Description: The aim of this project was to understand the domestic electricity consumption in the Republic of Cyprus and how it changes through space and time. In doing so, parameters such as temperature, geography and demographic characteristics of the local population are considered. The goal was to develop explorative 2D or 3D geo-visualizations using Kepler and Tableau, to identify patterns and correlations of electricity consumption. The project resulted in a series of interactive visualizations to analyze domestic consumption within different contexts. These have been curated in the data story (see further below) to illustrate certain observations and patterns. The data used in this project comes from Social Electricity, a project that took place in Cyprus between 2011-2016. The data includes electricity consumption figures at postal code level, recorded at bi-monthly intervals by the Electricity Authority of Cyprus. Additional data includes the average temperatures of the five major cities of Cyprus over the same period, number of houses under each postal code, geographical data and average household expenditures in rural and urban areas of the five districts of Cyprus. Since the residential sector in Cyprus consumes 30% of the country’s electricity approximately, the potential for electricity savings is significant. This, however, requires in depth knowledge of how electricity is distributed and consumed across the country. Data visualizations constitute a valuable tool for decision makers in Cyprus to develop effective policies for reducing electricity consumption across different regions of the country.

Collaboration with: Rainer Pits (University of Twente), Electricity Authority of Cyprus

Techniques used: Big data analysis, data visualizations

Started: January, 2020

Status: Finished

Data story:
The following geo-visualizations show the electricity consumption in postcodes at specific dates. The heat map intensity is based on the electricity consumption value and proximity of postcodes. The coastal areas have high electricity consumption in the summer months, especially between August and October, possibly due to tourism. Consistently high consumption can be seen in the northern area of rural Paphos and the flat, inland area roughly between the cities of Nicosia and Larnaca.

Interactive version of the figure is available.

The next visualization below depict the changes over time in the different districts of Cyprus, urban vs. rural. Overall, urban Nicosia has the highest electricity consumption. Through the years, it has roughly 40 kWh higher consumption on average than urban Limassol, which comes second. The lowest consumption is in urban Paphos, with urban Famagusta being second lowest. Consumption fluctuates between the areas each year, but they all follow a similar downward trend from 2011 until 2014, after which consumption increases again. In 2014, there was an economic crisis, so the decreased consumption could be attributed to that. Nicosia and Limassol generally have higher consumption in the urban areas. The difference between urban and rural areas in Nicosia and Limassol tends to be higher between July and September. A suggestion for policy makers is to tackle the electricity consumption spikes that occur in the urban areas of Nicosia and Limassol.

The next visualization correlates electricity consumption patterns with the average temperature. Peaks in electricity consumption generally occur during colder and warmer months, but the correlation is not very strong. The pattern is clearer in January and February when temperatures are at their lowest. This pattern is evident in all of the five major districts. Temperature does play a role in electricity consumption. Heating and cooling costs increase domestic electricity consumption significantly.

The following dual visualization of temperatures and consumption around Cyprus better explains the relation between these two parameters. The dual geo-visualization confirms the patterns described above, but provides greater context for where higher or lower consumption occurs. Looking at the differences between the warmest and coldest months, it appears that consumption is more evenly dispersed in colder months, meaning that more areas of the country are consuming high amounts of electricity. Moving towards spring, the electricity consumption decreases in most areas. When electricity demand increases again in summer, consumption appears more concentrated around the coastal areas, especially from August till October. Then, until winter, consumption across the country becomes relatively low. The mountainous areas are generally a few degrees Celsius colder through the year. This explains the high consumption in the winter months, as households spend more on heating relative to the coastal areas. Conversely, in the summer, temperatures in the mountains are cooler, so households spend less electricity on cooling.

Interactive version of the figure is available.

The next geo-visualization adds housing density data as black dots to the electricity consumption heat map. Here, housing density is defined as the number of houses that fall under each postal code. Some postal codes with low housing density have relatively high electricity consumption, while the opposite occurs as well, for some postal codes with high housing density. The addition of the housing density parameter also provides some context to the high consuming rural areas that were identified earlier, although there is no clear pattern between these regions. The northern part of rural Paphos appears to have multiple postal codes with low housing density and relatively high electricity consumption. In the rural areas between Nicosia and Larnaca, the housing density varies, but generally seems to be higher. Moreover, the coastal areas in the south and east of Cyprus, which have high consumption in the summer, also tend to have high housing densities. If policy makers aim to decrease electricity consumption, these insights suggest that those areas need some extra attention.
Interactive version of the figure is available.

Further insights on the relationship between housing density and electricity consumption appear in the next visualization. The highest electricity consumers appear to be inside postal codes with roughly 50 or less households. This appears to be the case across most areas of Cyprus, with the exceptions of Famagusta, urban Larnaca, and urban Paphos. It is an indication that large houses in sub-urban areas have higher energy needs than apartments and houses inside the urban areas.
Finally, expenditure on utilities was selected as a parameter to investigate economic influences on domestic electricity consumption. Due to the poor quality of the data, drawing correlations was more difficult here. The expenditure is generalized at the postal code level and it shows no changes over time, as the only data available was from 2014. In the next geo-visualization, the range of values for electricity consumption is not fixed (as previously) but it is relative to the rest data values in display. Some postal codes in northern Paphos, rural Larnaka and around the cities of Nicosia and Limassol have consistently the highest monthly electricity consumption. Most of the very high consumers are outside the urban areas, where more money is spent on utilities. It is evident that higher electricity consumption correlates with larger expenditures. However, in rural Paphos and Larnaca, there is a contrast between low expenditure values and high electricity consuming areas, which could be a sign of stronger wealth inequalities in these regions.
Interactive version of the figure is available.

Conclusion: Despite strong potential for solar and wind energy, Cyprus is still heavily reliant on the use of fossil fuels as their primary source of electricity. Besides environmental issues, a study on renewable energy integration in Cyprus found the country’s power grid as highly susceptible to price volatility of fossil fuels, which are largely imported. Besides transitioning towards renewable sources, reducing electricity consumption is necessary for reducing the demand for imported fuel and carbon emissions.
Energy poverty is another problem that deserves concern as it is still prevalent in Europe and has been found to severely impact quality of life. The authorities of Cyprus have defined energy poverty as the condition of consumers who may be in a difficult position because of low income, as evidenced by tax declarations in conjunction with their professional status, marital status and special health conditions, and therefore they are unable to meet the costs of the reasonable need of electricity supply, as these costs represent a significant proportion of their income. A study of energy poverty in Cyprus found that the Government of Cyprus has taken appropriate action in consumer protection and energy poverty-mitigating measures but miss a coordinated approach to specify energy vulnerable groups and tackle the problem on a national level. To effectively respond to the it is crucial to provide the authorities a comprehensive overview of how different parameters may affect the electricity consumption of certain regions, which is a task well suited for data visualizations.
This data story and the visualizations are intended as resources for decision makers in Cyprus when it comes to electricity policy. The analysis indicates some useful observations. In broad terms, understanding the electricity consumption across a country is a difficult and complex task. The parameters explored here make a start at explaining why different areas of the country have certain electricity consumption patterns. Nonetheless, the analysis made here is by no means comprehensive.