet load demand. Based on all the system co...

In recent years, demand side management (DSM) techniques have been designed for residential, industrial and commercial sectors. These techniques are very effective in flattening the load profile of customers in grid area networks. In this paper, a heuristic algorithms-based energy management controller is designed for a residential area in a smart...

Home Energy Management System (HEMS) enhances the load scheduling in the next-generation electric grid. Residential users send responses to utilities for scheduling their appliances to the off peak hours when prices are low. The scheduling of the household appliances still not succeeded too much by having some drawbacks. In this research, we have p...

Home Energy Management System (HEMS) enhances the load scheduling in the next-generation electric grid. Residential users send responses to utilities for scheduling their appliances to the off peak hours when prices are low. The scheduling of the household appliances still not succeeded too much by having some drawbacks. In this research, we have p...