A chronological literature review of electric vehicle interactions with power distribution systems

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.Introduction General Overview Chronological Review: Part I Chronological Review: Part II Brief Observations Conclusions and Future Works Final Reflections Author Contributions Funding Acknowledgments Conflicts of Interest Reference

A linearized approach for the electric light commercial vehicle routing problem combined with charging station siting and power distribution network assessment

Transportation electrification has demonstrated a significant position on power utilities and logistic companies, in terms of assets operation and management. Under this context, this paper presents the problem of seeking feasible and good quality routes for electric light commercial vehicles considering battery capacity and charging station siting on the power distribution system. Different transportation patterns for goods delivery are included, such as the capacitated vehicle routing problem and the shortest path problem for the last mile delivery. To solve the problem framed within a mixed integer linear mathematical model, the GAMS software is used and validated on a test instance conformed by a 19-customer transportation network, spatially combined with the IEEE 34 nodes power distribution system. The sensitivity analysis, performed during the computational experiments, show the behavior of the variables involved in the logistics operation, i.e., routing cost for each transport pattern. The trade-off between the battery capacity, the cost of the charging station installation, and energy losses on the power distribution system is also shown, including the energy consumption cost created by the charging operation.Universidad Tecnológica de Bolíva

Solution of the Optimal Reactive Power Flow Problem Using a Discrete-Continuous CBGA Implemented in the DigSILENT Programming Language

The problem of the optimal reactive power flow in transmission systems is addressed in this research from the point of view of combinatorial optimization. A discrete-continuous version of the Chu & Beasley genetic algorithm (CBGA) is proposed to model continuous variables such as voltage outputs in generators and reactive power injection in capacitor banks, as well as binary variables such as tap positions in transformers. The minimization of the total power losses is considered as the objective performance indicator. The main contribution in this research corresponds to the implementation of the CBGA in the DigSILENT Programming Language (DPL), which exploits the advantages of the power flow tool at a low computational effort. The solution of the optimal reactive power flow problem in power systems is a key task since the efficiency and secure operation of the whole electrical system depend on the adequate distribution of the reactive power in generators, transformers, shunt compensators, and transmission lines. To provide an efficient optimization tool for academics and power system operators, this paper selects the DigSILENT software, since this is widely used for power systems for industries and researchers. Numerical results in three IEEE test feeders composed of 6, 14, and 39 buses demonstrate the efficiency of the proposed CBGA in the DPL environment from DigSILENT to reduce the total grid power losses (between 21.17% to 37.62% of the benchmark case) considering four simulation scenarios regarding voltage regulation bounds and slack voltage outputs. In addition, the total processing times for the IEEE 6-, 14-, and 39-bus systems were 32.33 s, 49.45 s, and 138.88 s, which confirms the low computational effort of the optimization methods directly implemented in the DPL environmen

Voltage Stability Analysis in Medium-Voltage Distribution Networks Using a Second-Order Cone Approximation

This paper addresses the voltage stability margin calculation in medium-voltage distribution networks in the context of exact mathematical modeling. This margin calculation is performed with a second-order cone (SOCP) reformulation of the classical nonlinear non-convex optimal power flow problems. The main idea around the SOCP approximation is to guarantee the global optimal solution via convex optimization, considering as the objective function the λ-coefficient associated with the maximum possible increment of the load consumption at all the nodes. Different simulation cases are considered in one test feeder, described as follows: (i) the distribution network without penetration of distributed generation; (ii) the distribution network with penetration of distributed generation; and (iii) the distribution grid with capacitive compensation. Numerical results in the test system demonstrated the effectiveness of the proposed SOCP approximation to determine the λ-coefficient. In addition, the proposed approximation is compared with nonlinear tools available in the literature. All the simulations are carried out in the MATLAB software with the CVX package and the Gurobi solver

/ Aplicación de la metodología de sistemas suaves en un problema relacionado con la estrategia de innovación en el marco de modelos de gestión de innovación

    El artículo presenta una aplicación de la metodología de sistemas suaves en un problema relacionado con el Método Delphi y su alineamiento con una estrategia de innovación en el marco de un modelo de gestión de innovación, con el fin de generar un problema mejorado. Entre los principales resultados se destaca la ventaja del uso de la metodología de sistemas suaves para ayudar en el mejoramiento de problemas de actividad humana no estructurados relacionados, en este caso específico con un problema relacionado  con el método Delphi y su alineamiento con la estrategia de innovación empresarial en el marco de modelos de gestión de innovación, así como la posibilidad de complementar la metodología de sistemas suaves con cuestionarios de priorización para obtener opiniones de expertos para el mejoramiento del entendimiento del problema.The article presents an application of the soft systems methodology- SSM on a problem related to the Delphi Method and its alignment with an innovation strategy in the framework of a management model innovation, in order to generate an improved problem. Amongst the major findings throughout the case, highlights the advantages of using soft systems methodology to assist in the improvement of non-structured human activity problems, in this specific case, a problem associated with Delphi method and its alignment with the business innovation strategy in the context of innovation management models, additionally, the possibility of complementing the soft systems methodology prioritization questionnaires for expert opinions for improving the understanding of the problem

