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Distorted voltage supplied as unbalanced and/or non-constant frequency can be found in weak grids, such as microgrids, or systems working in islanding mode. These kinds of systems are more sensitive under load changes. Particularly, an unbalanced voltage supply may be produced for large, single-phase loads. On the other hand, the connection/disconnection of high current loads may lead to important frequency variation, especially in weak grids where the short circuit current capacity is reduced. These conditions make the control of the power converter a more difficult task, because of the variations in the frequency and unbalancing. To address these issues, this paper proposes a resonant control algorithm to deal with variations in the voltage amplitude as well as grid frequency when a distorted power supply is considered. The frequency variation is an important drawback for resonant control because the resonance must be tuned at the grid frequency. This issue is overcome by using a variable sampling frequency in order to avoid re-tuning the controller parameters. On the other hand, under unbalanced conditions, the proposed method relaxes the phase with lower voltage amplitude by taking more power from the other phases in order to help the stability of the grid supply. To corroborate the mathematical analysis and the proposed control, a stability study is performed, including experimental and simulated results.
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Software Defined Networking (SDN) is a communication alternative to increase the scalability and resilience of microgrid hierarchical control. The common architecture has a centralized and monolithic topology, where the controller is highly susceptible to latency problems, resiliency, and scalability issues. This paper proposes a novel and intelligent control network to improve the performance of microgrid communications, solving the typical drawback of monolithic SDN controllers. The SDN controller's functionalities are segregated into microservices groups and distributed through a bare-metal Kubernetes cluster. Results are presented from PLECS hardware in the loop simulation to validate the seamless transition between standard hierarchical control to the SDN networked microgrid. The microservices significantly impact the performance of the SDN controller, decreasing the latency by 10.76% compared with a monolithic architecture. Furthermore, the proposed approach demonstrates a 42.23% decrease in packet loss versus monolithic topologies and a 53.41% reduction in recovery time during failures. Combining Kubernetes with SDN microservices can eliminate the single point of failure in hierarchical control, improve application recovery time, and enhance containerization benefits, including security and portability. This proposal represents a reference framework for future edge computing and intelligent control approaches in networked microgrids.
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This work presents a methodology for optimal compensation of reactive power in Electric Microgrids using a multicriteria decision algorithm based on heuristic methods. It was verified the optimal location and dimensioning of fixed capacitor banks in a microgrid with 14 buses with objective functions based on cost, efficiency and quality criteria in a maximum demand operating condition and also considering the constraints of objective variables in minimum demand scenarios. The proposed capacitance to be installed was considered as a discrete variable. The location of discretized reactive capacitances was simulated at candidate nodes analyzing the power flow in the case study, resulting in a wide solution space that was tackled by means of multicriteria optimization, using dominance elimination techniques and the weighted sum method for decision making. The variables analyzed were: cost, maximum and average deviations of the voltage profile, power factor, total losses in the lines of the system and THD. All these variables were also verified in minimum demand scenarios. The proposed solution provides significant improvements in the variables analyzed and verifies the optimal performance of the technique. The mathematical analysis demonstrates the need of addressing the reactive compensation problem by means of multicriteria decision and the proposal provides a very novel tool for calculating the location and dimensioning of reactive compensation devices in distribution systems and microgrids. The programming was done in the Matlab environment with simulations using Simulink. The case study analyzed is a very novel validated Microgrid system of which it is known the variables that take part of this analysis, as an approximation of the study of a very real Microgrid.
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Protection coordination of AC microgrids (MGs) is a challenging task since they can operate either in grid-connected or islanded mode which drastically modifies the fault currents. In this context, traditional approaches to protection coordination, that only consider the time multiplier setting (TMS) as a decision variable may no longer be able to guarantee network security. This paper presents a novel approach for protection coordination in AC MGs that incorporates non-standard characteristic features of directional over-current relays (OCRs). Three optimization variables are considered for each relay: TMS, maximum limit of the plug setting multiplier (PSM) and standard characteristic curve (SCC). The proposed model corresponds to a mixed integer non-linear programming problem. Four metaheuristic techniques were implemented for solving the optimal coordination problem, namely: particle swarm optimization (PSO), genetic algorithm (GA), teaching-learning based optimization (TLBO) algorithm and shuffled frog leaping algorithm (SFLA). Numerous tests were run on an IEC MG as well as with the distribution portion of the IEEE 30-bus test system. Both systems incorporate distributed generation (DG) and feature several modes of operation. A comparison was made with other MG protection coordination approaches proposed in the specialized literature. In all cases, the proposed approach found reduced coordination times, evidencing the applicability and efficacy of the proposed approach.
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Abstract Microgrids have been widely applied to improve the energy quality parameters of a distribution system locally, in addition to ensuring the operation of the system in an isolated manner. The Model Predictive Control (MPC) is a great solution to guarantee the operation of the system considering forecasting models and also physical restrictions of the system, which ensure the optimal operation of the Microgrid. However, the construction of a control scheme following the objectives established in order to meet the connected and isolated operation of a Microgrid is still a challenge. This paper proposes the development of an MPC control scheme that assures optimal system operation in connected and islanded mode, improving power quality indexes, ensuring network requirements, and extending battery life cycle. The proposed control operation in the connected mode can attend to the needs of the Microgrid, reducing the impacts of peak demand and the intermittent variations in renewable generation, where a linear objective function is developed for this purpose. In the islanded mode, grid requirements are guaranteed through load shedding, considering improvements in continuity indicators. Forecasting models are implemented considering the MPC approach and a detailed network model is developed. Simulation results highlight the effectiveness of the proposed control strategy.
Assuntos
Controle de Qualidade , Instalação Elétrica/normas , Baterias , Energia RenovávelRESUMO
Abstract The electrical system is becoming more robust with the insertion of distributed energy resources (DERs) and the need for energy autonomy by consumers, given that the current scenario is a growth in demand for electric energy. This paper aims to apply a computational model capable of determining the optimal hourly allocation of controllable loads in residence, as well as studying the optimal dispatch of residential microgrids considering management on the demand side. In addition, this paper presents an economic feasibility analysis of residential microgrids considering distributed generation from wind and solar sources, distributed storage, electric vehicles, and residential controllable loads. Thus, it was possible to conclude that in residence, the insertion of distributed energy generation and storage elements can present a significant reduction in electric energy costs, which can be even greater if these elements are associated with optimized controllable load management.