Optimal Location and Operation of PV Sources in DC Grids to Reduce Annual Operating Costs While Considering Variable Power Demand and Generation

Due to the need to include renewable energy resources in electrical grids as well as the development and high implementation of PV generation and DC grids worldwide, it is necessary to propose effective optimization methodologies that guarantee that PV generators are located and sized on the DC electrical network. This will reduce the operation costs and cover the investment and maintenance cost related to the new technologies (PV distributed generators), thus satisfying all technical and operative constraints of the distribution grid. It is important to propose solution methodologies that require short processing times, with the aim of exploring a large number of scenarios while planning energy projects that are to be presented in public and private contracts, as well as offering solutions to technical problems of electrical distribution companies within short periods of time. Based on these needs, this paper proposes the implementation of a Discrete–Continuous Parallel version of the Particle Swarm Optimization algorithm (DCPPSO) to solve the problem regarding the integration of photovoltaic (PV) distributed generators (DGs) in Direct Current (DC) grids, with the purpose of reducing the annual costs related to energy purchasing as well as the investment and maintenance cost associated with PV sources in a scenario of variable power demand and generation. In order to evaluate the effectiveness, repeatability, and robustness of the proposed methodology, four comparison methods were employed, i.e., a commercial software and three discrete–continuous methodologies, as well as two test systems of 33 and 69 buses. In analyzing the results obtained in terms of solution quality, it was possible to identify that the DCPPSO proposed obtained the best performance in relation to the comparison methods used, with excellent results in relation to the processing times and standard deviation. The main contribution of the proposed methodology is the implementation of a discrete–continuous codification with a parallel processing tool for the evaluation of the fitness function. The results obtained and the reports in the literature for alternating current networks demonstrate that the DCPPSO is the optimization methodology with the best performance in solving the problem of the optimal integration of PV sources in economic terms and for any kind of electrical system and size. © 2022 by the authors

Sliding-mode controller for a step up-down battery charger with a single current sensor

This paper proposes a battery charger solution based on the Zeta DC/DC converter to provide a general interface between batteries and microgrid direct current (DC) buses. This solution enables to interface batteries and DC buses with voltage conversion ratios lower, equal, and higher than one using the same components and without redesigning the control system, thus ensuring global stability. The converter controller is designed to require only the measurement of a single inductor current, instead of both inductors currents, without reducing the system flexibility and stability. The controller stability is demonstrated using the sliding-mode theory, and a design procedure for the parameters is developed to ensure a desired bus performance. Finally, simulations and experiments validate the performance of the proposed solution under realistic operation conditions

Metaheuristic Optimization Methods for Optimal Power Flow Analysis in DC Distribution Networks

In this paper is addressed the optimal power flow problem in direct current grids, by using solution methods based on metaheuristics techniques and numerical methods. For which was proposed a mixed integer nonlinear programming problem, that describes the optimal power flow problem in direct current grids. As solution methodology was proposed a master–slave strategy, which used in master stage three continuous solution methods for solving the optimal power flow problem: a particle swarm optimization algorithm, a continuous version of the genetic algorithm and the black hole optimization method. In the slave stages was used a methods based on successive approximations for solving the power flow problem, entrusted for calculates the objective function associated to each solution proposed by the master stage. As objective function was used the reduction of power loss on the electrical grid, associated to the energy transport. To validate the solution methodologies proposed were used the test systems of 21 and 69 buses, by implementing three levels of maximum distributed power penetration: 20%, 40% and 60% of the power supplied by the slack bus, without considering distributed generators installed on the electrical grid. The simulations were carried out in the software Matlab, by demonstrating that the methods with the best performance was the BH/SA, due to that show the best trade-off between the reduction of the power loss and processing time, for solving the optimal power flow problem in direct current networks