Flujo de Potencia Óptimo de Ramas para Redes DC con Estructura Radial: Una Relajación Cónica

Abstract Objective: This work involves a convex-based mathematical reformulation for the optimal power flow problem in DC networks. The objective of the proposed optimization model corresponds to the minimization of the power losses through all the network branches considering a convex conic model that warranties finding the global optimal. Methodology: This is split into three stages: The first stage presents the mathematical model of optimal power flow for DC networks and all its geometric features that make it non-convex; the second stage presents the convex reformulation from a second order conic relaxation; the third stage shows the main characteristics of the DC system under study; and the fourth stage presents the optimal solution of the power flow problem and its comparisons with some methods reported in the specialized literature.     Results: The numerical validations demonstrate that the model of proposed convex optimal power flow obtains the same solution as the exact model of the problem with an efficiency of 100%, which is in contrast with the variability of the results that are presented by the metaheuristic techniques reported as comparison methodologies.     Conclusions: The proposed second-order conic relaxation warrantied the convexity of the solution space and therefore, the finding of the optimal solution at each execution; besides of this, demonstrated that for optimal power flow problems in DC networks, the numerical performance is better than most of the comparative metaheuristic methods; and the provided solution by the proposed relaxation is equivalent to that provided by the exact model. Keywords: Direct current networks, second-order conic relaxation, non-linear programming model, convex optimization.Resumen Objetivo: Este trabajo plantea una reformulación matemática de naturaleza convexa para el problema de flujo de potencia óptimo en redes de corriente continua (DC). El objetivo del modelo de optimización propuesto corresponde a la minimización de las pérdidas de potencia en todas las ramas de la red considerando un modelo cónico convexo que garantice el hallazgo de la solución óptima global. Metodología: Está dividida en tres etapas: la primera presenta el modelo matemático de flujo de potencia óptimo para redes DC y todas sus características geométricas que lo hacen no convexo; la segunda presenta la reformulación convexa a partir de una relajación cónica de segundo orden; la tercera etapa presenta las principales características del sistema DC bajo estudio; mientras que la cuarta etapa presenta la solución óptima del problema de flujo de potencia y sus comparaciones con algunos métodos reportados en la literatura especializada. Resultados: Las validaciones numéricas demuestran que el modelo de flujo de potencia óptimo convexo propuesto encuentra la misma solución el modelo exacto del problema y tiene una eficiencia del 100%, lo cual contrasta con la variabilidad de resultados que presentan las técnicas metaheurísticas reportadas como métodos de comparación. Conclusiones: La relajación cónica de segundo orden propuesta garantizó la convexidad del espacio de soluciones, y, por tanto, el hallazgo de la solución óptima en cada ejecución; además, demostró que para problemas de flujo de potencia óptimo en redes DC tiene el mejor desempeño numérico que la mayoría de los métodos metaheurísticos comparativos; y la solución provista por la relajación propuesta es equivalente a la proveída por el modelo exacto. Palabras clave: Redes de corriente continua, relajación cónica de segundo orden, modelo de programación no lineal, optimización convexa

A quadratic convex approximation for optimal operation of battery energy storage systems in DC distribution networks

This paper proposes a quadratic convex model for optimal operation of battery energy storage systems in a direct current (DC) network that approximates the original nonlinear non-convex one. The proposed quadratic convex model uses Taylor’s series expansion to transform the product between voltage variables in the power balance equations into a linear combination of them. Numerical simulations in the general algebraic modeling system (GAMS) for both models show small diferences in the daily energy losses, which are lower than 3.00%. The main advantage of the proposed quadratic model is that its optimal solution is achievable with interior point methods guaranteeing its uniqueness (convexity properties of the solution space and objective function), which is not possible to guarantee with the exact nonlinear non-convex model. The 30-bus DC test feeder with four distributed generators (with power generation forecast via artifcial neural networks with errors lower than 1% between real and predicted generation curves) and three batteries is used to validate the proposed convex and exact models. Numerical results obtained by GAMS show the efectiveness of the proposed quadratic convex model for diferent simulation scenarios tested, which was confrmed by the CVX tool for convex optimization in MATLA

Efficient Reduction in the Annual Investment Costs in AC Distribution Networks via Optimal Integration of Solar PV Sources Using the Newton Metaheuristic Algorithm

