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High penetration of renewable energy sources into isolated microgrids (µGs) is considered a critical challenge, as µGs’ operation at low inertia results in frequency stability problems. To solve this challenge, virtual inertia control based on an energy storage system is applied to enhance the inertia and damping properties of the µG. On the other hand, utilization of a phase-locked loop (PLL) is indispensable for measuring system frequency; however, its dynamics, such as measurement delay and noise generation, cause extra deterioration of frequency stability. In this paper, to improve µG frequency stability and minimize the impact of PLL dynamics, a new optimal frequency control technique is proposed. A whale optimization algorithm is used to enhance the virtual inertia control loop by optimizing the parameters of the virtual inertia controller with consideration of PLL dynamics and the uncertainties of system inertia. The proposed controller has been validated through comparisons with an optimized virtual inertia PI controller which is tuned utilizing MATLAB internal model control methodology and with H∞-based virtual inertia control. The results show the effectiveness of the proposed controller against different operating conditions and system disturbances and uncertainties.

Humidification dehumidification water desalination system using two cycles of air flow (open and closed-air cycles).

Abstract This article introduces an effective stochastic operation framework for optimal energy management of the shipboard power systems including large, nonlinear and dynamic loads. The proposed framework divides the ship power system into several agents, which coordinate with each other based on their demands/supplies until. The alternating direction method of multipliers (ADMM) is deployed as the multi-agent framework to solve the reformulated distributed energy management problem in the ship. Two types of turbo-generators are considered in the proposed system model, including single-shaft and twin-shaft models, to increase the part-load efficiency in certain times when facing variable speed operation. The proposed distributed framework is equipped with a recursive mechanism, which helps the ship system for running optimal load scheduling when facing insufficient power generation. In order to model the uncertainty effects associated with the forecast error in the interval-ahead load demand, a stochastic framework based on unscented transform is devised which can work in the nonlinear and correlated environments of shipboard power systems. Due to the nonlinear cost function in each agent, a powerful optimization algorithm based on modified θ-firefly algorithm (Mθ-FOA) is proposed. This is a phasor algorithm, which helps for escaping from premature convergence and getting trapped in local optima. The appropriate performance of the proposed stochastic model is examined on the real dataset of a ship power system. The simulation results show the high robustness, guarantied consensus, economic operation and feasible solution when power generation shortage based on load shedding in the system.

In Egyptian desert, growing plants is difficult due to harsh climate (hot at the daytime and cold at the night), infertile soil, low average rainfall and lack of fresh water for irrigation purposes. A set of simple transparent solar stills are integrated with a new solar driven agriculture greenhouse (GH). The stills are placed at the GH roof to use the extra solar radiation (above that required for plant photosynthesis process) for water desalination. In addition to water desalination concept the solar still units even reduce the cooling load during the daytime. A net of aluminum metal coated with black colour is placed on the base of the solar still units to raise the water temperature (enhance desalination process) and provide partially shading for the GH. Using aluminum net decreases also the number of solar still units required to produce the required amount of GH fresh water leading to a significant cost reduction.The main objectives of this work are sizing of the aluminum net, spacing between solar still units to obtain the threshold of plant requirements. Also fresh water production and greenhouse climatic conditions that plant needs (temperature, relative humidity, air velocity and amount of oxygen) are simulated.Numerical simulation was carried out for the hottest day of Borg Elarab, Alexandria (Egypt). 

Utilization of daylight in indoor spaces creates opportunities for energy savings and is linked to increasing productivity in the workplace. This sensitive aspect in environmentally aware architectural design depends on many interfacing factors. In this research, ceiling geometry is investigated as an element that can provide control to natural light, achieved through reflection and diffusion of the external and internal reflected components of daylight. This paper presents a generic optimization procedure for architects that aids in generation and finding of curvilinear and mesh ceiling forms. The objective was to maximize daylight uniformity ratios. A genetic algorithm was developed and coded in LUA, a versatile scripting language. Radiance simulation software was employed as the backend daylighting performance calculation engine, and Ecotect as the front end form input and visualization tool. Conclusions about the optimum ceiling geometry and form for a designed example case were drawn. The presented method provided architects with a variety of choices for designs which are weighed through daylighting performance. Results showed that this approach offers a robust and yet precise form finding method.