Design and Control of a Battery Charger/Discharger Based on the Flyback Topology

Devices connected to microgrids require safe conditions during their connection, disconnection and operation. The required safety is achieved through the design and control of the converters that interface elements with the microgrid. Therefore, the design of both power and control stages of a battery charger/discharger based on a flyback is proposed in this paper. First, the structure of a battery charger/discharger is proposed, including the battery, the flyback, the DC bus, and the control scheme. Then, three models to represent the battery charger/discharger are developed in this work; a switched model, an averaged model, and a steady-state model, which are used to obtain the static and dynamic behavior of the system, and also to obtain the design equations. Based on those models, a sliding-mode controller is designed, which includes the adaptive calculation of one parameter. Subsequently, a procedure to select the flyback HFT, the output capacitor, and the Kv parameter based on operation requirements of the battery charger/discharger is presented in detail. Five tests developed in PSIM demonstrate the global stability of the system, the correct design of the circuit and controller parameters, the satisfactory regulation of the bus voltage, and the correct operation of the system for charge, discharge and stand-by conditions. Furthermore, a contrast with a classical PI structure confirms the performance of the proposed sliding-mode controller

Auto-tuning of PV controllers to improve the speed response and stability of the P&O algorithm

This paper proposes an auto-tuning control system to ensure a fast response of the photovoltaic (PV) voltage by reducing the perturbation time of a P&O algorithm. This solution accelerates the tracking of the maximum power point and, at the same time, guarantees the system stability, which increases the amount of energy produced by the PV system. The control system consists of three cascaded controllers: a P&O algorithm dynamically parameterized by the adaptive law in order to guarantee stability; an adaptive PI controller whose parameters are modified by the adaptive law, depending on the operating conditions, to reduce the settling time of the system as much as possible; and a sliding mode current controller to mitigate environmental and load perturbations and ensure global stability. The design of the new control structure is supported by mathematical analyses and validated with simulations performed in PSIM in order to demonstrate the robustness of the proposed solution.En este trabajo se propone un sistema de control auto-ajustable para garantizar una respuesta rápida del sistema fotovoltaico (PV) mediante la reducción del tiempo de perturbación del algoritmo P&O. Con esta solución se logra acelerar el seguimiento del punto de máxima potencia y al mismo tiempo garantizar la estabilidad del sistema, incrementando de esta manera la cantidad de energía producida. La ley de control está compuesta por tres controladores en cascada: Un algoritmo P&O parametrizado dinámicamente; un control adaptativo PI, cuyos parámetros son modificados por la ley de adaptación dependiendo de las condiciones de operación para reducir el tiempo de establecimiento tanto como sea posible; y un controlador en modos deslizantes de corriente que mitiga las perturbaciones ambientales y de la carga para garantizar la estabilidad global. El diseño de la nueva estructura de control se soporta con análisis matemáticos y se valida con simulaciones realizadas en PSIM que demuestran la robustez de la solución

Photovoltaic Sources Modeling

This comprehensive guide surveys all available models for simulating a photovoltaic (PV) generator at different levels of granularity, from cell to system level, in uniform as well as in mismatched conditions. Providing a thorough comparison among the models, engineers have all the elements needed to choose the right PV array model for specific applications or environmental conditions matched with the model of the electronic circuit used to maximize the PV power production

Types of inverters and topologies for microgrid applications

Inverters are the key actuator in the control of AC microgrids, since they manage the power flows of both the generators and energy storage devices. In general, there are three types of inverters depending on the control strategy: grid feeding inverters, grid forming inverters and grid supporting inverters. Those inverters can be implemented with different hardware topologies, each one of them with advantages and disadvantages. This paper presents a sinthesis of the widely used inverter topologies used in AC microgrids. Moreover, this paper also describes the inverters control architectures and the main strategiesLos inversores son los principales actuadores en el control de microrredes en AC, pues ellos gestionan los flujos de potencia de los generadores y los dispositivos de almacenamiento de energía. En general, existen tres tipos de inversores dependiendo de la estrategia de control: inversores alimentadores de red, inversores formadores de red e inversores soporte de red. Dichos inversores pueden ser implementados con diferentes topologías hardware, cada una de ellas con ventajas y desventajas. Este artículo presenta una síntesis de las topologías de inversores ampliamente usadas en microrredes de AC. Además, el artículo también describe la arquitectura y las principales estratégicas de control de los inversores.