Optimal operation of hybrid AC/DC microgrids under uncertainty of renewable energy resources : A comprehensive review

The hybrid AC/DC microgrids have become considerably popular as they are reliable, accessible and robust. They are utilized for solving environmental, economic, operational and power-related political issues. Having this increased necessity taken into consideration, this paper performs a comprehensive review of the fundamentals of hybrid AC/DC microgrids and describes their components. Mathematical models and valid comparisons among different renewable energy sources’ generations are discussed. Subsequently, various operational zones, control and optimization methods, power flow calculations in the presence of uncertainties related to renewable energy resources are reviewed.fi=vertaisarvioitu|en=peerReviewed

Microgrids: Planning, Protection and Control

This Special Issue will include papers related to the planning, protection, and control of smart grids and microgrids, and their applications in the industry, transportation, water, waste, and urban and residential infrastructures. Authors are encouraged to present their latest research; reviews on topics including methods, approaches, systems, and technology; and interfaces to other domains such as big data, cybersecurity, human–machine, sustainability, and smart cities. The planning side of microgrids might include technology selection, scheduling, interconnected microgrids, and their integration with regional energy infrastructures. The protection side of microgrids might include topics related to protection strategies, risk management, protection technologies, abnormal scenario assessments, equipment and system protection layers, fault diagnosis, validation and verification, and intelligent safety systems. The control side of smart grids and microgrids might include control strategies, intelligent control algorithms and systems, control architectures, technologies, embedded systems, monitoring, and deployment and implementation

Control jerárquico-óptimo de microrredes aisladas

The objective of this article is to propose a novel method that uses hierarchical control to efficiently manage power resources in an isolated Direct Current (DC) microgrid. The scope of this paper is limited to a numerical study of the components of the micro-generation system using accurate mathematical models in a commercial simulation tool. The control methodology is based on power sharing by means of a hierarchical topology including several control layers. In particular, the internal control loops that regulate the electrical variables in individual generators are at the bottom of the hierarchy. In addition, the power-sharing technique distributes power at an intermediate level, and it is complemented by a Newton-Raphson optimization algorithm at the top, which aims to minimize the cost function. The cost of the microgrid is defined in terms of investment and maintenance indices. This study analyzes the case of a low-power isolated DC microgrid that combines an array of photovoltaic panels and a battery bank. The most relevant result was the optimization of its generation cost, which was verified using simulations of the control and power circuits. In conclusion, although simple, the proposed technique achieves efficient performance in managing the power resources of this microgrid under environmental disturbances.El objetivo del presente artículo fue proponer un método para realizar la gestión eficiente de recursos energéticos en una microrred aislada en corriente continua, empleando control jerárquico. El alcance del trabajo se limitó a estudios numéricos a través de modelos matemáticos precisos en una herramienta de simulación comercial para los componentes del sistema de microgeneración eléctrica. La metodología del control se basó en el reparto de potencias mediante una topología jerárquica con diferentes capas de control. Específicamente, los lazos de control internos que regulan las variables eléctricas en generadores individuales están en la base de la jerarquía, la técnica de reparto de potencias realiza una distribución de energía a un nivel intermedio y se complementa en un nivel superior por un algoritmo de optimización del tipo Newton-Raphson, minimizando un funcional de costo. Dicho costo de la microrred es definido, a su vez, en términos de índices de inversión y mantenimiento. Asimismo, una microrred CC aislada y de baja potencia, constituida por un arreglo de paneles fotovoltaicos combinados con un banco de baterías, es analizada como caso de estudio. El resultado más importante correspondió con la verificación de la optimización del costo de generación mediante simulaciones para los circuitos de control y potencia. En conclusión, la técnica propuesta verifica, a pesar de su simplicidad, un desempeño eficiente para el manejo de recursos energéticos de la microrred ante perturbaciones del entorno

Economic power schedule and transactive energy through an intelligent centralized energy management system for a DC residential distribution system

