Search

Photovoltaic (PV) power generation is the fastest growing technology in the distributed generation sector. In addition to integrating renewable energies, current grid is required to be reliable, stable, and of high-quality power. The large-scale integration of PV power into the grid is bound up with problems of the safe operation of the grid, bringing new challenges to the GCC (Gulf Cooperation Council) system. The objective of this paper was to study and analyze the integration of large-scale PV facilities into the GCC power grid and to address their energy security and environmental challenges. A new simulation model was developed to analyze and investigate the impact of integrating large-scale solar PV facilities into the distribution power grid and to carry out transient stability analysis.

Nowadays, many electrical utilities are moving towards self-healing distribution grid. This is realized by adding to distribution system various sensors, intelligent electronic devices (IEDs), phasor measurement units (PMU), sequence of event recorders (SERs), reclosers, detectors, measurement units, automated controllers, and other automation equipment. Those elements provide a continuous stream of data to support grid performance and improve its reliability. Huge amount of data obtained from different smart grid sources satisfy all the Big Data (BD) characteristics. The success of future electric grid depends mainly on the effective utilization of the huge amount of the data flow. This mass of information is essential to make next generation electric grid more efficient, reliable, secure, independent, and supportive during normal conditions and contingencies. The self-healing grid requires a robust real-time computation system that monitors, processes, provides predictive analytics, performs data mining and statistics, and makes faster decisions of the diverse and complex data collected within the traditional and nextgeneration electric grid. This helps to detect, locate, and isolate various faults, reconfigure and reroute power of the distribution network to minimize service disruptions and outages.Implementation of self-healing control system is associated with big data utilization which is a persisting challenge. Computational complexity challenges is associated with processing huge amounts of data during operation of the electric power system. Therefore, this paper presents acomprehensive studies of the impact of implementing a smart real-time dynamic self-healing control strategy using BD process platform with deep learning technique on the distribution system for current grid and future smart grid. The deep learning technique is a subfield of machine learning. The deep learning is shown to be highly efficient solution for the analysis of massive amounts of data which is performed by discovering and utilizing available regularities in the inputs to help self-healing control system to network reconfiguration, and coordination of various distributed energy resourcesin the smart grid. The deep learning system complexity does notdepend on the number of grid buses, this is because the power flow solving time is approximately linear with respect to the number of system buses. However, the complexity of the system depends on the number of the system inputs. The Long Short Term Memory (LSTM) recurrent neural network will be used in modeling sequential data such as time series data. Such network has the ability to learn contextual information over the history of the input sequence. The BD analyticswill be used as a key to deal with the uncertainties and different sizes of structured and unstructured data. The advanced analytics techniques such as predictive analytics, in addition to data mining, statistics, and faster decisions making will be utilized for data coming from sensors within the traditional and next-generation electric grid. The studies performed are based on real-time monitoring and control of the network topology and operating conditions taking into account different power sources and hybrid renewable energy sources which usually have different characteristics on the electric power grid. Finally, the real-time implementations of the proposed system will achieve dynamic resources optimization, network reconfiguration, and optimum operation of power grid using LSTM with big data platform.

