Load frequency controllers considering renewable energy integration in power system

Abstract: Load frequency control or automatic generation control is one of the main operations that take place daily in a modern power system. The objectives of load frequency control are to maintain power balance between interconnected areas and to control the power flow in the tie-lines. Electric power cannot be stored in large quantity that is why its production must be equal to the consumption in each time. This equation constitutes the key for a good management of any power system and introduces the need of more controllers when taking into account the integration of renewable energy sources into the traditional power system. There are many controllers presented in the literature and this work reviews the traditional load frequency controllers and those, which combined the traditional controller and artificial intelligence algorithms for controlling the load frequency

Load Frequency Control of Photovoltaic Generation-Integrated Multi-Area Interconnected Power Systems Based on Double Equivalent-Input-Disturbance Controllers

With the rapid increase of photovoltaic (PV) penetration and distributed grid access, photovoltaic generation (PVG)-integrated multi-area power systems may be disturbed by more uncertain factors, such as PVG, grid-tie inverter parameters, and resonance. These uncertain factors will exacerbate the frequency fluctuations of PVG integrated multi-area interconnected power systems. For such system, this paper proposes a load frequency control (LFC) strategy based on double equivalent-input-disturbance (EID) controllers. The PVG linear model and the multi-area interconnected power system linear model were established, respectively, and the disturbances were caused by grid voltage fluctuations in PVG subsystem and PV output power fluctuation and load change in multi-area interconnected power system. In PVG subsystems and multi-area interconnected power systems, two EID controllers add differently estimated equivalent system disturbances, which has the same effect as the actual disturbance, to the input channel to compensate for the impact of actual disturbances. The simulation results in MATLAB/Simulink show that the frequency deviation range of the proposed double EID method is 6% of FA-PI method and 7% of conventional PI method, respectively, when the grid voltage fluctuation and load disturbance exist. The double EID method can better compensate for the effects of external disturbances, suppress frequency fluctuations, and make the system more stable

Fuzzy logic-based controller of the bidirectional direct current to direct current converter in microgrid

Microgrids are small-scale power networks that include renewable energy sources, load, energy storage systems, and energy management systems (EMS). Lithium-ion batteries are the most used battery for energy storage in microgrids due to their advantages over other types of batteries. However, to protect the battery from the explosion and to manage to charge and discharge based on state-of-charge (SoC) value, this type of battery requires the use of an energy management system. The main objective of this paper is to propose an intelligent control strategy for energy management in the microgrid to control the charge and discharge of Li-ion batteries to stabilize the system and reduce the cost of electricity due to the high cost of grid electricity. The proposed technique is based on a fuzzy logic controller (FLC) for voltage control. The FLC is based on the measured voltage of the direct current (DC) bus and the fixed reference voltage to generate buck/boost converter signal control. The proposed technique has been simulated and tested using MATLAB/Simulink software which illustrates the tracking of desired power and DC bus voltage regulation. The simulation results confirm that the proposed systems can diminish the deviations of the system's voltage

ENERGY MANAGEMENT AND HARMONIC MITIGATION OF HYBRID RENEWABLE ENERGY MICROGRID USING COORDINATED CONTROL OF MULTI-AGENT SYSTEM

In this paper, a novel energy management method that is based on a Multi-Agent System (MAS) is presented for hybrid Distributed Energy Sources (DES) in a microgrid. These DESs include Photovoltaic (PV), wind energy systems, and Fuel Cell (FC) in the Microgrid (MG). The MG is responsible for supplying both active and reactive powers, allowing it to serve variable linear and non-linear loads. The MAS that has been proposed and is based on a decentralized control structure offers control not only for the energy management of the Distributed Generation (DG) but also for the management of power flow between the MG and the power grid that is connected to the MG. This control is offered by the MAS. The main objective of the control strategy is to manage the amount of energy that is transferred between the power grid and the MG concerning the supply conditions of the required internal energy via DES, which will ultimately result in a reduction in the dependence on the MG on the grid. For current harmonic compensation, a Static Compensator (STATCOM) with a Fuzzy Logic (FL) based Instantaneous Reactive Power control scheme is used. On the other hand, a discrete controller is utilized to manage the energy of the MG. The findings of the simulation and the experiments demonstrated that the implementation of the suggested Energy Management System (EMS) has good performance as a novel energy management solution for a hybrid distributed power generating system and harmonic compensation

