Policy mixes for incumbency: the destructive recreation of renewable energy, shale gas 'fracking,' and nuclear power in the United Kingdom

The notion of a ‘policy mix’ can describe interactions across a wide range of innovation policies, including ‘motors for creation’ as well as for ‘destruction’. This paper focuses on the United Kingdom’s (UK) ‘new policy direction’ that has weakened support for renewables and energy efficiency schemes while strengthening promotion of nuclear power and hydraulic fracturing for natural gas (‘fracking’). The paper argues that a ‘policy apparatus for incumbency’ is emerging which strengthens key regimebased technologies while arguably damaging emerging niche innovations. Basing the discussion around the three technology-based cases of renewable energy and efficiency, fracking, and nuclear power, this paper refers to this process as “destructive recreation”. Our study raises questions over the extent to which policymaking in the energy field is not so much driven by stated aims around sustainability transitions, as by other policy drivers. It investigates different ‘strategies of incumbency’ including ‘securitization’, ‘masking’, ‘reinvention’, and ‘capture.’ It suggests that analytical frameworks should extend beyond the particular sectors in focus, with notions of what counts as a relevant ‘policy maker’ correspondingly also expanded, in order to explore a wider range of nodes and critical junctures as entry points for understanding how relations of incumbency are forged and reproduced

Performance Verification Statement for the Chelsea UviLux Hydrocarbon and CDOM Fluorometers

ACT verifications are based on an evaluation of technology performance under specific, agreed- upon protocols, criteria, and quality assurance procedures. ACT and its Partner Institutions do not certify that a technology will always operate as verified and make no expressed or implied guarantee as to the performance of the technology or that a technology will always, or under circumstances other than those used in testing, operate at the levels verified. ACT does not seek to determine regulatory compliance; does not rank technologies nor compare their performance; does not label or list technologies as acceptable or unacceptable; and does not seek to determine “best available technology” in any form. The end user is solely responsible for complying with any and all applicable federal, state, and local requirements. This document has been peer reviewed by ACT Partner Institutions and a technology-specific advisory committee and was recommended for public release. Mention of trade names or commercial products does not constitute endorsement or recommendation by ACT for use.National Oceanographic and Oceanic Administration NOAA Integrated Ocean Observing System IOO

Domestic smart metering infrastructure and a method for home appliances identification using low‐rate power consumption data

The deployment of domestic smart metering infrastructure in Great Britain provides the opportunity for identification of home appliances utilising non-intrusive load monitoring methods. Identifying the energy consumption of certain home appliances generates useful insights for the energy suppliers and for other bodies with a vested interest in energy consumption. Consequently, the domestic smart metering system, which is an integral part of the smart cities' infrastructure, can also be used for home appliance identification purposes taking into account the limitations of the system. In this article, a step-by-step description on accessing data directly from the domestic Smart Meter via an external Consumer Access Device is described, as well as an easy-to-implement method for identifying commonly used home appliances through their power consumption signals sampled at a rate similar to the rate available by the domestic smart metering system. The experimental results indicate that the combination of time domain with frequency domain features extracted either from the 1D/2D Discrete Fourier Transform or the Discrete Cosine Transform provides improved recognition performance compared to the case where the time domain or the frequency domain features are used separately