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In this paper, we propose a master–slave methodology to address the problem of optimal integration (location and sizing) of Distributed Generators (DGs) in Direct Current (DC) networks. This proposed methodology employs a parallel version of the Population-Based Incremental Learning (PPBIL) optimization method in the master stage to solve the location problem and the Vortex Search Algorithm (VSA) in the slave stage to solve the sizing problem. In addition, it uses the reduction of power losses as the objective function, considering all the constraints associated with the technical conditions specific to DGs and DC networks. To validate its effectiveness and robustness, we use as comparison methods, different solution methodologies that have been reported in the specialized literature, as well as two test systems (the 21 and 69-bus test systems). All simulations were performed in MATLAB. According to the results, the proposed hybrid (PPBIL–VSA) methodology provides the best trade-off between quality of the solution and processing times and exhibits an adequate repeatability every time it is executed.
Luis Fernando Grisales-Noreña; Oscar Danilo Montoya; Ricardo Alberto Hincapié-Isaza; Mauricio Granada Echeverri; Alberto-Jesus Perea-Moreno. Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSA. Mathematics 2021, 9, 1913 .
AMA StyleLuis Fernando Grisales-Noreña, Oscar Danilo Montoya, Ricardo Alberto Hincapié-Isaza, Mauricio Granada Echeverri, Alberto-Jesus Perea-Moreno. Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSA. Mathematics. 2021; 9 (16):1913.
Chicago/Turabian StyleLuis Fernando Grisales-Noreña; Oscar Danilo Montoya; Ricardo Alberto Hincapié-Isaza; Mauricio Granada Echeverri; Alberto-Jesus Perea-Moreno. 2021. "Optimal Location and Sizing of DGs in DC Networks Using a Hybrid Methodology Based on the PPBIL Algorithm and the VSA." Mathematics 9, no. 16: 1913.
This paper addresses the optimal power flow problem in direct current (DC) networks employing a master–slave solution methodology that combines an optimization algorithm based on the multiverse theory (master stage) and the numerical method of successive approximation (slave stage). The master stage proposes power levels to be injected by each distributed generator in the DC network, and the slave stage evaluates the impact of each power configuration (proposed by the master stage) on the objective function and the set of constraints that compose the problem. In this study, the objective function is the reduction of electrical power losses associated with energy transmission. In addition, the constraints are the global power balance, nodal voltage limits, current limits, and a maximum level of penetration of distributed generators. In order to validate the robustness and repeatability of the solution, this study used four other optimization methods that have been reported in the specialized literature to solve the problem addressed here: ant lion optimization, particle swarm optimization, continuous genetic algorithm, and black hole optimization algorithm. All of them employed the method based on successive approximation to solve the load flow problem (slave stage). The 21- and 69-node test systems were used for this purpose, enabling the distributed generators to inject
Andrés Rosales-Muñoz; Luis Grisales-Noreña; Jhon Montano; Oscar Montoya; Alberto-Jesus Perea-Moreno. Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Direct Current Electrical Networks. Sustainability 2021, 13, 8703 .
AMA StyleAndrés Rosales-Muñoz, Luis Grisales-Noreña, Jhon Montano, Oscar Montoya, Alberto-Jesus Perea-Moreno. Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Direct Current Electrical Networks. Sustainability. 2021; 13 (16):8703.
Chicago/Turabian StyleAndrés Rosales-Muñoz; Luis Grisales-Noreña; Jhon Montano; Oscar Montoya; Alberto-Jesus Perea-Moreno. 2021. "Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Direct Current Electrical Networks." Sustainability 13, no. 16: 8703.
The problem of the optimal load redistribution in electrical three-phase medium-voltage grids is addressed in this research from the point of view of mixed-integer convex optimization. The mathematical formulation of the load redistribution problem is developed in terminals of the distribution node by accumulating all active and reactive power loads per phase. These loads are used to propose an objective function in terms of minimization of the average unbalanced (asymmetry) grade of the network with respect to the ideal mean consumption per-phase. The objective function is defined as the
Oscar Montoya; Andres Arias-Londoño; Luis Grisales-Noreña; José Barrios; Harold Chamorro. Optimal Demand Reconfiguration in Three-Phase Distribution Grids Using an MI-Convex Model. Symmetry 2021, 13, 1124 .
AMA StyleOscar Montoya, Andres Arias-Londoño, Luis Grisales-Noreña, José Barrios, Harold Chamorro. Optimal Demand Reconfiguration in Three-Phase Distribution Grids Using an MI-Convex Model. Symmetry. 2021; 13 (7):1124.
