Search

This paper presents a different Finite Control Set – Model Predictive Control (FCS-MPC) for grid-connected three-phase bidirectional power inverters. These are typically used in dc or ac renewable-based microgrids (MGs), where bidirectional operation and fast dynamic response is required. The bidirectional grid-connected inverters are an essential part of MG, which inject energy into the ac grid or demand energy from it. The dynamic behavior of the system is a major concern since the current can suddenly change depending on the hierarchical controller. This paper proposes a different cost function using sliding mode theory, which offers a good dynamic response, reduced computational burden, and a parameter-free control model. The operation principle of the proposed controller is given and evaluated using a Hardware-In-the-Loop (HIL) system, but also experimentally with a 1kW laboratory prototype. The final results demonstrate the advantages of using this approach in grid-connected three-phase bidirectional power inverters in terms of dynamic response and reduced computational burden, making this solution technically attractive and viable. [ABSTRACT FROM AUTHOR]

Nowadays, the use of the hardware in the loop (HIL) simulation has gained popularity among researchers all over the world. One of its main applications is the simulation of power electronics converters. However, the equipment designed for this purpose is difficult to acquire for some universities or research centers, so ad-hoc solutions for the implementation of HIL simulation in low-cost hardware for power electronics converters is a novel research topic. However, the information regarding implementation is written at a high technical level and in a specific language that is not easy for non-expert users to understand. In this paper, a systematic methodology using LabVIEW software (LabVIEW 2018) for HIL simulation is shown. A fast and easy implementation of power converter topologies is obtained by means of the differential equations that define each state of the power converter. Five simple steps are considered: designing the converter, modeling the converter, solving the model using a numerical method, programming an off-line simulation of the model using fixed-point representation, and implementing the solution of the model in a Field-Programmable Gate Array (FPGA). This methodology is intended for people with no experience in the use of languages as Very High-Speed Integrated Circuit Hardware Description Language (VHDL) for Real-Time Simulation (RTS) and HIL simulation. In order to prove the methodology's effectiveness and easiness, two converters were simulated—a buck converter and a three-phase Voltage Source Inverter (VSI)—and compared with the simulation of commercial software (PSIM® v9.0) and a real power converter. [ABSTRACT FROM AUTHOR]

Agricultural planning processes at farm to national level are essential for assessing and reacting to land conditions, opportunities, and threats for coffee production. However, lack or uncertainty of information is common during these processes. Bayesian networks can be used to manage these uncertainties. We, therefore, developed the first Bayesian network model for an Agroecological Land Evaluation for Coffea arabica L. (ALECA). A newly developed set of suitability functions was used to populate the nodes in the network. ALECA was then adjusted and validated to Central America. The results show that even without the use of coffee maps as input, ALECA accurately scores the suitability of actual coffee areas for coffee production as higher than that non-coffee areas, and can accurately predict the known order of quality of coffee reference zones in Central America. The results also show that ALECA can be used as a decision-support tool even under data uncertainty. [ABSTRACT FROM AUTHOR]

Although PV systems are one of the most widely used alternatives as a renewable energy source due to their well-known advantages, there are significant challenges to address related to voltage fluctuations and reverse power flow caused by high PV penetration scenarios. As a potential solution to this problem, an active power management strategy is proposed in this work using a residential cluster as a benchmark. The proposed strategy is analyzed and experimentally verified, offering a simple way to reduce the voltage fluctuations by regulating the active power delivered by the PV system, achieving also relevant functionalities for the system, such as the regulation of the DC bus voltage, maximum power point tracking (MPPT), synchronization with the grid voltage, detection of high penetration conditions, and a simple strategy for the main controller with an effective performance. The proposal system shows satisfactory results being able to maintain grid voltage fluctuations within the voltage standard specifications. [ABSTRACT FROM AUTHOR]