Degrading effect of energy generation from fossil fuel are extensively discussed and debated leading to paradigm shift to renewable energy generation. Energy generation from PV panels is the best alternative for state of Qatar which gets abundant sunlight throughout the year. Development of energy generation from PV panels helps in achieving the notion of “Energy Security”. Energy security refers to availability of reliable, cheap and quality power for consumption from customer point of view. Development in power electronics helps in achieving this idea by developing and operating converters circuits with good efficiency, efficacy, reliable, robust and free from maintenance. Encouraging the nurture and development of local energy suppliers will help in minimizing the cost of installation and maintenance. Including these economic constraints in the design of converters has become a crucial factor in developing industry oriented products through academic research. Suitability of several power converters for synchronizing the power generated from PV panels to utility grid. Recently developed Impedance source based converters are highly suitable for synchronizing the power generated from renewable energy to the utility grid. They eliminate the need for extra dc-dc converter by boosting the input voltage supplied from PV panels. Impedance source based converters are categorized as: Z Source Inverter and quasi Z Source Inverter (qZSI). qZSI is preferred due to its higher performance and continuous input current. Several methods are discussed in the literature to achieve boosting of input voltage. Inverter control requires modification in conventional Sine-Triangle compared based PWM. Operation of qZSI at different MPPT algorithms is also discussed. Cascaded qZSI operation to achieve higher power rating are also discussed. Implementation of advanced control techniques such as Model predictive control is also presented. Energy efficient qZSI achieved through different methods are also discussed. This paper presents novel control algorithm for control of qZSI as Front-End Converter (FEC) during non-sunshine hours. During sunshine hours, qZSI is controlled to inject active and reactive power into the grid. In absence of sunlight, qZSI can be operated as FEC to control reactive power management with the utility grid. To validate the proposed control algorithm, simulation results are presented for grid-connected qZSI powered from solar panel as shown in Fig. 1. Simulation results are formulated into following three sections: (a) Control of qZSI for active and reactive power management, (b) Transient response for qZSI to FEC transition and (c) Control of FEC for reactive power management.Control Algorithm: Control algorithm must satisfy the following requirements: a) When controlled as qZSI, i) Boosting of input voltage must be controlled to achieve the desired output rms voltage ii) Current injected into the grid can be at any power factor – unity, lagging or leading. b) Smooth transition from qZSI to FEC. c) When operated as FEC, i) DC Bus Voltage must be maintained constant and ii) Controlled reactive power management must be achieved. Proposed control algorithm is as shown in Fig. 2. It consists of two types of control blocks. Control blocks which are specific to a type of control algorithm and other which are common for both. Converter reference voltage generation and conventional Sine – Triangle comparison is common to control algorithms of both the inverters. For control of the inverter as qZSI, condition of Vin>Vth must be satisfied which means voltage generated from PV panels is sufficient for grid synchronization. During this mode, S1 and S3 are closed and S2 is opened. qZSI control consists of grid current control and dc bus voltage (Vdc) control. Active and reactive power demand is converted to current proportional and passed through PI controller to generate the converter voltage reference. DC Bus voltage controller gives the shoot-through duty cycle (D). Based on the value of D, shoot-through pulses are ORed with conventional pulses generated by sine-triangle comparison. When Vin>Vth is not satisfied, then the position of relays is changed. S1 and S3 are opened and S2 is closed. Due to this, the solar panel is disconnected from the inverter. The dc bus formed due to series connection of C1 and C2 must be controlled from the grid voltage. The dedicated control block shown in Fig. 2 for FEC generates the active current reference and add it up with required reactive current reference to give the grid current reference. This is passed through PI Controller to give the converter voltage reference. Conventional Sine-triangle comparison is performed to generate switching pulses.SIMULATION RESULTS To verify the control algorithm, the simulation results are shown in Fig. 3. Up to t = 2 sec, the inverter is operated as qZSI injecting controlled active power into the grid. At t = 2 sec, the relays are operated disconnecting the solar panel at the input and now inverter is controlled as FEC. Due to this, the dc bus voltage shoots up which is controlled with the control algorithm. To maintain the dc bus voltage, active current is drawn from the grid. Active current drawn is negligible compared to reactive power managed with the utility grid. Figure 3(a) shows the response of dc bus tracking during the operation. In qZSI mode, active power injection is controlled as shown in Fig. 3(b) and Fig. 3(c). When the inverter is controlled as FEC, reactive power absorbed and supplied are shown in Fig. 3(d) and Fig. 3(e) respectively.

