Power Quality Enhancement in Hybrid Photovoltaic-Battery System based on three–Level Inverter associated with DC bus Voltage Control

This modest paper presents a study on the energy quality produced by a hybrid system consisting of a Photovoltaic (PV) power source connected to a battery. A three-level inverter was used in the system studied for the purpose of improving the quality of energy injected into the grid and decreasing the Total Harmonic Distortion (THD). A Maximum Power Point Tracking (MPPT) algorithm based on a Fuzzy Logic Controller (FLC) is used for the purpose of ensuring optimal production of photovoltaic energy. In addition, another FLC controller is used to ensure DC bus stabilization. The considered system was implemented in the Matlab /SimPowerSystems environment. The results show the effectiveness of the proposed inverter at three levels in improving the quality of energy injected from the system into the grid.Peer reviewedFinal Published versio

A Hybrid Microgrid Operated by PV Wind and Diesel Generator with Advanced Control Strategy

All for a local area that gets its power from a solitary diesel generator (DG), this examination presents an efficient power energy choice for a microgrid. A twin feed enlistment generator draws power from a sun oriented photovoltaic (PV) cluster and the breeze to run this microgrid's electrical gear (DFIG). Two voltage source converters (VSCs) are sequentially coupled on the rotor side of the DFIG and share a DC transport that at last prompts the photovoltaic modules. Likewise associated with a similar DC transport as the DFIG stator is a bidirectional buck/help DC converter and a battery energy capacity (BES) to retain any overflow power. Most extreme energy collecting from the breeze and sun is accomplished by regulation of the bidirectional buck/help DC converter and the rotor side VSC. A changed form of the irritate and notice (P&O) technique is introduced for of expanding the energy result of a PV framework. Endeavors are being made to change VSC on the heap side to further develop DG's eco-friendliness. The ideal fuel-use reference DG power result may now be resolved utilizing a new, more broad methodology. Using the Sim Power Systems toolbox in MATLAB, we model and simulate many scenarios, including fluctuating wind speeds, fluctuating insolation, the impact of fluctuating load conditions on a bidirectional converter, and an unbalanced nonlinear load linked at the point of common coupling (PCC). Finding sinusoidal and balanced DG and DFIG stator currents

Power Management Strategies for a Wind Energy Source in an Isolated Microgrid and Grid Connected System

This thesis focuses on the development of power management control strategies for a direct drive permanent magnet synchronous generator (PMSG) based variable speed wind turbine (VSWT). Two modes of operation have been considered: (1) isolated/islanded mode, and (2) grid-connected mode. In the isolated/islanded mode, the system requires additional energy sources and sinks to counterbalance the intermittent nature of the wind. Thus, battery energy storage and photovoltaic (PV) systems have been integrated with the wind turbine to form a microgrid with hybrid energy sources. For the wind/battery hybrid system, several energy management and control issues have been addressed, such as DC link voltage stability, imbalanced power flow, and constraints of the battery state of charge (SOC). To ensure the integrity of the microgrid, and to increase its flexibility, dump loads and an emergency back-up AC source (can be a diesel generator set) have been used to protect the system against the excessive power production from the wind and PV systems, as well as the intermittent nature of wind source. A coordinated control strategy is proposed for the dump loads and back up AC source. An alternative control strategy is also proposed for a hybrid wind/battery system by eliminating the dedicated battery converter and the dump loads. To protect the battery against overcharging, an integrated control strategy is proposed. In addition, the dual vector voltage control (DVVC) is also developed to tackle the issues associated with unbalanced AC loads. To improve the performance of a DC microgrid consisting wind, battery, and PV, a distributed control strategy using DC link voltage (DLV) based control law is developed. This strategy provides simpler structure, less frequent mode transitions, and effective coordination among different sources without relying on real-time communication. In a grid-connected mode, this DC microgrid is connected to the grid through a single inverter at the point of common coupling (PCC). The generated wind power is only treated as a source at the DC side for the study of both unbalanced and balanced voltage sag issues at a distribution grid network. The proposed strategy consists of: (i) a vector current control with a feed-forward of the negative-sequence voltage (VCCF) to compensate for the negative sequence currents; and (ii) a power compensation factor (PCF) control for the VCCF to maintain the balanced power flow between the system and the grid. A sliding mode control strategy has also been developed to enhance the overall system performance. Appropriate grid code has been considered in this case. All the developed control strategies have been validated via extensive computer simulation with realistic system parameters. Furthermore, to valid developed control strategies in a realistic environment in real-time, a microgrid has been constructed using physical components: a wind turbine simulator (WTS), power electronic converters, simulated grid, sensors, real-time controllers and protection devices. All the control strategies developed in this system have been validated experimentally on this facility. In conclusion, several power management strategies and real-time control issues have been investigated for direct drive permanent magnet synchronous generator (PMSG) based variable speed wind turbine system in an islanded and grid-connected mode. For the islanded mode, the focuses have been on microgrid control. While for the grid-connected mode, main consideration has been on the mitigation of voltage sags at the point of common coupling (PCC)

