49 research outputs found

    Load frequency controllers considering renewable energy integration in power system

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    Abstract: Load frequency control or automatic generation control is one of the main operations that take place daily in a modern power system. The objectives of load frequency control are to maintain power balance between interconnected areas and to control the power flow in the tie-lines. Electric power cannot be stored in large quantity that is why its production must be equal to the consumption in each time. This equation constitutes the key for a good management of any power system and introduces the need of more controllers when taking into account the integration of renewable energy sources into the traditional power system. There are many controllers presented in the literature and this work reviews the traditional load frequency controllers and those, which combined the traditional controller and artificial intelligence algorithms for controlling the load frequency

    A Brief Analysis of Gravitational Search Algorithm (GSA) Publication from 2009 to May 2013

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    Gravitational Search Algorithm was introduced in year 2009. Since its introduction, the academic community shows a great interest on this algorith. This can be seen by the high number of publications with a short span of time. This paper analyses the publication trend of Gravitational Search Algorithm since its introduction until May 2013. The objective of this paper is to give exposure to reader the publication trend in the area of Gravitational Search Algorithm

    Modified rice husk and activated carbon filters for the removal of organics and heavy metals in water

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    Discharge of untreated industrial effluents containing heavy metals and organics is hazardous to the environment because of their toxicity and persistent nature. At the same time, agricultural waste poses disposal challenges, which can be converted into value added products like adsorbents that could serve as tools for contaminants abatement. Previous findings proved that, adsorption was a sustainable, economical and lucrative separation technique for the removal of such contaminants. This thesis presents the fabrication of a filter for the removal of organics and heavy metals in water which was prepared from treated rice husk and modified activated carbon (AC). The analysis of AC via Brunauer-Emmett-Teller (BET) surface area and scanning electron microscopy evidenced porosity of 707 m2/g as surface and a pore volume of 0.31 cm3/g. The elemental and thermogravimetric analysis proved that AC contain 48. 7% carbon, while the Fourier transform infrared spectroscopy shows that the surface contains functional groups such as O-H, C=C, C-O, C-O-C and C-H. The experimental results were fitted with fixed-bed adsorption models to understand the adsorbate-adsorbent relationship. Fixed-bed adsorption studies show that, the highest adsorption capacity of 248.2 mg/g and 234.12 mg/g for BPA and phenol respectively was obtained at 250 mg/L concentration and 9 mL/min flow rate. The results also revealed 73 % and 87 % as the highest removal capacity for heavy metal Pb and Cd respectively at 20 mg/L concentration and 9 mL/min flow rate. For sustainability, regeneration of the spent AC was carried out in a microwave which showed 75% yield after five cycles, while the rice husk was eluted with 0.lM hydrogen chloride and 37.8% efficiency was achieved after three successive cycles. The UV lamp incorporated in the filter shows total inactivation of E. coli after 7 minutes

    Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems

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    Many areas in power systems require solving one or more nonlinear optimization problems. While analytical methods might suffer from slow convergence and the curse of dimensionality, heuristics-based swarm intelligence can be an efficient alternative. Particle swarm optimization (PSO), part of the swarm intelligence family, is known to effectively solve large-scale nonlinear optimization problems. This paper presents a detailed overview of the basic concepts of PSO and its variants. Also, it provides a comprehensive survey on the power system applications that have benefited from the powerful nature of PSO as an optimization technique. For each application, technical details that are required for applying PSO, such as its type, particle formulation (solution representation), and the most efficient fitness functions are also discussed

    Critical Node Detection for Voltage Collapse Mitigation in Modern Power Systems: A Network Topological-Based Approach

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    Quick detection of critical nodes has become a great concern to most investors and utilities recently due to its influence on prevention of the frequent occurrence of voltage collapse within a power network. This paper, therefore presents an option for detecting critical nodes, an approach which is based on the network topological characteristics of power networks. The mathematical formulations of the approach from the basic circuit theory laws were revisited. A Normalized Eigenvalue (NEV) index using eigenvalue and eigenvector analyses was then developed using MATLAB 2019b as the simulation tool. A simple 10-bus network was used to test the effectiveness of the NEV index method suggested in this paper. The NEV for all the network buses was determined and ranked in decreasing value of NEV to measure the criticality and vulnerability of each load node to voltage collapse within the system. Buses 6 had the highest value of NEV index (1.00) while bus 4 had the lowest NEV index (0.00) value. This suggested that there is a possibility of occurrence of over-voltage at bus 6 and undervoltage at bus 4. Therefore, buses 4 and 6 were identified as the critical buses, where placement of the reactive power support will be most beneficial. The results obtained were compared with those obtained using other methods documented in the literature. The comparison showed the effectiveness of the approach in quick identification of critical parts of the network most especially during critical outages

    Pertanika Journal of Science & Technology

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