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Use of KPIs in an integrated decision support system for energy efficient district retrofitting

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Author: Bektas, K.E. · Luiten, G.T.
Type:article
Date:2014
Source:Sustainable Places 2014, Nice, France, October 1-3, 2014, 1-17
Identifier: 521427
Keywords: Energy · Buildings and Infrastructure · Built Environment · Building Engineering & Civil Engineering · SR - Structural Reliability · TS - Technical Sciences

Abstract

Retrofitting urban districts is a complex process. It deals with multiple stakeholders who have wide range of stakes, priorities, different time horizons and scale of investments. This complexity is boosted by the energy policies, as the retrofitting requires to incorporate both selection and use of different sustainability measures dealing with each stakeholder’s vision, financial capacity, and different performance expectations. Thus, retrofitting at district level displays an interplay between different measures at various scale and details. However, there are three critical observations in the decision making process of district renovation. 1. Decision making in practice is a dynamic, iterative yet complex process. When it attempts to be mediated through computers, there is a probability to end up with a rigid and prescriptive decision model, which does not correspond to the stakeholders’ practices. 2. Decision making in practice includes several Key Performance Indicators (KPIs) at different levels with different data requirements. However, their use is mainly on getting the scores, rather than how KPIs are included and can be instrumented for the stakeholders in making choices. 3. Decision making in practice is supported by several advanced software and tools that run calculation and provide credible input for decision. However, an integrated environment which is based on a clear process model and corresponds the way KPIs are used is missing. Thus, there is a need for an integrated decision support system that corresponds to the users’ iterative decision processes, enable them to make quantified and/or validated choices based on KPIs with connecting existing and advanced calculation modules.