Frequency and voltage partitioning in presence of renewable energy resources for power system (example: North Chile power network)

This paper investigates techniques for frequency and voltage partitioning of power network based on the graph-theory. These methods divide the power system into distinguished regions to avoid the spread of disturbances and to minimize the interaction between these regions for frequency and voltage control of power system. In case of required active and reactive power for improving the performance of the power system, control can be performed regionally instead of a centralized controller. In this paper, renewable energy sources are connected to the power network to verify the effect of these sources on the power systems partitioning and performance. The number of regions is found based on the frequency sensitivity for frequency partitioning and bus voltage for voltage partitioning to disturbances being applied to loads in each region. The methodology is applied to the north part of Chile power network. The results show the performance and ability of graph frequency and voltage partitioning algorithm to divide large scale power systems to smaller regions for applying decentralized controllers.Peer ReviewedPostprint (published version

Internet of Things Applications as Energy Internet in Smart Grids and Smart Environments

Energy Internet (EI) has been recently introduced as a new concept, which aims to evolve smart grids by integrating several energy forms into an extremely flexible and effective grid. In this paper, we have comprehensively analyzed Internet of Things (IoT) applications enabled for smart grids and smart environments, such as smart cities, smart homes, smart metering, and energy management infrastructures to investigate the development of the EI based IoT applications. These applications are promising key areas of the EI concept, since the IoT is considered one of the most important driving factors of the EI. Moreover, we discussed the challenges, open issues, and future research opportunities for the EI concept based on IoT applications and addressed some important research areas

Flatness-Based Control Methodologies to Improve Frequency Regulation in Power Systems with High Penetration of Wind

To allow for high penetration of distributed generation and alternative energy units, it is critical to minimize the complexity of generator controls and to minimize the need for close coordination across regions. We propose that existing controls be replaced by a two-tier structure of local control operating within a global context of situational awareness. Flatness as an extension of controllability for non-linear systems is a key to enabling planning and optimization at various levels of the grid in this structure. In this study, flatness-based control for: one, Automatic Generation Control (AGC) of a multi-machine system including conventional generators; and two, Doubly fed Induction Machine (DFIG) is investigated. In the proposed approach applied to conventional generators, the local control tracks the reference phase, which is obtained through economic dispatch at the global control level. As a result of applying the flatness-based method, an $n$ machine system is decoupled into n linear controllable systems in canonical form. The control strategy results in a distributed AGC formulation which is significantly easier to design and implement relative to conventional AGC. Practical constraints such as generator ramping rates can be considered in designing the local controllers. The proposed strategy demonstrates promising performance in mitigating frequency deviations and the overall structure facilitates operation of other non-traditional generators. For DFIG, the rotor flux and rotational speed are controlled to follow the desired values for active and reactive power control. Different control objectives, such as maximum power point tracking (MPPT), voltage support or curtailing wind to contribute in secondary frequency regulation, can be achieved in this two-level control structure

