An intelligent controlling method for battery lifetime increment using state of charge estimation in PV-battery hybrid system

In a photovoltaic (PV)-battery integrated system, the battery undergoes frequent charging and discharging cycles that reduces its operational life and affects its performance considerably. As such, an intelligent power control approach for a PV-battery standalone system is proposed in this paper to improve the reliability of the battery along its operational life. The proposed control strategy works in two regulatory modes: maximum power point tracking (MPPT) mode and battery management system (BMS) mode. The novel controller tracks and harvests the maximum available power from the solar cells under different atmospheric conditions via MPPT scheme. On the other hand, the state of charge (SOC) estimation technique is developed using backpropagation neural network (BPNN) algorithm under BMS mode to manage the operation of the battery storage during charging, discharging, and islanding approaches to prolong the battery lifetime. A case study is demonstrated to confirm the effectiveness of the proposed scheme which shows only 0.082% error for real-world applications. The study discloses that the projected BMS control strategy satisfies the battery-lifetime objective for off-grid PV-battery hybrid systems by avoiding the over-charging and deep-discharging disturbances significantly

Real-Time Selective Harmonic Minimization for Multilevel Inverters Using Genetic Algorithm and Artificial Neural Network Angle Generation

This work approximates the selective harmonic elimination problem using Artificial Neural Networks (ANN) to generate the switching angles in an 11-level full bridge cascade inverter powered by five varying DC input sources. Each of the five full bridges of the cascade inverter was connected to a separate 195W solar panel. The angles were chosen such that the fundamental was kept constant and the low order harmonics were minimized or eliminated. A non-deterministic method is used to solve the system for the angles and to obtain the data set for the ANN training. The method also provides a set of acceptable solutions in the space where solutions do not exist by analytical methods. The trained ANN is a suitable tool that brings a small generalization effect on the angles\u27 precision and is able to perform in real time (50/60Hz time window)

Design and real-time implementation of data-driven adaptive wide-area damping controller for back-to-back VSC-HVDC

This paper proposes a data-driven adaptive wide-area damping controller (D-WADC) for back-to-back VSC-HVDC to suppress the low frequency oscillation in a large-scale interconnected power system. The proposed D-WADC adopts a dual-loop control structure to make full use of the active and reactive power control of VSC-HVDC to improve the damping of the power system. A data-driven algorithm named the goal representation heuristic dynamic programming is employed to design the proposed D-WADC, which means the design procedure only requires the input and output data rather than the mathematic model of the concerned power system. Thus, the D-WADC can adapt to the change of operating condition through online weight modification. Besides, the adaptive delay compensator (ADC) is added to effectively compensate the stochastic delay involved in the wide-area feedback signal. Case studies are conducted based on the simplified model of a practical power system and the 16-machine system with a back-to-back VSC-HVDC. Both the simulation and hardware-in-loop experiment results verify that the proposed D-WADC can effectively suppress the low-frequency oscillation under a wide range of operating conditions, disturbances, and stochastic communication delays

Performance Analysis of Photovoltaic Fed Distributed Static Compensator for Power Quality Improvement

Owing to rising demand for electricity, shortage of fossil fuels, reliability issues, high transmission and distribution losses, presently many countries are looking forward to integrate the renewable energy sources into existing electricity grid. This kind of distributed generation provides power at a location close to the residential or commercial consumers with low transmission and distribution costs. Among other micro sources, solar photovoltaic (PV) systems are penetrating rapidly due to its ability to provide necessary dc voltage and decreasing capital cost. On the other hand, the distribution systems are confronting serious power quality issues because of various nonlinear loads and impromptu expansion. The power quality issues incorporate harmonic currents, high reactive power burden, and load unbalance and so on. The custom power device widely used to improve these power quality issues is the distributed static compensator (DSTATCOM). For continuous and effective compensation of power quality issues in a grid connected solar photovoltaic distribution system, the solar inverters are designed to operate as a DSTATCOM thus by increasing the efficiency and reducing the cost of the system. The solar inverters are interfaced with grid through an L-type or LCL-type ac passive filters. Due to the voltage drop across these passive filters a high amount of voltage is maintained across the dc-link of the solar inverter so that the power can flow from PV source to grid and an effective compensation can be achieved. So in the thesis a new topology has been proposed for PV-DSTATCOM to reduce the dc-link voltage which inherently reduces the cost and rating of the solar inverter. The new LCLC-type PV-DSTATCOM is implemented both in simulation and hardware for extensive study. From the obtained results, the LCLC-type PV-DSTATCOM found to be more effective than L-type and LCL-type PV-DSTATCOM. Selection of proper reference compensation current extraction scheme plays the most crucial role in DSTATCOM performance. This thesis describes three time-domain schemes viz. Instantaneous active and reactive power (p-q), modified p-q, and IcosΦ schemes. The objective is to bring down the source current THD below 5%, to satisfy the IEEE-519 Standard recommendations on harmonic limits. Comparative evaluation shows that, IcosΦ scheme is the best PV-DSTATCOM control scheme irrespective of supply and load conditions. In the view of the fact that the filtering parameters of the PV-DSTATCOM and gains of the PI controller are designed using a linearized mathematical model of the system. Such a design may not yield satisfactory results under changing operating conditions due to the complex, nonlinear and time-varying nature of power system networks. To overcome this, evolutionary algorithms have been adopted and an algorithm-specific control parameter independent optimization tool (JAYA) is proposed. The JAYA optimization algorithm overcomes the drawbacks of both grenade explosion method (GEM) and teaching learning based optimization (TLBO), and accelerate the convergence of optimization problem. Extensive simulation studies and real-time investigations are performed for comparative assessment of proposed implementation of GEM, TLBO and JAYA optimization on PV-DSTATCOM. This validates that, the PV-DSTATCOM employing JAYA offers superior harmonic compensation compared to other alternatives, by lowering down the source current THD to drastically small values. Another indispensable aspect of PV-DSTATCOM is that due to parameter variation and nonlinearity present in the system, the reference current generated by the reference compensation current extraction scheme get altered for a changing operating conditions. So a sliding mode controller (SMC) based p-q theory is proposed in the dissertation to reduce these effects. To validate the efficacy of the implemented sliding mode controller for the power quality improvement, the performance of the proposed system with both linear and non-linear controller are observed and compared by taking total harmonic distortion as performance index. From the obtained simulation and experimentation results it is concluded that the SMC based LCLC-type PV-DSTATCOM performs better in all critical operating conditions