Nowadays, new trends have made possible to reconfigure the traditional power systems in a more efficient way while world energy consumption is being continuously increased. To meet future energy demands, a more flexible, smart and configurable power system is required. To create such systems, microgrids are emerging and becoming a more attractive solution. The microgrid is a weak grid formed with different energy sources (renewable and conventional), energy storages, power electronics, power control systems and different loads. The microgrids are also particularly suitable for communities and regions where adequate renewable energy sources are available such as in Qatar. Therefore, the energy cost can be significantly decreased, energy security ensured, and energy production become environmental friendly with lower carbon footprints.The energy sources are the major part of the microgrid systems. As a result of increasing environmental awareness and as a consequence of the exhaustible nature of fossil fuels, renewable energy sources (RES) are playing an important role in modern microgrid systems. The RES based power generation systems have several advantages compared to the conventional power generation systems. Some of these advantages are sustainability, pollution-free operation and the possibility of being installed closer to the end users. In the last decades, especially the wind and photovoltaic (PV) based power generation systems have become more popular than other RESs. However, intermittent and stochastic nature of the wind and solar affect the stability, reliability and power quality of the microgrids. For instance, the PV based system cannot produce energy at night or during cloudy conditions, and wind-based systems generate energy that depends on the wind condition. To overcome these limitations, two or more (hybrid) RES, in addition to proper storage technologies, are needed to provide reliable, stable and continuous power to the customers. However, using different types of renewable energy sources in the same microgrid leads to complex control structure because these sources have different dynamic characteristics and need different control structures. Hence, a well-designed energy management and power flow control systems are essential to ensure the extraction of maximum power from these energy sources.Another part of the microgrid systems is an energy storage system (ESS) that plays a vital role to maintain stability and robustness as well as to improve the power quality of those systems. For these reasons, an effective ESS must characterize high power density as well as high energy density. In recent years, various types of battery technologies are used for energy storage systems. In spite of their maturity and variety, batteries still have limited lifecycle and poor power density, which is an important element for balancing the renewable based power generation systems. Thus, to support and improve the battery performance, lifetime and system cost, hybrid energy storage systems (HESS) can be suggested while comprising supercapacitors (SCs) and batteries. SCs have a number of advantages related to high efficiency (95%), high power density (up to 10000 W/kg),tolerance for deep discharges, and long life-cycle (500000 cycles at 100% depth-of-discharge). The combination of SCs and batteries allows to have the advantages of both solutions by obtaining high energy density, high power density, high life-cycle, high efficiency HESS and ensuring better power stability when interfacing with the grid. However, batteries and SCs have different charge and discharge characteristics. Therefore, a well-designed energy management and power flow control system is essential for that system to provide efficient operation and long life cycle.In the microgrid system, power flow should be bi-directional. For example, in case of insufficient energy, the utility grid can support the microgrid, vice versa, in case of exceed energy, microgrid can inject this energy to another microgrid(s) and/or to the utility grid. Therefore, in such systems, power electronic converters are important to allow the power flow between energy sources, energy storage devices, loads, and the utility grid. These power electronic converters not only allow to connect different electric devices together (whether they are loads, generators or storage devices), but also to provide suitable control for optimizing and protecting the whole system. Furthermore, to ensure the power connection between these different units, a direct current (dc) microgrid or an alternating current (ac) microgrid can be used. However, as mentioned above, most of these units are controlled by power converters, and each of these converters requires a dc-link. For this reason, one common dc-link can obtain appreciable savings for such systems.To ensure power flow between energy storage devices, energy sources, loads, and the utility grid (if needed), energy management algorithm is essential. A well-configured energy management algorithm increases energy efficiency, system stability, and battery life cycle. Therefore, the energy management algorithm and control structures must be defined properly according