Active and reactive power conditioning using SMES devices with PMW-CSC: A feedback nonlinear control approach

The active and reactive power conditioning using superconducting magnetic energy storage (SMES) systems for low-voltage distribution networks via feedback nonlinear control is proposed in this paper. The SMES system is interconnected to ac grid using a pulsed-width modulated current source converter (PWM-CSC). The dynamical model of the system exhibits a nonlinear structure, which is eliminated by the application of a nonlinear feedback controller based of the expected behavior of the closed-loop system. The steady state analysis under time-domain reference frame to verify the stability properties on the proposed controller is used. The general control rules allow improving different objectives. The robustness and applicability of the proposed controller is tested considering unbalance and harmonic distortion in the voltage provided by the ac grid. It is also considered the possibility to use the SMES system with the proposed controller to compensate the active power oscillations of a wind-generator system. © 2019 The AuthorsDepartamento Administrativo de Ciencia, Tecnología e Innovación, COLCIENCIAS Department of Science, Information Technology and Innovation, Queensland GovernmentThis work was partially supported by the National Scholarship Program Doctorates of the Administrative Department of Science, Technology and Innovation of Colombia ( COLCIENCIAS ), by calling contest 727-2015

Nonlinear analysis and control of a reaction wheel pendulum: Lyapunov-based approach

This paper presents a nonlinear analysis, control, and comparison of controllers based on the dynamical model of the reaction wheel pendulum (RWP) in a tutorial style. Classical methodologies such as proportional integral derivative (PID) control and state variables feedback control are explored. Lyapunov's method is proposed to analyze the stability of the proposed nonlinear controllers, and it is also used to design control laws guaranteeing globally asymptotically stability conditions in closed-loop. A swing up strategy is also included to bring the pendulum bar to the desired operating zone at the vertical upper position from an arbitrary initial location. Simulation results show that it is possible to obtain the same dynamical behavior of the RWP system adjusting the control gains adequately. All simulations were conducted via MATLAB Ordinary Differential Equation packages. © 2019 Karabuk Universit

Active and reactive power conditioning using SMES devices with PMW-CSC: A feedback nonlinear control approach

The active and reactive power conditioning using superconducting magnetic energy storage (SMES) systems for low-voltage distribution networks via feedback nonlinear control is proposed in this paper. The SMES system is interconnected to ac grid using a pulsed-width modulated current source converter (PWM-CSC). The dynamical model of the system exhibits a nonlinear structure, which is eliminated by the application of a nonlinear feedback controller based of the expected behavior of the closed-loop system. The steady state analysis under time-domain reference frame to verify the stability properties on the proposed controller is used. The general control rules allow improving different objectives. The robustness and applicability of the proposed controller is tested considering unbalance and harmonic distortion in the voltage provided by the ac grid. It is also considered the possibility to use the SMES system with the proposed controller to compensate the active power oscillations of a wind-generator system. © 2019 The AuthorsDepartamento Administrativo de Ciencia, Tecnología e Innovación, COLCIENCIAS, Department of Science, Information Technology and Innovation, Queensland Governmen

Alternative power flow method for direct current resistive grids with constant power loads: A truncated Taylor-based method

The power flow in electrical system permits analyzing and studying the steady-state behavior of any grid. Additionally, the power flow helps with the proper planning and management of the system. Therefore, it is increasingly necessary to propose power flows with fast convergence and high efficiency in their results. For this reason, this paper presents an alternative power flow approach for direct current networks with constant power loads based on a truncated Taylor-based approximation. This approach is based on a first-order linear approximation reformulated as a recursive, iterative method. It works with a slope variable concept based on derivatives, which allow few iterations and low processing times. Numerical simulations permit identifying the best power flow approaches reported in the specialized literature for radial and mesh dc grids, including the proposed approach. All the simulations were conducted in MATLAB 2015a. © Published under licence by IOP Publishing Ltd.Universidad Tecnológica de Pereira, UTP: C2018P020 Department of Science, Information Technology and Innovation, Queensland Government, DSITI: ColcienciasThis work was supported in part by the Administrative Department of Science, Technology and Innovation of Colombia (Colciencias) through the National Scholarship Program under Grant 727-2015 and in part by the Universidad Tecnológica de Bolívar under Project C2018P020

Optimal power flow studies in direct current grids: An application of the bio-inspired elephant swarm water search algorithm