Chicago/Turabian StyleOscar Montoya; Andres Arias-Londoño; Luis Grisales-Noreña; José Barrios; Harold Chamorro. 2021. "Optimal Demand Reconfiguration in Three-Phase Distribution Grids Using an MI-Convex Model." Symmetry 13, no. 7: 1124.
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 \(\hbox {CO}_2\) 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 \(\hbox {CO}_2\) emissions, and shorter computational processing times. All the simulations were performed in MATLAB.
J. A. Ocampo-Toro; O. D. Garzon-Rivera; L. F. Grisales-Noreña; O. D. Montoya-Giraldo; W. Gil-González. Optimal Power Dispatch in Direct Current Networks to Reduce Energy Production Costs and $$\hbox {CO}_2$$ Emissions Using the Antlion Optimization Algorithm. Arabian Journal for Science and Engineering 2021, 1 -12.
AMA StyleJ. A. Ocampo-Toro, O. D. Garzon-Rivera, L. F. Grisales-Noreña, O. D. Montoya-Giraldo, W. Gil-González. Optimal Power Dispatch in Direct Current Networks to Reduce Energy Production Costs and $$\hbox {CO}_2$$ Emissions Using the Antlion Optimization Algorithm. Arabian Journal for Science and Engineering. 2021; ():1-12.
Chicago/Turabian StyleJ. A. Ocampo-Toro; O. D. Garzon-Rivera; L. F. Grisales-Noreña; O. D. Montoya-Giraldo; W. Gil-González. 2021. "Optimal Power Dispatch in Direct Current Networks to Reduce Energy Production Costs and $$\hbox {CO}_2$$ Emissions Using the Antlion Optimization Algorithm." Arabian Journal for Science and Engineering , no. : 1-12.
This paper addresses the phase-balancing problem in three-phase power grids with the radial configuration from the perspective of master–slave optimization. The master stage corresponds to an improved version of the Chu and Beasley genetic algorithm, which is based on the multi-point mutation operator and the generation of solutions using a Gaussian normal distribution based on the exploration and exploitation schemes of the vortex search algorithm. The master stage is entrusted with determining the configuration of the phases by using an integer codification. In the slave stage, a power flow for imbalanced distribution grids based on the three-phase version of the successive approximation method was used to determine the costs of daily energy losses. The objective of the optimization model is to minimize the annual operative costs of the network by considering the daily active and reactive power curves. Numerical results from a modified version of the IEEE 37-node test feeder demonstrate that it is possible to reduce the annual operative costs of the network by approximately 20% by using optimal load balancing. In addition, numerical results demonstrated that the improved version of the CBGA is at least three times faster than the classical CBGA, this was obtained in the peak load case for a test feeder composed of 15 nodes; also, the improved version of the CBGA was nineteen times faster than the vortex search algorithm. Other comparisons with the sine–cosine algorithm and the black hole optimizer confirmed the efficiency of the proposed optimization method regarding running time and objective function values.
Oscar Montoya; Alexander Molina-Cabrera; Luis Grisales-Noreña; Ricardo Hincapié; Mauricio Granada. Improved Genetic Algorithm for Phase-Balancing in Three-Phase Distribution Networks: A Master-Slave Optimization Approach. Computation 2021, 9, 67 .
AMA StyleOscar Montoya, Alexander Molina-Cabrera, Luis Grisales-Noreña, Ricardo Hincapié, Mauricio Granada. Improved Genetic Algorithm for Phase-Balancing in Three-Phase Distribution Networks: A Master-Slave Optimization Approach. Computation. 2021; 9 (6):67.
Chicago/Turabian StyleOscar Montoya; Alexander Molina-Cabrera; Luis Grisales-Noreña; Ricardo Hincapié; Mauricio Granada. 2021. "Improved Genetic Algorithm for Phase-Balancing in Three-Phase Distribution Networks: A Master-Slave Optimization Approach." Computation 9, no. 6: 67.
The power flow problem in three-phase unbalanced distribution networks is addressed in this research using a derivative-free numerical method based on the upper-triangular matrix. The upper-triangular matrix is obtained from the topological connection among nodes of the network (i.e., through a graph-based method). The main advantage of the proposed three-phase power flow method is the possibility of working with single-, two-, and three-phase loads, including
Oscar Montoya; Juan Giraldo; Luis Grisales-Noreña; Harold Chamorro; Lazaro Alvarado-Barrios. Accurate and Efficient Derivative-Free Three-Phase Power Flow Method for Unbalanced Distribution Networks. Computation 2021, 9, 61 .
