Wave energy has been studied and explored because of its enormous potential to supply electricity for human activities. However, the uncertainty of its spatial and temporal variations increases the difficulty of harvesting wave energy commercially. There are no large-scale wave converters in commercial operation yet. A thorough understanding of wave energy dynamic behaviors will definitely contribute to the acceleration of wave energy harvesting. In this paper, about 40 years of meteorological data from the Gulf of Mexico were obtained, visualized, and analyzed to reveal the wave power density hotspot distribution pattern, and its correlation with ocean surface water temperatures and salinities. The collected geospatial data were first visualized in MATLAB. The visualized data were analyzed using the deep learning method to identify the wave power density hotspots in the Gulf of Mexico. By adjusting the temporal and spatial resolutions of the different datasets, the correlations between the number of hotspots and their strength levels and the surface temperatures and salinities are revealed. The R value of the correlation between the wave power density hotspots and the salinity changes from −0.371 to −0.885 in a negative direction, and from 0.219 to 0.771 in a positive direction. For the sea surface temperatures, the R values range from −0.474 to 0.393. Certain areas within the Gulf of Mexico show relatively strong correlations, which may be useful for predicting the wave energy behavior and change patterns.
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Will power be local? The role of local power organizations in energy transition acceleration
A salient problem faced by governments and industry alike is how to accelerate energy transitions to enhance affordability, accessibility, and greenhouse-gas reduction. Bringing together acceleration processes and spatial scale dynamics, this study highlights the potential for electricity distribution to play a keystone role in the energy transition. We present and examine survey data of electricity distribution utilities in a region of the U.S. to show how trends in decentralization and digitization are intertwined with decarbonization. These trends rebalance economic value toward distribution networks and away from centralized infrastructure. The survey data show that electricity distribution organizations are deploying local, renewable generation projects that produce electricity for one-third (1/3) less than the cost from a centralized generation-and-transmission entity. We suggest that this change and others are likely to transform distribution operators into more broad-based local power organizations. Although the cost advantage of distributed generation seemingly marks a future of local control and decentralized organizational forms, spatial scale dynamics indicate countervailing centralization trends, including that distribution networks may evolve to dependency on external digital, engineering, and capital providers. The outcome of the resulting conflicts will affect the potential for transition acceleration to be enabled or reduced.
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- Award ID(s):
- 1743772
- NSF-PAR ID:
- 10488284
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Technological Forecasting and Social Change
- Volume:
- 183
- Issue:
- C
- ISSN:
- 0040-1625
- Page Range / eLocation ID:
- 121884
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1016/j.techfore.2022.121884