Colombian power system is experienced important changes due to the large scale integration of renewable power generation based on solar and wind power; added to the fact that direct current networks have taken important attention, since they are efficient in terms of power loss and voltage profile at distribution or transmission levels For addressing this problem, this paper presents the application of an emerging bio-inspired metaheuristic optimization technique known as elephant swarm water search algorithm to the optimal power flow problem in direct current networks. A master-slave hybrid optimization strategy for optimal power flow analysis is addressed in this paper by decoupling this problem in two optimizing issues. The first problem corresponds to the selection of the power generated by all non-voltage controlled distributed generators; While the second problem lies in the solution of the classical power flow equations in direct current networks. The solution of the master problem (first problem) is made by applying the elephant swarm water search algorithm, while the second problem (slave problem) is solved by a conventional Gauss-Seidel numerical method. The proposed hybrid methodology allows solving the power flow problem by using any basic programming language with minimum computational effort and well-precision when is compared with optimizing packages such as general algebraic modeling system/CONOPT solver and conventional metaheuristic techniques such as genetic algorithms. © Published under licence by IOP Publishing Ltd.Universidad Tecnológica de Pereira, UTP: C2018P020 Department of Science, Information Technology and Innovation, Queensland Government, DSITI: ColcienciasThis work was supported in part by the Administrative Department of Science, Technology and Innovation of Colombia (Colciencias) through the National Scholarship Program under Grant 727-2015 and in part by the Universidad Tecnológica de Bolívar under Project C2018P020

An exact MINLP model for optimal location and sizing of DGs in distribution networks: A general algebraic modeling system approach

This paper addresses the classical problem of optimal location and sizing of distributed generators (DGs) in radial distribution networks by presenting a mixed-integer nonlinear programming (MINLP) model. To solve such model, we employ the General Algebraic Modeling System (GAMS) in conjunction with the BONMIN solver, presenting its characteristics in a tutorial style. To operate all the DGs, we assume they are dispatched with a unity power factor. Test systems with 33 and 69 buses are employed to validate the proposed solution methodology by comparing its results with multiple approaches previously reported in the specialized literature. A 27-node test system is also used for locating photovoltaic (PV) sources considering the power capacity of the Caribbean region in Colombia during a typical sunny day. Numerical results confirm the efficiency and accuracy of the MINLP model and its solution is validated through the GAMS package. © 2019 Ain Shams UniversityUniversidad Nacional de Colombia, UN: 38945, 58838 P17211 Universidad Tecnológica de Pereira, UTP: C2019P011, C2018P020 Departamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS), COLCIENCIAS: 727-2015This work was funded in part by the Administrative Department of Science, Technology, and Innovation of Colombia (COLCIENCIAS) through its National Scholarship Program, under Grant 727-2015 ; in part by Instituto Tecnológico Metropolitano de Medellín, under Project P17211; in part by Universidad Tecnológica de Bolívar, under Projects C2018P020 and C2019P011; and in part by Universidad Nacional de Colombia, under Proyect ”Estrategia de transformación del sector energético Colombiano en el horizonte de 2030 - Energética 2030” - ”Generación distribuida de energía eléctrica en Colombia a partir de energía solar y eólica” (Code: 58838, Hermes: 38945). Oscar D. Montoya received his BEE, M.Sc. and Ph.D degrees in Electrical Engineering from Universidad Tecnológica de Pereira, Colombia, in 2012 and 2014 respectively. His research interests include mathematical optimization, planning and control of power systems, renewable energies, energy storage, protective devices and smartgrids. Walter Gil-González received his BEE and M.Sc. degrees in Electrical Engineering from Universidad Tecnológica de Pereira, Colombia, in 2011 and 2013 respectively. He is currently studying a Ph.D in Electrical Engineering at Universidad Tecnológica de Pereira, Colombia. His research interests include mathematical optimization, planning and control of power systems, renewable energies, energy storage, protective devices and smartgrids. Luis F. Grisales received his BEE and M.Sc. degrees in Electrical Engineering from Universidad Tecnológica de Pereira, Colombia, in 2013 and 2015 respectively. He is currently studying a Ph.D in Engineering at Universidad Nacional de Colombia. Actually, is professor in the Instituto TecnolÓgico Metropolitano de Medellín, attached to the Department of Electromechanics and mechatronics, member of the research group MATyER. His research interests include mathematical modelling, optimization techniques, planning and control of power systems, renewable energies, energy storage, power electronic and smartgrids

Linear-based Newton-Raphson Approximation for Power Flow Solution in DC Power Grids

