Enabling local authorities to produce short-term energy plans

Abstract

Purpose – The purpose of this paper is to identify the most appropriate multidisciplinary data sources related with energy optimization decision support as well as the related methodologies, tools and techniques for data capturing and processing for each of them. Design/methodology/approach – A review is conducted on the state-of-play of decision support systems for energy optimization, focussing on the municipal sector, followed by an identification of the most appropriate multidisciplinary data sources related with energy optimization decision support. An innovative methodology is outlined to integrate semantically modeled data from multiple sources, to assist city authorities in energy management. Findings – City authorities need to lead relevant actions toward energy-efficient neighborhoods. Although there are more and more energy and other related data available at the city level, there are no established methods and tools integrating and analyzing them in a smart way, with the purpose to support the decision-making process on energy use optimization. Originality/value – A novel multidimensional approach is proposed, using semantic technologies to integrate data from multiple sources, to assist city authorities to produce short-term energy plans in an integrated, transparent and comprehensive way.

Understanding Smart Cities: A Systematic Review

“…Cities, as the closest management structure for citizens, should play a key role in the implementation of Europe 2020 and its flagship initiatives, as well as addressing climate and energy challenges (Androulaki, Doukas, Marinakis, Madrazo, & Legaki, 2016). Innovation has always been significant and is vital to the competitiveness of smart cities and tourist destinations.…”

An Advanced IoT-based System for Intelligent Energy Management in Buildings

“…It is of common understanding, however, that achieving energy savings in buildings is a difficult and complex process [ 13 , 14 ]. Integrated, transparent and comprehensive approaches are required to provide cities the tools and methods they need to achieve significant reduction of energy consumption and CO 2 emissions through the contribution of advanced ICT tools [ 15 , 16 ]. Indeed, although there is plenty of energy related data available in the cities, the need for methodologies and validated tools to collect, integrate and analyse them, supporting energy use management, is highlighted [ 17 , 18 ].…”

Decision Support for Intelligent Energy Management in Buildings Using the Thermal Comfort Model

“…Thus, a system which effectively captures the "real" sensation of the users and correlates it with the "predicted" one to detect a range of accepted set point temperatures becomes promising and overcomes the limits of the standardized approaches. Such an integrated decision support methodology and respective system is not present in the international scientific literature [20][21][22] . In this context, we introduce the Thermal Comfort Validator (TCV), a Decision Support System (DSS) which exploits both thermal comfort theory and feedback received from the building users in order to calibrate the theoretically optimal set point temperature based on their real sensation.…”