AMA StyleOscar Montoya, Juan Giraldo, Luis Grisales-Noreña, Harold Chamorro, Lazaro Alvarado-Barrios. Accurate and Efficient Derivative-Free Three-Phase Power Flow Method for Unbalanced Distribution Networks. Computation. 2021; 9 (6):61.
Chicago/Turabian StyleOscar Montoya; Juan Giraldo; Luis Grisales-Noreña; Harold Chamorro; Lazaro Alvarado-Barrios. 2021. "Accurate and Efficient Derivative-Free Three-Phase Power Flow Method for Unbalanced Distribution Networks." Computation 9, no. 6: 61.
This work proposed a base method for automated assessment of Small Hydro-Power (SHP) potential for a run-of-river (RoR) scheme using geographic information systems (GIS). The hydro-power potential (HP) was represented through a comprehensive methodology consisting of a structured raster database. A calibrated and validated hydrological model (Soil and Water Assessment Tool—SWAT) was used to estimate monthly streamflow as the Mesh Sweeping Approach (MSA) driver. The methodology was applied for the upper part of the Huazuntlan River Watershed in Los Tuxtlas Mountains, Mexico. The MSA divided the study area into a rectangular mesh. Then, at every location within the mesh, SHP was obtained. The main components of the MSA as a RoR scheme were the intake, the powerhouse, and the surge tank. The surge tank was located at cells where the hydro-power was calculated and used as a reference to later locate the intake and powerhouse by maximizing the discharge and head. SHP calculation was performed by sweeping under different values of the penstock’s length, and the headrace’s length. The maximum permissible lengths for these two variables represented potential hydro-power generation locations. Results showed that the headrace’s length represented the major contribution for hydro-power potential estimation. Additionally, values of 2000 m and 1500 m for the penstock and the headrace were considered potential thresholds as there is no significant increment in hydro-power after increasing any of these values. The availability of hydro-power on a raster representation has advantages for further hydro-power data analysis and processing.
Gerardo Alcalá; Luis Grisales-Noreña; Quetzalcoatl Hernandez-Escobedo; Jose Muñoz-Criollo; J. Revuelta-Acosta. SHP Assessment for a Run-of-River (RoR) Scheme Using a Rectangular Mesh Sweeping Approach (MSA) Based on GIS. Energies 2021, 14, 3095 .
AMA StyleGerardo Alcalá, Luis Grisales-Noreña, Quetzalcoatl Hernandez-Escobedo, Jose Muñoz-Criollo, J. Revuelta-Acosta. SHP Assessment for a Run-of-River (RoR) Scheme Using a Rectangular Mesh Sweeping Approach (MSA) Based on GIS. Energies. 2021; 14 (11):3095.
Chicago/Turabian StyleGerardo Alcalá; Luis Grisales-Noreña; Quetzalcoatl Hernandez-Escobedo; Jose Muñoz-Criollo; J. Revuelta-Acosta. 2021. "SHP Assessment for a Run-of-River (RoR) Scheme Using a Rectangular Mesh Sweeping Approach (MSA) Based on GIS." Energies 14, no. 11: 3095.
The problem of the optimal operation of battery energy storage systems (BESSs) in AC grids is addressed in this paper from the point of view of multi-objective optimization. A nonlinear programming (NLP) model is presented to minimize the total emissions of contaminant gasses to the atmosphere and costs of daily energy losses simultaneously, considering the AC grid complete model. The BESSs are modeled with their linear relation between the state-of-charge and the active power injection/absorption. The Pareto front for the multi-objective optimization NLP model is reached through the general algebraic modeling system, i.e., GAMS, implementing the pondered optimization approach using weighting factors for each objective function. Numerical results in the IEEE 33-bus and IEEE 69-node test feeders demonstrate the multi-objective nature of this optimization problem and the multiple possibilities that allow the grid operators to carry out an efficient operation of their distribution networks when BESS and renewable energy resources are introduced.
Federico Molina-Martin; Oscar Montoya; Luis Grisales-Noreña; Jesus Hernández; Carlos Ramírez-Vanegas. Simultaneous Minimization of Energy Losses and Greenhouse Gas Emissions in AC Distribution Networks Using BESS. Electronics 2021, 10, 1002 .
AMA StyleFederico Molina-Martin, Oscar Montoya, Luis Grisales-Noreña, Jesus Hernández, Carlos Ramírez-Vanegas. Simultaneous Minimization of Energy Losses and Greenhouse Gas Emissions in AC Distribution Networks Using BESS. Electronics. 2021; 10 (9):1002.
