Harmony Search Method: Theory and Applications

The Harmony Search (HS) method is an emerging metaheuristic optimization algorithm, which has been employed to cope with numerous challenging tasks during the past decade. In this paper, the essential theory and applications of the HS algorithm are first described and reviewed. Several typical variants of the original HS are next briefly explained. As an example of case study, a modified HS method inspired by the idea of Pareto-dominance-based ranking is also presented. It is further applied to handle a practical wind generator optimal design problem

Contributions to the development of the CRO-SL algorithm: Engineering applications problems

This Ph.D. thesis discusses advanced design issues of the evolutionary-based algorithm \textit{"Coral Reef Optimization"}, in its Substrate-Layer (CRO-SL) version, for optimization problems in Engineering Applications. The problems that can be tackled with meta-heuristic approaches is very wide and varied, and it is not exclusive of engineering. However we focus the Thesis on it area, one of the most prominent in our time. One of the proposed application is battery scheduling problem in Micro-Grids (MGs). Specifically, we consider an MG that includes renewable distributed generation and different loads, defined by its power profiles, and is equipped with an energy storage device (battery) to address its programming (duration of loading / discharging and occurrence) in a real scenario with variable electricity prices. Also, we discuss a problem of vibration cancellation over structures of two and four floors, using Tuned Mass Dampers (TMD's). The optimization algorithm will try to find the best solution by obtaining three physical parameters and the TMD location. As another related application, CRO-SL is used to design Multi-Input-Multi-Output Active Vibration Control (MIMO-AVC) via inertial-mass actuators, for structures subjected to human induced vibration. In this problem, we will optimize the location of each actuator and tune control gains. Finally, we tackle the optimization of a textile modified meander-line Inverted-F Antenna (IFA) with variable width and spacing meander, for RFID systems. Specifically, the CRO-SL is used to obtain an optimal antenna design, with a good bandwidth and radiation pattern, ideal for RFID readers. Radio Frequency Identification (RFID) has become one of the most numerous manufactured devices worldwide due to a reliable and inexpensive means of locating people. They are used in access and money cards and product labels and many other applications.Comment: arXiv admin note: text overlap with arXiv:1806.02654 by other author

A modified whale optimization algorithm-based adaptive fuzzy logic PID controller for load frequency control of autonomous power generation systems

An autonomous power generation system (APGS) contains units such as diesel energy generator, solar photovoltaic units, wind turbine generator and fuel cells along with energy-storing units such as the flywheel energy storage system and battery energy storage system. The components either run at lower/higher power output or may turn on/off at different instants of their operation. Due to this, the conventional controllers will not provide desired performance under varied load conditions. This paper proposes an adaptive fuzzy logic PID (AFPID) controller for load frequency control. In order to achieve an improved performance, a modified whale optimization algorithm (mWOA) was also proposed in this paper for tuning of the AFPID parameters. The proposed algorithm was first evaluated using standard test functions and compared with other recent algorithms to authenticate the competence of algorithm. The proposed mWOA algorithm outperforms PSO, GSA, DE and FEP algorithms in five out of seven unimodal test functions and four out of six multimodal test functions. The effectiveness of the AFPID compared with the conventional PID and the proposed AFPID provides better performance. Reduction of 39.13% in error criteria (objective function) compared with WOA-PID controller. The proposed approach was also compared with some recently proposed frequency control approaches in a widely used two-area test system

Multi particle swarm optimisation algorithm applied to supervisory power control systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonPower quality problems come in numerous forms (commonly spikes, surges, sags, outages and harmonics) and their resolution can cost from a few hundred to millions of pounds, depending on the size and type of problem experienced by the power network. They are commonly experienced as burnt-out motors, corrupt data on hard drives, unnecessary downtime and increased maintenance costs. In order to minimise such events, the network can be monitored and controlled with a specific control regime to deal with particular faults. This study developed a control and Optimisation system and applied it to the stability of electrical power networks using artificial intelligence techniques. An intelligent controller was designed to control and optimise simulated models for electrical system power stability. Fuzzy logic controller controlled the power generation, while particle swarm Optimisation (PSO) techniques optimised the system’s power quality in normal operation conditions and after faults. Different types of PSO were tested, then a multi-swarm (M-PSO) system was developed to give better Optimisation results in terms of accuracy and convergence speed.. The developed Optimisation algorithm was tested on seven benchmarks and compared to the other types of single PSOs. The developed controller and Optimisation algorithm was applied to power system stability control. Two power electrical network models were used (with two and four generators), controlled by fuzzy logic controllers tuned using the Optimisation algorithm. The system selected the optimal controller parameters automatically for normal and fault conditions during the operation of the power network. Multi objective cost function was used based on minimising the recovery time, overshoot, and steady state error. A supervisory control layer was introduced to detect and diagnose faults then apply the correct controller parameters. Different fault scenarios were used to test the system performance. The results indicate the great potential of the proposed power system stabiliser as a superior tool compared to conventional control systems

