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Production of energy and its usage per capita is considered as indicators that depict the living standards of a nation. The economic growth of a country is directly dependent on the availability of energy resources. To create a balance between energy demand and available energy resources, renewable resources are being in much focused these days. The most important renewable energy resources include solar, wind, geothermal and biogas, etc. Solar energy is one of the most important resources of renewable energy, used to convert light energy directly into electrical energy. Maximum power extraction is a major problem associated with Photovoltaic (PV) power systems. Maximum power point tracking (MPPT) is required to improve the energy conversion efficiency of, Photovoltaic power system. The MPPT is a dynamic process of getting the optimal output power from solar PV Arrays under different irradiation levels and temperature change. The performance of an MPPT Controller is dependent on the fact that how rapidly it can attain the Maximum Power Point (MPP) and stability of output. Previously Different MPPT Controllers have been designed to extract maximum power from PV modules under changing weather conditions. To overcome the limitations of previous methods, an intelligent method based on fuzzy logic is proposed for maximum power point tracking. To analyze the performance of fuzzy logic based MPPT controller a PV System is designed in MATLAB/SIMULINK. The resulted Simulations show that the proposed system has a fast response and good performance characteristics. It can improve the efficiency of PV array improves effectively against change in irradiation and temperature.

Energy crises have been a big challenge for the world to overcome and researchers have come up with systems that use renewable energy sources to produce or utilize power. Solar-powered Stirling's engine is one of the most advanced sources of renewable energy for generating electric power via solar heat. Previously, Stirling's engine has been operated with biogas, coal, and molten salt, but these methods are not environment-friendly. The aim of this research is to create a system capable of transforming heat energy into an electric power source. Shaft and electric power at various temperatures and pressures have been tested. 3kW kinematic Stirling engine is successfully configured, tested, and analyzed. The receiver aper that absorbs the solar rays has been improved to an extent that its efficiency has increased to 80%. The results indicate that the efficiency of the proposed design is much higher as compared to previous designs.

Solid oxide fuel cell (SOFC) provides several benefits such as high efficiency, modularity, quiet operation and cogeneration alternatives. Nevertheless, the main weakness in SOFC-based power plant has the slow dynamic response during transient situations in peak demand since this problem can be addressed by using complementary system such as a super-capacitor (SC). This paper provides an optimal load sharing and arrangement strategy (LSAS) for a hybrid power system which combines a SOFC stack, a SC module and a battery bank that support local grid. According to LSAS, the SOFC is the primary power source. The SC module is utilized as a backup and complement device to take care of the load following problems of SOFC during transient. The battery bank is added as a high energy density and/or backup device to stabilize the DC bus voltage, while an electrolyzer (ELYZ) is used as a dump load during surplus power. The LSAS operates in two layers. The external layer accomplished the overall power management system. Depending upon load demand, this layer generates references to the internal layer. The internal layer controls the individual subsystems, i.e., SOFC, ELYZ, SC and battery according to the references coming from the external layer. A complete MATLAB/Simulink model has been established to check the performance of the proposed system for the real load conditions. Simulation results show the effectiveness of the proposed system in terms of power transfer, load tracking and grid stability.

This work provides the dynamic operation and supervisory control of a hybrid renewable energy system which supplies power in stand-alone as well as in grid-connected mode. It contains a photovoltaic as a primary source controlled via fuzzy and a Proton Exchange Membrane Fuel Cell (PEMFC) as a secondary source controlled via Proportional Integral Differential (PID) controller. The high intermittency nature of photovoltaic is addressed through the integration of super-capacitor and battery bank in the proposed architecture. The overall strategy of the proposed system is achieved using dynamic power switches of the power converters. The strategy maximizes the use of available photovoltaic /fuel cell/ super-capacitor/battery power and reduces stress on the public grid under all conditions for 24 hours. The proposed test-bed is simulated under real weather pattern and load variations. Simulations conclude the effectiveness of the proposed architecture.

