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dc.contributor.authorNielsen, Brita Fladvad
dc.contributor.authorHauge, Åshild Lappegard
dc.contributor.authorSørnes, Kari
dc.contributor.authorWalnum, Harald Taxt
dc.contributor.authorUusinoka, Taru
dc.date.accessioned2020-11-06T07:06:25Z
dc.date.available2020-11-06T07:06:25Z
dc.date.created2020-11-05T10:55:52Z
dc.date.issued2018
dc.identifier.urihttps://hdl.handle.net/11250/2686644
dc.description.abstractPlanning Instruments for Smart Energy Communities” (PI-SEC) is a Norwegian research project being carried out in the period April 2016 to March 2019. It is funded by the Research Council of Norway and aims to develop effective planning tools for the integration of energy issues at community level. The project will contribute with increased knowledge about parameters that are key to cities focusing on smart and sustainable energy and will provide guidance as to how these cities address issues related to the planning, operation and monitoring of new and existing areas. The project’s research partners are NTNU and SINTEF, in collaboration with the cities of Bergen and Oslo. Standard Norway, FutureBuilt and the Norwegian Green Building Council are reference partners. The districts Ådland and Loddefjord in Bergen, and Furuset in Oslo, are participating in pilot studies as part of the project. The project is divided into two work packages (WPs). WP1 adopts a bottom-up approach from building project development, while WP2 has a top-down approach from municipal planning. There are four tasks assigned to each work package. The aims of this research have been to test the planning tools available to energy smart communities developed in PI-SEC 2016-2017 (Nielsen et al, 2016; Walnum et al., 2017): • How do the selected targets, KPIs and planning instruments perform when implemented into Norwegian neighbourhood development projects? • Can planning instruments be improved based on these results? • What targets, KPIs and planning instruments form the best basis for the development of a common definition and assessment framework for smart energy communities in Norway? The results are based on qualitative group and individual interviews of potential users of the tools, carried out during project meetings and workshops. LEGO and design games were used as a part of workshop data collection approaches. Results and conclusions: • The selected aims, key indicators and planning instruments seem to fit well in the context of the selected pilot studies and shed light on the ways in which cities can work towards achieving emissions reduction targets. The tools receive positive evaluations at superior level. However, it remains a challenge to persuade municipal employees to use the tools. • It is difficult to identify the right employees and end-users for tools that map overall energy use and related emissions. Data collection in connection with the tools is time-consuming, and there is a lack of clarity regarding the responsibility for evaluation of overall emissions, and how this should be applied. Even if the municipalities have a legal responsibility for energy supply, many outsource this by transferring responsibility to private or inter-municipal companies, which are expected to take responsibility for both practice and expertise. This greatly erodes the levels of responsibility and expertise for energy issues within the municipalities themselves. This may mean that the toolbox is inappropriate and unadjusted, that the wrong catchments have been addressed, or that recommendations from Annex 632 regarding each municipality’s key duty to employ personnel with responsibility have been ignored. It is probable that the answer is a mixture of these alternatives. In the future, we have to - Improve the toolbox and focus it on needs - Recommend focused role clarification, and room for energy smart communities as part of municipal Planning If responsibility for community energy planning is defined more clearly within the municipalities, the tools may become more relevant and enable the municipalities more easily to implement them in the future planning of energy-smart communities. • Informants within the municipalities require checklists or tools, provided that these are perceived as relevant. They want tools that encourage interaction in situations where participating stakeholders are empowered to learn from each other and collaborate more efficiently and meaningfully. This is in line with findings in other studies showing that city planners are inclined to reject new time-consuming tasks but welcome the expansion of networks that enable the sharing of specific experiences, combined with innovation. • Work with the PI-SEC planning wheel shows that decision-making processes depend on a good start. It is key to obtain appropriate and engaged stakeholders right from the start. There is still a requirement for focused work to encourage energy companies, property developers, property managers, municipal planners, the national highway authorities and residents to work more strategically in teams. The current planning system is too rigid and divides the stakeholders into process directions that are not conducive to effective, integrated planning. One solution to this lies in the development of alternative approaches to strategic planning (for example, as illustrated by Bergen’s strategic plan programme). There is a striking lack of knowledge of the energy companies’ different roles and opportunities within the municipalities. • A key challenge to the implementation of the PI-SEC Scenario Calculator within the municipalities is the major current lack of focus on stationary energy in municipal planning. Overall emissions reduction targets are not sufficiently detailed to enable measurement of CO2 emissions, or to find out if a given municipality’s targets are met. The Calculator may help to increase awareness and expertise. However, this will require greater commitment to the targets among the various municipal departments. • Even if the largest city municipalities possess the expertise to apply the PI-SEC Scenario Calculator, many smaller municipalities do not, and are heavily reliant on consultants. Energy and other consultants may represent a more appropriate target group for the Calculator than municipal personnel. Informants state that if the aim is to encourage municipal personnel to apply the tool, they want more automation, a link between the tool and GIS, and the automatic input of building data and energy into the model. They do not want to spend time punching data into the tool. • It is difficult to assess the usefulness of the PI-SEC Scenario Calculator without testing by potential users. A municipality employee in one of the test cities stated that after testing the tool against a real project, she perceived its usefulness in a completely new way. Persuading municipal personnel to use the Scenario Calculator has remained a challenge that PI SEC has been focusing on for some time. Unfortunately, the motivation of municipal personnel has not been sufficient to encourage more people to test it. • The PI-SEC Scenario Calculator cannot be used independently of other tools for area planning, because emission reduction targets have to be grouped together with other area quality targets. • There are also barriers linked to taking results from the PI-SEC Scenario Calculator into account. Results often demonstrate that the energy efficiency of privately-owned buildings has a major impact in reducing CO2 emissions. The municipalities seem to lack instruments that can be applied for these types of processes involving private sector landlords. Free energy consultations and creative initiatives for providing financial help and support will be decisive in following up the results generated by the PI-SEC Scenario Calculator.
dc.language.isoengen_US
dc.publisherPI-SEC : SINTEF : NTNUen_US
dc.relation.ispartofseriesPI-SEC;1.3 / 2.3
dc.titleToolkit Testing in the Planning of Smart Energy Communities. PI-SEC Report 1.3 / 2.3 : Municipal practice and project planningen_US
dc.typeResearch reporten_US
dc.description.versionpublishedVersionen_US
dc.subject.nsiVDP::Teknologi: 500en_US
dc.source.pagenumber66en_US
dc.identifier.cristin1845178
cristin.ispublishedtrue
cristin.fulltextoriginal


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