This paper presents a linear-based Newton method for load flow solution in DC power grids. This approximation is based on the classical Taylor's series expansion combined to the open-circuit voltage obtained when all the constant power load points are disconnected. This solution strategy avoids the usage of an iterative process to solve the load flow problem in DC power grids reducing its processing time. Notwithstanding its simplicity, the proposed method is very accurate when is compared to classical Gauss-Seidel or Newton-Raphson methods concerning the solution quality. Simulation results are conducted via MATLAB software by using two radial test feeders composed by 10 and 33 nodes reported in the specialized literature. © 2018 IEEE

Optimal Integration of Distributed Generators into DC Microgrids Using a Hybrid Methodology: Genetic and Vortex Search Algorithms

This paper addresses the problem of optimal location and sizing of distributed generators (DGs) in direct current (DC) grids. To solve it, we propose an optimization approach with an objective function that aims to reduce power losses due to energy transport, while considering all the constraints that represent DC grids in a distributed generation environment. For the mathematical formulation of the problem, we used a mixed-integer nonlinear programming (MINLP) model, which allowed us to evaluate the impact of all possible configurations (i.e., location and size of DGs in the DC network) on the objective function and the constraints. The solution method proposed here is a master–slave strategy that implements a hybrid solution methodology that combines a genetic algorithm (GA) and the vortex search algorithm (VSA). The GA is in charge of solving the location problem in the master stage, and the VSA is responsible for sizing the DGs in the slave stage. To evaluate the effectiveness and robustness of the proposed GA/VSA methodology, we employed two test systems (i.e., 21 and 69 buses) considering a maximum penetration of distributed generation equal to 40% of the power generated by the slack buses. Furthermore, we also implemented nine other hybrid methodologies based on metaheuristic techniques (proposed in the literature for solving the problem addressed here) to make comparisons. All the solution methods used and proposed in this paper are based on sequential programming to avoid the need for specialized software and thus reduce the complexity and cost of the solutions. The effectiveness of the proposed solution was evaluated in two scenarios: (1) peak power demand and (2) variation in power generation and demand associated with photovoltaic generation and user demand in Medellín, Colombia. The results demonstrate that the GA/VSA methodology achieved the best results in terms of solution quality and processing times in all the test scenarios proposed in this study. © 2022, King Fahd University of Petroleum & Minerals

Economic Dispatch of BESS and renewable generators in DC microgrids using voltage-dependent load models

This paper addresses the optimal dispatch problem for battery energy storage systems (BESSs) in direct current (DC) mode for an operational period of 24 h. The problem is represented by a nonlinear programming (NLP) model that was formulated using an exponential voltage-dependent load model, which is the main contribution of this paper. An artificial neural network was employed for the short-term prediction of available renewable energy from wind and photovoltaic sources. The NLP model was solved by using the general algebraic modeling system (GAMS) to implement a 30-node test feeder composed of four renewable generators and three batteries. Simulation results demonstrate that the cost reduction for a daily operation is drastically affected by the operating conditions of the BESS, as well as the type of load model used. © 2019 MDPI AG. All rights reserved

Optimal Power Dispatch in Direct Current Networks to Reduce Energy Production Costs and CO 2 Emissions Using the Antlion Optimization Algorithm

In this study, we present a master–slave methodology to solve the problem of optimal power dispatch in a direct current (DC) microgrid. In the master stage, the Antlion Optimization (ALO) method solves the problem of power dispatch by the Distributed Generators (DGs); in the slave stage, a numerical method based on successive approximations (SA) evaluates the load flows required by the potential solutions proposed by the ALO technique. The objective functions in this paper are the minimization of energy production costs and the reduction of CO 2 emissions produced by the diesel generators in the microgrid. To favor energy efficiency and have a lower negative impact on the environment, the DC microgrids under study here include three DGs (one diesel generator and two generators based on renewable energy sources, i.e., solar energy and wind power) and a slack bus connected to a public electrical grid. The effectiveness of the proposed ALO–SA methodology was tested in the 21- and 69-bus test systems. We used three other optimization techniques to compare methods in the master stage: particle swarm optimization, continuous genetic algorithm, and black hole optimization. Additionally, we combined SA with every method to solve the load flow problem in the slave stage. The results show that, among the methods analyzed in this study, the proposed ALO–AS methodology achieves the best performance in terms of lower energy production costs, less CO 2 emissions, and shorter computational processing times. All the simulations were performed in MATLAB. © 2021, King Fahd University of Petroleum & Minerals.Ocampo-Toro, J. A., Garzon-Rivera, O. D., Grisales-Noreña, L. F., Montoya-Giraldo, O. D., & Gil-González, W. (2021). Optimal Power Dispatch in Direct Current Networks to Reduce Energy Production Costs and CO 2 Emissions Using the Antlion Optimization Algorithm. Arabian Journal for Science and Engineering, 46(10), 9995-10006