Electric Vehicles Charging Stations’ Architectures, Criteria, Power Converters, and Control Strategies in Microgrids

Electric Vehicles (EV) usage is increasing over the last few years due to a rise in fossil fuel prices and the rate of increasing carbon dioxide (CO2) emissions. The EV charging stations are powered by the existing utility power grid systems, increasing the stress on the utility grid and the load demand at the distribution side. The DC grid-based EV charging is more efficient than the AC distribution because of its higher reliability, power conversion efficiency, simple interfacing with renewable energy sources (RESs), and integration of energy storage units (ESU). The RES-generated power storage in local ESU is an alternative solution for managing the utility grid demand. In addition, to maintain the EV charging demand at the microgrid levels, energy management and control strategies must carefully power the EV battery charging unit. Also, charging stations require dedicated converter topologies, control strategies and need to follow the levels and standards. Based on the EV, ESU, and RES accessibility, the different types of microgrids architecture and control strategies are used to ensure the optimum operation at the EV charging point. Based on the above said merits, this review paper presents the different RES-connected architecture and control strategies used in EV charging stations. This study highlights the importance of different charging station architectures with the current power converter topologies proposed in the literature. In addition, the comparison of the microgrid-based charging station architecture with its energy management, control strategies, and charging converter controls are also presented. The different levels and types of the charging station used for EV charging, in addition to controls and connectors used in the charging station, are discussed. The experiment-based energy management strategy is developed for controlling the power flow among the available sources and charging terminals for the effective utilization of generated renewable power. The main motive of the EMS and its control is to maximize usage of RES consumption. This review also provides the challenges and opportunities for EV charging, considering selecting charging stations in the conclusion.publishedVersio

Maximum power point tracking (MPPT) of a scale-up pressure retarded osmosis (PRO) osmotic power plant

This paper presents a maximum power point tracking (MPPT) of a scale-up pressure retarded osmosis (PRO) based osmotic power generator. Inspired by the well-known MPPT in photovoltaic (PV) array, two algorithms, perturb & observe (P&O) and incremental mass-resistance (IMR) method, are investigated. Using a series of simulations, both the algorithms are demonstrated to be capable of tracking the maximum power point (MPP) and capturing the transitions between varied MPPs due to the fluctuations of operating temperature. However, in both cases the trade-off between the rise time and the oscillation is found requiring further consideration on the selection of the step-size for perturbation pressure or incremental pressure. In order to improve the performance of the MPPT, furthermore, an optimum model-based controller (OMC) is used to estimate the initial optimum pressure for the MPPT in a scale-up PRO process. It is found that with OMC, the performance of the MPPT is improved significantly. Finally, a strategy to operate and coordinate the MPPT and OMC to deal with the rapid variations of the salinities are proposed and evaluated in terms of individual variation of the concentration or flow rate and co-variation of the both. The simulations demonstrate the preferred performance of the proposed strategy to adjust the operation subject to the rapid changes of the salinities

Power Quality Enhancement in Electricity Grids with Wind Energy Using Multicell Converters and Energy Storage

