Advanced and Innovative Optimization Techniques in Controllers: A Comprehensive Review

New commercial power electronic controllers come to the market almost every day to help improve electronic circuit and system performance and efficiency. In DC–DC switching-mode converters, a simple and elegant hysteretic controller is used to regulate the basic buck, boost and buck–boost converters under slightly different configurations. In AC–DC converters, the input current shaping for power factor correction posts a constraint. But, several brilliant commercial controllers are demonstrated for boost and fly back converters to achieve almost perfect power factor correction. In this paper a comprehensive review of the various advanced optimization techniques used in power electronic controllers is presented

Performance Analysis of Flexible A.C. Transmission System Devices for Stability Improvement of Power System

When large power systems are interconnected by relatively weak tie line, low-frequency oscillations are observed. Recent developments in power electronics have led to the development of the Flexible AC Transmission Systems (FACTS) devices in power systems. FACTS devices are capable of controlling the network condition in a very fast manner and this feature of FACTS can be exploited to improve the stability of a power system. To damp electromechanical oscillations in the power system, the supplementary controller can be applied with FACTS devices to increase the system damping. The supplementary controller is called damping controller. The damping controllers are designed to produce an electrical torque in phase with the speed deviation. The objective of this thesis is to develop some novel control techniques for the FACTS based damping controller design to enhance power system stability. Proper selection of optimization techniques plays an important role in for the stability enhancement of power system. In the present thesis Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Gravitational search algorithm (GSA) along with their hybrid form have been applied and compared for a FACTS based damping controller design. Important conclusions have been drawn on the suitability of optimization technique. The areas of research achieved in this thesis have been divided into two parts: The aim of the first part is to develop the linearized model (Philip-Hefron model) of a single machine infinite bus power system installed with FACTS devices, such as Static Synchronous Series Compensator (SSSC) and Unified Power Flow Controller (UPFC). Different Damping controller structures have been used and compared to mitigate the system damping by adding a component of additional damping torque proportional to speed change through the excitation system. The various soft-computing techniques have been applied in order to find the controller parameters. The recently developed Gravitational Search Algorithm (GSA) based SSSC damping controller, and a new hybrid Genetic Algorithm and Gravitational Search Algorithm (hGA-GSA) based UPFC damping controller seems to the most effective damping controller to mitigate the system oscillation. The aim of second part is to develop the Simulink based model (to over-come the problem associated with the linearized model) for an SMIB as well as the multi-machine power system. Coordinated design of PSS with various FACTS devices based damping controllers are carried out considering appropriate time delays due to sensor time constant and signal transmission delays in the design process. A hybrid Particle Swarm Optimization and Gravitational Search Algorithm (hPSO-GSA) technique is employed to optimally and coordinately tune the PSS and SSSC based controller parameters and has emerged as the most superior method of coordinated controller design considered for both single machine infinite bus power system as well as a multi-machine power system. Finally, the damping capabilities of SSSC based damping controllers are thoroughly investigated by considering a new derived modified signal known as Modified Local Input Signal which comprises both the local signal (speed deviation) and remote signal (line active power). Appropriate time delays due to sensor time constant and signal transmission delays are considered in the design process. The hybrid Particle Swarm Optimization and Gravitational Search Algorithm (hPSO-GSA) technique is used to tune the damping controller parameters. It is observed that the new modified local input signal based SSSC controller provides the best system performance compared to other alternatives considered for a single machine infinite bus power system and multi-machine power system

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

H2 Control for Improved Stability of Multi-area Electric Power System with High Levels of Inverter-Based Generation