Chicago/Turabian StyleFederico Molina-Martin; Oscar Montoya; Luis Grisales-Noreña; Jesus Hernández; Carlos Ramírez-Vanegas. 2021. "Simultaneous Minimization of Energy Losses and Greenhouse Gas Emissions in AC Distribution Networks Using BESS." Electronics 10, no. 9: 1002.
This paper addresses the problem of optimal conductor selection in direct current (DC) distribution networks with radial topology. A nonlinear mixed-integer programming model (MINLP) is developed through a branch-to-node incidence matrix. An important contribution is that the proposed MINLP model integrates a set of constraints related to the telescopic structure of the network, which allows reducing installation costs. The proposed model also includes a time-domain dependency that helps analyze the DC network under different load conditions, including renewable generation and battery energy storage systems, and different voltage regulation operative consigns. The objective function of the proposed model is made up of the total investment in conductors and the total cost of energy losses in one year of operation. These components of the objective function show multi-objective behavior. For this reason, different simulation scenarios are performed to identify their effects on the final grid configuration. An illustrative 10-nodes medium-voltage DC grid with 9 lines is used to carry out all the simulations through the General Algebraic Modeling System known as GAMS.
Oscar Danilo Montoya; Walter Gil-González; Luis F. Grisales-Noreña. On the mathematical modeling for optimal selecting of calibers of conductors in DC radial distribution networks: An MINLP approach. Electric Power Systems Research 2021, 194, 107072 .
AMA StyleOscar Danilo Montoya, Walter Gil-González, Luis F. Grisales-Noreña. On the mathematical modeling for optimal selecting of calibers of conductors in DC radial distribution networks: An MINLP approach. Electric Power Systems Research. 2021; 194 ():107072.
Chicago/Turabian StyleOscar Danilo Montoya; Walter Gil-González; Luis F. Grisales-Noreña. 2021. "On the mathematical modeling for optimal selecting of calibers of conductors in DC radial distribution networks: An MINLP approach." Electric Power Systems Research 194, no. : 107072.
The problem of the optimal placement and dimensioning of constant power sources (i.e., distributed generators) in electrical direct current (DC) distribution networks has been addressed in this research from the point of view of convex optimization. The original mixed-integer nonlinear programming (MINLP) model has been transformed into a mixed-integer conic equivalent via second-order cone programming, which produces a MI-SOCP approximation. The main advantage of the proposed MI-SOCP model is the possibility of ensuring global optimum finding using a combination of the branch and bound method to address the integer part of the problem (i.e., the location of the power sources) and the interior-point method to solve the dimensioning problem. Numerical results in the 21- and 69-node test feeders demonstrated its efficiency and robustness compared to an exact MINLP method available in GAMS: in the case of the 69-node test feeders, the exact MINLP solvers are stuck in local optimal solutions, while the proposed MI-SOCP model enables the finding of the global optimal solution. Additional simulations with daily load curves and photovoltaic sources confirmed the effectiveness of the proposed MI-SOCP methodology in locating and sizing distributed generators in DC grids; it also had low processing times since the location of three photovoltaic sources only requires 233.16s, which is 3.7 times faster than the time required by the SOCP model in the absence of power sources.
Federico Molina-Martin; Oscar Danilo Montoya; Luis Fernando Grisales-Noreña; Jesus C. Hernández. A Mixed-Integer Conic Formulation for Optimal Placement and Dimensioning of DGs in DC Distribution Networks. Electronics 2021, 10, 176 .
AMA StyleFederico Molina-Martin, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña, Jesus C. Hernández. A Mixed-Integer Conic Formulation for Optimal Placement and Dimensioning of DGs in DC Distribution Networks. Electronics. 2021; 10 (2):176.
Chicago/Turabian StyleFederico Molina-Martin; Oscar Danilo Montoya; Luis Fernando Grisales-Noreña; Jesus C. Hernández. 2021. "A Mixed-Integer Conic Formulation for Optimal Placement and Dimensioning of DGs in DC Distribution Networks." Electronics 10, no. 2: 176.
This paper analyzes the problem of optimally sizing a transmission shaft via the vortex search algorithm (VSA) optimizer. The objective function was to minimize the shaft weight through an adequate selection of the diameters of each section of the device, and the constraints were the physical conditions that should be met to design safe, fatigue-proof shafts. The solution and the mathematical model were validated using Autodesk Inventor. In addition, the performance of the VSA was compared to that of the continuous genetic algorithm . The numerical results show that the programmed model has the physical and methodological characteristics needed to produce a better output than conventional design techniques. Therefore, this model can be a powerful tool to solve nonlinear non-convex optimization problems such as the case investigated here.
