Wind and solar power generation will continue to grow in the energy supply of the future, but its inherent variability (intermittency) requires appropriate energy systems for storing and using power. Storage of possibly temporary excess of power as methane from hydrogen gas and carbon dioxide is a promising option. With electrolysis hydrogen gas can be generated from (renewable) power. The combination of such hydrogen with carbon dioxide results in the energy carrier methane that can be handled well and may may serve as carbon feedstock of the future. Biogas from biomass delivers both methane and carbon dioxide. Anaerobic microorganisms can make additional methane from hydrogen and carbon dioxide in a biomethanation process that compares favourably with its chemical counterpart. Biomethanation for renewable power storage and use makes appropriate use of the existing infrastructure and knowledge base for natural gas. Addition of hydrogen to a dedicated biogas reactor after fermentation optimizes the biomethanation conditions and gives maximum flexibility. The low water solubility of hydrogen gas limits the methane production rate. The use of hollow fibers, nano-bubbles or better-tailored methane-forming microorganisms may overcome this bottleneck. Analyses of patent applications on biomethanation suggest a lot of freedom to operate. Assessment of biomethanation for economic feasibility and environmental value is extremely challenging and will require future data and experiences. Currently biomethanation is not yet economically feasible, but this may be different in the energy systems of the near future.
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Battery energy storage (BES) can provide many grid services, such as power flow management to reduce distribution grid overloading. It is desirable to minimise BES storage capacities to reduce investment costs. However, it is not always clear how battery sizing is affected by battery siting and power flow simultaneity (PFS). This paper describes a method to compare the battery capacity required to provide grid services for different battery siting configurations and variable PFSs. The method was implemented by modelling a standard test grid with artificial power flow patterns and different battery siting configurations. The storage capacity of each configuration was minimised to determine how these variables affect the minimum storage capacity required to maintain power flows below a given threshold. In this case, a battery located at the transformer required 10–20% more capacity than a battery located centrally on the grid, or several batteries distributed throughout the grid, depending on PFS. The differences in capacity requirements were largely attributed to the ability of a BES configuration to mitigate network losses. The method presented in this paper can be used to compare BES capacity requirements for different battery siting configurations, power flow patterns, grid services, and grid characteristics.
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This study presents a methodology designed to optimize various parameters of each access point within a Multiple-Input Single-Output (MISO) Visible Light Communication (VLC) system. The primary objective is to enhance both power and spectral efficiencies. A MISO-VLC model is presented based on experimental evaluations and a problem formulation considering intermodulation distortions based on Orthogonal Frequency Division Multiplexing modulation. A Hybrid Multi-Objective Optimization (HMO) approach is proposed, combining the Non-Sorting Genetic Algorithm III (NSGA-III) and the Multi-objective Grey Wolf Optimization (MOGWO). The proposed HMO's success was validated by a 66 % reduction in transmitted power, maintaining the Error Vector Magnitude (EVM) performance metrics even at lower power transmission levels and minimizing the guard band to its lower bound.
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