Optimal SSSC-based power damping inter-area oscillations using firefly and harmony search algorithms

The static synchronous series compensator (SSSC) can add a series reactance to the transmission line, and when it is fed using auxiliary signals, it can participate in damping inter-area oscillations by changing the series reactance. In this paper, the effect of the SSSC on small-signal stability is investigated. The design of a controller for damping oscillations is designed and discussed. Moreover, using the firefly and the harmony search algorithms, the optimal parameters controlling SSSC are addressed. The effectiveness of these two algorithms and the rate of SSSC participation in damping inter-area oscillation are also discussed. MATLAB software was used to analyse the models and to perform simulations in the time domain. The simulation results on the sample system, in two areas, indicated the optimal accuracy and precision of the proposed controller

Invited Review: Recent developments in vibration control of building and bridge structures

This paper presents a state-of-the-art review of recent articles published on active, passive, semi-active and hybrid vibration control systems for structures under dynamic loadings primarily since 2013. Active control systems include active mass dampers, active tuned mass dampers, distributed mass dampers, and active tendon control. Passive systems include tuned mass dampers (TMD), particle TMD, tuned liquid particle damper, tuned liquid column damper (TLCD), eddy-current TMD, tuned mass generator, tuned-inerter dampers, magnetic negative stiffness device, resetting passive stiffness damper, re-entering shape memory alloy damper, viscous wall dampers, viscoelastic dampers, and friction dampers. Semi-active systems include tuned liquid damper with floating roof, resettable variable stiffness TMD, variable friction dampers, semi-active TMD, magnetorheological dampers, leverage-type stiffness controllable mass damper, semi-active friction tendon. Hybrid systems include shape memory alloys-liquid column damper, shape memory alloy-based damper, and TMD-high damping rubber

LQR Tuning Using AIS for Frequency Oscillation Damping

Commonly, primary control, i.e. governor, in the generation unit had been employed to stabilize the change of frequency due to the change of electrical load during system operation. But, the drawback of the primary control was it could not return the frequency to its nominal value when the disturbance was occurred. Thus, the aim of the primary control was only stabilizing the frequency to reach its new value after there were load changes. Therefore, the LQR control is employed as a supplementary control called Load Frequency Control (LFC) to restore and keep the frequency on its nominal value after load changes occurred on the power system grid. However, since the LQR control parameters were commonly adjusted based on classical or Trial-Error Method (TEM), it was incapable of obtaining good dynamic performance for a wide range of operating conditions and various load change scenarios. To overcome this problem, this paper proposed an Artificial Immune System (AIS) via clonal selection to automatically adjust the weighting matrices, Q and R, of LQR related to various system operating conditions changes. The efficacy of the proposed control scheme was tested on a two-area power system network. The obtained simulation results have shown that the proposed method could reduce the settling time and the overshoot of frequency oscillation, which is better than conventional LQR optimal control and without LQR optimal control

AI Applications to Power Systems

Today, the flow of electricity is bidirectional, and not all electricity is centrally produced in large power plants. With the growing emergence of prosumers and microgrids, the amount of electricity produced by sources other than large, traditional power plants is ever-increasing. These alternative sources include photovoltaic (PV), wind turbine (WT), geothermal, and biomass renewable generation plants. Some renewable energy resources (solar PV and wind turbine generation) are highly dependent on natural processes and parameters (wind speed, wind direction, temperature, solar irradiation, humidity, etc.). Thus, the outputs are so stochastic in nature. New data-science-inspired real-time solutions are needed in order to co-develop digital twins of large intermittent renewable plants whose services can be globally delivered

Multi-mode damping control approach for the optimal resilience of renewable-rich power systems

The integration of power-electronics-based power plants is developing significantly due to the proliferation of renewable energy sources. Although this type of power plant could positively affect society in terms of clean and sustainable energy, it also brings adverse effects, especially with the stability of the power system. The lack of inertia and different dynamic characteristics are the main issues associated with power-electronics-based power plants that could affect the oscillatory behaviour of the power system. Hence, it is important to design a comprehensive damping controller to damp oscillations due to the integration of a power-electronics-based power plant. This paper proposes a damping method for enhancing the oscillatory stability performance of power systems with high penetration of renewable energy systems. A resilient wide-area multimodal controller is proposed and used in conjunction with a battery energy storage system (BESS) to enhance the damping of critical modes. The proposed control also addresses resiliency issues associated with control signals and controllers. The optimal tuning of the control parameters for this proposed controller is challenging. Hence, the firefly algorithm was considered to be the optimisation method to design the wide-area multimodal controllers for BESS, wind, and photovoltaic (PV) systems. The performance of the proposed approach was assessed using a modified version of the Java Indonesian power system under various operating conditions. Both eigenvalue analysis and time-domain simulations are considered in the analysis. A comparison with other well-known metaheuristic methods was also carried out to show the proposed method’s efficacy. Obtained results confirmed the superior performance of the proposed approach in enhancing the small-signal stability of renewable-rich power systems. They also revealed that the proposed multimodal controller could enhance the penetration of renewable energy sources in the Javan power system by up to 50%. © 2022 by the authors. Licensee MDPI, Basel, Switzerland