Increased generation capacity from non-dispatchable energy resources such as wind and solar has created challenges to ensuring the reliable delivery of electric power. This research develops a systematic three-step method of assessing the reliability of electric power systems under a variety of different possible fault conditions to ensure that overall system stability is preserved in a manner the meets regulatory requirements. The first step is a risk-based reliability method (RBRM) that accounts for the probability of a line outage versus the severity of impact. This allows system planners to judiciously allocate expenses for reliability improvements based on the greatest economic benefit. The second approach is the synchrophasor validation method (SVM) which allows system planners and analysis to develop accurate models of electric power system behavior. This improves the decision making capability for implementing new system designs and equipment choices. The third new area is the development of norm-based wide-area control methods that optimize system stability and reliability based on the statistical characteristics found in the first two steps. This norm-based approach includes calculating optimal values for parameters of flexible ac transmission system (FACTS) devices and high voltage direct current (HVDC) links in order to have results within the regulatory requirements of the North American Electric Reliability Corporation (NERC). Power flow and frequency criteria are used to verify conformance with the regulations. These criteria are evaluated under N-1-1 conditions in two reduced order models to demonstrate the ability of the norm-based wide-area controller to maintain performance of these systems within acceptable ranges. The obtained simulation results confirm the benefits of the proposed technique in meeting regulatory requirements under conditions of N-1-1 contingencies in electric power systems with large amounts of renewable energy resources

Low-Frequency Oscillation Mitigation usin an Optimal Coordination of CES and PSS based on BA

Small signal stability represents the reliability of generator for transferring electrical energy to the consumers. The stress of the generator increases proportionally with the increasing number of load demand as well as the uncertainty characteristic of the load demand. This condition makes the small signal stability performance of power system become vulnerable. This problem can be handled using power system stabilizer (PSS) which is installed in the excitation system. However, PSS alone is not enough to deal with the uncertainty of load issue because PSS supplies only an additional signal without providing extra active power to the grid. Hence, utilizing capacitor energy storage (CES) may solve the load demand and uncertainty issues. This paper proposes a coordination between CES and PSS to mitigate oscillatory behavior of the power system. Moreover, bat algorithm is used as an optimization method for designing the coordinated controller between CES and PSS. In order to assess the proposed method, a multi-machine two-area power system is applied as the test system. Eigenvalue, damping ratio, and time domain simulations are performed to examine the significant results of the proposed method. From the simulation, it is found that the present proposal is able to mitigate the oscillatory behavior of the power system by increasing damping performance from 4.9% to 59.9%

Artificial Intelligence-based Control Techniques for HVDC Systems

The electrical energy industry depends, among other things, on the ability of networks to deal with uncertainties from several directions. Smart-grid systems in high-voltage direct current (HVDC) networks, being an application of artificial intelligence (AI), are a reliable way to achieve this goal as they solve complex problems in power system engineering using AI algorithms. Due to their distinctive characteristics, they are usually effective approaches for optimization problems. They have been successfully applied to HVDC systems. This paper presents a number of issues in HVDC transmission systems. It reviews AI applications such as HVDC transmission system controllers and power flow control within DC grids in multi-terminal HVDC systems. Advancements in HVDC systems enable better performance under varying conditions to obtain the optimal dynamic response in practical settings. However, they also pose difficulties in mathematical modeling as they are non-linear and complex. ANN-based controllers have replaced traditional PI controllers in the rectifier of the HVDC link. Moreover, the combination of ANN and fuzzy logic has proven to be a powerful strategy for controlling excessively non-linear loads. Future research can focus on developing AI algorithms for an advanced control scheme for UPFC devices. Also, there is a need for a comprehensive analysis of power fluctuations or steady-state errors that can be eliminated by the quick response of this control scheme. This survey was informed by the need to develop adaptive AI controllers to enhance the performance of HVDC systems based on their promising results in the control of power systems. Doi: 10.28991/ESJ-2023-07-02-024 Full Text: PD

Improve the Flexibility of Power Distribution Network by Using Back-to-back Voltage Source Converter

