This paper investigates the potential of rice straw for producing energy in Egypt. It is estimated that about 3.1 million tons/year of rice straw are disposed by burning directly in the open field causing environmental problems. The present study was undertaken to assess the performance of rice straw power plant to specify the amount of the power, and GHG mitigation relative to the disposal rice-straw in energy production. The results indicate that rice straw can provide an annual net electric energy output of 2,447 GWh/year. The plant can reduce CO2 emissions of (1.2M ton CO2/year)

Offshore wind turbines are being used to harness the high value of wind energy usually available on the sea sufficiently far from the shore (i.e. some kilometers). The present study provides an assessment of the potential of offshore wind energy along the Mediterranean Sea in Egypt. The techno-economic assessment was conducted considering a 7.0 MW offshore wind turbine at seven sites along the Mediterranean Sea. Fixed platforms were considered, assuming that the maximum sea depth will be 60 m, that is representative of the sea depth in the Mediterranean coast of Egypt at 5 km from the shore. The analysis reveals that a very large amount of energy can be harvested. The minimum energy production is obtained at Alexandria with a capacity factor of 55%, and the maximum energy production is obtained at El Dabaa station with a capacity factor of 63%. The levelized cost of electricity (LCOE) is estimated as to be equal to about 0.075–0.079 US$/kWh which can be considered very competitive with other renewable energy systems in Egypt. The results prove the techno-economic feasibility of the offshore wind energy resource in Egypt, and it would motivate both the research community and the policy makers for more attention regarding this resource.

Power factor (PF) is a measure of how effectively electricity is used. The low PF causes considerable power losses along the power supply chain. In particular, it overloads the distribution system and increases the power plant's burden to compensate the expected power losses. Most of the existing PF correction techniques are developed based on capacitor and assuming that power systems are static. However, the power systems are dynamic systems such that their states change over time, necessitating dynamic correction systems. In the emerging smart grid systems, real-time measurements can easily be taken for voltage, current and harmonics. Then, the measured data can be transmitted to a PF controller to reach the desired PF value. However, the problem that may arise in real-time applications is how to determine and adjust the optimal capacitor size that can balance the power factor. In this regard, we propose a real-time correction system based on multi-step capacitor banks to improve PF in co-operation with de-tuned filters to mitigate the harmonics. First, a mathematical model has been formulated for the proposed power factor correction system. The model can be employed to determine the optimal operational settings of the multi-step capacitor and the reactor value that optimize the reactive power while considering the desired PF value and restricting the harmonics. Second, a genetic optimization approach is applied to solve the proposed mathematical model as it can provide accurate solution in a short computational time. A Monte Carlo simulation approach is considered for validating the proposed PF correction system. The simulation results show that the average PF of the randomly generated test instances has improved from 0.7 to 0.95 (35% increase). Furthermore, we conducted real experiments using a PF testbed for experimental validation. The results are found to be consistent with the simulation results, which validate the effectiveness and applicability of the proposed correction system. Furthermore, the saved kVA in one day is estimated to be 26% of total kVA.