GIS-based Energy Consumption Mapping

Estimating energy savings for the residential building stock at urban scale

Chrysi Balta

MSc Geographical Information Science

Climate change is a growing issue globally, with housing energy consumption at city level being a major contributor of CO₂ emissions. According to the European Institute for Energy Research, European cities consume 70% of the overall primary energy consumption of the continent, expected to reach 75% by 2030. Reduction of CO2 emissions is a priority in the EU. The Energy Performance Buildings Directive (EPBD) requires from each member the establishment of a long term strategy for investment in “green” interventions and improvements to the existing building stock.

Project Aim

This thesis is focusing on the problem of energy consumption of the dwelling stock in the urban environment, using GIS to map energy consumption and calculate energy and CO₂ emissions savings after certain retrofitting measures. The overall aim of the project is to explore energy consumption patterns at urban scale and provide a methodology for evaluating retrofitting scenarios and support decision making in the context of location-based policy implementation to promote effective, sustainable urban planning.

Methods & Data

The methodology is based on a bottom-up, engineering-based approach, with the use of representative building typologies - archetypes (Caputo et al., 2013). An overview of the methodology is shown in Figure 1.

Figure 1 – Methodology approach

This methodology is applied on the study area of Kos town in Greece.

Figure 2 – The study area

Figure 3 – Representative buildings of the study area

The data about the population, the buildings and the climate are collected from:

· the Hellenic Statistical Authority;

· Cadastral Authority and

· Field surveys in the area.

The database is built on ArcGIS, to form an “energy cadastre”. According to the results of stock analysis the representative building typologies in the study area are identified, according to the Hellenic and European standards (TABULA project).

Table 1 – Archetypes of buildings in the study area

Figure 4 – Linking data to the database

The project follows the Hellenic legislative framework and best practice in energy auditing. Final energy calculations are performed on the TEE-KENAK simulation software – the official software of the Technical Chamber of Greece (TEE) for the assessment of energy performance of buildings.

Scenarios

Three scenarios of retrofitting measures are defined according to current policies and are simulated to calculate the new primary energy and CO2 emissions. The results are extrapolated to the whole building stock, incorporated in the database and visualised on ESRI ArcMap.

Results & Discussion

Energy Balance

The results show that the current situation of the building stock is highly energy-consuming, because of the age of the stock as well as the bad state of maintenance. As seen in Table 2, archetypes A and B are proved to be the most energy-consuming, due to their age and the change in building materials. Comparing to the northern European housing stock, energy performance is lower as policies to promote energy efficiency have not been implemented.

70% of energy consumption goes for space heating, due to the lack of insulation and double-glazing. Space cooling is accounting for 2.2% to 5.2% of total yearly consumption, as it is needed for only three months a year and is usually provided by relatively new and efficient air-conditioning units.

	Energy Class
	A+
	A
	B+
	B
	C
	D
	E
	F
	G

Figure 5 – Energy classification scale

Figure 6 – Energy classification results

Table 2 – Energy balance results

Scenarios Evaluation

It is observed that the scenario of solar thermal panels for DHW makes the most remarkable difference at individual dwelling level, reducing total electrical energy consumption by 25-50% with a payback time of 2.5 years on average.

However, at city level, the insulation scenario provides the greatest decrease of heating energy demand and consequently of total energy consumption. This has to do with the fact that almost 66% of the housing stock is built before 1980, in the period of no legal obligation for thermal insulation. The effect of the different scenarios to energy and carbon savings and performance classification can be observed in Figure 7.

Overall, the decision for the best scenario is dependent on the final objective. For example, if local administrators want to achieve radical reduction in total primary energy consumption, the preferable choice would be scenario 1. On the other hand, if the objective is to involve the individual owner, then scenario 2 should be promoted.

Figure 7 – Comparative view of the impact of the 3 scenarios

Figure 8 - Clustering of consumption

Clustering of Consumption

Clustering analysis identified areas at excessive risk and great need for policy measures. Global Moran’s I shows that consumption is clustered with a chance of less than 1% that this is a result of randomness.

Local indicators of clustering are used to detect areas with excess consumption. Neighbourhoods are detected, where high consumption clustering is noted. In yellow colour, individual buildings are shown, which can be targeted due their relatively high energy consumption compared to their neighbours.

Conclusions

Key References

The housing sector in Greece is problematic in terms of energy consumption, with little use of the available renewable resources that needs to be improved, due to article 9 of the directive 2010/31/EU. New policies have to be implemented for environmental and social reasons.

This bottom-up, engineering approach for mapping energy consumption with the use of building typologies, adapted to the characteristics of the city, proved to be efficient and in connection to GIS provides a way to compare different retrofitting scenarios, observe the different results in space and detect areas at excess risk. This database can facilitate the Energy Performance Certification, make it faster and cheaper and reduce the costs of real estate transactions

This could be improved with the increasing availability of data about the buildings and consumers’ behaviours. An INSPIRE compliant solution would maximise the pace of changes, as the public becomes more informed and engaged to the project of zero-energy buildings.

This methodology can be adapted to every city and national context, considering its special characteristics and practices. It assists local authorities, which have an important role in the implementation of energy policies and energy planners, local administrators and other stakeholders who can take more effective actions at managing their stock.

Caputo P., Costa G., Ferrari S., 2013. A supporting method for defining energy strategies in the building sector at urban scale. Energy Policy, 55, 261-270.

Dall’O’ G., Galante A., Pasetti G., 2012a. A methodology for evaluating the potential energy savings of retrofitting residential building stocks. Sustainable Cities and Societies, 4, 12-21.

Daskalaki, E. G., Droutsa, K., Gaglia, A., Balaras, C.A., Kontoyiannidis S., 2011. Building typologies as a tool for assessing the energy performance of residential buildings – A case study for the Hellenic building stock. Energy and Buildings, 43, 3400-3409.

Ministry of Environment, Energy and Climate Change (YPEKA), 2012. [Energy efficiency at buildings – The programme guide]. Athens: YPEKA (in Greek).

Theodoridou, I., Papadopoulos, A.M., Hegger, M., 2011. A typological classification of the Greek residential building stock. Energy and Buildings, 43, 2779-2787.

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Chrysi Balta  - MSc GIS
The University of Edinburgh
August 2014
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