to system requirements. Several research activities focus on the energy management algorithm for HESS and power flow control algorithm. Types of the developed algorithms depend on the system power, storage techniques, types of energy sources, and operating modes such as grid-connected and/or standalone. However, most of these studies focused on only one microgrid and its control. In reality, more than one microgrid in the same region and different types of distributed generation units in these microgrids are common. Typically, the energy management control structure can be divided into three categories; centralized, distributed, and multi-level control structures. In all three cases, each energy sources and energy storage devices are controlled by the local controller to determine the optimal operating point locally. To increase the impact of the microgrids, the microgrids should be controlled by the same centralized controller. The microgrids also should have monitoring facilities to observe and reconfigure the energy consumption of the consumers.The main goal of this study is to design, develop and implement novel smart energy management and power control strategy for two grid-connected microgrids. The presented two microgrids have different charactersitics in terms of renewable energy sources and energy storage technologies. Thus, by the proposed smart energy management and power control strategy, the two different microgrids operate at their best efficiency points regardless of different conditions. They can also operate in bidirectional with each other and/or utility grid. For example, if there is exceed power in one of the microgrids, this energy will be transferred to the other microgrid and/or the utility grid, vice versa if there is insufficient power for the local loads, microgrids request power from the utility grid. This innovative feature of the study will be an effective solution for growing microgrids toward securing the increased power demand. Furthermore, this study presents condition monitoring to adjust and reconfigure the energy consumption of the consumers.To verify the proposed smart energy management and power flow control system, two laboratory-scale microgrids are designed and implemented. As shown in Fig. 1, the proposed prototype consists of two microgrids connected to the utility grid through the grid interactive inverters. These microgrids can also connect to each other through isolated bi-directional converter. In addition to these, each microgrid consists of four subsystems. (1) Wind energy conversion subsystem, (2) PV energy conversion subsystem, (3) Hybrid energy storage subsystem, and (4) Power electronics interface for AC load. Each subsystem has own local controller that can communicate with centralized controllers in order to increase system efficiency. Furthermore, whole system is controlled by a central controller to ensure optimal power flow between Microgrid I, Microgrid II and utility grid. The results of the study will not only benefit the energy management of multi microgrids but will also benefit the power grid operation especially the distribution system creating positive environmental impacts paving the road for future large-scale integration of the smart grid flexible load technology in Qatar.

Photovoltaic (PV) power generation is the fastest growing segment of distributed generation technologies. In addition, the need for reliable, stable and quality power is on the rise. Large-scale PV power connected to the grid contributes to the safe operation of the grid to bring new challenges in GCC. This study focuses on future large-scale PV energy system integration into the GCC power grid to address its energy security and environmental challenges. A new simulation model is developed to analyze and investigate the impact of integrating large-scale solar PV facilities into the distribution grid, and to carry out transient stability analysis.

Background & Objectives: Power converters have become over the last decades an enabling technology for PV applications. As demonstrated by scientific literature on the subject, current research efforts are directed toward the use of intermediate solutions between fully centralized and totally distributed (one inverter for each panel or strings of panels) PV grid connection architectures, for cost, reliability and maintenance concerns. Within this trend, topologies of utility scale PV inverters are moving towards Multi-Level Inverters (MLI), which provide better power quality, lighter passive filtering components, and potential to eliminate bulky line frequency transformers. However, in high performance grid-connected PV systems, the failure of the power electronics converters has very serious consequences on the overall system operation. In view of an optimal utilization of the generated electrical power and as per the general fault-tolerance requirements, deploying a power electronics converter capable of continuing to operate effectively in the presence of any single point failure is essential for such as systems. A large-scale solar plant needs to tolerate short-term malfunctions while maintaining the inverter connected to the grid and eventually