<span lang="EN-US">This paper presents a stand-alone hybrid renewable energy system (SHRES) consisting of solar photovoltaic (PV), wind turbine (WT) and battery energy storage (BES) in an effort reduce the dependence on fossil fuels. The renewable energy sources have individual inverters and the PV inverter of the SHRES is operated using active and reactive power control. The PV inverter have two main control structures which are active power control and reactive power control and each contain a proportional integral (PI) controller. Accurate control of the PV inverter’s active power is essential for PV curtailment applications. Thus, this paper aims to enhance the performance of the SHRES in this work by optimizing the performance of the PV inverter’s active power PI controller parameters through the design of adaptive controllers. Therefore, an adaptive controller and an optimized adaptive controller are proposed in this paper. The performances of the proposed controllers are evaluated by minimizing the objective function which is the integral of the time weighted absolute error (ITAE) criterion and this performance is then compared with a controller that is tuned by the traditional trial and error method. Simulation results showed that the optimized adaptive controller is better as it recorded an error improvement of 42.59%. The dynamic optimized adaptive controller is more adept at handling the fast changes of the SHRES operation.</span>
Multi-vector smart local energy systems are playing an increasingly importantly role in the fast-track decarbonisation of our global energy services. An emergent contributor to global decarbonisation is green hydrogen. Green hydrogen can remove or reduce the burden of electrification of heat and transport on energy networks and provide a sustainable energy resource. In this paper, we explore how to optimally design a standalone hybrid green power system (HGPS) to supply a specific load demand with on-line charging of Electric Vehicles (EV). The HGPS includes wind turbine (WT) units, photovoltaic (PV) arrays, electrolyser and fuel cell (FC). For reliability analysis, it is assumed that WT, PV, DC/AC converter, and EV charger can also be sources of potential failure. Our methodology utilises a particle swarm optimization, coupled with a range of energy scenarios as to fully evaluate the varying interdependences and importance of economic and reliability indices, for the standalone HGPS. Our analysis indicates that EV charging with peak loading can have significant impact on the HGPS, resulting in significant reductions in the reliability indices of the HGPS, therefore enhance the operation of HGPS and reduces the overall cost. Our analysis demonstrates the importance of understanding local demand within a multi-vector optimization framework, as to ensure viable and resilient energy services. INDEX TERMSSmart local energy system, green hydrogen, reliability, economics, optimization, electric vehicle charging. NOMENCLATURE ACRONYMS BES Battery Energy Storage. DGs Distributed Generation Sources. EENS Expectation Of Not Served Energy. ELF Equivalent Loss Factor. ESS Energy Storage System. EV Electric Vehicle. FC Fuel Cell.The associate editor coordinating the review of this manuscript and approving it for publication was Frederico Guimarães .
Noise is defined as an unpleasant or loud sound, which may cause disturbance to others. It can damage an inner ear and even cause noise-induced hearing loss, threatening health and well-being. Researchers have successfully studied and invented many different types, shapes, and sizes of sound absorbers to absorb/control unwanted noises. A simple method used to control noise is by controlling the noise source using acoustic absorption panels, reducing noise along the transmission path, and protecting the noise at the receiving end before it reaches the receiver. Presently, the market or in most developed countries uses synthetic materials for buildings to absorb sound. The commonly used synthetic materials are glass or mineral fibers as they can be produced chemically in the factory very quickly. However, materials such as foam, rock wool, and glass wool made from minerals are recognized for their poisonous and polluting effects, which are harmful to human health and the environment. This paper reported the effect of substitution of Jute on the acoustic performance of Oil Palm Frond (OPF) natural fibers (150 kg/m3) with a thickness of 19 mm. Jute is suitable for insulating, antistatic, and low thermal conductivity. It also has a promising result of sound absorption coefficient (SAC) at lower frequency range (50 - 1000 Hz), and on the contrary for OPF, the SAC is only promising at higher frequency range (2000 Hz - 6400 Hz). Thus, it will be very remarkable to study these two blending fibers' acoustic performance. The findings show the substitution of Jute to broaden the frequency range of SAC above 0.8. For 20 % of jute substitution, SAC's frequency range above 0.8 is 1600 – 6400 Hz. Whereas for both 40 % and 60 % of jute substitution, the frequency range is marginally widened to 1400 – 6400 Hz. For 80 % of jute substitution, the frequency range of SAC above 0.8 has been increased to 1000 – 6400 Hz. An impressive result has been observed, where 100 % OPF unable to reach the SAC of 0.9 throughout the frequency range of 0 – 6400 Hz. Jute has proved its ability to improve its acoustic performance at a more comprehensive frequency range.
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