Exploring the complementary relationship between solar and hydro energy harvesting for self-powered water monitoring in low-light conditions

Highlights

• Hydro energy harvesting could enable more ubiquitous monitoring of water resources.

• Hydro power complements solar power by lowering the variance in harvested energy.

• Hydro energy harvesting can exceed solar power when dense tree canopy is present.

• In the Southeastern US, as much as 58% of water bodies have dense tree canopy.

• In the contiguous US, first through fourth order streams have 32% mean tree canopy.

Abstract

Relying on solar energy alone to power water monitoring stations limits the ability to monitor water resources in low-light locations, such as for streams with dense tree canopy cover. To address this limitation, water monitoring stations could have a supplementary micro hydro-turbine to harvest kinetic energy from streamflow. To explore this possibility, we simulated the energy harvesting potential at 42 locations with long term stream velocity records and determined the canopy cover for streams across the contiguous United States (CONUS). Results show that a site with typical streamflow velocity and dense evergreen tree canopy would have 1.6 times less sample loss, from 68% to 43%, after adding hydro energy harvesters. Many streams across the CONUS with dense canopy cover could benefit from this, especially headwater streams and streams in the Southeastern US where many watersheds have more than 50% of their stream length under dense tree canopy cover.

Introduction

Water resources have been monitored with networks of in-situ sensing systems for studying many hydrological and environmental problems such as flooding, runoff pollution, and aquatic ecosystem degradation for decades (Bartos et al., 2018; Rode et al., 2016; Ruhala and Zarnetske, 2017; Wymore et al., 2018). In the United States, by the time of writing of this paper, the United States Geological Survey (USGS) has collected and made publicly available surface water historical instantaneous data (water quantity and/or quality) for 14,481 different (active and inactive or discontinued) stream locations across the nation. While this may seem like a large number of monitoring sites, considering the Nationwide Rivers Inventory (NRI) estimated a total of 5,200,000 km of streams in the contiguous United States (CONUS) (Benke, 1990), it means that there is only one USGS water sensing station for approximately every 360 km of stream length. This density of in-stream measurement is insufficient for understanding many properties and functions occurring within waterbodies (Horsburgh et al., 2010; Kirchner et al., 2004). While the limited spatial density of current water sensing networks is certainly a function of the high installation and maintenance cost of each individual stream-gauging station, another limiting factor is the availability of energy to power the sensing equipment. Given that many sensing locations are off-grid, energy harvesting, the process of deriving energy from the surrounding environment and converting it to a usable form (e.g., electrical energy), must be used to power the sensing system and recharge batteries at the sensing station.

A variety of energy harvesting approaches from different renewable energy sources (e.g., vibration, wind, and solar energy harvesting) for wireless sensor networks have been studied in past research studies (see Olatinwo and Joubert (2019) for a review). Among such approaches, the most common energy harvesting approach for water monitoring is solar power (Chen et al., 2017) due to its relatively low-cost, robustness, and high-power output ratings (Shaikh and Zeadally, 2016). Prior studies have shown how solar energy harvesting can be exploited for sensing environmental variables and water-related characteristics (Bartos et al., 2018; Jones et al., 2017; Kapetanovic et al., 2017; Quinn et al., 2010). Additionally, tools such as pvlib python, an open-source community supported tool (Holmgren et al., 2018), enable estimating solar power generation prior to actual deployment of a given solar panel. However, solar energy harvesting is not always a viable option due to low-light conditions (e.g., forested areas with dense tree canopies or high wall canyons), consistent cloudy weather (Azevedo and Lopes, 2016; Jeong and Culler, 2012; Taneja et al., 2008), or within urban environments (e.g., within subsurface drainage infrastructure). This motivates the need to investigate other energy harvesting sources for such locations. For water monitoring, one obvious energy harvesting source is the kinetic energy of water flow as a potential supplemental energy source to solar energy for low-light conditions.

While prior research has widely explored the potential for larger scale hydropower harvesting applications such as run-of-river hydropower plants (e.g., Yildiz and Vrugt (2019)), fewer studies have investigated the smaller-scale micro hydropower harvesting potential for monitoring applications in natural streams or stormwater infrastructure systems. There has been significant work, however, exploring micro hydropower harvesting for drinking water pipe networks that show this technology's potential for other water resource and environmental applications (Hoffmann et al., 2013; Rödel et al., 2016; Ye and Soga, 2012). There has also been recent laboratory work exploring micro hydro-turbine power harvesting that can inform field application studies. Two such studies evaluated the effect of different energy harvesting mechanisms (e.g., hydro-turbine harvesting power from flow-velocity) and different design choices (e.g., hydro-turbine geometries) on the efficiency of the systems (Azevedo and Lopes, 2016; Kamenar et al., 2016). These systems were able to generate hydro power up to hundreds of milliwatts based on both the energy harvester design choices and the characteristics of energy harvesting environment (e.g., flow-velocity for hydro-turbine), which could be enough to power a water sensing system in the natural environment with real-time data communication.

Any energy harvesting sources (e.g, solar or hydro) can be temporary and spatially limited or even periodically unavailable leading to intermittent power outages and sensing gaps without sufficient energy storage infrastructure (e.g,. batteries). Therefore, a combined use of energy harvesting sources, when possible, is expected to prevent or reduce the time periods when the sensing system is out of power, reducing the need for sophisticated energy storage infrastructure. For example, Morais et al. (2008) showed how using a small solar-panel combined with a small hydro generator placed in a nearby irrigation or hydroponic water pipe and a wind generator was able to supply a generic wireless data acquisition platform energy store in agricultural and livestock environments even with low solar radiation.

This prior research provides important understanding and software needed to enable energy harvesting from different energy sources (i.e., solar, hydro, and wind) for sensing the natural environments, and highlights the importance of a combined energy harvesting from various energy sources when individual sources are limited. However, reviewing prior research reveals that hydro energy harvesting to power in-stream water monitoring stations for locations with limited access to solar energy (i.e., riparian forest zones where sunlight penetrating the tree canopy and reaching the solar panel underneath it can be highly limited) is not explored yet. This comparison is necessary to better understand if hydro energy harvesting is a viable option for achieving high-coverage and dense spatial sensing of waterways, in particular for those locations with limited availability of solar power. Furthermore, knowing what fraction of streams in the CONUS are candidates for hydro energy harvesting due to dense tree canopy limiting solar energy harvesting will aid in understanding the potential impact of advancing hydro energy harvesting to monitor more locations in the stream network toward a long term vision of ubiquitous monitoring of the nation's waterbodies.

Given these knowledge gaps, the first goal of this study is to compare and simulate energy harvesting in multiple river locations using a solar panel versus a hydro-turbine in order to investigate their complementary relationship in self-powering water monitoring stations under different light conditions due to the presence of tree canopy covering waterways. The second goal is to determine the stream length in the CONUS with dense tree canopy to estimate the potential impact of hydro energy harvesting. Section 2 discusses the materials and methods used to achieve both of these goals including the datasets used to simulate the solar and hydro energy harvesting, sensor stations specifications, and energy harvesting simulations. Section 3 presents the results of the analysis including a discussion of the findings and their limitations. Finally, we summarize and offer conclusions from the study in Section 4.