Sag effects on protection system in distributed generation grids

Distributed Generators (DGs) are sensible to voltage sags, so the protection devices must trip fast to disconnect the faulted part of the grid. The DG disconnection will not be desirable in the near future with a large penetration, so it will be necessary to lay down new requirements that should be based on avoiding unnecessary disconnections. Therefore, to prevent unnecessary tripping when inverter-based DGs are connected to the Medium Voltage (MV) grid, reliable and effective protection strategies need to be developed, considering the limited short-circuit current contribution of DG. The initial goal of this study is to employ different possible control strategies for a grid-connected inverter according to the Spanish grid code and to analyze the output voltage behavior during symmetrical and unsymmetrical voltage sags. The analytical development of the proposed strategies shows the impacts of the sag on currents, voltages, active and reactive powers. Another goal of this research is to propose a protection strategy based on Artificial Intelligence for a radial or ring distribution system with high DG penetration. The protection strategy is based on three different algorithms to develop a more secure, redundant, and reliable protection system to ensure supply continuity during disturbances in ring and radial grids without compromising system stability. In order to classify, locate and distinguish between permanent or transient faults, new protection algorithms based on artificial intelligence are proposed in this research, allowing network availability improvement disconnecting only the faulted part of the system. This research introduces the innovative use of directional relay based on a communication system and Artificial Neural Network (ANN). The first algorithm, Centralize algorithm (CE), collects the data from all the PDs in the grid in the centralized controller. This algorithm detects the power flow direction and calculates the positive-sequence current of all the PDs in the grid. Significant benefits of this system are that it consolidates the entire systems security into a single device, which can facilitate system security control. However, the CE will not pinpoint the exact location of the fault if there is any loss of information due to poor communication. Therefore, the systems redundancy can be improved by cooperating with a second algorithm, the Zone algorithm (ZO). ZO algorithm is based on zone control using peer-to-peer connectivity in the same line. The faulty line in that zone may be identified by combining the two PDs data on the same line. The most relevant advantage of this algorithm is its flexibility to adapt to any grid modification or disturbance, even if they are just temporary, unlike the CE, which is fixed to the existing grid configuration. The third protection algorithm, Local algorithm (LO), has been proposed without depending on the communication between the PDs; then, the protection system can work properly in case of a total loss of communication. Each PD should be able to detect if the fault is located in the protected line or another line by using only the local information of the PD. According to the type of fault and based on local measurements at each PD of abc voltages and currents, different algorithms will be applied depending on the calculation of the sequence components. The main advantage of this algorithm is the separate decision of each PD, and avoiding communication problems. In case of radial grids, both mechanical breakers and Solid State Relays (SSRs) are used to verify the protection strategies, and in the case of ring grids, mechanical breakers are used, due to the limitations in required voltage difference of SSR. The proposed protection algorithms are compared with conventional protections (Overcurrent and Differential) protections to validate the contribution of the proposed algorithms, especially in reconfigurable smart grids.El objetivo inicial de este estudio es emplear diferentes estrategias de control posibles para un inversor conectado a la red segun el código de red español y analizar el comportamiento de la tensión de salida durante caídas de tensión simétricas y asimétricas. El desarrollo analítico de las estrategias propuestas muestra los impactos de los huecos de tensión en las corrientes, tensiones, potencias activas y reactivas. Otro objetivo de esta investigación es proponer una estrategia de protecclón basada en lnteligencia Artificial para una red del Sistema de Distribución, radial o en anillo, con elevada penetración de Generación Distribuida. La estrategia de protección se basa en tres algoritmos diferentes para desarrollar un sistema de protección más seguro, redundante, y fiable, que asegure la continuidad de suministro durante perturbaciones en redes radiales o en anillo sin comprometer la estabilidad del sistema. Para clasificar, localizar y distinguir entre faltas permanentes o transitorias, se proponen en este trabajo nuevos algoritmos de protección basados en inteligencia artificial, permitiendo la mejora de la disponibilidad de la red, al desconectar sólo la parte del sistema en falta. Esta investigación introduce la innovación del uso del rele direccional basado en un sistema de comunicación y Redes Neuronales Artificiales (ANN). El primer algoritmo, Algoritmo Central (CE), recibe los datos de todos los PDs de la red en un control central. Este algoritmo detecta la dirección de flujo de cargas y calcula la corriente de secuencia positiva de todos los PDs de la red. El entrenamiento de ANNs incluye variaciones en la corriente de cortocircuito y la dirección del flujo de potencia en cada PD. Los beneficios mas significativos de este sistema son que concentra la seguridad total del sistema en un único dispositivo, lo que puede facilitar el control de la seguridad del sistema. Sin embargo, el CE no determinara con precisión la localización exacta de la falta si hay alguna perdida de información debida a una pobre comunicación. Por lo tanto, la redundancia del sistema se puede mejorar cooperando con un segundo algoritmo, el algoritmo de Zona (ZO). El algoritmo ZO se basa en un control de zona usando la conectividad entre dispositivos de protección de una misma línea. La línea en falta en esa zona puede identificarse combinando los datos de los dos PDs de la misma línea.. La ventaja mas relevante de este algoritmo es su flexibilidad para adaptarse a cualquier modificación de la red o perturbación, incluso si sólo son temporales, a diferencia del CE, que se ha adaptado para la configuración de la red existente. El tercer algoritmo de protección, algoritmo Local (LO), ha sido propuesto sin dependencia de la comunicación entre PDs; por lo tanto, el sistema de protección puede operar correctamente en el caso de una pérdida total de comunicación. Cada PD debe poder detectar si la falta esta ubicada en la línea protegida o en otra línea, utilizando sóIo la información local del PD. Según el tipo de falta, y en base a medidas locales en cada PD, de tensiones y corrientes abc, se aplican diferentes algoritmos en función del cálculo de las componentes simétricas. La principal ventaja de este algoritmo es la actuación por separado de cada PD, evitando los problemas de comunicación. En el caso de las redes radiales, se utilizan tanto interruptores mecánicos como réles de estado sóIido (SSR) para verificar las estrategias de protección, y en el caso de las redes en anillo se utilizan interruptores mecánicos, debido a las limitaciones de tensión para su conexión. Los algoritmos de protección propuestos se comparan con protecciones convencionales (Sobrecorriente y Diferencial) para validar la contribución de los algoritmos propuestos, especialmente en redes inteligentes reconfigurables.Postprint (published version

