Power industry is incidenting a change from the present electric grid to a more secure, reliable, capable and advanced smart grid. Renewable energy sources such as wind and solar energy systems will be incorporated and potentially in bid scale in order to obtain these aims. Many possible applications of renewable energy sources have been inspected. In this article, reliability enhancement of power system considering the impact of wind and solar energy sources integration into grid with advanced intelligent strategies is focused. Further, different models are utilized to obtain the proposed renewable energy sources operation. Further, a reliability assessment framework is discussed to examine the reliability impact of renewable energy sources integration into the grid. A comprehensive case study and risk analysis has been performed based on the different risk indexes to show the usefulness of the proposed strategies and assessment framework, and to give precious insight on the reliability impact resulting from the wind and solar energy resources integration into the grid. The main advantages of renewable energy sources integration into grid with intelligent techniques are presented here along with the reliability evaluation. The results of the study reveals that the integration of the solar and wind energy systems into the grid enhances overall the reliability of the entire power system.

The state of the power system has changed over the last decades. Recently, the power system has faced several challenges and issues. On the one side, demands for electrical energy are increasing day-by-day, with power losses, grid failure, and lack of smart technology; on the other side, security threats are also increasing. The current power grid cannot deal with these issues. The Internet of things (IoT) has grown quickly in a very short time because of its main features. By using IoT in the power grid, we can enhance the conventional grid’s efficiency, capacity, reliability, sustainability, scalability, and stability. Using the IoT in smart grids resolves the numerous problems faced by current smart grids. According to the latest research on IoT-enabled smart grid (SG) systems, security issues have been identified as one of the key problems. This paper reviews the different security aspects and applications while integrating the IoT with smart grids and discusses various frameworks. Apart from this, we also focus on various IoT and non-IoT technologies used in the smart grid network, such as sensing, communication, and computing technologies, as well as their standards.

Hybrid electric vehicles are an effective alternative to the conventional fuel engine vehicles and thus efficient and intelligent energy management is the key for establishing a significant market for the hybrid electric vehicles globally. Recent developments in the field of intelligent techniques and demand to make the energy systems intelligent have become a means to develop energy efficient hybrid electric vehicles. The energy management issue becomes vital in order to enhance the autonomy of hybrid electric vehicles and to reduce the costs. Therefore, a novel approach with intelligent techniques, to control the plug-in hybrid electric vehicles, in front of different customer profiles has been presented. This paper presents the battery performance improvement of a plug-in hybrid electric vehicle using fuzzy logic controller and neural fuzzy logic controller with battery state of charge as a deciding parameter and consequently comparing the performance of both cases. The battery state of charge and engine speed as input has been selected and based on their values the advanced controller decides the accurate torque required to be converted to energy which could be used to charge the battery and this can be achieved by controlling the forward gain value. For this, an advanced fuzzy controller and advanced adaptive nuero fuzzy inference system controller are used to decide the value of forward gain. Simulink environment is used to simulate the performance of the proposed system. This could be helpful in deciding which type of intelligent system is to be used for the power efficient operation of the hybrid electric vehicle. The results of both the control techniques are compared and the better controller is recommended for energy management of a plug-in electric vehicles. The results indicate that advanced control techniques provide the good performance and improving the fuel budget of hybrid electric vehicles.

In this paper, a fuzzy fault tree analysis technique for reliability evaluation of the wind energy system is presented. The technique combines the operational failures effect and the errors in the fuzzy environment for the wind energy system configuration. In conventional fault tree analysis, the acceptance of the risks probability values is not considered. Besides, it is very difficult to have a precise assessment of the wind system failure rates or the undesired events occurrence probability due to absence of adequate data. Therefore, to overcome these disadvantages, a fault tree analysis based on the fuzzy set theory is presented and applied to the wind energy system. Moreover, if the fault probabilities of the wind energy system fault are not exact values then the fault probabilities are regarded as a fuzzy number and the fuzzy failure rate is known by using fuzzy rules. Also, the fuzzy fault tree analysis is one of the powerful reliability judgment method, which provides the failure modes and its consequences, which are proved on a wind energy system. Furthermore, the risk analysis method is applied based on the fuzzy risk index (FRI) to know the exact impact of every basic event on the top event. Therefore, outcomes show that the fuzzy based fault tree technique combines the probabilities imprecision and engineering inaccuracy are more flexible and adaptive, and it has great use in reliability engineering.

Solar energy technology has gained significant attention in recent years. It has strongly emerged as an alternative to the conventional mode of electricity generation for developing countries like India for their rising energy needs. Solar energy based electricity generation not only addresses environmental concerns but also increases the energy security and reduces the carbon footprints generated by the coal-based power plant. To boost the share of Renewable energy in the energy mix, the renewable energy policy introduced by the government has acted as a catalyst for large scale deployment of solar energy system to push it as the major energy alternative for India. The normal intensity of solar radiation in India is 220 MW per km square with around 300 sunny days in a year, whereas the coal-based plant generates a huge amount of carbon footprints. Therefore, solar based power generation has the potential of not only reducing the emissions and but also it can cater the rising energy demand. Thus solar photovoltaic plants has become a major alternative energy option in India with the ability to give an improved power supply, reduced global warming and enhance the security of energy supply. In this paper, efforts have been made to look into the overall perspective of solar energy and coal based generation by studying and analyzing the present status, technologies use, accessibility, policies interventions, major contributions, future potentials and trends of solar energy and fossil fuels in the Indian power sector. A feasibility analysis of solar technology implementation with the replacement of coal based plant pant is carried out for Singrauli, India. Results of the proposed study shows that the coal-based power plant generates a huge amount of carbon footprints and it can be reduced by replacing the coal based power plants with solar energy based power generation system. Consequently solar energy based power generation system is a key alternative for developing countries like India having metrological parameters similar to the case study done in this paper with the capacity to provide an improved supply, decreased global warming in addition to improving the energy security.

Attributing to the irreplaceable quality of nil carbon footprints, the power system considering the integration of electric vehicles and renewable energy resources are appealing growing attention in the recent time, but the reliability of their associated components, is a main matter of concern nowadays. Therefore, in this paper, a novel incentive based fuzzy fault tree analysis (NIBFFTA) approach for restructured power system considering the influence of integrating Electric vehicles and Renewable energy resources-based hybrid wind-solar energy is presented. The approach combines the impacts of different components failure rate and the incentive Gaussian distribution effects under the inducement fuzzy fault tree atmosphere for the grid integrated Renewable energy resources and Electric vehicles configurations. In the basic fault tree analysis, the vague and inaccurate events such as system switches and low power component failures could not be identified competently. Moreover, the probability values of fault occurrences in the complete power system are not considered into account. Additionally, it is quite hard to have a precise assessment of the grid-connected wind energy power systems and EV configuration failure chances or the possibility of occurrence of undesired actions in the complete system because of data deficiency. To overwhelm these demerits, a novel incentive based fuzzy fault tree analysis based on the Gaussian distribution and fuzzy set model is recommended and used for the restructured power system considering the impact of integrating Electric vehicles and Renewable energy resources. Besides, the probability analysis of fault occurrence is also proposed to determine the impact of each basic event of the proposed system on the top event. Furthermore, the prediction analysis of fault occurrence is also done to know the effect of every basic action of the system on the top action. Whereas, prediction analysis factors for the different basic events of the proposed systems are evaluated and these can be used to obtain the real consequence of basic events on the proposed system. It is found that a novel incentive based fuzzy fault tree analysis approach is more significant and efficient than the conventional fault tree method for risk assessment of restructured power system with integrating the electric vehicles and renewable energy resources.