Programmable logic controllers (PLCs) are at the vanguard of industrial automation. In this article a PLC based control system is design and later on implemented on an induction motor used inside textile industry in spinning plant, further it can be implemented on any other industry. Also, it is implemented by designing hardware circuitry for induction motor's speed control by attaching motor to PLC and tested it. The results are collected for at two conditions; normal and trip operation conditions. With the addition of PLC in the existing system for control and automation of spinning machine's induction motor accuracy is higher than the normal traditional voltage-frequency (V/f) control mechanism and control system. This control system using PLC increases the efficiency of induction motor to 95%. In terms of speed regulation and efficiency, the PLC is very adaptable tool for industry and electric drives control.

Two technology opportunities, integration of renewable energy sources and the electrification of vehicles are being encouraged to reduce dependency on fossil fuels and pollution problems. Nevertheless, the huge increase of plug-in hybrid electric vehicles (PHEVs) on roads will cause an additional load in demand, especially at rush hours, and therefore, threatens the stability of existing power grids. Considering PHEV stay for several hours in the workplace, (i.e., university), this may provide an inimitable framework to charge PHEV from wind in the workplace. This paper introduces the possibility of introducing intelligent control of wind power and battery storage units as supplementary power sources for future PHEV charging demands during rush hours. The operation of the proposed algorithm is based on the priority levels of PHEVs charging, and fluctuations in DC link voltage levels due to the variation in wind speed. The priorities of PHEVs charging are developed according to their power requirements, maximum rating of distribution transformer and park duration of PHEVs in the workplace during wind speed. Various non-isolated proportional&ndash, integral controllers and improved intelligent fuzzy control are used to keep a minimum critical DC link voltage to permit the power conditioning system to operate a charging station uninterruptedly, even at low wind speed. The improved intelligent fuzzy controller also contributes to minimizing the stress on the DC bus and ensures quality output power. The performance of the proposed charging station is verified for the real PHEV under real-world record of wind speed. All the energy sources, electric charging station and their controllers are designed in MATLAB/Simulink. Finally, the feasibility of proposed charging station is checked experimentally in the laboratory.

This manuscript focuses on a hybrid power system combining a solar photovoltaic array and energy storage system based on hydrogen technology (fuel cell, hydrogen tank and electrolyzer) and battery. The complete architecture is connected to the national grid through power converters to increase the continuity of power. The proposed a hybrid power system is designed to work under classical-based energy management algorithm. According to the proposed algorithm, the PV has the priority in meeting the load demands. The hydrogen technology is utilized to ensure long-term energy balance. The battery is used as a backup and/or high power device to take care of the load following problems of hydrogen technology during transient. The dynamic performance of a hybrid power system is tested under different solar radiation, temperature and load conditions for the simulation of 24 Hrs. The effectiveness of the proposed system in terms of power sharing, grid stability, power quality and voltage regulation is verified by Matlab simulation results.

This work provides a micro-grid, which consists of Photovoltaic (PV) array, a micro-turbine (MT) set and a supercapacitor (SC) module to support the grid and/or grid integrated domestic load. Each subsystem (e.g., PV, MT, and SC) is controlled through non-isolated conventional controllers whereas the overall system operation and power flow priorities are performed via power control and management system. According to proposed system operation, PV has the priority to meet the demand. MT is synchronized as a secondary system to support continuous power flow for 24 hours. The SC module is utilized as an energy storage device during excess power and/or backup during demand. A complete Simulink test-bed is designed and checked under real load and weather conditions for at Islamabad, Pakistan. MATLAB Simulations conclude the effectiveness of the proposed system in terms of feasibility, load tracking and continuity.