M. A. Rodriguez-Cabal; J. D. Betancur-Gómez; L. F. Grisales-Noreña; Oscar Danilo Montoya; Diego Hincapie. Optimal Design of Transmission Shafts Using a Vortex Search Algorithm. Arabian Journal for Science and Engineering 2021, 46, 3293 -3300.
AMA StyleM. A. Rodriguez-Cabal, J. D. Betancur-Gómez, L. F. Grisales-Noreña, Oscar Danilo Montoya, Diego Hincapie. Optimal Design of Transmission Shafts Using a Vortex Search Algorithm. Arabian Journal for Science and Engineering. 2021; 46 (4):3293-3300.
Chicago/Turabian StyleM. A. Rodriguez-Cabal; J. D. Betancur-Gómez; L. F. Grisales-Noreña; Oscar Danilo Montoya; Diego Hincapie. 2021. "Optimal Design of Transmission Shafts Using a Vortex Search Algorithm." Arabian Journal for Science and Engineering 46, no. 4: 3293-3300.
This study analyzes the numerical convergence and processing time required by several classical and new solution methods proposed in the literature to solve the power-flow problem (PF) in direct-current (DC) networks considering radial and mesh topologies. Three classical numerical methods were studied: Gauss–Jacobi, Gauss–Seidel, and Newton–Raphson. In addition, two unconventional methods were selected. They are iterative and allow solving the DC PF in radial and mesh configurations. The first method uses a Taylor series expansion and a set of decoupling equations to linearize around the desired operating point. The second method manipulates the set of non-linear equations of the DC PF to transform it into a conventional fixed-point form. Moreover, this method is used to develop a successive approximation methodology. For the particular case of radial topology, three methods based on triangular matrix formulation, graph theory, and scanning algorithms were analyzed. The main objective of this study was to identify the methods with the best performance in terms of quality of solution (i.e., numerical convergence) and processing time to solve the DC power flow in mesh and radial distribution networks. We aimed at offering to the reader a set of PF methodologies to analyze electrical DC grids. The PF performance of the analyzed solution methods was evaluated through six test feeders; all of them were employed in prior studies for the same application. The simulation results show the adequate performance of the power-flow methods reviewed in this study, and they permit the selection of the best solution method for radial and mesh structures.
Luis Fernando Grisales-Noreña; Oscar Danilo Montoya; Walter Julian Gil-González; Alberto-Jesus Perea-Moreno; Miguel-Angel Perea-Moreno. A Comparative Study on Power Flow Methods for Direct-Current Networks Considering Processing Time and Numerical Convergence Errors. Electronics 2020, 9, 2062 .
AMA StyleLuis Fernando Grisales-Noreña, Oscar Danilo Montoya, Walter Julian Gil-González, Alberto-Jesus Perea-Moreno, Miguel-Angel Perea-Moreno. A Comparative Study on Power Flow Methods for Direct-Current Networks Considering Processing Time and Numerical Convergence Errors. Electronics. 2020; 9 (12):2062.
Chicago/Turabian StyleLuis Fernando Grisales-Noreña; Oscar Danilo Montoya; Walter Julian Gil-González; Alberto-Jesus Perea-Moreno; Miguel-Angel Perea-Moreno. 2020. "A Comparative Study on Power Flow Methods for Direct-Current Networks Considering Processing Time and Numerical Convergence Errors." Electronics 9, no. 12: 2062.
This research addresses the problem of the optimal location and sizing distributed generators (DGs) in direct current (DC) distribution networks from the combinatorial optimization. It is proposed a master–slave optimization approach in order to solve the problems of placement and location of DGs, respectively. The master stage applies to the classical Chu & Beasley genetic algorithm (GA), while the slave stage resolves a second-order cone programming reformulation of the optimal power flow problem for DC grids. This master–slave approach generates a hybrid optimization approach, named GA-SOCP. The main advantage of optimal dimensioning of DGs via SOCP is that this method makes part of the exact mathematical optimization that guarantees the possibility of finding the global optimal solution due to the solution space’s convex structure, which is a clear improvement regarding classical metaheuristic optimization methodologies. Numerical comparisons with hybrid and exact optimization approaches reported in the literature demonstrate the proposed hybrid GA-SOCP approach’s effectiveness and robustness to achieve the global optimal solution. Two test feeders compose of 21 and 69 nodes that can locate three distributed generators are considered. All of the computational validations have been carried out in the MATLAB software and the CVX tool for convex optimization.