Frequency regulation for power systems with renewable energy sources

Both the increasing penetration of renewable sources and their participation in the production of power in the electrical system require a more comprehensive analysis of the dynamic behavior of the grid frequency regulation structure. In this sense, this work presents the use of Control Sensitivity Functions to describe the dynamical characteristics of both primary and secondary control loops in frequency regulation. Bode plots are employed as a visualization and analysis tool. These sensitivity functions are applied to study the behavior of the power system with the contribution of wind turbines through the inertia emulation techniques. In this regard, the effects of inertia variations in frequency control are addressed for power systems under the integration of wind units. The transfer functions of the system are obtained starting from a linearized wind turbine model. The mathematical relationships are formulated to analyze the sensitivity and stability regarding inertia coefficient H. These expressions are then verified through simulation of several cases under different stability conditions and disturbances in wind speed and loadResumen: Tanto la creciente penetración de fuentes renovables de energía como su participación en el despacho de suministro energético en el sistema de potencia requiere un análisis completo del comportamiento dinámico de la estructura de regulación de frecuencia. En este sentido, esta tesis presenta el uso de las Funciones de Sensibilidad de Control para describir las características dinámicas de los lazos primario y secundario de regulación de frecuencia en sistemas de potencia, utilizando diagramas de Bode como herramienta de visualización y análisis. Estas funciones de sensibilidad se aplican en el estudio del comportamiento dinámico de la regulación en frecuencia con contribuciones de turbinas eólicas a través de las técnicas de emulación inercial. Bajo este escenario, los efectos de las incertidumbres o variaciones en la inercia son estudiados desde la integración de las turbinas eólicas en la estructura de control. Partiendo de una representación lineal del sistema, se proponen las formulaciones matemáticas necesarias para analizar la sensibilidad y la estabilidad del sistema con respecto a los cambios en la inercia. Estas expresiones se verifican a través de simulación de varios casos bajo diferentes condiciones de estabilidad y perturbaciones en la velocidad del viento y en la carga del sistemaDoctorad

Load frequency control for multi-area interconnected power system using artificial intelligent controllers

Power system control and stability have been an area with different and continuous challenges in order to reach the desired operation that satisfies consumers and suppliers. To accomplish the purpose of stable operation in power systems, different loops have been equipped to control different parameters. For example, Load Frequency Control (LFC) is introduced to maintain the frequency at or near its nominal values, this loop is also responsible for maintaining the interchanged power between control areas interconnected via tie-lines at scheduled values. Other loops are also employed within power systems such as the Automatic Voltage Regulator (AVR). This thesis focuses on the problem of frequency deviation in power systems and proposes different solutions based on different theories. The proposed methods are implemented in two different power systems namely: unequal two-area interconnected thermal power system and the simplified Great Britain (GB) power system. Artificial intelligence-based controllers have recently dominated the field of control engineering as they are practicable with relatively low solution costs, this is in addition to providing a stable, reliable and robust dynamic performance of the controlled plant. They professionally can handle different technical issues resulting from nonlinearities and uncertainties. In order to achieve the best possible control and dynamic system behaviour, a soft computing technique based on the Bees Algorithm (BA) is suggested for tuning the parameters of the proposed controllers for LFC purposes. Fuzzy PID controller with filtered derivative action (Fuzzy PIDF) optimized by the BA is designed and implemented to improve the frequency performance in the two different systems under study during and after load disturbance. Further, three different fuzzy control configurations that offer higher reliability, namely Fuzzy Cascade PI − PD, Fuzzy PI plus Fuzzy PD, and Fuzzy (PI + PD), optimized by the BA have also been implemented in the two-area interconnected power system. The robustness of these fuzzy configurations has been evidenced against parametric uncertainties of the controlled power systems Sliding Mode Control (SMC) design, modelling and implementation have also been conducted for LFC in the investigated systems where the parameters are tuned by the BA. The mathematical model design of the SMC is derived based on the parameters of the testbed systems. The robustness analysis of the proposed SMC against the controlled systems’ parametric uncertainties has been carried out considering different scenarios. Furthermore, to authenticate the excellence of the proposed controllers, a comparative study is carried out based on the obtained results and those from previously introduced works based on classical PID tuned by the Losi Map-Based Chaotic Optimization Algorithm (LCOA), Fuzzy PID Optimized by Teaching Learning-Based Optimization (TLBO

Real-time dispatch and frequency control in an electricity grid with volatile generation sources and loads

