Amy M. Bilton

Design of power systems for reverse osmosis desalination in remote communities

AbstractMany remote communities lack access to a reliable water supply. They often have access to brackish groundwater or seawater, making reverse osmosis desalination a possible solution. However, reverse osmosis desalination is an energy-intensive process and many remote communities are off the electrical grid. Determining the most economic reverse osmosis system configuration and electrical power source for a given remote community is a challenge due to their unique resource availabilities. This paper presents an optimization-based approach to compare the economics of different small-scale reverse osmosis systems and power sources for remote communities. In this approach, physical models describe the performance of electrical power systems composed of photovoltaics, wind turbines, diesel generators, batteries, and hybrid systems. These power system models are coupled to a reverse osmosis system model to determine the water production. An optimization is performed to determine the most economic power sy...

ON THE KINEMATICS OF SOLAR MIRRORS USING MASSIVELY PARALLEL BINARY ACTUATION

Precision mirrors are required for effective solar energy collectors. Manufacturing such mirrors and making them robust to disturbances such as thermal gradients is expensive. In this paper, the use of parallel binary actuation to control the shape of mirrors for solar concentrators is explored. The approach embeds binary actuators in a compliant mirror substructure. Actuators are deployed in a specified pattern to correct the mirror shape. The analysis for binary-actuated compliant mirror structures is presented. Analytical models are developed for one-dimensional and two-dimensional compliant structures with embedded binary actuators. These analytical models are validated using finite element analysis and experimental studies. The models and experiments demonstrate the capabilities of binary actuated mirrors. System workspace is explored, the principle of superposition required for their control is demonstrated, as is the mirror ability to correct its figure.

Enhancing the Performance of Photovoltaic Powered Reverse Osmosis Desalination Systems by Active Thermal Management

Reverse osmosis (RO) is a well-known process for desalinating seawater and brackish groundwater. Desalination is energy-intensive, so using photovoltaic (PV) panels to power the process is an attractive and cost-effective concept, especially for community-scale systems. Increasing the system efficiency will lower the total cost of water produced, making the systems more economically competitive for a greater number of geographic locations. It is noted in this paper that the amount of water produced by a PV-powered RO (PVRO) system can be increased if the temperatures of the solar panel and the reverse osmosis feed water are actively managed. For a given level of solar radiation, a photovoltaic panel produces more power at a lower temperature. Also, for a given power, an RO system produces more clean water at a higher input (feed) water temperature. An active thermal management system is needed to exploit these complementary characteristics by cooling the solar panel and warming the RO feed water, increasing the amount of fresh water produced. This can be accomplished by running the RO feed water through a heat exchanger attached to the back of the solar panel, cooling it. Furthermore, the ability to cool the solar panels permits the addition of low-cost, flat-plate concentrating mirrors to be used with the PV panels, which further increases the PV power output. The flow of the water through the respective units must be actively controlled as there are limits for the maximum temperatures of both the RO water and PV panels. In this paper, a concept for an active PVRO thermal control system is presented. Simulations and experimental results show the effectiveness of this approach. In experiment, a 57% increase in fresh water production was achieved. These experimental results agree well with simulation models.Copyright

Sensor architecture for the robotic control of large flexible space structures

The future construction and maintenance of very large space structures such as orbital solar power stations and telescopes will require teams of free-flying space robots. For robots to effectively perform these tasks, they will require knowledge of the structures vibrations. Here, a robotic based sensor architecture for the vibration estimation of very large structures is presented. It is shown that this information can be effectively estimated by combining data provided by free-flying remote robot “observers” equipped with range sensors with structure-mounted acceleration sensors. A modified Kalman filter fuses low-bandwidth vision data from the remote sensing robots with the high bandwidth, but spatially sparse structure-mounted acceleration sensors. Results from experimental studies are presented that confirm the effectiveness of this approach. 2007 Wiley Periodicals, Inc.

The modular design of photovoltaic reverse osmosis systems: making technology accessible to nonexperts

Abstract Photovoltaic reverse osmosis systems can provide water to many underserved communities. These systems need to be custom-tailored for the water demand, solar insolation, and water characteristics of a specific location. Systems can be constructed from modular components to be cost effective. Designing a custom system composed of modular components is not a simple task. For a given modular inventory, a large number of possible system configurations exist. Determining the best system configuration is a daunting task for a small community without expertise. This paper presents a computer-based modular design method that can enable nonexperts to configure such a system for their community from an inventory of modular components. The method employs fundamental engineering principles to reduce the number of possible configurations and optimization methods to configure a system. Examples cases for a range of communities demonstrate the power of this approach.