Oscar Danilo Montoya; Walter Gil-González; Luis Fernando Grisales-Noreña. Hybrid GA-SOCP Approach for Placement and Sizing of Distributed Generators in DC Networks. Applied Sciences 2020, 10, 8616 .
AMA StyleOscar Danilo Montoya, Walter Gil-González, Luis Fernando Grisales-Noreña. Hybrid GA-SOCP Approach for Placement and Sizing of Distributed Generators in DC Networks. Applied Sciences. 2020; 10 (23):8616.
Chicago/Turabian StyleOscar Danilo Montoya; Walter Gil-González; Luis Fernando Grisales-Noreña. 2020. "Hybrid GA-SOCP Approach for Placement and Sizing of Distributed Generators in DC Networks." Applied Sciences 10, no. 23: 8616.
This paper addresses the problem of the locating and sizing of distributed generators (DGs) in direct current (DC) grids and proposes a hybrid methodology based on a parallel version of the Population-Based Incremental Learning (PPBIL) algorithm and the Particle Swarm Optimization (PSO) method. The objective function of the method is based on the reduction of the power loss by using a master-slave structure and the consideration of the set of restrictions associated with DC grids in a distributed generation environment. In such a structure, the master stage (PPBIL) finds the location of the generators and the slave stage (PSO) finds the corresponding sizes. For the purpose of comparison, eight additional hybrid methods were formed by using two additional location methods and two additional sizing methods, and this helped in the evaluation of the effectiveness of the proposed solution. Such an evaluation is illustrated with the electrical test systems composed of 10, 21 and 69 buses and simulated on the software, MATLAB. Finally, the results of the simulation demonstrated that the PPBIL–PSO method obtains the best balance between the reduction of power loss and the processing time.
Luis Grisales-Noreña; Oscar Montoya; Carlos Ramos-Paja; Quetzalcoatl Hernandez-Escobedo; Alberto-Jesus Perea-Moreno. Optimal Location and Sizing of Distributed Generators in DC Networks Using a Hybrid Method Based on Parallel PBIL and PSO. Electronics 2020, 9, 1808 .
AMA StyleLuis Grisales-Noreña, Oscar Montoya, Carlos Ramos-Paja, Quetzalcoatl Hernandez-Escobedo, Alberto-Jesus Perea-Moreno. Optimal Location and Sizing of Distributed Generators in DC Networks Using a Hybrid Method Based on Parallel PBIL and PSO. Electronics. 2020; 9 (11):1808.
Chicago/Turabian StyleLuis Grisales-Noreña; Oscar Montoya; Carlos Ramos-Paja; Quetzalcoatl Hernandez-Escobedo; Alberto-Jesus Perea-Moreno. 2020. "Optimal Location and Sizing of Distributed Generators in DC Networks Using a Hybrid Method Based on Parallel PBIL and PSO." Electronics 9, no. 11: 1808.
This paper deals with a classical problem in power system analysis regarding the optimal location and sizing of distributed generators (DGs) in direct current (DC) distribution networks using the mathematical optimization. This optimization problem is divided into two sub-problems as follows: the optimal location of DGs is a problem, with those with a binary structure being the first sub-problem; and the optimal sizing of DGs with a nonlinear programming (NLP) structure is the second sub-problem. These problems originate from a general mixed-integer nonlinear programming model (MINLP), which corresponds to an NP-hard optimization problem. It is not possible to provide the global optimum with conventional programming methods. A mixed-integer semidefinite programming (MI-SDP) model is proposed to address this problem, where the binary part is solved via the branch and bound (B&B) methods and the NLP part is solved via convex optimization (i.e., SDP). The main advantage of the proposed MI-SDP model is the possibility of guaranteeing a global optimum solution if each of the nodes in the B&B search is convex, as is ensured by the SDP method. Numerical validations in two test feeders composed of 21 and 69 nodes demonstrate that in all of these problems, the optimal global solution is reached by the MI-SDP approach, compared to the classical metaheuristic and hybrid programming models reported in the literature. All the simulations have been carried out using the MATLAB software with the CVX tool and the Mosek solver.
Walter Gil-González; Alexander Molina-Cabrera; Oscar Danilo Montoya; Luis Fernando Grisales-Noreña. An MI-SDP Model for Optimal Location and Sizing of Distributed Generators in DC Grids That Guarantees the Global Optimum. Applied Sciences 2020, 10, 7681 .