This research addresses the problem of the optimal placement and sizing of (PV) sources in medium voltage distribution grids through the application of the recently developed Newton metaheuristic optimization algorithm (NMA). The studied problem is formulated through a mixedinteger nonlinear programming model where the binary variables regard the installation of a PV source in a particular node, and the continuous variables are associated with power generations as well as the voltage magnitudes and angles, among others. To improve the performance of the NMA, we propose the implementation of a discrete–continuous codification where the discrete component deals with the location problem and the continuous component works with the sizing problem of the PV sources. The main advantage of the NMA is that it works based on the first and second derivatives of the fitness function considering an evolution formula that contains its current solution (xt i ) and the best current solution (xbest), where the former one allows location exploitation and the latter allows the global exploration of the solution space. To evaluate the fitness function and its derivatives, the successive approximation power flow method was implemented, which became the proposed solution strategy in a master–slave optimizer, where the master stage is governed by the NMA and the slave stage corresponds to the power flow method. Numerical results in the IEEE 34- and IEEE 85-bus systems show the effectiveness of the proposed optimization approach to minimize the total annual operative costs of the network when compared to the classical Chu and Beasley genetic algorithm and the MINLP solvers available in the general algebraic modeling system with reductions of 26.89% and 27.60% for each test feeder with respect to the benchmark cases.Centro de Investigación y Desarrollo Científico de la Universidad Distrital Francisco José de Caldas subvención 1643-12-202

Modelos explicativos em anatomía

The current situation of the Anatomy teaching and learning has great challenges that it must overcome, one of them is to intervene in an effective way the explanatory models on structuring concepts in the formation of the future professional. In this research the main goal was to identify the explanatory models of the students on a superior member, to intervene and evaluate, through a teaching proposal based on the development of argumentative processes, their models. To do this, a qualitative research was carried out in which 30 students from Anatomy of the first semester of Physiotherapy participated in the Autonomous University of Manizales. The results show that the main explanatory models of the students on the subject refer to a heterogeneous model, it is nonspecific and after the intervention, the students pass to an integrating model from a structural, functional and semiological model. This shows the importance of the identification and structuring of proposals that allow bringing the concepts closer to perspectives of a scientific nature in the field of Anatomy.La situación actual de la enseñanza y aprendizaje de la anatomía tiene grandes retos que debe superar, uno de ellos es intervenir de manera efectiva los modelos explicativos sobre temas estructurantes en la formación del futuro profesional. En esta investigación las intenciones fueron identificar los modelos explicativos de los estudiantes, sobre miembro superior, e intervenir y evaluar mediante la aplicación de una propuesta de enseñanza sustentada en el desarrollo de procesos argumentativos de dichos modelos. Para ello, se realizó una investigación cualitativa en la que participaron treinta estudiantes de anatomía de primer semestre de Fisioterapia, en la Universidad Autónoma de Manizales. Los resultados muestran que los principales modelos explicativos iniciales de los estudiantes sobre el tema refieren a un modelo heterogéneo que es inespecífico y luego de la intervención se movilizan a uno integrador, desde un modelo estructural, funcional y semiológico. Con ello se muestra la importancia del reconocimiento y la estructuración de propuestas que permitan acercar los conceptos hacia perspectivas de corte científico en el campo de la anatomía.A situação atual do ensino e aprendizagem da Anatomia tem grandes desafios que devem superar. Um deles é intervir de maneira efetiva nos modelos explicativos sobre temas estruturais na formação do futuro profissional. Nesta pesquisa as intenções foram identificar os modelos explicativos dos estudantes sobre o membro superior, intervir e avaliar, mediante a aplicação de uma proposta de ensino sustentada no desenvolvimento de processos argumentativos dos ditos modelos. Para isto se realizou uma pesquisa qualitativa em que participaram 30 estudantes de Anatomia do primeiro semestre de Fisioterapia da Universidade Autônoma de Manizales. Os resultados mostram que os principais modelos explicativos iniciais dos estudantes sobre o tema, referem a um modelo heterogêneo que é inespecífico e em seguida a intervenção didática, trocam por um modelo integrado a partir de um modelo estrutural, funcional e semiológico. Com isto se mostra a importância da identificação e da estruturação de propostas que permitam aproximar os conceitos dos estudantes até perspectivas científicas no campo da Anatomia

A new matheheuristic approach based on Chu-Beasley genetic approach for the multi-depot electric vehicle routing problem

Operations with Electric Vehicles (EVs) on logistic companies and power utilities are increasingly related due to the charging stations representing the point of standard coupling between transportation and power networks. From this perspective, the Multi-depot Electric Vehicle Routing Problem (MDEVRP) is addressed in this research, considering a novel hybrid matheheuristic approach combining exact approaches and a Chu-Beasley Genetic Algorithm. An existing conflict is shown in three objectives handled through the experimentations: routing cost, cost of charging stations, and increased cost due to energy losses. EVs driving range is chosen as the parameter to perform the sensitivity analysis of the proposed MDEVRP. A 25-customer transportation network conforms to a newly designed test instance for methodology validation, spatially combined with a 33 nodes power distribution system