Energy production improvement based on dynamic mobile positioning data (ENERPO)

The main idea of the project is to improve the prediction of electricity consumption with the aim to increase the efficiency of electricity use. The prediction will be improved by taking the dynamic electricity consumer data into account This would also lead to increased efficiency of electricity generation (minimize the difference between predicted and actual consumption).

Just as an example, in Estonia the capability to predict electricity consumption is already at a very good level. Average difference between hourly predicted and actual consumption stands are 3% with a median difference of 2.3% (based on Bering AS data January 2014 to March 2015). Currently, prediction is based on many external variables, including weather, day of the week, time, season, etc. At times prediction can immensely differ from actual data – 2.7% of the time the difference is over 10% and differences can be up to 50%. The errors in prediction might lead to losses of several thousands of EUR per day. Similar trends and potential can be expected to be also in other Nordic-Baltic countries. This project aims at increasing the predictability of electricity consumption via analysing the locational information of electricity consumers. For that purpose mobile positioning technique is used.

Such analysis of linking locational mobile data and patterns of energy consumption has not been explored yet. The project will explore such the possibilities of such analysis in Estonia, Finland and Lithuania. The I importance of locational data for meeting the UN Sustainable Development Goals has be stressed recently at the UN Data Forum in January 2017 in Cape Town.
The seed money would be used for developing the main project that will study the usefulness of dynamic population data gathered by analysing big data from mobile network operators – mobile location data traces of domestic subscribers. The main questions to be addressed in a full project will be:

• Consumption of electricity in household is sufficiently related to people staying at home or out of home, to which use of most appliances is tied. The project will aim to solve the question: How much does the I population “staying at home” and “staying away from home” impact electricity consumption at home; is it possible to determine a causal, measurable statistical relation between staying away from home and home j electricity consumption that can be modelled and thus used in predictions? Also, how is electricity consumption affected by later arrival at home, going to events, etc.?
• Leaving home for work means increased electricity consumption at workplace (offices, small businesses, shops). Is there any significant correlation between the two phenomena?  What is the effect of population movement outside home and work – during rush hours 18% of Estonians are in move.
• Is it possible to control electricity generation taking into account the locations of statistically relevant number of population? For example the Song Festival of Estonia means that 6% of people normally all over the country are in the city Tallinn up to late hours. The population placement data has good prove of that
• How to differentiate between households and in terms of electricity distribution?
• Should the prediction be applied in terms of general statistics or through individual profiles? What geographical aggregation is useful when taking into account distribution?
• Should we consider prediction models based on historic data or rather short-term corrections based on real-time mobile data, or both?
• What is the environmental benefit of improved predictions?

The main project outcomes are the practical recommendations for national electricity transmission system operators of three countries (Fl, EE and LT) how to optimise the system with maximum environmental benefit via mobile positioning technologies.

The main focus of the project is towards the household and tertiary sectors electricity consumption. Consumption by other sectors like industry, service, agriculture, etc. is weakly or not at ail correlated in almost all cases with population placement Energy consumption data is available in all three Baltic countries, also in the rest of Baltic Sea Region countries. The opportunities for electricity trade, more exact predictions provide an advantage for both savings and electricity market trading in whole Baltic Sea Region. To widen the same approach to the Baltic and Nordic States, Lithuania and Finland would be involved in the project. By this, the main project could generate manifold bigger result on saving electricity (possibly by millions of EUROS to the benefit of consumers and producers) and creating environmental benefit. When outcomes of the pilot models and studies prove the usefulness of the concept, the approach could be extended to the whole Nordic-Baltic energy region. The transnational value of the project is also related to the interconnectedness of the Nordic and Baltic countries via common energy market thus optimisation of electricity transmission plays an important role in the region.

Total cost: 50 000 EUR (LEI part 12 500 EUR)

Coordinator:

Partners:

• STOCKHOLM ENVIRONMENT INSTITUTE TALLINN CENTRE, Estonia
• LAPPEENRANTA UNIVERSITY OF TECHNOLOGY, Finland
• LITHUANIAN ENERGY INSTITUTE, Lithuania