AMA StyleWalter Gil-González, Alexander Molina-Cabrera, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña. An MI-SDP Model for Optimal Location and Sizing of Distributed Generators in DC Grids That Guarantees the Global Optimum. Applied Sciences. 2020; 10 (21):7681.
Chicago/Turabian StyleWalter Gil-González; Alexander Molina-Cabrera; Oscar Danilo Montoya; Luis Fernando Grisales-Noreña. 2020. "An MI-SDP Model for Optimal Location and Sizing of Distributed Generators in DC Grids That Guarantees the Global Optimum." Applied Sciences 10, no. 21: 7681.
Objective: In this paper, is present a hybrid optimization methodology for the optimal location and sizing of distributed generators (DGs) in electrical distribution networks. We propose a mixed-integer nonlinear problem (MINLP) model for the mathematical formulation, whose objective function is the minimization of power losses due to the Joule effect in conductors. The constraints we considered include active and reactive power balance, voltage regulation, percentage of penetration of DGs into the distribution network, and total DGs allowed in such network. Methodology: To solve the MINLP model, we employed a master–slave strategy that uses the Chu-Beasley genetic algorithm (CBGA) and the optimal power flow (OPF) model as the master and slave algorithms, respectively. This hybrid technique helps to reduce the complexity of the MINLP model by eliminating binary variables through the master algorithm and then solving the resulting Nonlinear problem (NLP), which corresponds to the OPF model, using a classical interior-point method available in MATLAB’s fmincon toolbox. Results: We tested the efficiency and robustness of the proposed methodology in 33- and 69-node radial distribution networks. The results show its high performance in terms of power loss reduction and final sizing of DGs Conclusions: The results obtained in the test systems under analysis reveal that there is a direct and proportional relationship between technical losses, the percentage of distributed generation penetration, and the number of generators available.
Walter Gil-González; Oscar Danilo Montoya; Luis Fernando Grisales-Noreña; Carlos Alberto Ramírez Vanegas; Alexander Molina Cabrera. Hybrid Optimization Strategy for Optimal Location and Sizing of DG in Distribution Networks. Tecnura 2020, 24, 47 -61.
AMA StyleWalter Gil-González, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña, Carlos Alberto Ramírez Vanegas, Alexander Molina Cabrera. Hybrid Optimization Strategy for Optimal Location and Sizing of DG in Distribution Networks. Tecnura. 2020; 24 (66):47-61.
Chicago/Turabian StyleWalter Gil-González; Oscar Danilo Montoya; Luis Fernando Grisales-Noreña; Carlos Alberto Ramírez Vanegas; Alexander Molina Cabrera. 2020. "Hybrid Optimization Strategy for Optimal Location and Sizing of DG in Distribution Networks." Tecnura 24, no. 66: 47-61.
This paper deals with the problem of the optimal selection of capacitor banks in electrical AC distribution systems for minimizing the costs of energy losses during a year of operation through a discrete version of the vortex search algorithm (DVSA). This algorithm works with a hypersphere with a variable radius defined by an exponential function where a Gaussian distribution is used to generate a set of candidate solutions uniformly distributed around the center of this hypersphere. This center corresponds to the best solution obtained at the iteration t, which is initialized at the center of the solution space at the iterative search beginning. The main advantage of combining the exponential function with the Gaussian distribution is the correct balance between the exploration and exploitation of the solution space, which allows reaching the global optimal solution of the optimization problem with a low standard deviation, i.e., guaranteeing repeatability at each simulation. Two classical distribution networks composed of 33 and 69 nodes were used to validate the proposed DVSA algorithm. They demonstrated that the DVSA improves numerical reports found in specialized literature regarding the optimal selection and location of fixed-step capacitor banks with a low computational burden. All the simulations were carried out in MATLAB software.
Walter Gil-González; Oscar Danilo Montoya; Arul Rajagopalan; Luis Fernando Grisales-Noreña; Jesus C. Hernández. Optimal Selection and Location of Fixed-Step Capacitor Banks in Distribution Networks Using a Discrete Version of the Vortex Search Algorithm. Energies 2020, 13, 4914 .
AMA StyleWalter Gil-González, Oscar Danilo Montoya, Arul Rajagopalan, Luis Fernando Grisales-Noreña, Jesus C. Hernández. Optimal Selection and Location of Fixed-Step Capacitor Banks in Distribution Networks Using a Discrete Version of the Vortex Search Algorithm. Energies. 2020; 13 (18):4914.
Chicago/Turabian StyleWalter Gil-González; Oscar Danilo Montoya; Arul Rajagopalan; Luis Fernando Grisales-Noreña; Jesus C. Hernández. 2020. "Optimal Selection and Location of Fixed-Step Capacitor Banks in Distribution Networks Using a Discrete Version of the Vortex Search Algorithm." Energies 13, no. 18: 4914.
