skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: GreenCoin: A Renewable Energy-Aware Cryptocurrency
In this paper, we propose GreenCoin – an energy-efficient cryptocurrency system with mining protocols designed to favor locations with relatively higher availability of renewable energy. Traditionally, crypto coin mining involves solving complex mathematical problems by high-end computing devices consuming an enormous amount of electricity, thus adversely affecting net carbon emissions. To reduce cost and emissions, GreenCoin uses a modified proof of stake (PoS) consensus algorithm, which itself is more energy efficient compared to other state-of-the-art methods. Our modified PoS algorithm, called Green PoS (GPoS), allows GreenCoin to favor nodes (with reward and privilege) located in regions with higher availability of renewable energy. We present a detailed system architecture of GreenCoin and explain the operating method of GPoS. We also provide results from empirical studies demonstrating the renewable energy-aware approach of GreenCoin.  more » « less
Award ID(s):
2107101
PAR ID:
10535081
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
IEEE
Date Published:
ISBN:
979-8-3503-4394-6
Page Range / eLocation ID:
70 to 80
Subject(s) / Keyword(s):
renewable energy blockchain cryptocurrency
Format(s):
Medium: X
Location:
Boston, MA, USA
Sponsoring Org:
National Science Foundation
More Like this
  1. The increasing penetration of renewable energy resources in distribution systems necessitates high-speed monitoring and control of voltage for ensuring reliable system operation. However, existing voltage control algorithms often make simplifying assumptions in their formulation, such as real-time availability of smart meter measurements (for monitoring), or real-time knowledge of every power injection information (for control). This paper leverages the recent advances made in high-speed state estimation for real-time unobservable distribution systems to formulate a deep reinforcement learning (DRL)-based control algorithm that utilizes the state estimates alone to control the voltage of the entire system. The results obtained for a modified (renewable-rich) IEEE 34-node distribution feeder indicate that the proposed approach excels in monitoring and controlling voltage of active distribution systems. 
    more » « less
  2. Quantification of environmental impacts through life cycle assessment is essential when evaluating bioenergy systems as potential replacements for fossil-based energy systems. Bioenergy systems employing localized fast pyrolysis combined with electrocatalytic hydrogenation followed by centralized hydroprocessing (Py-ECH) can have higher carbon and energy efficiencies than traditional cellulosic biorefineries. A cradle-to-grave life cycle assessment was performed to compare the performance of Py-ECH versus cellulosic fermentation in three environmental impact categories: climate change, water scarcity, and eutrophication. Liquid hydrocarbon production using Py-ECH was found to have much lower eutrophication potential and water scarcity footprint than cellulosic ethanol production. Greater amounts of renewable electricity led to lower greenhouse gas emissions for the Py-ECH processing. When the renewable fraction of grid electricity is higher than 87%, liquid hydrocarbon production using Py-ECH has lower greenhouse gas emissions than cellulosic ethanol production. A sensitivity analysis illustrates the major role of annual soil carbon sequestration in determining system-wide net greenhouse gas emissions. 
    more » « less
  3. The nexus of food, energy, and water systems offers a meaningful lens to evaluate hydroelectric dam removal decisions. Maintaining adequate power supplies and flourishing fish populations hangs on the balance of managing the tradeoffs of water resource management. Aside from energy adequacy, substituting hydropower with other renewable energy sources impacts the overall energy dispatch behavior of the grid, including emissions of existing fossil fuels. This study extends earlier work in the literature to evaluate the adequacy impact to the power supply by removing four Lower Snake River dams in the Columbia River Basin in favor of supporting migratory salmon populations. The authors explore the climate performance, i.e., fossil fuel dispatch changes, of simulated renewable substitution portfolios to supplement performance metrics alongside adequacy and initial investment metrics. The study finds that including the climate metric greatly influences the favorability of some alternative portfolios that would otherwise be overlooked, with some portfolios improving climate mitigation efforts by reducing emissions over the baseline scenario. The contribution is in advancing a straightforward and supplementary climate performance method that can accompany any energy portfolio analysis. 
    more » « less
  4. The abundant availability of crop waste and forestry residues in Texas provides great potential for producing renewable diesel in the local towns of Texas. This study aims to evaluate the environmental impacts of renewable diesel use in Texas transportation and the potential of renewable diesel production in Texas. The GREET model was used to customize the life cycle pathway of renewable diesel and evaluate its environmental impacts. The models of renewable diesel produced from forestry residue and corn stover were built to calculate life cycle gas emissions of combination short-haul heavy-duty trucks fueled with renewable diesel. Life cycle GHG emissions of renewable diesel are much lower than those of low-sulfur diesel. However, with respect to renewable diesel derived from corn stover, life cycle PM10 and PM2.5 emissions were almost double those of low-sulfur diesel in 2024, and both emissions will be reduced by 37–38% in 2035. The life cycle emission trends of SOx, black carbon, and primary organic carbon are very similar to those of PM10 and PM2.5. The total cost of ownership (TCO) of heavy-duty trucks using renewable diesel produced from forestry residues or corn stover would be 10.3–14.8% higher than those consuming regular low-sulfur diesel in Texas. 
    more » « less
  5. Wind energy and wave energy are considered to have enormous potential as renewable energy sources in the energy system to make great contributions in transitioning from fossil fuel to renewable energy. However, the uncertain, erratic, and complicated scenarios, as well as the tremendous amount of information and corresponding parameters, associated with wind and wave energy harvesting are difficult to handle. In the field of big data handing and mining, artificial intelligence plays a critical and efficient role in energy system transition, harvesting and related applications. The derivative method of deep learning and its surrounding prolongation structures are expanding more maturely in many fields of applications in the last decade. Even though both wind and wave energy have the characteristics of instability, more and more applications have implemented using these two renewable energy sources with the support of deep learning methods. This paper systematically reviews and summarizes the different models, methods and applications where the deep learning method has been applied in wind and wave energy. The accuracy and effectiveness of different methods on a similar application were compared. This paper concludes that applications supported by deep learning have enormous potential in terms of energy optimization, harvesting, management, forecasting, behavior exploration and identification. 
    more » « less