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In this advance era, smart grid (SG) deployment is a global trend in which demand side management (DSM) have great significance to make the entire network more stable and efficient. SG is a novel form of conventional grid with large number of information and communication technologies. This research deals with the challenge of DSM in SG by implementing the approach of artificial neural network (ANN) to fulfil the demand of customers from average to peak times. There are various topologies are used for DSM discuss in literature, however ANN is more efficient with less response time by informing about energy prediction to providers and consumers which are connected with several clouds. The results shows the prediction of demand from daily to monthly basis by implementing the approach of ANN. The procedure of testing to training of ANN dataset is prepared using the MATLAB software.

One of the future goal in smart grid that maximize the performance of the system up to 100% and in this production large amount should be obtained from renewable energy resources. To make a reduction in the cost of energy, geothermal sources and fossil fuels are also used with smart grid to increase the efficiency of the grid. Today due to high cost of energy, very high losses in the actual power system, risks occur due to nuclear and oil and gas energy, and globally environment changes are the way of motivating to convert these sources into conventional energy sources. So today is the era of SG with integrating of renewable energy resources to maximize the efficiency and reduce the cost and make the system more stable. Traditional power systems are converted into smart grids due high efficiency, more securable, more reliable, and especially highly protection of the user data and bi directional energy flow. Due to this in this paper we discuss the IOT (Internet of things) based communication technologies to make the system more stable with high efficiency, minimum cost and with high protection of the user data in smart grid. IOT aided smart grid systems that consist of existing applications, prototypes and architectures. This research paper also highlights the challenges, open issues and a lot of research directions for the internet of things (IOT)-aided smart grid systems.

The term smart grid (SG) allows optimizing energy efficiency by flexible interconnection of central and distributed generators (DG) through transmission and distribution system to industrial and consumer end-users. In near future it is predicted that Distributed Generation (DG) from renewable energy resources (RES) will play a massive role to fulfill the users need and enhance the efficiency of smart grid. The increasing use of switching applications in SG integrated with RES may cause power quality problems in the term of harmonics pollution in the distribution systems. This paper proposes the designing and use of LLCL filter to mitigate the effect of harmonics in smart grids. The performance of the suggested method is checked by the simulation results using ETAP (Electrical Transient and Analyzer Program) and MATLAB (Matrix Laboratory). Theoretical analysis has been done using Simulation and real time data results of Sapphire Textile Industry unit-3.

Installation of hybrid electrical power system is imperative to fulfil the escalated energy demand of consumers. Now a days, there is a propensity in using renewable energy resources due to its cost effectiveness. However, multiple generating systems and the switching between them creates serious problems regarding distortions and harmonics which needs to be eliminated. In this study, a grid connected hybrid system has been proposed with linear loads. The hybrid system works under the standard conditions of wind and temperature. System has been assessed by applying Newton Raphson method and efficiency has been improved by using lead lag compensator (LLC). ETAP software has been used for simulation purpose. The effectiveness of the electrical system is measured by considering the load intake and consumption.

Now a days, Fuel Efficiency and minimum pollution in vehicles is a major research area. Solar Hybrid vehicles are becoming popular because they are fuel economical and able to provide power and speed upon need without any charging limitations. But the major setback in them is their prolong charging time. Hybrid technology-based automobiles are getting increased attention which results in their increased cost. Due to this, it is almost impossible for a common consumer to afford it. The work presented here; throws light on the employment of solar hybrid electric vehicle technology on a regular gasoline motorbike. The implementation of solar hybrid electric technology on the motorbike is done in a modified parallel hybrid configuration. Motorbike efficiency is to be improved by emphasis on electrical part and its development. This research, discusses all the phases from designing to construction and implementation of this technology on the motorbike.

Fossil fuels are more efficient and low cost as compared to Renewable Energy resources. Numerous methods have been proposed to decrease the initial cost and to increase the efficiency of Renewable Energy resources (RES). The proposed method is the combination of solar and geothermal power. In this research paper, binary power plant is designed combining geothermal heat, extraction from abandoned gas/oil bores and energy from photovoltaic system (PV). The cost of drilling and casing has been ignored in designing of proposed method. Two photovoltaic scenarios have been used in combination with geothermal power. In first one, PV system is used to work with hybrid geothermal and photovoltaic power cycle while in second scenario, hybrid geothermal and concentrated solar thermal system is used to generate heat for super heating geothermal binary cycle. This concentrated solar thermal cycle (CSTC) needs more periodic maintenance depending upon the area of system. Using the proposed system, the efficiency of the system has increased by 35% as compared to the traditional PV systems.

Microgrids (MG) has become the most imperative issue in the modern research. A microgrid is a cluster of distributed energy resources (DER) along with energy storage devices in the premises of load, which provides the opportunity to employ renewable energy resources (RES), along with the traditional power system. In most of the developing countries like Pakistan, ageing and overloading of the transmission lines is one of the major problem in energy system. The old infrastructure of electric power grid is not proficient of compensating the increased demand of power. However, these effects can be encountered by deploying the distributed energy resources nearby to the load. Apart from technical constrains, there are certain non-technical issues regarding deployment of microgrids in Pakistan. This survey investigates the problems associated with the implementation of microgrid and its challenges, which hinder its deployment in Pakistan. In this paper microgrid policies of Pakistan, challenges and driving factors of microgrid have been investigated. This will help to motivate the people to implement DER's and MG. Ultimately it will accelerate the implementation process of MG and will improve the overall power system of Pakistan.

Resources in sensor networks are scarce, especially in terms of energy, which is required to make nodes alive. Enhancing the energy efficiency by applying different techniques is the main research topic in WSN. The biggest advantage of WSN is that they can be deployed in harsh environment like in seismic regions, volcanic eruption, forest and battle field etc. They also play a vital role in monitoring areas, precise agriculture and medical field. To increase the lifetime of network several protocols have been defined. In this paper, comparisons of different protocols of LEACH have been made to judge performance of these protocols. The protocols LEACH, LEACH-C, MH-LEACH, TL-LEACH, E-LEACH, TB-LEACH, W-LEACH and LEACH-VH have been studied and compared in terms of their energy efficiency. In all the protocols of LEACH cluster head selection mechanism have been discussed in a different way due to which energy is saved. The simulation results of these protocols are observed on MATLAB. All these protocols are implemented on stationary source and sink and implemented on homogenous as well as on heterogeneous network. In future more energy can be saved by applying different strategies in the existing protocols.

Hypertensive retinopathy is a retinal disease which results as a consequence of high blood pressure. Its early detection is necessary in reducing the likelihood of permanent visual damage. The percentage of people suffering from Hypertension is high, so it is required to develop a system which automatically detects the presence of this disease. High blood pressure damages retinal vessels and due to which arteries width is reduced. This damage can be analyzed by extracting the blood vessels, classifying the segmented vessels into veins and arteries and finally computing their Arteriovenous Ratio, which is an important measure to establish whether a person is suffering from Hypertensive Retinopathy or not. This research presents a technique for automatic classification of blood vessels of retina using different classifiers and the performance of each classifier is compared on same feature set. A novel combination of features is used for classification of vessels, which is an essential step for calculation of Arteriovenous Ratio and subsequently the detection of Hypertensive Retinopathy. MATLAB has been used for this research. The results that are achieved using the proposed feature set show's 89% accuracy.