A Theory of Renewable Energy from Natural Evaporation

About 50% of the solar energy absorbed at the Earth’s surface is used to drive evaporation, a powerful form of energy dissipation due to water’s large latent heat of vaporization. Evaporation powers the water cycle that affects global water resources and climate. Critically, the evaporation driven water cycle impacts various renewable energy resources, such as wind and hydropower. While recent advances in water responsive materials and devices demonstrate the possibility of converting energy from evaporation into work, we have little understanding to-date about the potential of directly harvesting energy from evaporation. Here, we develop a theory of the energy available from natural evaporation to predict the potential of this ubiquitous resource. We use meteorological data from locations across the USA to estimate the power available from natural evaporation, its intermittency on varying timescales, and the changes in evaporation rates imposed by the energy conversion process. We find that harvesting energy from natural evaporation could provide power densities up to 10 W m-2 (triple that of present US wind power) along with evaporative losses reduced by 50%. When restricted to existing lakes and reservoirs larger than 0.1 km2 in the contiguous United States (excluding the Great Lakes), we estimate the total power available to be 325 GW. Strikingly, we also find that the large heat capacity of water bodies is sufficient to control power output by storing excess energy when demand is low. Taken together, our results show how this energy resource could provide nearly continuous renewable energy at power densities comparable to current wind and solar technologies – while saving water by cutting evaporative losses. Consequently, this work provides added motivation for exploring materials and devices that harness energy from evaporation

Potential for natural evaporation as a reliable renewable energy resource

The evaporation of water represents an alternative source of renewable energy. Building on previous models of evaporation, Cavusoglu et al. show that the power available from this natural resource is comparable to wind and solar power, yet it does not suffer as much from varying weather conditions

Code and Data for Potential for natural evaporation as reliable renewable energy resource

<p><u><b>See ReadMe.docx for more details.</b></u></p><p><b>dBmTMY3</b></p><p>This csv file is a 21 column by 340910 row database that stores 365 days of mean meteorological conditions for 934 weather stations identified in the Typical Meteorological Year (TMY) 3 dataset provided by the DOE/NREL [1]. The first 14 columns are a re-processing product of the daily averaging across the TMY for that specific location. The last 7 columns are the result of calculations using a model of an evaporation driven engine operating at steady-state</p><p><br></p><p><b>dBGLWDTMY3</b></p><p>This csv is a 14 column by 11049 row database that stores the locations and sizes of 11048 lakes and reservoirs larger than 0.1 km2 across the contiguous US as identified by Lehner and Döll [2]. At each location, we interpolate the annual mean power density, reduced evaporation rate, and surface temperature elevation possible due to using evaporation driven engines from the dBmTMY3 dataset. Using the surface area, we calculate the total power available and annual water savings. We also note the distance to the nearest TMY3 weather station and the USAF Code of the station. The first 7 rows are extracted from Lehner and Döll [2], columns 8 – 12 are calculated at each location, and columns 13 & 14 are determined between Lehner and Döll [2] and the TMY3 database [1].</p><p><br></p><p><b>dBCAv2010</b>, <b>dBTXv2010</b>, and <b>dBNYv2010</b> </p><p>Each csv file is a 159 column by 26281 row databases that stores 26280 hours of meteorological conditions for three respective Class 1 weather stations (USAF Codes 723815, 722650, 725020) identified in the Typical Meteorological Year 3 dataset provided by the DOE/NREL [1]. Each database uses an annual normalized demand curve of 2010 provided by the respective Independent System Operator (CAISO [3], ERCOT[4], and NYISO[5]). The first 6 columns are created from the respective TMY3 database [1], columns 7 – 9 are calculated for no engine conditions, columns 10 – 35 are normalized power load for 2010 reported by the respective Independent System Operator, and columns 36 – 159 are calculated with a PI control method.</p