provide grid support.One of the main advantages of Cascaded H-Bridge (CHB) MLI is the modularity. A CHB inverter employs many partially separate power modules (cells). If these cells equipped with a bypass switching device (external switch), then if one of the power modules fails it can be bypassed and operation can continue at reduced capacity. This even allows the faulty cell to be replaced by a new one without turning off the system. However, bypassing a module reduces the voltage and power available from the inverter. Then, the problem becomes how to obtain the highest power level with the remaining operative cells.Moreover, the association of a quasi Z-Source (qZS) network with a CHB MLI was deeply investigated in the last decade for grid-tied PV systems. This single-stage mix-topology is characterized by high-quality staircase output voltage with lower harmonic distortions, independent DC-link voltage compensation with the special voltage step-up/down function in a single-stage power conversion, and independent control of the power delivery with high reliability.By taking advantage of the high CHB inverter's modularity and flexibility of the qZS network in controlling the DC-link voltage, this research work proposes a new fault-tolerant control strategy for a reconfigurable grid-connected PV system. Methods: The system under study consists of a three-phase sixteen-cell CHB inverter where each module is fed by a qZS network (Fig. 1). The proposed combined controller achieves grid-tie current injection, DC-link voltage balance for all qZS-CHB inverter modules, anti-islanding protection, and fault-tolerant operation. The fault-tolerance feature is explored and discussed for two modulation techniques, which are the Level-Shifted Pulse Width Modulation (LSPWM) and Pulse Width Amplitude Modulation (PWAM). The proposed strategy can be easily implemented without extra hardware requirements. It takes into account key crucial factors for high-efficiency and reliability grid-connected PV systems such as; cost reduction (selection of high efficient and high performing qZS-CHB MLI topology), high power quality (grid current injection with unity power factor and low harmonics distortion), active anti-islanding protection (according to grid codes), and fault-tolerance (continuous operation during malfunction of some system components, which leads to the system reconfiguration). The fault-tolerant design is taking advantage of the large number of redundant switching states for the same output voltage level, which characterizes the selected cascaded topology. However, one can note that this redundancy is effective only for the intermediate levels output voltages, while the extreme levels (highest and lowest levels) are achieved by only one switching state. Accordingly, the proposed approach offers circuit reconfiguration (based on a measurement based fault detection strategy) and voltage stress adjustment to achieve a balanced line-to-line voltage when a fault occurs.Moreover, Battery Energy Storage Sources (BESS) are used as additional source of energy to support the grid at fault times. At normal operating conditions, the BESS are used to store the excess power available from the PV to avoid the over voltage state. At fault conditions, the BESS could be used to provide the amount of power lost because of the failure of one or more of the inverter modules.

With the unexpectedly fluctuating price of oil and the increasing threat of global climate change, Electric Vehicles (EVs) and renewable energy, particularly photovoltaic (PV) generation are becoming a viable option since they are not directly affected by the unstable oil price and yet are environmentally friendly.The PV generation has attracted attention in the “Solar Belt” countries, especially in Qatar where annual mean of global solar radiation (around 2000 kWh/m2/year) is large. The ample roof space on large residential and commercial buildings in Qatar and ability of the PV panel covers to protect vehicles from the exposure to sunshine makes the use of PV generation a natural choice.When connected to the grid, EV battery can behave as mobile energy storage making EV capable of either charging via grid-to-vehicle (G2V) as a “load” or discharging via vehicle-to-grid (V2G) or vehicle-to-building (V2B) as a “generator” or a dispatchable “back-up storage”. This bi-directional power flow feature provides flexibility needed to match variability of the renewable sources. The integration of electric vehicles and PV generation achieves two goals: a) it displaces the urban tailpipe pollution to the location where the power plants are, which typically in rural areas, and b) it allows energy storage when solar generation is active, which is mostly during the day, and discharging during the night, which allows better control of the generation variability.The objective of this paper is to discuss the methodology and technology needed to coordinate EVs' charging and PV-based generation in order to improve the performance of electric grid and at the same time reduce the environmental pollution. The paper focuses on three issues: a) integration of photovoltaic (PV) generation and EV charging stations through