Optimal Control of Hybrid Systems and Renewable Energies

This book is a collection of papers covering various aspects of the optimal control of power and energy production from renewable resources (wind, PV, biomass, hydrogen, etc.). In particular, attention is focused both on the optimal control of new technologies and on their integration in buildings, microgrids, and energy markets. The examples presented in this book are among the most promising technologies for satisfying an increasing share of thermal and electrical demands with renewable sources: from solar cooling plants to offshore wind generation; hybrid plants, combining traditional and renewable sources, are also considered, as well as traditional and innovative storage systems. Innovative solutions for transportation systems are also explored for both railway infrastructures and advanced light rail vehicles. The optimization and control of new solutions for the power network are addressed in detail: specifically, special attention is paid to microgrids as new paradigms for distribution networks, but also in other applications (e.g., shipboards). Finally, optimization and simulation models within SCADA and energy management systems are considered. This book is intended for engineers, researchers, and practitioners that work in the field of energy, smart grid, renewable resources, and their optimization and control

Renewable Energy

Renewable Energy is energy generated from natural resources - such as sunlight, wind, rain, tides and geothermal heat - which are naturally replenished. In 2008, about 18% of global final energy consumption came from renewables, with 13% coming from traditional biomass, such as wood burning. Hydroelectricity was the next largest renewable source, providing 3% (15% of global electricity generation), followed by solar hot water/heating, which contributed with 1.3%. Modern technologies, such as geothermal energy, wind power, solar power, and ocean energy together provided some 0.8% of final energy consumption. The book provides a forum for dissemination and exchange of up - to - date scientific information on theoretical, generic and applied areas of knowledge. The topics deal with new devices and circuits for energy systems, photovoltaic and solar thermal, wind energy systems, tidal and wave energy, fuel cell systems, bio energy and geo-energy, sustainable energy resources and systems, energy storage systems, energy market management and economics, off-grid isolated energy systems, energy in transportation systems, energy resources for portable electronics, intelligent energy power transmission, distribution and inter - connectors, energy efficient utilization, environmental issues, energy harvesting, nanotechnology in energy, policy issues on renewable energy, building design, power electronics in energy conversion, new materials for energy resources, and RF and magnetic field energy devices