The growing awareness of depleting fossil fuels and climate change has motivated the electricity supply industry to constantly explore sustainable and scalable alternatives. Considering the innovation in generation technology alone, globally, the focus is on the integration of Renewable Energy Sources (RESs), like solar and wind-based power generation into the electricity grid. At the same time, deregulation has opened up various options to consumers to optimise their own energy usage. However, both of these trends have started to transform the paradigm of power system operation. Dealing with the highly volatile nature of RESs and unpredictable load behaviour, has become a significant issue for grid operators. Today, the supply intermittency and uncertainty of RESs and load is associated with a higher forecast error. Moreover, this supply uncertainty varies at different time scales, with higher levels at the time scale of generation planning, (i.e. a day), and at reduced levels on the time scale of control, (i.e., in seconds). Nevertheless, even in Real-Time (RT), the forecast error coupled with sudden supply fluctuations can be large enough to impact the electricity demand and supply balance significantly, which leads to poor frequency stability and increased operational cost. In view of these issues frequency regulation services need to be more flexible and capable of fast action to ensure system stability, and holistically designed to ensure cost optimality. Apart from the uncertainty in demand and supply, the additional important factor to the sub-optimal operational cost is a hierarchical approach of decision making such as centralised Economic Dispatch (ED) for generation allocation followed by local Automatic Generation Control (AGC) for frequency regulation. In cognisance of these issues, the main objectives of this PhD project are to develop new intelligent distributed control strategies for frequency regulation. These methodologies are developed to improve the frequency response under volatile generation and load conditions by using faster resources for regulation services, and to achieve optimal electricity dispatch under system constraints in RT. These optimal control methods can potentially also defer additional infrastructure investments and maximise the utilisation of RESs and the interconnection network. The research is categorised into four sections. As a first step to algorithm development, an Embedded Integrator based Distributed Model Predictive Control (EIDMPC) scheme is developed, which utilises a fast acting Demand Response (DR) alongside Governor Response (GR) for frequency control. A system model for each control area is first developed with DR and GR as manipulated input variables and the Area Control Error (ACE) as an output control variable. Then an EIDMPC scheme is formulated to obtain an optimal linear feedback control law to achieve a high computation speed, and the closed loop stability is assessed. The dependence of EIDMPC on the communication network is discussed and a model to handle communication loss is also given. The simulation studies are conducted on a two area interconnected power system in MATLAB, and results are discussed, showing benefits of the EIDMPC scheme. The second algorithm development addresses cost optimisation. Here, a centralised optimisation problem is formulated for an interconnected power system, which combines the objectives of Economic Dispatch (ED) and Automatic Generation Control (AGC) in view of the network flow thermal limits. A distributed AGC law is derived from the formulation using a log-barrier approximation approach, which converges to a steady-state solution with minimal distance from that of the centralised formulation. This AGC law namely, Network Constrained Optimal AGC (NCOAGC), regulates frequency deviations in a cost-optimal manner while restricting power flow in the tie-lines to be within their thermal limits. The stability of the NCOAGC law is proven and numerical studies are conducted to substantiate the performance benefits. Next, the research is extended to overcome the assumptions used in the development of NCOAGC algorithm by considering practical aspects of an interconnected power system, such as multiple generators and different generation technologies within a single control area. The enhancements for NCOAGC are identified and an algorithm is proposed to find the controller gains for NCOAGC under such scenarios. The algorithm is then tested with dynamic bus voltages and nonlinear network flows by developing an interconnected power system model with 4 control areas and 40 buses in the DIgSILENT PF 2017 simulation platform. Finally, a new dynamic control formulation is proposed to accommodate the generation constraints in addition to the network flow thermal limits to the optimisation problem by using a State Constraint Distributed Model Predictive Control (SCDMPC) scheme. The SCDMPC also improves the dynamic optimal performance. A prediction model to handle communication delay is developed and a functional observer to estimate the unmeasured feed forward disturbance is also developed. Since the SCDMPC optimisation problem has the input as well as state constraints, an algorithm is proposed to handle infeasible scenarios. The infeasibility handling algorithm does not increase the number of unknowns and thus the computation time is not impacted. At the end, the thesis is concluded and scope for future research is identified

Design and implementation of hybrid series compensators for smart grid applications