This paper proposes two approaches for optimal scheduling of unit commitment (UC) considering reserve generating for competitive market. The particle swarm optimization (PSO) technique is used to find out the solution of both optimal UC and power generation problems, simultaneously. The two proposed approaches depend on various sigmoid functions to obtain the binary values PSO. The first approach takes the fuzzification of generation costs as a sigmoid function; while the second approach takes the fuzzification of power generation as sigmoid function. A proposed objective function is presented dependent on the exponential form which leads to fast convergence of PSO solution. This objective aims to minimize the generation costs as well as maximize their own profit while all load demand and generation reserve are satisfied. Hence, the generations companies (GENCO) schedule their generators with objective maximize their own profit with regard for system social benefit. This means that, this objective helps GENCO to make a decision, how much power and reserve should be sold in markets and how to schedule generators in order to receive the maximum the profit. Different comparisons are carried out using various standard test systems to show the capability of the two proposed sigmoid approaches and the proposed objective function compared with other techniques

Land use and climate change always induce significant changes in various parameters of the hydrologic cycle (e.g., surface runoff, infiltration, evapotranspiration). The Wadi El-Assiuti downstream area in the Eastern Desert of Egypt is one of the most promising areas for development that is suffering from insufficient water availability and inadequate water quality for different purposes. The main goal of this research is to evaluate the changes in groundwater quality, land use, and climate in association with geology and flooding during three periods within the years 1997–2019 in the downstream portion of Wadi El-Assiuti in the Eastern Desert of Egypt, using spatiotemporal variation associated with groundwater hydrochemical analysis and GIS techniques. About 133 groundwater samples were collected to examine groundwater quality changes over time. Different groundwater quality indices were calculated, and the results show that TDS levels of groundwater in the study area ranged between 1080–2780 mg/L, 672–4564 mg/L, and 811–6084 mg/L, while SAR levels varied within 6.15–15.34, 1.83–28.87, and 1.43–30.57 for the years 1997, 2007, and 2019, respectively. Both RSBC and SSP values exhibited significantly increasing trends over time. KR values were within 1.36–4.06 in 1997, 0.58–14.09 in 2007, and 0.35–14.92 in 2019; MAR values were within 6.9–45.2 in 1997, 20.79–71.5 in 2007, and 17.71–75.81 in 2019; and PI values were within 60.16–83 in 1997, 45.56–101.03 in 2007, and 42.51–148.88 in 2019. Across the entire study area, ongoing land use changes increased from 1.1% in 1997 to 4.1% in 2019. Findings pointed to the significant contribution of the deep Nubian Sandstone Aquifer to the groundwater aquifer at Wadi El-Assiuti through fractures and deep faults. Given the climatic conditions from 1997–2019, these changes may have affected water quality in shallow aquifers, especially with increasing evaporation. Realizing the spatiotemporal variation of the aquifer recharge system, land use development, and climate change clearly would help in water resource management. This study revealed that flooding events, deep-seated geologic structures, and land use development associated with human activities have the highest impact on groundwater quality.

Particle Swarm Optimization technique has been improved by fractional order calculus to be used for photovoltaic (PV) modeling. The modified technique which is called Fractional Order Darwinian Particle Swarm Optimization (FODPSO) has been constructed to estimate the optimal electrical parameters of PV modules. Single and double diode models have been used to designate the PV modules. FODPSO and PSO algorithms have been designed and applied on two different PV modules at different irradiances and temperatures. In order to validate the proposed modeling technique, Root Mean Square Error (RMSE) of the current, RMSE of power and Summation of the Individual Absolute Error (SIAE) results obtained using FODPSO and traditional Particle Swarm Optimization (PSO) algorithms have been compared. Minimum RMSE and SIAE have been achieved using the FODPSO technique. To verify the FODPSO results accuracy, accurate measurements of short circuit current, open circuit voltage, and maximum power, voltage at maximum power and current at maximum power have been performed for both PV modules. FODPSO-estimated results show excellent agreement with the experimental ones at different irradiances and temperatures.

This paper proposes the use of modified biochar, derived from Sawdust (SD) biomass using sonication (SSDB) and Ozonation (OSDB) processes, as an additive for biogas production from green algae Cheatomorpha linum (C. linum) either individually or co-digested with natural diet for rotifer culture (S. parkel). Brunauer-Emmett-Teller (BET), Fourier-Transform Infrared (FTIR), thermal-gravimetric (TGA), and X-ray diffraction (XRD) analyses were used to characterize the generated biochar. Ultrasound (US) specific energy, dose, intensity and dissolved ozone (O3) concentration were also calculated. FTIR analyses proved the capability of US and ozonation treatment of biochar to enhance the biogas production process. The kinetic model proposed fits successfully with the data of the experimental work and the modified Gompertz models that had the maximum R2 value of 0.993 for 150 mg/L of OSDB. The results of this work confirmed the significant impact of US and ozonation processes on the use of biochar as an additive in biogas production. The highest biogas outputs 1059 mL/g VS and 1054 mL/g VS) were achieved when 50 mg of SSDB and 150 mg of OSDB were added to C. linum co-digested with S. parkle.