Direct current (DC) residential distribution systems (RDS) consisting of DC living homes will be a significant integral part of future green transmission. Meanwhile, the increasing number of distributed resources and intelligent devices will change the power flow between the main grid and the demand side. The utilization of distributed generation (DG) requires an economic operation, stability, and an environmentally friendly approach in the whole DC system. This paper not only presents an optimization schedule and transactive energy (TE) approach through a centralized energy management system (CEMS), but also a control approach to implement and ensure DG output voltages to various DC buses in a DC RDS. Based on data collection, prediction and a certain objectives, the expert system in a CEMS can work out the optimization schedule, after this, the voltage droop control for steady voltage is aligned with the command of the unit power schedule. In this work, a DC RDS is used as a case study to demonstrate the process, the RDS is associated with unit economic models, and a cost minimization objective is proposed that is to be achieved based on the real-time electrical price. The results show that the proposed framework and methods will help the targeted DC residential system to reduce the total cost and reach stability and efficiency

Evolution of microgrids with converter-interfaced generations: Challenges and opportunities

© 2019 Elsevier Ltd Although microgrids facilitate the increased penetration of distributed generations (DGs) and improve the security of power supplies, they have some issues that need to be better understood and addressed before realising the full potential of microgrids. This paper presents a comprehensive list of challenges and opportunities supported by a literature review on the evolution of converter-based microgrids. The discussion in this paper presented with a view to establishing microgrids as distinct from the existing distribution systems. This is accomplished by, firstly, describing the challenges and benefits of using DG units in a distribution network and then those of microgrid ones. Also, the definitions, classifications and characteristics of microgrids are summarised to provide a sound basis for novice researchers to undertake ongoing research on microgrids

Cooperative Control And Advanced Management Of Distributed Generators In A Smart Grid

Smart grid is more than just the smart meters. The future smart grids are expected to include a high penetration of distributed generations (DGs), most of which will consist of renewable energy sources, such as solar or wind energy. It is believed that the high penetration of DGs will result in the reduction of power losses, voltage profile improvement, meeting future load demand, and optimizing the use of non-conventional energy sources. However, more serious problems will arise if a decent control mechanism is not exploited. An improperly managed high PV penetration may cause voltage profile disturbance, conflict with conventional network protection devices, interfere with transformer tap changers, and as a result, cause network instability. Indeed, it is feasible to organize DGs in a microgrid structure which will be connected to the main grid through a point of common coupling (PCC). Microgrids are natural innovation zones for the smart grid because of their scalability and flexibility. A proper organization and control of the interaction between the microgrid and the smartgrid is a challenge. Cooperative control makes it possible to organize different agents in a networked system to act as a group and realize the designated objectives. Cooperative control has been already applied to the autonomous vehicles and this work investigates its application in controlling the DGs in a micro grid. The microgrid power objectives are set by a higher level control and the application of the cooperative control makes it possible for the DGs to utilize a low bandwidth communication network and realize the objectives. Initially, the basics of the application of the DGs cooperative control are formulated. This includes organizing all the DGs of a microgrid to satisfy an active and a reactive power objective. Then, the cooperative control is further developed by the introduction of clustering DGs into several groups to satisfy multiple power objectives. Then, the cooperative distribution optimization is introduced iii to optimally dispatch the reactive power of the DGs to realize a unified microgrid voltage profile and minimize the losses. This distributed optimization is a gradient based technique and it is shown that when the communication is down, it reduces to a form of droop. However, this gradient based droop exhibits a superior performance in the transient response, by eliminating the overshoots caused by the conventional droop. Meanwhile, the interaction between each microgrid and the main grid can be formulated as a Stackelberg game. The main grid as the leader, by offering proper energy price to the micro grid, minimizes its cost and secures the power. This not only optimizes the economical interests of both sides, the microgrids and the main grid, but also yields an improved power flow and shaves the peak power. As such, a smartgrid may treat microgrids as individually dispatchable loads or generators