DC or AC bus, b) interfacing the DC or AC bus to the power system using advanced power electronics, and c) analysis of the impacts of the PVs and EVs on the power grid operation. The integration and interfacing will be optimized to support several utility applications: demand side management, outage management and asset management.The different modes of interfacing and integrating EVs and PVs into the grid are defined under different scenarios. As an example, the demand side management analysis scenarios under different power grid conditions are shown in Figs. 1 and 2. When power grid demand is low, and the valley filling is needed, EVs can be put into charging via G2V mode and combined with PV generation to keep the power balance between supply and demand, as shown in Fig. 1. When power grid suffers from the peak load and load shaving is needed, EVs can be turned to V2G mode, and combined with PV generation can be utilized to help relieve the demand burden, as shown in Fig. 2. A local battery storage may be used to store the extra power generated from PV or abundant energy from the EV battery to act as the grid interface. The potential impact of EV charging/discharging on the power grid demand profile is simulated. How the grid performance will be improved when PV generation is taken into consideration is investigated. With the interfacing of EV energy storage and PV generation, more energy will be available for flexible control to help grid flatten the demand curve and reduce the peak load. Based on the comparison and analysis, the integration and interfacing of EVs and PVs are coordinated to support the demand side management application.Proper power electronic solutions allowing bidirectional power flow with fast charging/discharging is also presented. The approach is toward finding optimal solutions in terms of decreasing the time of charging/discharging and adhering to the international standards related to grid side power quality issues. Many high-frequency AC link inverters have been proposed to realize such interface system in the past. One topology is considered promising. It has a bi-directional power flow feature. The inverter operates by first charging the link from the input and then discharging the stored energy to the output. The link inductor (L) stores the energy and the small capacitor (C) placed in parallel with (L) provides the soft switching. Between each power transfer mode there is a resonant mode at which the link inductor and capacitor resonate and no power is transferred. Despite its merits of having a small inductance size, and flexible multiport feature, this converter has two main drawbacks: a) High filtering needs especially at the input terminals, and b) Poor voltage boosting capabilities. These drawbacks are overcome in our proposed novel configuration shown in Fig. 3. Quasi-Z-Source Inverters (qZSIs) have many attractive advantages that are suitable for applying in PV systems and batteries. The use of qZSIs for this configuration has the following good features: Higher boosting capabilities.Lower harmonic content in input current.No filtering requirements at the input terminals.Features lower component (capacitor) rating. On the other hand, a one more power switch (S0) is added to allow bidirectional flow-in case of battery discharging.According to the battery state of charge, the PV available output power, and the grid availability, the following power flow schemes are possible:I. When PV is online: 1. From PV to Grid, while Battery is offline.2. From PV to (Grid + Battery).3. From (PV + Grid) to Battery.4. From (PV + Battery) to Grid. II. When PV is offline: 5. From Grid to Battery.6. From Battery to Grid. In case of outage of the power grid, the schemes will be directed to be as follows:I. When PV is online: 7. From PV to local loads, while Battery is offline.8. From PV to (local loads+ Battery).9. From (PV + Battery) to local loads. II. When PV is offline: 10. From Battery to local loads. The analysis of the impact of EVs and PVs on outage management includes establishing the simulation model of the typical outage condition profile, simulating the performance of PV generation to cover the interrupted load and establishing coordination methodology to make the best use of the energy from PVs and EVs. The analysis of the impact on asset management includes establishing the simulation model of the typical asset management process for existing utility assets, simulating the impact of bidirectional flow due to PV generation, and mitigation of negative asset effects such as overloading due to EV charging and establishing coordination algorithm for minimizing the overall impact of the integration of PV and EV. Evaluation of how transformer maintenance can be optimized under the new operating modes will be discussed.The results of the study will not only benefit the placement planning for EV charging stations and roof top PV installations to better utilize the electric grid resources, but will also benefit the power grid operation especially the distribution system creating positive environmental impacts paving the road for future large-scale integration of the smart grid flexible load technology in Qatar.

