Data Mapper

Introduction

The scenario tool is an online tool that gives a quick, easy and tailor-made access to scenario results on the energy demand development until 2030 of the European shopping centre building stock.

The non-residential building sector is more heterogeneous and complex compared to the residential sector due to variations in usage pattern, energy intensity and construction techniques. Shopping centre buildings equate this complexity. To meet this challenge, the following steps for EU-28 and Norway were carried out:

  • Analysis of the energy demand for energy services in different shop types and shopping centres built in different periods;
  • Calculation of the total final energy demand of the shopping centre building stock;
  • Modelling of the final total energy demand from 2012 to 2030 taking into account new building construction, retrofitting of the existing building stock and last but not least scenario framework conditions including technologic, economic and legal changes between 2012 and 2030;

The scenario part of data mapper was developed as a part of T5.7 Replication potential in EU-27 + Norway”. A comprehensive description of the methodology, input data and scenario framework is available in the CommONEnergy Report “Replication potential in EU-28 + Norway”.

Shopping centre sector is a very dynamic sector. The growth and market saturation is influenced by different parameters such as demographic development and consumer incomes, cultural preferences, difficulties in obtaining government permits, planning policies and dominant presence of other retail formats. We built four different scenarios which reflect these abovementioned parameters and try to identify their impact on the final energy demand development: (1) the first scenario is a status quo scenario including moderate energy efficiency measures for lighting, appliances, refrigeration, ventilation and space heating (2) the second scenario includes policies addressing more ambitious measures and control systems for lighting, appliances, refrigeration, ventilation and space heating (3) the third scenario includes policies addressing higher energy efficiency like in the 2nd scenario and additionally there is a renovation rate obligation for space heating and, (4) the fourth scenario includes an external framework condition taking new shopping centre developments into account considering growing market share of the internet sales. This last scenario is combined with the 1st scenario. Parameters used in all scenarios are summarized in table below.

Table1: Parameters used in four different scenarios

Energy efficiency measures Renovation rate New building development
Scenario 1 (status quo scenario including moderate energy efficiency measures for lighting, appliances, refrigeration, ventilation and space heating) Energy efficiency measures for lighting, appliances, refrigeration, ventilation and space heating are implemented which reduce energy demand by 57%, 49%, 50%, 25%, 26%, respectively Moderate yearly renovation rate (thermal yearly renovation rate reducing space heating and ventilation - 1.8% and for other energy services is as follows: 5.5% for lighting, 5.3% for refrigeration and appliances) Linked to GDP scenario from 2012-2030 (OECD (2016)) and historical sales growth resulting in high growth in the mature markets and limited growth in saturated markets
Scenario 2 (policies addressing higher measures for lighting, appliances, refrigeration, ventilation and space heating and control systems) Energy efficiency measures for lighting, appliances, refrigeration, ventilation and space heating are implemented which reduce energy demand by 59%, 53%, 53%, 45%, 36%, respectively As in the first scenario As in the first scenario
Scenario 3 (policies addressing higher energy efficiency like in 2nd scenario and additionally there is a renovation rate obligation for space heating) As the second scenario Increased yearly renovation rate of thermal renovation reducing space heating – 3.5 % yearly As in the first scenario
Scenario 4 (external framework condition scenario – internet sale scenario combined with status quo scenario) As in the first scenario As in the first scenario Modelled with an annual reduction of the initial sales growth by 1.5% which reduce new building construction rate