Utilization of renewable energies in association with energy storage is increased in different applications such as electrical vehicles (EVs), electric boats (EBs), and smart grids. A robust controller strategy plays a significant role to optimally utilize the energy resources available in a power system. In this paper, a suitable controller for the energy resources of an EB which consists of a 5 kW solar power plant, 5 kW fuel cell, and 2 kW battery package is designed based on the linear parameter varying (LPV) controller design approach. Initially, all component dynamics are augmented, and by exploiting the sector-nonlinearity approach, the LPV representation is derived. Then, the LPV control method determines the suitable gains of the states’ feedbacks to provide the required pulse commands of the boost converters of the energy resources to regulate the DC-link voltage and supply the power of EB loads. Comparing with the state-of-the-art nonlinear control methods, the developed control approach assures the stability of the overall system, as it considers all component dynamics in the design procedure. The real-time simulation results demonstrate the performance of the designed controller in the creation of a constant DC-link voltage.
To avoid pollution of transportation applications, renewable energies are deployed. Whereas they are uncontrolled, fully controlled pollution-free energy sources and storage units should be also considered. However, a complicated direct current (DC) microgrid (MG) is obtained, which suffers from nonlinearities, high order, and uncertainties of the power elements. Therefore, it is vital to use advanced nonlinear controllers to assure closed-loop stability and performance of the overall system. In this paper, a neural network (NN)-based adaptive linear parameter varying (LPV) controller is suggested for the whole DC MG power system. The main advantage of the developed controller is that it deploys the operating information of all power energy sources to manipulate each component. This enhances the DC MG stability margin and fast regulation of the power and voltage. Besides, the proposed controller has a systematic and fully offline design algorithm by combining numerical solvers and theoretical theories. The LPV controller is designed via the numerical linear matrix inequality (LMI) approach and the adaptation law for the NN parameters is designed based on the Lyapunov stability theory. A DC MG benchmark including a 5kW fuel cell, a 5kW solar plant, and a 2kW battery package is considered as the case study, which can be utilized in future fully electric boats (EBs). Numerical simulations with different scenarios are conducted to verify the performance of the proposed controller. Furthermore, comparative results are provided to show the advantages of the proposed method dealing with power fluctuations of the solar plant and DC loads over state-of-the-art nonlinear methods.
Light is one of the most critical factors for the growth of microalgae; therefore, optimization and accessibility of light improve productivity and wastewater nutrient removal is important. The flashing light effect allows microalgae to use light effectively through intermittent exposure. Nutrient assimilation and membrane fouling were considered in a reciprocal membrane photobioreactor (RMPBR) and an LED flashing light was provided as a source of illumination. The objective of this study was to bridge the gap between light delivery and RMPBR performance. In this connection, we examined flashing lights with frequencies of 1 Hz and 1000 Hz at a constant duty cycle of 60% along with continuous light. Regarding the effect of the flashing light on RMPBR, the cells which acclimated to flashing light of 1000 Hz resulted in maximum removal of nitrate (97%) and phosphate (70%). However, the culture with the low frequency of 1 Hz was only able to remove nitrate and phosphate up to 68% and 47%, respectively. Furthermore, the reactor with 1-Hz flashing light frequency was fouled earlier within 84 h thereby reaching the highest pore-blocking. Proteins and carbohydrates were recognized as a major cause of fouling in the lowfrequency flashing light. We conclude that high-frequency flashing light (1000 Hz) could be an effective light condition for nutrient uptake in wastewater treatment.
The membrane photobioreactor (MPBR) is a well‐operated system concerning microalgae cultivation and nutrients assimilation from wastewater effluent. In the present paper, a sample of pulp and paper wastewater was primarily treated by activated sludge system (ACS), and the concentration of nitrate and phosphate decreased as about 26 and 10%, respectively. Then, it was transferred into six flat plate MPBR systems with 5 L capacity and 0.45 μm membrane pore size for the secondary treatment process (nitrate and phosphate assimilation) by Chlorella vulgaris (green microalgae) species during six cultivation periods. In this section, the effects of different light intensities (100 and 300 μmol m−2 s−1) and light–dark cycles (24–0, 16–8, and 12–12) on nitrate and phosphate uptake through the treated pulp and paper wastewater effluent after 24 hr were investigated. The maximum photosynthetic productivity and nitrate‐phosphate removals after 24 hr (nitrate: 57% and phosphate: 43%) were recorded for the culture under 300 μmol m−2 s−1 and 24–0 light–dark regime within the MPBR system.
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