Electricity consumption has increased substantially over the last decade. According to the Gulf Research Center (2013), residential sector represents the largest portion (about 50%) of electricity consumption in the GCC region, due to substantial growth of electrical residential appliances. Therefore, we present a novel online smart residential load management system that is used to monitor and control power consumption of the loads for minimizing energy consumption, balancing electric power supply, reducing peak demand, and minimizing energy bill while considering residential customer preferences and comfort level. The presented online algorithm manages power consumption by assigning the residential load according to utilities power supply events. The input data to the management algorithm is set based on the categorized loads according to: importance (vital, essential, and non-essential electrical loads), electrical power consumption, electricity bill limitation, utilities power limitation, and load priority. The data are processed and fed to the presented algorithm, which accurately manages the power of Dwelling Loads using external controlled disconnectors. The proposed online algorithm yields to improve the overall grid efficiency and reliability, especially during the demand response periods. Simulation results demonstrate the validity of the proposed algorithm.

In today's world, the need for more energy seems to be ever increasing. The high cost and limited sources of fossil fuels, in addition to the need to reduce greenhouse gasses, have made renewable energy sources (RES) attractive in today's world economy. However, the fluctuating and intermittent nature of these RES causes variations of power flow that can significantly affect the stability and operation of the electrical grid. In addition, the power output of these RES is not as easy to adjust to changing demand cycles as the output from the traditional power sources. To overcome these problems, energy from these RES must be stored when excess is produced and then released, when production levels are less than the required demand. Therefore, in order for RES to become completely reliable as primary sources of energy, energy storage systems (ESS) is a crucial factor. The impact of the ESS in future grid is receiving more attention than ever from system designers, grid operations and regulators. Energy storage technologies have the potential to support our energy system's evolution, they can be used for multiple applications, such as: energy management, backup power, load leveling, frequency regulation, voltage support, and grid stabilization. In this work, an overview of the current and future energy storage technologies used for electric power applications is carried out. Furthermore, an assessment of the dynamic performance of energy storage technologies for the stabilization and control of the power flow of emerging smart grid will be presented. The EES can enhance the operation security and ensure the continuity of energy supply in future smart grids.

The increasing price of conventional fossil fuel and the need to reduce green-house gas emissions have prompted the adoption of clean electrical energy generation sources. The abundance of renewable energy, particularly solar and wind, over the world combined with increasing efficiency of the Photovoltaic (PV) cells has led to reducing cost per kWh of generated green electricity and created potential for establishing high power renewable energy systems at medium voltage scale. The design, fabrication, installation and testing of a large PV power generation systems still, however, pose great challenge in term of obtaining highly-efficient, highly-reliable, transformer-less with buck/boost voltage capabilities, and reduced cost and maintenance. This work is aimed to present the status of renewable energy installation worldwide and to discuss grid connected issues. The increasing penetration of PV energy has motivated the establishment of grid connection requirements. The requirements for power injection should be clearly defined: The grid requires sinusoidal AC with stable voltage and frequency, and the harmonics content should be kept within limits as addressed in various standards, codes, and guidelines. Hence, PV plants connected to the public grid give rise to two highly important requirements: the power quality of the grid should not be reduced when solar power is fed into the grid; and personal safety must be ensured in the event of mains interference. Large PV systems are usually tied at high-voltage level. Such systems consist of generation, transmission, distribution phases, and consumers at the end [1]. This proposed work will discuss the status of renewable energy worldwide installation at high level and will [resent the standards and regulations for the connection of PV renewable energy sources to electric grid. Different technical and non-technical issues related to the installation and the operation of such systems will be carefully discussed, analyzed and related problems investigated. There is a pressing need to review and to evaluate the design and operational constraints of large-scale renewable energy systems, therefore this work aims to discuss and open-up new avenues in this direction. References [1] H. Abu-Rub, M. Malinowski, K. Al-Haddad, Power Electronics for Renewable Energy Systems, Transportation and Industrial Applications. Hoboken, NJ: John Wiley & Sons, 2014 (in press).

