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Effect of carbonization on the surface and influence on heavy metal removal by water hyacinth stem-based carbon
No full textPurpose – The aim of this study is to examine the effect of carbonization on the surface and its influence on
heavy metal removal by water hyacinth based carbon.
Design/methodology/approach – Dried water hyacinth stem was used as precursor to prepare carbon
based adsorbent by pyrolysis method. The adsorbent proximate (ash, volatile matter and fixed carbon) and
elemental (carbon hydrogen nitrogen sulfur) composition, surface area, pore size distribution, surface
chemistry was examined and compared.
Findings – The results demonstrated that through carbonization in comparison to dried water hyacinth stem,
it increased the surface area (from 58.46 to 328.9 m2
/g), pore volume (from 0.01 to 0.07 cc/g), pore size (from 1.44
to 7.557 A) thus enhancing heavy metal adsorption. The metal adsorption capacity of Cd, Pb and Zn was
measured and analyzed through induced coupled plasma-mass spectrometer. At metal concentration of 0.1 mg/
l adsorption rate for Cd, Pb and Zn was 99% due to increased large surface area, coupled with large pore size
and volume. Furthermore, the adsorbent surface hydroxyl group (OH ) enhanced adsorption of positively
charged metal ions through electrostatic forces.
Practical implications – It is presumed that not only adsorption with synthetic wastewater but real
wastewater samples should be examined to ascertain the viability of adsorbent for commercial application.
Originality/value – There are little or scanty data on the effects of carbonization on water hyacinth stem
based carbon and subsequent effects on heavy metal removal in effluents
Modeling and Energy Management Strategy in a Grid Connected Solar PV System
No full textElectric power is substantially an important resource in the modern world. With the increase in demand for electric energy, there is a need to search for alternative energy sources because conventional resources are being exhausted. This results to significant increase in electricity cost. Use of green energy as an alternative to the conventional generation of electricity is currently on the rise. This study presented modeling and energy management of a grid-connected solar PV system aimed at reducing electric energy cost to an ordinary consumer in Kenya. Electricity cost is one of the top expenses of the ordinary consumer. The study was conducted at Murang’a University of Technology, Kenya. MATLAB Simulink software was used for modeling. Arduino Uno was chosen to perform real-time energy management that involved switching between the micro sources and the grid when the supply current from the micro sources dropped below a defined threshold value. Arduino microcontroller used instantaneous method of calculating current, voltage and power. An Application Programming Interface was proposed for forecasting energy production from the solar Photovoltaic system. Significant savings in electric energy bill was expected with the proper application of the Energy Management System in a smart house. The prototype developed managed to disconnect the loads one at a time and reconnect the particular load to the grid whenever the supply current from the micro sources dropped below the specified threshold value
Single Axis Solar Tracking System
No full textThis paper is about the design and development of a microcontroller based solar tracking system. Solar energy is rapidly becoming an alternative means of electrical source in Kenya and all over the world and the solar energy becomes profitable when the solar rays are tracked with its maximum efficiency. The best way to get the maximum power output of solar array is by sun tracking. Usually, solar panels are steady and always the front faces the direction the sun rises from and it evident from the stationary mounted panels we see on buildings and other solar plants, this causes less amount of light incident on the panel. When we use the solar tracker system, it will move in the direction of the sun and get more amount of light incident. The great benefits of solar energy is that it is sustainable, highly reliable and requires little maintenance. Therefore, came up a system that deals with the design and construction of solar tracking system, whereby the solar panel follows the sun as it moves. The project is based on a microcontroller which controls the system by communicating with sensors and motor based on movement of the sun, the system employs light dependent resistors that will vary their resistance depending on the light intensities, light dependent resistors give output to the Arduino every time and Arduino processes the data and sends a control signal to the motor. Through the design, implementation, testing and results of the project, an efficient way of increasing the production of solar power is demonstrated
A Voltage Stability Constrained Optimal Power Flow using Multi-objective Particle Swarm Optimization Algorithm
No full textAs the global demand for energy rises, power system networks are teetering on the verge of collapsing owing to a compromise in system stability. During system disturbances, the network's inability to supply adequate reactive power causes instability and eventual collapse. As such, optimized generation scheduling during system disturbances can improve the utilization of the power plants while lowering power loss, improving voltage regulation, reducing branch loading, and ensuring the secure operation of system equipment. Since power systems have conflicting and multiple objectives, this study proposes a multiobjective optimal power flow incorporating three objective functions: generation cost, power loss, and the maximum value of the line Voltage Collapse Proximity Index. The Multiobjective Particle Swarm Optimization Algorithm is used to minimize these objectives on the IEEE 30-bus system for different case studies in normal, contingency, and stressed system conditions. Fuzzy Decision Theory is utilized for obtaining the best compromise solutions amongst a set of Pareto optimal solutions. The results show that the voltage stability of the system is improved by an average of 63.09% during system disturbances with multiobjective optimization. Simultaneous optimization of the three objective functions provides the most voltage stable condition for all system conditions, preventing possible collapse
Efficient Control strategy based on instantaneous power theory and model predictive control for grid connected photovoltaic system
No full textDue to the rapid decline of fossil resources and the impact of their use for electric power generation on the environment, renewable energy sources are increasingly explored and integrated into the power grid. Among the Renewable energy sources, photovoltaic (PV) systems are one of the most integrated into the utility grid. Thus, this paper presents a control scheme based on instantaneous power theory (IPT)and model predictive control (MPC) to inject the PV power into the grid at unity power factor with minimum current harmonics. The proposed control strategy is applied to a two-stage grid connected PV system which employs boost converter and two-level voltage source inverter. The current references are obtained in the dq reference frame based on IPT. A finite control set model predictive control (FCS-MPC) is used to control the inverter current in order to inject with high accuracy the current references into the grid. The effectiveness and the performance of the proposed control strategy is confirmed by MATLAB/Simulink under various solar irradiance level