In recent years, the wind power industry is experiencing a rapid growth and more wind farms with larger size wind turbines are being connected to the power system. While this contributes to the overall security of electricity supply, large-scale deployment of wind energy into the grid also presents many technical challenges. Most of these challenges are one way or another, related to the variability and intermittent nature of wind and affect the power quality of the distribution grid. Power quality relates to factors that cause variations in the voltage level and frequency as well as distortion in the voltage and current waveforms due to wind variability which produces both harmonics and inter-harmonics. The main motivation behind work is to propose a new topology of the static AC/DC/AC multicell converter to improve the power quality in grid-connected wind energy conversion systems. Serial switching cells have the ability to achieve a high power with lower-size components and improve the voltage waveforms at the input and output of the converter by increasing the number of cells. Furthermore, a battery energy storage system is included and a power management strategy is designed to ensure the continuity of power supply and consequently the autonomy of the proposed system. The simulation results are presented for a 149.2 kW wind turbine induction generator system and the results obtained demonstrate the reduced harmonics, improved transient response, and reference tracking of the voltage output of the wind energy conversion system.Peer reviewedFinal Accepted Versio

Power Flow Control of the Grid-Integrated Hybrid DG System using an ARFMF Optimization

A power flow control scheme for a grid-integrated Hybrid DG System (HDGS) is presented in this work, utilizing an advanced random forest algorithm combined with the moth-flame optimization (ARFMF) approach. The proposed control scheme combines the random forest algorithm (RFA) and moth-flame optimization algorithm (MFO) for consolidated execution. The random forest algorithm (RFA), an AI technique, is well-suited for nonlinear systems due to its accurate interpolation and extrapolation capabilities. It is an ensemble learning method that combines multiple decision trees to make predictions. The algorithm constructs a forest of decision trees and aggregates their predictions to produce the final output. The moth-flame optimization (MFO) process is a meta-heuristic optimization procedure inspired by the transverse orientation of moths in nature. It improves initial random solutions and converges to superior positions in the search area. Similarly, the MFO is effective in nonlinear systems as it accurately interpolates and extrapolates arbitrary information. In the proposed technique, the RFA performs the calculation process to determine precise control gains for the HDGS through online implementation based on power variation between the source side and the load side. The recommended dataset is used to implement the AI approach for online execution, reducing optimization process time. The learning process of the RFA is guided by the MFO optimization algorithm. The MFO technique defines the objective function using system information based on equal and unequal constraints, including the accessibility of renewable energy sources, power demand, and state of charge (SOC) of storage systems. Storage devices such as batteries stabilize the energy generated by renewable energy systems to maintain a constant, stable output power. The proposed model is implemented on the MATLAB/Simulink platform, and its execution is compared to previous approaches

Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

In the field of wind turbine performance optimization, many techniques are employed to track the maximum power point (MPPT), one of the most commonly used MPPT algorithms is the perturb and observe technique (PO) because of its ease of implementation. However, the main disadvantage of this method is the lack of accuracy due to fluctuations around the maximum power point. In contrast, MPPT control employing neural networks proved to be an effective solution, in terms of accuracy. The contribution of this work is to propose a hybrid maximum power point tracking control using two types of MPPT control: neural network control (NNC) and the perturbation and observe method (PO), thus the PO method can offer better performance. Furthermore, this study aims to provide a comparison of the hybrid method with each algorithm and NNC. At the resulting duty cycle of the 2 methods, we applied the combination operation. A DC-DC boost converter is subjected to the hybrid MPPT control.  This converter is part of a wind energy conversion system employing a permanent magnet synchronous generator (PMSG). The chain is modeled using MATLAB/Simulink software. The effectiveness of the controller is tested at varying wind speeds. In terms of the Integral time absolute error (ITAE), using the PO technique, the ITAE is 9.72. But, if we apply the suggested technique, it is smaller at 4.55. The corresponding simulation results show that the proposed hybrid method performs best compared to the PO method. Simulation results ensure the performance of the proposed hybrid MPPT control.

Modeling and Lyapunov-designed based on adaptive gain sliding mode control for wind turbines

In this paper, modeling and the Lyapunov-designed control approach are studied for the Wind Energy Conversion Systems (WECS). The objective of this study is to ensure the maximum energy production of a WECS while reducing the mechanical stress on the shafts (turbine and generator). Furthermore, the proposed control strategy aims to optimize the wind energy captured by the wind turbine operating under rating wind speed, using an Adaptive Gain Sliding Mode Control (AG-SMC). The adaptation for the sliding gain and the torque estimation are carried out using the sliding surface as an improved solution that handles the conventional sliding mode control. Furthermore, the resultant WECS control policy is relatively simple, meaning the online computational cost and time are considerably reduced. Time-domain simulation studies are performed to discuss the effectiveness of the proposed control strateg