Realization of multilevel inverters for multiphase high power AC drives with open-end windings is presented in this paper, with a specific case of five-phase five-level inverter configurations. The five-level voltage profile is realized by feeding both ends of the stator windings using a three-level five-phase flying capacitor inverter on one side and a five-phase two-level inverter on the other side. The flying capacitors' voltages are effectively balanced by utilizing the switching state redundancies. The capacitor voltages can be balanced at any modulation index, irrespective of the operating power factor. The operation of a drive at a higher voltage is preferred in many applications due to the advantages such as higher efficiency and reduction in size and weight. However, this demands higher DC link voltage in many topologies. The DC voltage magnitude required in the proposed topology is half of that required in the conventional multilevel neutral point clamped (NPC) topology, for a given output voltage. Hence, the scheme proposed in this paper can be advantageous in such applications where there is a limitation in obtaining DC voltage sources of higher magnitudes, such as in electric and hybrid electric vehicles. Another attractive feature of this topology is the enhanced reliability, as it is possible to operate the drive with half power even if any one of the inverters completely fails. The number of active switches used in this topology is lesser than that in equivalent five-level NPC inverters. Unlike the NPC inverter, this topology does not require any clamping diodes and is also free from issues like neutral point fluctuations. A carrier based pulse width modulation (PWM) technique combined with a hysteresis controller for balancing of the capacitors' voltages is used for the control of the inverter. The proposed drive topology can be applied to high power AC drives such as in oil and gas industries, electric/hybrid electric vehicles, ship propulsion, traction etc. The simulation and experimental results support the proposed idea.

I. Introduction Photovoltaic (PV) energy generation has been one of the most active research areas in the past decades, because it is essentially inexhaustible and environmental friendly with respect to the conventional energy sources. However, nowadays the higher initial installation cost, lower efficiency and reliability of the PV system still block its widespread application. To overcome these problems, our project focuses on a novel PV system, including the novel PV interface inverter by combination of the battery into the quasi-Z-source inverter (qZSI). All of these aim at controlling output power of the PV system to the grid flexibly, thus, to extremely improve the scientific and economic developments of Qatar. II. Methods And Results This paper proposes the charging and discharging control of qZSI with battery for PV power generation system. 1) To monitor the battery state of charge (SOC), the output power-based SOC control is designed. 2) The closed-loop control of shoot-through duty rati...

Condition monitoring and fault diagnostics of electrical machines are extremely important in any industrial setup. In some applications, such as the oil and gas industries, production units, power generation, refining and milling, the failure of critical equipment like generators, milling machines, motors, fans and pumps costs millions of dollars in reduced output, emergency maintenance costs and lost revenues. However, in the utility industry, malfunctioning of the electrical machinery is not acceptable not only because of its financial damage, but also the threat that is caused by a sudden failure or malfunctioning of the part. The research is aimed at developing a system that will detect incipient failures of electrical machinery before actual failure results in system or industrial process disruption. The objective is to make repeatable decisions based on complex relationships between large amounts of measured and estimated data. The condition of the machines will be available at all times, and the incipient detection and predictive maintenance system will provide an accurate prediction of any potential failure on demand. Two techniques are under consideration, the first one is based on pattern recognition that analyzes electrical measurements of electrical components to characterize the profile of electric machines at the beginning of life for a ‘baseline signature’. Then, at regular intervals, or when a failure is suspected, the technique will be used to derive the present profile and compare it with the ‘baseline’ profile. The other method is based on adaptive neuro-fuzzy inference system (ANFiS). The synergy of artificial neural network and expert fuzzy logic yield ANFiS that is a simple and effective diagnostic tool not requiring precise mathematical models of the motor and controllers. The proposed ANFiS controller will provide qualitative and quantitative knowledge of the health of a rotating machine through valid heuristic reasoning. Various types of electrical and mechanical faults will be investigated and the technique based on expert knowledge (ANFiS system) will be utilized for incipient fault diagnostics.