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Title: Land reuse in support of renewable energy development

Authors:
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1415900
Resource Type:
Journal Article: Publisher's Accepted Manuscript
Journal Name:
Land Use Policy
Additional Journal Information:
Journal Volume: 66; Journal Issue: C; Related Information: CHORUS Timestamp: 2018-01-05 19:59:01; Journal ID: ISSN 0264-8377
Publisher:
Elsevier
Country of Publication:
United Kingdom
Language:
English

Citation Formats

Waite, Jacqueline L. Land reuse in support of renewable energy development. United Kingdom: N. p., 2017. Web. doi:10.1016/j.landusepol.2017.04.030.
Waite, Jacqueline L. Land reuse in support of renewable energy development. United Kingdom. doi:10.1016/j.landusepol.2017.04.030.
Waite, Jacqueline L. 2017. "Land reuse in support of renewable energy development". United Kingdom. doi:10.1016/j.landusepol.2017.04.030.
@article{osti_1415900,
title = {Land reuse in support of renewable energy development},
author = {Waite, Jacqueline L.},
abstractNote = {},
doi = {10.1016/j.landusepol.2017.04.030},
journal = {Land Use Policy},
number = C,
volume = 66,
place = {United Kingdom},
year = 2017,
month = 7
}

Journal Article:
Free Publicly Available Full Text
This content will become publicly available on May 5, 2018
Publisher's Accepted Manuscript

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  • No abstract prepared.
  • Renewable energy sources enjoy growing political support and have plenty of room to grow in the worldwide energy mix. And grow they will, according to most projections. The US Energy Information Administration`s (EIA`s) International Energy Outlook 1997 says consumption of hydroelectricity and other renewables will increase by 56% during 1995--2015. The renewable share of the total energy mix will remain at about current levels, however. The EIA projection includes only renewable fuels used in the generation of electricity. It therefore excludes most biomass energy. Despite the importance of biomass energy, data on consumption of it are sparse. IEA estimates thatmore » in the industrialized world, the biomass share of primary energy consumption amounts to 3.5%. Also excluded from EIA`s projection because of insufficiency of data are dispersed renewables, a category that includes energy consumed at the site of production, such as solar panels used for water heating. This paper discusses regional trends, North American activity, Western Europe, Asian developments, and the rest of the world.« less
  • This article examines the importance of national and sub-national policies in supporting the development of successful global wind turbine manufacturing companies. We explore the motivations behind establishing a local wind power industry, and the paths that different countries have taken to develop indigenous large wind turbine manufacturing industries within their borders. This is done through a cross-country comparison of the policy support mechanisms that have been employed to directly and indirectly promote wind technology manufacturing in twelve countries. We find that in many instances there is a clear relationship between a manufacturer's success in its home country market and itsmore » eventual success in the global wind power market. Whether new wind turbine manufacturing entrants are able to succeed will likely depend in part on the utilization of their turbines in their own domestic market, which in turn will be influenced by the annual size and stability of that market. Consequently, policies that support a sizable, stable market for wind power, in conjunction with policies that specifically provide incentives for wind power technology to be manufactured locally, are most likely to result in the establishment of an internationally competitive wind industry.« less
  • Power extracted from fast moving tidal currents has been identified as a potential commercial-scale source of renewable energy. Device developers and utilities are pursuing deployment of prototype tidal turbines to assess technology viability, site feasibility, and environmental interactions. Deployment of prototype turbines requires permits from a range of regulatory authorities. Ensuring the safety of marine animals, particularly those under protection of the Endangered Species Act of 1973 (ESA) and the Marine Mammal Protection Act of 1972 has emerged as a key regulatory challenge for initial MHK deployments. The greatest perceived risk to marine animals is from strike by the rotatingmore » blades of tidal turbines. Development of the marine mammal alert system (MAAS) was undertaken to support monitoring and mitigation requirements for tidal turbine deployments. The prototype system development focused on Southern Resident killer whales (SRKW), an endangered population of killer whales that frequents Puget Sound and is intermittently present in the part of the sound where deployment of prototype tidal turbines is being considered. Passive acoustics were selected as the primary means because of the vocal nature of these animals. The MAAS passive acoustic system consists of two-stage process involving the use of an energy detector and a spectrogram-based classifier to distinguish between SKRW’s calls and noise. A prototype consisting of two 2D symmetrical star arrays separated by 20 m center to center was built and evaluated in the waters of Sequim Bay using whale call playback.« less
  • Due to the significant environmental impact of power production from fossil fuels and nuclear fission, future energy systems will increasingly rely on distributed and renewable energy sources (RES). The electrical feed-in from photovoltaic (PV) systems and wind energy converters (WEC) varies greatly both over short and long time periods (from minutes to seasons), and (not only) by this effect the supply of electrical power from RES and the demand for electrical power are not per se matching. In addition, with a growing share of generation capacity especially in distribution grids, the top-down paradigm of electricity distribution is gradually replaced bymore » a bottom-up power supply. This altogether leads to new problems regarding the safe and reliable operation of power grids. In order to address these challenges, the notion of Smart Grids has been introduced. The inherent flexibilities, i.e. the set of feasible power schedules, of distributed power units have to be controlled in order to support demand–supply matching as well as stable grid operation. Controllable power units are e.g. combined heat and power plants, power storage systems such as batteries, and flexible power consumers such as heat pumps. By controlling the flexibilities of these units we are particularly able to optimize the local utilization of RES feed-in in a given power grid by integrating both supply and demand management measures with special respect to the electrical infrastructure. In this context, decentralized systems, autonomous agents and the concept of self-organizing systems will become key elements of the ICT based control of power units. In this contribution, we first show how a decentralized load management system for battery charging/discharging of electrical vehicles (EVs) can increase the locally used share of supply from PV systems in a low voltage grid. For a reliable demand side management of large sets of appliances, dynamic clustering of these appliances into uniformly controlled appliance sets is necessary. We introduce a method for self-organized clustering for this purpose and show how control of such clusters can affect load peaks in distribution grids. Subsequently, we give a short overview on how we are going to expand the idea of self-organized clusters of units into creating a virtual control center for dynamic virtual power plants (DVPP) offering products at a power market. For an efficient organization of DVPPs, the flexibilities of units have to be represented in a compact and easy to use manner. We give an introduction how the problem of representing a set of possibly 10{sup 100} feasible schedules can be solved by a machine-learning approach. In summary, this article provides an overall impression how we use agent based control techniques and methods of self-organization to support the further integration of distributed and renewable energy sources into power grids and energy markets. - Highlights: • Distributed load management for electrical vehicles supports local supply from PV. • Appliances can self-organize into so called virtual appliances for load control. • Dynamic VPPs can be controlled by extensively decentralized control centers. • Flexibilities of units can efficiently be represented by support-vector descriptions.« less