This piece of work provides a hybrid power plant integrating a wind coupled with Permanent Magnet Synchronous Generator (PMSG), a super-capacitor (SC), a battery and a diesel engine (DE) set which operates without a grid connection. Each subsystem (e.g., wind, SC, battery, DE) has controlled through non-isolated PID/PI embedded controller power converters while the overall operation and power flow priorities are achieved through Programming Logic Controller (PLC). According to the algorithm, the wind has the priority to meet the demand. The SC and battery modules are utilized as an energy storage devices during surplus power and/or backup during demand. A diesel engine is also added to increase the reliability of the system for 24 hours. The performance of proposed design is tested at different wind speed and load conditions for a small community at Karachi, Pakistan. MATLAB results conclude the effectiveness of proposed system in terms of power quality and load tracking.

This piece of work focuses on wind power generation with hybrid storage system, e.g., hydrogen (fuel cell) and supercapacitor. The wind power has the priority to meet the demand. The fuel cell is added as a backup to ensure long-term energy balance while the supercapacitor is utilized as a buffer and/or backup source during transient. The complete architecture is connected to the utility through various power converters to improve the overall system stability, continuity and reliability of power. The operation of the proposed system is performed through Power Management and Control Strategy (PMCS). The PMCS works in such a way as to maximize the use of wind/fuel/supercapacitor and reduce stress on the utility. The performance of the system is tested for complete one day under different weather and load conditions. MATLAB/Simulink results are shown to verify the effectiveness of the proposed model.

This paper deals with the design and control of a micro-grid, including various alternative energy resources (photovoltaic and wind) and battery energy storage system which operates in stand-alone as well as in grid-connected mode. The proposed micro-grid is controlled via various non-isolated converters while an energy management is performed through switching based algorithm. According to the strategy, the wind is used as the primary power source while the Photovoltaic (PV) is added to improve the reliability of system under different weather conditions. The battery module is utilized as an energy storage system during surplus power and/or backup device during demand. The proposed system used real record of weather pattern and load conditions for a small community at Islamabad, Pakistan. This city is gifted with several natural resources that can generate a significant amount of power energy for the region. MATLAB simulation results show the effectiveness of proposed system in terms of grid stability, power sharing, load tracking and power quality.

Applications of PHEV have been observed as popular in transportation sector, but, an uncoordinated charging of PHEV poses an extra load during peak times which brings up many technical problems in which durability of power system occurs first. Considering PHEV to stay for several hours in the parking lot may offer a unique opportunity to charge PHEV from photovoltaic power in those hours. The proposed charging facility is working under smart charging scheduling paradigm, which is independent from forecasting models of PHEVs charging. The proposed paradigm schedules of PHEV is in an optimal way based on two parameters i.e., priority levels of PHEVs charging, and variations in DC link voltage level. Furthermore, the priorities of PHEV charging are based on their power demand, maximum rating of distribution transformer and stay duration of PHEVs in the parking lot during high irradiation of solar effect. The sensing of proposed paradigm is based on change in DC link voltage. The DC link voltage changes due to variance in solar irradiance, temperature and real-time residential load. Such priorities are updated whenever smart charging scheduling paradigm detects changes in voltage and initiate/terminate PHEVs charging. Simulation results express the effectiveness of proposed charging station effectively.

In this study, the energy management and switching control of plug-in hybrid electric vehicles (PHEVs) in a hybrid smart micro-grid system was designed. The charging station in this research consists of real market PHEVs of different companies with different sizes. The rate of charging of PHEVs is managed via switching control to receive maximum benefits from renewable energy sources and reduce the consumption of electricity from the grid. To support the optimum utilization of sustainable power, charging time and network stability, seven scenarios were developed for different interaction among the proposed micro-grid system and PHEVs. The proposed hybrid smart micro-grid system consists of three renewable energy sources: photovoltaic (PV) array controlled via an intelligent fuzzy control maximum power point subsystem, a fuel cell stack and a microturbine set controlled by proportional integral differential/proportional integral subsystems. A hybrid energy storage system (super-capacitor, battery storage bank and hydrogen) and residential load are also included in the proposed architecture. The hybrid smart micro-grid system is checked in terms of voltage regulation, frequency deviation and total harmonic distortion (THD). It was found that these are in limits according to the international standards. The simulations verify the feasibility of the proposed system and fulfill the requirement of vehicle-to-grid and grid-to-vehicle operations in a smart grid environment.