The vision of future modern grids goes through the increase of renewable énergies penetration while providing an efficient, reliable and sustainable power supply to consumers. According to the recent report on climate challenging the way electrical energy is produced and because of the rapid emerging of power electronics based equipment; some serious actions should be engaged. In order to achieve such promoting visions, all power grids are required to become smarter especially at the distribution level. Increasing the application of renewable energy sources and distributed generations assist these vision in the development of a modern power grid where modern equipment are becoming highly sensitive to the supplied voltage quality. Moreover, in this paradigm of design, the traditional power systems based on large concentrated power plants should be able to deal with these unpredictable sources of energy at distribution level. Under these circumstances, considerable activities were carried out aiming to render the grid more flexible and intelligent while taking the power efficiency and its environmental impacts into account. In this way, the power quality issues should be considered for the development of new type of smart grids which are more efficient and sustainable with regards to environmental constraints. Available active and passive compensators are widely involved to improve major power quality issues. Recent trends towards realization of multitasking devices which can solve several power quality issues simultaneously, propose Hybrid active filters or Unified power quality conditioners. These versatile devices should threaten both voltage and current related issues in one place for compensation. They can significantly improve power quality issues, such as voltage distortions, voltage sags, voltage swells, voltage unbalances, and ensure a constant and reliable voltage supply to the load. On the other hand, they compensate for current problems of linear and non-linear loads, such as current harmonics, unbalances, neutral current, and load reactive power. The Hybrid series active filter (HSeAF) is among the most versatile and efficient power electronics based active power compensators. Without the shunt passive filter, the active part could operate solely to rectify for voltage problems and is commonly known as Dynamic voltage restorer. A conventional HSeAF, targeting three-phase system, consists of a three separate series isolation transformer connected to a three-phase converter sharing a common DC link bus. The device is controlled as a variable voltage source in similar but duality manner as of Shunt active power filter. A shunt passive filter tuned for harmonic frequencies is installed to produce an alternative path for load current harmonics and reducing voltage distortions at the load terminals. The existing literature suggests utilizing the hybrid active power filters to compensate for load current related issues only, while due to the complexity and implementation outlays of such devices, it shows a significant drawback of under usage of series compensation to address such power quality problems. The present doctoral research is based on the philosophy of optimal utilization of the available resources in the most efficient way to enhance the product efficiency and to reduce the overall cost. This work proposes a novel control approach for three-phase system in which both the grid’s voltage and load current issues are treated in a co-ordination between the series active and the shunt passive filters without affecting the basic voltage or current compensation capabilities. This eventually results in a better utilization of the series active filter, reduction of the shunt passive filter rating to some extent, and ultimately in the reduction of the overall cost for a unified compensator. Moreover, this thesis also introduces a novel transformerless topology in which the threephase configuration is split into separate devices. It is then possible to extent the Series active power compensation based for three-phase systems with three or four wires to single-phase or bi-phase systems. This newly transformerless hybrid series active filter (THSeAF) is first hosted for single-phase system where appropriate developed controllers ensure adequate operation under low profile power quality systems. The developed single-phase THSeAF concept is successfully validated through digital simulations as well as real-time extensive experimental investigations. The experimental results show that for a given laboratory test conditions with highly polluted nonlinear loads, the active compensator ride of the bulky transformer is capable of compensating load current and correcting the power factor. Moreover, the performance of the THSeAF under polluted grid supply with voltage harmonics, sags, and swells, demonstrates regulated and reduced voltage distortions at the load’s terminals. Following this successful transformerless configuration, and to integrate the series compensation concepts dedicated for power quality improvement of distribution network, the three-phase configuration is anticipated. Three-phase control strategies developed previously for the HSeAF are applied to the proposed topology to make the point of common coupling (PCC) smarter and to decentralize the control of the distribution network. This affordable solution increases the efficiency and sustainability of modern smart power systems and help higher penetration of renewable fluctuating power into the network. The off-line simulations demonstrate that the three-phase THSeAF is capable of healing voltage problems and load current issues simultaneously. The real-time experimental results, carried out on a laboratory prototype, validate successfully the proposed configuration