Adaptive Heliostat Solar Arrays Using Shape-Optimized Compliant Mirrors

In a Solar Power Tower (SPT) system, the ideal shape of a heliostat concentrator is a section of paraboloid which is a function of the location in the array and the incidence sun angle. This shape is difficult to achieve and limits the system efficiency. A shape-optimized compliant (SOC) design of parabolic heliostats is presented here to solve this problem. An approximation of the ideal shape is suggested to use an optimized stationary paraboloid shape which only varies with heliostat location in the array. A compliant structure design is proposed that to use a simple flat mirror with a two-dimensional tailored stiffness profile to form the required parabolic surface using adjustment mechanisms at each corner. This design is validated by numerical simulations including FEA tools, ray tracing, and classical nonlinear optimization. The annual performance shows that the SOC heliostat will substantially improve the efficiency and benefit the SPT system.© 2012 ASME

Modular Design of Community-Scale Photovoltaic Reverse Osmosis Systems Under Uncertainty

Photovoltaic reverse osmosis (PVRO) systems can provide a viable clean water source for many remote communities. To be cost-effective, PVRO systems need to be custom-tailored for the local water demand, solar insolation, and water characteristics. Designing a custom system composed of modular components is not simple due to the large number of design choices and the variations in the sunlight and demand. This paper presents a modular design architecture, which when implemented on a low-cost PC, would enable users to configure systems from inventories of modular components. The method uses a hierarchy of filters or design rules, which can be provided in the form of an expert system, to limit the design space. The architecture then configures a system from the reduced design space using a genetic algorithm to minimize the system lifetime cost subject to system constraints. The genetic algorithm uses a detailed cost model and physics-based PVRO system model which determines the ability of the system to meet demand. Determining the ability to meet demand is challenging due to variations in water demand and solar radiation. Here, the community’s historical water demand, solar radiation history, and PVRO system physics are used in a Markov model to quantify the ability of a system to meet demand or the loss-of-water probability (LOWP). Case studies demonstrate the approach and the cost-reliability trade-off for community-scale PVRO systems. In addition, long-duration simulations are used to demonstrate the Markov model appropriately captures the uncertainty.Copyright

Design Optimization of Sustainable Off-Grid Power Systems for the Developing World

Electrification of remote areas in the developing world can greatly improve the health and economic standing of the population. Unfortunately, providing power to these remote areas can be expensive and determining the most economical solution is not trivial. This paper presents a method to compare the economics of different small-scale power systems for developing world. In this method, models are developed to describe the performance of power systems composed of diesel generators, batteries with photovoltaics or wind turbines, and hybrid systems. These models are coupled to an optimizer to determine the lowest cost solution that meets the desired system reliability. The reliability is expressed as Loss of Load Probability, and is computed using hourly solar and wind data. In this paper, this method is used to design a power system for a small hospital in the developing world. The results are presented for three sample locations in Honduras, Pakistan, and Uganda. Results show that the economic attractiveness of different technologies varies greatly due to local climatic conditions. The variety and soundness of the solutions found using this method show that it can aid in the design of a small-scale power system for any location in the developing world.Copyright

Optimization of Renewable Energy Power Systems for Remote Communities

Many remote communities rely on diesel generators as their primary power source, which is expensive and harmful to the environment. Renewable energy systems, based on photovoltaics and wind turbines, present a more sustainable and potentially cost-effective option for remote communities with abundant sun and wind. Designing and implementing community-owned and operated renewable power generation alternatives for critical infrastructure such as hospitals, water sanitation, and schools is one approach towards community autonomy and resiliency. However, configuring a cost-effective and reliable renewable power system is challenging due to the many design choices to be made, the large variations in the renewable power sources, and the location specific renewable power source availability. This paper presents an optimization-based approach to aid the configuration of a solar photovoltaic (PV), wind turbine generator and lead-acid battery storage hybrid power system. The approach, implemented in MATLAB, uses a detailed time-series system model to analyze system Loss of Load Probability (LOLP) and a lifetime system cost model to analyze system cost. These models are coupled to a genetic algorithm to perform a multi-objective optimization of system reliability and cost.The method was applied to two case studies to demonstrate the approach: a windy location (Gibraltar, UK), and a predominantly sunny location (Riyadh, Saudi Arabia). Hourly solar and wind resource data was extracted for these locations from the National Oceanic and Atmospheric Administration for five-year data sets. The village load requirements were statistically generated from a mean daily load for the community estimated based on the population and basic electricity needs. The case studies demonstrate that the mix and size of technologies is dependent on local climatic conditions. In addition, the results show the tradeoff between system reliability and cost, allowing designers to make important decisions for the remote communities.Copyright

Controllable energy recovery for a smart PVRO desalination system

Photovoltaic reverse osmosis (PVRO) systems are a viable clean water source for many underserved communities. PVRO systems often use batteries and fixed recovery ratio energy recovery devices to operate at a constant (non-optimal) pressure. An alternate approach that eliminates expensive batteries and greatly increases water production is to optimally control the operation of the system in real-time to respond to variations in solar radiation and water conditions. This paper presents the development of a computer-controlled energy recovery device (ERD) for PVRO systems. It allows for optimal control of both the RO operating pressure and recovery ratio using an integrated computer-controlled variable nozzle/Pelton generator system. Analytical models are developed for the variable nozzle, Pelton bucket and Pelton turbine. These models are validated using a custom designed experimental system. The efficiency of the components is evaluated to demonstrate the capability of this key device for smart PVRO systems.