In the last decade, the deployment of electric vehicles (EVs) has been largely promoted. This development has increased challenges in the power systems in the context of planning and operation due to the massive amount of recharge needed for EVs. Furthermore, EVs may also offer new opportunities and can be used to support the grid to provide auxiliary services. In this regard, and considering the research around EVs and power grids, this paper presents a chronological background review of EVs and their interactions with power systems, particularly electric distribution networks, considering publications from the IEEE Xplore database. The review is extended from 1973 to 2019 and is developed via systematic classification using key categories that describe the types of interactions between EVs and power grids. These interactions are in the framework of the power quality, study of scenarios, electricity markets, demand response, demand management, power system stability, Vehicle-to-Grid (V2G) concept, and optimal location of battery swap and charging stations.
Andrés Arias-Londoño; Oscar Danilo Montoya; Luis Fernando Grisales-Noreña. A Chronological Literature Review of Electric Vehicle Interactions with Power Distribution Systems. Energies 2020, 13, 3016 .
AMA StyleAndrés Arias-Londoño, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña. A Chronological Literature Review of Electric Vehicle Interactions with Power Distribution Systems. Energies. 2020; 13 (11):3016.
Chicago/Turabian StyleAndrés Arias-Londoño; Oscar Danilo Montoya; Luis Fernando Grisales-Noreña. 2020. "A Chronological Literature Review of Electric Vehicle Interactions with Power Distribution Systems." Energies 13, no. 11: 3016.
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.
Oscar Danilo Montoya; Walter Gil-González; L.F. Grisales-Noreña. An exact MINLP model for optimal location and sizing of DGs in distribution networks: A general algebraic modeling system approach. Ain Shams Engineering Journal 2020, 11, 409 -418.
AMA StyleOscar Danilo Montoya, Walter Gil-González, L.F. Grisales-Noreña. An exact MINLP model for optimal location and sizing of DGs in distribution networks: A general algebraic modeling system approach. Ain Shams Engineering Journal. 2020; 11 (2):409-418.
Chicago/Turabian StyleOscar Danilo Montoya; Walter Gil-González; L.F. Grisales-Noreña. 2020. "An exact MINLP model for optimal location and sizing of DGs in distribution networks: A general algebraic modeling system approach." Ain Shams Engineering Journal 11, no. 2: 409-418.
This paper proposes an energy management system (EMS) for the day-ahead dispatch of battery storage systems (BSS) under a distributed generation environment for direct current (DC) networks, with the main objective of reducing the cost of the energy purchased to the utility grid. This approach considers the state-of-charge (SOC) of the BSS and the production variation of the renewable generators, in particular of wind and photovoltaic technologies, and the variations in the power consumption and energy costs. The proposed EMS uses a master-slave strategy formed by a parallel implementation of the particle swarm optimizer (PPSO) and a multi-period power flow method based on successive approximations (SA), with the aim of achieving the optimal daily operation of the BSS. The objective function selected for the optimization was the reduction of the energy purchasing costs, also including the power balance, devices capabilities and voltage regulation. The effectiveness of the EMS is evaluated in a test system of 21 buses, comparing the solution quality and speed with three optimization techniques published in literature: a black hole optimizer, a continuous genetic algorithm with matrix structure, and a traditional Chu & Beasley genetic algorithm. In addition, two simulation scenarios were used to identify the optimal final SOC conditions for the BSS. Finally, the results show that the proposed EMS provides the best trade-off between quality solution and speed. The simulations are conducted in MATLAB software using sequential quadratic programming.
L.F. Grisales-Noreña; Oscar Danilo Montoya; Carlos Andrés Ramos-Paja. An energy management system for optimal operation of BSS in DC distributed generation environments based on a parallel PSO algorithm. Journal of Energy Storage 2020, 29, 101488 .
AMA StyleL.F. Grisales-Noreña, Oscar Danilo Montoya, Carlos Andrés Ramos-Paja. An energy management system for optimal operation of BSS in DC distributed generation environments based on a parallel PSO algorithm. Journal of Energy Storage. 2020; 29 ():101488.
Chicago/Turabian StyleL.F. Grisales-Noreña; Oscar Danilo Montoya; Carlos Andrés Ramos-Paja. 2020. "An energy management system for optimal operation of BSS in DC distributed generation environments based on a parallel PSO algorithm." Journal of Energy Storage 29, no. : 101488.