This paper provides a design and power control of hybrid grid power plant including a fuel cell, an electrolyzer, a microturbine and an ultra-capacitor which supplies power to support the grid and grid integrated typical domestic load. The proposed hybrid power plant is working under simple power control algorithm. According to the proposed algorithm, the fuel cell is the primary power source. The microturbine is added as a secondary system to confirm continuous power flow. The ultra-capacitor module is utilized as a backup and complement device to take care of the load following problems of fuel cell during transient. The electrolyzer is used as a dump load to generate hydrogen and to reduce power fluctuation during surplus power. A complete Matlab/Simulink model has been established to check the performance of the proposed system for the real load conditions. Simulation results show that the proposed system facilitates the grid stability, power quality and continuity.

The introduction of Plug-in Hybrid Electric Vehicles (PHEVs) in the transportation sector has facilitated the public in terms of reducing fossil fuels consumption and pollution problems. However, the growing popularity of PHEVs create new technical problems in the power system in terms of grid stability and upgradation of distribution transformers. To balance the extra load of PHEVs, a smart charging station based on wind output power sensing is presented in this paper. The required charging of PHEVs batteries is coordinately satisfied from wind and/or grid integrated wind generation. The operation of the proposed smart charging station is effectively completed in seven possible different interactions among the PHEVs, wind and the grid via different switching modes. Matlab/Simulink results are presented to confirm the effectiveness of the proposed charging station.

The widespread applications of plug-in hybrid electric vehicles (PHEVs) established that there will be a massive inrush of PHEVs by the end of this century. There is a rising risk that this anticipation in the number of PHEVs will impose an extra burden in demand, especially at peak times and, therefore, threaten the stability of existing power grids. To satisfy the additional load of PHEVs, a smart charging station (CS) facility based on PV output power sensing due to the variation in solar irradiance and temperature is presented in this paper. The power required to charge the PHEVs is effectively managed from grid-connected photovoltaic (PV) generation. To confirm the optimal utilization of available power, charging time and grid stability, five possible switching modes have been considered for different interaction among the PHEVs, PV and the grid. Simulation results confirm the effectiveness of the proposed CS facility. The proposed CS and their controllers are designed in MATLAB/Simulink.

The charging infrastructure plays a key role in the healthy and rapid development of the electric vehicle industry. This paper presents an energy management and control system of an electric vehicle charging station. The charging station (CS) is integrated to a grid-connected hybrid power system having a wind turbine maximum power point tracking (MPPT) controlled subsystem, photovoltaic (PV) MPPT controlled subsystem and a controlled solid oxide fuel cell with electrolyzer subsystem which are characterized as renewable energy sources. In this article, an energy management system is designed for charging and discharging of five different plug-in hybrid electric vehicles (PHEVs) simultaneously to fulfil the grid-to-vehicle (G2V), vehicle-to-grid (V2G), grid-to-battery storage system (G2BSS), battery storage system-to-grid (BSS2G), battery storage system-to-vehicle (BSS2V), vehicle-to-battery storage system (V2BSS) and vehicle-to-vehicle (V2V) charging and discharging requirements of the charging station. A simulation test-bed in Matlab/Simulink is developed to evaluate and control adaptively the AC-DC-AC converter of non-renewable energy source, DC-DC converters of the storage system, DC-AC grid side inverter and the converters of the CS using adaptive proportional-integral-derivate (AdapPID) control paradigm. The effectiveness of the AdapPID control strategy is validated through simulation results by comparing with conventional PID control scheme.