Employing increasing distributed generations (DGs) into existing distribution networks is an inevitable trend of the development of modern electric power systems because of the benefits including the environmentally friendly generation, higher efficiency and improved flexibility and reliability. However, high DG penetration level could pose various issues among which the voltage violation and fault level increase are the most concerned. According to the current situation of UK distribution networks, voltage violation is likely to be the first constraint to be met when DG penetration level is increased to certain level. Therefore, compensators are considered to be implemented to regulate the voltage. The reactive power compensators that widely used in transmission systems appear less effective in distribution networks thus active power compensation is desired. Soft-open points (SOPs) are power-electronic devices used replacing the normally-open points which can control active power transfer between two feeders and/or provide reactive power compensation. The back-to-back voltage source converter (B2B-VSC) is preferred as the SOP because of its capability of restricting fault current despite that it has higher power loss and associated capital cost. Two types of controller are developed for the B2B-VSC-based SOP: one is based on the PI control theory and the other is based on the concept of synchronverters. For the former type, the controller design is introduced comprehensively including system modelling and parameters selection. The precise selection of the damping ratio for nonstandard second-order system is derived, and a technique of resetting integrator in output voltage controller loop to achieve fast and smooth islanding transition is proposed. For the latter type, modifications are made to adapt the synchronverter idea to the application of an SOP. Simulations and experiments are carried out to validate the controller designs and both the controllers are verified to be able to provide sufficient performance on voltage regulation, fault current restriction and independent load supply in island mode. In general, the controller based on PI control theory has better performance in fault condition thanks to the current control loop, and the controller based on synchronverter owns better reliability because it does not require additional detections and signal switches inside the controller. At last, the use of an SOP in a dynamic load dominated network after the loss of mains is further investigated. Torque-speed characteristic is used to analyse the influence of the VSC’s filter impedance on the stability margin of an induction motor. Though the filter impedance can significantly decrease the stability margin, the output impedance of the VSC can be mitigated by properly designing the output voltage controller. Simulation and experiment are carried out to validate the analyses and controller design. The results show that the VSC is capable of supplying an induction motor in island mode

A Novel Improved Sea-Horse Optimizer for Tuning Parameter Power System Stabilizer

Power system stabilizer (PSS) is applied to dampen system oscillations so that the frequency does not deviate beyond tolerance. PSS parameter tuning is increasingly difficult when dealing with complex and nonlinear systems. This paper presents a novel hybrid algorithm developed from incorporating chaotic maps into the sea-horse optimizer. The algorithm developed is called the chaotic sea-horse optimizer (CSHO). The proposed method is adopted from the metaheuristic method, namely the sea-horse optimizer (SHO). The SHO is a method that duplicates the life of a sea-horse in the ocean when it moves, looks for prey and breeds.  In This paper, The CSHO method is used to tune the power system stabilizer parameters on a single machine system. The proposed method validates the benchmark function and performance on a single machine system against transient response. Several metaheuristic methods are used as a comparison to determine the effectiveness and efficiency of the proposed method. From the research, it was found that the application of the logistics Tent map from the chaotic map showed optimal performance. In addition, the application of the PSS shows effective and efficient performance in reducing overshoot in transient conditions

Adaptive Control for Power System Voltage and Frequency Regulation

Variable and uncertain wind power output introduces new challenges to power system voltage and frequency stability. To guarantee the safe and stable operation of power systems, the control for voltage and frequency regulation is studied in this work. Static Synchronous Compensator (STATCOM) can provide fast and efficient reactive power support to regulate system voltage. In the literature, various STATCOM control methods have been discussed, including many applications of proportional–integral (PI) controllers. However, these previous works obtain the PI gains via a trial and error approach or extensive studies with a tradeoff of performance and applicability. Hence, control parameters for the optimal performance at a given operating point may not be effective at a different operating point. To improve the controller’s performance, this work proposes a new control model based on adaptive PI control, which can self-adjust the control gains during disturbance, such that the performance always matches a desired response in relation to operating condition changes. Further, a new method called the flatness-based adaptive control (FBAC), for STATCOM is also proposed. By this method, the nonlinear STATCOM variables can easily and exactly be controlled by controlling the flat output without solving differential equations. Further, the control gains can be dynamically tuned to satisfy the time-varying operation condition requirement. In addition to the voltage control, frequency control is also investigated in this work. Automatic generation control (AGC) is used to regulate the system frequency in power systems. Various control methods have been discussed in order to design control gains and obtain good frequency response performances. However, the control gains obtained by existing control methods are usually fixed and designed for specific scenarios in the studied power system. The desired response may not be obtained when variable wind power is integrated into power systems. To address these challenges, an adaptive gain-tuning control (AGTC) for AGC with effects of wind resources is presented in this dissertation. By AGTC, the PI control parameters can be automatically and dynamically calculated during the disturbance to make AGC consistently provide excellent performance under variable wind power. Simulation result verifies the advantages of the proposed control strategy