Mohamed El-Morsi

Design optimization of batteryless photovoltaic-powered reverse osmosis water desalination in remote areas

Reverse osmosis (RO) is one of the main technologies for water desalination, which can be used in locations with water resources that have high salinity content (such as saline ground water or seawater) to produce fresh water. Energy requirement for RO is less than other desalination processes, but is in the form of electric power, which can be scarce as fresh water in in remote areas not connected to the grid. Fortunately, many areas with fresh water shortage due to lack of rainfall have abundant sunshine. The combination of solar power and RO desalination is attractive, but remote areas usually requires small modular units, which favors photovoltaic (PV) solar energy harvesting. It is important to consider the net cost-effectiveness of the system when designing the PV-RO desalination plant. Adding battery storage to a PV-RO system has the advantage of steadier operation, but is an additional cost whose real benefit is only realized with a larger PV array that can harvest more energy during daytime. This paper compares the net unit cost of fresh water for realistic scenarios of PV-RO systems with and without battery storage. A multi-level optimization approach previously developed by the authors for time-variant power PV-RO systems is adopted; a “sub-loop” optimization determines the operating pressure and flow rate given a fixed system configuration and instantaneous power input, while an “outer loop” optimizes the configuration of the desalination plant. The sub-loop optimization is done via an enumeration approach, while the outer loop is optimized via a mixed real-coded genetic algorithm (GA). A demonstration study shows a batteryless system being approx. 30% more expensive per unit fresh water production than a fully optimized battery-backed system. However, most of the cost of a batteryless system is in initial investment, which with 7% less annual operating cost, can present a plausible design choice for remote areas.Copyright

Energetic Optimization of the Flat Plate Solar Collector

In this chapter, the Taguchi method combined with response surface methodology is introduced to energetically optimize various design parameters of the flat plate solar collector. The design parameters of a flat plate collector are the key factors affecting its performance. The effect of the ambient temperature, solar radiation, and wind speed is also included in the design array to achieve a robust configuration. The Taguchi method results showed that the number of collector flow tubes and the back insulation thickness are the most significant factors in the performance characteristics. Since the Taguchi method optimizes only the performance responses individually. Therefore, the data are then preprocessed by the response model approach based on the I-optimal computer design using the coordinate exchange algorithm. The results showed the ability of the proposed method for optimizing the performance of various components of the solar water heating system in particular and renewable energy systems in general.

Multi-Objective Optimization of Gas Blend Alternative Refrigerants for Vapor-Compression Refrigeration Systems

This paper presents a theoretical study on optimizing the mixing ratios of hydrocarbon blends to be used as refrigerants in existing refrigeration equipment. The primary objective is to maximize the coefficient of performance. The gas blending optimization problem is posed in a multi-objective framework, where the optimization seeks to generate Pareto optimal solutions that span the trade-off frontier between coefficient of performance versus deviation from a desired volumetric refrigeration capacity, while adhering to a maximum compression ratio. Design variables in the optimization are the mass fractions of hydrocarbon gases in the blend. A domain reduction scheme is introduced, which allows for efficient conduction of exhaustive search, with up to three hydrocarbon gases in the blend. While exhaustive search guarantees that the obtained solutions are global optima, the computational resources it requires scale poorly as the number of design variables increase. Two alternative approaches, (multi-start SQP) and (NSGA-II) are also tested for solving the optimization problem. Numerical simulation case studies for replacement of R12, R22 and R134a with hydrocarbon blends of isobutane, propane and propylene show agreement between solution methods that good compromises are possible to achieve, but a small loss in coefficient of performance is inevitable.Copyright

Multi-Level Design Optimization of Reverse Osmosis Water Desalination Powered via Photovoltaic Panels With Battery Storage

Reverse osmosis (RO) is one of the main commercial technologies for desalination of water with salinity content too high for human consumption in order to produce fresh water. RO may hold promise for remote areas with scarce fresh water resources, however, RO energy requirements being in the form of electric power have few options in such areas. Fortunately, scarce rainfall is often associated with abundant sunshine, which makes solar photovoltaic (PV) power an attractive option. Equipping a photovoltaic powered reverse osmosis (PV-RO) desalination plant with battery storage has an advantage of steadier and longer hours of operation, thereby making better use of the investments in RO system components, but the additional cost from including batteries may end up increasing the overall cost of fresh water. It is therefore of paramount importance to consider the overall cost-effectiveness of the PV-RO system when designing the desalination plant. Recent work by the authors has generalized the steady operation model of RO systems to hourly adjusted power-dispatch via a proportional-derivative (PD) controller that depends on the state of charge (SOC) of the battery, yet the operating conditions; namely pressure and flow for a given power dispatch were only empirically selected. This paper considers a multi-level optimization model for PV-RO systems with battery storage by considering a “sub-loop” optimization of the feed pressure and flow given power dispatch for a fixed RO system configuration, as well as a “top-level” optimization where the system configuration itself is adjusted by the design variables. Effect of the sub-loop optimization is assessed by comparing the obtained cost of fresh water with the previous empirically adjusted system for locations and weather conditions near the city of Hurgada on the Red Sea.© 2014 ASME