Contributions to the development of the CRO-SL algorithm: Engineering applications problems

Esta tesis doctoral aborda el diseño del algoritmo evolutivo Coral Reef Optimization, en su versión Substrate-Layer, para la optimización de problemas en diferentes ámbitos de la ingeniería. Los algoritmos evolutivos han sido ampliamente aplicados a problemas de optimización difícilmente abordables de manera analítica, ya sea por tener espacios de búsqueda enormes o por ser no lineales. Si bien la ejecución de estos algoritmos no supone un gran coste computacional hoy en día, sí lo supone las funciones de coste que constantemente deben evaluar. La creciente capacidad de procesamiento en la tecnología le abre las puertas al abordaje de problemas temporalmente costosos por medio de la metaheurística. Uno de los inconvenientes de esta, es que no hay forma de saber a priori cuál de ellos es mejor para un problema específico, y sea cual sea la elección, la ejecución del mismo no te asegura que vayas a obtener el óptimo. Es por este motivo por el cual se ha elegido el algoritmo CRO-SL, ya que permite combinar los procesos de búsqueda más potentes, ayudándose entre ellos para alcanzar el óptimo global. La problemática a la que se puede aplicar la metaheurística es muy variada y no tiene por qué ser exclusiva de la ingeniería, sin embargo en esta tesis sí vamos a centrarla en ella. Una de las aplicaciones que vamos a ver es el diseño de una antena de tipo F invertida (IFA), para sistemas de IDentificación por Radio-Frecuencia (RFID). Estas han sido muy utilizadas en productos a lo largo de todo el mundo tanto en tarjetas de crédito como en etiquetas de productos debido a su pequeño tamaño y a una fabricación sencilla y barata. En concreto, en este trabajo se usarán como conductores láminas de cobre y como dieléctrico, fieltro. Se pretende así, diseñar el ancho y el espaciamiento de estas tiras de cobre para que emita en un ancho de banda determinado con una calidad determinada. También se abordará un problema de control de vibración en estructuras de dos y cuatro pisos mediante el uso de elementos amortiguadores pasivos, TMD's(Tunned Mass Dampers). Esta aplicación viene motivada por la necesidad de mitigar las vibraciones procedentes de la tierra, como pudiera ser en un terremoto. En este caso el algoritmo no sólo intentará optimizar las características físicas de los TMD's sino también su colocación dentro del edificio. En tercer lugar, se realizará un control activo de las vibraciones que generamos los humanos al caminar en una estructura civil, mediante el uso de actuadores de masa inercial. En este problema se tratará de optimizar la localización de los actuadores así como sintonizar las ganancias de control. Por último veremos un problema de optimización de planificación de las baterías en micro-redes(MG). Específicamente, consideramos una MG que incluye generación renovable y diferentes cargas, definidas por sus perfiles de potencia, y está equipada con un dispositivo de almacenamiento de energía (batería) para abordar su programación (duración de carga / descarga y ocurrencia) en un escenario real de precios variables de electricidad. Mediante la aplicación del CRO-SL a estos problemas se pretende cumplir dos objetivos. El primero es comprobar la aptitud del propio algoritmo en las aplicaciones mencionadas. Para ello además se realizarán experimentos con los algoritmos más populares y los resultados podrán ser comparados entre sí. El segundo es promover el uso del CRO-SL como herramienta de comparación entre métodos de exploración. Algunos de los algoritmos metaheurísticos se basan en la iteración de un proceso de búsqueda sobre una población de individuos codificados, que encarnan la solución a un determinado problema. El CRO-SL toma prestado la forma en la que otros algoritmos cambian a sus individuos, y forma nuevas soluciones de manera paralela. Entre los algoritmos evolutivos más conocidos que vamos a ver durante el desarrollo de esta tesis se encuentran los algoritmos Harmony Search, Differential Evolution y Genetic Algorithm. Además se verán otro tipo de mutaciones como la de tipo Gaussiana, mutación simple o cruce multipunto. Por último, durante el desarrollo de esta tesis también se ha probado una nueva forma de búsqueda basada en atractores extraños. Gracias a la capacidad de comparación del CRO-SL podremos ver si esta nueva forma de búsqueda es útil o no