This research performed a techno-economic analysis of diesel-biogas hybrid microgrid system. The paper modeled, designed, and simulated the microgrid system using MAT-LAB/SIMULINK and performed system optimization using HOMER software. The anaerobic digestion (AD) processes were designed and simulated with the aid of Simulink to obtain the methane yield from the reactor. Results show that the methane yield is 95.04 kg/day at a reactor temperature of 55 • C. The synchronous generator was modeled and simulated for the application of both diesel fuel and biogas fuel system. The HOMER software was used to optimize the hybrid micro-grid system with the diesel system taken as the base case. Biogas production was varied between 1 and 5 tons while the calculated energy demand of the village was 271925 kWh. At a biomass production of 4 tons and above, the hybrid system became powered by only the biogas system for total energy production. The energy produced by biogas is 452820 kWh and a cost of energy (COE) of $0.0484. The net present cost (NPC) of the base case system is $1141292 while that of the hybrid system is $176600 and that of the biogas system is $170085 which shows the saving cost of 84.5% and 85.1%, respectively, compared to the base case system over the project lifetime.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Biogas power generation is renewable energy made from biological materials. Biogas power production is technology which helps in development of sustainable energy supply systems. This paper develops Genetic Algorithm optimization model for Biogas electrical power generation of Ilora in Oyo, Oyo state. The production is done using co-digestion system of pig dung and Poultry dung under the process of anaerobic digestion. The pig dung and poultry dung were mixed 50:50%. MATLAB and VISUAL BASIC Software was used to carry out simulations to develop optimized Genetic Algorithm model for Biogas power production with aims to improving electricity accessibility and durability of the community. The results of the research reveal the Empirical Biogas power production without and with Genetic Algorithm optimization. The Result showed that biogas electrical power generated without and with Genetic Algorithm Optimization were 5KW and 11.18KW respectively. The biogas power generation was increased by 6.18KW, which is 38.2% increase after Genetic Algorithm optimization. The results show the application of the Genetic Algorithm optimization model which can be used to improving Biogas power generation when amount of methane gas produced from the animal dung varies with speed of thermal rotating shaft.

This research work modelled and optimized the hybrid microgrid energy system for electricity generation at the University of Abuja, Nigeria, using PV, wind, diesel, and battery renewable energy resources. The model and optimization of the system are performed through HOMER software. The estimated university average annual power consumption is 2355 kWh/day, and the optimal load demand is 313.40 kWp. The PV/wind/diesel/ converter/battery hybrid system has the lowest cost of energy (COE) of 0.1616 $/kWh, operating cost of $50,592, and net present cost (NPC) of $1,795,026 but diesel/wind/converter/battery hybrid system has highest COE of 0.4242 $/kWh and NPC of $4,710,983. The optimal total electricity generated is 1,272,778 kWh/yr while electricity generated by PV contribute the highest energy of 1,030,485 kWh/yr (81%), whereas diesel generator and wind produced energy of 93,927 kWh/yr (7.38%) and 148,366 kWh/yr (11.7%) respectively. The wind/diesel/converter/battery hybrid system produced carbon dioxide (CO2) of 557,749 kg/yr. The most environmentally friendly is the wind/PV/battery and PV/battery hybrid system without pollutants emissions, but the diesel/wind/battery hybrid system has the highest rate of pollutants emissions. The result shows that PV’s electrical power is extremely high from February to June, which causes a high rate of irradiance within the specified period.

The hydroelectric plants flow rate always varies with time due to the speed rotation of turbines which affect the amplitude and frequency of electrical energy generated.  Hydro plants are being utilized for the purpose of peaking as well as base load, pumped storage and spinning reserve power operation etc. Especially in a system consisting of large industries, where frequency and voltage fluctuations are required to be kept minimum, their stability determines the quality of power. For efficient use of plant, complex control techniques are employed in the station automation and these involve the turbine governor in control features for which a flexible governor design is essential. MATLAB 2007 Software was used to carry out simulations analysis to develop fuzzy logic controller for hydropower Generator speed regulation with aims of stabilizing output power supply in order to increase the water flows rate through the hydropower penstock. The result of the research shows the hydropower generator speed model which can be used to stabilized power output as a result of increase in turbine speed rotation when fuzzy logic controller is applied. The result showed that hydropower Generation speed regulation with and without fuzzy logic controller were 319.8m/s and 65m/s respectively. The speed increased by 254.8m/s. the result shows that application of  fuzzy logic controller gives better result and increase the rotational speed of hydropower.

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