{"id":901,"date":"2020-06-12T11:02:16","date_gmt":"2020-06-12T10:02:16","guid":{"rendered":"https:\/\/www.mub.eps.manchester.ac.uk\/thebeam\/?page_id=901"},"modified":"2020-06-12T11:02:16","modified_gmt":"2020-06-12T10:02:16","slug":"generic-feasibility-assessment","status":"publish","type":"page","link":"https:\/\/www.sites.se.manchester.ac.uk\/thebeam\/generic-feasibility-assessment\/","title":{"rendered":"Generic Feasibility Assessment"},"content":{"rendered":"

Generic Feasibility Assessment<\/h1>\n

There seems a clear need for a methodology for evaluating the claims of \u2018new\u2019 reactor systems at a strategic level, to ensure that the claims of \u2018good\u2019 for the systems are considered alongside the \u2018bad\u2019 and the \u2018ugly\u2019. This should extend to examining which are the energy futures which will extract value from any given system\u2019s characteristics, and which futures will reduce or remove a system\u2019s attributes as drivers for deployment.<\/p>\n

The common method of comparing complex systems is to use Multi-Attribute Decision Analysis (MADA). In this method a group of attributes are defined to cover the main parameters of the systems, and scores are allocated depending on how well or badly a system performs. For example, a fast reactor system might score highly on \u2018uranium usage\u2019, which a once-through LWR regime would score badly. Not all parameters will be deemed to carry the same importance, so the \u2018scores\u2019 which have been compiled are \u2018weighted\u2019 by a set of \u2018weighting values\u2019, and the \u2018weighted scores\u2019 added to provide an overall \u2018consolidated score\u2019 for the particular system.<\/p>\n

In 2012-2013, the National Nuclear Laboratory developed a MADA system to examine nuclear power systems<\/a>, based on 42 metrics derived from those used by the Generation IV International Forum. These were subsequently divided into seven groups (Cost, PRPP, Safety, Strategic, Deployability, Sustainability, Waste<\/a>)\u00a0and used to assess advanced reactor systems<\/a>. The scores from these analyses defined \u2018winners\u2019 and \u2018losers\u2019, but the approach suffered from two main disadvantages:<\/p>\n

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  1. The use of a MADA with a large number of metrics makes the result very difficult to communicate meaningfully, even to committed stakeholders \u2013 there is often a shared understanding by \u2018those that were in the room for the analysis\u2019, which fails to be transferable to others.<\/li>\n
  2. The suitability of a reactor system depends very strongly on \u2018the world in which it must operate\u2019. For example, high scores for uranium economy (e.g. fast reactors) should be highly weighted in a \u2018uranium scarce\u2019 future, but will not feature in a \u2018uranium plentiful and cheap\u2019 future.<\/li>\n<\/ol>\n

    Subsequently, joint working by the Dalton Nuclear Institute, IDM and NNL addressed the weaknesses of the MADA approach to evolve the Generic Feasibility Assessment technique. The key change was the recognition that, in the UK and other states with well-established nuclear programmes, safety, environmental and proliferation\/security attributes are all covered by well-developed regulatory regimes \u2013 so that reactor system deployment is not about \u201chow safe, secure, and environmentally benign\u201d a system is \u2013 but rather how much time and effort must be expended to allow the system to conform with this tried and tested regulatory framework.<\/p>\n

    This leads to five further questions which any system seeking entry into an energy market must answer:<\/p>\n

      \n
    1. How much time and effort will be required to achieve regulatory approvals to deploy this nuclear energy system?<\/li>\n
    2. Is it likely that the nuclear energy system is capable of being economically competitive with the reference (once-through Pressurised Water Reactor) system?<\/li>\n
    3. Is there a credible path between state-led R&D investment now and private sector deployment in the future \u2013 the \u2018Valley of Death?<\/li>\n
    4. If this system was deployed…? (covers fuel supply, waste disposal and reactor\/fuel cycle siting issues)<\/li>\n
    5. Can it meet market demands? (for e.g. flexibility, process heat)<\/li>\n<\/ol>\n

      The system data from the complex NNL analyses are utilised, but are accumulated into a more useable number (typically 12) of attributes, and are assessed by pairwise comparison to a \u2018reference system\u2019. This has initially been assumed to be current Pressurised Water Reactor (PWR) with a once-through cycle, for which many of the parameters are already well known. The comparisons made are based on published data which can be referenced, linked and made publically available. The result is an analysis which relies on easily assimilated graphics and words, rather than complex and opaque marking systems.<\/p>\n

      Generic Feasibility Assessment has been applied to several advanced reactor systems (see Nuclear System Assessment<\/a>).<\/p>\n

      GFA was also used on the assessment of Small and Modular Reactors using Emerging Technologies which was carried out for the Department of Energy and Climate Change by the National Nuclear Laboratory, Integrated Decision Management Ltd and Dalton in 2015\/16 (see Techno-Economic Assessment<\/a>).<\/p>\n

      Read more about the Techno-Economic Assessment<\/a><\/strong><\/p>\n

      Go back to the Nuclear System Assessment overview<\/a><\/strong><\/p>\n

      Resources<\/h1>\n