Adaptive Neural Network-Based Control of a Hybrid AC/DC Microgrid

In this paper, the behavior of a grid-connected hybrid ac/dc microgrid has been investigated. Different renewable energy sources - photovoltaics modules and a wind turbine generator - have been considered together with a solid oxide fuel cell and a battery energy storage system. The main contribution of this paper is the design and the validation of an innovative online-trained artificial neural network-based control system for a hybrid microgrid. Adaptive neural networks are used to track the maximum power point of renewable energy generators and to control the power exchanged between the front-end converter and the electrical grid. Moreover, a fuzzy logic-based power management system is proposed in order to minimize the energy purchased from the electrical grid. The operation of the hybrid microgrid has been tested in the MATLAB/Simulink environment under different operating conditions. The obtained results demonstrate the effectiveness, the high robustness and the self-adaptation ability of the proposed control system

Frequency Control of Microgrid Network using Intelligent Techniques – ANN, PSO and ANFIS

The electric grid is a complex system that transmits electricity from the point of generation to the point of consumption. According to the IEA, worldwide energy-related carbon emissions in 2021 will be 36.3Gt, 60% greater than at the start of the industrial revolution. Researchers have used intelligent solutions for power system frequency regulation to ensure that the system\u27s frequency is maintained. A proper frequency control of the microgrid necessitates the modeling and study of the systems. To emulate the operation of the human brain, frequency control employs a variety of artificial intelligence-based computer algorithms. This thesis generates a complete state space model of a microgrid composed of solar power plants, wind turbines, battery storage systems, and backup generators. The system frequency control was created for this system and analyzed against a benchmark PID controller utilizing several intelligent controllers such as PSO optimized PID, ANN, and ANFIS. The suggested intelligent frequency controllers were be simulated and validated using MATLAB/ Simulink

A Constant Grid Interface Current Controller for DC Microgrid

With the increased percentage of distributed renewable energy sources (RES) connected to the power network, it is challenging to maintain the balance between the power generation and consumptions against the unpredictable renewable energy generation and load variations. Considering this, this study proposed a new DC microgrid control strategy to reduce the disturbance to the main power grid from the distributed generation and load variations within the DC microgrid. The DC microgrid model used in this study includes an energy storage unit (battery), a distributed generation unit (PV) and loads. A fuzzy logic controller (FLC) is used to actively regulate the battery charging/discharging current to absorb the power variation caused by PV generation and load changes. The proposed control strategy is validated by simulation in MATLAB/Simulink

Passivity - Based Control and Stability Analysis for Hydro-Solar Power Systems

Los sistemas de energía modernos se están transformando debido a la inclusión de renovables no convencionales fuentes de energía como la generación eólica y fotovoltaica. A pesar de que estas fuentes de energía son buenas alternativas para el aprovechamiento sostenible de la energía, afectan el funcionamiento y la estabilidad del sistema de energía, debido a su naturaleza inherentemente estocástica y dependencia de las condiciones climáticas. Además, los parques solares y eólicos tienen una capacidad de inercia reducida que debe ser compensada por grandes generadores síncronos en sistemas hidro térmicos convencionales, o por almacenamiento de energía dispositivos. En este contexto, la interacción dinámica entre fuentes convencionales y renovables debe ser estudiado en detalle. Para 2030, el Gobierno de Colombia proyecta que el poder colombiano El sistema integrará en su matriz energética al menos 1,2 GW de generación solar fotovoltaica. Por esta razón, es necesario diseñar controladores robustos que mejoren la estabilidad en los sistemas de energía. Con alta penetración de generación fotovoltaica e hidroeléctrica. Esta disertación estudia nuevas alternativas para mejorar el sistema de potencia de respuesta dinámica durante y después de grandes perturbaciones usando pasividad control basado. Esto se debe a que los componentes del sistema de alimentación son inherentemente pasivos y permiten formulaciones hamiltonianas, explotando así las propiedades de pasividad de sistemas eléctricos. Las principales contribuciones de esta disertación son: una pasividad descentralizada basada control de los sistemas de control de turbinas hidráulicas para sistemas de energía de múltiples máquinas para estabilizar el rotor acelerar y regular el voltaje terminal de cada sistema de control de turbinas hidráulicas en el sistema como, así como un control basado en PI pasividad para las plantas solares fotovoltaicas